WO2019178217A1 - Methods and compositions for treating, diagnosing, and prognosing cancer - Google Patents

Methods and compositions for treating, diagnosing, and prognosing cancer Download PDF

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Publication number
WO2019178217A1
WO2019178217A1 PCT/US2019/022036 US2019022036W WO2019178217A1 WO 2019178217 A1 WO2019178217 A1 WO 2019178217A1 US 2019022036 W US2019022036 W US 2019022036W WO 2019178217 A1 WO2019178217 A1 WO 2019178217A1
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cancer
patients
cohort
expression
risk
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PCT/US2019/022036
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French (fr)
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Ajay Goel
Raju KANDIMALLA
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Baylor Research Institute
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Publication of WO2019178217A1 publication Critical patent/WO2019178217A1/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P3/00—Drugs for disorders of the metabolism
    • A61P3/04—Anorexiants; Antiobesity agents
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/57419—Specifically defined cancers of colon
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • the present invention relates generally to the fields of molecular biology and oncology. More particularly, it concerns methods and compositions involving biomarkers and cancer prognosis, diagnosis, and treatment.
  • the current disclosure relates to methods and compositions for the treatment of cancers in a patient with a particular biomarker profile. Aspects of the disclosure relate to a method for evaluating a patient comprising measuring the level of expression in a biological sample from the patient of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
  • Further aspects of the disclosure relate to a method comprising measuring in a biological sample from a cancer patient the levels of expression of the following biomarkers FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1 and YTHDF2.
  • Further aspects relate to a method comprising measuring in a biological sample from a cancer patient increased levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 and reduced levels of expression of 2) METTL14, YTHDF1 and/or YTHDF2 as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • FIG. 1 Further aspects relate to a method of treating a patient with cancer comprising administering a chemotherapy and/or radiation to the patient after a biological sample from the patient has been measured for the level of expression of at least one or more of the following listed biomarkers: one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
  • FIG. 1 Further aspects relate to a method of treating a patient with cancer comprising administering an FTO inhibitor to the patient after a biological sample from the patient has been measured to have a level of expression for FTO that is upregulated compared to the level of FTO in either a low-risk patient survival cohort, a non-recurrent cancer cohort, or a cohort of CMS 1 cancer patients.
  • compositions comprising an FTO inhibitor.
  • the composition further comprises an EGFR inhibitor.
  • the composition further comprises an EMT protein inhibitor.
  • kits comprising 1, 2, 3, 4, 5, 6, 7 or more probes or detection agents for detecting a cancer biomarker selected from FTO, METTL3, WTAP, ALKBH5; METTL14, YTHDF1 and/or YTHDF2.
  • the methods of the disclosure include the detection or screening for multiple cancers, such as at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 cancers at the same time.
  • the biomarkers provide a screen that will indicate that a cancer is present.
  • the methods may further comprise an additional screen to determine the type of cancer.
  • the cancer comprises colorectal cancer, gastric cancer, breast cancer, ovarian cancer, pancreatic adenocarcinoma, hepatocellular carcinoma, lung adenocarcinoma, bladder urothelial carcinoma, head and neck squamous cell carcinoma, acute myeloid leukemia, lung squamous cell carcinoma, esophageal adenocarcinoma, or esophageal squamous cell carcinoma.
  • the cancer comprises colorectal cancer.
  • the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer.
  • CMS4 consensus molecular subtype 4
  • the patient has and/or has been determined to have an EGFR mutant cancer.
  • the patient has not been administered an EGFR inhibitor therapy.
  • the patient has been administered an EGFR inhibitor therapy.
  • the patient is currently undergoing an EGFR inhibitor therapy regimen.
  • At least FTO is measured. In some embodiments, FTO expression is upregulated. In some embodiments, at least METTL3 is measured. In some embodiments, METTL3 expression is upregulated. In some embodiments, at least WTAP is measured. In some embodiments, WTAP expression is upregulated. In some embodiments, at least ALKBH5 is measured. In some embodiments, ALKBH5 expression is upregulated. In some embodiments, at least METTL14 is measured. In some embodiments, METTL14 expression is downregulated. In some embodiments, at least YTHDF1 is measured. In some embodiments, YTHDF1 expression is downregulated. In some embodiments, at least YTHDF2 is measured. In some embodiments, YTHDF2 expression is downregulated.
  • the expression level of the biomarkers is upregulated at least, at most, or exactly 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold (or any derivable range therein) from a control.
  • the expression level of the biomarkers is downregulated at least, at most, or exactly 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold (or any derivable range therein) from a control.
  • the expression level of the biomarker is not significantly different than the control level or within 0.5, 1, 1.5, or 2 standard deviations of a control.
  • the levels of expression of at least two listed biomarkers is measured. In some embodiments, the levels of expression of at least three listed biomarkers is measured. In some embodiments, the levels of expression of at least four listed biomarkers is measured. In some embodiments, the levels of expression of at least five listed biomarkers is measured. In some embodiments, the levels of expression of at least six listed biomarkers is measured. In some embodiments, the levels of expression of at least seven listed biomarkers is measured. In some embodiments, the levels of expression of at least 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) biomarkers is measured.
  • At least FTO and METTL3 is measured and/or determined. In some embodiments, at least FTO and WTAP is measured. In some embodiments, at least FTO and ALKBH5 is measured. In some embodiments, at least FTO and METTL14 is measured. In some embodiments, at least FTO and YTHDF1 is measured. In some embodiments, at least FTO and YTHDF2 is measured. In some embodiments, at least METTL3 and WTAP is measured. In some embodiments, at least METTL3 and ALKBH5 is measured. In some embodiments, at least METTL3 and METTL14 is measured. In some embodiments, at least METTL3 and YTHDF1 is measured.
  • At least METTL3 and YTHDF2 is measured. In some embodiments, at least WTAP and ALKBH5 is measured. In some embodiments, at least WTAP and METTL14 is measured. In some embodiments, at least WTAP and YTHDF1 is measured. In some embodiments, at least WTAP and YTHDF2 is measured. In some embodiments, at least ALKBH5 and METTL14 is measured. In some embodiments, at least ALKBH5 and YTHDF1 is measured. In some embodiments, at least ALKBH5 and YTHDF2 is measured. In some embodiments, at least METTL14 and YTHDF1 is measured.
  • At least METTL14 and YTHDF2 is measured. In some embodiments, at least YTHDF1 and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, and WTAP is measured. In some embodiments, at least FTO, METTL3, and ALKBH5 is measured. In some embodiments, at least FTO, METTL3, and METTL14 is measured. In some embodiments, at least FTO, METTL3, and YTHDF1 is measured. In some embodiments, at least FTO, METTL3, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, and ALKBH5 is measured.
  • At least FTO, WTAP, and METTL14 is measured. In some embodiments, at least FTO, WTAP, and YTHDF1 is measured. In some embodiments, at least FTO, WTAP, and YTHDF2 is measured. In some embodiments, at least FTO, ALKBH5, and METTL14 is measured. In some embodiments, at least FTO, ALKBH5, and YTHDF1 is measured. In some embodiments, at least FTO, ALKBH5, and YTHDF2 is measured. In some embodiments, at least FTO, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, METTL14, and YTHDF2 is measured.
  • At least FTO, YTHDF1, and YTHDF2 is measured.
  • at least METTL3, WTAP, and ALKBH5 is measured.
  • at least METTL3, WTAP, and METTL14 is measured.
  • at least METTL3, WTAP, and YTHDF1 is measured.
  • at least METTL3, WTAP, and YTHDF2 is measured.
  • at least METTL3, ALKBH5, and METTL14 is measured.
  • at least METTL3, ALKBH5, and YTHDF1 is measured.
  • at least METTL3, ALKBH5, and YTHDF2 is measured.
  • At least METTL3, METTL14, and YTHDF1 is measured. In some embodiments, at least METTL3, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, and METTL14 is measured. In some embodiments, at least WTAP, ALKBH5, and YTHDF1 is measured. In some embodiments, at least WTAP, ALKBH5, and YTHDF2 is measured. In some embodiments, at least WTAP, METTL14, and YTHDF1 is measured.
  • At least WTAP, METTL14, and YTHDF2 is measured. In some embodiments, at least WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, and METTL14 is measured.
  • At least METTL3, WTAP, ALKBH5, and YTHDF1 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, METTL14, and YTHDF1 is measured. In some embodiments, at least
  • METTL3, WTAP, METTL14, and YTHDF2 is measured.
  • METTL3, WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least
  • WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least
  • WTAP, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured.
  • At least FTO, METTL3, WTAP, ALKBH5, and METTL14 is measured. In some embodiments, at least FTO, METTF3, WTAP, AFKBH5, and YTHDF1 is measured. In some embodiments, at least FTO, METTF3, WTAP, AFKBH5, and YTHDF2 is measured. In some embodiments, at least FTO, METTF3, WTAP, METTF14, and YTHDF1 is measured. In some embodiments, at least FTO, METTF3, WTAP, METTF14, and YTHDF2 is measured.
  • At least FTO, METTL3, WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, METTL14, YTHDF1, and YTHDF2 is measured.
  • At least FTO, WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, METTL14, and YTHDF1 is measured.
  • At least METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF1 is measured.
  • At least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, YTHDF1, and YTHDF2 is measured.
  • At least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured.
  • the expression level of no other biomarker in the biological sample is measured. In some embodiments, at least one of the listed biomarkers is excluded from being measured. In some embodiments, at least two of the listed biomarkers are excluded from being measured.
  • the method comprises or further comprises comparing the level(s) of expression to a control sample(s) or control level(s) of expression.
  • the control sample(s) have expression levels that are representative of normal cells from a cohort of patients, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort patients with CMS4 cancer.
  • control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort
  • the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
  • the method further comprises treating the patient.
  • the treatment excludes one or more of EGFR inhibitors, adjuvant therapy, neo adjuvant therapy, and EMT inhibitors.
  • the treatment comprises an EGFR inhibitor. In some embodiments, the treatment comprises administration of an FTO inhibitor. In some embodiments, the treatment comprises an epithelial to mesenchymal transition (EMT) protein inhibitor. In some embodiments, the EMT protein inhibitor comprises an inhibitor of a protein selected from APP, XPOl, NTRK1, ELAVL1, HuR, and combinations thereof. In some embodiments, the inhibitor is a small molecule, nucleic acid, or protein. In some embodiments, the inhibitor inhibits protein expression. In some embodiments, the inhibitor inhibits protein activity. In some embodiments, the nucleic acid is an siRNA or miRNA.
  • the protein is an FTO-specific, EMT protein- specific, and/or EGFR-specific binding protein or peptide.
  • the FTO-specific and/or EGFR-specific binding protein comprises all or part of an antibody.
  • the EGFR inhibitor comprises a tyrosine kinase inhibitor (TKI).
  • TKI comprises gefitinib, erlotinib, lapatinib, neratinib, osimertinib, vandetanib, dacomitinib, or combinations thereof.
  • the EGFR inhibitor comprises an antibody.
  • the antibody comprises cetuximab, panitumumab, necitumumab, or combinations thereof.
  • 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • a) the levels of expression of 1) FTO, METTF3, WTAP and/or AFKBH5 are upregulated and/or 2) METTF14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non- recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer.
  • the patient identified as high risk is treated with one or more of an EGFR inhibitor, an FTO inhibitor, an EMT protein inhibitor, adjuvant, and neoadjuvant therapy.
  • the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a cancerous sample.
  • the method further comprises treating the patient for cancer after measuring the level of expression of one or more listed biomarkers.
  • expression is measured using one or more hybridization and/or amplification assays.
  • the assay comprises polymerase chain reaction.
  • the level of expression of no additional biomarkers is measured.
  • a cohort comprises at least 50, 100, 200, 300, 400, 500 or more patients (or any derivable range therein).
  • the control sample(s) have expression levels that are representative of normal colorectal cells, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
  • control sample(s) have expression levels that are representative of cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein). In some embodiments, the control sample(s) have expression levels that are representative of cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein).
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
  • the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, a normal mucosal sample, or a colorectal sample.
  • the treatment comprises or further comprises surgery.
  • expression is measured using one or more hybridization and/or amplification assays.
  • the assay comprises polymerase chain reaction.
  • the method comprises or further comprises measuring the level of expression of at least one or more of the following additional listed biomarkers: one or more of the listed biomarkers: METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
  • at least METTL3 is measured.
  • METTL3 expression is upregulated.
  • at least WTAP is measured.
  • WTAP expression is upregulated.
  • at least ALKBH5 is measured.
  • ALKBH5 expression is upregulated.
  • at least METTL14 is measured.
  • METTL14 expression is downregulated.
  • at least YTHDF1 is measured.
  • YTHDF1 expression is downregulated.
  • at least YTHDF2 is measured.
  • YTHDF2 expression is downregulated.
  • the method comprises or further comprises comparing the level(s) of expression of the additional listed biomarkers to a control sample(s) or control level(s) of expression.
  • the treatment comprises chemotherapy, radiation, surgery, adjuvant, and/or neoadjuvant therapy. In some embodiments, the treatment excludes chemotherapy, radiation, adjuvant, and/or neoadjuvant therapy.
  • the biomarker comprises the human gene. In some embodiments, the biomarker comprises a homolog or variant of the human gene.
  • the kit further comprises one or more agents for detecting one or more controls.
  • the kit further comprises reagents for isolating nucleic acids from a biological sample.
  • the reagents are for isolating nucleic acids from a serum sample.
  • the reagents are for isolating nucleic acids from a sample described herein.
  • the term subject or patient may refer to an animal (for example a mammal), including but not limited to humans, non-human primates, rodents, dogs, or pigs.
  • the methods of obtaining provided herein include methods of biopsy such as fine needle aspiration, core needle biopsy, vacuum assisted biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy or skin biopsy.
  • the sample is obtained from a biopsy .
  • the sample may be obtained from any of the tissues provided herein that include but are not limited to gall bladder, skin, heart, lung, breast, pancreas, liver, muscle, kidney, smooth muscle, bladder, intestine, brain, prostate, or thyroid tissue.
  • the sample may include but not be limited to blood, serum, sweat, hair follicle, buccal tissue, tears, menses, urine, feces, or saliva.
  • the sample may be a tissue sample, a whole blood sample, a urine sample, a saliva sample, a serum sample, a plasma sample or a fecal sample.
  • the sample is obtained from cystic fluid or fluid derived from a tumor or neoplasm.
  • any medical professional such as a doctor, nurse or medical technician may obtain a biological sample for testing.
  • the patient or subject may obtain a biological sample for testing without the assistance of a medical professional, such as obtaining a whole blood sample, a urine sample, a fecal sample, a buccal sample, or a saliva sample.
  • a medical professional such as obtaining a whole blood sample, a urine sample, a fecal sample, a buccal sample, or a saliva sample.
  • the sample may be a fresh, frozen or preserved sample or a fine needle aspirate.
  • the sample is a formalin-fixed, paraffin- embedded (FFPE) sample.
  • An acquired sample may be placed in short term or long term storage by placing in a suitable medium, excipient, solution, or container. In certain cases storage may require keeping the sample in a refrigerated, or frozen environment. The sample may be quickly frozen prior to storage in a frozen environment. In certain instances the frozen sample may be contacted with a suitable cryopreservation medium or compound.
  • cryopreservation mediums or compounds include but are not limited to: glycerol, ethylene glycol, sucrose, or glucose.
  • Some embodiments further involve isolating nucleic acids such as ribonucleic or RNA from a biological sample or in a sample of the patient.
  • Other steps may or may not include amplifying a nucleic acid in a sample and/or hybridizing one or more probes to an amplified or non-amplified nucleic acid.
  • the methods may further comprise assaying nucleic acids in a sample.
  • a microarray may be used to measure or assay the level of biomarker expression in a sample.
  • the methods may further comprise recording the biomarker expression level in a tangible medium or reporting the expression level to the patient, a health care payer, a physician, an insurance agent, or an electronic system.
  • a difference between or among weighted coefficients ore expression levels or between or among the weighted comparisons may be, be at least or be at most about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0, 16.5, 17.0, 17.5, 18.0, 18.5, 19.0.
  • determination of calculation of a diagnostic, prognostic, or risk score is performed by applying classification algorithms based on the expression values of biomarkers with differential expression p values of about, between about, or at most about 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.020, 0.021, 0.022, 0.023, 0.024, 0.025, 0.026, 0.027, 0.028, 0.029, 0.03, 0.031, 0.032, 0.033, 0.034, 0.035, 0.036, 0.037, 0.038, 0.039, 0.040, 0.041, 0.042, 0.043, 0.044, 0.045, 0.046, 0.047, 0.048, 0.049, 0.050, 0.051, 0.052, 0.053, 0.054, 0.055, 0.056,
  • the prognosis score is calculated using one or more statistically significantly differentially expressed biomarkers (either individually or as difference pairs).
  • any of the methods described herein may be implemented on tangible computer- readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform one or more operations.
  • a tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to an expression level of a biomarkers in a sample from a patient; and b) determining a difference value in the expression levels using the information corresponding to the expression levels in the sample compared to a control or reference expression level for the gene.
  • tangible computer-readable medium further comprise computer- readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising making recommendations comprising: wherein the patient in the step a) is under or after a first treatment for cancer, administering the same treatment as the first treatment to the patient if the patient does not have increased expression level; administering a different treatment from the first treatment to the patient if the patient has increased expression level.
  • receiving information comprises receiving from a tangible data storage device information corresponding to the expression levels from a tangible storage device.
  • the medium further comprises computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the difference value to a tangible data storage device, calculating a prognosis score for the patient, treating the patient with a traditional therapy if the patient does not have expression levels, and/or or treating the patient with an alternative esophageal therapy if the patient has increased expression levels.
  • the tangible, computer-readable medium further comprise computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising calculating a prognosis score for the patient.
  • the operations may further comprise making recommendations comprising: administering a treatment to a patient that is determined to have a decreased expression level.
  • the terms “or” and“and/or” are utilized to describe multiple components in combination or exclusive of one another.
  • “x, y, and/or z” can refer to“x” alone,“y” alone,“z” alone,“x, y, and z,”“(x and y) or z,”“x or (y and z),” or“x or y or z.” Is is specifically contemplated that x, y, or z may be specifically excluded from an
  • any limitation discussed with respect to one embodiment of the invention may apply to any other embodiment of the invention.
  • any composition of the invention may be used in any method of the invention, and any method of the invention may be used to produce or to utilize any composition of the invention.
  • Aspects of an embodiment set forth in the Examples are also embodiments that may be implemented in the context of embodiments discussed elsewhere in a different Example or elsewhere in the application, such as in the Summary of Invention, Detailed Description of the Embodiments, Claims, and description of Figure Legends.
  • FIG. 1A-H Internal and external validations in CRC, GC, BRCA and OV demonstrated the robust prognostic value of RNAMethyPro.
  • FIG. 2A-D Pan-cancer functional analyses identified conserved biological processes and protein-protein interaction subnetwork dysregulated in RNAMethyPro high-risk patients.
  • A Heatmap of enrichment scores of hallmark gene sets across 13 cancer types. Hierarchical clustering on the enrichment score matrix identified a small cluster consisting of BRCA, AML and PDAC and a major cluster of the other 10 cancer types.
  • B An enrichment map illustrating associations between hallmark gene sets with different degrees of conservation across various cancer types. Node size represents the number of genes in a gene set. Nodes are colored in proportion to the conservation scores of gene sets across 10 cancer types of the major cluster. Edges between gene sets showed their association quantified by Jaccard index.
  • C Heatmaps showing the average log2 fold difference of the indicated genes (rows) in core gene sets for EMT, matrix remodeling and TGF-b pathway between RNAMethyPro high- and low-risk groups across the 13 different cancer types.
  • D conserveed protein-protein interaction (PPI) subnetwork underlying the RNAMethyPro high-risk patients across the 10 cancer types identified using BioNet (FDR ⁇ le-4). Node size is proportionate to the degree of each node in the network.
  • Node color represents the conservation score calculated by the number of times (out of the total 10 cancer types) that the corresponding gene is differentially expressed in the high-risk group compared to the low-risk group (Benjamini-Hochberg adjusted P ⁇ 0.05).
  • Nodes with labels represent EMT signature genes.
  • Hub proteins (NTRK1, XPOl, ELAVL1 and APP) in the network are highlighted with bold labels.
  • Edges represent physical protein-protein interactions between genes obtained from BioGRID database (version 3.4.134).
  • Edges colored in dark black represent interactions between the four hub proteins and EMT signature gene products.
  • FIG. 3A-C RNAMethyPro high-risk group is significantly associated with the mesenchymal subtype of CRC.
  • A Significant associations were found between RNAMethyPro risk groups (high- vs low-risk) and clinical and molecular characteristics in the CIT cohort (* P ⁇ 0.05, ** P ⁇ 0.01 and *** P ⁇ 0.001, Fisher’s exact tests). Heatmap shows expression levels of m6A signature genes in all patient samples ordered by RNAMethyPro risk score.
  • B Bar plot compares RNAMethyPro risk scores of tumors classified to different CMSs in the CIT cohort.
  • CMS4 tumors show significantly higher risk scores than CMS 1, CMS2 and CMS3 (*** P ⁇ 0.0001, one-tailed Student’s t-tests).
  • C Heatmap showing the pair-wise associations between RNAMethyPro risk groups (rows) and CMS subtypes (columns) in the CIT cohort. Colors are proportionate to the -loglO transformed p-values derived from hypergeometric tests.
  • FIG. 4A-E Integrative analysis revealed complex physical and functional interactions between m6A regulators and EMT.
  • A Bar plot compares normalized expression levels of m6A regulators and EMT signature genes, showing significant differences between RNAMethyPro high- and low-risk groups (P ⁇ 0.01 in all comparisons, Wilcoxon rank sum tests).
  • B Protein-protein interactions between m6A regulators (red nodes), hub proteins in the conserved subnetwork (green nodes) and EMT key factors (blue nodes).
  • RNAMethyPro risk groups Dots in the scatter plots are colored by RNAMethyPro risk groups.
  • D-E Bar plots illustrate stromal and immune scores in CRC Meta-validation cohort calculated by ESTIMATE, indicating stronger (D) stromal and (E) immune infiltration in the RNAMethyPro high-risk group (** P ⁇ 0.01,*** P ⁇ 0.001, one-tailed Student’s t-tests).
  • FIG. 5A-G RNAMethyPro is predictive of anti-EGFR therapy response in CRC cell lines and metastatic patients.
  • A Waterfall plot comparing cetuximab sensitivities of 28 MSS cell lines without KRAS, NRAS, BRAF and PIK3CA mutations (48). Bars represent arbitrary indices of cetuximab effects (median-centered) on cell lines as described in (48). Cell lines sensitive to cetuximab are shown with a negative index. Cell lines classified to RNAMethyPro high-, intermediate- and low-risk groups are colored in red, gray and blue, respectively.
  • RNAMethyPro low-risk group Barplot showing that cell lines belonging to the RNAMethyPro low-risk group are significantly more sensitive to cetuximab than those classified to intermediate- and high-risk groups (* P ⁇ 0.05 and *** P ⁇ 0.001, one-tailed Student’s t-tests).
  • C Heatmap showing expression levels of m6A signature genes and KRAS mutations in the Khambata-Ford cohort with 80 patients with metastatic cancer, ordered by RNAMethyPro risk score.
  • (F) Bar plot illustrating the difference in Cetuximab response between RNAMethyPro high- and low-risk groups (P 0.06, Fisher’s exact test, PD versus SD/PR/CR). CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease.
  • (G) Kaplan-Meier graph of patients stratified for RNAMethyPro risk (high-risk group versus low-risk group, P 0.036, log-rank test).
  • FIG. 6A-I Internal validation of the prognostic value of RNAMethyPro in the other 9 cancer types.
  • FIG. 7A-J GSEA plots for EMT in 10 cancer types.
  • FIG. 9 A coexpression network of functional associations between m 6 A regulator genes (red nodes), hub genes in the conserved subnetwork (green nodes) and EMT signature genes (blue nodes). Edge widths are proportionate to Pearson correlation coefficients between gene expression levels of gene pairs that are significantly correlated (P ⁇ 0.05) in the CRC META-validation cohort.
  • Certain aspects of the invention provide a test that could assist physicians to select the optimal therapy for a patient from several alternative treatment options.
  • a major clinical challenge in cancer treatment is to identify the subset of patients who will benefit from a therapeutic regimen, both in metastatic and adjuvant settings.
  • the number of anti-cancer drugs and multi-drug combinations has increased substantially in the past decade, however, treatments continue to be applied empirically using a trial- and-error approach.
  • methods and compositions are provided to diagnose patients to determine the optimal treatment option for cancer patients.
  • the term“substantially the same”,“not significantly different”, or“within the range” refers to a level of expression that is not significantly different than what it is compared to.
  • the term substantially the same refers to a level of expression that is less than 2, 1.5, or 1.25 fold different than the expression level it is compared to or less than 20, 15, 10, or 5% difference in expression.
  • subject or“patient” is meant any single subject for which therapy is desired, including humans, cattle, dogs, guinea pigs, rabbits, chickens, and so on. Also intended to be included as a subject are any subjects involved in clinical research trials not showing any clinical sign of disease, or subjects involved in epidemiological studies, or subjects used as controls.
  • primer or“probe” as used herein, is meant to encompass any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process.
  • primers are oligonucleotides from ten to twenty and/or thirty base pairs in length, but longer sequences can be employed.
  • Primers may be provided in double-stranded and/or single- stranded form, although the single-stranded form is preferred.
  • a probe may also refer to a nucleic acid that is capable of hybridizing by base complementarity to a nucleic acid of a gene of interest or a fragment thereof.
  • “increased expression” or“elevated expression” or“decreased expression” refers to an expression level of a biomarker in the subject’s sample as compared to a reference level representing the same biomarker or a different biomarker.
  • the reference level may be a reference level of expression from a non-cancerous tissue from the same subject.
  • the reference level may be a reference level of expression from a different subject or group of subjects.
  • the reference level of expression may be an expression level obtained from a sample (e.g., a tissue, fluid or cell sample) of a subject or group of subjects without cancer, with colorectal cancer, or an expression level obtained from a non-cancerous tissue of a subject or group of subjects with cancer.
  • the reference level may be a single value or may be a range of values.
  • the reference level of expression can be determined using any method known to those of ordinary skill in the art.
  • the reference level may also be depicted graphically as an area on a graph. In certain embodiments, a reference level is a normalized level.
  • determining or“evaluating” as used herein may refer to measuring, quantitating, or quantifying (either qualitatively or quantitatively).
  • Embodiments of the disclosure relate to administration of inhibitors, such as inhibitory nucleic acids, polypeptides, antibodies, or molecular inhibitors. These are further described below.
  • Certain embodiments of the disclosure relate to administration of FTO inhibitors.
  • the inhibitor may be specific for FTO or the inhibitor may inhibit a class of enzymes that include dioxygenases.
  • FTO relates to FTO alpha-ketoglutarate dependent dioxygenase.
  • the human gene is located at l6ql2.2 (NC_0000l6.l0 (53703963..54114467)). The following are representative mRNA and protein sequences of human FTO.
  • FTO FTO alpha-ketoglutarate dependent dioxygenase
  • transcript variant 3 mRNA
  • NCBI Reference Sequence: NM_00l080432.3 is herein incorporated by reference:
  • alpha-ketoglutarate-dependent dioxygenase FTO isoform 3 [Homo sapiens]; NCBI
  • a FTO inhibitor may refer to any member of the class of compound or agents having an IC50 of 100 mM or lower concentration for a FTO activity, for example, at least or at most or about 200, 100, 80, 50, 40, 20, 10, 5, 1 pM, 100, 10, 1 nM or lower concentration (or any range or value derivable therefrom) or any compound or agent that inhibits the expression of FTO.
  • FTO activity or function may include, but not be limited to, dioxygenase activity, enzymatic activity, and/or substrate binding activity.
  • MTT assay, colony formation assay, invasion assay, apoptosis assay, or cell cycle analysis may be used to test the FTO inhibitors.
  • the FTO inhibitor comprises IOX3.
  • Other exemplary FTO inhibitors have been described in WO2016206573A1, which is herein incorporated by reference.
  • Nucleic acid inhibitors are commercially available.
  • ABM® provides commercially available siRNA FTO inhibitor nucleic acids (Cat. # ⁇ 008315).
  • Inhibitory nucleic acids or any ways of inhibiting gene expression of a gene are known in the art are contemplated in certain embodiments.
  • Examples of an inhibitory nucleic acid include but are not limited to siRNA (small interfering RNA), short hairpin RNA (shRNA), double-stranded RNA, an antisense oligonucleotide, a ribozyme and a nucleic acid encoding thereof.
  • An inhibitory nucleic acid may inhibit the transcription of a gene or prevent the translation of a gene transcript in a cell.
  • An inhibitory nucleic acid may be from 16 to 1000 nucleotides long, and in certain embodiments from 18 to 100 nucleotides long.
  • the nucleic acid may have nucleotides of at least or at most 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 50, 60,
  • isolated means altered or removed from the natural state through human intervention.
  • an siRNA naturally present in a living animal is not “isolated,” but a synthetic siRNA, or an siRNA partially or completely separated from the coexisting materials of its natural state is “isolated.”
  • An isolated siRNA can exist in substantially purified form, or can exist in a non-native environment such as, for example, a cell into which the siRNA has been delivered.
  • Inhibitory nucleic acids are well known in the art.
  • siRNA and double- stranded RNA have been described in U.S. Patents 6,506,559 and 6,573,099, as well as in U.S. Patent Publications 2003/0051263, 2003/0055020, 2004/0265839, 2002/0168707,
  • an inhibitory nucleic acid may be capable of decreasing the expression of UPP2 by at least 10%, 20%, 30%, or 40%, more particularly by at least 50%, 60%, or 70%, and most particularly by at least 75%, 80%, 90%, 95% or more or any range or value in between the foregoing.
  • an inhibitor may be between 17 to 25 nucleotides in length and comprises a 5’ to 3’ sequence that is at least 90% complementary to the 5’ to 3’ sequence of a mature mRNA.
  • an inhibitor molecule is 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides in length, or any range derivable therein.
  • an inhibitor molecule has a sequence (from 5’ to 3’) that is or is at least 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, 99.9 or 100% complementary, or any range derivable therein, to the 5’ to 3’ sequence of a mature mRNA, particularly a mature, naturally occurring mRNA.
  • One of skill in the art could use a portion of the probe sequence that is complementary to the sequence of a mature mRNA as the sequence for an mRNA inhibitor. Moreover, that portion of the probe sequence can be altered so that it is still 90% complementary to the sequence of a mature mRNA.
  • an antibody or a fragment thereof that binds to at least a portion of the protein and inhibits protein activity; its associated use in treatment of diseases is contemplated in embodiments.
  • the anti-FTO antibody is a monoclonal antibody or a polyclonal antibody.
  • the antibody is a chimeric antibody, an affinity matured antibody, a humanized antibody, or a human antibody.
  • the antibody is an antibody fragment.
  • the antibody is a Fab, Fab', Fab'-SH, F(ab')2, or scFv.
  • the antibody is a chimeric antibody, for example, an antibody comprising antigen binding sequences from a non-human donor grafted to a heterologous non-human, human or humanized sequence (e.g., framework and/or constant domain sequences).
  • the non-human donor is a mouse.
  • an antigen binding sequence is synthetic, e.g., obtained by mutagenesis (e.g., phage display screening, etc.).
  • a chimeric antibody has murine V regions and human C region.
  • the murine light chain V region is fused to a human kappa light chain or a human IgGl C region.
  • antibody fragments include, without limitation: (i) the Fab fragment, consisting of VL, VH, CL and CH1 domains; (ii) the "Fd” fragment consisting of the VH and CH1 domains; (iii) the "Fv” fragment consisting of the VL and VH domains of a single antibody; (iv) the "dAb” fragment, which consists of a VH domain; (v) isolated CDR regions; (vi) F(ab')2 fragments, a bivalent fragment comprising two linked Fab fragments; (vii) single chain Fv molecules (“scFv”), wherein a VH domain and a VL domain are linked by a peptide linker which allows the two domains to associate to form a binding domain; (viii) bi-specific single chain Fv dimers (see U.S.
  • a monoclonal antibody is a single species of antibody wherein every antibody molecule recognizes the same epitope because all antibody producing cells are derived from a single B-lymphocyte cell line.
  • Hybridoma technology involves the fusion of a single B lymphocyte from a mouse previously immunized with a UPP2 antigen with an immortal myeloma cell (usually mouse myeloma). This technology provides a method to propagate a single antibody-producing cell for an indefinite number of generations, such that unlimited quantities of structurally identical antibodies having the same antigen or epitope specificity (monoclonal antibodies) may be produced.
  • a goal of hybridoma technology is to reduce the immune reaction in humans that may result from administration of monoclonal antibodies generated by the non-human (e.g. mouse) hybridoma cell line.
  • a hybridoma or other cell producing an antibody may also be subject to genetic mutation or other changes, which may or may not alter the binding specificity of antibodies produced by the hybridoma.
  • polyclonal or monoclonal antibodies, binding fragments and binding domains and CDRs may be created that are specific to a protein of interest, one or more of its respective epitopes, or conjugates of any of the foregoing, whether such antigens or epitopes are isolated from natural sources or are synthetic derivatives or variants of the natural compounds.
  • Antibodies may be produced from any animal source, including birds and mammals. Particularly, the antibodies may be ovine, murine (e.g., mouse and rat), rabbit, goat, guinea pig, camel, horse, or chicken.
  • newer technology permits the development of and screening for human antibodies from human combinatorial antibody libraries.
  • bacteriophage antibody expression technology allows specific antibodies to be produced in the absence of animal immunization, as described in U.S. Pat. No. 6,946,546, which is incorporated herein by this reference. These techniques are further described in: Marks (1992); Stemmer (1994); Gram et al. (1992); Barbas et al. (1994); and Schier et al. (1996).
  • antibodies to a protein described herein will have the ability to neutralize or counteract the effects of the protein regardless of the animal species, monoclonal cell line or other source of the antibody.
  • Certain animal species may be less preferable for generating therapeutic antibodies because they may be more likely to cause allergic response due to activation of the complement system through the "Fc" portion of the antibody.
  • whole antibodies may be enzymatically digested into "Fc" (complement binding) fragment, and into binding fragments having the binding domain or CDR. Removal of the Fc portion reduces the likelihood that the antigen binding fragment will elicit an undesirable immunological response and, thus, antibodies without Fc may be particularly useful for prophylactic or therapeutic treatments.
  • antibodies may also be constructed so as to be chimeric, partially or fully human, so as to reduce or eliminate the adverse immunological consequences resulting from administering to an animal an antibody that has been produced in, or has sequences from, other species.
  • a“small molecule” refers to an organic compound that is either synthesized via conventional organic chemistry methods (e.g., in a laboratory) or found in nature. Typically, a small molecule is characterized in that it contains several carbon-carbon bonds, and has a molecular weight of less than about 1500 grams/mole. In certain embodiments, small molecules are less than about 1000 grams/mole. In certain embodiments, small molecules are less than about 550 grams/mole. In certain embodiments, small molecules are between about 200 and about 550 grams/mole. In certain embodiments, small molecules exclude peptides (e.g., compounds comprising 2 or more amino acids joined by a peptidyl bond). In certain embodiments, small molecules exclude nucleic acids.
  • a small molecule inhibitior may be any small molecules that is determined to inhibit protein function or activity. Such small molecules may be determined based on functional assays in vitro or in vivo.
  • Methods and compositions may be provided for treating, prognosing, and/or diagnosing cancer. Based on a biomarker, different treatments may be prescribed or recommended for different cancer patients. .
  • the patient is diagnosed as having and/or determined to have Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or M0; T4, NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml cancer.
  • the patient is one that has and/or has been determined to have stage I cancer.
  • the patient is one that has and/or has been determined to have stage II cancer. In some embodiments, the patient is one that has and/or has been determined to have stage III cancer. In some embodiments, the patient is one that has and/or has been determined to have stage IV cancer.
  • the control may be the expression level of the biomarker in a sample from a patient that has Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or M0; T4, NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml cancer.
  • the control may be the level of expression of the biomarker from a patient having stage I cancer.
  • the control may be the level of expression of the biomarker from a patient having stage II cancer.
  • the control may be the level of expression of the biomarker from a patient having stage III cancer.
  • the control may be the level of expression of the biomarker from a patient having stage IV cancer.
  • Colorectal cancer also known as colon cancer, rectal cancer, or bowel cancer, is a cancer from uncontrolled cell growth in the colon or rectum (parts of the large intestine), or in the appendix.
  • Certain aspects of the methods are provided for patients that are stage I-IV colorectal cancer patients.
  • the patient is a stage II or III patient.
  • the patient is a stage I or II patient.
  • the patient is a stage I, II, or III patient.
  • the patient is diagnosed as having and/or determined to have Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or
  • T4 NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml.
  • the most common staging system is the TNM (for tumors/nodes/metastases) system, from the American Joint Committee on Cancer (AJCC).
  • the TNM system assigns a number based on three categories.“T” denotes the degree of invasion of the intestinal wall, “N” the degree of lymphatic node involvement, and“M” the degree of metastasis.
  • T denotes the degree of invasion of the intestinal wall
  • N the degree of lymphatic node involvement
  • M the degree of metastasis.
  • the broader stage of a cancer is usually quoted as a number I, II, III, IV derived from the TNM value grouped by prognosis; a higher number indicates a more advanced cancer and likely a worse outcome. Details of this system are in the graph below:
  • Stage II-A T3 NO M0 T3 Tumor invades subserosa or beyond (without other organs involved)
  • Stage II-B T4 NO M0 T4 Tumor invades adjacent organs or perforates the visceral peritoneum
  • Stage III-A T1-2 N1 MO Nl Metastasis to 1 to 3 regional lymph nodes. Tl or T2.
  • Stage III-B T3-4 Nl MO Nl Metastasis to 1 to 3 regional lymph nodes.
  • Stage III-C any T, N2 MO N2: Metastasis to 4 or more regional lymph nodes.
  • Stage IV any T, any N, Ml Distant metastases present. Any T, any N.
  • Methods of the disclosure may include a cancer therapy as described herein. Described herein are additional therapies that may be administered to a patient for use in the methods of the disclosure. It is contemplated that a cancer treatment may exclude any of the cancer treatments described herein. Furthermore, embodiments of the disclosure include patients that have been previously treated for a therapy described herein, are currently being treated for a therapy described herein, or have not been treated for a therapy described herein. In some embodiments, the patient is one that has been determined to be resistant to a therapy described herein. In some embodiments, the patient is one that has been determined to be sensitive to a therapy described herein.
  • the cancer therapy comprises surgical removal of a tumor. This can either be done by an open laparotomy or sometimes laparoscopically.
  • the cancer therapy comprises chemotherapy.
  • the chemotherapy is used in a neoadjuvant setting before surgery to shrink the cancer before attempting to remove it (neoadjuvant therapy).
  • the two most common sites of recurrence of colorectal cancer is in the liver and lungs.
  • the treatment of early colorectal cancer excludes chemotherapy.
  • the treatment of early colorectal cancer includes neoadjuvant therapy (chemotherapy or radiotherapy before the surgical removal of the primary tumor), but excludes adjuvant therapy (chemotherapy and/or radiotherapy after surgical removal of the primary tumor.
  • chemotherapy may be used in addition to surgery in certain cases.
  • chemotherapy may be used in the neoadjuvant setting.
  • the methods include the administration of a chemotherapeutic.
  • the chemotherapeutic comprises antimetabolites or thymidylate synthase inhibitors such as fluorouracil (5-FU).
  • the chemotherapeutic comprises cytotoxic drugs, such as irinotecan or oxaliplatin.
  • the chemotherapeutic comprises combinations such as irinotecan, fluorouracil, and Jeucovorin (FOLFIRI); and oxaliplatin, fluorouracil, and leucovorin (FOLFOX).
  • the cancer therapy comprises an antibody.
  • the cancer therapy comprises Avastin® (bevacizumab) (Genentech Inc., South San Francisco CA) and/or epidermal growth factor receptor Erbitux® (cetuximab) (Imclone Inc. New York City).
  • the cancer therapy may include one or more of the chemical therapeutic agents including thymidylate synthase inhibitors or antimetabolites such as fluorouracil (5-FU), alone or in combination with other therapeutic agents.
  • the first treatment to be tested for response therapy may be antimetabolites or thymidylate synthase inhibitors, prodrugs, or salts thereof. .
  • Antimetabolites can be used in cancer treatment, as they interfere with DNA production and therefore cell division and the growth of tumors. Because cancer cells spend more time dividing than other cells, inhibiting cell division harms tumor cells more than other cells. Anti-metabolites masquerade as a purine (azathioprine, mercaptopurine) or a pyrimidine, chemicals that become the building-blocks of DNA. They prevent these substances becoming incorporated in to DNA during the S phase (of the cell cycle), stopping normal development and division. They also affect RNA synthesis.
  • azathioprine azathioprine, mercaptopurine
  • pyrimidine chemicals that become the building-blocks of DNA. They prevent these substances becoming incorporated in to DNA during the S phase (of the cell cycle), stopping normal development and division. They also affect RNA synthesis.
  • thymidine is used in DNA but not in RNA (where uracil is used instead)
  • inhibition of thymidine synthesis via thymidylate synthase selectively inhibits DNA synthesis over RNA synthesis. Due to their efficiency, these drugs are the most widely used cytostatics. In the ATC system, they are classified under L01B. In some embodiments, this treatment regimen is for advanced cancer. In some embodiments, this treatment regimen is excluded for early cancer.
  • Thymidylate synthase inhibitors are chemical agents which inhibit the enzyme thymidylate synthase and have potential as an anticancer chemotherapy.
  • thymidylate synthetase can be inhibited by the thymidylate synthase inhibitors such as fluorinated pyrimidine fluorouracil, or certain folate analogues, the most notable one being raltitrexed (trade name Tomudex).
  • Five agents were in clinical trials in 2002: raltitrexed, pemetrexed, nolatrexed, ZD9331, and GS7904L. Additional non-limiting examples include: Raltitrexed, used for colorectal cancer since 1998; Fluorouracil, used for colorectal cancer; BGC 945; OST7904L.
  • prodrugs that can be converted to thymidylate synthase inhibitors in the body, such as Capecitabine (INN), an orally- administered chemotherapeutic agent used in the treatment of numerous cancers.
  • Capecitabine is a prodrug, that is enzymatically converted to 5-fluorouracil in the body.
  • this treatment regimen is for advanced cancer.
  • this treatment regimen is excluded for early cancer.
  • Further chemotherapeutic agents that may be used include capecitabine, fluorouracil, irinotecan, leucovorin, oxaliplatin and UFT. Another type of agent that is sometimes used are the epidermal growth factor receptor inhibitors.
  • cancer therapies also include a variety of combination therapies with both chemical and radiation based treatments.
  • Combination chemotherapies include, for example, cisplatin (CDDP), carboplatin, procarbazine, mechlorethamine, cyclophosphamide, camptothecin, ifosfamide, melphalan, chlorambucil, busulfan, nitrosurea, dactinomycin, daunorubicin, doxorubicin, bleomycin, plicomycin, mitomycin, etoposide (VP 16), tamoxifen, raloxifene, estrogen receptor binding agents, taxol, gemcitabien, navelbine, famesyl-protein tansferase inhibitors, transplatinum, 5-fluorouracil, vincristin, vinblastin and methotrex
  • CDDP cisplatin
  • carboplatin carboplatin
  • procarbazine mechlorethamine
  • Surgical options may include non-curative surgical removal of some of the cancer tissue, bypassing part of the intestines, or stent placement. These procedures can be considered to improve symptoms and reduce complications such as bleeding from the tumor, abdominal pain and intestinal obstruction.
  • Non-operative methods of symptomatic treatment include radiation therapy to decrease tumor size as well as pain medications.
  • this treatment regimen is for advanced cancer. In some embodiments, this treatment regimen is excluded for early cancer.
  • Immunotherapeutics generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells.
  • the immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell.
  • the antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing.
  • the antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent.
  • the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target.
  • Various effector cells include cytotoxic T cells and NK cells.
  • Immunotherapies that are designed to boost the body’s natural defenses to fight the cancer may also be used.
  • Immunotherapeutics generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells.
  • the immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell.
  • the antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing.
  • the antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent.
  • the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target.
  • Various effector cells include cytotoxic T cells and NK cells. Immune therapy methods are further described below:
  • Embodiments of the disclosure may include administration of immune checkpoint inhibitors, which are further described below.
  • PD-l can act in the tumor microenvironment where T cells encounter an infection or tumor. Activated T cells upregulate PD-l and continue to express it in the peripheral tissues. Cytokines such as IFN-gamma induce the expression of PDL1 on epithelial cells and tumor cells. PDL2 is expressed on macrophages and dendritic cells. The main role of PD-l is to limit the activity of effector T cells in the periphery and prevent excessive damage to the tissues during an immune response. Inhibitors of the disclosure may block one or more functions of PD-l and/or PDL1 activity.
  • Alternative names for“PD-l” include CD279 and SLEB2.
  • Alternative names for “PDL1” include B7-H1, B7-4, CD274, and B7-H.
  • Alternative names for“PDL2” include B7- DC, Btdc, and CD273.
  • PD-l, PDL1, and PDL2 are human PD-l, PDL1 and PDL2.
  • the PD-l inhibitor is a molecule that inhibits the binding of PD-l to its ligand binding partners.
  • the PD-l ligand binding partners are PDL1 and/or PDL2.
  • a PDL1 inhibitor is a molecule that inhibits the binding of PDL1 to its binding partners.
  • PDL1 binding partners are PD-l and/or B7-1.
  • the PDL2 inhibitor is a molecule that inhibits the binding of PDL2 to its binding partners.
  • a PDL2 binding partner is PD-l.
  • the inhibitor may be an antibody, an antigen binding fragment thereof, an immunoadhesin, a fusion protein, or oligopeptide.
  • Exemplary antibodies are described in U.S. Patent Nos. 8,735,553, 8,354,509, and 8,008,449, all incorporated herein by reference.
  • Other PD-l inhibitors for use in the methods and compositions provided herein are known in the art such as described in U.S. Patent Application Nos. US2014/0294898, US 2014/022021, and US2011/0008369, all incorporated herein by reference.
  • the PD-l inhibitor is an anti-PD-l antibody (e.g., a human antibody, a humanized antibody, or a chimeric antibody).
  • the anti-PD- 1 antibody is selected from the group consisting of nivolumab, pembrolizumab, and pidilizumab.
  • the PD-l inhibitor is an immunoadhesin (e.g., an immunoadhesin comprising an extracellular or PD-l binding portion of PDL1 or PDL2 fused to a constant region (e.g. , an Fc region of an immunoglobulin sequence).
  • the PDL1 inhibitor comprises AMP- 224.
  • Nivolumab also known as MDX- 1106-04, MDX- 1106, ONO-4538, BMS-936558, and OPDIVO ® , is an anti-PD-l antibody described in W 02006/121168.
  • Pembrolizumab also known as MK-3475, Merck 3475, lambrolizumab, KEYTRUDA ® , and SCH-900475, is an anti-PD-l antibody described in W02009/114335.
  • Pidilizumab also known as CT-011, hBAT, or hBAT-l, is an anti-PD-l antibody described in W02009/101611.
  • AMP-224 also known as B7-DCIg, is a PDL2-Fc fusion soluble receptor described in W02010/027827 and WO2011/066342.
  • Additional PD-l inhibitors include MEDI0680, also known as AMP-514, and REGN2810.
  • the immune checkpoint inhibitor is a PDL1 inhibitor such as Durvalumab, also known as MEDI4736, atezolizumab, also known as MPDL3280A, avelumab, also known as MSB00010118C, MDX-1105, BMS-936559, or combinations thereof.
  • the immune checkpoint inhibitor is a PDL2 inhibitor such as rHIgMl2B7.
  • the inhibitor comprises the heavy and light chain CDRs or VRs of nivolumab, pembrolizumab, or pidilizumab. Accordingly, in one embodiment, the inhibitor comprises the CDR1, CDR2, and CDR3 domains of the VH region of nivolumab, pembrolizumab, or pidilizumab, and the CDR1, CDR2 and CDR3 domains of the VL region of nivolumab, pembrolizumab, or pidilizumab.
  • the antibody competes for binding with and/or binds to the same epitope on PD-l, PDL1, or PDL2 as the above- mentioned antibodies.
  • the antibody has at least about 70, 75, 80, 85, 90, 95, 97, or 99% (or any derivable range therein) variable region amino acid sequence identity with the above-mentioned antibodies.
  • CTLA-4 cytotoxic T-lymphocyte-associated protein 4
  • CD 152 cytotoxic T-lymphocyte-associated protein 4
  • the complete cDNA sequence of human CTLA-4 has the Genbank accession number L15006.
  • CTLA-4 is found on the surface of T cells and acts as an“off’ switch when bound to B7-1 (CD80) or B7-2 (CD86) on the surface of antigen-presenting cells.
  • CTLA4 is a member of the immunoglobulin superfamily that is expressed on the surface of Helper T cells and transmits an inhibitory signal to T cells.
  • CTLA4 is similar to the T-cell co-stimulatory protein, CD28, and both molecules bind to B7-1 and B7-2 on antigen-presenting cells.
  • CTLA-4 transmits an inhibitory signal to T cells, whereas CD28 transmits a stimulatory signal.
  • Intracellular CTLA- 4 is also found in regulatory T cells and may be important to their function. T cell activation through the T cell receptor and CD28 leads to increased expression of CTLA-4, an inhibitory receptor for B7 molecules.
  • Inhibitors of the disclosure may block one or more functions of CTLA-4, B7-1, and/or B7-2 activity. In some embodiments, the inhibitor blocks the CTLA-4 and B7-1 interaction. In some embodiments, the inhibitor blocks the CTLA-4 and B7-2 interaction.
  • the immune checkpoint inhibitor is an anti-CTLA-4 antibody (e.g ., a human antibody, a humanized antibody, or a chimeric antibody), an antigen binding fragment thereof, an immunoadhesin, a fusion protein, or oligopeptide.
  • an anti-CTLA-4 antibody e.g ., a human antibody, a humanized antibody, or a chimeric antibody
  • an antigen binding fragment thereof e.g a human antibody, a humanized antibody, or a chimeric antibody
  • an immunoadhesin e.g., a human antibody, a humanized antibody, or a chimeric antibody
  • an antigen binding fragment thereof e.g., an immunoadhesin, a fusion protein, or oligopeptide.
  • Anti-human-CTLA-4 antibodies (or VH and/or VL domains derived therefrom) suitable for use in the present methods can be generated using methods well known in the art.
  • art recognized anti-CTLA-4 antibodies can be used.
  • the anti- CTLA-4 antibodies disclosed in: US 8,119,129, WO 01/14424, WO 98/42752; WO 00/37504 (CP675,206, also known as tremelimumab; formerly ticilimumab), U.S. Patent No. 6,207,156; Hurwitz el al, 1998; can be used in the methods disclosed herein.
  • the teachings of each of the aforementioned publications are hereby incorporated by reference.
  • Antibodies that compete with any of these art-recognized antibodies for binding to CTLA-4 also can be used.
  • a humanized CTLA-4 antibody is described in International Patent Application No. W 02001/014424, W02000/037504, and U.S. Patent No. 8,017,114; all incorporated herein by reference.
  • a further anti-CTLA-4 antibody useful as a checkpoint inhibitor in the methods and compositions of the disclosure is ipilimumab (also known as 10D1, MDX- 010, MDX- 101, and Yervoy®) or antigen binding fragments and variants thereof (see, e.g., WOO 1/14424).
  • the inhibitor comprises the heavy and light chain CDRs or VRs of tremelimumab or ipilimumab. Accordingly, in one embodiment, the inhibitor comprises the CDR1, CDR2, and CDR3 domains of the VH region of tremelimumab or ipilimumab, and the CDR1, CDR2 and CDR3 domains of the VL region of tremelimumab or ipilimumab.
  • the antibody competes for binding with and/or binds to the same epitope on PD-l, B7-1, or B7-2 as the above- mentioned antibodies. In another embodiment, the antibody has at least about 70, 75, 80, 85, 90, 95, 97, or 99% (or any derivable range therein) variable region amino acid sequence identity with the above-mentioned antibodies.
  • the methods comprise administration of a cancer immunotherapy.
  • Cancer immunotherapy (sometimes called immuno-oncology, abbreviated IO) is the use of the immune system to treat cancer.
  • Immunotherapies can be categorized as active, passive or hybrid (active and passive). These approaches exploit the fact that cancer cells often have molecules on their surface that can be detected by the immune system, known as tumour-associated antigens (TAAs); they are often proteins or other macromolecules (e.g. carbohydrates).
  • TAAs tumour-associated antigens
  • Active immunotherapy directs the immune system to attack tumor cells by targeting TAAs.
  • Passive immunotherapies enhance existing anti-tumor responses and include the use of monoclonal antibodies, lymphocytes and cytokines. Immumotherapies are known in the art, and some are described below.
  • the immunotherapy comprises an inhibitor of a co stimulatory molecule.
  • the inhibitor comprises an inhibitor of B7-1 (CD80), B7-2 (CD86), CD28, ICOS, 0X40 (TNFRSF4), 4-1BB (CD137; TNFRSF9), CD40L (CD40LG), GITR (TNFRSF18), and combinations thereof.
  • Inhibitors include inhibitory antibodies, polypeptides, compounds, and nucleic acids.
  • Dendritic cell therapy provokes anti-tumor responses by causing dendritic cells to present tumor antigens to lymphocytes, which activates them, priming them to kill other cells that present the antigen.
  • Dendritic cells are antigen presenting cells (APCs) in the mammalian immune system. In cancer treatment they aid cancer antigen targeting.
  • APCs antigen presenting cells
  • One example of cellular cancer therapy based on dendritic cells is sipuleucel-T.
  • dendritic cells can also be activated in vivo by making tumor cells express GM- CSF. This can be achieved by either genetically engineering tumor cells to produce GM-CSF or by infecting tumor cells with an oncolytic virus that expresses GM-CSF.
  • Another strategy is to remove dendritic cells from the blood of a patient and activate them outside the body.
  • the dendritic cells are activated in the presence of tumor antigens, which may be a single tumor- specific peptide/protein or a tumor cell lysate (a solution of broken down tumor cells). These cells (with optional adjuvants) are infused and provoke an immune response.
  • Dendritic cell therapies include the use of antibodies that bind to receptors on the surface of dendritic cells. Antigens can be added to the antibody and can induce the dendritic cells to mature and provide immunity to the tumor. Dendritic cell receptors such as TLR3, TLR7, TLR8 or CD40 have been used as antibody targets.
  • Chimeric antigen receptors are engineered receptors that combine a new specificity with an immune cell to target cancer cells. Typically, these receptors graft the specificity of a monoclonal antibody onto a T cell. The receptors are called chimeric because they are fused of parts from different sources.
  • CAR-T cell therapy refers to a treatment that uses such transformed cells for cancer therapy.
  • CAR-T cell design involves recombinant receptors that combine antigen-binding and T-cell activating functions.
  • the general premise of CAR-T cells is to artificially generate T-cells targeted to markers found on cancer cells.
  • scientists can remove T-cells from a person, genetically alter them, and put them back into the patient for them to attack the cancer cells.
  • CAR-T cells create a link between an extracellular ligand recognition domain to an intracellular signalling molecule which in turn activates T cells.
  • the extracellular ligand recognition domain is usually a single-chain variable fragment (scFv).
  • scFv single-chain variable fragment
  • Exemplary CAR-T therapies include Tisagenlecleucel (Kymriah) and Axicabtagene ciloleucel (Yescarta).
  • the CAR-T therapy targets CD 19.
  • Cytokine therapy includes Tisagenlecleucel (Kymriah) and Axicabtagene ciloleucel (Yescarta).
  • Cytokines are proteins produced by many types of cells present within a tumor. They can modulate immune responses. The tumor often employs them to allow it to grow and reduce the immune response. These immune-modulating effects allow them to be used as drugs to provoke an immune response. Two commonly used cytokines are interferons and interleukins.
  • Interferons are produced by the immune system. They are usually involved in anti viral response, but also have use for cancer. They fall in three groups: type I (IFNa and IFNP), type II (IFNy) and type III (IFNk).
  • Interleukins have an array of immune system effects.
  • IL-2 is an exemplary interleukin cytokine therapy.
  • Adoptive T cell therapy is a form of passive immunization by the transfusion of T- cells (adoptive cell transfer). They are found in blood and tissue and usually activate when they find foreign pathogens. Specifically they activate when the T-cell's surface receptors encounter cells that display parts of foreign proteins on their surface antigens. These can be either infected cells, or antigen presenting cells (APCs). They are found in normal tissue and in tumor tissue, where they are known as tumor infiltrating lymphocytes (TILs). They are activated by the presence of APCs such as dendritic cells that present tumor antigens. Although these cells can attack the tumor, the environment within the tumor is highly immunosuppressive, preventing immune-mediated tumour death. [60]
  • APCs antigen presenting cells
  • T-cells specific to a tumor antigen can be removed from a tumor sample (TILs) or filtered from blood. Subsequent activation and culturing is performed ex vivo, with the results reinfused. Activation can take place through gene therapy, or by exposing the T cells to tumor antigens.
  • TILs tumor sample
  • Activation can take place through gene therapy, or by exposing the T cells to tumor antigens.
  • the additional therapy comprises an oncolytic virus.
  • An oncolytic virus is a virus that preferentially infects and kills cancer cells. As the infected cancer cells are destroyed by oncolysis, they release new infectious virus particles or virions to help destroy the remaining tumour. Oncolytic viruses are thought not only to cause direct destruction of the tumour cells, but also to stimulate host anti-tumour immune responses for long-term immunotherapy 4. Polysaccharides
  • the additional therapy comprises polysaccharides.
  • Certain compounds found in mushrooms primarily polysaccharides, can up-regulate the immune system and may have anti-cancer properties.
  • beta-glucans such as lentinan have been shown in laboratory studies to stimulate macrophage, NK cells, T cells and immune system cytokines and have been investigated in clinical trials as immunologic adjuvants.
  • the additional therapy comprises neoantigen administration.
  • Many tumors express mutations. These mutations potentially create new targetable antigens (neoantigens) for use in T cell immunotherapy.
  • the presence of CD8+ T cells in cancer lesions, as identified using RNA sequencing data, is higher in tumors with a high mutational burden.
  • the level of transcripts associated with cytolytic activity of natural killer cells and T cells positively correlates with mutational load in many human tumors.
  • the additional therapy comprises a chemotherapy.
  • chemotherapeutic agents include (a) Alkylating Agents, such as nitrogen mustards (e.g., mechlorethamine, cylophosphamide, ifosfamide, melphalan, chlorambucil), ethylenimines and methylmelamines (e.g., hexamethylmelamine, thiotepa), alkyl sulfonates (e.g., busulfan), nitrosoureas (e.g., carmustine, lomustine, chlorozoticin, streptozocin) and triazines (e.g., dicarbazine), (b) Antimetabolites, such as folic acid analogs (e.g., methotrexate), pyrimidine analogs (e.g., 5-fluorouracil, floxuridine, cytarabine, azauridine) and purine analogs and
  • nitrogen mustards e.g.
  • Cisplatin has been widely used to treat cancers such as, for example, metastatic testicular or ovarian carcinoma, advanced bladder cancer, head or neck cancer, cervical cancer, lung cancer or other tumors. Cisplatin is not absorbed orally and must therefore be delivered via other routes such as, for example, intravenous, subcutaneous, intratumoral or intraperitoneal injection. Cisplatin can be used alone or in combination with other agents, with efficacious doses used in clinical applications including about 15 mg/m2 to about 20 mg/m2 for 5 days every three weeks for a total of three courses being contemplated in certain embodiments.
  • the amount of cisplatin delivered to the cell and/or subject in conjunction with the construct comprising an Egr-l promoter operably linked to a polynucleotide encoding the therapeutic polypeptide is less than the amount that would be delivered when using cisplatin alone.
  • chemotherapeutic agents include antimicrotubule agents, e.g., Paclitaxel (“Taxol”) and doxorubicin hydrochloride (“doxorubicin”).
  • Paclitaxel e.g., Paclitaxel
  • doxorubicin hydrochloride doxorubicin hydrochloride
  • Doxorubicin is absorbed poorly and is preferably administered intravenously.
  • appropriate intravenous doses for an adult include about 60 mg/m2 to about 75 mg/m2 at about 2l-day intervals or about 25 mg/m2 to about 30 mg/m2 on each of 2 or 3 successive days repeated at about 3 week to about 4 week intervals or about 20 mg/m2 once a week.
  • the lowest dose should be used in elderly patients, when there is prior bone- marrow depression caused by prior chemotherapy or neoplastic marrow invasion, or when the drug is combined with other myelopoietic suppressant drugs.
  • Nitrogen mustards are another suitable chemotherapeutic agent useful in the methods of the disclosure.
  • a nitrogen mustard may include, but is not limited to, mechlorethamine (HN2), cyclophosphamide and/or ifosfamide, melphalan (L-sarcolysin), and chlorambucil.
  • Cyclophosphamide (CYTOXAN®) is available from Mead Johnson and NEOSTAR® is available from Adria), is another suitable chemotherapeutic agent.
  • Suitable oral doses for adults include, for example, about 1 mg/kg/day to about 5 mg/kg/day
  • intravenous doses include, for example, initially about 40 mg/kg to about 50 mg/kg in divided doses over a period of about 2 days to about 5 days or about 10 mg/kg to about 15 mg/kg about every 7 days to about 10 days or about 3 mg/kg to about 5 mg/kg twice a week or about 1.5 mg/kg/day to about 3 mg/kg/day.
  • the intravenous route is preferred.
  • the drug also sometimes is administered intramuscularly, by infiltration or into body cavities.
  • Additional suitable chemotherapeutic agents include pyrimidine analogs, such as cytarabine (cytosine arabinoside), 5-fluorouracil (fluouracil; 5-FU) and floxuridine (fluorode- oxyuridine; FudR).
  • 5-FU may be administered to a subject in a dosage of anywhere between about 7.5 to about 1000 mg/m2. Further, 5-FU dosing schedules may be for a variety of time periods, for example up to six weeks, or as determined by one of ordinary skill in the art to which this disclosure pertains.
  • Gemcitabine diphosphate (GEMZAR®, Eli Lilly & Co.,“gemcitabine”), another suitable chemotherapeutic agent, is recommended for treatment of advanced and metastatic pancreatic cancer, and will therefore be useful in the present disclosure for these cancers as well.
  • the amount of the chemotherapeutic agent delivered to the patient may be variable.
  • the chemotherapeutic agent may be administered in an amount effective to cause arrest or regression of the cancer in a host, when the chemotherapy is administered with the construct.
  • the chemotherapeutic agent may be administered in an amount that is anywhere between 2 to 10,000 fold less than the chemotherapeutic effective dose of the chemotherapeutic agent.
  • the chemotherapeutic agent may be administered in an amount that is about 20 fold less, about 500 fold less or even about 5000 fold less than the chemotherapeutic effective dose of the chemotherapeutic agent.
  • chemotherapeutic s of the disclosure can be tested in vivo for the desired therapeutic activity in combination with the construct, as well as for determination of effective dosages.
  • suitable animal model systems prior to testing in humans, including, but not limited to, rats, mice, chicken, cows, monkeys, rabbits, etc.
  • In vitro testing may also be used to determine suitable combinations and dosages, as described in the examples.
  • the additional therapy or prior therapy comprises radiation, such as ionizing radiation.
  • ionizing radiation means radiation comprising particles or photons that have sufficient energy or can produce sufficient energy via nuclear interactions to produce ionization (gain or loss of electrons).
  • An exemplary and preferred ionizing radiation is an x-radiation. Means for delivering x-radiation to a target tissue or cell are well known in the art.
  • the amount of ionizing radiation is greater than 20 Gy and is administered in one dose. In some embodiments, the amount of ionizing radiation is 18 Gy and is administered in three doses. In some embodiments, the amount of ionizing radiation is at least, at most, or exactly 2, 4, 6, 8, 10, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 18, 19, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 40 Gy (or any derivable range therein). In some embodiments, the ionizing radiation is administered in at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 does (or any derivable range therein). When more than one dose is administered, the does may be about 1, 4, 8, 12, or 24 hours or 1, 2, 3, 4, 5, 6, 7, or 8 days or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, or 16 weeks apart, or any derivable range therein.
  • the amount of IR may be presented as a total dose of IR, which is then administered in fractionated doses.
  • the total dose is 50 Gy administered in 10 fractionated doses of 5 Gy each.
  • the total dose is 50-90 Gy, administered in 20-60 fractionated doses of 2-3 Gy each.
  • the total dose of IR is at least, at most, or about 20, 21, 22, 23, 24, 25, 26, 27,
  • the total dose is administered in fractionated doses of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 20, 25, 30, 35, 40, 45, or 50 Gy (or any derivable range therein.
  • fractionated doses are administered (or any derivable range therein).
  • at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 (or any derivable range therein) fractionated doses are administered per day.
  • at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 (or any derivable range therein) fractionated doses are administered per week.
  • Curative surgery includes resection in which all or part of cancerous tissue is physically removed, excised, and/or destroyed and may be used in conjunction with other therapies, such as the treatment of the present embodiments, chemotherapy, radiotherapy, hormonal therapy, gene therapy, immunotherapy, and/or alternative therapies.
  • Tumor resection refers to physical removal of at least part of a tumor.
  • treatment by surgery includes laser surgery, cryosurgery, electrosurgery, and microscopically-controlled surgery (Mohs’ surgery).
  • a cavity may be formed in the body.
  • Treatment may be accomplished by perfusion, direct injection, or local application of the area with an additional anti-cancer therapy. Such treatment may be repeated, for example, every 1, 2, 3, 4, 5, 6, or 7 days, or every 1, 2, 3, 4, and 5 weeks or every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months. These treatments may be of varying dosages as well.
  • agents may be used in combination with certain aspects of the present embodiments to improve the therapeutic efficacy of treatment.
  • additional agents include agents that affect the upregulation of cell surface receptors and GAP junctions, cytostatic and differentiation agents, inhibitors of cell adhesion, agents that increase the sensitivity of the hyperproliferative cells to apoptotic inducers, or other biological agents. Increases in intercellular signaling by elevating the number of GAP junctions would increase the anti-hyperproliferative effects on the neighboring hyperproliferative cell population.
  • cytostatic or differentiation agents can be used in combination with certain aspects of the present embodiments to improve the anti-hyperproliferative efficacy of the treatments.
  • Inhibitors of cell adhesion are contemplated to improve the efficacy of the present embodiments.
  • Examples of cell adhesion inhibitors are focal adhesion kinase (FAKs) inhibitors and Lovastatin. It is further contemplated that other agents that increase the sensitivity of a hyperproliferative cell to apoptosis, such as the antibody c225, could be used in combination with certain aspects of the present embodiments to improve the treatment efficacy.
  • the methods of the disclosure may be combined with one or more other colon cancer diagnosis or screening tests at increased frequency if the patient is determined to be at high risk for recurrence or have a poor prognosis based on the biomarker described above.
  • the colon monitoring may include any methods known in the art.
  • the monitoring include obtaining a sample and testing the sample for diagnosis.
  • the colon monitoring may include colonoscopy or coloscopy, which is the endoscopic examination of the large bowel and the distal part of the small bowel with a CCD camera or a fiber optic camera on a flexible tube passed through the anus. It can provide a visual diagnosis (e.g. ulceration, polyps) and grants the opportunity for biopsy or removal of suspected colorectal cancer lesions.
  • colonoscopy or coloscopy can be used for treatment.
  • the monitoring diagnosis may include sigmoidoscopy, which is similar to colonoscopy— the difference being related to which parts of the colon each can examine.
  • a colonoscopy allows an examination of the entire colon (1200-1500 mm in length).
  • a sigmoidoscopy allows an examination of the distal portion (about 600 mm) of the colon, which may be sufficient because benefits to cancer survival of colonoscopy have been limited to the detection of lesions in the distal portion of the colon.
  • a sigmoidoscopy is often used as a screening procedure for a full colonoscopy, often done in conjunction with a fecal occult blood test (FOBT). About 5% of these screened patients are referred to colonoscopy.
  • FOBT fecal occult blood test
  • the monitoring diagnosis may include virtual colonoscopy, which uses 2D and 3D imagery reconstructed from computed tomography (CT) scans or from nuclear magnetic resonance (MR) scans, as a totally non-invasive medical test.
  • CT computed tomography
  • MR nuclear magnetic resonance
  • the monitoring include the use of one or more screening tests for colon cancer including, but not limited to fecal occult blood testing, flexible sigmoidoscopy and colonoscopy. Of the three, only sigmoidoscopy cannot screen the right side of the colon where 42% of malignancies are found. Virtual colonoscopy via a CT scan appears as good as standard colonoscopy for detecting cancers and large adenomas but is expensive, associated with radiation exposure, and cannot remove any detected abnormal growths like standard colonoscopy can.
  • Fecal occult blood testing (FOBT) of the stool is typically recommended every two years and can be either guaiac based or immunochemical.
  • M2-PK test identifies an enzyme in colorectal cancers and polyps rather than blood in the stool. It does not require any special preparation prior to testing. M2-PK is sensitive for colorectal cancer and polyps and is able to detect bleeding and non-bleeding colorectal cancer and polyps. In the event of a positive result people would be asked to undergo further examination e.g. colonoscopy.
  • a receiver operating characteristic (ROC), or ROC curve, is a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate against the false positive rate at various threshold settings.
  • the true-positive rate is also known as sensitivity in biomedical informatics, or recall in machine learning.
  • the false-positive rate is also known as the fall-out and can be calculated as 1 - specificity).
  • the ROC curve is thus the sensitivity as a function of fall-out.
  • the ROC curve can be generated by plotting the cumulative distribution function (area under the probability distribution from -infinity to + infinity) of the detection probability in the y- axis versus the cumulative distribution function of the false-alarm probability in x-axis.
  • ROC analysis provides tools to select possibly optimal models and to discard suboptimal ones independently from (and prior to specifying) the cost context or the class distribution.
  • ROC analysis is related in a direct and natural way to cost/benefit analysis of diagnostic decision making.
  • ROC analysis provides a tool for creating cut-off values to partition patient populations into high expression and low expression of certain biomarkers.
  • ROC is also known as a relative operating characteristic curve, because it is a comparison of two operating characteristics (TPR and FPR) as the criterion changes.
  • ROC analysis curves are known in the art and described in Metz CE (1978) Basic principles of ROC analysis. Seminars in Nuclear Medicine 8:283-298; Youden WJ (1950) An index for rating diagnostic tests. Cancer 3:32-35; Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry 39:561-577; and Greiner M, Pfeiffer D, Smith RD (2000) Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Preventive Veterinary Medicine 45:23-41, which are herein incorporated by reference in their entirety.
  • methods involve obtaining a sample from a subject.
  • the methods of obtaining provided herein may include methods of biopsy such as fine needle aspiration, core needle biopsy, vacuum assisted biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy or skin biopsy.
  • the sample is obtained from a biopsy from esophageal tissue by any of the biopsy methods previously mentioned.
  • the sample may be obtained from any of the tissues provided herein that include but are not limited to non-cancerous or cancerous tissue and non-cancerous or cancerous tissue from the serum, gall bladder, mucosal, skin, heart, lung, breast, pancreas, blood, liver, muscle, kidney, smooth muscle, bladder, colon, intestine, brain, prostate, esophagus, or thyroid tissue.
  • the sample may be obtained from any other source including but not limited to blood, sweat, hair follicle, buccal tissue, tears, menses, feces, or saliva.
  • any medical professional such as a doctor, nurse or medical technician may obtain a biological sample for testing.
  • the biological sample can be obtained without the assistance of a medical professional.
  • a sample may include but is not limited to, tissue, cells, or biological material from cells or derived from cells of a subject.
  • the biological sample may be a heterogeneous or homogeneous population of cells or tissues.
  • the biological sample may be obtained using any method known to the art that can provide a sample suitable for the analytical methods described herein.
  • the sample may be obtained by non-invasive methods including but not limited to: scraping of the skin or cervix, swabbing of the cheek, saliva collection, urine collection, feces collection, collection of menses, tears, or semen.
  • the sample may be obtained by methods known in the art.
  • the samples are obtained by biopsy.
  • the sample is obtained by swabbing, endoscopy, scraping, phlebotomy, or any other methods known in the art.
  • the sample may be obtained, stored, or transported using components of a kit of the present methods.
  • multiple samples such as multiple esophageal samples may be obtained for diagnosis by the methods described herein.
  • multiple samples such as one or more samples from one tissue type (for example esophagus) and one or more samples from another specimen (for example serum) may be obtained for diagnosis by the methods.
  • multiple samples such as one or more samples from one tissue type (e.g.
  • samples from another specimen may be obtained at the same or different times.
  • Samples may be obtained at different times are stored and/or analyzed by different methods. For example, a sample may be obtained and analyzed by routine staining methods or any other cytological analysis methods.
  • the biological sample may be obtained by a physician, nurse, or other medical professional such as a medical technician, endocrinologist, cytologist, phlebotomist, radiologist, or a pulmonologist.
  • the medical professional may indicate the appropriate test or assay to perform on the sample.
  • a molecular profiling business may consult on which assays or tests are most appropriately indicated.
  • the patient or subject may obtain a biological sample for testing without the assistance of a medical professional, such as obtaining a whole blood sample, a urine sample, a fecal sample, a buccal sample, or a saliva sample.
  • the sample is obtained by an invasive procedure including but not limited to: biopsy, needle aspiration, endoscopy, or phlebotomy.
  • the method of needle aspiration may further include fine needle aspiration, core needle biopsy, vacuum assisted biopsy, or large core biopsy.
  • multiple samples may be obtained by the methods herein to ensure a sufficient amount of biological material.
  • the sample is a fine needle aspirate of a esophageal or a suspected esophageal tumor or neoplasm.
  • the fine needle aspirate sampling procedure may be guided by the use of an ultrasound, X-ray, or other imaging device.
  • the molecular profiling business may obtain the biological sample from a subject directly, from a medical professional, from a third party, or from a kit provided by a molecular profiling business or a third party.
  • the biological sample may be obtained by the molecular profiling business after the subject, a medical professional, or a third party acquires and sends the biological sample to the molecular profiling business.
  • the molecular profiling business may provide suitable containers, and excipients for storage and transport of the biological sample to the molecular profiling business.
  • a medical professional need not be involved in the initial diagnosis or sample acquisition.
  • An individual may alternatively obtain a sample through the use of an over the counter (OTC) kit.
  • OTC kit may contain a means for obtaining said sample as described herein, a means for storing said sample for inspection, and instructions for proper use of the kit.
  • molecular profiling services are included in the price for purchase of the kit. In other cases, the molecular profiling services are billed separately.
  • a sample suitable for use by the molecular profiling business may be any material containing tissues, cells, nucleic acids, genes, gene fragments, expression products, gene expression products, or gene expression product fragments of an individual to be tested. Methods for determining sample suitability and/or adequacy are provided.
  • the subject may be referred to a specialist such as an oncologist, surgeon, or endocrinologist.
  • the specialist may likewise obtain a biological sample for testing or refer the individual to a testing center or laboratory for submission of the biological sample.
  • the medical professional may refer the subject to a testing center or laboratory for submission of the biological sample.
  • the subject may provide the sample.
  • a molecular profiling business may obtain the sample.
  • a meta-analysis of expression or activity can be performed.
  • a meta-analysis combines the results of several studies that address a set of related research hypotheses. This is normally done by identification of a common measure of effect size, which is modeled using a form of meta-regression.
  • three types of models can be distinguished in the literature on meta- analysis: simple regression, fixed effects meta regression and random effects meta-regression. Resulting overall averages when controlling for study characteristics can be considered meta-effect sizes, which are more powerful estimates of the true effect size than those derived in a single study under a given single set of assumptions and conditions.
  • a meta-gene expression value in this context, is to be understood as being the median of the normalized expression of a biomarker gene or activity. Normalization of the expression of a biomarker gene is preferably achieved by dividing the expression level of the individual marker gene to be normalized by the respective individual median expression of this marker genes, wherein said median expression is preferably calculated from multiple measurements of the respective gene in a sufficiently large cohort of test individuals.
  • the test cohort preferably comprises at least 3, 10, 100, 200, 1000 individuals or more including all values and ranges thereof. Dataset- specific bias can be removed or minimized allowing multiple datasets to be combined for meta-analyses (See Sims et al. BMC Medical Genomics (1:42), 1-14, 2008, which is incorporated herein by reference in its entirety).
  • the calculation of a meta-gene expression value is performed by: (i) determining the gene expression value of at least two, preferably more genes (ii) "normalizing" the gene expression value of each individual gene by dividing the expression value with a coefficient which is approximately the median expression value of the respective gene in a representative breast cancer cohort (iii) calculating the median of the group of normalized gene expression values.
  • a gene shall be understood to be specifically expressed in a certain cell type if the expression level of the gene in the cell type is at least about 2-fold, 5-fold, lO-fold, lOO-fold, 1000-fold, or 10000-fold higher (or any range derivable therein) than in a reference cell type, or in a mixture of reference cell types.
  • Reference cell types include non-cancerous tissue cells or a heterogenous population of cancers.
  • a suitable threshold level is first determined for a marker gene.
  • the suitable threshold level can be determined from measurements of the marker gene expression in multiple individuals from a test cohort. The median expression of the marker gene in said multiple expression measurements is taken as the suitable threshold value.
  • Comparison of multiple marker genes with a threshold level can be performed as follows: 1. The individual marker genes are compared to their respective threshold levels. 2. The number of marker genes, the expression level of which is above their respective threshold level, is determined. 3. If a marker genes is expressed above its respective threshold level, then the expression level of the marker gene is taken to be "above the threshold level".
  • Some embodiments include determining that a measured expression level is higher than, lower than, increased relative to, decreased relative to, equal to, or within a predetermined amount of a reference expression level.
  • a higher, lower, increased, or decreased expression level is at least 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 50, 100, 150, 200, 250, 500, or 1000 fold (or any derivable range therein) or at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, or 900% different than the reference level, or any derivable range therein.
  • a predetermined threshold level may represent a predetermined threshold level, and some embodiments include determining that the measured expression level is higher by a predetermined amount or lower by a predetermined amount than a reference level.
  • a level of expression may be qualified as“low” or “high,” which indicates the patient expresses a certain gene or miRNA at a level relative to a reference level or a level with a range of reference levels that are determined from multiple samples meeting particular criteria. The level or range of levels in multiple control samples is an example of this.
  • that certain level or a predetermined threshold value is at, below, or above 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
  • a threshold level may be derived from a cohort of individuals meeting a particular criteria.
  • the number in the cohort may be, be at least, or be at most 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 441, 450, 460, 470, 480, 490, 500, 510,
  • a measured expression level can be considered equal to a reference expression level if it is within a certain amount of the reference expression level, and such amount may be an amount that is predetermined. This can be the case, for example, when a classifier is used to identify the molecular subtype of a metastasis.
  • the predetermined amount may be within 0.1, 0.2, 0.3, 0.4,
  • a comparison to mean expression levels in cancerous samples of a cohort of patients would involve: comparing the expression level of gene A in the patient’s cancerous sample with the mean expression level of gene A in cancerous samples of the cohort of patients, comparing the expression level of gene B in the patient’s sample with the mean expression level of gene B in samples of the cohort of patients, and comparing the expression level of miRNA X in the patient’s metastasis with the mean expression level of miRNA X in cancerous samples of the cohort of patients. Comparisons that involve determining whether the expression level measured in a patient’s sample is within a predetermined amount of a mean expression level or reference expression level are similarly done on a gene-by-
  • aspects of the methods include assaying nucleic acids to determine expression levels.
  • Arrays can be used to detect differences between two samples.
  • Specifically contemplated applications include identifying and/or quantifying differences between biomarkers from a sample that is normal and from a sample that is not normal, between a cancerous condition and a non-cancerous condition, or between two differently treated samples.
  • biomarkers may be compared between a sample believed to be susceptible to a particular disease or condition and one believed to be not susceptible or resistant to that disease or condition.
  • a sample that is not normal is one exhibiting phenotypic trait(s) of a disease or condition or one believed to be not normal with respect to that disease or condition.
  • Phenotypic traits include symptoms of, or susceptibility to, a disease or condition of which a component is or may or may not be genetic or caused by a hyperproliferative or neoplastic cell or cells.
  • An array comprises a solid support with nucleic acid probes attached to the support.
  • Arrays typically comprise a plurality of different nucleic acid probes that are coupled to a surface of a substrate in different, known locations.
  • These arrays also described as “microarrays” or colloquially “chips” have been generally described in the art, for example, U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195, 6,040,193, 5,424,186 and Fodor et al., 1991), each of which is incorporated by reference in its entirety for all purposes. Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, e.g., U.S. Pat. No.
  • arrays may be nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate, see U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992, which are hereby incorporated in their entirety for all purposes.
  • a number of difference assays could be employed to analyze biomarkers, their activities, and their effects.
  • assays include, but are not limited to, nucleic amplification, polymerase chain reaction, quantitative PCR, RT-PCR, in situ hybridization, Northern hybridization, hybridization protection assay (HPA)(GenProbe), branched DNA (bDNA) assay (Chiron), rolling circle amplification (RCA), single molecule hybridization detection (US Genomics), Invader assay (ThirdWave Technologies), and/or Bridge Litigation Assay (Genaco).
  • the therapy provided herein may comprise administration of a combination of therapeutic agents, such as a first cancer therapy and a second cancer therapy.
  • the therapies may be administered in any suitable manner known in the art.
  • the first and second cancer treatment may be administered sequentially (at different times) or concurrently (at the same time).
  • the first and second cancer treatments are administered in a separate composition.
  • the first and second cancer treatments are in the same composition.
  • Embodiments of the disclosure relate to compositions and methods comprising therapeutic compositions.
  • the different therapies may be administered in one composition or in more than one composition, such as 2 compositions, 3 compositions, or 4 compositions.
  • Various combinations of the agents may be employed, for example, a first cancer treatment is “A” and a second cancer treatment is“B”:
  • the therapeutic agents of the disclosure may be administered by the same route of administration or by different routes of administration.
  • the cancer therapy is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally.
  • the antibiotic is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally.
  • the appropriate dosage may be determined based on the type of disease to be treated, severity and course of the disease, the clinical condition of the individual, the individual's clinical history and response to the treatment, and the discretion of the attending physician.
  • the treatments may include various“unit doses.”
  • Unit dose is defined as containing a predetermined-quantity of the therapeutic composition.
  • the quantity to be administered, and the particular route and formulation, is within the skill of determination of those in the clinical arts.
  • a unit dose need not be administered as a single injection but may comprise continuous infusion over a set period of time.
  • a unit dose comprises a single administrable dose.
  • the quantity to be administered depends on the treatment effect desired.
  • An effective dose is understood to refer to an amount necessary to achieve a particular effect.
  • doses in the range from 10 mg/kg to 200 mg/kg can affect the protective capability of these agents.
  • doses include doses of about 0.1, 0.5,
  • Such doses can be administered at multiple times during a day, and/or on multiple days, weeks, or months.
  • the effective dose of the pharmaceutical composition is one which can provide a blood level of about 1 mM to 150 mM.
  • the effective dose provides a blood level of about 4 mM to 100 mM.; or about 1 mM to 100 mM; or about 1 mM to 50 mM; or about 1 mM to 40 mM; or about 1 mM to 30 mM; or about 1 mM to 20 mM; or about 1 mM to 10 mM; or about 10 mM to 150 mM; or about 10 mM to 100 mM; or about 10 mM to 50 mM; or about 25 mM to 150 mM; or about 25 mM to 100 mM; or about 25 mM to 50 pM; or about 50 pM to 150 pM; or about 50 pM to 100 pM (or any range derivable therein).
  • the dose can provide the following blood level of the agent
  • the therapeutic agent that is administered to a subject is metabolized in the body to a metabolized therapeutic agent, in which case the blood levels may refer to the amount of that agent.
  • the blood levels discussed herein may refer to the unmetabolized therapeutic agent.
  • Precise amounts of the therapeutic composition also depend on the judgment of the practitioner and are peculiar to each individual. Factors affecting dose include physical and clinical state of the patient, the route of administration, the intended goal of treatment (alleviation of symptoms versus cure) and the potency, stability and toxicity of the particular therapeutic substance or other therapies a subject may be undergoing.
  • dosage units of pg/kg or mg/kg of body weight can be converted and expressed in comparable concentration units of pg/ml or mM (blood levels), such as 4 pM to 100 pM. It is also understood that uptake is species and organ/tissue dependent. The applicable conversion factors and physiological assumptions to be made concerning uptake and concentration measurement are well-known and would permit those of skill in the art to convert one concentration measurement to another and make reasonable comparisons and conclusions regarding the doses, efficacies and results described herein.
  • methods include treating cancer, treating a patient determined to have cancer, prognosing cancer, diagnosing cancer, and controls with a sample from a cancerous tissue.
  • the cancer may be any cancer listed herein.
  • the cancer comprises epithelial cancer, (e.g., breast, gastrointestinal, lung), prostate cancer, bladder cancer, lung (e.g., small cell lung) cancer, colon cancer, ovarian cancer, brain cancer, gastric cancer, renal cell carcinoma, pancreatic cancer, liver cancer, esophageal cancer, head and neck cancer, or a colorectal cancer.
  • the cancer comprises adenocortical carcinoma, agnogenic myeloid metaplasia, AIDS-related cancers (e.g., AIDS-related lymphoma), anal cancer, appendix cancer, astrocytoma (e.g., cerebellar and cerebral), basal cell carcinoma, bile duct cancer (e.g., extrahepatic), bladder cancer, bone cancer, (osteosarcoma and malignant fibrous histiocytoma), brain tumor (e.g., glioma, brain stem glioma, cerebellar or cerebral astrocytoma (e.g., pilocytic astrocytoma, diffuse astrocytoma, anaplastic (malignant) astrocytoma), malignant glioma, ependymoma, oligodenglioma, meningioma, meningiosarcoma, craniopharyngioma, haemangioblast
  • kits containing compositions of the invention or compositions to implement methods of the invention.
  • kits can be used to evaluate one or more biomarker molecules.
  • a kit contains, contains at least or contains at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
  • kits for evaluating biomarker activity in a cell there are kits for evaluating biomarker activity in a cell.
  • Kits may comprise components, which may be individually packaged or placed in a container, such as a tube, bottle, vial, syringe, or other suitable container means.
  • Individual components may also be provided in a kit in concentrated amounts; in some embodiments, a component is provided individually in the same concentration as it would be in a solution with other components. Concentrations of components may be provided as lx, 2x, 5x, lOx, or 20x or more.
  • Kits for using probes, synthetic nucleic acids, nonsynthetic nucleic acids, and/or inhibitors of the disclosure for prognostic or diagnostic applications are included as part of the disclosure. Specifically contemplated are any such molecules corresponding to any biomarker identified herein.
  • control nucleic acids include nucleic acids, probes, and inhibitors.
  • the control molecules can be used to verify transfection efficiency and/or control for transfection-induced changes in cells.
  • kits for analysis of a pathological sample by assessing biomarker profile for a sample comprising, in suitable container means, two or more biomarker probes, wherein the biomarker probes detect one or more of the biomarkers identified herein.
  • the kit can further comprise reagents for labeling nucleic acids in the sample.
  • the kit may also include labeling reagents, including at least one of amine-modified nucleotide, poly(A) polymerase, and poly(A) polymerase buffer.
  • Labeling reagents can include an amine- reactive dye.
  • Example 1- A pan cancer discovery identifies a biologically conserved signature of N 6 -methyladenosine regulators as robust predictors of patient survival in multiple cancers
  • m6A N6-methyladenosine
  • RNA methylation in cancer progression and metastasis; yet its potential clinical significance, if any, remains unclear.
  • the inventors comprehensively and systematically evaluated the role of m6A regulators as potential disease biomarkers, and identified the key biological pathways associated with this epigenetic alteration in multiple human cancers.
  • the inventors analyzed gene expression profiles of 9,712 cancer cell lines and clinical specimens from 25 publicly-available datasets, encompassing 13 human cancers. Based upon the expression levels of seven m6A regulators, the inventors trained a multivariate Cox regression model for each cancer type, followed by evaluation of its prognostic significance. A pan-cancer analysis was undertaken to identify evolutionary conserved biological network(s) across multiple cancer types.
  • RNAMethyPro a 7-gene expression signature of m6A regulators for determining prognosis in 13 human cancers.
  • Pan-cancer analysis identified activated epithelial-mesenchymal transition (EMT), as a highly conserved pathway in high-risk patients predicted by RNAMethyPro in 10 of the 13 cancer types.
  • EMT epithelial-mesenchymal transition
  • a network-based analysis revealed an intimate functional interplay between m6A regulators and EMT-associated factors via druggable targets such as XPOl and NTRK1.
  • RNAMethyPro was further exemplified in colorectal cancer, where high-risk patients demonstrated strong associations with a mesenchymal subtype, activated stromal infiltration, and poor therapeutic response to targeted anti-EGFR therapy.
  • RNAMethyPro is a novel, EMT-associated prognostic gene-expression signature in multiple human cancers, and may offer an important clinical decision-making tool in the future.
  • RNAMethyPro novel m6A regulator-associated gene expression signature, which robustly predicted patient survival in multiple human cancers.
  • the inventors’ analysis revealed that high-risk patients identified by RNAMethyPro were associated with highly conserved biological processes such as the activation of epithelial mesenchymal transition pathway highlighting the clinical significance of this assay to serve as companion diagnostics in improving the clinical outcomes in multiple human cancers.
  • RNAMethyPro a novel and robust gene expression signature based upon m6A regulators, for predicting the prognosis of patients in 13 different human cancer types.
  • RNAMethyPro not only allowed identification of high-risk cancer patients with poor-prognosis, but also led to the recognition that de-regulated expression of m6A-regulators was intimately associated with an EMT phenotype which was highly conserved across 10 cancer types. More specifically, in colorectal cancer patients, RNAMethyPro-led identification of the high-risk group significantly associated with the mesenchymal subtype, demonstrated activation of EMT and TGFP pathway, increased cancer sternness and higher overall stromal and immune content.
  • RNAMethyPro also emerged as a robust predictor of response to anti-EGFR therapy in colorectal patients with metastatic disease.
  • the inventors’ findings provide compelling data for the clinical significance of m6A regulators, and set the stage for future validation and further in-depth mechanistic studies in future.
  • the inventors For colorectal, gastric, breast and ovarian cancers, the inventors analyzed data from two independent patient cohorts for the internal and external validations. To make gene expression levels comparable, z-normalization was performed in each dataset. For each cancer type, a multivariate Cox regression model was trained on the corresponding training set, and the trained model was subsequently used to calculate risk scores for both the training and validation (when available) datasets. Patients were subsequently stratified into low, intermediate and high-risk groups, using the 25th and 75th percentile risk scores derived from the training sets as the cutoff thresholds.
  • RNAMethyPro risk stratification Based on RNAMethyPro risk stratification, differentially expressed genes between low and high-risk groups were identified based on TCGA datasets from 13 cancer types, using ‘LIMMA’ R package.
  • GSEA Gene set enrichment analysis
  • HTSanalyzeR 219
  • the inventors constructed an enrichment map, where nodes encoded gene set size and edges encodes the strength of association quantified by Jaccard similarity coefficient (or Jaccard index).
  • Jaccard similarity coefficient or Jaccard index
  • RNAMethyPro high-risk groups conserved across the 10 cancer types (OV, HCC, LUSC, LUAD, HNSC, GC, ESCC, EAC, CRC and BLCA).
  • the inventors employed BioNet - a model-based network approach previously published (31). Specifically, the inventors aggregated p-values derived from differential gene expression analysis using‘LIMMA’ R package between RNAMethyPro high- and low-risk groups in the 10 cancer types by lOth order statistic.
  • RSEM scaled estimates of gene expression levels were first converted to transcripts per million (TPM) by multiplication with 1 million, followed by log2-transformation.
  • TPM transcripts per million
  • the TCGA-OV dataset consisted of processed gene expression profiles based on Affymetrix HG133A microarrays.
  • TCGA-PAAD dataset the inventors kept 76 specimens of high purity for further analysis.
  • TCGA-BRCA dataset the inventors analyzed 517 specimens with complete clinical information.
  • GSE39582, GSE14333, GSE17536, GSE26906, GSE33113, GSE37892, GSE39084, GSE5851, GSE62254 were all based on Affymetrix Human Genome U133 Plus 2.0 Arrays, and the probe set IDs were converted to official gene symbols according to the annotation ‘GPL570’ in GEO.
  • GSE59857 dataset was measured on Illumina HumanHT-l2 V4.0 expression beadchip platform and annotated by‘GPL10558’ in GEO. All datasets from GEO database were downloaded directly in their processed form. For 7 GEO datasets used as the CRC meta-validation set, the inventors further removed the non-biological batch effects using ‘combat’ function in R‘sva’ package.
  • METABRIC (23) gene expression discovery and validation datasets were obtained for breast cancer analysis.
  • AML acute myeloid leukemia
  • RNA-seq data was downloaded from TARGET (24) database, and was first converted from FPKM to TPM followed by log2-transformation.
  • the inventors systematically evaluated the prognostic significance of m6A regulatory machinery, focusing on a panel of 3 m6A‘writers’ (METTL3, METTL14 and WTAP), 2 ‘erasers’ (FTO and ALKBH5) and 2 ‘readers’ (YTHDF1 and YTHDF2).
  • the inventors performed comprehensive bioinformatic analysis of 25 public gene expression datasets comprising a total of more than 9000 patients, across 13 cancer types (Table S l, Supplementary Material and Methods).
  • RNAMethyPro derived formula
  • OS overall survival
  • RFS relapse-free survival
  • RNAMethyPro For four cancer types (colorectal, gastric, breast and ovarian), where additional independent patient cohorts were available, the inventors next sought to externally validate the prognostic potential of RNAMethyPro.
  • DFS disease-free survival
  • RNAMethyPro To gain insights into the mechanistic underpinnings of high-risk patients identified by RNAMethyPro, the inventors systematically interrogated various key biological processes dysregulated across the 13 cancer types. More specifically, for each cancer type, the inventors analyzed the corresponding gene expression datasets (Table S l) for gene set enrichment analysis (GSEA) on 50 hallmark gene sets obtained from MSigDB using HTSanalyzeR (29). Unsupervised hierarchical clustering on the obtained matrix of gene set enrichment scores identified two distinct clusters of cancers - a smaller cluster comprising of breast (BRCA), pancreatic (PD AC) and acute myeloid leukemia (AML), and a larger cluster of 10 other cancer types.
  • GSEA gene set enrichment analysis
  • the larger cluster was primarily enriched for GI cancers typified by specific biological processes related to epithelial-mesenchymal transition, angiogenesis and cancer sternness (FIG. 2A).
  • activation of MYC and pancreatic beta cells emerged as major drivers of disease pathogenesis in PDAC (35-37).
  • Breast cancer patients with poor prognosis were characterized by a basal subtype- specific features, such as MYC and E2F activation (32), whereas high-risk AML subgroup associated with heme metabolism and interferon- alpha response, in line with previous reports (33,34).
  • RNAMethyPro high-risk groups To further dissect the biological properties associated with RNAMethyPro high-risk groups, the inventors constructed a comprehensive enrichment map and identified a subnetwork of highly conserved biological processes associated with cancer progression and metastasis (FIG. 2B). Central to this functional network of pathways was EMT, which was significantly upregulated in the RNAMethyPro high-risk group in all the 10 cancer types within the major cluster (FIG. 7). Core signature genes for EMT, matrix remodeling processes, and transforming growth factor-b (TGF-b) were mostly significantly upregulated in RNAMethyPro-identified high-risk patients in all GI cancers (except PDAC) and lung adenocarcinoma (LUAD; FIG. 2C).
  • EMT Central to this functional network of pathways was EMT, which was significantly upregulated in the RNAMethyPro high-risk group in all the 10 cancer types within the major cluster (FIG. 7).
  • lung squamous cell carcinoma which is another major type of non- small-cell lung carcinoma, did not show any significant upregulation of these signature genes in the RNAMethyPro high-risk subgroup (FIG. 2C) - highlighting the specificity of the m6A signature for different cancer types.
  • RNAMethyPro To identify functionally conserved modules underlying the dysregulated biological processes associated with RNAMethyPro high-risk groups, the inventors employed a network- based approach by integrating human interactome and gene expression data. Interestingly, the conserved subnetwork of protein-protein interactions the inventors identified were enriched for a number of EMT signature genes (FIG. 2D). Central to the network were four hub proteins including, APP (38), XPOl (39), NTRK1 (40) and ELAVL1 (or HuR) (41), which have been previously implicated for their regulatory roles in tumorigenesis and/or metastasis. Taken together, the inventors’ findings revealed that upregulation of EMT is a key common mechanism associated with high-risk cancer patients, highlighting potential interactions between m6A regulatory machinery and cancer metastasis.
  • RNAMethyPro is predictive of therapeutic response to anti-EGFR drugs in colorectal cancer
  • RNAMethyPro risk groups By using colorectal cancer as a case study, the inventors next performed integrative analysis to further elucidate the biological and clinical characteristics associated with RNAMethyPro risk groups.
  • CMSs Consensus Molecular Subtypes
  • CMS4 patients had the highest risk scores, while CMS 1 subgroup had the lowest, and CMS2 & CMS3 patients possessed in between risk-scores (FIG. 3B).
  • RNAMethyPro high-risk group showed significant upregulation in gene sets related to the EMT, matrix remodeling, TGFP pathway and cancer stem cell, with concurrent downregulation of the WNT signaling pathway, MYC targets and mesenchymal-epithelial transition (MET; FIG. 8), which were described as the key molecular characteristics of CMS4 colorectal cancers (42). 4. Integrative analysis revealed complex physical and functional crosstalk between m 6 A regulators and EMT in colorectal cancer
  • m6A regulatory machinery must interact with EMT to regulate cancer metastasis in various human malignancies.
  • RNAMethyPro is predictive of therapeutic response to anti-EGFR drugs in colorectal cancer
  • RNAMethyPro risk groups were significantly associated with various CRC subtypes, and accordingly hypothesized that risk scores derived from this signature may also be predictive of therapeutic response to anti-EGFR drugs.
  • the inventors first analyzed a public cohort of 151 CRC cell lines with gene expression and cetuximab sensitivity data (GSE59857) (48).
  • the inventors focused on 28 microsatellite stable cell lines without KRAS, NRAS, HRAS, BRAF and PIK3CA mutations, which have been shown to be significantly associated with refractory cetuximab response (49).
  • FTsing the established scoring formula for CRC the inventors calculated risk scores followed by stratification of all cell lines into low-, intermediate- and high-risk groups.
  • all cell lines could also be successfully classified into cetuximab resistant and sensitive groups. Indeed, the inventors found that the predicted RNAMethyPro risk was significantly associated with cetuximab resistance (FIG.
  • the overall strengths of the inventors’ study include: 1) analysis of data from more than 9,700 cell lines and clinical specimens encompassing 13 cancer types, which represents thus far the most comprehensive analysis in the field to date; 2) the use of a network-based pan-cancer analysis to identify key pathways and protein subnetworks associated with m6A deregulation; 3) integrative analysis of gene expression, molecular and clinicopathological characteristics, as well as drug response data, demonstrating the very first associations between m6A modifications and clinical outcomes in proof-of-principle analysis in colorectal cancer.
  • the inventors’ identification for the promising clinical significance of m6A regulators motivated them to dissect the underlying functional determinants that are potentially shared across multiple cancer types.
  • biological processes such as epithelial-mesenchymal transition (EMT), angiogenesis and cancer sternness were commonly upregulated in RNAMethyPro identified high-risk patients across 10 different cancers.
  • EMT epithelial-mesenchymal transition
  • RNAMethyPro RNAMethyPro identified high-risk patients across 10 different cancers.
  • the inventors’ model- based network approach identified a conserved functional module of protein-protein interactions enriched for EMT signature gene products, and led the inventors to firstly identify four hub proteins, APP, ELAVL1 (HuR), XPOl and NTRK1, whose roles in predicting adjuvant therapy benefit, cancer progression and metastasis have been suggested previously (38-41). More importantly, the inventors’ discovery for the strong functional and physical interactions between these four hub proteins, m6A regulators and EMT signature genes, suggests that the m6A machinery facilitates the EMT process directly or indirectly via these hub proteins, in multiple human cancers.
  • the identification of the hub proteins is clinically relevant, since they are druggable and several inhibitors are already approved by the US FDA (e.g., Entrectinib targeting NTRK1) or are currently being evaluated in clinical trials (e.g., KPT-330 targeting XPOl).
  • EMT drivers such as SMAD2, SMAD3, ZEB 1, TGFB2 and TGFBR2 were all significantly upregulated in RNAMethyPro-identified high-risk tumors, the inventors hypothesized that m6A regulators may functionally interact with EMT induced by activated TGFP pathway in the stromal cells.
  • RNAMethyPro stratified risk groups were not only significantly associated with MSI/MSS, CIMP status, BRAF mutations, but more importantly, also with the recently discovered consensus molecular subtypes (CMSs) in CRC. This is in line with previous biological findings, where FTO was shown to be associated with poor prognosis molecular subtypes of breast cancer and AML.
  • RNAMethyPro a novel gene-expression signature comprising of seven m6A regulators, for robust prediction of prognosis in multiple cancers.
  • the inventors identified activated EMT as a highly conserved biological process across multiple cancer types. Additional investigations in colorectal cancer revealed critical and previously unrecognized associations of RNAMethyPro high-risk group with the mesenchymal subtype and poor anti-EGFR response. Pending future validation and potential mechanistic evaluation of findings reported in this study, RNAMethyPro may offer an important clinical decision-making tool in the near future.
  • Table 1 Log-rank test and univariate analysis of RNAMethyPro risk score in each cohort analyzed for internal or external validation
  • ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell. 2013;49: 18-29.
  • Cancer Genome Atlas Research Network Electronic address: andrew_aguirre@dfci.harvard.edu, Cancer Genome Atlas Research Network. Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma. Cancer Cell. 20l7;32: l85- 203.el3.
  • Marisa L de Reynies A, Duval A, Selves J, Gaub MP, Vescovo L, et al. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

Abstract

The current disclosure relates to methods and compositions for the treatment of cancers in a patient with a particular biomarker profile. Aspects of the disclosure relate to a method for evaluating a patient comprising measuring the level of expression in a biological sample from the patient of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2. Further aspects of the disclosure relate to a method comprising measuring in a biological sample from a cancer patient the levels of expression of the following biomarkers FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1 and YTHDF2.

Description

METHODS AND COMPOSITIONS FOR TREATING, DIAGNOSING, AND
PROGNOSING CANCER
DESCRIPTION
[0001] This application claims the benefit of priority to U.S. Provisional Patent Application Serial No. 62/642,312, filed March 13, 2018, hereby incorporated by reference in its entirety.
BACKGROUND OF THE INVENTION
1. Field of the Invention
[0002] The present invention relates generally to the fields of molecular biology and oncology. More particularly, it concerns methods and compositions involving biomarkers and cancer prognosis, diagnosis, and treatment.
2. Description of Related Art
[0003] It is well-known that early cancer detection saves lives. For example, ninety to 100 percent of people diagnosed at the earliest stage of breast, colon, and skin cancers will survive for at least five years. However, regular screens for every cancer type is expensive and impractical. Cancer can be considered to actually be hundreds or even thousands of different diseases, since one would have to take into account all the different cancer types and the many different genomic alterations that can drive each cancer. There is a need in the art for screening methods that can detect and/or prognose multiple different cancers at the same time. Such methods could lead to the earlier detection of cancer and could also direct health care professionals to more effective and timely administration of therapeutics.
SUMMARY OF THE INVENTION
[0004] The current disclosure relates to methods and compositions for the treatment of cancers in a patient with a particular biomarker profile. Aspects of the disclosure relate to a method for evaluating a patient comprising measuring the level of expression in a biological sample from the patient of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
[0005] Further aspects of the disclosure relate to a method comprising measuring in a biological sample from a cancer patient the levels of expression of the following biomarkers FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1 and YTHDF2. [0006] Further aspects relate to a method comprising measuring in a biological sample from a cancer patient increased levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 and reduced levels of expression of 2) METTL14, YTHDF1 and/or YTHDF2 as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
[0007] Further aspects relate to a method of treating a patient with cancer comprising administering a chemotherapy and/or radiation to the patient after a biological sample from the patient has been measured for the level of expression of at least one or more of the following listed biomarkers: one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
[0008] Further aspects relate to a method of treating a patient with cancer comprising administering an FTO inhibitor to the patient after a biological sample from the patient has been measured to have a level of expression for FTO that is upregulated compared to the level of FTO in either a low-risk patient survival cohort, a non-recurrent cancer cohort, or a cohort of CMS 1 cancer patients.
[0009] Further aspects relate to a method of prognosing a patient with cancer and/or evaluating treatment for the patient comprising: a) measuring the level of expression of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5; METTL14, YTHDF1 and/or YTHDF2 in a blood sample from the patient; b) comparing the level(s) of expression to a control sample(s) or control level(s) of expression; and, c) prognosing the patient and/or evaluating treatment for the patient based on the levels of measured expression.
[0010] Further aspects relate to a pharmaceutical composition comprising an FTO inhibitor. In some embodiments, the composition further comprises an EGFR inhibitor. In some embodiments, the composition further comprises an EMT protein inhibitor.
[0011] Further aspects of the disclosure relate to a kit comprising 1, 2, 3, 4, 5, 6, 7 or more probes or detection agents for detecting a cancer biomarker selected from FTO, METTL3, WTAP, ALKBH5; METTL14, YTHDF1 and/or YTHDF2.
[0012] In some aspects the methods of the disclosure include the detection or screening for multiple cancers, such as at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 cancers at the same time. In some embodiments, the biomarkers provide a screen that will indicate that a cancer is present. The methods may further comprise an additional screen to determine the type of cancer. [0013] In some embodiments, has and/or has been determined to have cancer. In some embodiments, the cancer comprises colorectal cancer, gastric cancer, breast cancer, ovarian cancer, pancreatic adenocarcinoma, hepatocellular carcinoma, lung adenocarcinoma, bladder urothelial carcinoma, head and neck squamous cell carcinoma, acute myeloid leukemia, lung squamous cell carcinoma, esophageal adenocarcinoma, or esophageal squamous cell carcinoma. In some embodiments, the cancer comprises colorectal cancer.
[0014] In some embodiments, the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer. In some embodiments, the patient has and/or has been determined to have an EGFR mutant cancer. In some embodiments, the patient has not been administered an EGFR inhibitor therapy. In some embodiments, the patient has been administered an EGFR inhibitor therapy. In some embodiments, the patient is currently undergoing an EGFR inhibitor therapy regimen.
[0015] In some embodiments, at least FTO is measured. In some embodiments, FTO expression is upregulated. In some embodiments, at least METTL3 is measured. In some embodiments, METTL3 expression is upregulated. In some embodiments, at least WTAP is measured. In some embodiments, WTAP expression is upregulated. In some embodiments, at least ALKBH5 is measured. In some embodiments, ALKBH5 expression is upregulated. In some embodiments, at least METTL14 is measured. In some embodiments, METTL14 expression is downregulated. In some embodiments, at least YTHDF1 is measured. In some embodiments, YTHDF1 expression is downregulated. In some embodiments, at least YTHDF2 is measured. In some embodiments, YTHDF2 expression is downregulated.
[0016] In some embodiments, the expression level of the biomarkers is upregulated at least, at most, or exactly 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold (or any derivable range therein) from a control. In some embodiments, the expression level of the biomarkers is downregulated at least, at most, or exactly 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold (or any derivable range therein) from a control. In some embodiments, the expression level of the biomarker is not significantly different than the control level or within 0.5, 1, 1.5, or 2 standard deviations of a control.
[0017] In some embodiments, the levels of expression of at least two listed biomarkers is measured. In some embodiments, the levels of expression of at least three listed biomarkers is measured. In some embodiments, the levels of expression of at least four listed biomarkers is measured. In some embodiments, the levels of expression of at least five listed biomarkers is measured. In some embodiments, the levels of expression of at least six listed biomarkers is measured. In some embodiments, the levels of expression of at least seven listed biomarkers is measured. In some embodiments, the levels of expression of at least 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) biomarkers is measured.
[0018] In some embodiments, at least FTO and METTL3 is measured and/or determined. In some embodiments, at least FTO and WTAP is measured. In some embodiments, at least FTO and ALKBH5 is measured. In some embodiments, at least FTO and METTL14 is measured. In some embodiments, at least FTO and YTHDF1 is measured. In some embodiments, at least FTO and YTHDF2 is measured. In some embodiments, at least METTL3 and WTAP is measured. In some embodiments, at least METTL3 and ALKBH5 is measured. In some embodiments, at least METTL3 and METTL14 is measured. In some embodiments, at least METTL3 and YTHDF1 is measured. In some embodiments, at least METTL3 and YTHDF2 is measured. In some embodiments, at least WTAP and ALKBH5 is measured. In some embodiments, at least WTAP and METTL14 is measured. In some embodiments, at least WTAP and YTHDF1 is measured. In some embodiments, at least WTAP and YTHDF2 is measured. In some embodiments, at least ALKBH5 and METTL14 is measured. In some embodiments, at least ALKBH5 and YTHDF1 is measured. In some embodiments, at least ALKBH5 and YTHDF2 is measured. In some embodiments, at least METTL14 and YTHDF1 is measured. In some embodiments, at least METTL14 and YTHDF2 is measured. In some embodiments, at least YTHDF1 and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, and WTAP is measured. In some embodiments, at least FTO, METTL3, and ALKBH5 is measured. In some embodiments, at least FTO, METTL3, and METTL14 is measured. In some embodiments, at least FTO, METTL3, and YTHDF1 is measured. In some embodiments, at least FTO, METTL3, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, and ALKBH5 is measured. In some embodiments, at least FTO, WTAP, and METTL14 is measured. In some embodiments, at least FTO, WTAP, and YTHDF1 is measured. In some embodiments, at least FTO, WTAP, and YTHDF2 is measured. In some embodiments, at least FTO, ALKBH5, and METTL14 is measured. In some embodiments, at least FTO, ALKBH5, and YTHDF1 is measured. In some embodiments, at least FTO, ALKBH5, and YTHDF2 is measured. In some embodiments, at least FTO, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, and ALKBH5 is measured. In some embodiments, at least METTL3, WTAP, and METTL14 is measured. In some embodiments, at least METTL3, WTAP, and YTHDF1 is measured. In some embodiments, at least METTL3, WTAP, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, and METTL14 is measured. In some embodiments, at least METTL3, ALKBH5, and YTHDF1 is measured. In some embodiments, at least METTL3, ALKBH5, and YTHDF2 is measured. In some embodiments, at least METTL3, METTL14, and YTHDF1 is measured. In some embodiments, at least METTL3, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, and METTL14 is measured. In some embodiments, at least WTAP, ALKBH5, and YTHDF1 is measured. In some embodiments, at least WTAP, ALKBH5, and YTHDF2 is measured. In some embodiments, at least WTAP, METTL14, and YTHDF1 is measured. In some embodiments, at least WTAP, METTL14, and YTHDF2 is measured. In some embodiments, at least WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, and METTL14 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, and YTHDF1 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, METTL14, and YTHDF1 is measured. In some embodiments, at least
METTL3, WTAP, METTL14, and YTHDF2 is measured. In some embodiments, at least
METTL3, WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least
WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least
WTAP, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured.
[0019] In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, and METTL14 is measured. In some embodiments, at least FTO, METTF3, WTAP, AFKBH5, and YTHDF1 is measured. In some embodiments, at least FTO, METTF3, WTAP, AFKBH5, and YTHDF2 is measured. In some embodiments, at least FTO, METTF3, WTAP, METTF14, and YTHDF1 is measured. In some embodiments, at least FTO, METTF3, WTAP, METTF14, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least METTL3, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF1 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least FTO, WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, METTL14, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, YTHDF1, and YTHDF2 is measured. In some embodiments, at least FTO, METTL3, WTAP, ALKBH5, METTL14, and YTHDF2 is measured. In some embodiments, at least METTL3, WTAP, ALKBH5, METTL14, YTHDF1, and YTHDF2 is measured.
[0020] In some embodiments, the expression level of no other biomarker in the biological sample is measured. In some embodiments, at least one of the listed biomarkers is excluded from being measured. In some embodiments, at least two of the listed biomarkers are excluded from being measured.
[0021] In some embodiments, the method comprises or further comprises comparing the level(s) of expression to a control sample(s) or control level(s) of expression. In some embodiments, the control sample(s) have expression levels that are representative of normal cells from a cohort of patients, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%. In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer. In some embodiments, the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
[0022] In some embodiments, the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort patients with CMS4 cancer. In some embodiments, the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort patients with CMS4 cancer.
[0023] In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0024] In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0025] In some embodiments, a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0026] In some embodiments, the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
[0027] In some embodiments, the method further comprises treating the patient. In some embodiments, the treatment excludes one or more of EGFR inhibitors, adjuvant therapy, neo adjuvant therapy, and EMT inhibitors.
[0028] In some embodiments, the treatment comprises an EGFR inhibitor. In some embodiments, the treatment comprises administration of an FTO inhibitor. In some embodiments, the treatment comprises an epithelial to mesenchymal transition (EMT) protein inhibitor. In some embodiments, the EMT protein inhibitor comprises an inhibitor of a protein selected from APP, XPOl, NTRK1, ELAVL1, HuR, and combinations thereof. In some embodiments, the inhibitor is a small molecule, nucleic acid, or protein. In some embodiments, the inhibitor inhibits protein expression. In some embodiments, the inhibitor inhibits protein activity. In some embodiments, the nucleic acid is an siRNA or miRNA. In some embodiments, the protein is an FTO-specific, EMT protein- specific, and/or EGFR-specific binding protein or peptide. In some embodiments, the FTO-specific and/or EGFR-specific binding protein comprises all or part of an antibody. In some embodiments, the EGFR inhibitor comprises a tyrosine kinase inhibitor (TKI). In some embodiments, the TKI comprises gefitinib, erlotinib, lapatinib, neratinib, osimertinib, vandetanib, dacomitinib, or combinations thereof. In some embodiments, the EGFR inhibitor comprises an antibody. In some embodiments, the antibody comprises cetuximab, panitumumab, necitumumab, or combinations thereof.
[0029] In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any range derivable therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0030] In some embodiments, a) the levels of expression of 1) FTO, METTF3, WTAP and/or AFKBH5 are upregulated and/or 2) METTF14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non- recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0031] In some embodiments, the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer. In some embodiments, the patient identified as high risk is treated with one or more of an EGFR inhibitor, an FTO inhibitor, an EMT protein inhibitor, adjuvant, and neoadjuvant therapy.
[0032] In some embodiments, the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a cancerous sample.
[0033] In some embodiments, the method further comprises treating the patient for cancer after measuring the level of expression of one or more listed biomarkers.
[0034] In some embodiments, expression is measured using one or more hybridization and/or amplification assays. In some embodiments, the assay comprises polymerase chain reaction. In some embodiments, the level of expression of no additional biomarkers is measured.
[0035] In some embodiments, a cohort comprises at least 50, 100, 200, 300, 400, 500 or more patients (or any derivable range therein). In some embodiments, the control sample(s) have expression levels that are representative of normal colorectal cells, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%. In some embodiments, the control sample(s) have expression levels that are representative of cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein). In some embodiments, the control sample(s) have expression levels that are representative of cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein). In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0036] In some embodiments, the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0037] In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 99% (or any derivable range therein), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer. In some embodiments, 1, 2, 3, 4, 5, 6, or 7 (or any derivable range therein) measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
[0038] In embodiments of the disclosure, the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, a normal mucosal sample, or a colorectal sample.
[0039] In some embodiments, the treatment comprises or further comprises surgery. In some embodiments, expression is measured using one or more hybridization and/or amplification assays. In some embodiments, the assay comprises polymerase chain reaction.
[0040] In some embodiments, the method comprises or further comprises measuring the level of expression of at least one or more of the following additional listed biomarkers: one or more of the listed biomarkers: METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2. In some embodiments, at least METTL3 is measured. In some embodiments, METTL3 expression is upregulated. In some embodiments, at least WTAP is measured. In some embodiments, WTAP expression is upregulated. In some embodiments, at least ALKBH5 is measured. In some embodiments, ALKBH5 expression is upregulated. In some embodiments, at least METTL14 is measured. In some embodiments, METTL14 expression is downregulated. In some embodiments, at least YTHDF1 is measured. In some embodiments, YTHDF1 expression is downregulated. In some embodiments, at least YTHDF2 is measured. In some embodiments, YTHDF2 expression is downregulated.
[0041] In some embodiments, the method comprises or further comprises comparing the level(s) of expression of the additional listed biomarkers to a control sample(s) or control level(s) of expression.
[0042] In some embodiments, the treatment comprises chemotherapy, radiation, surgery, adjuvant, and/or neoadjuvant therapy. In some embodiments, the treatment excludes chemotherapy, radiation, adjuvant, and/or neoadjuvant therapy. In some embodiments, the biomarker comprises the human gene. In some embodiments, the biomarker comprises a homolog or variant of the human gene.
[0043] In some embodiments, the kit further comprises one or more agents for detecting one or more controls. In some embodiments, the kit further comprises reagents for isolating nucleic acids from a biological sample. In some embodiments, the reagents are for isolating nucleic acids from a serum sample. In some embodiments, the reagents are for isolating nucleic acids from a sample described herein.
[0044] The term subject or patient may refer to an animal (for example a mammal), including but not limited to humans, non-human primates, rodents, dogs, or pigs. The methods of obtaining provided herein include methods of biopsy such as fine needle aspiration, core needle biopsy, vacuum assisted biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy or skin biopsy.
[0045] In certain embodiments the sample is obtained from a biopsy . In other embodiments the sample may be obtained from any of the tissues provided herein that include but are not limited to gall bladder, skin, heart, lung, breast, pancreas, liver, muscle, kidney, smooth muscle, bladder, intestine, brain, prostate, or thyroid tissue.
[0046] Alternatively, the sample may include but not be limited to blood, serum, sweat, hair follicle, buccal tissue, tears, menses, urine, feces, or saliva. In particular embodiments, the sample may be a tissue sample, a whole blood sample, a urine sample, a saliva sample, a serum sample, a plasma sample or a fecal sample. [0047] In certain aspects the sample is obtained from cystic fluid or fluid derived from a tumor or neoplasm. In certain aspects of the current methods, any medical professional such as a doctor, nurse or medical technician may obtain a biological sample for testing. In further aspects of the current methods, the patient or subject may obtain a biological sample for testing without the assistance of a medical professional, such as obtaining a whole blood sample, a urine sample, a fecal sample, a buccal sample, or a saliva sample.
[0048] In further embodiments, the sample may be a fresh, frozen or preserved sample or a fine needle aspirate. In particular embodiments, the sample is a formalin-fixed, paraffin- embedded (FFPE) sample. An acquired sample may be placed in short term or long term storage by placing in a suitable medium, excipient, solution, or container. In certain cases storage may require keeping the sample in a refrigerated, or frozen environment. The sample may be quickly frozen prior to storage in a frozen environment. In certain instances the frozen sample may be contacted with a suitable cryopreservation medium or compound. Examples of cryopreservation mediums or compounds include but are not limited to: glycerol, ethylene glycol, sucrose, or glucose.
[0049] Some embodiments further involve isolating nucleic acids such as ribonucleic or RNA from a biological sample or in a sample of the patient. Other steps may or may not include amplifying a nucleic acid in a sample and/or hybridizing one or more probes to an amplified or non-amplified nucleic acid. The methods may further comprise assaying nucleic acids in a sample. In certain embodiments, a microarray may be used to measure or assay the level of biomarker expression in a sample. The methods may further comprise recording the biomarker expression level in a tangible medium or reporting the expression level to the patient, a health care payer, a physician, an insurance agent, or an electronic system.
[0050] A difference between or among weighted coefficients ore expression levels or between or among the weighted comparisons may be, be at least or be at most about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0, 16.5, 17.0, 17.5, 18.0, 18.5, 19.0. 19.5, 20.0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300, 305, 310, 315, 320, 325, 330, 335, 340, 345, 350, 355, 360, 365, 370, 375, 380, 385, 390, 395, 400, 410, 420, 425, 430, 440, 441, 450, 460, 470, 475, 480, 490, 500, 510, 520, 525, 530, 540, 550, 560, 570, 575,
580, 590, 600, 610, 620, 625, 630, 640, 650, 660, 670, 675, 680, 690, 700, 710, 720, 725, 730, 740, 750, 760, 770, 775, 780, 790, 800, 810, 820, 825, 830, 840, 850, 860, 870, 875, 880, 890, 900, 910, 920, 925, 930, 940, 950, 960, 970, 975, 980, 990, 1000 times or -fold (or any range derivable therein).
[0051] In some embodiments, determination of calculation of a diagnostic, prognostic, or risk score is performed by applying classification algorithms based on the expression values of biomarkers with differential expression p values of about, between about, or at most about 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.020, 0.021, 0.022, 0.023, 0.024, 0.025, 0.026, 0.027, 0.028, 0.029, 0.03, 0.031, 0.032, 0.033, 0.034, 0.035, 0.036, 0.037, 0.038, 0.039, 0.040, 0.041, 0.042, 0.043, 0.044, 0.045, 0.046, 0.047, 0.048, 0.049, 0.050, 0.051, 0.052, 0.053, 0.054, 0.055, 0.056, 0.057, 0.058, 0.059, 0.060, 0.061, 0.062, 0.063, 0.064, 0.065, 0.066, 0.067, 0.068, 0.069, 0.070, 0.071, 0.072, 0.073, 0.074, 0.075, 0.076, 0.077, 0.078, 0.079, 0.080, 0.081, 0.082, 0.083, 0.084, 0.085, 0.086, 0.087, 0.088, 0.089, 0.090, 0.091, 0.092, 0.093, 0.094, 0.095, 0.096, 0.097, 0.098, 0.099, 0.1, 0.2, 0.3, 0.4,
0.5, 0.6, 0.7, 0.8, 0.9 or higher (or any range derivable therein). In certain embodiments, the prognosis score is calculated using one or more statistically significantly differentially expressed biomarkers (either individually or as difference pairs).
[0052] Any of the methods described herein may be implemented on tangible computer- readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform one or more operations. In some embodiments, there is a tangible computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: a) receiving information corresponding to an expression level of a biomarkers in a sample from a patient; and b) determining a difference value in the expression levels using the information corresponding to the expression levels in the sample compared to a control or reference expression level for the gene.
[0053] In other aspects, tangible computer-readable medium further comprise computer- readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising making recommendations comprising: wherein the patient in the step a) is under or after a first treatment for cancer, administering the same treatment as the first treatment to the patient if the patient does not have increased expression level; administering a different treatment from the first treatment to the patient if the patient has increased expression level.
[0054] In some embodiments, receiving information comprises receiving from a tangible data storage device information corresponding to the expression levels from a tangible storage device. In additional embodiments the medium further comprises computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising: sending information corresponding to the difference value to a tangible data storage device, calculating a prognosis score for the patient, treating the patient with a traditional therapy if the patient does not have expression levels, and/or or treating the patient with an alternative esophageal therapy if the patient has increased expression levels.
[0055] The tangible, computer-readable medium further comprise computer-readable code that, when executed by a computer, causes the computer to perform one or more additional operations comprising calculating a prognosis score for the patient. The operations may further comprise making recommendations comprising: administering a treatment to a patient that is determined to have a decreased expression level.
[0056] As used herein, the terms “or” and“and/or” are utilized to describe multiple components in combination or exclusive of one another. For example,“x, y, and/or z” can refer to“x” alone,“y” alone,“z” alone,“x, y, and z,”“(x and y) or z,”“x or (y and z),” or“x or y or z.” Is is specifically contemplated that x, y, or z may be specifically excluded from an
[0057] Throughout this application, the term“about” is used according to its plain and ordinary meaning in the area of cell biology to indicate that a value includes the standard deviation of error for the device or method being employed to determine the value.
[0058] The term“comprising,” which is synonymous with“including,”“containing,” or “characterized by,” is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. The phrase“consisting of’ excludes any element, step, or ingredient not specified. The phrase“consisting essentially of’ limits the scope of described subject matter to the specified materials or steps and those that do not materially affect its basic and novel characteristics. It is contemplated that embodiments described in the context of the term “comprising” may also be implemented in the context of the term“consisting of’ or“consisting essentially of.”
[0059] It is specifically contemplated that any limitation discussed with respect to one embodiment of the invention may apply to any other embodiment of the invention. Furthermore, any composition of the invention may be used in any method of the invention, and any method of the invention may be used to produce or to utilize any composition of the invention. Aspects of an embodiment set forth in the Examples are also embodiments that may be implemented in the context of embodiments discussed elsewhere in a different Example or elsewhere in the application, such as in the Summary of Invention, Detailed Description of the Embodiments, Claims, and description of Figure Legends.
BRIEF DESCRIPTION OF THE DRAWINGS
[0060] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.
[0061] FIG. 1A-H: Internal and external validations in CRC, GC, BRCA and OV demonstrated the robust prognostic value of RNAMethyPro. Kaplan-Meier curves show significant associations between RNAMethyPro stratified risk groups and disease-free survival or overall survival for (A) CRC training cohort, TCGA-COADREAD (n = 509); (B) CRC validation cohort, CIT (n = 566); (C) GC training cohort, TCGA-STAD (n = 202); (D) GC validation cohort, ACRG-GC (n = 282); (E) BRCA training cohort, METABRIC discovery (n = 995); (F) BRCA validation cohort, METABRIC validation (n = 986); (G) OV training cohort, MAYO-OV (n = 174); (H) OV validation cohort, TCGA-OV (n = 511). Only patients with available survival information were included in the analyses.
[0062] FIG. 2A-D: Pan-cancer functional analyses identified conserved biological processes and protein-protein interaction subnetwork dysregulated in RNAMethyPro high-risk patients. (A) Heatmap of enrichment scores of hallmark gene sets across 13 cancer types. Hierarchical clustering on the enrichment score matrix identified a small cluster consisting of BRCA, AML and PDAC and a major cluster of the other 10 cancer types. (B) An enrichment map illustrating associations between hallmark gene sets with different degrees of conservation across various cancer types. Node size represents the number of genes in a gene set. Nodes are colored in proportion to the conservation scores of gene sets across 10 cancer types of the major cluster. Edges between gene sets showed their association quantified by Jaccard index. To make the network relatively sparse, edges with extremely low Jaccard indices (<0.03) were removed. (C) Heatmaps showing the average log2 fold difference of the indicated genes (rows) in core gene sets for EMT, matrix remodeling and TGF-b pathway between RNAMethyPro high- and low-risk groups across the 13 different cancer types. (D) Conserved protein-protein interaction (PPI) subnetwork underlying the RNAMethyPro high-risk patients across the 10 cancer types identified using BioNet (FDR < le-4). Node size is proportionate to the degree of each node in the network. Node color represents the conservation score calculated by the number of times (out of the total 10 cancer types) that the corresponding gene is differentially expressed in the high-risk group compared to the low-risk group (Benjamini-Hochberg adjusted P < 0.05). Nodes with labels represent EMT signature genes. Hub proteins (NTRK1, XPOl, ELAVL1 and APP) in the network are highlighted with bold labels. Edges represent physical protein-protein interactions between genes obtained from BioGRID database (version 3.4.134). Edges colored in dark black represent interactions between the four hub proteins and EMT signature gene products.
[0063] FIG. 3A-C: RNAMethyPro high-risk group is significantly associated with the mesenchymal subtype of CRC. (A) Significant associations were found between RNAMethyPro risk groups (high- vs low-risk) and clinical and molecular characteristics in the CIT cohort (* P < 0.05, ** P < 0.01 and *** P < 0.001, Fisher’s exact tests). Heatmap shows expression levels of m6A signature genes in all patient samples ordered by RNAMethyPro risk score. (B) Bar plot compares RNAMethyPro risk scores of tumors classified to different CMSs in the CIT cohort. CMS4 tumors show significantly higher risk scores than CMS 1, CMS2 and CMS3 (*** P < 0.0001, one-tailed Student’s t-tests). (C) Heatmap showing the pair-wise associations between RNAMethyPro risk groups (rows) and CMS subtypes (columns) in the CIT cohort. Colors are proportionate to the -loglO transformed p-values derived from hypergeometric tests.
[0064] FIG. 4A-E: Integrative analysis revealed complex physical and functional interactions between m6A regulators and EMT. (A) Bar plot compares normalized expression levels of m6A regulators and EMT signature genes, showing significant differences between RNAMethyPro high- and low-risk groups (P < 0.01 in all comparisons, Wilcoxon rank sum tests). (B) Protein-protein interactions between m6A regulators (red nodes), hub proteins in the conserved subnetwork (green nodes) and EMT key factors (blue nodes). (C) Scatter plot showing significant Pearson correlations between FTO and ZEB 1 expression in CRC Meta validation cohort (r = 0.322, P < le-22). Dots in the scatter plots are colored by RNAMethyPro risk groups. (D-E) Bar plots illustrate stromal and immune scores in CRC Meta-validation cohort calculated by ESTIMATE, indicating stronger (D) stromal and (E) immune infiltration in the RNAMethyPro high-risk group (** P < 0.01,*** P < 0.001, one-tailed Student’s t-tests).
[0065] FIG. 5A-G: RNAMethyPro is predictive of anti-EGFR therapy response in CRC cell lines and metastatic patients. (A) Waterfall plot comparing cetuximab sensitivities of 28 MSS cell lines without KRAS, NRAS, BRAF and PIK3CA mutations (48). Bars represent arbitrary indices of cetuximab effects (median-centered) on cell lines as described in (48). Cell lines sensitive to cetuximab are shown with a negative index. Cell lines classified to RNAMethyPro high-, intermediate- and low-risk groups are colored in red, gray and blue, respectively. (B) Barplot showing that cell lines belonging to the RNAMethyPro low-risk group are significantly more sensitive to cetuximab than those classified to intermediate- and high-risk groups (* P < 0.05 and *** P < 0.001, one-tailed Student’s t-tests). (C) Heatmap showing expression levels of m6A signature genes and KRAS mutations in the Khambata-Ford cohort with 80 patients with metastatic cancer, ordered by RNAMethyPro risk score. (D) Boxplot showing RNAMethyPro risk scores are significantly higher in CMS4 tumors than non-CMS4 tumors (P = 0.00065, one-tailed Student’s t-test). (E) Heatmap showing pairwise associations between RNAMethyPro risk groups and CMS subtypes, colored by -loglO transformed p-values derived from hypergeometric tests. (F) Bar plot illustrating the difference in Cetuximab response between RNAMethyPro high- and low-risk groups (P = 0.06, Fisher’s exact test, PD versus SD/PR/CR). CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease. (G) Kaplan-Meier graph of patients stratified for RNAMethyPro risk (high-risk group versus low-risk group, P = 0.036, log-rank test).
[0066] FIG. 6A-I. Internal validation of the prognostic value of RNAMethyPro in the other 9 cancer types. Kaplan-Meier graphs stratified for RNAMethyPro risk groups for (A) Pancreatic adenocarcinoma (TCGA-PAAD cohort, n = 149); (B) Hepatocellular carcinoma (TCGA-LIHC cohort, n = 287); (C) TCGA Lung adenocarcinoma (TCGA-LUAD cohort, n = 249); (D) Bladder urothelial carcinoma (TCGA-BLCA cohort, n = 275); (E) Head and Neck squamous cell carcinoma (TCGA-HNSC cohort, n = 261); (F) Acute myeloid leukemia (TARGET-AML cohort, n = 284); (G) Lung squamous cell carcinoma (TCGA-LUSC cohort, n = 154); (H) Esophageal adenocarcinoma (TCGA-ESCA (EAC) cohort, n = 32); (I) Esophageal squamous cell carcinoma (ECGA-ESCA (ESCC) cohort, n = 70). Only patients with available survival information were included in the analyses.
[0067] FIG. 7A-J. GSEA plots for EMT in 10 cancer types.
[0068] FIG. 8A-H. GSEA plots for characteristic gene signatures and pathways associated with the mesenchymal CMS4 subtype of CRC (TCGA-COADREAD cohort, n = 626).
[0069] FIG. 9. A coexpression network of functional associations between m6A regulator genes (red nodes), hub genes in the conserved subnetwork (green nodes) and EMT signature genes (blue nodes). Edge widths are proportionate to Pearson correlation coefficients between gene expression levels of gene pairs that are significantly correlated (P < 0.05) in the CRC META-validation cohort.
DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
[0070] Certain aspects of the invention provide a test that could assist physicians to select the optimal therapy for a patient from several alternative treatment options. A major clinical challenge in cancer treatment is to identify the subset of patients who will benefit from a therapeutic regimen, both in metastatic and adjuvant settings. The number of anti-cancer drugs and multi-drug combinations has increased substantially in the past decade, however, treatments continue to be applied empirically using a trial- and-error approach. Here methods and compositions are provided to diagnose patients to determine the optimal treatment option for cancer patients.
I. Definitions
[0071] The term“substantially the same”,“not significantly different”, or“within the range” refers to a level of expression that is not significantly different than what it is compared to. Alternatively, or in conjunction, the term substantially the same refers to a level of expression that is less than 2, 1.5, or 1.25 fold different than the expression level it is compared to or less than 20, 15, 10, or 5% difference in expression.
[0072] By“subject” or“patient” is meant any single subject for which therapy is desired, including humans, cattle, dogs, guinea pigs, rabbits, chickens, and so on. Also intended to be included as a subject are any subjects involved in clinical research trials not showing any clinical sign of disease, or subjects involved in epidemiological studies, or subjects used as controls.
[0073] The term "primer" or“probe” as used herein, is meant to encompass any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process. Typically, primers are oligonucleotides from ten to twenty and/or thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single- stranded form, although the single-stranded form is preferred. A probe may also refer to a nucleic acid that is capable of hybridizing by base complementarity to a nucleic acid of a gene of interest or a fragment thereof.
[0074] As used herein,“increased expression” or“elevated expression” or“decreased expression” refers to an expression level of a biomarker in the subject’s sample as compared to a reference level representing the same biomarker or a different biomarker. In certain aspects, the reference level may be a reference level of expression from a non-cancerous tissue from the same subject. Alternatively, the reference level may be a reference level of expression from a different subject or group of subjects. For example, the reference level of expression may be an expression level obtained from a sample (e.g., a tissue, fluid or cell sample) of a subject or group of subjects without cancer, with colorectal cancer, or an expression level obtained from a non-cancerous tissue of a subject or group of subjects with cancer. The reference level may be a single value or may be a range of values. The reference level of expression can be determined using any method known to those of ordinary skill in the art. The reference level may also be depicted graphically as an area on a graph. In certain embodiments, a reference level is a normalized level.
[0075] The term“determining” or“evaluating” as used herein may refer to measuring, quantitating, or quantifying (either qualitatively or quantitatively).
II. Inhibitors
[0076] Embodiments of the disclosure relate to administration of inhibitors, such as inhibitory nucleic acids, polypeptides, antibodies, or molecular inhibitors. These are further described below.
A. FTO
[0077] Certain embodiments of the disclosure relate to administration of FTO inhibitors. The inhibitor may be specific for FTO or the inhibitor may inhibit a class of enzymes that include dioxygenases. FTO relates to FTO alpha-ketoglutarate dependent dioxygenase. The human gene is located at l6ql2.2 (NC_0000l6.l0 (53703963..54114467)). The following are representative mRNA and protein sequences of human FTO.
[0078] Homo sapiens FTO alpha-ketoglutarate dependent dioxygenase (FTO), transcript variant 3, mRNA; NCBI Reference Sequence: NM_00l080432.3 is herein incorporated by reference:
gcggtggcgaaggcggctttagtggcagcatgaagcgcaccccgactgccgaggaacgagagcgcgaagctaagaaactgaggc ttcttgaagagcttgaagacacttggctcccttatctgacccccaaagatgatgaattctatcagcagtggcagctgaaatatcctaaact aattctccgagaagccagcagtgtatctgaggagctccataaagaggttcaagaagcctttctcacactgcacaagcatggctgcttatt tcgggacctggttaggatccaaggcaaagatctgctcactccggtatctcgcatcctcattggtaatccaggctgcacctacaagtacct gaacaccaggctctttacggtcccctggccagtgaaagggtctaatataaaacacaccgaggctgaaatagccgctgcttgtgagacc ttcctcaagctcaatgactacctgcagatagaaaccatccaggctttggaagaacttgctgccaaagagaaggctaatgaggatgctgt gccattgtgtatgtctgcagatttccccagggttgggatgggttcatcctacaacggacaagatgaagtggacattaagagcagagcag catacaacgtaactttgctgaatttcatggatcctcagaaaatgccatacctgaaagaggaaccttattttggcatggggaaaatggcagt gagctggcatcatgatgaaaatctggtggacaggtcagcggtggcagtgtacagttatagctgtgaaggccctgaagaggaaagtga ggatgactctcatctcgaaggcagggatcctgatatttggcatgttggttttaagatctcatgggacatagagacacctggtttggcgata ccccttcaccaaggagactgctatttcatgcttgatgatctcaatgccacccaccaacactgtgttttggccggttcacaacctcggtttag ttccacccaccgagtggcagagtgctcaacaggaaccttggattatattttacaacgctgtcagttggctctgcagaatgtctgtgacgat gtggacaatgatgatgtctctttgaaatcctttgagcctgcagttttgaaacaaggagaagaaattcataatgaggtcgagtttgagtggct gaggcagttttggtttcaaggcaatcgatacagaaagtgcactgactggtggtgtcaacccatggctcaactggaagcactgtggaag aagatggagggtgtgacaaatgctgtgcttcatgaagttaaaagagaggggctccccgtggaacaaaggaatgaaatcttgactgcca tccttgcctcgctcactgcacgccagaacctgaggagagaatggcatgccaggtgccagtcacgaattgcccgaacattacctgctga tcagaagccagaatgtcggccatactgggaaaaggatgatgcttcgatgcctctgccgtttgacctcacagacatcgtttcagaactca gaggtcagcttctggaagcaaaaccctagaaggagcacaagtctcaggcggaggagaaaaagagatcggcttttctcctccaacgtt gtcatgggcttaagcaagagcagtggagacttctcttggcccctagattgtagcacccgggtcccaatccaaaacagctaggaaatgg tgcccatgaagttttaaatgttttaaaatgaccctgtgttatagtctgatttggtgttaaacaggaccttcttcccccaaaattgttcagattata aaatgtgagccattcagcccccaaggtccagggcaggcgacaggaacgagcccagcgtgtgacaaagcctaacctactttcctctttc ccaagctttttcagagactctggagtggacccagccctctggggaaagacagaacttagagacatcccagttactcaccacacccata gtgctgtccaatatggtagccactagctagctgtggctacttcaatttaaattcagttttaattttaattaaaaatgcagctcttcagtcgccct ggccacatttcaagtgcttaacagcctcatgtggctagtgactgctgtattggacggtacagatatggaacattttcatcatcgaagaaag tcctattggacaacacttctataaaaagtttgagagcaggaattctcatttccattcgtctgtagcttctatccccaaaggcaaagaaactaa aagagaaatgactcattgaagattggcctctttcctttctctaagacaaacctaagtaaaagcctgagctttgagtcctatgctcagcacac gggaaggagatgttaataattaaaataaagttgatatcctgtctttagggagttcccttgatctcttgaaagagacacagccccatttacatt atttcgtggatttcaccagcatagtatagtttttttctgtaagtccctcattcttatgtaataacaggtggaactgaggtttgaagaacctcagt ggcccatcctgatgacattggagactcaaagagacaagagagagtagggtttaaaacctgagctttaagactcccactagcttcgtgtc ctttggcatgttaacgtgcctcagtttcctcatctgtataatggggatatatgaaaggcaccagtcctaaggtgaacattaagtgagatgat tctagttacagacttagaacaatttccagcacatagttaaatatccaggaaattctggtactgttatgtgtgggtgagctgacctggatgta gatgttttcctctctcttgctgacccctccgccagttttgtcttgtgatgccattaacacatctctccctttctgacctggctcctgcccattggt gtcccaagaaatcgtgagaatagttagccccccgtctccccagcctgttgctttctcgtgtagttgttcacagtagttgagaagttgaaga gcttttgcctattgaaggtgcactgagaataaactctttcctgccaccagaattgcagtggttcacggcctgcactcattcccatgaatgca gttaatagccacagaaatgtcacattaagcaaagcagccagggtctcatcgtgttgagactcgagtctctcagaccttggattcattccct ggtgtctttgagcctcagtttcctcattggtaaaagagaagtgaagcagtgtctcacagggtcattacagagattaaatgaaataaatgaa ataacatagaccaggagggcgtggtgtttaaaagtcacagatggggcaccctcgggccatccagcccagtgttttctttagcccctatg atgttcattttttgttatatcccattaggtgcccatatttaaaaattgggagatttcacataaaattaaaaggtctgcattttcttttttcttttcttttt ttttttttttgagacacagtctcactctgtcaccaggctagagtgcagtggcacgatctcagctcactgcaacctctgcctcccaggttcaa gtaattctcctgcctcagcctcccaagtagctgggactacaggcacgtgccaccacgcccagctaatttttgtatttttagcagagatggg gtttcaccacattggccaggatggtctcgatctcaacctcgtgatccacccacctcggtctcccaaagcgctgggattacaggcgtgag ccaccgcgccaagccaaggtctgcatttttctttagaactcagaacacccaatagtcctaggcccccatcctcgcatggcagcaagcta aataagcatcttcccactgcgagttggggcatgacccagcctatggtttgccatactccctctttttctccgttttttcattaattgtgaacctg acctgcatcaccctttcatgtcagtgctctccaaacctgcttgcttgcacccctctagtcgaaatattttgtgcttaccccaatatatgtgtgt gactattgaactctattcgtagactgcttgtactaatgtcatttgcatcataaaatattcatatccaataaacatattaaaaggatgagataag aaaccgagagattttgctgtttttttccttttgcatggatgagccagcttcactgtcctgggtggggcccaggtggaattagttctcaaagtc ctccaggtggagtcagggaatgtgcaacagggttggagaaatcactactttaagtgaatccgaaaggtgagatcacatttgctctaaag aaatggtgatcccagcactttgggaggctgaggcagcagatcactggaggtcaggagttcgagaccagcctggccaacacggtgaa accccgtctctactgaaaacacaaaaattagctgggtgtggtggtgtgtgcctgtaatcccagctactcgggaggctgaggcaggcaa atcgcttggcccgggaggcggaggttgcagtgagccgagatcatgccactgcactccagcctgggccacggagcgagagaagaa agaaatggtgactttcattgatcatgtgtttgaggatttcatgtgctctccagggaggtttcaggtgggtagaaggaggtgggcaagacc caataaaaaagcagctggtgcgggcaatgacaatgaactcgtatcctgcagggtcaaaggaaggcttgcttctgctgtgaattggaga aggactttcctggaagcacaggcccagaaatcgcacccttctccccatgtgtgcggataagggaccacttccatcagcagcagcccc ctcctgctttcctgccagtcctccctgtggtcccaggtctcttgagaaaagtgatctaagagatccctttgcaatgaggtgctactgactgc cctacctccctcccttcctcccatgaatgtttcttggtgctgaccacagcctcagcaatgaggcaagcctggggacccaagacagatct ctgcctcccaggctagtggatgccctgggatatgtagtcaccaaaataggaacttaccccatagtggggaaatagacagtaagcagca aatcaataacaagagtgttccagatggttgtaagtgccaggaagggaaccaactgggagagggacaagaggagatggtgactgacc aaggggaccttgatcaggctgtggggaagggaggtggttgggaagagcttcccaggaaaggggacggcgggcccaggcaggag agccttgggagggggtgcccaaggaaggaaaagggccctgagcctgaagccgagaagaccaggaggggagaaggggagatgt agggcagagcagacgggagccgctcgggttttattccacacaccccaggaagcatgagagggtttcaagcagcaagggcatggaa gtaacttggtgagatatttttatgcattagatcatcgctctatctggattccagagggtctctgagagagcaaacagcttaatccaaaggag cggctttccaactgggaatgtccccctggctgggtgagatctcaagatggcctgcggcccctctagattgcctgcctacagagttcact ctaaacagcccctcccctccacaccccagcagatccattcctgacgccctcactggcaggctccagccccacagagctttctagacat aaaagagcagggtcatggcatcattggtgacacaattttagtaataagcttcaaaacccatcactccactgaatccagggatgccagaa ttgagagtccataggacccgtttaacggatcccacattcagtagacggttttttgtatgcttcgagggaaggaaggtattttcaaatgcaa cttcttttttttttttcttgctctagttagggctgattttaccactgggcaaattgcatacatttggatccatgccacgctaaaaactgtttattttg gagatctgtcagaggcaagcacatggaagacaaggggattctggtttgaaaaggcaattctcatccagacagattcagatggagagg agcggtgtggattaaaatgcgccgaagtggtaatgccgtttatcccgtttgcctttgttactctgtgattaaatggtatttttaattaagtttcat tgggagccataggtatcgcggtggtgaaatcaatttgacaaccataaaggggagagacggcacaggcgtgttgtgatgattgcggct gtagggaaagccgggcagcttgcagaggatgggtgggaggaggggaagccggctaagaatgacttcctgcaagacagcaaggg cacccctgggccactgctgtgtttgggaggcaggttttgggggttgtcagaaggcattcacctggttctctcgctcacctgagacaccc gatagattcctggaaactccaggaaagtatctgaagatctggttctccattctctcttattaacaaggagaaccacaagtgccccccagat cccggctagaaggaccagacagctttccaccccggttcccaggcagccctgctcccatagtcctgtgtcccatcggccccatgctccc aggacagtcctaattcccacctctcagaaccttgtcagccaagttcttcctgctctctggcccaaatcctcctcctacattggaaactgag cctctctgcatcctctgctctttctatcccgctgtcattcatcagattttccaaatctttggattcctgagtggcagaagaggttttctgagttta agttctgattctgtgtgtgattctcactctaccacctcttcaaacctttgttgtcttatctacaaaatagaatagtagtaatccatcacctaaggt tgttgtgaaggttcaataagttaatgcgtatttaaaatgcctcccacagtacctgacatatactgggcttcagtgaggtactagctattattat taaccaagtttcctgtggtaacagttgtagctttgtgactgggccaaatcacttaacccctctgcgctccagtctttgtttctataatggggat gatgataatgcctagctcattggattgttctgtcccctacgatcagccatgttaagtgattcatatcatgtctggtacttaaaaatcacgcca cgcatgtacattattatgatgaaaaatatgatccgtgatatcctgaccaaaatattaaagggactaaagatagctgtggcttgttcaagaag aatattgtgtcactatcccatatattatcccatttgctcttcacagcttccatttttcgctaggcggatggcatggaactttttataaatgagata ttatgaaaaatgatgttttaggactctcatttctacagtgggagtaggtcacccattgcaattttggatttgcttaaaaaaattcttgccatcac cttctaatggatgatctgtgtacaacaattgtttattgactctgaatgtctaagtaccagggtcagtctatttcaaggggagggaagcattaa ttaacctccagcattagattcagtgattcttttccaatgatgcagttcatgactttgctcgcatttacttttcatcaatcctgaaagaattgaggt aaaatagttcctctgcacatgtgtgtcaagctaaatggataacagcagatacagatctgtttgcctgtctgcacttgcctttagacaaaattc atcaattttacaaaagccactgactaaacatggcaccaatacaaatgaagcacttctagcaggcggagattccctttgtttctgatctggta aatgcggtagtttcctgctgagagatgggaagtgctggcctaggacagcaaggtgccctacaggtggggccaaaagggtcaagacc gttctacaggaagtttaggagaagttcaatggttccagatcctgtgtgcttcgggtaattctgaccctcttcattagtgataatggcatgaa gctctttcacacagtcttttttttttttctttttttttttcagacagggtctcaccctgtcacgtaggctggagtgcagtggtgagatcacggctc actgcagcctcgacttcatgggctcaagcgattctcctgcctcagcctcctaagtagtcgggatcataggcacttgccaccacatccgg ctaatttttttgtagagacaggatttcaccacattacacaggctggtttcaaactccgaggctcaagtgatctgcctgcatcggcctcccaa agcgctgagattacaagcgtgagccactacgccttgccctccacacagccttgcttggtgttaaagattaaacaaagaccacaggtgat cactgtcttcgtggtgccagtttcaagggcacccttcttcccttcccagcctccgagagaaggagagagggtccacaagccagatccat ccccatccacacaggtaaaaccacgactgtgcagctagcaggtggagataacatttggaaaaaggctttgtaaatgctaaagtcctact caagtccaagggagagaaattattattattcgttttgtgaaaccaatttagtttggctgggtaatggaagaatttctacatacattcattacttc tgatcaggcaagaccagtctgacacaggaacagtctatggctcactcttaaagccacagcaggctgccagggcttggagaaatagaa acctctcttgcacaagaatagtctcaatgaatcatgttaaggcctctttaggtttttcagactccatgcaccctgtggaaactgcctttcttga gtagaggtacgttcagcacttcataaaataatcttggagcctccagacacacggatggaggagcatgatttcatttgtttctttgcaaaact gctgtccccaactgaaaaacctgattatcctttcaaatagggaattcggctttccacgttggaaccagaacagttaaccttcaaaccccca aggcttgcaagagatgaatcagtttctcagacagccaaagccgtggcttataactcatccaacccagaaaactggaccgctggtcacct tccttccccctgcccccaactctgcagacagaggtttcccgttgattatgccttgattagagtcaggagagaagcaaaccaggtatatag gattccattatccttccctcctctgctcccaaccagggtcacgctgagagggatctcggtgaacatgtgaacaatcaagccatgtttacca tggacgtttagttttcttttctcaaaatcaaaacagagtttagtaggcagcgtatttcatacatgccccttgatcaatggaatgatctgtcaga agccattaaagcccccattagcttgaatgcattcaaagctaaactattggatcatttaagggctgcagtgattgtttttaatataccgtacatt gatttctccctgtgagcagcaacataagtttgaaactaactgtgtatgactaaggctccatttgctgtctccaaccctctgtgagaagcatg gtttcacttcgaccagaaatgtctgtgtatagttttcaaagagatgcagaccctgttcgatttcccaagatttagactgggtcgggttgttatt tcttttttccctgagctttctcccatttctttgtgcccattaagtgagctgtgcgtgcagaatgggagaggcatccctgccaaggacttcaag tgaaaggcggtgggagaaattgttctgaaagcatgaagcccagctgaggccaaaatcaaagtgaatttgacagccttgggccagcaa aactctgtacccagcagaaaacaatagatgtgtggctgtgtcaggggcatcctcactgggacatagcttggggagctgaaggtacctt ggaagggccagatgaggaagctagccaaggccacaggccttcctttgactgccatattgccagctcttcatagtattgactcttcagtct tagccaacacacacttgttgattccttccggaatgtcagactctgctagcaacacaaggtccctgtcctcaaaatcctattcttaatcagca tttctaatttctgccctttgctcattttaatacagagcctgaggataggagagcagcgtggtgaaagaagcaatagttaccacatttgcaaa ggcacataccccaaagagaagtttttaatatgtcacacccatattttatagatggggcaatggaagtccagatgggagaagttatttcag gtgaattatagaaactggatttcaagtttctgataagtattgaatttgggaaggctgtgaacattcttgagcccccctcccaagttcaccttc aacatcctaaagcaggttgaagaggaagatggttccaggtcacttacaagaacaggaacagcccctccctccaaatttgagcccaga aaggagaacctttgttactctagaaaacagtgtgtgtgctattgttttctccataggtcacaaacatccacaagatattggtgattttacatat tattagagccactgaaatttatgatgcaggatattaacgtcaaagaggccaagatgcatcattcagaacactggcaggtcaagcagaaa ccaccgtagtaaaattgaaagctggagtcagcaaagtatagcccacagccaaatctggcccatcccctgttcttataaagttttattggaa cgcagccatgctcatcggtttatgtattatctatggctgtttccaactacagtggcagagctgaatagttgcaaaggaccatagggctatc aaagccccaaatagtcattgtctgacccttcatagaaaaattttgctgaactgtagtctagctccaaggattgttgtatcacctgtgatcgtg cctattaagcaattaacgtcatgtctagtacttagtaatgactcagcatgtatcaattacgatgataaatattatcatggcatccaaaccaaa atactcatgccaacatctctctgtacagaaacatggaaaaagagcgatgctattaaggaggaaaatggagccaggagcaaaacctaa ggctatttctgaactaaagaggcctgaataaggtagtgaaaggaccagggaaagccttcccacggggatggagagccacctcctccc cggctttctggttcagatgtcttgtctcaacagacggcagattcgcagggaagcaggccgagcctgatcttttctccgctagaactgctc aacaggtgaagaatctttttccagcactcctgagcccttcgggtcgcggaacagtgcgaagattattccaatgcctcattcggagaggt gataatctggtctgtggtttctttttcggtggggcatggggtgggggtgagtgtcatgctttctaaggcacagggctgactaaagggtgtc ctatttataagtcagtaaaacacagcggcttcatactctgtgcttattacccagaagccccggctcttagagtttctattaagatgtacctcat aaatatatacgcctcctatgtacccacaaaaattaaaaataaaaaaattgaaatca (SEQ ID NO:l).
[0079] alpha-ketoglutarate-dependent dioxygenase FTO isoform 3 [Homo sapiens]; NCBI
Reference Sequence: NP_00l07390l.l (incorporated by reference): mkrtptaeerereakklrlleeledtwlpyltpkddefyqqwqlkypklilreassvseelhkevqeafltlhkhgclfrdlvriqgkd lltpvsrilignpgctykylntrlftvpwpvkgsnikhteaeiaaacetflklndylqietiqaleelaakekanedavplcmsadfpr vgmgssyngqdevdiksraaynvtllnfmdpqkmpylkeepyfgmgkmavswhhdenlvdrsavavysyscegpeeese ddshlegrdpdiwhvgfkiswdietpglaiplhqgdcyfmlddlnathqhcvlagsqprfssthrvaecstgtldyilqrcqlalqn vcddvdnddvslksfepavlkqgeeihnevefewlrqfwfqgnryrkctdwwcqpmaqlealwkkmegvtnavlhevkre glpveqrneiltailasltarqnlrrewharcqsriartlpadqkpecrpywekddasmplpfdltdivselrgqlleakp (SEQ ID
NO:2).
[0080] A FTO inhibitor may refer to any member of the class of compound or agents having an IC50 of 100 mM or lower concentration for a FTO activity, for example, at least or at most or about 200, 100, 80, 50, 40, 20, 10, 5, 1 pM, 100, 10, 1 nM or lower concentration (or any range or value derivable therefrom) or any compound or agent that inhibits the expression of FTO. Examples of FTO activity or function may include, but not be limited to, dioxygenase activity, enzymatic activity, and/or substrate binding activity. In some embodiments, MTT assay, colony formation assay, invasion assay, apoptosis assay, or cell cycle analysis may be used to test the FTO inhibitors. In some embodiments, the FTO inhibitor comprises IOX3. Other exemplary FTO inhibitors have been described in WO2016206573A1, which is herein incorporated by reference.
[0081] Nucleic acid inhibitors are commercially available. For example, ABM® provides commercially available siRNA FTO inhibitor nucleic acids (Cat. # Ϊ008315).
B. Inhibitory nucleic acids
[0082] Inhibitory nucleic acids or any ways of inhibiting gene expression of a gene are known in the art are contemplated in certain embodiments. Examples of an inhibitory nucleic acid include but are not limited to siRNA (small interfering RNA), short hairpin RNA (shRNA), double-stranded RNA, an antisense oligonucleotide, a ribozyme and a nucleic acid encoding thereof. An inhibitory nucleic acid may inhibit the transcription of a gene or prevent the translation of a gene transcript in a cell. An inhibitory nucleic acid may be from 16 to 1000 nucleotides long, and in certain embodiments from 18 to 100 nucleotides long. The nucleic acid may have nucleotides of at least or at most 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 50, 60,
70, 80, 90 or any range derivable therefrom.
[0083] As used herein,“isolated” means altered or removed from the natural state through human intervention. For example, an siRNA naturally present in a living animal is not “isolated,” but a synthetic siRNA, or an siRNA partially or completely separated from the coexisting materials of its natural state is “isolated.” An isolated siRNA can exist in substantially purified form, or can exist in a non-native environment such as, for example, a cell into which the siRNA has been delivered.
[0084] Inhibitory nucleic acids are well known in the art. For example, siRNA and double- stranded RNA have been described in U.S. Patents 6,506,559 and 6,573,099, as well as in U.S. Patent Publications 2003/0051263, 2003/0055020, 2004/0265839, 2002/0168707,
2003/0159161, and 2004/0064842, all of which are herein incorporated by reference in their entirety.
[0085] Particularly, an inhibitory nucleic acid may be capable of decreasing the expression of UPP2 by at least 10%, 20%, 30%, or 40%, more particularly by at least 50%, 60%, or 70%, and most particularly by at least 75%, 80%, 90%, 95% or more or any range or value in between the foregoing.
[0086] In further embodiments, there are synthetic nucleic acids that are UPP2 inhibitors. An inhibitor may be between 17 to 25 nucleotides in length and comprises a 5’ to 3’ sequence that is at least 90% complementary to the 5’ to 3’ sequence of a mature mRNA. In certain embodiments, an inhibitor molecule is 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides in length, or any range derivable therein. Moreover, an inhibitor molecule has a sequence (from 5’ to 3’) that is or is at least 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, 99.9 or 100% complementary, or any range derivable therein, to the 5’ to 3’ sequence of a mature mRNA, particularly a mature, naturally occurring mRNA. One of skill in the art could use a portion of the probe sequence that is complementary to the sequence of a mature mRNA as the sequence for an mRNA inhibitor. Moreover, that portion of the probe sequence can be altered so that it is still 90% complementary to the sequence of a mature mRNA.
C. Inhibitory antibodies
[0087] In certain embodiments, an antibody or a fragment thereof that binds to at least a portion of the protein and inhibits protein activity; its associated use in treatment of diseases is contemplated in embodiments.
[0088] In some embodiments, the anti-FTO antibody is a monoclonal antibody or a polyclonal antibody. In some embodiments, the antibody is a chimeric antibody, an affinity matured antibody, a humanized antibody, or a human antibody. In some embodiments, the antibody is an antibody fragment. In some embodiments, the antibody is a Fab, Fab', Fab'-SH, F(ab')2, or scFv. In one embodiment, the antibody is a chimeric antibody, for example, an antibody comprising antigen binding sequences from a non-human donor grafted to a heterologous non-human, human or humanized sequence (e.g., framework and/or constant domain sequences). In one embodiment, the non-human donor is a mouse. In one embodiment, an antigen binding sequence is synthetic, e.g., obtained by mutagenesis (e.g., phage display screening, etc.). In one embodiment, a chimeric antibody has murine V regions and human C region. In one embodiment, the murine light chain V region is fused to a human kappa light chain or a human IgGl C region.
[0089] Examples of antibody fragments include, without limitation: (i) the Fab fragment, consisting of VL, VH, CL and CH1 domains; (ii) the "Fd" fragment consisting of the VH and CH1 domains; (iii) the "Fv" fragment consisting of the VL and VH domains of a single antibody; (iv) the "dAb" fragment, which consists of a VH domain; (v) isolated CDR regions; (vi) F(ab')2 fragments, a bivalent fragment comprising two linked Fab fragments; (vii) single chain Fv molecules ("scFv"), wherein a VH domain and a VL domain are linked by a peptide linker which allows the two domains to associate to form a binding domain; (viii) bi-specific single chain Fv dimers (see U.S. Pat. No. 5,091,513) and (ix) diabodies, multivalent or multispecific fragments constructed by gene fusion (U.S. Patent Pub. 2005/0214860). Fv, scFv or diabody molecules may be stabilized by the incorporation of disulphide bridges linking the VH and VL domains. Minibodies comprising a scFv joined to a CH3 domain may also be made (Hu et al, 1996).
[0090] A monoclonal antibody is a single species of antibody wherein every antibody molecule recognizes the same epitope because all antibody producing cells are derived from a single B-lymphocyte cell line. Hybridoma technology involves the fusion of a single B lymphocyte from a mouse previously immunized with a UPP2 antigen with an immortal myeloma cell (usually mouse myeloma). This technology provides a method to propagate a single antibody-producing cell for an indefinite number of generations, such that unlimited quantities of structurally identical antibodies having the same antigen or epitope specificity (monoclonal antibodies) may be produced. However, in therapeutic applications a goal of hybridoma technology is to reduce the immune reaction in humans that may result from administration of monoclonal antibodies generated by the non-human (e.g. mouse) hybridoma cell line.
[0091] Methods have been developed to replace light and heavy chain constant domains of the monoclonal antibody with analogous domains of human origin, leaving the variable regions of the foreign antibody intact. Alternatively, "fully human" monoclonal antibodies are produced in mice transgenic for human immunoglobulin genes. Methods have also been developed to convert variable domains of monoclonal antibodies to more human form by recombinantly constructing antibody variable domains having both rodent and human amino acid sequences. In "humanized" monoclonal antibodies, only the hypervariable CDR is derived from mouse monoclonal antibodies, and the framework regions are derived from human amino acid sequences. It is thought that replacing amino acid sequences in the antibody that are characteristic of rodents with amino acid sequences found in the corresponding position of human antibodies will reduce the likelihood of adverse immune reaction during therapeutic use. A hybridoma or other cell producing an antibody may also be subject to genetic mutation or other changes, which may or may not alter the binding specificity of antibodies produced by the hybridoma.
[0092] It is possible to create engineered antibodies, using monoclonal and other antibodies and recombinant DNA technology to produce other antibodies or chimeric molecules which retain the antigen or epitope specificity of the original antibody, i.e., the molecule has a binding domain. Such techniques may involve introducing DNA encoding the immunoglobulin variable region or the CDRs of an antibody to the genetic material for the framework regions, constant regions, or constant regions plus framework regions, of a different antibody. See, for instance, U.S. Pat. Nos. 5,091,513, and 6,881,557, which are incorporated herein by this reference.
[0093] By known means as described herein, polyclonal or monoclonal antibodies, binding fragments and binding domains and CDRs (including engineered forms of any of the foregoing), may be created that are specific to a protein of interest, one or more of its respective epitopes, or conjugates of any of the foregoing, whether such antigens or epitopes are isolated from natural sources or are synthetic derivatives or variants of the natural compounds.
[0094] Antibodies may be produced from any animal source, including birds and mammals. Particularly, the antibodies may be ovine, murine (e.g., mouse and rat), rabbit, goat, guinea pig, camel, horse, or chicken. In addition, newer technology permits the development of and screening for human antibodies from human combinatorial antibody libraries. For example, bacteriophage antibody expression technology allows specific antibodies to be produced in the absence of animal immunization, as described in U.S. Pat. No. 6,946,546, which is incorporated herein by this reference. These techniques are further described in: Marks (1992); Stemmer (1994); Gram et al. (1992); Barbas et al. (1994); and Schier et al. (1996).
[0095] Methods for producing polyclonal antibodies in various animal species, as well as for producing monoclonal antibodies of various types, including humanized, chimeric, and fully human, are well known in the art. Methods for producing these antibodies are also well known. For example, the following U.S. patents and patent publications provide enabling descriptions of such methods and are herein incorporated by reference: U.S. Patent publication Nos. 2004/0126828 and 2002/0172677; and U.S. Pat. Nos. 3,817,837; 3,850,752; 3,939,350; 3,996,345; 4,196,265; 4,275,149; 4,277,437; 4,366,241; 4,469,797; 4,472,509; 4,606,855;
4,703,003; 4,742,159; 4,767,720; 4,816,567; 4,867,973; 4,938,948; 4,946,778; 5,021,236;
5,164,296; 5,196,066; 5,223,409; 5,403,484; 5,420,253; 5,565,332; 5,571,698; 5,627,052;
5,656,434; 5,770,376; 5,789,208; 5,821,337; 5,844,091; 5,858,657; 5,861,155; 5,871,907;
5,969,108; 6,054,297; 6,165,464; 6,365,157; 6,406,867; 6,709,659; 6,709,873; 6,753,407;
6,814,965; 6,849,259; 6,861,572; 6,875,434; and 6,891,024. All patents, patent publications, and other publications cited herein and therein are hereby incorporated by reference in the present application.
[0096] It is fully expected that antibodies to a protein described herein will have the ability to neutralize or counteract the effects of the protein regardless of the animal species, monoclonal cell line or other source of the antibody. Certain animal species may be less preferable for generating therapeutic antibodies because they may be more likely to cause allergic response due to activation of the complement system through the "Fc" portion of the antibody. However, whole antibodies may be enzymatically digested into "Fc" (complement binding) fragment, and into binding fragments having the binding domain or CDR. Removal of the Fc portion reduces the likelihood that the antigen binding fragment will elicit an undesirable immunological response and, thus, antibodies without Fc may be particularly useful for prophylactic or therapeutic treatments. As described above, antibodies may also be constructed so as to be chimeric, partially or fully human, so as to reduce or eliminate the adverse immunological consequences resulting from administering to an animal an antibody that has been produced in, or has sequences from, other species.
D. Inhibitory small molecules
[0097] As used herein, a“small molecule” refers to an organic compound that is either synthesized via conventional organic chemistry methods (e.g., in a laboratory) or found in nature. Typically, a small molecule is characterized in that it contains several carbon-carbon bonds, and has a molecular weight of less than about 1500 grams/mole. In certain embodiments, small molecules are less than about 1000 grams/mole. In certain embodiments, small molecules are less than about 550 grams/mole. In certain embodiments, small molecules are between about 200 and about 550 grams/mole. In certain embodiments, small molecules exclude peptides (e.g., compounds comprising 2 or more amino acids joined by a peptidyl bond). In certain embodiments, small molecules exclude nucleic acids.
[0098] For example, a small molecule inhibitior may be any small molecules that is determined to inhibit protein function or activity. Such small molecules may be determined based on functional assays in vitro or in vivo.
III. Cancer Staging and Treatments
[0099] Methods and compositions may be provided for treating, prognosing, and/or diagnosing cancer. Based on a biomarker, different treatments may be prescribed or recommended for different cancer patients. . In some embodiments, the patient is diagnosed as having and/or determined to have Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or M0; T4, NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml cancer. In some embodiments, the patient is one that has and/or has been determined to have stage I cancer. In some embodiments, the patient is one that has and/or has been determined to have stage II cancer. In some embodiments, the patient is one that has and/or has been determined to have stage III cancer. In some embodiments, the patient is one that has and/or has been determined to have stage IV cancer. The control may be the expression level of the biomarker in a sample from a patient that has Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or M0; T4, NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml cancer. In some embodiments, the control may be the level of expression of the biomarker from a patient having stage I cancer. In some embodiments, the control may be the level of expression of the biomarker from a patient having stage II cancer. In some embodiments, the control may be the level of expression of the biomarker from a patient having stage III cancer. In some embodiments, the control may be the level of expression of the biomarker from a patient having stage IV cancer.
A. Colorectal Cancer staging
[00100] Colorectal cancer, also known as colon cancer, rectal cancer, or bowel cancer, is a cancer from uncontrolled cell growth in the colon or rectum (parts of the large intestine), or in the appendix. Certain aspects of the methods are provided for patients that are stage I-IV colorectal cancer patients. In particular aspects, the patient is a stage II or III patient. In a further embodiment, the patient is a stage I or II patient. In a further embodiment, the patient is a stage I, II, or III patient. In some embodiments, the patient is diagnosed as having and/or determined to have Tis, NO, and/or M0; Tl, NO, and/or M0; T2, NO, and/or M0; T3, NO, and/or
M0; T4, NO, and/or M0; Tl-2, Nl, and/or M0; T3-4, Nl, and/or M0; any T, N2, and/or M0; or any T, any N, and/or Ml.
[00101] The most common staging system is the TNM (for tumors/nodes/metastases) system, from the American Joint Committee on Cancer (AJCC). The TNM system assigns a number based on three categories.“T” denotes the degree of invasion of the intestinal wall, “N” the degree of lymphatic node involvement, and“M” the degree of metastasis. The broader stage of a cancer is usually quoted as a number I, II, III, IV derived from the TNM value grouped by prognosis; a higher number indicates a more advanced cancer and likely a worse outcome. Details of this system are in the graph below:
AJCC TNM stage TNM stage criteria for colorectal cancer stage
Stage 0 Tis NO M0 Tis: Tumor confined to mucosa; cancer -in-situ
Stage I Tl NO M0 Tl: Tumor invades submucosa
Stage I T2 NO M0 T2: Tumor invades muscularis propria
Stage II-A T3 NO M0 T3: Tumor invades subserosa or beyond (without other organs involved)
Stage II-B T4 NO M0 T4: Tumor invades adjacent organs or perforates the visceral peritoneum Stage III-A T1-2 N1 MO Nl: Metastasis to 1 to 3 regional lymph nodes. Tl or T2. Stage III-B T3-4 Nl MO Nl: Metastasis to 1 to 3 regional lymph nodes. T3 or T4. Stage III-C any T, N2 MO N2: Metastasis to 4 or more regional lymph nodes. Any T. Stage IV any T, any N, Ml: Distant metastases present. Any T, any N.
Ml
B. Therapy
[00102] Methods of the disclosure may include a cancer therapy as described herein. Described herein are additional therapies that may be administered to a patient for use in the methods of the disclosure. It is contemplated that a cancer treatment may exclude any of the cancer treatments described herein. Furthermore, embodiments of the disclosure include patients that have been previously treated for a therapy described herein, are currently being treated for a therapy described herein, or have not been treated for a therapy described herein. In some embodiments, the patient is one that has been determined to be resistant to a therapy described herein. In some embodiments, the patient is one that has been determined to be sensitive to a therapy described herein.
[00103] In some embodiments, the cancer therapy comprises surgical removal of a tumor. This can either be done by an open laparotomy or sometimes laparoscopically. In some embodiments, the cancer therapy comprises chemotherapy. In some embodiments, the chemotherapy is used in a neoadjuvant setting before surgery to shrink the cancer before attempting to remove it (neoadjuvant therapy). The two most common sites of recurrence of colorectal cancer is in the liver and lungs. In some embodiments, the treatment of early colorectal cancer excludes chemotherapy. In further embodiments, the treatment of early colorectal cancer includes neoadjuvant therapy (chemotherapy or radiotherapy before the surgical removal of the primary tumor), but excludes adjuvant therapy (chemotherapy and/or radiotherapy after surgical removal of the primary tumor.
[00104] In both cancer of the colon and rectum, chemotherapy may be used in addition to surgery in certain cases. In rectal cancer, chemotherapy may be used in the neoadjuvant setting.
[00105] In certain embodiments, there may be a decision regarding the therapeutic treatment based on biomarker expression. In some embodiments, the methods include the administration of a chemotherapeutic. In some embodiments, the chemotherapeutic comprises antimetabolites or thymidylate synthase inhibitors such as fluorouracil (5-FU). In some embodiments, the chemotherapeutic comprises cytotoxic drugs, such as irinotecan or oxaliplatin. In some embodiments, the chemotherapeutic comprises combinations such as irinotecan, fluorouracil, and Jeucovorin (FOLFIRI); and oxaliplatin, fluorouracil, and leucovorin (FOLFOX). [00106] In some embodiments, the cancer therapy comprises an antibody. In some embodiments, the cancer therapy comprises Avastin® (bevacizumab) (Genentech Inc., South San Francisco CA) and/or epidermal growth factor receptor Erbitux® (cetuximab) (Imclone Inc. New York City). In some embodiments, the cancer therapy may include one or more of the chemical therapeutic agents including thymidylate synthase inhibitors or antimetabolites such as fluorouracil (5-FU), alone or in combination with other therapeutic agents. For example, in some embodiments, the first treatment to be tested for response therapy may be antimetabolites or thymidylate synthase inhibitors, prodrugs, or salts thereof. .
[00107] Antimetabolites can be used in cancer treatment, as they interfere with DNA production and therefore cell division and the growth of tumors. Because cancer cells spend more time dividing than other cells, inhibiting cell division harms tumor cells more than other cells. Anti-metabolites masquerade as a purine (azathioprine, mercaptopurine) or a pyrimidine, chemicals that become the building-blocks of DNA. They prevent these substances becoming incorporated in to DNA during the S phase (of the cell cycle), stopping normal development and division. They also affect RNA synthesis. However, because thymidine is used in DNA but not in RNA (where uracil is used instead), inhibition of thymidine synthesis via thymidylate synthase selectively inhibits DNA synthesis over RNA synthesis. Due to their efficiency, these drugs are the most widely used cytostatics. In the ATC system, they are classified under L01B. In some embodiments, this treatment regimen is for advanced cancer. In some embodiments, this treatment regimen is excluded for early cancer.
[00108] Thymidylate synthase inhibitors are chemical agents which inhibit the enzyme thymidylate synthase and have potential as an anticancer chemotherapy. As an anti-cancer chemotherapy target, thymidylate synthetase can be inhibited by the thymidylate synthase inhibitors such as fluorinated pyrimidine fluorouracil, or certain folate analogues, the most notable one being raltitrexed (trade name Tomudex). Five agents were in clinical trials in 2002: raltitrexed, pemetrexed, nolatrexed, ZD9331, and GS7904L. Additional non-limiting examples include: Raltitrexed, used for colorectal cancer since 1998; Fluorouracil, used for colorectal cancer; BGC 945; OST7904L.
[00109] In further embodiments, there may be involved prodrugs that can be converted to thymidylate synthase inhibitors in the body, such as Capecitabine (INN), an orally- administered chemotherapeutic agent used in the treatment of numerous cancers. Capecitabine is a prodrug, that is enzymatically converted to 5-fluorouracil in the body. In some embodiments, this treatment regimen is for advanced cancer. In some embodiments, this treatment regimen is excluded for early cancer. [00110] Further chemotherapeutic agents that may be used include capecitabine, fluorouracil, irinotecan, leucovorin, oxaliplatin and UFT. Another type of agent that is sometimes used are the epidermal growth factor receptor inhibitors.
[00111] In certain embodiments, alternative treatments may be prescribed or recommended based on the biomarker profile. In addition to traditional chemotherapy for colorectal cancer patients, cancer therapies also include a variety of combination therapies with both chemical and radiation based treatments. Combination chemotherapies include, for example, cisplatin (CDDP), carboplatin, procarbazine, mechlorethamine, cyclophosphamide, camptothecin, ifosfamide, melphalan, chlorambucil, busulfan, nitrosurea, dactinomycin, daunorubicin, doxorubicin, bleomycin, plicomycin, mitomycin, etoposide (VP 16), tamoxifen, raloxifene, estrogen receptor binding agents, taxol, gemcitabien, navelbine, famesyl-protein tansferase inhibitors, transplatinum, 5-fluorouracil, vincristin, vinblastin and methotrexate, or any analog or derivative variant of the foregoing.
[00112] In people with incurable colorectal cancer, treatment options including palliative care can be considered for improving quality of life. Surgical options may include non-curative surgical removal of some of the cancer tissue, bypassing part of the intestines, or stent placement. These procedures can be considered to improve symptoms and reduce complications such as bleeding from the tumor, abdominal pain and intestinal obstruction. Non-operative methods of symptomatic treatment include radiation therapy to decrease tumor size as well as pain medications. In some embodiments, this treatment regimen is for advanced cancer. In some embodiments, this treatment regimen is excluded for early cancer.
[00113] Immunotherapeutics, generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells. The immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell. The antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing. The antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent. Alternatively, the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target. Various effector cells include cytotoxic T cells and NK cells.
[00114] Immunotherapies that are designed to boost the body’s natural defenses to fight the cancer may also be used. Immunotherapeutics, generally, rely on the use of immune effector cells and molecules to target and destroy cancer cells. The immune effector may be, for example, an antibody specific for some marker on the surface of a tumor cell. The antibody alone may serve as an effector of therapy or it may recruit other cells to actually effect cell killing. The antibody also may be conjugated to a drug or toxin (chemotherapeutic, radionuclide, ricin A chain, cholera toxin, pertussis toxin, etc.) and serve merely as a targeting agent. Alternatively, the effector may be a lymphocyte carrying a surface molecule that interacts, either directly or indirectly, with a tumor cell target. Various effector cells include cytotoxic T cells and NK cells. Immune therapy methods are further described below:
1. Checkpoint Inhibitors and Combination Treatment
[00115] Embodiments of the disclosure may include administration of immune checkpoint inhibitors, which are further described below.
a. PD- 1, PDL1, and PDL2 inhibitors
[00116] PD-l can act in the tumor microenvironment where T cells encounter an infection or tumor. Activated T cells upregulate PD-l and continue to express it in the peripheral tissues. Cytokines such as IFN-gamma induce the expression of PDL1 on epithelial cells and tumor cells. PDL2 is expressed on macrophages and dendritic cells. The main role of PD-l is to limit the activity of effector T cells in the periphery and prevent excessive damage to the tissues during an immune response. Inhibitors of the disclosure may block one or more functions of PD-l and/or PDL1 activity.
[00117] Alternative names for“PD-l” include CD279 and SLEB2. Alternative names for “PDL1” include B7-H1, B7-4, CD274, and B7-H. Alternative names for“PDL2” include B7- DC, Btdc, and CD273. In some embodiments, PD-l, PDL1, and PDL2 are human PD-l, PDL1 and PDL2.
[00118] In some embodiments, the PD-l inhibitor is a molecule that inhibits the binding of PD-l to its ligand binding partners. In a specific aspect, the PD-l ligand binding partners are PDL1 and/or PDL2. In another embodiment, a PDL1 inhibitor is a molecule that inhibits the binding of PDL1 to its binding partners. In a specific aspect, PDL1 binding partners are PD-l and/or B7-1. In another embodiment, the PDL2 inhibitor is a molecule that inhibits the binding of PDL2 to its binding partners. In a specific aspect, a PDL2 binding partner is PD-l. The inhibitor may be an antibody, an antigen binding fragment thereof, an immunoadhesin, a fusion protein, or oligopeptide. Exemplary antibodies are described in U.S. Patent Nos. 8,735,553, 8,354,509, and 8,008,449, all incorporated herein by reference. Other PD-l inhibitors for use in the methods and compositions provided herein are known in the art such as described in U.S. Patent Application Nos. US2014/0294898, US 2014/022021, and US2011/0008369, all incorporated herein by reference. [00119] In some embodiments, the PD-l inhibitor is an anti-PD-l antibody (e.g., a human antibody, a humanized antibody, or a chimeric antibody). In some embodiments, the anti-PD- 1 antibody is selected from the group consisting of nivolumab, pembrolizumab, and pidilizumab. In some embodiments, the PD-l inhibitor is an immunoadhesin (e.g., an immunoadhesin comprising an extracellular or PD-l binding portion of PDL1 or PDL2 fused to a constant region (e.g. , an Fc region of an immunoglobulin sequence). In some embodiments, the PDL1 inhibitor comprises AMP- 224. Nivolumab, also known as MDX- 1106-04, MDX- 1106, ONO-4538, BMS-936558, and OPDIVO®, is an anti-PD-l antibody described in W 02006/121168. Pembrolizumab, also known as MK-3475, Merck 3475, lambrolizumab, KEYTRUDA®, and SCH-900475, is an anti-PD-l antibody described in W02009/114335. Pidilizumab, also known as CT-011, hBAT, or hBAT-l, is an anti-PD-l antibody described in W02009/101611. AMP-224, also known as B7-DCIg, is a PDL2-Fc fusion soluble receptor described in W02010/027827 and WO2011/066342. Additional PD-l inhibitors include MEDI0680, also known as AMP-514, and REGN2810.
[00120] In some embodiments, the immune checkpoint inhibitor is a PDL1 inhibitor such as Durvalumab, also known as MEDI4736, atezolizumab, also known as MPDL3280A, avelumab, also known as MSB00010118C, MDX-1105, BMS-936559, or combinations thereof. In certain aspects, the immune checkpoint inhibitor is a PDL2 inhibitor such as rHIgMl2B7.
[00121] In some embodiments, the inhibitor comprises the heavy and light chain CDRs or VRs of nivolumab, pembrolizumab, or pidilizumab. Accordingly, in one embodiment, the inhibitor comprises the CDR1, CDR2, and CDR3 domains of the VH region of nivolumab, pembrolizumab, or pidilizumab, and the CDR1, CDR2 and CDR3 domains of the VL region of nivolumab, pembrolizumab, or pidilizumab. In another embodiment, the antibody competes for binding with and/or binds to the same epitope on PD-l, PDL1, or PDL2 as the above- mentioned antibodies. In another embodiment, the antibody has at least about 70, 75, 80, 85, 90, 95, 97, or 99% (or any derivable range therein) variable region amino acid sequence identity with the above-mentioned antibodies.
b. CTLA-4, B7-1, and B7-2
[00122] Another immune checkpoint that can be targeted in the methods provided herein is the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), also known as CD 152. The complete cDNA sequence of human CTLA-4 has the Genbank accession number L15006. CTLA-4 is found on the surface of T cells and acts as an“off’ switch when bound to B7-1 (CD80) or B7-2 (CD86) on the surface of antigen-presenting cells. CTLA4 is a member of the immunoglobulin superfamily that is expressed on the surface of Helper T cells and transmits an inhibitory signal to T cells. CTLA4 is similar to the T-cell co-stimulatory protein, CD28, and both molecules bind to B7-1 and B7-2 on antigen-presenting cells. CTLA-4 transmits an inhibitory signal to T cells, whereas CD28 transmits a stimulatory signal. Intracellular CTLA- 4 is also found in regulatory T cells and may be important to their function. T cell activation through the T cell receptor and CD28 leads to increased expression of CTLA-4, an inhibitory receptor for B7 molecules. Inhibitors of the disclosure may block one or more functions of CTLA-4, B7-1, and/or B7-2 activity. In some embodiments, the inhibitor blocks the CTLA-4 and B7-1 interaction. In some embodiments, the inhibitor blocks the CTLA-4 and B7-2 interaction.
[00123] In some embodiments, the immune checkpoint inhibitor is an anti-CTLA-4 antibody ( e.g ., a human antibody, a humanized antibody, or a chimeric antibody), an antigen binding fragment thereof, an immunoadhesin, a fusion protein, or oligopeptide.
[00124] Anti-human-CTLA-4 antibodies (or VH and/or VL domains derived therefrom) suitable for use in the present methods can be generated using methods well known in the art. Alternatively, art recognized anti-CTLA-4 antibodies can be used. For example, the anti- CTLA-4 antibodies disclosed in: US 8,119,129, WO 01/14424, WO 98/42752; WO 00/37504 (CP675,206, also known as tremelimumab; formerly ticilimumab), U.S. Patent No. 6,207,156; Hurwitz el al, 1998; can be used in the methods disclosed herein. The teachings of each of the aforementioned publications are hereby incorporated by reference. Antibodies that compete with any of these art-recognized antibodies for binding to CTLA-4 also can be used. For example, a humanized CTLA-4 antibody is described in International Patent Application No. W 02001/014424, W02000/037504, and U.S. Patent No. 8,017,114; all incorporated herein by reference.
[00125] A further anti-CTLA-4 antibody useful as a checkpoint inhibitor in the methods and compositions of the disclosure is ipilimumab (also known as 10D1, MDX- 010, MDX- 101, and Yervoy®) or antigen binding fragments and variants thereof (see, e.g., WOO 1/14424).
[00126] In some embodiments, the inhibitor comprises the heavy and light chain CDRs or VRs of tremelimumab or ipilimumab. Accordingly, in one embodiment, the inhibitor comprises the CDR1, CDR2, and CDR3 domains of the VH region of tremelimumab or ipilimumab, and the CDR1, CDR2 and CDR3 domains of the VL region of tremelimumab or ipilimumab. In another embodiment, the antibody competes for binding with and/or binds to the same epitope on PD-l, B7-1, or B7-2 as the above- mentioned antibodies. In another embodiment, the antibody has at least about 70, 75, 80, 85, 90, 95, 97, or 99% (or any derivable range therein) variable region amino acid sequence identity with the above-mentioned antibodies.
2. Other immunotherapies
[00127] In some embodiments, the methods comprise administration of a cancer immunotherapy. Cancer immunotherapy (sometimes called immuno-oncology, abbreviated IO) is the use of the immune system to treat cancer. Immunotherapies can be categorized as active, passive or hybrid (active and passive). These approaches exploit the fact that cancer cells often have molecules on their surface that can be detected by the immune system, known as tumour-associated antigens (TAAs); they are often proteins or other macromolecules (e.g. carbohydrates). Active immunotherapy directs the immune system to attack tumor cells by targeting TAAs. Passive immunotherapies enhance existing anti-tumor responses and include the use of monoclonal antibodies, lymphocytes and cytokines. Immumotherapies are known in the art, and some are described below.
a. Inhibition of co- stimulatory molecules
[00128] In some embodiments, the immunotherapy comprises an inhibitor of a co stimulatory molecule. In some embodiments, the inhibitor comprises an inhibitor of B7-1 (CD80), B7-2 (CD86), CD28, ICOS, 0X40 (TNFRSF4), 4-1BB (CD137; TNFRSF9), CD40L (CD40LG), GITR (TNFRSF18), and combinations thereof. Inhibitors include inhibitory antibodies, polypeptides, compounds, and nucleic acids.
b. Dendritic cell therapy
[00129] Dendritic cell therapy provokes anti-tumor responses by causing dendritic cells to present tumor antigens to lymphocytes, which activates them, priming them to kill other cells that present the antigen. Dendritic cells are antigen presenting cells (APCs) in the mammalian immune system. In cancer treatment they aid cancer antigen targeting. One example of cellular cancer therapy based on dendritic cells is sipuleucel-T.
[00130] One method of inducing dendritic cells to present tumor antigens is by vaccination with autologous tumor lysates or short peptides (small parts of protein that correspond to the protein antigens on cancer cells). These peptides are often given in combination with adjuvants (highly immunogenic substances) to increase the immune and anti-tumor responses. Other adjuvants include proteins or other chemicals that attract and/or activate dendritic cells, such as granulocyte macrophage colony- stimulating factor (GM-CSF). [00131] Dendritic cells can also be activated in vivo by making tumor cells express GM- CSF. This can be achieved by either genetically engineering tumor cells to produce GM-CSF or by infecting tumor cells with an oncolytic virus that expresses GM-CSF.
[00132] Another strategy is to remove dendritic cells from the blood of a patient and activate them outside the body. The dendritic cells are activated in the presence of tumor antigens, which may be a single tumor- specific peptide/protein or a tumor cell lysate (a solution of broken down tumor cells). These cells (with optional adjuvants) are infused and provoke an immune response.
[00133] Dendritic cell therapies include the use of antibodies that bind to receptors on the surface of dendritic cells. Antigens can be added to the antibody and can induce the dendritic cells to mature and provide immunity to the tumor. Dendritic cell receptors such as TLR3, TLR7, TLR8 or CD40 have been used as antibody targets.
c. CAR-T cell therapy
[00134] Chimeric antigen receptors (CARs, also known as chimeric immunoreceptors, chimeric T cell receptors or artificial T cell receptors) are engineered receptors that combine a new specificity with an immune cell to target cancer cells. Typically, these receptors graft the specificity of a monoclonal antibody onto a T cell. The receptors are called chimeric because they are fused of parts from different sources. CAR-T cell therapy refers to a treatment that uses such transformed cells for cancer therapy.
[00135] The basic principle of CAR-T cell design involves recombinant receptors that combine antigen-binding and T-cell activating functions. The general premise of CAR-T cells is to artificially generate T-cells targeted to markers found on cancer cells. Scientists can remove T-cells from a person, genetically alter them, and put them back into the patient for them to attack the cancer cells. Once the T cell has been engineered to become a CAR-T cell, it acts as a“living drug”. CAR-T cells create a link between an extracellular ligand recognition domain to an intracellular signalling molecule which in turn activates T cells. The extracellular ligand recognition domain is usually a single-chain variable fragment (scFv). An important aspect of the safety of CAR-T cell therapy is how to ensure that only cancerous tumor cells are targeted, and not normal cells. The specificity of CAR-T cells is determined by the choice of molecule that is targeted.
[00136] Exemplary CAR-T therapies include Tisagenlecleucel (Kymriah) and Axicabtagene ciloleucel (Yescarta). In some embodiments, the CAR-T therapy targets CD 19. d. Cytokine therapy
[00137] Cytokines are proteins produced by many types of cells present within a tumor. They can modulate immune responses. The tumor often employs them to allow it to grow and reduce the immune response. These immune-modulating effects allow them to be used as drugs to provoke an immune response. Two commonly used cytokines are interferons and interleukins.
[00138] Interferons are produced by the immune system. They are usually involved in anti viral response, but also have use for cancer. They fall in three groups: type I (IFNa and IFNP), type II (IFNy) and type III (IFNk).
[00139] Interleukins have an array of immune system effects. IL-2 is an exemplary interleukin cytokine therapy.
e. Adoptive T-cell therapy
[00140] Adoptive T cell therapy is a form of passive immunization by the transfusion of T- cells (adoptive cell transfer). They are found in blood and tissue and usually activate when they find foreign pathogens. Specifically they activate when the T-cell's surface receptors encounter cells that display parts of foreign proteins on their surface antigens. These can be either infected cells, or antigen presenting cells (APCs). They are found in normal tissue and in tumor tissue, where they are known as tumor infiltrating lymphocytes (TILs). They are activated by the presence of APCs such as dendritic cells that present tumor antigens. Although these cells can attack the tumor, the environment within the tumor is highly immunosuppressive, preventing immune-mediated tumour death. [60]
[00141] Multiple ways of producing and obtaining tumour targeted T-cells have been developed. T-cells specific to a tumor antigen can be removed from a tumor sample (TILs) or filtered from blood. Subsequent activation and culturing is performed ex vivo, with the results reinfused. Activation can take place through gene therapy, or by exposing the T cells to tumor antigens.
3. Oncolytic virus
[00142] In some embodiments, the additional therapy comprises an oncolytic virus. An oncolytic virus is a virus that preferentially infects and kills cancer cells. As the infected cancer cells are destroyed by oncolysis, they release new infectious virus particles or virions to help destroy the remaining tumour. Oncolytic viruses are thought not only to cause direct destruction of the tumour cells, but also to stimulate host anti-tumour immune responses for long-term immunotherapy 4. Polysaccharides
[00143] In some embodiments, the additional therapy comprises polysaccharides. Certain compounds found in mushrooms, primarily polysaccharides, can up-regulate the immune system and may have anti-cancer properties. For example, beta-glucans such as lentinan have been shown in laboratory studies to stimulate macrophage, NK cells, T cells and immune system cytokines and have been investigated in clinical trials as immunologic adjuvants.
5. Neoantigens
[00144] In some embodiments, the additional therapy comprises neoantigen administration. Many tumors express mutations. These mutations potentially create new targetable antigens (neoantigens) for use in T cell immunotherapy. The presence of CD8+ T cells in cancer lesions, as identified using RNA sequencing data, is higher in tumors with a high mutational burden. The level of transcripts associated with cytolytic activity of natural killer cells and T cells positively correlates with mutational load in many human tumors.
6. Chemotherapies
[00145] In some embodiments, the additional therapy comprises a chemotherapy. Suitable classes of chemotherapeutic agents include (a) Alkylating Agents, such as nitrogen mustards (e.g., mechlorethamine, cylophosphamide, ifosfamide, melphalan, chlorambucil), ethylenimines and methylmelamines (e.g., hexamethylmelamine, thiotepa), alkyl sulfonates (e.g., busulfan), nitrosoureas (e.g., carmustine, lomustine, chlorozoticin, streptozocin) and triazines (e.g., dicarbazine), (b) Antimetabolites, such as folic acid analogs (e.g., methotrexate), pyrimidine analogs (e.g., 5-fluorouracil, floxuridine, cytarabine, azauridine) and purine analogs and related materials (e.g., 6-mercaptopurine, 6-thioguanine, pentostatin), (c) Natural Products, such as vinca alkaloids (e.g., vinblastine, vincristine), epipodophylotoxins (e.g., etoposide, teniposide), antibiotics (e.g., dactinomycin, daunorubicin, doxorubicin, bleomycin, plicamycin and mitoxanthrone), enzymes (e.g., L-asparaginase), and biological response modifiers (e.g., Interferon- a), and (d) Miscellaneous Agents, such as platinum coordination complexes (e.g., cisplatin, carboplatin), substituted ureas (e.g., hydroxyurea), methylhydiazine derivatives (e.g., procarbazine), and adreocortical suppressants (e.g., taxol and mitotane). In some embodiments, cisplatin is a particularly suitable chemotherapeutic agent.
[00146] Cisplatin has been widely used to treat cancers such as, for example, metastatic testicular or ovarian carcinoma, advanced bladder cancer, head or neck cancer, cervical cancer, lung cancer or other tumors. Cisplatin is not absorbed orally and must therefore be delivered via other routes such as, for example, intravenous, subcutaneous, intratumoral or intraperitoneal injection. Cisplatin can be used alone or in combination with other agents, with efficacious doses used in clinical applications including about 15 mg/m2 to about 20 mg/m2 for 5 days every three weeks for a total of three courses being contemplated in certain embodiments. In some embodiments, the amount of cisplatin delivered to the cell and/or subject in conjunction with the construct comprising an Egr-l promoter operably linked to a polynucleotide encoding the therapeutic polypeptide is less than the amount that would be delivered when using cisplatin alone.
[00147] Other suitable chemotherapeutic agents include antimicrotubule agents, e.g., Paclitaxel (“Taxol”) and doxorubicin hydrochloride (“doxorubicin”). The combination of an Egr-l promoter/TNFa construct delivered via an adenoviral vector and doxorubicin was determined to be effective in overcoming resistance to chemotherapy and/or TNF-a, which suggests that combination treatment with the construct and doxorubicin overcomes resistance to both doxorubicin and TNF-a.
[00148] Doxorubicin is absorbed poorly and is preferably administered intravenously. In certain embodiments, appropriate intravenous doses for an adult include about 60 mg/m2 to about 75 mg/m2 at about 2l-day intervals or about 25 mg/m2 to about 30 mg/m2 on each of 2 or 3 successive days repeated at about 3 week to about 4 week intervals or about 20 mg/m2 once a week. The lowest dose should be used in elderly patients, when there is prior bone- marrow depression caused by prior chemotherapy or neoplastic marrow invasion, or when the drug is combined with other myelopoietic suppressant drugs.
[00149] Nitrogen mustards are another suitable chemotherapeutic agent useful in the methods of the disclosure. A nitrogen mustard may include, but is not limited to, mechlorethamine (HN2), cyclophosphamide and/or ifosfamide, melphalan (L-sarcolysin), and chlorambucil. Cyclophosphamide (CYTOXAN®) is available from Mead Johnson and NEOSTAR® is available from Adria), is another suitable chemotherapeutic agent. Suitable oral doses for adults include, for example, about 1 mg/kg/day to about 5 mg/kg/day, intravenous doses include, for example, initially about 40 mg/kg to about 50 mg/kg in divided doses over a period of about 2 days to about 5 days or about 10 mg/kg to about 15 mg/kg about every 7 days to about 10 days or about 3 mg/kg to about 5 mg/kg twice a week or about 1.5 mg/kg/day to about 3 mg/kg/day. Because of adverse gastrointestinal effects, the intravenous route is preferred. The drug also sometimes is administered intramuscularly, by infiltration or into body cavities.
[00150] Additional suitable chemotherapeutic agents include pyrimidine analogs, such as cytarabine (cytosine arabinoside), 5-fluorouracil (fluouracil; 5-FU) and floxuridine (fluorode- oxyuridine; FudR). 5-FU may be administered to a subject in a dosage of anywhere between about 7.5 to about 1000 mg/m2. Further, 5-FU dosing schedules may be for a variety of time periods, for example up to six weeks, or as determined by one of ordinary skill in the art to which this disclosure pertains.
[00151] Gemcitabine diphosphate (GEMZAR®, Eli Lilly & Co.,“gemcitabine”), another suitable chemotherapeutic agent, is recommended for treatment of advanced and metastatic pancreatic cancer, and will therefore be useful in the present disclosure for these cancers as well.
[00152] The amount of the chemotherapeutic agent delivered to the patient may be variable. In one suitable embodiment, the chemotherapeutic agent may be administered in an amount effective to cause arrest or regression of the cancer in a host, when the chemotherapy is administered with the construct. In other embodiments, the chemotherapeutic agent may be administered in an amount that is anywhere between 2 to 10,000 fold less than the chemotherapeutic effective dose of the chemotherapeutic agent. For example, the chemotherapeutic agent may be administered in an amount that is about 20 fold less, about 500 fold less or even about 5000 fold less than the chemotherapeutic effective dose of the chemotherapeutic agent. The chemotherapeutic s of the disclosure can be tested in vivo for the desired therapeutic activity in combination with the construct, as well as for determination of effective dosages. For example, such compounds can be tested in suitable animal model systems prior to testing in humans, including, but not limited to, rats, mice, chicken, cows, monkeys, rabbits, etc. In vitro testing may also be used to determine suitable combinations and dosages, as described in the examples.
7. Radiotherapy
[00153] In some embodiments, the additional therapy or prior therapy comprises radiation, such as ionizing radiation. As used herein,“ionizing radiation” means radiation comprising particles or photons that have sufficient energy or can produce sufficient energy via nuclear interactions to produce ionization (gain or loss of electrons). An exemplary and preferred ionizing radiation is an x-radiation. Means for delivering x-radiation to a target tissue or cell are well known in the art.
[00154] In some embodiments, the amount of ionizing radiation is greater than 20 Gy and is administered in one dose. In some embodiments, the amount of ionizing radiation is 18 Gy and is administered in three doses. In some embodiments, the amount of ionizing radiation is at least, at most, or exactly 2, 4, 6, 8, 10, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 18, 19, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 40 Gy (or any derivable range therein). In some embodiments, the ionizing radiation is administered in at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 does (or any derivable range therein). When more than one dose is administered, the does may be about 1, 4, 8, 12, or 24 hours or 1, 2, 3, 4, 5, 6, 7, or 8 days or 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, or 16 weeks apart, or any derivable range therein.
[00155] In some embodiments, the amount of IR may be presented as a total dose of IR, which is then administered in fractionated doses. For example, in some embodiments, the total dose is 50 Gy administered in 10 fractionated doses of 5 Gy each. In some embodiments, the total dose is 50-90 Gy, administered in 20-60 fractionated doses of 2-3 Gy each. In some embodiments, the total dose of IR is at least, at most, or about 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120,
125, 130, 135, 140, or 150 (or any derivable range therein). In some embodiments, the total dose is administered in fractionated doses of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 20, 25, 30, 35, 40, 45, or 50 Gy (or any derivable range therein. In some embodiments, at least, at most, or exactly 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93,
94, 95, 96, 97, 98, 99, or 100 fractionated doses are administered (or any derivable range therein). In some embodiments, at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 (or any derivable range therein) fractionated doses are administered per day. In some embodiments, at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 (or any derivable range therein) fractionated doses are administered per week.
8. Surgery
[00156] Approximately 60% of persons with cancer will undergo surgery of some type, which includes preventative, diagnostic or staging, curative, and palliative surgery. Curative surgery includes resection in which all or part of cancerous tissue is physically removed, excised, and/or destroyed and may be used in conjunction with other therapies, such as the treatment of the present embodiments, chemotherapy, radiotherapy, hormonal therapy, gene therapy, immunotherapy, and/or alternative therapies. Tumor resection refers to physical removal of at least part of a tumor. In addition to tumor resection, treatment by surgery includes laser surgery, cryosurgery, electrosurgery, and microscopically-controlled surgery (Mohs’ surgery).
[00157] Upon excision of part or all of cancerous cells, tissue, or tumor, a cavity may be formed in the body. Treatment may be accomplished by perfusion, direct injection, or local application of the area with an additional anti-cancer therapy. Such treatment may be repeated, for example, every 1, 2, 3, 4, 5, 6, or 7 days, or every 1, 2, 3, 4, and 5 weeks or every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months. These treatments may be of varying dosages as well.
9. Other Agents
[00158] It is contemplated that other agents may be used in combination with certain aspects of the present embodiments to improve the therapeutic efficacy of treatment. These additional agents include agents that affect the upregulation of cell surface receptors and GAP junctions, cytostatic and differentiation agents, inhibitors of cell adhesion, agents that increase the sensitivity of the hyperproliferative cells to apoptotic inducers, or other biological agents. Increases in intercellular signaling by elevating the number of GAP junctions would increase the anti-hyperproliferative effects on the neighboring hyperproliferative cell population. In other embodiments, cytostatic or differentiation agents can be used in combination with certain aspects of the present embodiments to improve the anti-hyperproliferative efficacy of the treatments. Inhibitors of cell adhesion are contemplated to improve the efficacy of the present embodiments. Examples of cell adhesion inhibitors are focal adhesion kinase (FAKs) inhibitors and Lovastatin. It is further contemplated that other agents that increase the sensitivity of a hyperproliferative cell to apoptosis, such as the antibody c225, could be used in combination with certain aspects of the present embodiments to improve the treatment efficacy.
C. Monitoring
[00159] In certain aspects, the methods of the disclosure may be combined with one or more other colon cancer diagnosis or screening tests at increased frequency if the patient is determined to be at high risk for recurrence or have a poor prognosis based on the biomarker described above.
[00160] The colon monitoring may include any methods known in the art. In particular, the monitoring include obtaining a sample and testing the sample for diagnosis. For example, the colon monitoring may include colonoscopy or coloscopy, which is the endoscopic examination of the large bowel and the distal part of the small bowel with a CCD camera or a fiber optic camera on a flexible tube passed through the anus. It can provide a visual diagnosis (e.g. ulceration, polyps) and grants the opportunity for biopsy or removal of suspected colorectal cancer lesions. Thus, colonoscopy or coloscopy can be used for treatment.
[00161] In further aspects, the monitoring diagnosis may include sigmoidoscopy, which is similar to colonoscopy— the difference being related to which parts of the colon each can examine. A colonoscopy allows an examination of the entire colon (1200-1500 mm in length). A sigmoidoscopy allows an examination of the distal portion (about 600 mm) of the colon, which may be sufficient because benefits to cancer survival of colonoscopy have been limited to the detection of lesions in the distal portion of the colon. A sigmoidoscopy is often used as a screening procedure for a full colonoscopy, often done in conjunction with a fecal occult blood test (FOBT). About 5% of these screened patients are referred to colonoscopy.
[00162] In additional aspects, the monitoring diagnosis may include virtual colonoscopy, which uses 2D and 3D imagery reconstructed from computed tomography (CT) scans or from nuclear magnetic resonance (MR) scans, as a totally non-invasive medical test.
[00163] The monitoring include the use of one or more screening tests for colon cancer including, but not limited to fecal occult blood testing, flexible sigmoidoscopy and colonoscopy. Of the three, only sigmoidoscopy cannot screen the right side of the colon where 42% of malignancies are found. Virtual colonoscopy via a CT scan appears as good as standard colonoscopy for detecting cancers and large adenomas but is expensive, associated with radiation exposure, and cannot remove any detected abnormal growths like standard colonoscopy can. Fecal occult blood testing (FOBT) of the stool is typically recommended every two years and can be either guaiac based or immunochemical. Annual FOBT screening results in a 16% relative risk reduction in colorectal cancer mortality, but no difference in all cause mortality. The M2-PK test identifies an enzyme in colorectal cancers and polyps rather than blood in the stool. It does not require any special preparation prior to testing. M2-PK is sensitive for colorectal cancer and polyps and is able to detect bleeding and non-bleeding colorectal cancer and polyps. In the event of a positive result people would be asked to undergo further examination e.g. colonoscopy.
IV. ROC analysis
[00164] In statistics, a receiver operating characteristic (ROC), or ROC curve, is a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate against the false positive rate at various threshold settings. (The true-positive rate is also known as sensitivity in biomedical informatics, or recall in machine learning. The false-positive rate is also known as the fall-out and can be calculated as 1 - specificity). The ROC curve is thus the sensitivity as a function of fall-out. In general, if the probability distributions for both detection and false alarm are known, the ROC curve can be generated by plotting the cumulative distribution function (area under the probability distribution from -infinity to + infinity) of the detection probability in the y- axis versus the cumulative distribution function of the false-alarm probability in x-axis.
[00165] ROC analysis provides tools to select possibly optimal models and to discard suboptimal ones independently from (and prior to specifying) the cost context or the class distribution. ROC analysis is related in a direct and natural way to cost/benefit analysis of diagnostic decision making. ROC analysis provides a tool for creating cut-off values to partition patient populations into high expression and low expression of certain biomarkers.
[00166] The ROC is also known as a relative operating characteristic curve, because it is a comparison of two operating characteristics (TPR and FPR) as the criterion changes. ROC analysis curves are known in the art and described in Metz CE (1978) Basic principles of ROC analysis. Seminars in Nuclear Medicine 8:283-298; Youden WJ (1950) An index for rating diagnostic tests. Cancer 3:32-35; Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry 39:561-577; and Greiner M, Pfeiffer D, Smith RD (2000) Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Preventive Veterinary Medicine 45:23-41, which are herein incorporated by reference in their entirety.
V. Sample Preparation
[00167] In certain aspects, methods involve obtaining a sample from a subject. The methods of obtaining provided herein may include methods of biopsy such as fine needle aspiration, core needle biopsy, vacuum assisted biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy or skin biopsy. In certain embodiments the sample is obtained from a biopsy from esophageal tissue by any of the biopsy methods previously mentioned. In other embodiments the sample may be obtained from any of the tissues provided herein that include but are not limited to non-cancerous or cancerous tissue and non-cancerous or cancerous tissue from the serum, gall bladder, mucosal, skin, heart, lung, breast, pancreas, blood, liver, muscle, kidney, smooth muscle, bladder, colon, intestine, brain, prostate, esophagus, or thyroid tissue. Alternatively, the sample may be obtained from any other source including but not limited to blood, sweat, hair follicle, buccal tissue, tears, menses, feces, or saliva. In certain aspects of the current methods, any medical professional such as a doctor, nurse or medical technician may obtain a biological sample for testing. Yet further, the biological sample can be obtained without the assistance of a medical professional.
[00168] A sample may include but is not limited to, tissue, cells, or biological material from cells or derived from cells of a subject. The biological sample may be a heterogeneous or homogeneous population of cells or tissues. The biological sample may be obtained using any method known to the art that can provide a sample suitable for the analytical methods described herein. The sample may be obtained by non-invasive methods including but not limited to: scraping of the skin or cervix, swabbing of the cheek, saliva collection, urine collection, feces collection, collection of menses, tears, or semen.
[00169] The sample may be obtained by methods known in the art. In certain embodiments the samples are obtained by biopsy. In other embodiments the sample is obtained by swabbing, endoscopy, scraping, phlebotomy, or any other methods known in the art. In some cases, the sample may be obtained, stored, or transported using components of a kit of the present methods. In some cases, multiple samples, such as multiple esophageal samples may be obtained for diagnosis by the methods described herein. In other cases, multiple samples, such as one or more samples from one tissue type (for example esophagus) and one or more samples from another specimen (for example serum) may be obtained for diagnosis by the methods. In some cases, multiple samples such as one or more samples from one tissue type (e.g. esophagus) and one or more samples from another specimen (e.g. serum) may be obtained at the same or different times. Samples may be obtained at different times are stored and/or analyzed by different methods. For example, a sample may be obtained and analyzed by routine staining methods or any other cytological analysis methods.
[00170] In some embodiments the biological sample may be obtained by a physician, nurse, or other medical professional such as a medical technician, endocrinologist, cytologist, phlebotomist, radiologist, or a pulmonologist. The medical professional may indicate the appropriate test or assay to perform on the sample. In certain aspects a molecular profiling business may consult on which assays or tests are most appropriately indicated. In further aspects of the current methods, the patient or subject may obtain a biological sample for testing without the assistance of a medical professional, such as obtaining a whole blood sample, a urine sample, a fecal sample, a buccal sample, or a saliva sample.
[00171] In other cases, the sample is obtained by an invasive procedure including but not limited to: biopsy, needle aspiration, endoscopy, or phlebotomy. The method of needle aspiration may further include fine needle aspiration, core needle biopsy, vacuum assisted biopsy, or large core biopsy. In some embodiments, multiple samples may be obtained by the methods herein to ensure a sufficient amount of biological material.
[00172] General methods for obtaining biological samples are also known in the art. Publications such as Ramzy, Ibrahim Clinical Cytopathology and Aspiration Biopsy 2001, which is herein incorporated by reference in its entirety, describes general methods for biopsy and cytological methods. In one embodiment, the sample is a fine needle aspirate of a esophageal or a suspected esophageal tumor or neoplasm. In some cases, the fine needle aspirate sampling procedure may be guided by the use of an ultrasound, X-ray, or other imaging device.
[00173] In some embodiments of the present methods, the molecular profiling business may obtain the biological sample from a subject directly, from a medical professional, from a third party, or from a kit provided by a molecular profiling business or a third party. In some cases, the biological sample may be obtained by the molecular profiling business after the subject, a medical professional, or a third party acquires and sends the biological sample to the molecular profiling business. In some cases, the molecular profiling business may provide suitable containers, and excipients for storage and transport of the biological sample to the molecular profiling business.
[00174] In some embodiments of the methods described herein, a medical professional need not be involved in the initial diagnosis or sample acquisition. An individual may alternatively obtain a sample through the use of an over the counter (OTC) kit. An OTC kit may contain a means for obtaining said sample as described herein, a means for storing said sample for inspection, and instructions for proper use of the kit. In some cases, molecular profiling services are included in the price for purchase of the kit. In other cases, the molecular profiling services are billed separately. A sample suitable for use by the molecular profiling business may be any material containing tissues, cells, nucleic acids, genes, gene fragments, expression products, gene expression products, or gene expression product fragments of an individual to be tested. Methods for determining sample suitability and/or adequacy are provided.
[00175] In some embodiments, the subject may be referred to a specialist such as an oncologist, surgeon, or endocrinologist. The specialist may likewise obtain a biological sample for testing or refer the individual to a testing center or laboratory for submission of the biological sample. In some cases the medical professional may refer the subject to a testing center or laboratory for submission of the biological sample. In other cases, the subject may provide the sample. In some cases, a molecular profiling business may obtain the sample. VI. Evaluating Levels of Methylation of Biomarkers
[00176] In certain aspects a meta-analysis of expression or activity can be performed. In statistics, a meta-analysis combines the results of several studies that address a set of related research hypotheses. This is normally done by identification of a common measure of effect size, which is modeled using a form of meta-regression. Generally, three types of models can be distinguished in the literature on meta- analysis: simple regression, fixed effects meta regression and random effects meta-regression. Resulting overall averages when controlling for study characteristics can be considered meta-effect sizes, which are more powerful estimates of the true effect size than those derived in a single study under a given single set of assumptions and conditions. A meta-gene expression value, in this context, is to be understood as being the median of the normalized expression of a biomarker gene or activity. Normalization of the expression of a biomarker gene is preferably achieved by dividing the expression level of the individual marker gene to be normalized by the respective individual median expression of this marker genes, wherein said median expression is preferably calculated from multiple measurements of the respective gene in a sufficiently large cohort of test individuals. The test cohort preferably comprises at least 3, 10, 100, 200, 1000 individuals or more including all values and ranges thereof. Dataset- specific bias can be removed or minimized allowing multiple datasets to be combined for meta-analyses (See Sims et al. BMC Medical Genomics (1:42), 1-14, 2008, which is incorporated herein by reference in its entirety).
[00177] The calculation of a meta-gene expression value is performed by: (i) determining the gene expression value of at least two, preferably more genes (ii) "normalizing" the gene expression value of each individual gene by dividing the expression value with a coefficient which is approximately the median expression value of the respective gene in a representative breast cancer cohort (iii) calculating the median of the group of normalized gene expression values.
[00178] A gene shall be understood to be specifically expressed in a certain cell type if the expression level of the gene in the cell type is at least about 2-fold, 5-fold, lO-fold, lOO-fold, 1000-fold, or 10000-fold higher (or any range derivable therein) than in a reference cell type, or in a mixture of reference cell types. Reference cell types include non-cancerous tissue cells or a heterogenous population of cancers.
[00179] In certain algorithms a suitable threshold level is first determined for a marker gene. The suitable threshold level can be determined from measurements of the marker gene expression in multiple individuals from a test cohort. The median expression of the marker gene in said multiple expression measurements is taken as the suitable threshold value.
[00180] Comparison of multiple marker genes with a threshold level can be performed as follows: 1. The individual marker genes are compared to their respective threshold levels. 2. The number of marker genes, the expression level of which is above their respective threshold level, is determined. 3. If a marker genes is expressed above its respective threshold level, then the expression level of the marker gene is taken to be "above the threshold level".
[00181] Some embodiments include determining that a measured expression level is higher than, lower than, increased relative to, decreased relative to, equal to, or within a predetermined amount of a reference expression level. In some embodiments, a higher, lower, increased, or decreased expression level is at least 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 50, 100, 150, 200, 250, 500, or 1000 fold (or any derivable range therein) or at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, or 900% different than the reference level, or any derivable range therein. These values may represent a predetermined threshold level, and some embodiments include determining that the measured expression level is higher by a predetermined amount or lower by a predetermined amount than a reference level. In some embodiments, a level of expression may be qualified as“low” or “high,” which indicates the patient expresses a certain gene or miRNA at a level relative to a reference level or a level with a range of reference levels that are determined from multiple samples meeting particular criteria. The level or range of levels in multiple control samples is an example of this. In some embodiments, that certain level or a predetermined threshold value is at, below, or above 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,
98, 99, 100 percentile, or any range derivable therein. Moreover, a threshold level may be derived from a cohort of individuals meeting a particular criteria. The number in the cohort may be, be at least, or be at most 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 441, 450, 460, 470, 480, 490, 500, 510,
520, 530, 540, 550, 560, 570, 580, 590, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400,
1500, 1600, 1700, 1800, 1900, 2000 or more (or any range derivable therein). A measured expression level can be considered equal to a reference expression level if it is within a certain amount of the reference expression level, and such amount may be an amount that is predetermined. This can be the case, for example, when a classifier is used to identify the molecular subtype of a metastasis. The predetermined amount may be within 0.1, 0.2, 0.3, 0.4,
0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
23, 24, 25, 30, 35, 40, 45, or 50% of the reference level, or any range derivable therein.
[00182] For any comparison of gene or miRNA expression levels to a mean expression levels or a reference expression levels, the comparison is to be made on a gene -by-gene and miRNA- by-miRNA basis. For example, if the expression levels of gene A, gene B, and miRNA X in a patient’s cancerous sample are measured, a comparison to mean expression levels in cancerous samples of a cohort of patients would involve: comparing the expression level of gene A in the patient’s cancerous sample with the mean expression level of gene A in cancerous samples of the cohort of patients, comparing the expression level of gene B in the patient’s sample with the mean expression level of gene B in samples of the cohort of patients, and comparing the expression level of miRNA X in the patient’s metastasis with the mean expression level of miRNA X in cancerous samples of the cohort of patients. Comparisons that involve determining whether the expression level measured in a patient’s sample is within a predetermined amount of a mean expression level or reference expression level are similarly done on a gene-by-gene and miRNA-by-miRNA basis, as applicable.
VII. Nucleic Acid Assays
[00183] Aspects of the methods include assaying nucleic acids to determine expression levels. Arrays can be used to detect differences between two samples. Specifically contemplated applications include identifying and/or quantifying differences between biomarkers from a sample that is normal and from a sample that is not normal, between a cancerous condition and a non-cancerous condition, or between two differently treated samples. Also, biomarkers may be compared between a sample believed to be susceptible to a particular disease or condition and one believed to be not susceptible or resistant to that disease or condition. A sample that is not normal is one exhibiting phenotypic trait(s) of a disease or condition or one believed to be not normal with respect to that disease or condition. It may be compared to a cell that is normal with respect to that disease or condition. Phenotypic traits include symptoms of, or susceptibility to, a disease or condition of which a component is or may or may not be genetic or caused by a hyperproliferative or neoplastic cell or cells.
[00184] An array comprises a solid support with nucleic acid probes attached to the support. Arrays typically comprise a plurality of different nucleic acid probes that are coupled to a surface of a substrate in different, known locations. These arrays, also described as "microarrays" or colloquially "chips" have been generally described in the art, for example, U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195, 6,040,193, 5,424,186 and Fodor et al., 1991), each of which is incorporated by reference in its entirety for all purposes. Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, e.g., U.S. Pat. No. 5,384,261, incorporated herein by reference in its entirety for all purposes. Although a planar array surface is used in certain aspects, the array may be fabricated on a surface of virtually any shape or even a multiplicity of surfaces. Arrays may be nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate, see U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992, which are hereby incorporated in their entirety for all purposes.
[00185] In addition to the use of arrays and microarrays, it is contemplated that a number of difference assays could be employed to analyze biomarkers, their activities, and their effects. Such assays include, but are not limited to, nucleic amplification, polymerase chain reaction, quantitative PCR, RT-PCR, in situ hybridization, Northern hybridization, hybridization protection assay (HPA)(GenProbe), branched DNA (bDNA) assay (Chiron), rolling circle amplification (RCA), single molecule hybridization detection (US Genomics), Invader assay (ThirdWave Technologies), and/or Bridge Litigation Assay (Genaco).
VIII. Administration of Therapeutic Compositions
[00186] The therapy provided herein may comprise administration of a combination of therapeutic agents, such as a first cancer therapy and a second cancer therapy. The therapies may be administered in any suitable manner known in the art. For example, the first and second cancer treatment may be administered sequentially (at different times) or concurrently (at the same time). In some embodiments, the first and second cancer treatments are administered in a separate composition. In some embodiments, the first and second cancer treatments are in the same composition.
[00187] Embodiments of the disclosure relate to compositions and methods comprising therapeutic compositions. The different therapies may be administered in one composition or in more than one composition, such as 2 compositions, 3 compositions, or 4 compositions. Various combinations of the agents may be employed, for example, a first cancer treatment is “A” and a second cancer treatment is“B”:
A/B/A B/A/B B/B/A A/A/B A/B/B B/A/A A/B/B/B B/A/B/B
B/B/B/A B/B/A/B A/A/B/B A/B/A/B A/B/B/A B/B/A/A
B/A/B/A B/A/A/B A/A/A/B B/A/A/A A/B/A/A A/A/B/A [00188] The therapeutic agents of the disclosure may be administered by the same route of administration or by different routes of administration. In some embodiments, the cancer therapy is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally. In some embodiments, the antibiotic is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally. The appropriate dosage may be determined based on the type of disease to be treated, severity and course of the disease, the clinical condition of the individual, the individual's clinical history and response to the treatment, and the discretion of the attending physician.
[00189] The treatments may include various“unit doses.” Unit dose is defined as containing a predetermined-quantity of the therapeutic composition. The quantity to be administered, and the particular route and formulation, is within the skill of determination of those in the clinical arts. A unit dose need not be administered as a single injection but may comprise continuous infusion over a set period of time. In some embodiments, a unit dose comprises a single administrable dose.
[00190] The quantity to be administered, both according to number of treatments and unit dose, depends on the treatment effect desired. An effective dose is understood to refer to an amount necessary to achieve a particular effect. In the practice in certain embodiments, it is contemplated that doses in the range from 10 mg/kg to 200 mg/kg can affect the protective capability of these agents. Thus, it is contemplated that doses include doses of about 0.1, 0.5,
1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, and 200, 300, 400,
500, 1000 pg/kg, mg/kg, pg/day, or mg/day or any range derivable therein. Furthermore, such doses can be administered at multiple times during a day, and/or on multiple days, weeks, or months.
[00191] In certain embodiments, the effective dose of the pharmaceutical composition is one which can provide a blood level of about 1 mM to 150 mM. In another embodiment, the effective dose provides a blood level of about 4 mM to 100 mM.; or about 1 mM to 100 mM; or about 1 mM to 50 mM; or about 1 mM to 40 mM; or about 1 mM to 30 mM; or about 1 mM to 20 mM; or about 1 mM to 10 mM; or about 10 mM to 150 mM; or about 10 mM to 100 mM; or about 10 mM to 50 mM; or about 25 mM to 150 mM; or about 25 mM to 100 mM; or about 25 mM to 50 pM; or about 50 pM to 150 pM; or about 50 pM to 100 pM (or any range derivable therein). In other embodiments, the dose can provide the following blood level of the agent that results from a therapeutic agent being administered to a subject: about, at least about, or at most about
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78,
79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 mM or any range derivable therein. In certain embodiments, the therapeutic agent that is administered to a subject is metabolized in the body to a metabolized therapeutic agent, in which case the blood levels may refer to the amount of that agent. Alternatively, to the extent the therapeutic agent is not metabolized by a subject, the blood levels discussed herein may refer to the unmetabolized therapeutic agent.
[00192] Precise amounts of the therapeutic composition also depend on the judgment of the practitioner and are peculiar to each individual. Factors affecting dose include physical and clinical state of the patient, the route of administration, the intended goal of treatment (alleviation of symptoms versus cure) and the potency, stability and toxicity of the particular therapeutic substance or other therapies a subject may be undergoing.
[00193] It will be understood by those skilled in the art and made aware that dosage units of pg/kg or mg/kg of body weight can be converted and expressed in comparable concentration units of pg/ml or mM (blood levels), such as 4 pM to 100 pM. It is also understood that uptake is species and organ/tissue dependent. The applicable conversion factors and physiological assumptions to be made concerning uptake and concentration measurement are well-known and would permit those of skill in the art to convert one concentration measurement to another and make reasonable comparisons and conclusions regarding the doses, efficacies and results described herein.
IX. Methods of the Disclosure
[00194] In the embodiments of the disclosure, methods include treating cancer, treating a patient determined to have cancer, prognosing cancer, diagnosing cancer, and controls with a sample from a cancerous tissue.
[00195] The cancer may be any cancer listed herein. In some embodiments, the cancer comprises epithelial cancer, (e.g., breast, gastrointestinal, lung), prostate cancer, bladder cancer, lung (e.g., small cell lung) cancer, colon cancer, ovarian cancer, brain cancer, gastric cancer, renal cell carcinoma, pancreatic cancer, liver cancer, esophageal cancer, head and neck cancer, or a colorectal cancer. In some embodiments, the cancer comprises adenocortical carcinoma, agnogenic myeloid metaplasia, AIDS-related cancers (e.g., AIDS-related lymphoma), anal cancer, appendix cancer, astrocytoma (e.g., cerebellar and cerebral), basal cell carcinoma, bile duct cancer (e.g., extrahepatic), bladder cancer, bone cancer, (osteosarcoma and malignant fibrous histiocytoma), brain tumor (e.g., glioma, brain stem glioma, cerebellar or cerebral astrocytoma (e.g., pilocytic astrocytoma, diffuse astrocytoma, anaplastic (malignant) astrocytoma), malignant glioma, ependymoma, oligodenglioma, meningioma, meningiosarcoma, craniopharyngioma, haemangioblastomas, medulloblastoma, supratentorial primitive neuroectodermal tumors, visual pathway and hypothalamic glioma, and glioblastoma), breast cancer, bronchial adenomas/carcinoids, carcinoid tumor (e.g., gastrointestinal carcinoid tumor), carcinoma of unknown primary, central nervous system lymphoma, cervical cancer, colon cancer, colorectal cancer, chronic myeloproliferative disorders, endometrial cancer (e.g., uterine cancer), ependymoma, esophageal cancer, Ewing's family of tumors, eye cancer (e.g., intraocular melanoma and retinoblastoma), gallbladder cancer, gastric (stomach) cancer, gastrointestinal carcinoid tumor, gastrointestinal stromal tumor (GIST), germ cell tumor, (e.g., extracranial, extragonadal, ovarian), gestational trophoblastic tumor, head and neck cancer, hepatocellular (liver) cancer (e.g., hepatic carcinoma and heptoma), hypopharyngeal cancer, islet cell carcinoma (endocrine pancreas), laryngeal cancer, laryngeal cancer, leukemia, lip and oral cavity cancer, oral cancer, liver cancer, lung cancer (e.g., small cell lung cancer, non-small cell lung cancer, adenocarcinoma of the lung, and squamous carcinoma of the lung), lymphoid neoplasm (e.g., lymphoma), medulloblastoma, ovarian cancer, mesothelioma, metastatic squamous neck cancer, mouth cancer, multiple endocrine neoplasia syndrome, myelodysplastic syndromes, myelodysplastic/myeloproliferative diseases, nasal cavity and paranasal sinus cancer, nasopharyngeal cancer, neuroblastoma, neuroendocrine cancer, oropharyngeal cancer, ovarian cancer (e.g., ovarian epithelial cancer, ovarian germ cell tumor, ovarian low malignant potential tumor), pancreatic cancer, parathyroid cancer, penile cancer, cancer of the peritoneal, pharyngeal cancer, pheochromocytoma, pineoblastoma and supratentorial primitive neuroectodermal tumors, pituitary tumor, pleuropulmonary blastoma, lymphoma, primary central nervous system lymphoma (microglioma), pulmonary lymphangiomyomatosis, rectal cancer, renal cancer, renal pelvis and ureter cancer (transitional cell cancer), rhabdomyosarcoma, salivary gland cancer, skin cancer (e.g., non-melanoma (e.g., squamous cell carcinoma), melanoma, and Merkel cell carcinoma), small intestine cancer, squamous cell cancer, testicular cancer, throat cancer, thymoma and thymic carcinoma, thyroid cancer, tuberous sclerosis, urethral cancer, vaginal cancer, vulvar cancer, Wilms' tumor, and post transplant lymphoproliferative disorder (PTLD), abnormal vascular proliferation associated with phakomatoses, edema (such as that associated with brain tumors), or Meigs' syndrome.
X. Kits
[00196] Certain aspects of the present invention also concern kits containing compositions of the invention or compositions to implement methods of the invention. In some embodiments, kits can be used to evaluate one or more biomarker molecules. In certain embodiments, a kit contains, contains at least or contains at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 100, 500, 1,000 or more probes, synthetic molecules or inhibitors, or any value or range and combination derivable therein. In some embodiments, there are kits for evaluating biomarker activity in a cell.
[00197] Kits may comprise components, which may be individually packaged or placed in a container, such as a tube, bottle, vial, syringe, or other suitable container means.
[00198] Individual components may also be provided in a kit in concentrated amounts; in some embodiments, a component is provided individually in the same concentration as it would be in a solution with other components. Concentrations of components may be provided as lx, 2x, 5x, lOx, or 20x or more.
[00199] Kits for using probes, synthetic nucleic acids, nonsynthetic nucleic acids, and/or inhibitors of the disclosure for prognostic or diagnostic applications are included as part of the disclosure. Specifically contemplated are any such molecules corresponding to any biomarker identified herein.
[00200] In certain aspects, negative and/or positive control nucleic acids, probes, and inhibitors are included in some kit embodiments. The control molecules can be used to verify transfection efficiency and/or control for transfection-induced changes in cells.
[00201] It is contemplated that any method or composition described herein can be implemented with respect to any other method or composition described herein and that different embodiments may be combined. The claims originally filed are contemplated to cover claims that are multiply dependent on any filed claim or combination of filed claims.
[00202] Any embodiment of the invention involving specific biomarker by name is contemplated also to cover embodiments involving biomarkers whose sequences are at least 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99% identical to the mature sequence of the specified RNA, DNA, or protein. [00203] Embodiments of the disclosure include kits for analysis of a pathological sample by assessing biomarker profile for a sample comprising, in suitable container means, two or more biomarker probes, wherein the biomarker probes detect one or more of the biomarkers identified herein. The kit can further comprise reagents for labeling nucleic acids in the sample. The kit may also include labeling reagents, including at least one of amine-modified nucleotide, poly(A) polymerase, and poly(A) polymerase buffer. Labeling reagents can include an amine- reactive dye.
XI. Examples
[00204] The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention.
Example 1- A pan cancer discovery identifies a biologically conserved signature of N6-methyladenosine regulators as robust predictors of patient survival in multiple cancers
[00205] Purpose: Accumulating evidence indicates the role of N6-methyladenosine (m6A) regulator-mediated RNA methylation in cancer progression and metastasis; yet its potential clinical significance, if any, remains unclear. In this first-of-its-kind study, the inventors comprehensively and systematically evaluated the role of m6A regulators as potential disease biomarkers, and identified the key biological pathways associated with this epigenetic alteration in multiple human cancers.
[00206] The inventors analyzed gene expression profiles of 9,712 cancer cell lines and clinical specimens from 25 publicly-available datasets, encompassing 13 human cancers. Based upon the expression levels of seven m6A regulators, the inventors trained a multivariate Cox regression model for each cancer type, followed by evaluation of its prognostic significance. A pan-cancer analysis was undertaken to identify evolutionary conserved biological network(s) across multiple cancer types.
[00207] The inventors developed and established RNAMethyPro - a 7-gene expression signature of m6A regulators for determining prognosis in 13 human cancers. Pan-cancer analysis identified activated epithelial-mesenchymal transition (EMT), as a highly conserved pathway in high-risk patients predicted by RNAMethyPro in 10 of the 13 cancer types. A network-based analysis revealed an intimate functional interplay between m6A regulators and EMT-associated factors via druggable targets such as XPOl and NTRK1. Finally, the clinical significance of RNAMethyPro was further exemplified in colorectal cancer, where high-risk patients demonstrated strong associations with a mesenchymal subtype, activated stromal infiltration, and poor therapeutic response to targeted anti-EGFR therapy.
[00208] RNAMethyPro, is a novel, EMT-associated prognostic gene-expression signature in multiple human cancers, and may offer an important clinical decision-making tool in the future.
A. INTRODUCTION
[00209] To unravel the true clinical potential of m6A regulators, a comprehensive and systematic pan-cancer analysis approach was undertaken which identified a novel m6A regulator-associated gene expression signature, RNAMethyPro, which robustly predicted patient survival in multiple human cancers. Moreover, the inventors’ analysis revealed that high-risk patients identified by RNAMethyPro were associated with highly conserved biological processes such as the activation of epithelial mesenchymal transition pathway highlighting the clinical significance of this assay to serve as companion diagnostics in improving the clinical outcomes in multiple human cancers. Herein, using a systematic, pan cancer approach, the inventors developed RNAMethyPro, a novel and robust gene expression signature based upon m6A regulators, for predicting the prognosis of patients in 13 different human cancer types. Interestingly, RNAMethyPro not only allowed identification of high-risk cancer patients with poor-prognosis, but also led to the recognition that de-regulated expression of m6A-regulators was intimately associated with an EMT phenotype which was highly conserved across 10 cancer types. More specifically, in colorectal cancer patients, RNAMethyPro-led identification of the high-risk group significantly associated with the mesenchymal subtype, demonstrated activation of EMT and TGFP pathway, increased cancer sternness and higher overall stromal and immune content. Further a network-based analysis suggested strong physical and functional crosstalk between m6A machinery and key EMT- associated proteins such as XPOl and NTRK1 - for which, therapeutic interventions have already been approved by the FDA, or are currently being explored in various clinical trials. In addition to its prognostic utility, RNAMethyPro also emerged as a robust predictor of response to anti-EGFR therapy in colorectal patients with metastatic disease. Taken together, the inventors’ findings provide compelling data for the clinical significance of m6A regulators, and set the stage for future validation and further in-depth mechanistic studies in future. B. MATERIALS AND METHODS
1. Development and validation of m6A prognostic classifiers
[00210] For colorectal, gastric, breast and ovarian cancers, the inventors analyzed data from two independent patient cohorts for the internal and external validations. To make gene expression levels comparable, z-normalization was performed in each dataset. For each cancer type, a multivariate Cox regression model was trained on the corresponding training set, and the trained model was subsequently used to calculate risk scores for both the training and validation (when available) datasets. Patients were subsequently stratified into low, intermediate and high-risk groups, using the 25th and 75th percentile risk scores derived from the training sets as the cutoff thresholds. To evaluate the prognostic performance, 5-year disease-free survival (DFS) was considered as an indicator for colorectal, gastric and breast cancers; while overall survival (OS) was used for ovarian cancer due to limited clinical records and relatively short follow-up. For other cancers, the three risk groups were stratified using the same cutoff thresholds at 25th and 75th percentiles of risk scores, derived from the Cox regression model trained on the corresponding dataset. Only patients with valid survival information available were used in the analyses.
2. Gene set enrichment analysis
[00211] Based on RNAMethyPro risk stratification, differentially expressed genes between low and high-risk groups were identified based on TCGA datasets from 13 cancer types, using ‘LIMMA’ R package. Gene set enrichment analysis (GSEA) was performed using HTSanalyzeR (29) with 5000 permutations for 50 hallmark gene sets (>=15 genes) obtained from MSigDB v6. l. To illustrate the association between these 50 hallmark gene sets, the inventors constructed an enrichment map, where nodes encoded gene set size and edges encodes the strength of association quantified by Jaccard similarity coefficient (or Jaccard index). Node color represented conservation scores, defined by the frequency that a gene set is significantly enriched (P < 0.05) in the RNAMethyPro high-risk group in each of the cancer types studied.
3. Estimate analysis of stromal and immune content
[00212] In order to confirm the hypothesis that CRC patients in the RNAMethyPro high-risk group had higher stromal and immune content, gene expression profiles from TCGA- COADREAD cohort were used for calculating stromal and immune scores with ESTIMATE (30). The statistical significance of differences between the high-risk and intermediate/low-risk groups were evaluated using Kruskal-Wallis tests. 4. Network analysis
[00213] To identify functional modules dysregulated in the RNAMethyPro high-risk groups conserved across the 10 cancer types (OV, HCC, LUSC, LUAD, HNSC, GC, ESCC, EAC, CRC and BLCA), the inventors employed BioNet - a model-based network approach previously published (31). Specifically, the inventors aggregated p-values derived from differential gene expression analysis using‘LIMMA’ R package between RNAMethyPro high- and low-risk groups in the 10 cancer types by lOth order statistic. After successfully fitting the aggregated p-values to a beta-uniform mixture model, signal-to-noise ratios were calculated to score gene products in the human interactome retrieved from BioGRID database (version 3.4.134), followed by identification of enriched subnetwork using‘BioNet’ R package (31) (FDR < le-4). The obtained subnetwork of protein-protein interactions is visualized using ‘RedeR’ R package.
5. Statistical analysis
[00214] Statistical analyses were performed using R (version 3.4.3, www.r-project.org). Continuous variables were expressed as mean and standard error of the means, and were compared using student’s t-tests or Wilcoxon rank sum tests. Categorical variables were compared using one-tailed Fisher’s exact tests or hypergeometric tests. Survival analyses were performed using the Kaplan-Meier method and compared with log-rank tests using‘survival’ package. Multivariate cox regression models were trained using‘coxph’ function in‘survival’ package. Hazard ratios were calculated using function‘hazard.ratio’ in‘survcomp’ package. P < 0.05 was considered as significant for all tests.
6. Public datasets
[00215] In this study, the inventors analyzed a total of 9,712 specimens, which comprised of 25 datasets for 13 different types of cancers (Table S l). TCGA datasets, level-3 gene expression profiles for tumor specimens, were downloaded from Firehose Broad GDAC portal (http://gdac.broadinstitute.org/, accessed on Jun 1, 2017) for colorectal adenocarcinomas (TCGA-COADREAD (1), n = 626), stomach adenocarcinomas (TCGA-STAD (2), n = 415), pancreatic ductal adenocarcinomas (TCGA-PAAD (3), n = 179), liver hepatocellular carcinomas (TCGA-FIHC (4), n = 373), ovarian serous cystadenocarcinomas (TCGA-OV (5), n = 514), lung adenocarcinomas (TCGA-FUAD (6), n = 517), lung squamous cell carcinomas (TCGA-FUSC (7), n = 501), esophageal carcinomas (TCGA-ESCA (8), n = 165, including esophageal squamous cell carcinoma and esophageal adenocarcinoma), head and neck squamous cell carcinoma (TCGA-HNSC (9), n = 522), bladder urothelial carcinoma (TCGA- BLCA (10), n = 408) and breast cancer (TCGA-BRCA (11), n = 1100) respectively. For all the datasets other than the ovarian cohort, RSEM scaled estimates of gene expression levels were first converted to transcripts per million (TPM) by multiplication with 1 million, followed by log2-transformation. The TCGA-OV dataset consisted of processed gene expression profiles based on Affymetrix HG133A microarrays. For TCGA-PAAD dataset, the inventors kept 76 specimens of high purity for further analysis. For TCGA-BRCA dataset, the inventors analyzed 517 specimens with complete clinical information.
[00216] From Gene Expression Omnibus (GEO) database, the inventors also obtained CIT (GSE39582 (12), n = 566), Khambata-Ford (GSE5851 (13), n = 80), Jorissen (GSE14333 (14), n = 290), Smith (GSE17536 (15), n = 177), Bimbaum (GSE26906 (16), n = 86), AMC-AJCCII- 90 (GSE33113 (17), n = 90), Laibe (GSE37892 (18), n = 130), Kirzin (GSE39084 (19), n = 68), Medico (GSE59857 (20), n = 155, of which 151 with cetuximab response) datasets for colorectal cancer, ACRG-GC dataset (GSE62254 (21), n = 300) for gastric cancer, as well as MAYO-OV dataset (GSE53963 (22), n = 174) for ovarian cancer in their processed form. GSE39582, GSE14333, GSE17536, GSE26906, GSE33113, GSE37892, GSE39084, GSE5851, GSE62254 were all based on Affymetrix Human Genome U133 Plus 2.0 Arrays, and the probe set IDs were converted to official gene symbols according to the annotation ‘GPL570’ in GEO. GSE59857 dataset was measured on Illumina HumanHT-l2 V4.0 expression beadchip platform and annotated by‘GPL10558’ in GEO. All datasets from GEO database were downloaded directly in their processed form. For 7 GEO datasets used as the CRC meta-validation set, the inventors further removed the non-biological batch effects using ‘combat’ function in R‘sva’ package.
[00217] Additionally, METABRIC (23) gene expression discovery and validation datasets were obtained for breast cancer analysis. For acute myeloid leukemia (AML), RNA-seq data was downloaded from TARGET (24) database, and was first converted from FPKM to TPM followed by log2-transformation.
[00218] For genes with multiple probe sets, the inventors kept the ones with the largest median absolute deviations (MADs). Only patients with complete survival information were used for survival analyses. In the TCGA-OV dataset, two genes (METTL14 and ALKBH5) were missing, and therefore, the inventors marked corresponding values as ‘NA’. For all colorectal cancer datasets, CMS (consensus molecular subtype) labels were calculated using ‘CMSclassifier’ package (https://github.com/Sage-Bionetworks/CMSclassifier). C. RESULTS
1. A panel of seven m6A regulator genes predict survival in various cancers
[00219] The inventors systematically evaluated the prognostic significance of m6A regulatory machinery, focusing on a panel of 3 m6A‘writers’ (METTL3, METTL14 and WTAP), 2 ‘erasers’ (FTO and ALKBH5) and 2 ‘readers’ (YTHDF1 and YTHDF2). The inventors performed comprehensive bioinformatic analysis of 25 public gene expression datasets comprising a total of more than 9000 patients, across 13 cancer types (Table S l, Supplementary Material and Methods). For each type of cancer, a multivariate Cox regression model was first trained using the corresponding training dataset, and the derived formula (hereafter referred to as ‘RNAMethyPro’) was subsequently used to calculate risk scores predictive of overall survival (OS; for ovarian and pancreatic cancer) or relapse-free survival (RFS; for the other 11 cancer types). Using cutoff thresholds on the 25th and 75th percentiles of the risk scores, patients in each cohort were stratified into low-, intermediate- and high-risk groups. The inventors observed that the high-risk patients had a significantly shorter survival compared to low-risk patients (FIG. 1A, 1C, 1E, and 1G, FIG. 6, Table 1), indicating that the prognostic power of RNAMethyPro was successfully validated in all the 13 cancer types.
[00220] For four cancer types (colorectal, gastric, breast and ovarian), where additional independent patient cohorts were available, the inventors next sought to externally validate the prognostic potential of RNAMethyPro. For colorectal cancer, the risk scoring formula trained using the TCGA-COADREAD cohort was subsequently applied to the CIT cohort (n = 566), followed by stratification of the patients based on the application of the same cutoff thresholds determined in the training cohort. Consistent with the TCGA-COADREAD cohort, in the CIT cohort, the inventors also observed that the high-risk patients had a significantly shorter disease-free survival (DFS) vs. low-risk patients (P = 0.00153, log-rank test) with a corresponding Hazard Ratio (HR) of 2.24 (1.34 - 3.74; FIG. 1B, Table 1). Similarly, the m6A signature showed robust potential for predicting survival in validation cohorts in gastric (FIG. 1D, ACRG-GC cohort: HR, 1.78 [1.12 - 2.83], P = 0.0136), breast (FIG. 1F, METABRIC validation cohort: HR, 1.73 [1.14 - 2.63], P = 0.00946) and ovarian cancer (FIG. 1H, TCGA- OV cohort: HR, 1.56 [1.04 - 2.35], P = 0.0317). Taken together, by using systematic statistical approaches on both the internal and external validation cohorts, the inventors were able to demonstrate the robust prognostic significance of RNAMethyPro in various cancers. 2. Identification of highly conserved biological processes associated with cancer metastasis in high-risk patients identified by RNAMethyPro
[00221] To gain insights into the mechanistic underpinnings of high-risk patients identified by RNAMethyPro, the inventors systematically interrogated various key biological processes dysregulated across the 13 cancer types. More specifically, for each cancer type, the inventors analyzed the corresponding gene expression datasets (Table S l) for gene set enrichment analysis (GSEA) on 50 hallmark gene sets obtained from MSigDB using HTSanalyzeR (29). Unsupervised hierarchical clustering on the obtained matrix of gene set enrichment scores identified two distinct clusters of cancers - a smaller cluster comprising of breast (BRCA), pancreatic (PD AC) and acute myeloid leukemia (AML), and a larger cluster of 10 other cancer types. Interestingly, the larger cluster was primarily enriched for GI cancers typified by specific biological processes related to epithelial-mesenchymal transition, angiogenesis and cancer sternness (FIG. 2A). Interestingly, different from other GI cancers, activation of MYC and pancreatic beta cells emerged as major drivers of disease pathogenesis in PDAC (35-37). Breast cancer patients with poor prognosis were characterized by a basal subtype- specific features, such as MYC and E2F activation (32), whereas high-risk AML subgroup associated with heme metabolism and interferon- alpha response, in line with previous reports (33,34).
[00222] To further dissect the biological properties associated with RNAMethyPro high-risk groups, the inventors constructed a comprehensive enrichment map and identified a subnetwork of highly conserved biological processes associated with cancer progression and metastasis (FIG. 2B). Central to this functional network of pathways was EMT, which was significantly upregulated in the RNAMethyPro high-risk group in all the 10 cancer types within the major cluster (FIG. 7). Core signature genes for EMT, matrix remodeling processes, and transforming growth factor-b (TGF-b) were mostly significantly upregulated in RNAMethyPro-identified high-risk patients in all GI cancers (except PDAC) and lung adenocarcinoma (LUAD; FIG. 2C). Interestingly, lung squamous cell carcinoma (LUSC), which is another major type of non- small-cell lung carcinoma, did not show any significant upregulation of these signature genes in the RNAMethyPro high-risk subgroup (FIG. 2C) - highlighting the specificity of the m6A signature for different cancer types.
[00223] To identify functionally conserved modules underlying the dysregulated biological processes associated with RNAMethyPro high-risk groups, the inventors employed a network- based approach by integrating human interactome and gene expression data. Interestingly, the conserved subnetwork of protein-protein interactions the inventors identified were enriched for a number of EMT signature genes (FIG. 2D). Central to the network were four hub proteins including, APP (38), XPOl (39), NTRK1 (40) and ELAVL1 (or HuR) (41), which have been previously implicated for their regulatory roles in tumorigenesis and/or metastasis. Taken together, the inventors’ findings revealed that upregulation of EMT is a key common mechanism associated with high-risk cancer patients, highlighting potential interactions between m6A regulatory machinery and cancer metastasis.
3. RNAMethyPro is predictive of therapeutic response to anti-EGFR drugs in colorectal cancer
[00224] By using colorectal cancer as a case study, the inventors next performed integrative analysis to further elucidate the biological and clinical characteristics associated with RNAMethyPro risk groups. Using TCGA-COADREAD dataset, the inventors first trained a multivariate Cox regression model and obtained the following risk scoring formula: 0.24 * METTL3 - 0.14 * METTL14 + 0.09 * WTAP - 0.14 * YTHDF1 - 0.22 * YTHDF2 + 0.22 * FTO + 0.03 * ALKBH5. Based on this formula, the inventors calculated risk scores and stratified patients in the CIT cohort (n = 566) using the 25th and 75th percentiles in the training cohort patients into low-, intermediate- and high-risk groups. Interestingly, the inventors found that the high-risk group was significantly enriched for patients with cancer relapse or death (P = 0.00095, Fisher’s exact test), while the low risk group significantly comprised of patients with CIN, CIMP, MSI, and BRAF mutations (P = 0.00034, 0.0063, 8.59e-l l, 0.0013, respectively, Fisher’s exact tests; FIG. 3 A). Notably, the inventors found that both the low- and high-risk groups were significantly associated with unique Consensus Molecular Subtypes (CMSs) previously defined by the colorectal cancer subtyping consortium (CRCSC) (42) (FIG. 3A, P < le-l6, Fisher’s exact test). More specifically, CMS4 patients had the highest risk scores, while CMS 1 subgroup had the lowest, and CMS2 & CMS3 patients possessed in between risk-scores (FIG. 3B). Hypergeometric tests further confirmed that the RNAMethyPro high-, intermediate- and low-risk groups were significantly overrepresented for patients classified to CMS4, CMS2 and CMS 1, respectively (FIG. 3C, P = 5.30e-l0 and 9.95e-08). These results are consistent with previously reported findings that patients with CMS 1 tumors had the best prognosis, while CMS4 tumors resulted in the worst DFS (42). Furthermore, the inventors found that indeed the RNAMethyPro high-risk group showed significant upregulation in gene sets related to the EMT, matrix remodeling, TGFP pathway and cancer stem cell, with concurrent downregulation of the WNT signaling pathway, MYC targets and mesenchymal-epithelial transition (MET; FIG. 8), which were described as the key molecular characteristics of CMS4 colorectal cancers (42). 4. Integrative analysis revealed complex physical and functional crosstalk between m6A regulators and EMT in colorectal cancer
[00225] For a better understanding of the biological processes associated with RNAMethyPro high-risk groups in CRC, the inventors analyzed CRC Meta-validation cohort (n = 841), which was generated by merging six independent public datasets (Table S 1). Among all the seven m6A regulators studied, WTAP, METTL3, FTO and ALKBH5 were all significantly upregulated in the high-risk group vis-a-vis low and intermediate groups (FIG. 4A, P < 0.001, student’s t tests), while YTHDF1, YTHDF2 and METTL14 were all significantly downregulated in the high-risk group (FIG. 4A, P < 0.001, student’s t tests). Based on the observation of upregulated EMT (FIG. 8) and associated key signature genes such as TGFB2, TGFBR2, SMAD2 and ZEB 1 (FIG. 4A) in the high-risk patients, the inventors infer that m6A regulatory machinery must interact with EMT to regulate cancer metastasis in various human malignancies.
[00226] To systematically investigate any potential physical and functional crosstalk, the inventors constructed a protein-protein interaction (PPI) network based on BioGRID database (FIG. 4B) and a coexpression network (FIG. 9) which involved EMT signature genes, m6A regulators and the four hub genes in the conserved subnetwork described earlier (FIG. 2D). Interestingly, in the PPI network, the inventors found direct interaction between YTHDF2 and SMAD3 (FIG. 4B), in addition to the recently identified interaction between SMAD2/3 and METTL3-METTL14-WTAP complex induced by TGFP signaling (43). More strikingly, most m6A regulators directly or indirectly interacted with the EMT gene products via hub proteins such as ELAV1 and APP (FIG. 4B). Although FTO was not found to physically interact with the EMT machinery, its gene expression was significantly correlated with ZEB 1 (Pearson correlation coefficient: 0.323, P = 3.55e-l5), as well as SMAD3, TGFB2 and TGFBR2 (FIG. 4C, Figure S4, Table S2). Besides FTO, other m6A regulators were also intimately interconnected with hub genes in the conserved subnetwork and EMT signature genes (FIG. 9), highlighting their intensive functional crosstalk in mediating cancer metastasis. Furthermore, compared to RNAMethyPro intermediate- and low-risk groups, the inventors also observed significantly higher stromal and immune infiltration (FIG. 4D-E) in the high-risk group, which is consistent with recent studies poor-prognosis CRC is a primarily a consequence of abundant stromal content with TGFP activation (44,45). 5. RNAMethyPro is predictive of therapeutic response to anti-EGFR drugs in colorectal cancer
[00227] Molecular subtypes of CRC are associated with response to anti-EGFR therapies independent of KRAS mutations (47). In this study, the inventors were able to demonstrate that the RNAMethyPro risk groups were significantly associated with various CRC subtypes, and accordingly hypothesized that risk scores derived from this signature may also be predictive of therapeutic response to anti-EGFR drugs. To validate the inventors’ hypothesis, the inventors first analyzed a public cohort of 151 CRC cell lines with gene expression and cetuximab sensitivity data (GSE59857) (48). To avoid any potential confounding factors, the inventors focused on 28 microsatellite stable cell lines without KRAS, NRAS, HRAS, BRAF and PIK3CA mutations, which have been shown to be significantly associated with refractory cetuximab response (49). FTsing the established scoring formula for CRC, the inventors calculated risk scores followed by stratification of all cell lines into low-, intermediate- and high-risk groups. Meanwhile, based on arbitrary indices of cetuximab’ s effect (median- centered, as described previously (48)), all cell lines could also be successfully classified into cetuximab resistant and sensitive groups. Indeed, the inventors found that the predicted RNAMethyPro risk was significantly associated with cetuximab resistance (FIG. 5A, P = 0.00086, Fisher’s exact test). More specifically, cell lines classified into the low-risk group were significantly more resistant to cetuximab than those in the intermediate- and high-risk groups (FIG. 5B, P < 0.05 and P < 0.001, one-tailed Student’s t-tests).
[00228] To further investigate the predictive potential of RNAMethyPro, the inventors classified 80 metastatic CRC patients treated with cetuximab in the Khambata-Ford cohort (50) into low-, intermediate- and high-risk groups. Similar to the CIT cohort with mostly stage II/III patients, the inventors observed that in the Khambata-Ford cohort that CMS4 tumors also had higher risk scores compared to non-CMS4 tumors (P = 0.0018, one-tailed Student’s t-test, FIG. 5D), and the high-risk group was significantly associated with CMS4 CRC subtype (P = 0.0417, hypergeometric test, FIG. 5E). Compared to the low-risk group, the inventors found the high-risk group of patients were more resistant to cetuximab treatment (PD vs SD/PR/CR, P = 0.06, Fisher’s exact test, FIG. 5F), and were associated with significantly poorer DFS (HR 1.98, [1.03 - 3.80], P = 0.036, log-rank test, FIG. 5G). Interestingly, univariate and multivariate Cox regression analysis showed that RNAMethyPro-derived risk scores were significantly associated with poor DFS (P = 0.0373 and 0.0295, respectively, Table S3), whereas KRAS mutation, a well-established determinant of anti-EGFR drug response, failed to show any significance (P = 0.213 and 0.177, respectively, Table S3). Collectively, these results also highlight the additional potential for using RNAMethyPro as a tool for predicting therapeutic response to anti-EGFR therapy, which will refine and further optimize treatment decision making in metastatic CRC patients.
D. DISCUSSION
[00229] To the best of the inventors’ knowledge, to date there are no systematic studies that have comprehensively analyzed the true clinical potential of m6A regulator genes in clinical decision-making. Here, the inventors have performed the most comprehensive pan-cancer analysis on the role of m6A regulators in multiple cancer types. The overall strengths of the inventors’ study include: 1) analysis of data from more than 9,700 cell lines and clinical specimens encompassing 13 cancer types, which represents thus far the most comprehensive analysis in the field to date; 2) the use of a network-based pan-cancer analysis to identify key pathways and protein subnetworks associated with m6A deregulation; 3) integrative analysis of gene expression, molecular and clinicopathological characteristics, as well as drug response data, demonstrating the very first associations between m6A modifications and clinical outcomes in proof-of-principle analysis in colorectal cancer.
[00230] The inventors’ identification for the promising clinical significance of m6A regulators motivated them to dissect the underlying functional determinants that are potentially shared across multiple cancer types. Based on the gene set enrichment analysis and conservation enrichment map, the inventors identified that biological processes such as epithelial-mesenchymal transition (EMT), angiogenesis and cancer sternness were commonly upregulated in RNAMethyPro identified high-risk patients across 10 different cancers. Although the association between m6A regulators and EMT was proposed previously, the inventors’ findings for the firstly highlight this to be a key common denominator pathway which is highly conserved in multiple major malignancies. Interestingly, the inventors’ model- based network approach identified a conserved functional module of protein-protein interactions enriched for EMT signature gene products, and led the inventors to firstly identify four hub proteins, APP, ELAVL1 (HuR), XPOl and NTRK1, whose roles in predicting adjuvant therapy benefit, cancer progression and metastasis have been suggested previously (38-41). More importantly, the inventors’ discovery for the strong functional and physical interactions between these four hub proteins, m6A regulators and EMT signature genes, suggests that the m6A machinery facilitates the EMT process directly or indirectly via these hub proteins, in multiple human cancers. Furthermore, the identification of the hub proteins is clinically relevant, since they are druggable and several inhibitors are already approved by the US FDA (e.g., Entrectinib targeting NTRK1) or are currently being evaluated in clinical trials (e.g., KPT-330 targeting XPOl). Based on the observation that key EMT drivers such as SMAD2, SMAD3, ZEB 1, TGFB2 and TGFBR2 were all significantly upregulated in RNAMethyPro-identified high-risk tumors, the inventors hypothesized that m6A regulators may functionally interact with EMT induced by activated TGFP pathway in the stromal cells.
[00231] Although earlier studies have reported oncogenic and tumor suppressive roles of different m6A regulators in various malignancies, none of the previous studies have been undertaken in colorectal cancer. This study is the first comprehensive research interrogating associations between m6A regulatory machinery and clinical outcomes in colorectal cancer. Clinically, in addition to demonstrating the robust prognostic value of RNAMethyPro, the inventors also showed its association with anti-EGFR drug response in cell lines and metastatic CRC patients. In addition to facilitating selection of appropriate patients for anti-EGFR therapy, the ability to stratify cell lines for anti-EGFR response will provide experimental tools to evaluate novel drug targets and drug combinations in the near future. Biologically, the inventors found RNAMethyPro stratified risk groups were not only significantly associated with MSI/MSS, CIMP status, BRAF mutations, but more importantly, also with the recently discovered consensus molecular subtypes (CMSs) in CRC. This is in line with previous biological findings, where FTO was shown to be associated with poor prognosis molecular subtypes of breast cancer and AML.
[00232] In conclusion, the inventors developed RNAMethyPro - a novel gene-expression signature comprising of seven m6A regulators, for robust prediction of prognosis in multiple cancers. Using a comprehensive pan-cancer analysis, the inventors identified activated EMT as a highly conserved biological process across multiple cancer types. Additional investigations in colorectal cancer revealed critical and previously unrecognized associations of RNAMethyPro high-risk group with the mesenchymal subtype and poor anti-EGFR response. Pending future validation and potential mechanistic evaluation of findings reported in this study, RNAMethyPro may offer an important clinical decision-making tool in the near future.
H. TABLES
Table 1: Log-rank test and univariate analysis of RNAMethyPro risk score in each cohort analyzed for internal or external validation
Figure imgf000072_0001
Table Sl A summary of public datasets analyzed in this study
Figure imgf000072_0002
Figure imgf000073_0001
Figure imgf000074_0002
Total 9712
Figure imgf000074_0001
Table S2 Pearson correlation coefficients and associated p-values quantifying the strength and statistical significance of coexpression between the seven m6A regulator genes, EMT signature genes (ZEB 1, SMAD2, SMAD3, TGFB2, TGFBR2) and the four hub genes (XPOl, NTRK1, ELAVL1 and APP)
Figure imgf000075_0001
Figure imgf000076_0001
Figure imgf000077_0001
Table S3 Univariate and multivariate analysis of RNAMethyPro risk score, and available molecular and clinical factors in the Khambata-Ford cohort
Figure imgf000077_0002
[00233] All of the methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims. All references and publications referred to throughout the disclosure are incorporated by reference for all purposes.
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Claims

1. A method for evaluating a patient comprising measuring the level of expression in a biological sample from the patient of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
2. The method of claim 1, wherein the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer.
3. The method of any one of claims 1-2, wherein the patient has and/or has been determined to have an EGFR mutant cancer.
4. The method of claim 3, wherein the patient has not been administered an EGFR inhibitor therapy.
5. The method of claim 3, wherein the patient has been administered an EGFR inhibitor therapy.
6. The method of any of claims 1-2, wherein at least FTO is measured.
7. The method of claim 6, wherein FTO expression is upregulated.
8. The method of any of claims 1-2, wherein at least METTL3 is measured.
9. The method of claim 8, wherein METTL3 expression is upregulated.
10. The method of any of claims 1-2, wherein at least WTAP is measured.
11. The method of claim 10, wherein WTAP expression is upregulated.
12. The method of any of claims 1-2, wherein at least ALKBH5 is measured.
13. The method of claim 12, wherein ALKBH5 expression is upregulated.
14. The method of any of claims 1-2, wherein at least METTL14 is measured.
15. The method of claim 14, wherein METTL14 expression is downregulated.
16. The method of any of claims 1-2, wherein at least YTHDF1 is measured.
17. The method of claim 16, wherein YTHDF1 expression is downregulated.
18. The method of any of claims 1-2, wherein at least YTHDF2 is measured.
19. The method of claim 18, wherein YTHDF2 expression is downregulated.
20. The method of any of claims 1-19, wherein the levels of expression of at least two listed biomarkers is measured.
21. The method of claim 20, wherein the levels of expression of at least three listed biomarkers is measured.
22. The method of claim 21, wherein the levels of expression of at least four listed biomarkers is measured.
23. The method of claim 22, wherein the levels of expression of at least five listed biomarkers is measured.
24. The method of claim 23, wherein the levels of expression of at least six listed biomarkers is measured.
25. The method of claim 24, wherein the levels of expression of at least seven listed biomarkers is measured.
26. The method of any of claims 1-25, wherein the expression level of no other biomarker in the biological sample is measured.
27. The method of any of claims 1-26, wherein at least one of the listed biomarkers is excluded from being measured.
28. The method of claim 27, wherein at least two of the listed biomarkers are excluded from being measured.
29. The method of any of claims 1-28, further comprising comparing the level(s) of expression to a control sample(s) or control level(s) of expression.
30. The method of claim 29, wherein the control sample(s) have expression levels that are representative of normal cells from a cohort of patients, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
31. The method of claim 30, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
32. The method of claim 30, wherein the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
33. The method of claim 30, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
34. The method of claim 30, wherein the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort patients with CMS4 cancer.
35. The method of any of claims 1-34, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
36. The method of claim 35, wherein either a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
37. The method of claim 35 or 36, wherein the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
38. The method of claim 37, wherein the method further comprises treating the patient.
39. The method of claim 38, wherein the treatment excludes one or more of EGFR inhibitors, adjuvant therapy, neo-adjuvant therapy, and EMT inhibitors.
40. The method of any of claims 1-34, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
41. The method of claim 40, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
42. The method of claim 40 or 41, wherein the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer.
43. The method of claim 42, wherein the method further comprises treating the patient.
44. The method of claim 43, wherein the treatment comprises an EGFR inhibitor.
45. The method of claim 43 or 44, wherein the treatment comprises administration of an FTO inhibitor.
46. The method of any one of claims 43-45, wherein the treatment comprises an epithelial to mesenchymal transition (EMT) protein inhibitor.
47. The method of claim 47, wherein the EMT protein inhibitor comprises an inhibitor of a protein selected from APP, XPOl, NTRK1, ELAVL1, HuR, and combinations thereof.
48. The method of claim 44 or 45, wherein the inhibitor is a small molecule, nucleic acid, or protein.
49. The method of any one of claims 44-48, wherein the inhibitor inhibits protein expression.
50. The method of any one of claims 44-48, wherein the inhibitor inhibits protein activity.
51. The method of any of claims 46-50, wherein the nucleic acid is an siRNA or miRNA.
52. The method of any of claims 46-50, wherein the protein is an FTO-specific, EMT protein- specific, and/or EGFR-specific binding protein or peptide.
53. The method of claim 52, wherein the FTO-specific and/or EGFR-specific binding protein comprises all or part of an antibody.
54. The method of any one of claims 44-53, wherein the EGFR inhibitor comprises a tyrosine kinase inhibitor (TKI).
55. The method of claim 54, wherein the TKI comprises gefitinib, erlotinib, lapatinib, neratinib, osimertinib, vandetanib, dacomitinib, or combinations thereof.
56. The method of any one of claims 44-53, wherein the EGFR inhibitor comprises an antibody.
57. The method of claim 56, wherein the antibody comprises cetuximab, panitumumab, necitumumab, or combinations thereof.
58. The method of any of claims 1-46, wherein the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a cancerous sample.
59. The method of any of claims 1-58, further comprising treating the patient for cancer after measuring the level of expression of one or more listed biomarkers.
60. The method of any of claims 1-59, wherein expression is measured using one or more hybridization and/or amplification assays.
61. The method of claim 60, wherein the assay comprises polymerase chain reaction.
62. A method comprising measuring in a biological sample from a cancer patient the levels of expression of the following biomarkers FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1 and YTHDF2.
63. The method of claim 62, wherein the level of expression of no additional biomarkers is measured.
64. The method of any of claims 1-63, wherein a cohort comprises at least 50, 100, 200, 300, 400, 500 or more patients.
65. A method comprising measuring in a biological sample from a cancer patient increased levels of expression of 1) FTO, METTF3, WTAP and/or AFKBH5 and reduced levels of expression of 2) METTF14, YTHDF1 and/or YTHDF2 as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
66. The method of any of claims 1-65, wherein a cohort comprises at least 50, 100, 200, 300, 400, 500 or more patients.
67. A method of treating a patient with cancer comprising administering a chemotherapy and/or radiation to the patient after a biological sample from the patient has been measured for the level of expression of at least one or more of the following listed biomarkers: one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
68. The method of claim 67, wherein the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer.
69. The method of any of claims 67-68, wherein at least FTO is measured.
70. The method of claim 69, wherein FTO expression is upregulated.
71. The method of any of claims 67-68, wherein at least METTL3 is measured.
72. The method of claim 71, wherein METTL3 expression is upregulated.
73. The method of any of claims 67-68, wherein at least WTAP is measured.
74. The method of claim 73, wherein WTAP expression is upregulated.
75. The method of any of claims 67-68, wherein at least ALKBH5 is measured.
76. The method of claim 75, wherein ALKBH5 expression is upregulated.
77. The method of any of claims 67-68, wherein at least METTL14 is measured.
78. The method of claim 77, wherein METTL14 expression is downregulated.
79. The method of any of claims 67-68, wherein at least YTHDF1 is measured.
80. The method of claim 79, wherein YTHDF1 expression is downregulated.
81. The method of any of claims 67-68, wherein at least YTHDF2 is measured.
82. The method of claim 81, wherein YTHDF2 expression is downregulated.
83. The method of any of claims 67-82, wherein the levels of expression of at least two listed biomarkers is measured.
84. The method of claim 83, wherein the levels of expression of at least three listed biomarkers is measured.
85. The method of claim 84, wherein the levels of expression of at least four listed biomarkers is measured.
86. The method of claim 85, wherein the levels of expression of at least five listed biomarkers is measured.
87. The method of claim 86, wherein the levels of expression of at least six listed biomarkers is measured.
88. The method of claim 87, wherein the levels of expression of at least seven listed biomarkers is measured.
89. The method of any of claims 67-88, wherein the expression level of no other biomarker in the biological sample is measured.
90. The method of any of claims 67-89, wherein at least one of the listed biomarkers is excluded from being measured.
91. The method of claim 90, wherein at least two of the listed biomarkers are excluded from being measured.
92. The method of any of claims 67-91, further comprising comparing the level(s) of expression to a control sample(s) or control level(s) of expression.
93. The method of claim 92, wherein the control sample(s) have expression levels that are representative of normal colorectal cells, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
94. The method of claim 93, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
95. The method of claim 93, wherein the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
96. The method of claim 93, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
97. The method of claim 93, wherein the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
98. The method of any of claims 67-97, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
99. The method of claim 98, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from a cohort of patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
100. The method of claim 98 or 99, wherein the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
101. The method of any of claims 67-97, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
102. The method of claim 101, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
103. The method of claim 101 or 102, wherein the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer.
104. The method of claim 103, wherein the patient is administered an EGFR inhibitor.
105. The method of claim 103, wherein the patient is administered an FTO inhibitor.
106. The method of claim 103, wherein the patient is administered an epithelial to mesenchymal transition (EMT) protein inhibitor.
107. The method of claim 106, wherein the EMT protein inhibitor comprises an inhibitor of a protein selected from APP, XPOl, NTRK1, ELAVL1, HuR, and combinations thereof.
108. The method of any one of claims 104-107, wherein the inhibitor is a small molecule, nucleic acid, or protein.
109. The method of any one of claims 104-108, wherein the inhibitor inhibits protein expression.
110. The method of any one of claims 104-109, wherein the inhibitor inhibits protein activity.
111. The method of any one of claims 108-110, wherein the nucleic acid is an siRNA or miRNA.
112. The method of any of claims 104-110, wherein the protein is an FTO-specific, EMT protein- specific, and/or EGFR-specific binding protein or peptide.
113. The method of claim 112, wherein the FTO-specific and/or EGFR-specific binding protein comprises all or part of an antibody.
114. The method of any one of claims 104-113, wherein the EGFR inhibitor comprises a tyrosine kinase inhibitor (TKI).
115. The method of claim 114, wherein the TKI comprises gefitinib, erlotinib, lapatinib, neratinib, osimertinib, vandetanib, dacomitinib, or combinations thereof.
116. The method of any one of claims 104-113, wherein the EGFR inhibitor comprises an antibody.
117. The method of claim 116, wherein the antibody comprises cetuximab, panitumumab, necitumumab, or combinations thereof.
118. The method of any of claims 67-117, wherein the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a colorectal sample.
119. The method of any of claims 67-118, wherein the treatment further comprises surgery.
120. The method of any of claims 67-119, wherein expression is measured using one or more hybridization and/or amplification assays.
121. The method of claim 120, wherein the assay comprises polymerase chain reaction.
122. The method of any of claims 67-121, wherein a cohort comprises at least 50, 100,
200, 300, 400, 500 or more patients.
123. A method of treating a patient with cancer comprising administering an FTO inhibitor to the patient after a biological sample from the patient has been measured to have a level of expression for FTO that is upregulated compared to the level of FTO in either a low-risk patient survival cohort, a non-recurrent cancer cohort, or a cohort of CMS1 cancer patients.
124. The method of claim 123, further comprising measuring the level of expression of at least one or more of the following additional listed biomarkers: one or more of the listed biomarkers: METTL3, WTAP, ALKBH5, METTL14, YTHDF1, or YTHDF2.
125. The method of claim 123, wherein the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer.
126. The method of any of claims 123-125, wherein at least METTL3 is measured.
127. The method of claim 126, wherein METTL3 expression is upregulated.
128. The method of any of claims 123-125, wherein at least WTAP is measured.
129. The method of claim 128, wherein WTAP expression is upregulated.
130. The method of any of claims 123-125, wherein at least ALKBH5 is measured.
131. The method of claim 130, wherein ALKBH5 expression is upregulated.
132. The method of any of claims 123-125, wherein at least METTL14 is measured.
133. The method of claim 132, wherein METTL14 expression is downregulated.
134. The method of any of claims 123-125, wherein at least YTHDF1 is measured.
135. The method of claim 134, wherein YTHDF1 expression is downregulated.
136. The method of any of claims 123-125, wherein at least YTHDF2 is measured.
137. The method of claim 136, wherein YTHDF2 expression is downregulated.
138. The method of any of claims 123-137, wherein the levels of expression of at least two listed biomarkers is measured.
139. The method of claim 138, wherein the levels of expression of at least three listed biomarkers is measured.
140. The method of claim 139, wherein the levels of expression of at least four listed biomarkers is measured.
141. The method of claim 140, wherein the levels of expression of at least five listed biomarkers is measured.
142. The method of claim 141, wherein the levels of expression of at least six listed biomarkers is measured.
143. The method of claim 142, wherein the levels of expression of at least seven listed biomarkers is measured.
144. The method of any of claims 123-143, wherein the expression level of no other biomarker in the biological sample is measured.
145. The method of any of claims 123-144, wherein at least one of the listed biomarkers is excluded from being measured.
146. The method of claim 145, wherein at least two of the listed biomarkers are excluded from being measured.
147. The method of any of claims 123-146, further comprising comparing the level(s) of expression of the additional listed biomarkers to a control sample(s) or control level(s) of expression.
148. The method of claim 147, wherein the control sample(s) have expression levels that are representative of normal colorectal cells, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
149. The method of claim 148, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
150. The method of claim 148, wherein the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
151. The method of claim 148, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
152. The method of claim 148, wherein the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
153. The method of any of claims 123-152, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
154. The method of claim 153, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
155. The method of claim 153 or 154, wherein the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
156. The method of any of claims 123-152, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
157. The method of claim 156, wherein either a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
158. The method of claim 156 or 157, wherein the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer.
159. The method of any of claims 123-158, wherein the FTO inhibitor is a small molecule, nucleic acid, or protein.
160. The method of claim 159, wherein the FTO inhibitor inhibits FTO expression.
161. The method of claim 159, wherein the FTO inhibitor inhibits FTO activity.
162. The method of any of claims 159-161, wherein the nucleic acid is an siRNA or miRNA.
163. The method of any of claims 159-161, wherein the protein is an FTO-specific binding protein or peptide.
164. The method of claim 163, wherein the FTO-specific binding protein comprises all or part of an antibody.
165. The method of any of claims 123-159, wherein the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a colorectal sample.
166. The method of any of claims 123-165, wherein the treatment further comprises surgery.
167. The method of any of claims 123-166, wherein expression is measured using one or more hybridization and/or amplification assays.
168. The method of claim 167, wherein the assay comprises polymerase chain reaction.
169. A method of prognosing a patient with cancer and/or evaluating treatment for the patient comprising:
a) measuring the level of expression of one or more of the listed biomarkers: FTO, METTL3, WTAP, ALKBH5; METTL14, YTHDF1 and/or YTHDF2 in a blood sample from the patient;
b) comparing the level(s) of expression to a control sample(s) or control level(s) of expression; and,
c) prognosing the patient and/or evaluating treatment for the patient based on the levels of measured expression.
170. The method of claim 169, wherein the cancer patient was determined to have consensus molecular subtype 4 (CMS4) cancer.
171. The method of any of claims 169-170, wherein at least FTO is measured.
172. The method of claim 171, wherein FTO expression is upregulated.
173. The method of any of claims 169-170, wherein at least METTL3 is measured.
174. The method of claim 173, wherein METTL3 expression is upregulated.
175. The method of any of claims 169-170, wherein at least WTAP is measured.
176. The method of claim 175, wherein WTAP expression is upregulated.
177. The method of any of claims 169-170, wherein at least ALKBH5 is measured.
178. The method of claim 177, wherein ALKBH5 expression is upregulated.
179. The method of any of claims 169-170, wherein at least METTL14 is measured.
180. The method of claim 179, wherein METTL14 expression is downregulated.
181. The method of any of claims 169-170, wherein at least YTHDF1 is measured.
182. The method of claim 181, wherein YTHDF1 expression is downregulated.
183. The method of any of claims 169-170, wherein at least YTHDF2 is measured.
184. The method of claim 183, wherein YTHDF2 expression is downregulated.
185. The method of any of claims 169-184, wherein the levels of expression of at least two listed biomarkers is measured.
186. The method of claim 185, wherein the levels of expression of at least three listed biomarkers is measured.
187. The method of claim 186, wherein the levels of expression of at least four listed biomarkers is measured.
188. The method of claim 187, wherein the levels of expression of at least five listed biomarkers is measured.
189. The method of claim 188, wherein the levels of expression of at least six listed biomarkers is measured.
190. The method of claim 189, wherein the levels of expression of at least seven listed biomarkers is measured.
191. The method of any of claims 169-190, wherein the expression level of no other biomarker in the biological sample is measured.
192. The method of any of claims 169-191, wherein at least one of the listed bio markers is excluded from being measured.
193. The method of claim 192, wherein at least two of the listed biomarkers are excluded from being measured.
194. The method of any of claims 169-193, further comprising comparing the level(s) of expression to a control sample(s) or control level(s) of expression.
195. The method of claim 194, wherein the control sample(s) have expression levels that are representative of normal colorectal cells, cancer cells from patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with CMS 1 cancer, cancer cells from patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from p a cohort of atients with CMS4 cancer, cancer cells from a cohort of patients with a risk of recurrence less than 50%, and/or cancer cells from a cohort of patients with a risk of recurrence greater than 50%.
196. The method of claim 195, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
197. The method of claim 195, wherein the control sample(s) have expression levels that are representative of samples from cancer patients with a risk of surviving 5 years disease- free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer.
198. The method of claim 195, wherein the control level(s) of expression are representative of expression levels in samples from cancer patients with a risk of surviving 5 years disease- free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
199. The method of claim 195, wherein the control sample(s) have expression levels that are representative of cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
200. The method of any of claims 169-199, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
201. The method of claim 200, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP are downregulated and/or ALKBH5; METTL14, YTHDF1 and/or YTHDF2 are upregulated as compared to cells from patients with CMS 1 cancer or b) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
202. The method of claim 200 or 201, wherein the patient is identified as in the low-risk survivor cohort or as likely not to have recurrent cancer.
203. The method of any of claims 169-199, wherein 1, 2, 3, 4, 5, 6, or 7 measured expression levels of the listed biomarkers in the biological sample from the patient are a) differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low-risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or b) are not differentially expressed as compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
204. The method of claim 203, wherein either
a) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are downregulated as compared to cancer patients with a risk of surviving 5 years disease-free that is greater than 50% (low- risk survivor cohort), cancer cells from a cohort of patients with non-recurrent cancer, or from cancer cells from a cohort of patients with CMS 1 cancer or
b) the levels of expression of 1) FTO, METTL3, WTAP and/or ALKBH5 are not upregulated and/or 2) METTL14, YTHDF1 and/or YTHDF2 are not downregulated compared to the levels of expression in cancer patients with a risk of surviving 5 years disease-free that is less than 50% (high-risk survivor cohort), cancer cells from a cohort of patients with recurrent cancer, or from cancer cells from a cohort of patients with CMS4 cancer.
205. The method of claim 203 or 204, wherein the patient is identified as in the high-risk survivor cohort or as likely to have recurrent cancer.
206. The method of claim 205, wherein the patient is administered an FTO inhibitor.
207. The method of claim 206, wherein the FTO inhibitor is a small molecule, nucleic acid, or protein.
208. The method of claim 206 or 207, wherein the FTO inhibitor inhibits FTO expression.
209. The method of claim 206 or 207, wherein the FTO inhibitor inhibits FTO activity.
210. The method of any of claims 207-209, wherein the nucleic acid is an siRNA or miRNA.
211. The method of any of claims 207-209, wherein the protein is an FTO-specific binding protein or peptide.
212. The method of claim 211, wherein the FTO-specific binding protein comprises all or part of an antibody.
213. The method of any of claims 169-207, wherein the biological sample is a blood sample, a tissue sample, a tumor sample, fecal sample, or a colorectal sample.
214. The method of any of claims 169-213, further comprising treating the patient for cancer after measuring the level of expression of one or more listed biomarkers.
215. The method of claim 214, wherein the treatment comprises chemotherapy, radiation, and/or surgery.
216. The method of any of claims 169-215, wherein expression is measured using one or more hybridization and/or amplification assays.
217. The method of claim 216, wherein the assay comprises polymerase chain reaction.
218. The method of any of claims 123-217, wherein a cohort comprises at least 50, 100, 200, 300, 400, 500 or more patients.
219. The method of any one of claims 1-218, wherein the patient has and/or has been determined to have cancer.
220. The method of claim 219, wherein the cancer comprises colorectal cancer, gastric cancer, breast cancer, ovarian cancer, pancreatic adenocarcinoma, hepatocellular carcinoma, lung adenocarcinoma, bladder urothelial carcinoma, head and neck squamous cell carcinoma, acute myeloid leukemia, lung squamous cell carcinoma, esophageal adenocarcinoma, or esophageal squamous cell carcinoma.
221. The method of claim 220, wherein the cancer comprises colorectal cancer.
222. A pharmaceutical composition comprising an FTO inhibitor.
223. The composition of claim 222, wherein the FTO inhibitor is a small molecule, nucleic acid, or protein.
224. The composition of claim 222 or 223, wherein the FTO inhibitor inhibits FTO expression.
225. The composition of claim 222 or 223, wherein the FTO inhibitor inhibits FTO activity.
226. The composition of any of claims 223-225, wherein the nucleic acid is an siRNA or miRNA.
227. The composition of any of claims 223-225, wherein the protein is an FTO-specific binding protein or peptide.
228. The composition of claim 227, wherein the FTO-specific binding protein comprises all or part of an antibody.
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