WO2019178216A1 - Méthodes et compositions pour le traitement, le diagnostic et le pronostic du cancer des ovaires - Google Patents

Méthodes et compositions pour le traitement, le diagnostic et le pronostic du cancer des ovaires Download PDF

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WO2019178216A1
WO2019178216A1 PCT/US2019/022035 US2019022035W WO2019178216A1 WO 2019178216 A1 WO2019178216 A1 WO 2019178216A1 US 2019022035 W US2019022035 W US 2019022035W WO 2019178216 A1 WO2019178216 A1 WO 2019178216A1
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mir
expression
measured
levels
patient
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PCT/US2019/022035
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English (en)
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Ajay Goel
Raju KANDIMALLA
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Baylor Research Institute
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Priority to CN201980031953.5A priority Critical patent/CN112154217A/zh
Publication of WO2019178216A1 publication Critical patent/WO2019178216A1/fr

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    • 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
    • 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
    • C12Q2600/112—Disease subtyping, staging or classification
    • 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
    • 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
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

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.
  • Ovarian cancer is the most lethal gynecological malignancy among women in United States and around the world [1]. About 75% of patients are diagnosed at late stage disease where the tumor has spread in to the abdomen and thereby the 5- year survival rates are mere 10-30% [2]. Though the survival rates in stage I is 90% [1], due to the lack of effective screening strategies and early detection markers, the inventors are unable to diagnose these patients early [3]. Routine pelvic examination and transvaginal ultrasound are not very efficient tools for population screening due to the poor sensitivity [4] . Since three decades serum CA125 protein levels has been routinely used in the clinic, however the sensitivity of CA125 is very poor in detecting early stage cancers and furthermore, it has limited specificity [5, 6].
  • the current disclosure relates to methods, compositions, and kits for treating ovarian cancer and for evaluation subjects. Aspects of the disclosure relate to a method for evaluating a patient comprising measuring the level of expression of one or more of the listed miRNAs in a biological sample from the patient: miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p.
  • FIG. 1 Further aspects relate to a method of beating a patient with ovarian cancer comprising administering chemotherapy and/or radiation and/or performing surgery to remove all or part of one or both ovaries after a biological sample from the patient has been measured for the level of expression of at least one of the listed biomarkers: miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p.
  • the listed biomarkers miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p.
  • a method of diagnosing a patient with ovarian cancer comprising a) measuring the level of expression in a biological sample from the patient of at least one of the listed biomarkers: miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR- 508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p; b) comparing the measured expression levels to conbol levels or conbol samples, wherein the control levels or conbol samples are representative of expression levels negative for ovarian cancer or positive for ovarian cancer; c) diagnosing the patient with ovarian cancer if at least one measured expression levels is increased as compared to representative levels of expression in normal ovarian cells or determining the patient does not have ovarian cancer based on the measured expression levels.
  • kits comprising 1 , 2, 3, 4, 5, 6, 7, or 8 probes or primer sets for determining expression levels of miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, and/or miR-513c-5p.
  • at least the listed biomarker of miR-182-5p is measured.
  • at least the listed biomaiker of miR-183-5p is measured.
  • at least the listed biomarker of miR-202-3p is measured.
  • at least the listed biomarker of miR-205-5p is measured.
  • At least the listed biomaiker of miR-508-3p is measured. In some embodiments, at least the listed biomaiker of miR-509-3-5p is measured. In some embodiments, at least the listed biomaiker of miR-513b-5p is measured. In some embodiments, at least the listed biomarker of miR-513c- 5p is measured. In some embodiments, the levels of expression of at least two listed biomarkers are measured. In some embodiments, the levels of expression of at least three listed biomarkers are measured. In some embodiments, the levels of expression of at least four listed biomarkers are measured. In some embodiments, the levels of expression of at least five listed biomaikers are measured. In some embodiments, the levels of expression of at least six listed biomarkers are measured. In some embodiments, the levels of expression of at least seven listed biomaikers are measured. In some embodiments, the levels of expression of all eight listed biomaikers are measured.
  • the method comprises or further comprises measuring the level of expression in a biological sample from the patient of at least one biomarker in FIG. 7 that is not one of the listed biomaikers. In some embodiments, at least two additional biomaikers of FIG. 7 are measured. In some embodiments, at least four additional biomarkers in FIG. 7 are measured. In some embodiments, at least 6 additional biomaikers in FIG. 7 are measured. In some embodiments, at least one of miR-182-5p, miR-183-5p, miR-202-3p, miR- 205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p is excluded from being measured.
  • At least two of miR-182-5p, miR-183-5p, miR-202-3p, miR- 205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p are excluded from being measured. In some embodiments, at least three of miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, or miR-513c-5p are excluded from being measured.
  • the method 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 ovarian cells.
  • the control sample(s) have expression levels that are representative of the level of expression in a biological sample from patients not having ovarian cancer.
  • the control expression level(s) are the level of expression in a biological sample from a patient without ovarian cancer.
  • the control level(s) of expression are representative of expression levels in samples negative for ovarian cancer.
  • the control sample(s) have expression levels that are representative of samples positive for ovarian cancer.
  • control sample(s) have expression levels that are representative of ovarian cancer cells. In some embodiments, the control sample(s) have expression levels that are representative of the level of expression in a biological sample from a patient or patients with ovarian cancer. In some embodiments, the control expression level(s) are expression levels in a biological sample from a patient with ovarian cancer.
  • At least one measured expression level of the listed biomarkers in the biological sample from the patient is reduced compared to the levels of expression in ovarian cancer cells or is within the range of expression representative of normal ovarian cells. In some embodiments, at least two measured expression levels of the listed biomarkers in the biological sample from the patient are reduced compared to the levels of expression in ovarian cancer cells or are within the range of expression representative of normal ovarian cells. In some embodiments, at least three measured expression levels of the listed biomarkers in the biological sample from the patient are reduced compared to the levels of expression in ovarian cancer cells or are within the range of expression representative of normal ovarian cells.
  • At least four measured expression levels of the listed biomarkers in the biological sample from the patient are reduced compared to the levels of expression in ovarian cancer cells or are with the range of expression representative of normal ovarian cells. In some embodiments, at least five measured expression levels of the listed biomarkers in the biological sample from the patient are reduced compared to the levels of expression in ovarian cancer cells or are with the range of expression representative of normal ovarian cells. In some embodiments, at least six measured expression levels of the listed biomarkers in the biological sample from the patient is reduced compared to the levels of expression in ovarian cancer cells or is with the range of expression representative of normal ovarian cells.
  • At least seven measured expression levels of the listed biomarkers in the biological sample from the patient is reduced compared to the levels of expression in ovarian cancer cells or is with the range of expression representative of normal ovarian cells. In some embodiments, all eight measured expression levels of the listed biomarkers in the biological sample from the patient is reduced compared to the levels of expression in ovarian cancer cells or is with the range of expression representative of normal ovarian cells. [0014] In some embodiments, at least one measured expression level of the listed biomaikers in the biological sample from the patient is increased compared to the levels of expression in normal ovarian cells or is within the range of expression representative of ovarian cancer cells.
  • At least two measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells. In some embodiments, at least three measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells. In some embodiments, at least four measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells.
  • At least five measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells. In some embodiments, at least six measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells. In some embodiments, at least seven measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells. In some embodiments, all eight measured expression levels of the listed biomaikers in the biological sample from the patient are increased compared to the levels of expression in normal ovarian cells or are within the range of expression representative of ovarian cancer cells.
  • the at least two biomarkers comprise miR-182-5p and miR- 183-5p. In some embodiments, the at least two biomaikers comprise miR-182-5p and miR- 202-3p. In some embodiments, the at least two biomaikers comprise miR-182-5p and miR- 205-5p. In some embodiments, the at least two biomaikers comprise miR-182-5p and miR- 508-3p. In some embodiments, the at least two biomaikers comprise miR-182-5p and miR-
  • the at least two biomaikers comprise miR-182-5p and miR- 513b-5p. In some embodiments, the at least two biomarkers comprise miR-182-5p and miR- 513c-5p. In some embodiments, the at least two biomaikers comprise miR-183-5p and miR- 202-3p. In some embodiments, the at least two biomarkers comprise miR-183-5p and miR- 205-5p. In some embodiments, the at least two biomaikers comprise miR-183-5p and miR-
  • the at least two biomarkers comprise miR-183-5p and miR-
  • the at least two biomarkers comprise miR-183-5p and miR- 513b-5p. In some embodiments, the at least two biomarkers comprise miR-183-5p and miR- 513c-5p. In some embodiments, the at least two biomarkers comprise miR-202-3p and miR-
  • the at least two biomarkers comprise miR-202-3p and miR-
  • the at least two biomarkers comprise miR-202-3p and miR-
  • the at least two biomarkers comprise miR-202-3p and miR- 513b-5p. In some embodiments, the at least two biomarkers comprise miR-202-3p and miR- 513c-5p. In some embodiments, the at least two biomarkers comprise miR-205-5p and miR-
  • the at least two biomarkers comprise miR-205-5p and miR-
  • the at least two biomarkers comprise miR-205-5p and miR- 513b-5p. In some embodiments, the at least two biomarkers comprise miR-205-5p and miR- 513c-5p. In some embodiments, the at least two biomarkers comprise miR-508-3p and miR- 509-3-5p. In some embodiments, the at least two biomaikers comprise miR-508-3p and miR-
  • the at least two biomarkers comprise miR-508-3p and miR- 513c-5p. In some embodiments, the at least two biomaikers comprise miR-509-3-5p and miR- 513b-5p. In some embodiments, the at least two biomarkers comprise miR-509-3-5p and miR- 513c-5p. In some embodiments, the at least two biomarkers comprise miR-513b-5p and miR- 513c-5p.
  • the at least three biomarkers comprise miR-182-5p, miR- 183-5p, and miR-202-3p. In some embodiments, the at least three biomaikers comprise miR- 182-5p, miR-183-5p, and miR-205-5p. In some embodiments, the at least three biomaikers comprise miR-182-5p, miR-183-5p, and miR-508-3p. In some embodiments, the at least three biomaikers comprise miR-182-5p, miR-183-5p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-183-5p, and miR-513b-5p.
  • the at least three biomaikers comprise miR-182-5p, miR-183-5p, and miR-513c- 5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-183-5p, and miR-202-3p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-202-3p, and miR-205-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-202-3p, and miR-508-3p. In some embodiments, the at least three biomaikers comprise miR-182-5p, miR-202-3p, and miR-509-3-5p.
  • the at least three biomarkers comprise miR-182-5p, miR-202-3p, and miR-513b-5p. In some embodiments, the at least three biomaikers comprise miR-182-5p, miR-202-3p, and miR-513c- 5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-205-5p, and miR-508-3p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-205-5p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-205-5p, and miR-513b-5p.
  • the at least three biomarkers comprise miR-182-5p, miR-205-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-508-3p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-508-3p, and miR-513b- 5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-508-3p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-509-3-5p, and miR-513b-5p.
  • the at least three biomarkers comprise miR-182-5p, miR-509-3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-182-5p, miR-513b-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-202-3p, and miR-205- 5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-202-3p, and miR-508-3p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-202-3p, and miR-509-3-5p.
  • the at least three biomarkers comprise miR-183-5p, miR-202-3p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-202-3p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-205-5p, and miR-508-3p. In some embodiments, the at least three biomarkers comprise miR- 183-5p, miR-205-5p, and miR-509-
  • the at least three biomarkers comprise miR-183-5p, miR-205-5p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-205-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-508-3p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR- 183-5p, miR-508-3p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-508-3p, and miR-513c-5p.
  • the at least three biomarkers comprise miR-183-5p, miR-509-3-5p, and miR- 513b-5p. In some embodiments, the at least three biomarkers comprise miR-183-5p, miR-509- 3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR- 183-5p, miR-513b-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-205-5p, and miR-508-3p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-205-5p, and miR-509-3-5p.
  • the at least three biomarkers comprise miR-202-3p, miR-205-5p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-205-5p, and miR-513c- 5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-508-3p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR-202- 3p, miR-508-3p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-508-3p, and miR-513c-5p.
  • the at least three biomarkers comprise miR-202-3p, miR-509-3-5p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-509-3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-202-3p, miR-513b-5p, and miR- 513c-5p. In some embodiments, the at least three biomarkers comprise miR-205-5p, miR-508- 3p, and miR-509-3-5p. In some embodiments, the at least three biomarkers comprise miR- 205-5p, miR-508-3p, and miR-513b-5p.
  • the at least three biomarkers comprise miR-205-5p, miR-508-3p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-205-5p, miR-509-3-5p, and miR-513b-5p. In some embodiments, the at least three biomarkers comprise miR-205-5p, miR-509-3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-205-5p, miR-513b-5p, and miR- 513c-5p. In some embodiments, the at least three biomarkers comprise miR-508-3p, miR-509-
  • the at least three biomarkers comprise miR- 508-3p, miR-509-3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-508-3p, miR-513b-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-509-3-5p, miR-509-3-5p, and miR-513c-5p. In some embodiments, the at least three biomarkers comprise miR-509-3-5p, miR-513b-5p, and miR- 513c-5p.
  • the biological sample is a tissue sample, a tumor sample, a lymph node sample, blood, serum, saliva, or squamous cell sample. In some embodiments, the biological sample is a serum sample. In some embodiments, the biological sample comprises nucleic acids. In some embodiments, the biological sample is a fractionated sample comprising nucleic acids. In some embodiments, the biological sample is a franctionated sample that is enriched for nucleic acids. In some embodiments, the biological sample is a sample comprising ovarian cells.
  • the patient has symptoms of ovarian cancer. In some embodiments, the patient does not have symptoms of ovarian cancer. In some embodiments, the patient has undergone a previous screening procedure for ovarian cancer. In some embodiments, the patient has not undergone a previous screening procedure for ovarian cancer.
  • the method further comprises diagnosing the patient with ovarian cancer based on one or more measured levels of expression of the listed biomarkers in the patient's biological sample.
  • the patient is diagnosed with stage I or stage II cancer based on the expression level of at least one listed biomarker.
  • the method further comprises treating the patient for ovarian cancer after measuring the level of expression of one or more listed biomarkers.
  • the patient is treated after measuring an increased level of expression of at least one listed biomarkers as compared to normal ovarian cells.
  • the patient is treated after measuring an increased level of expression of at least two listed biomarkers as compared to normal ovarian cells.
  • the patient is treated after measuring an increased level of expression of at least three listed biomarkers as compared to normal ovarian cells.
  • the patient is treated after measuring an increased level of expression of at least four listed biomarkers as compared to normal ovarian cells.
  • the patient is treated after measuring an increased level of expression of at least five listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is treated after measuring an increased level of expression of at least six listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is treated after measuring an increased level of expression of at least seven listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is treated after measuring an increased level of expression of all eight listed biomarkers as compared to normal ovarian cells.
  • the patient has been diagnosed with ovarian cancer based on the expression levels of one or more listed biomarkers. In some embodiments, patient has been diagnosed with ovarian cancer based on increased expression levels of all eight listed biomarkers as compared to the expression levels indicative of normal ovarian cells. In some embodiments, the pathology of one or more ovarian cells is analyzed. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least one listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least two listed biomarkers as compared to normal ovarian cells.
  • the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least three listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least four listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least five listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least six listed biomarkers as compared to normal ovarian cells.
  • the patient is diagnosed with ovarian cancer after measuring an increased level of expression of at least seven listed biomarkers as compared to normal ovarian cells. In some embodiments, the patient is diagnosed with ovarian cancer after measuring an increased level of expression of all eight listed biomarkers as compared to normal ovarian cells.
  • control sample(s) have expression levels that are representative of samples negative for ovarian cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples negative for ovarian cancer. In some embodiments, the control sample(s) have expression levels that are representative of samples positive for ovarian cancer. In some embodiments, the control level(s) of expression are representative of expression levels in samples positive for ovarian cancer.
  • control sample(s) have expression levels that are representative of biological samples from a patient that is negative for ovarian cancer. In some embodiments, the control level(s) of expression are representative of expression levels in biological samples from a patient that is negative for ovarian cancer. In some embodiments, the control sample(s) have expression levels that are representative of biological samples from patients that are positive for ovarian cancer. In some embodiments, the control level(s) of expression are representative of expression levels in biological samples from patients that are positive for ovarian cancer.
  • the ovarian cancer is Stage I or Stage P.
  • the pathology of the patient’s ovarian cells have been analyzed.
  • the biomarkers a human biomarkers.
  • the biomarkers are mammalian biomarkers.
  • the biomarkers comprise a mature and/or processed miRNA.
  • 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 from the ovaries, a polyp, the uterus, mucosa or submucosa.
  • the sample is from a surgically removed polyp.
  • 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, ovary, 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 mine 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.
  • the cyst, tumor or neoplasm is in the reproductive system.
  • 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.
  • 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,
  • 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,
  • the prognosis score is 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).
  • 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.” It is specifically contemplated that x, y, or z may be specifically excluded from an embodiment.
  • 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.
  • 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-C Discovery and Independent Tissue Validation of OCaMIR.
  • RNA sequencing Differentially expressed miRNAs between stage I ovarian cancer vs. normal with an adjusted p-value of less than 0.05 and absolute log fold change of 2 from the small RNA sequencing.
  • 24 are downregulated (in black) and 8 are upregulated (in red) in ovarian cancer
  • FIG. 2A-E OCaMIR assay serum independent training and validation across four retrospective and one prospective cohorts.
  • ROC curves and risk-score plots of OCaMIR A) Serum retrospective training cohort; GSE106817 miRNA micro array, B) Serum retrospective validation cohort 1; GSE31568 miRNA microarray, C) Serum retrospective validation cohort 2; GSE 113486 miRNA microarray, D) Serum retrospective validation cohort 3; Czech
  • FIG. 3A-D Evaluation of OCaMIR assay performance in detecting stage I ovarian cancer in serum as well as its specificity for ovarian cancer detection.
  • ROC curves and stage- wise risk-score plots of OCaMIR A) Serum retrospective training cohort; GSE106817 miRNA microarray, B) Serum retrospective validation cohort 3; Czech Republic RT-PCR, C) Serum prospective validation cohort; West China RT-PCR and D) ROC curves of OCaMIR assay across various diseases including ovarian cancer.
  • FIG. 4 Individual miRNA expression levels between cancer vs. healthy across all serum cohorts
  • FIG. 5 Individual miRNA expression levels between cancer vs. healthy across all serum cohorts.
  • FIG. 6 Workflow of biomarker discovery.
  • FIG. 8 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.99 and 0.998 in cohort.
  • FIG. 9. A heatmap of the identified 8-miRNA signature and the risk score curve.
  • Tumors enriched with high risk scores and miRNAs signature in cohort are associated with high risk scores and miRNAs signature in cohort.
  • FIG. 10 Phase P: In silico validation of the diagnostic value of the 8-miRNA signature.
  • FIG. 11 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.96 and 0.974 in TCGA (stage I and normal).
  • FIG. 12 A heatmap of the identified 8-miRNA signature and the risk score curve. Tumors enriched with high risk scores and miRNAs signature in TCGA (stage I and normal).
  • FIG. 13 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.96 and 0.974 in TCGA (stage I, stage P and normal).
  • FIG. 14 A heatmap of the identified 8-miRNA signature and the risk score curve. Tumors enriched with high risk scores and miRNAs signature in TCGA (stage I, stage P and normal).
  • FIG. 15 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.89 and 0.998 in TCGA (all).
  • FIG. 16 A heatmap of the identified 8-miRNA signature and the risk score curve. Tumors enriched with high risk scores and miRNAs signature in TCGA (all).
  • FIG. 17 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.83 and 0.98 in GSE65819 (primary and normal).
  • ROC Receiver operating characteristic
  • PRC precision recall
  • FIG. 18 A heatmap of the identified 8-miRNA signature and the risk score curve.
  • FIG. 19 Receiver operating characteristic (ROC) and precision recall (PRC) of the 8-miRNA signature are 0.81 and 0.94 in GSE65819 (ascites and normal).
  • FIG. 20 A heatmap of the identified 8-miRNA signature and the risk score curve.
  • 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 inventors identified a panel of eight miRNAs that are highly accurate in identifying early stage ovarian cancer.
  • the identified tissue miRNA markers were independently validated in multiple retrospective tissue and serum cohorts from different ethnicities by developing a multivariate logistic regression based classifier.
  • 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, 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 is an average level of expression determined from a cohort of subjects with cancer or without cancer.
  • the reference level may also be depicted graphically as an area on a graph.
  • a reference level is a normalized level, while in other embodiments, it may be a level that is not stable with respect to the tissue or biological sample being tested.
  • determining or“evaluating” as used herein may refer to measuring, quantitating, or quantifying (either qualitatively or quantitatively).
  • microRNAs may be used in methods and compositions for determining the prognosis, for diagnosing subjects, for determining a response to a particular cancer treatment, of a particular patient, and for treating individuals with esophageal cancer.
  • MiRNAs may be naturally occurring, small non-coding RNAs that are about 17 to about 25 nucleotide bases (nt) in length in their biologically active form. miRNAs post- transcriptionally regulate gene expression by repressing target mRNA translation. It is thought that miRNAs function as negative regulators, i.e. greater amounts of a specific miRNA will correlate with lower levels of target gene expression.
  • pri- miRNAs There may be three forms of miRNAs existing in vivo, primary miRNAs (pri- miRNAs), premature miRNAs (pre-miRNAs), and mature miRNAs.
  • Primary miRNAs are expressed as stem-loop structured transcripts of about a few hundred bases to over 1 kb.
  • the pri-miRNA transcripts are cleaved in the nucleus by an RNase II endonuclease called Drosha that cleaves both strands of the stem near the base of the stem loop. Drosha cleaves the RNA duplex with staggered cuts, leaving a 5' phosphate and 2 nt overhang at the 3' end.
  • the cleavage product, the premature miRNA (pre-miRNA) may be about 60 to about
  • Pre-miRNA is transported from the nucleus to the cytoplasm by Ran-GTP and Exportin-5.
  • Pre-miRNAs are processed further in the cytoplasm by another RNase P endonuclease called Dicer.
  • Dicer recognizes the 5 ' phosphate and 3 ' overhang, and cleaves the loop off at the stem-loop junction to form miRNA duplexes.
  • the miRNA duplex binds to the RNA-induced silencing complex (RISC), where the antisense strand is preferentially degraded and the sense strand mature miRNA directs RISC to its target site.
  • RISC RNA-induced silencing complex
  • miRNAs function by engaging in base pairing (perfect or imperfect) with specific sequences in their target genes' messages (mRNA). The miRNA degrades or represses translation of the mRNA, causing the target genes' expression to be post-transcriptionally down-regulated, repressed, or silenced. In animals, miRNAs do not necessarily have perfect homologies to their target sites, and partial homologies lead to translational repression, whereas in plants, where miRNAs tend to show complete homologies to the target sites, degradation of the message (mRNA) prevails.
  • MicroRNAs are widely distributed in the genome, dominate gene regulation, and actively participate in many physiological and pathological processes. For example, the regulatory modality of certain miRNAs is found to control cell proliferation, differentiation, and apoptosis; and abnormal miRNA profiles are associated with oncogenesis. Additionally, it is suggested that viral infection causes an increase in miRNAs targeted to silence“pro-cell survival” genes, and a decrease in miRNAs repressing genes associated with apoptosis (programmed cell death), thus tilting the balance toward gaining apoptosis signaling.
  • Methods and compositions may be provided for treating ovarian cancer with particular applications of biomarkers. Based on a profile of biomarkers, different treatments may be prescribed or recommended for different cancer patients and patient populations.
  • the type of cell where the cancer begins determines the type of ovarian cancer present.
  • Ovarian cancer types include: epithelial tumors, which begin in the thin layer of tissue that covers the outside of the ovaries; stromal tumors, which begin in the ovarian tissue that contains hormone-producing cells; and germ cell tumors, which begin in the egg-producing cells.
  • the cancer comprises an epithelial tumor.
  • the cancer comprises a stromal tumor.
  • the cancer comprises a germ cell tumor.
  • T relates to the size of the tumor and is classified by determining the spread of the ovary to the fallopian tube and/or to nearby pelvic organs such as the uterus or bladder.
  • N relates to the spread of the tumor to lymph nodes. N is determined by determining the spread of the tumor to the lymph nodes in the pelvis or around the aorta.
  • M relates to whether the tumor has metastasized.
  • the staging system in the table below uses the pathologic stage (also called the surgical stage). It can be determined by examining tissue removed during an operation. This is also known as surgical staging. Sometimes, if surgery is not possible right away, the cancer will be given a clinical stage instead. This is based on the results of a physical exam, biopsy, and imaging tests done before surgery.
  • The“cancer” referred to in the methods described herein may include or exclude any of the above stages or TNM categories.
  • the cancer may be or may exclude stage I, IA, IB, IC, P, PA, PB, PIAI, IPA2, IPB, IIIC, IV A, and/or IVB.
  • the patient may be one that has and/or has been determined to have stage I, IA, IB, IC, P, PA, IIB, PIAI, PIA2, IPB, IIIC, IV A, and/or IVB cancer.
  • the cancer may be classified or further classified as Tl, NO, and/or M0; Tla, NO, and/or M0; Tib, NO, and/or M0; Tic, NO, and/or M0; T2, NO, and/or M0; T2a, NO, and/or M0; T2b, NO, and/or M0; Tl, T2, and/or Nl; M0, T3a, NO and/or Nl; M0, T3b, NO, and/or Nl; M0, T3c, NO, Nl and/or M0; Any T, Any N, and/or Mia; Any T Any N, and/or Mlb.
  • Treatment of ovarian cancer usually involves a combination of surgery and chemotherapy. Treatments of ovarian cancer include those described below.
  • Operations to remove ovarian cancer include: 1) Surgery to remove one ovary. For very early stage cancer that hasn't spread beyond one ovary, surgery may involve removing the affected ovary and its fallopian tube. 2) Surgery to remove both ovaries. If cancer is present in both ovaries, but there are no signs of additional cancer, a surgeon may remove both ovaries and both fallopian tubes. 3) Surgery to remove both ovaries and the uterus. If your cancer is more extensive or if you don't wish to preserve your ability to have children, your surgeon will remove the ovaries, the fallopian tubes, the uterus, nearby lymph nodes and a fold of fatty abdominal tissue (omentum).
  • Chemotherapy may be used in a neoadjuvant or adjuvant setting.
  • Chemotherapy drugs are typically either injected into a vein, taken by mouth, or administered intraperioneally.
  • the patient is administered a chemotherapy.
  • Exemplary chemotherapeutic regimens include carboplatin and paclitaxel or combinations thereof.
  • Other exemplary chemotherapeutic regimens include cisplatin and docetaxel, and combinations thereof.
  • Further chemotherapeutic treatment regimens that may be used in embodiments of the disclosure include cisplatin, etoposide, bleomycin, and combinations thereof. In some embodiments, a combination of carboplatin and etoposide is used.
  • 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-mercaptopur
  • 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/m 2 to about 75 mg/m 2 at about 21-day intervals or about 25 mg/m 2 to about 30 mg/m 2 on each of 2 or 3 successive days repeated at about 3 week to about 4 week intervals or about 20 mg/m 2 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 (HN 2 ), 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.
  • Targeted therapy uses medications that target the specific vulnerabilities present within your cancer cells.
  • Targeted therapy drugs are usually reserved for treating ovarian cancer that returns after initial treatment or cancer that resists other treatments. Your doctor may test your cancer cells to determine which targeted therapy is most likely to have an effect on your cancer.
  • An exemplary targeted therapy includes bevacizumab.
  • Further therapies include olaparib (Lynparza), rucaparib (Rubraca), and niraparib (Zejula).
  • 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).
  • 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.
  • Further therapeutic include hormone therapy, leuprolide, goserelin (Zoladex), tamoxifen, or an aromatase inhibitor.
  • 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-1 can act in the tumor microenvironment where T cells encounter an infection or tumor. Activated T cells upregulate PD-1 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- 1 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-1 and/or PDL1 activity.
  • Alternative names for“PD-1” include CD279 and SLEB2.
  • Alternative names for“PD-1” include CD279 and SLEB2.
  • PDL1 include B7-H1, B7-4, CD274, and B7-H.
  • Alternative names for“PDL2” include B7- DC, Btdc, and CD273.
  • PD-1, PDL1, and PDL2 are human PD-1, PDL1 and PDL2.
  • the PD-1 inhibitor is a molecule that inhibits the binding of PD-1 to its ligand binding partners.
  • the PD-1 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-1 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-1.
  • 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-1 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, US2014/022021, and US2011/0008369, all incorporated herein by reference.
  • the PD-1 inhibitor is an anti-PD-1 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-1 inhibitor is an immunoadhesin (e.g., an immunoadhesin comprising an extracellular or PD-1 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-1 antibody described in
  • Pembrolizumab also known as MK-3475, Merck 3475, lambrolizumab, KEYTRUDA ® , and SCH-900475, is an anti-PD-1 antibody described in W02009/114335.
  • Pidilizumab also known as CT-011, hBAT, or hBAT-1, is an anti-PD-1 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-1 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 rHIgM12B7.
  • 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-1, 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., 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 et 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. W02001/014424, 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. In another embodiment, the antibody competes for binding with and/or binds to the same epitope on PD-1, B7-1, or B7-2 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.
  • 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.
  • 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
  • GM-CSF granulocyte macrophage colony-stimulating factor
  • 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 CD19.
  • 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 IRNb), type P (IFNy) and type IP (IFNX).
  • 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.
  • a therapy described herein is excluded in the methods and/or compositions of the disclosure.
  • 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.
  • the patient is one that has been determined to be resistant to a therapy described herein.
  • the patient is one that has been determined to be sensitive to a therapy described herein.
  • Methods of the disclosure may include tests and exams either pre-operatively or post-operatively to monitor the ovaries. Monitoring methods may include a pelvic exam, imaging tests such as and ultrasound or CT scan or the abdomen and pelvis, and blood tests that test for organ function and overall health.
  • ovarian cancer markers such as CA125 may be tested for in methods of the disclosure. It is also contemplated that the methods of the disclosure may include one or more monitoring techniques. Certain embodiments exclude testing the patient for CA125 levels.
  • 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 curve was first developed by electrical engineers and radar engineers during World War P for detecting enemy objects in battlefields and was soon introduced to psychology to account for perceptual detection of stimuli. ROC analysis since then has been used in medicine, radiology, biometrics, and other areas for many decades and is increasingly used in machine learning and data mining research.
  • 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.
  • a ROC analysis may be used to create cut-off values for prognosis and/or diagnosis purposes.
  • 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, hi 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.
  • 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 ait 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, 10-fold, 100-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 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, 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,
  • 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, 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.
  • 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-gen
  • 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 miRNA 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.
  • miRNA 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.
  • 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.
  • arrays 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.
  • RNAs 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).
  • HPA hybridization protection assay
  • bDNA branched DNA
  • RCA rolling circle amplification
  • US Genomics Invader assay
  • GTWave Technologies Invader assay
  • Bridge Litigation Assay Geneaco
  • 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. 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.
  • 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.
  • 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 mM; or about 50 mM to 150 mM; or about 50 mM to 100 mM (or any range derivable therein).
  • 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,
  • 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.
  • 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.
  • kits containing compositions of the invention or compositions to implement methods of the invention.
  • kits can be used to evaluate one or more miRNA molecules.
  • 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.
  • there are kits for evaluating biomarker activity in a cell 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.
  • 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.
  • 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 miRNA.
  • 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.
  • ovarian cancer still remains as a deadly disease with highest mortality among other gynecological cancers. So far there have been no attempts to discover biomarkers using early stage OC patients.
  • MicroRNAs miRNAs have been recognized as great tool to develop non- invasive biomarkers in various cancers including ovarian cancer.
  • OCaMIR miRNAs
  • Taqman based RT-PCR assays were used for the analysis of OCaMIR in Czech Republic and West China Cohorts.
  • OCaMIR achieved an AUC of 0.88 in the tissue discovery cohort for detecting stage I OC and an AUC of 0.90 for stage I and 0.99 for all stages in the TCGA and 0.98 in GSE65819 independent tissue validation cohorts.
  • the logistic regression based training and validation of OCaMIR achieved an AUC of 0.86 (GSE106817), 0.84 (GSE31568), 0.87 (GSE113486), and 0.91 (Czech Republic Cohort) in the retrospective serum validation cohorts.
  • the prospective validation of OCaMIR achieved an AUC of 0.92 in the West China cohort.
  • the performance of OCaMIR was superior to CA125 and is highly specific for OC detection.
  • OCaMIR showed excellent precision in detecting OC both at tissue and serum level across multiple independent cohorts spanning various ethnic backgrounds and thereby provides an excellent tool for the early detection and population screening of OC.
  • Exciting prospective validation results using RT-PCR based assays in an independent lab highlights the adaptability of this assay in to the clinics.
  • the performance of OCaMIR in stage I OC detection, the superiority over CA125, high OC specificity and being cost effective for screening makes this assay standout from previously identified biomarkers.
  • the inventors have acquired a total of 22 fresh frozen stage I high-grade serous epithelial ovarian cancer specimens and 9 adjacent normal fallopian tube tissues from Asterand biobank. Tumors were staged in accordance with the FIGO (The International Federation of Gynecology and Obstetrics) criteria and an expert pathologist reviewed all pathological data. All the tissue samples included have greater than 70% tumor cellularity.
  • the inventors have used TCGA as well as GSE65819 [26] public cohorts for which the level 3 or preprocessed miRNA expression values and clinical data was downloaded from Broad GDAC Firehose, and Gene Expression Omnibus (GEO), respectively.
  • the inventors have used three previously published serum cohorts as well as two international independent external retrospective and prospective validation cohorts.
  • the public cohorts include GSE106817 [13], GSE113486 [27], and GSE31568 [28], for which the preprocessed miRNA expression values as well as clinical data was downloaded from GEO.
  • the retrospective serum cohort was collected at the Department of Comprehensive Cancer Care, Masaryk Memorial Cancer Institute, Faculty of Medicine, Masaryk University, Brno, Czech Republic, and sent to us on dry ice for the RT-PCR based validation. All the samples were collected before the treatment and at initial diagnosis of OC.
  • the inventors also received the CA125 levels that were tested at Masaryk Memorial Cancer Institute.
  • NGS library construction for miRNA from tissue was performed using a modified protocol for the Truseq Small RNA Kit (Illumina) with up to 200ng of total RNA input. Quality of individual libraries was assessed using the High Sensitivity DNA Kit (Agilent). Libraries were size selected individually ( ⁇ 148 nt) by gel electrophoresis using a Pippin HT instrument
  • Cutadapt software Post trimming, all the sequences contained high-quality scores and the peaks concentrated at 22 nt, representing microRNA. Clean reads were aligned to hg38 and annotated by“microRNA.subset.of.GENCODE.V24.gtf”. The mapping of the reads and obtaining counts of miRNA was done using the STAR aligner. Differential miRNAs expression analysis was done by limma [30] (Linear Models for Micro array and RNA-Seq Data package).
  • Raw sequencing data can be accessible as fastq files through the Gene Expression Omnibus
  • RNA enriched for small non-coding RNAs was extracted from 200 ul serum specimens using the miRNeasy serum kit (Qiagen, Valencia, CA) according to the manufacturer's instructions.
  • synthetic C. elegans miRNA cel-miR-39, Qiagen was added to each 200ul denatured serum.
  • the expression of miRNAs was quantified by TaqMan miRNA real- time qRT-PCR assays (Applied Biosystems, Foster City, CA) using QuantStudioTM 7 Flex Real-Time PCR System (Applied Biosystems).
  • BH Bojamini-Hochberg
  • Power calculation for the discovery phase was performed using“RNASeqPower” package in R [31], which resulted in power greater than 0.90.
  • limma Bioconductor package in R 3.2.4
  • An absolute log 2 fold change of 2 and BH corrected adjusted p-value of less than 0.05 were used to finalize the miRNA targets and subsequent model building.
  • a multivariate logistic regression model was built consisting of 8 upregulated miRNAs from the discovery cohort and the coefficients derived from the tissue cohort were applied to TCGA and GSE65819 for independent tissue validation.
  • the dynamic expression range of the miRNAs between tissue RNA-sequencing and serum were different and therefore, the inventors have developed a serum logistic regression based training model of the 8 miRNA panel in GSE106817 and the coefficients and logistic regression model derived from this training cohort was applied to all the public as well Czech Republic retrospective serum validation cohorts. The same regression model was also applied to the prospective serum validation cohort.
  • PV predictive probability values
  • the inventors prioritized the eight miRNAs consisting of hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-202-3p, hsa-miR-205-5p, hsa-miR- miR-508-3p, hsa-miR-509-3-5p, hsa-miR-513b-5p, and hsa-miR-513c-5p (referred as “OCaMIR”) that are upregulated in cancer to evaluate their diagnostic accuracy in stage I OC.
  • a logistic regression model derived from the combination of the eight miRNAs and the resulting risk-scores for the discovery cohort are shown in FIG. IB.
  • OCaMIR achieved an AUC of 0.92 without cross-validation and 0.88 for detecting stage I OC upon 1000 times cross-validation FIG. IB.
  • the logistic regression model derived from the discovery cohort was applied to TCGA and GSE65819 tissue cohorts to evaluate OCaMIR in independent tissue cohorts.
  • OCaMIR achieved an AUC of 0.90 in detecting stage I OC in TCGA cohort, while an AUC of 0.99 and 0.98 upon 1000 times cross-validation for detecting all stages in TCGA and GSE65819 respectively (FIG.
  • OCaMIR a non-invasive diagnostic assay
  • the inventors subsequently analyzed multiple serum miRNA expression cohorts that are available publicly as well as an external retrospective serum validation cohort using qRT-PCR.
  • the expression of individual miRNAs are upregulated in cancer compared to the healthy normal across all the serum validation cohorts (FIG. 4).
  • AUCs of individual miRNAs for all the serum cohorts are presented in Table 2.
  • OCaMIR risk-score The risk-score plots (OCaMIR risk-score) shown in FIG. 2A, clearly demonstrates the difference between healthy and cancer serum specimens.
  • OCaMIR achieved an AUC of 0.86 for detecting OC (FIG. 2A) upon 1000 times cross validation in GSE106817 serum training cohort.
  • OCaMIR attained a sensitivity of 84%, specificity of 74%, positive predictive value of 77% (PPV) and negative predictive value of 83% (NPV) in GSE106817 serum training cohort (Supplementary Table 1).
  • OCaMIR achieved an AUC of 0.84 (GSE31568), 0.87 (GSE113486), and 0.91 (Czech Republic) for the detection of ovarian cancer including all stages upon 1000 times cross validation (FIG. 2B, C, and D respectively).
  • OCaMIR sensitivity, specificity, PPV and NPV for all the serum validation cohorts are presented in Supplementary Table 1. These results highlights the applicability of the inventors * markers in serum for non-invasive detection.
  • OCaMIR Assay in Serum is Highly Accurate in Detecting Stage 1 OC, Superior to CA125 and is Highly Specific for OC Detection
  • OCaMIR is highly accurate in detecting stage I OC with an AUC of 0.88 and 0.86 in GSE106817 and Czech Republic serum cohorts respectively (FIG. 3 A and B).
  • OCaMIR sensitivity, specificity, PPV and NPV for stage I OC detection are presented in Supplementary Table 2.
  • the inventors’ Czech Republic serum validation cohort has CA125 levels for both healthy and cancer specimens, which allowed us to compare the performance of OCaMIR to CA125 in OC detection. As shown in FIG.
  • OCaMIR achieved an AUC of 0.91 for all stages and 0.86 for stage I (FIG. 3B) cancers.
  • CA125 achieved an AUC of 0.82 and 0.73 for the detection of all stages and stage I OC respectively (FIG. 3B).
  • GSE31568 micro array expression cohort where the miRNA expression data was available for various diseases including OC. As depicted in FIG.
  • OCaMIR achieved an AUC of 0.85 in OC, while the detection accuracies for other diseases including acute myocardial infarction, chronic obstructive pulmonary disease, lung cancer, melanoma, multiple sclerosis, pancreatic cancer, pancreatitis, periodontitis, prostate cancer, sarcoidosis, stomach cancer and Wilms tumor are in the range of 0.16 to 0.73. This confirms that the OCaMIR assay is better than the conventional marker CA125 and it is highly specific for OC detection.
  • OCaMIR was highly accurate in detecting OC patients with an AUC of 0.92 and attained a sensitivity of 86%, specificity of 92%, positive predictive value of 91% (PPV) and negative predictive value of 89% (NPV) in this prospective cohort (Supplementary Table 1).
  • the AUC for stage I OC in the prospective cohort was 0.81 (FIG. 3C).
  • OCaMIR performed better than the CA125 for the detection of stage I as well as all stages in the west china prospective cohort (FIG. 3C).
  • CEA cost-effective analysis
  • OCaMIR in international multicenter independent retrospective tissue, serum as well as a prospective serum cohorts encompassing different platforms and ethnicities that can be easily translated into the clinical care.
  • OCaMIR outperformed CA125 [6] the current widely used tumor marker of OC both for the detection of early as well as late stage OC.
  • the Markov model based cost estimation analysis revealed that a large-scale screening of OC using OCaMIR in high-risk population between 55 to 80 years old is cost-effective relative to current practice of no screening.
  • OCaMIR assay the inventors developed in this study showed great potential across different patient populations and sample sources, which is very exciting and holds great promise for future investigations.
  • Cortez MA Calin GA. MicroRNA identification in plasma and serum: a new tool to diagnose and monitor diseases. Expert Opin Biol Ther 2009; 9: 703-711.
  • Niu K, Shen W, Zhang Y et al. MiR-205 promotes motility of ovarian cancer cells via targeting ZEB1. Gene 2015; 574: 330-336.
  • McMillen BD Aponte MM
  • Liu Z et al Expression analysis of MIR-182-5P and its associated target genes in advanced ovarian carcinoma. Mod Pathol 2012; 25: 1644-1653.

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Abstract

La présente invention concerne des méthodes, des compositions et des kits pour traiter le cancer des ovaires et pour évaluer des sujets. Des aspects de l'invention concernent un procédé d'évaluation d'un patient comprenant la mesure du niveau d'expression d'un ou plusieurs des miARN listés dans un échantillon biologique provenant du patient : miR-182-5p, miR-183-5p, miR-202-3p, miR-205-5p, miR-508-3p, miR-509-3-5p, miR-513b-5p, ou miR-513c-5p.
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CN112458174A (zh) * 2020-12-01 2021-03-09 河北仁博科技有限公司 miR-4527在制备诊断或治疗肿瘤耐药性的制剂中的应用
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CN114990216A (zh) * 2022-05-31 2022-09-02 山东大学齐鲁医院 微小rna分子作为生物标记物在胆管癌预后中的应用

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