WO2017096458A1 - Signature génique immunitaire prédictive des bienfaits de l'anthracycline - Google Patents

Signature génique immunitaire prédictive des bienfaits de l'anthracycline Download PDF

Info

Publication number
WO2017096458A1
WO2017096458A1 PCT/CA2016/000305 CA2016000305W WO2017096458A1 WO 2017096458 A1 WO2017096458 A1 WO 2017096458A1 CA 2016000305 W CA2016000305 W CA 2016000305W WO 2017096458 A1 WO2017096458 A1 WO 2017096458A1
Authority
WO
WIPO (PCT)
Prior art keywords
group
genes
subject
immune score
expression
Prior art date
Application number
PCT/CA2016/000305
Other languages
English (en)
Inventor
Marsela BRAUNSTEIN
John MS BARTLETT
Cindy YAO
Melanie SPEARS
Original Assignee
Ontario Institute For Cancer Research (Oicr)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ontario Institute For Cancer Research (Oicr) filed Critical Ontario Institute For Cancer Research (Oicr)
Publication of WO2017096458A1 publication Critical patent/WO2017096458A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/57415—Specifically defined cancers of breast
    • 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
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • the present disclosure relates generally to prognosing or classifying a subject with breast cancer. More particularly, the present disclosure relates to methods and devices directed to predicting anthracycline treatment benefit in a subject with breast cancer.
  • breast cancer is the leading cause of cancer death for women.
  • treatment options for breast cancer patients include chemotherapy, endocrine therapy and trastuzumab.
  • Anthracyclines are commonly used as they non- specifically target rapidly-proliferating cells. Consequently, patients treated with anthracyclines may recover from breast cancer, but suffer severe side-effects such as cardiac toxicity and leukemia. Conversely, patients may not respond to anthracyclines at all or develop drug resistance after prolonged use, which includes cross-resistance to structurally unrelated anti-cancer drugs.
  • TOP2A and CEP17 are predictive biomarkers of clinical anthracycline sensitivity; yet it remains to be established whether these biomarkers can be targeted with drugs in clinic. Therefore, it is not only important to spare non-responders from unnecessary side-effects by discovering novel biomarkers, but also to identify new therapeutic approaches to improve patient survival. [0004] The contribution of immune cells is well appreciated in cancer development, progression and therapy resistance.
  • TIL Tumour-infiltrating lymphocytes
  • ER estrogen receptor negative
  • HER2 + subtypes rather than ER + cancers.
  • CD4 + and CD8 + T cells outnumber other lymphocytes as well as myeloid cells. 8
  • TIL's translational potential as cancer-associated prognostic and predictive markers emerged.
  • high densities of TILs correlate with improved clinical outcome in triple negative breast cancers (TNBC); 9;10 which was followed by the finding of a TIL-gene signature as a prognostic biomarker in TNBC.
  • lymphocytes were predictive of response to chemotherapy but only in lymphocyte-predominant breast cancers (LPBC) defined as having >50-60 lymphocytic infiltration. 12 This is an arbitrary cut-off point that the researchers used to demonstrate the principle, rather than a biological subtype of breast cancer.
  • LPBC lymphocyte-predominant breast cancers
  • intratumoral, but not stromal CD8 + T cells were shown to be predictive of anthracycline therapy but only in ER " breast cancers.
  • breast cancers still need to be evaluated specifically for lymphocyte populations and profiled for their functional orientation, type and effector function in order to determine their predictive biomarker potential.
  • a method of predicting a benefit of anthracycline therapy for a subject with breast cancer comprising: a) providing a sample of a breast cancer tumour of the subject; b) determining the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; c) comparing said expression levels to a reference expression level of the group of genes from control samples from a population; and d) determining the benefit of anthracycline therapy for the subject; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to an immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being associated with a lesser benefit of anthracycline therapy.
  • a computer-implemented method of predicting benefit of anthracycline therapy for a subject with breast cancer comprising: a) receiving, at at least one processor, data reflecting the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; b) comparing, at the at least one processor, said expression levels to a reference expression level of the group of genes from control samples from a population; c) outputting, at the at least one processor, an immune score; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to the immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being associated with lesser benefit of anthracycline therapy.
  • a computer program product for use in conjunction with a general-purpose computer having a processor and a memory connected to the processor, the computer program product comprising a computer readable storage medium having a computer mechanism encoded thereon, wherein the computer program mechanism may be loaded into the memory of the computer and cause the computer to carry out the method described herein.
  • a computer readable medium having stored thereon a data structure for storing the computer program product described herein.
  • a device for predicting benefit of anthracycline therapy for a subject with breast cancer comprising: at least one processor; and electronic memory in communication with the at one processor, the electronic memory storing processor-executable code that, when executed at the at least one processor, causes the at least one processor to: a) receive data reflecting the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; b) compare said expression levels to a reference expression level of the group of genes from control samples from a population, said reference expression level being stored in the memory; c) output an immune score; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to the immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being
  • a method of treating a subject with breast cancer comprising: a) determining the immune score of the subject according to the method described herein; and b) selecting a treatment based on said immune score, and preferably treating the subject according to the treatment.
  • composition comprising a plurality of isolated nucleic acid sequences, wherein each isolated nucleic acid sequence hybridizes to: (a) the mRNA of a group of genes comprising at least one of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; and/or (b) a nucleic acid complementary to a).
  • an array comprising one or more polynucleotide probes complementary and/or hybridizable to an expression product of each gene of a group genes comprising at least three of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3.
  • kits comprising reagents for detecting mRNA from a sample of a breast cancer tumour of at least three genes selected from the group comprising: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3.
  • FIG. 1 is a modified Reporting Recommendations for Tumour Marker Prognostic Studies (REMARK) diagram of the BR9601 trial.
  • the trial recruited 374 pre- and post-menopausal women with completely excised, histologically confirmed breast cancer and a clear indication for adjuvant chemotherapy.
  • Patients were randomized to receive either eight cycles of CMF (i.v. cyclophosphamide 750mg/m2, methotrexate 50mg/m2 and 5-fluorouracil 600mg/m2) every 21 days, or E-CMF (four cycles of epirubicin 100mg/m2 every 21 days followed by four cycles of CMF regimen).
  • Profile shows the total number of samples available for the gene expression analyses.
  • FIG. 2 shows an overview of individual gene prediction values. P-values were obtained from the treatment-by-marker interaction calculations.
  • the genes are listed in the following order: FOXP3, CD4, IFNgamma, GZMB, CD3 epsilon, CD45RO, Tbet, CXCL9, CD48, IRF1 , CD8 alpha, VCAM1 , CXCL12, LCK, CXCR3, JAK2, CCL5, CXCL10, ICAM1 , CXCL13, SELL, IL-12, CCR5, CD68, MS4A1 , STAT1 , CCR1 , CCL22, CD19, CCR3, STAT3, CCR4, CXCR2, IL8, CXCR4, MADCAM1 , PRF1 , and CX3CL1.
  • FOXP3, CD4, IFNy, GZMB, CD3e, CD45RO when their gene expression is low, patients benefit from E-CMF over conventional CMF therapy, whereas when their gene expression is high, there is no difference in patient survival.
  • PRF1 , CX3CL1 it is their high expression that predicts for benefit of E-CMF over CMF, whereas there is no difference in patient survival when their gene expression is low.
  • FIG. 3 shows directionality of expression of each gene within the 9-immune gene signature.
  • the expression of each gene is categorized as being "low” if it is below the population median, or "high” if it is above the population median.
  • developed 9-gene signature contains patients whose tumours have various expression values (z-scores) of these genes.
  • FIG. 4 shows a novel 9-immune gene signature is predictive of benefit from E- CMF (dark line) over CMF (light line).
  • Kaplan-Meier analyses showing A) distant recurrence- free survival (DRFS) and B) breast cancer-specific overall survival (OS).
  • DRFS distant recurrence- free survival
  • OS breast cancer-specific overall survival
  • FIG. 5 is a heatmap illustrating preprocessing methods.
  • the heatmap shows ranking of preprocessing methods based on their ability to maximize mRNA abundance differences between HER2+ and HER2- samples, while minimizing batch effects. For the 252 combinations of preprocessing methods assessed, two rankings were established using the two criteria, and subsequently aggregated using the rank product. The heatmap is then sorted on the rank product with the most effective preprocessing parameters listed at the top.
  • FIG. 6 is a heatmap of mRNA abundance levels scaled as z-scores. Immune- score genes are displayed as rows and patients as columns. Covariate bars for the patients were displayed below showing DRFS, HER2 status, age, grade, N stage and T stage. Patients were sorted based on the distant relapse events and the average mRNA abundance levels.
  • Genes are displayed in rows in the following order: FOXP3, CD4, IFNgamma, GZMB, CD3 epsilon, CD45RO, Tbet, CXCL9, CD48, IRF1 , CD8 alpha, VCAM1 , CXCL12, LCK, CXCR3, JAK2, CCL5, CXCL10, ICAM1 , CXCL13, SELL, IL-12, CCR5, CD68, MS4A1 , STAT1 , CCR1 , CCL22, CD19, CCR3, STAT3, CCR4, CXCR2, IL8, CXCR4, MADCAM1 , PRF1 , and CX3CL1.
  • TILs tumour-infiltrating lymphocytes
  • a drug benefit includes the impact of the drug on the likelihood of survival of a subject or patient, which can be expressed using overall survival and/or distant relapse-free survival.
  • a “greater benefit” or “lesser benefit” may refer to the benefit of anthracycline therapy on the survival of patient compared to a lack of anthracycline therapy.
  • Nanostring platform to gain insight into the lymphocytic populations and develop a TIL gene signature that is predictive of anthracycline benefit.
  • a immunoprofiling panel was used that included 38 TIL genes and chemokines that may be responsible for recruiting TILs to the tumour site.
  • the refinement of the 38-gene panel resulted in the generation of a novel 9- gene signature that includes cytotoxic T lymphocytes (CTL) and chemokine genes.
  • CTL cytotoxic T lymphocytes
  • this disclosure provides a method of prognosing or classifying a subject or patient with breast cancer.
  • the method predicts benefit of anthracycline therapy for a subject with breast cancer.
  • the method involves determining mRNA abundance using a sample of a breast cancer tumour obtained from the subject.
  • anthracyclines are a class of cell-cycle non-specific drugs used in cancer chemotherapy, and are derived from Streptomyces bacterium Streptomyces peucetius var. caesius. These compounds are used to treat many cancers, such as breast cancer.
  • Anthracyclines include, but are not limited to, daunorubicin, doxorubicin, epirubicin, idarubicin, and valrubicin.
  • breast cancer and “breast cancer tumour” refers to at least one or more breast cancer types having neither, one, or both of estrogen and progesterone receptors.
  • ER-positive denotes presence of estrogen receptors
  • PR-positive denotes presence of progesterone receptors.
  • Hormone-positive cancer denotes cancer where the cancer cells contain either estrogen or progesterone receptors
  • hormone-negative cancer denotes cancer where the cancer cells do not contain either estrogen or progesterone receptors.
  • a breast cancer may also be classified by the level of HER2/neu protein associated with the cancer tumor.
  • HER2-positive denotes cancer with increased levels of HER2/neu and/or increased copies of the HER2/neu gene
  • HER2-negative denotes cancer that does not have increased levels of HER2.
  • Triple-negative denotes cancer that does not have estrogen or progesterone receptors and do not have increased levels of HER2.
  • Triple-positive denotes cancer that are ER-positive, PR-positive, and have increased levels of HER2.
  • a method of predicting a benefit of anthracycline therapy for a subject with breast cancer comprising: a) providing a sample of a breast cancer tumour of the subject; b) determining the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; c) comparing said expression levels to a reference expression level of the group of genes from control samples from a population; and d) determining the benefit of anthracycline therapy for the subject; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to an immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being associated with a lesser benefit of anthracycline therapy.
  • sample refers to any fluid, cell or tissue sample from a subject which can be assayed for biomarker expression products and/or a reference expression profile, e.g. peptides differentially present in a liquid biopsy.
  • prognosis refers to a clinical outcome group such as a worse survival group or a better survival group associated with a disease subtype which is reflected by a reference profile such as a biomarker reference expression profile or reflected by an expression level of the fifteen biomarkers disclosed herein.
  • the prognosis provides an indication of disease progression and includes an indication of likelihood of death due to breast cancer.
  • the clinical outcome class includes a better survival group and a worse survival group.
  • prognosing or classifying means predicting or identifying the clinical outcome group that a subject belongs to according to the subject's similarity to a reference profile or biomarker expression level associated with the prognosis.
  • prognosing or classifying comprises a method or process of determining whether an individual has a better or worse survival outcome, or grouping individuals into a better survival group or a worse survival group, or predicting whether or not an individual will respond to therapy.
  • gene means a polynucleotide which may include coding sequences, intervening sequences and regulatory elements controlling transcription and/or translation. Genes include normal alleles of the gene encoding polymorphisms, including silent alleles having no effect on the amino acid sequence of the gene's encoded polypeptide as well as alleles leading to amino acid sequence variants of the encoded polypeptide that do not substantially affect its function. These terms also may optionally include alleles having one or more mutations which affect the function of the encoded polypeptide's function.
  • level of expression or “expression level” as used herein refers to a measurable level of expression of the products of biomarkers, such as, without limitation, micro-RNA, or messenger RNA transcript expressed or of a specific exon or other portion of a transcript, the level of proteins, peptides or portions thereof expressed of the biomarkers, the number or presence of DNA polymorphisms of the biomarkers, the enzymatic or other activities of the biomarkers, and the level of specific metabolites.
  • an expression level of a group of genes refers to the expression level of the group as a whole.
  • determining the expression refers to determining or quantifying RNA or proteins or protein activities or protein-related metabolites expressed by the biomarkers.
  • RNA includes mRNA transcripts, and/or specific spliced or other alternative variants of mRNA, including anti-sense products.
  • protein or “peptides”, it refers to proteins expressed by genes are measurable in a sample.
  • expression profile refers to a dataset representing the expression level(s) of one or more biomarkers.
  • An expression profile may represent one subject, or alternatively a consolidated dataset of a cohort of subjects, for example to establish a reference expression profile as a control.
  • control refers to a specific value or dataset that can be used to prognose or classify the value e.g expression level or reference expression profile obtained from the test sample associated with an outcome class.
  • a dataset may be obtained from samples from a group of subjects known to have cancer having different tumor states and/or healthy individuals.
  • the expression data of the biomarkers in the dataset can be used to create a control value that is used in testing samples from new patients.
  • a cohort of subjects is used to obtain a control dataset.
  • a control cohort patients may be a group of individuals with or without cancer.
  • the control cohort is the group of individuals with breast cancer, namely the BR9601 trial group.
  • a reference expression level is obtained by taking the median expression level.
  • median is the value separating the higher half of a population from the lower half. In simple terms, it may be thought of as the "middle" value of a dataset, such as the control cohort dataset. For example, a subject is classified into a high immune score group where the subject has an immune score above the population median. On the other hand, a subject is classified into a low immune score group where the subject has an immune score below the population median.
  • all survival refers to the percentage of or length of time that people in a study or treatment group are still alive following from either the date of diagnosis or the start of treatment for a disease, such as cancer. In a clinical trial, measuring the overall survival is one way to see how well a new treatment works.
  • relapse-free survival refers to, in the case of caner, the percentage of or length of time that people in a study or treatment group survive without any signs or symptoms of that cancer after primary treatment for that cancer. In a clinical trial, measuring the relapse-free survival is one way to see how well a new treatment works. It is defined as any disease recurrence (local, regional, or distant).
  • the term "good survival” or “better survival” as used herein refers to an increased chance of survival as compared to patients in the "poor survival” group.
  • the biomarkers of the application can prognose or classify patients into a "good survival group”. These patients are at a lower risk of death after surgery.
  • pool survival or “worse survival” as used herein refers to an increased risk of death as compared to patients in the "good survival” group.
  • biomarkers or genes of the application can prognose or classify patients into a “poor survival group”. These patients are at greater risk of death or adverse reaction from disease or surgery, treatment for the disease or other causes.
  • the term "differentially expressed” or “differential expression” as used herein refers to a difference in the level of expression of the biomarkers that can be assayed by measuring the level of expression of the products of the biomarkers, such as the difference in level of mRNA or a portion thereof expressed. In a preferred embodiment, the difference is statistically significant.
  • the term “difference in the level of expression” refers to an increase or decrease in the measurable expression level of a given biomarker, for example as measured by the amount of mRNA as compared with the measurable expression level of a given biomarker in a control.
  • the group of genes is at least 4, 5, 6, 7, 8, or 9 of the genes.
  • the method further comprises building a subject gene expression profile from the determined expression levels of the group of genes.
  • Anthracycline Therapy comprises administration of epirubicin.
  • Anthracycline therapy may also comprise other anthracyclines.
  • the anthracycline therapy further comprises administration of a least one additional chemotherapeutic agent, such as a combination therapy of an anthracyclines (for example epirubicin) and least one additional chemotherapeutic agent.
  • chemotherapeutic agent refers to cytotoxic agents that are known to be of use in chemotherapy for cancer. Chemotherapeutic agents are often combined into chemotherapy regimens for combination chemotherapy.
  • CMF Cyclophosphamide Methotrexate Fluorouracil
  • the method further comprises a signature score comprising a weighted sum expression of each of the group of genes, optionally scaled for imRNA abundance.
  • the signature score may be calculated using equation (2) below:
  • an indicator function / was run to determine whether the expression level of that sample e p is above or below the median population gene expression level m g or the reference expression level. Scores are summed over all genes to calculate the signature score.
  • the subject is classified into a high immune score group where the subject has an immune score above the population median, and wherein the subject is classified into a low immune score group where the subject has an immune score below the population median.
  • the expression of GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, or IRF1 was relatively low and STAT3 was relatively high
  • the expression of GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 was relatively high and STAT3 was relatively low, in comparison to a population cohort.
  • determining the gene expression level comprises use of nanostring.
  • determining mRNA abundance of the genes comprises use of quantitative PCR.
  • RNA products of the biomarkers within a sample, including arrays, such as microarrays, RT-PCR (including quantitative RT-PCR), nuclease protection assays and Northern blot analyses.
  • arrays such as microarrays, RT-PCR (including quantitative RT-PCR), nuclease protection assays and Northern blot analyses.
  • a computer-implemented method of predicting benefit of anthracycline therapy for a subject with breast cancer comprising: a) receiving, at at least one processor, data reflecting the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL 3, IL8, IRF1 and STAT3; b) comparing, at the at least one processor, said expression levels to a reference expression level of the group of genes from control samples from a population; c) outputting, at the at least one processor, an immune score; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to the immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being associated with a lesser benefit of anthracycline therapy.
  • processor may be any type of processor, such as, for example, any type of general-purpose microprocessor or microcontroller (e.g., an IntelTM x86, PowerPCTM, ARMTM processor, or the like), a digital signal processing (DSP) processor, an integrated circuit, a field programmable gate array (FPGA), or any combination thereof.
  • general-purpose microprocessor or microcontroller e.g., an IntelTM x86, PowerPCTM, ARMTM processor, or the like
  • DSP digital signal processing
  • FPGA field programmable gate array
  • memory may include a suitable combination of any type of computer memory that is located either internally or externally such as, for example, random-access memory (RAM), read-only memory (ROM), compact disc read-only memory (CDROM), electro-optical memory, magneto-optical memory, erasable programmable read- only memory (EPROM), and electrically-erasable programmable read-only memory (EEPROM), or the like.
  • RAM random-access memory
  • ROM read-only memory
  • CDROM compact disc read-only memory
  • electro-optical memory magneto-optical memory
  • EPROM erasable programmable read- only memory
  • EEPROM electrically-erasable programmable read-only memory
  • computer readable storage medium (also referred to as a machine-readable medium, a processor-readable medium, or a computer usable medium having a computer-readable program code embodied therein) is a medium capable of storing data in a format readable by a computer or machine.
  • the machine-readable medium can be any suitable tangible, non-transitory medium, including magnetic, optical, or electrical storage medium including a diskette, compact disk read only memory (CD-ROM), memory device (volatile or non-volatile), or similar storage mechanism.
  • the computer readable storage medium can contain various sets of instructions, code sequences, configuration information, or other data, which, when executed, cause a processor to perform steps in a method according to an embodiment of the disclosure.
  • data structure a particular way of organizing data in a computer so that it can be used efficiently.
  • Data structures can implement one or more particular abstract data types (ADT), which specify the operations that can be performed on a data structure and the computational complexity of those operations.
  • ADT abstract data types
  • a data structure is a concrete implementation of the specification provided by an ADT.
  • the method further comprises building, at the at least one processor, a subject gene expression profile from the determined expression levels of the group of genes.
  • the immune score comprises the weighted sum expression of the group of genes.
  • the subject is classified into a high immune score group where the subject has an immune score above the population median, and wherein the subject is classified into a low immune score group where the subject has an immune score below the population median.
  • the expression of GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, or IRF1 was relatively low and STAT3 was relatively high
  • the expression of GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL 3, IL8, IRF1 was relatively high and STAT3 was relatively low.
  • the processor further outputs a recommendation to treat the subject with anthracycline if the subject has a relatively low immune score or is in the low immune score group.
  • a computer program product for use in conjunction with a general-purpose computer having a processor and a memory connected to the processor, the computer program product comprising a computer readable storage medium having a computer mechanism encoded thereon, wherein the computer program mechanism may be loaded into the memory of the computer and cause the computer to carry out the method described herein.
  • a computer readable medium having stored thereon a data structure for storing the computer program product described herein.
  • a device for predicting benefit of anthracycline therapy for a subject with breast cancer comprising: at least one processor; and electronic memory in communication with the at one processor, the electronic memory storing processor-executable code that, when executed at the at least one processor, causes the at least one processor to: a) receive data reflecting the level of expression in the sample for a group of genes comprising at least 3 of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; b) compare said expression levels to a reference expression level of the group of genes from control samples from a population, the reference expression levels being stored in the memory; c) output an immune score; wherein a statistically significant difference or similarity in the expression of the group of genes compared to the reference expression level correlates to the immune score; a relatively low immune score being associated with a greater benefit of anthracycline therapy, and a relatively high immune score being
  • the code further causes the at least one processor to build a subject gene expression profile from the determined expression levels of the group of genes.
  • the code further causes the at least one processor to classify the subject, wherein the subject is classified into a high immune score group where the subject has an immune score above the population median, and wherein the subject is classified into a low immune score group where the subject has an immune score below the population median.
  • a method of treating a subject with breast cancer comprising: a) determining the immune score of the subject according to the method described herein; and b) selecting a treatment based on said immune score, and preferably treating the subject according to the treatment.
  • anthracycline therapy is selected as the treatment where the immune score is relatively low.
  • the selected treatment further comprises a checkpoint inhibitor therapy.
  • checkpoint Inhibitor and “checkpoint inhibitor therapy” refers to a type of drug that blocks certain proteins made by some types of immune system cells, such as T cells, and some cancer cells. These proteins help keep immune responses in check and can keep T cells from killing cancer cells. When these proteins are blocked, the “brakes” on the immune system are released and T cells are able to kill cancer cells better. Examples of checkpoint proteins found on T cells or cancer cells include PD-1/PD-L1 and CTLA-4/B7-1/B7-2. Some immune checkpoint inhibitors are used to treat cancer.
  • compositions comprising a plurality of isolated nucleic acid sequences, wherein each isolated nucleic acid sequence hybridizes to: (a) the mRNA of a group of genes comprising at least one of. GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3; and/or (b) a nucleic acid complementary to a); wherein the composition is used to measure the expression levels of the group of genes.
  • an array comprising one or more polynucleotide probes complementary and/or hybridizable to an expression product of each gene of a group genes comprising at least three of: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3.
  • kits comprising reagents for detecting mRNA from a sample of a breast cancer tumour of at least three genes selected from the group comprising: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL 3, IL8, IRF1 and STAT3.
  • primers include an oligonucleotide which is capable of acting as a point of initiation of polynucleotide synthesis along a complementary strand when placed under conditions in which synthesis of a primer extension product which is complementary to a polynucleotide is catalyzed.
  • Such conditions include the presence of four different nucleotide triphosphates or nucleoside analogs and one or more agents for polymerization such as DNA polymerase and/or reverse transcriptase, in an appropriate buffer ("buffer” includes substituents which are cofactors, or which affect pH, ionic strength, etc.), and at a suitable temperature.
  • a primer must be sufficiently long to prime the synthesis of extension products in the presence of an agent for polymerase.
  • a typical primer contains at least about 5 nucleotides in length of a sequence substantially complementary to the target sequence, but somewhat longer primers are preferred.
  • a primer will always contain a sequence substantially complementary to the target sequence, that is the specific sequence to be amplified, to which it can anneal.
  • complementary refers to sequences of polynucleotides which are capable of forming Watson & Crick base pairing with another specified polynucleotide throughout the entirety of the complementary region. This term is applied to pairs of polynucleotides based solely upon their sequences and does not refer to any specific conditions under which the two polynucleotides would actually bind
  • probe refers to a molecule which can detectably distinguish between target molecules differing in structure, such as allelic variants. Detection can be accomplished in a variety of different ways but preferably is based on detection of specific binding. Examples of such specific binding include antibody binding and nucleic acid probe hybridization.
  • hybridize or “hybridizable” refers to the sequence specific non- covalent binding interaction with a complementary nucleic acid.
  • the hybridization is under high stringency conditions. Appropriate stringency conditions which promote hybridization are known to those skilled in the art, or can be found in Current Protocols in Molecular Biology, John Wiley & Sons, N.Y. (1989), 6.3.1 6.3.6. For example, 6.0 x sodium chloride/sodium citrate (SSC) at about 45°C, followed by a wash of 2.0 x SSC at 50°C may be employed.
  • SSC sodium chloride/sodium citrate
  • the polynucleotide compositions can be primers, can be cDNA, can be RNA, can be DNA complementary to target cDNA or a portion thereof, genomic DNA, unspliced RNA, spliced RNA, alternately spliced RNA, synthetic forms, and mixed polymers, both sense and antisense strands, and may be chemically or biochemically modified or may contain non-natural or derivatized nucleotide bases, as will be readily appreciated by those skilled in the art.
  • nucleic acid includes RNA
  • reference to the sequence shown should be construed as reference to the RNA equivalent, with U substituted for T.
  • Examples of amplification techniques include strand displacement amplification, as disclosed in U.S. Pat. No. 5,744,311 ; transcription-free isothermal amplification, as disclosed in U.S. Pat. No. 6,033,881 ; repair chain reaction amplification, as disclosed in WO 90/01069; ligase chain reaction amplification, as disclosed in European Patent Appl. 320 308; gap filling ligase chain reaction amplification, as disclosed in U.S. Pat. No. 5,427,930; and RNA transcription-free amplification, as disclosed in U.S. Pat. No. 6,025, 134.
  • Kit refers to a combination of physical elements, e.g., probes, including without limitation specific primers, labeled nucleic acid probes, antibodies, protein-capture agent(s), reagent(s), instruction sheet(s) and other elements useful to practice the invention, in particular to identify the levels of particular RNA molecules in a sample.
  • probes and/or primers can be provided in one or more containers or in an array or microarray device.
  • levels of RNA encoded by a target gene can be determined in one analysis.
  • a combination kit may therefore include primers capable of amplifying cDNA derived from RNA encoded by different target genes.
  • the primers may be differentially labeled, for example using different fluorescent labels, so as to differentiate between RNA from different target genes.
  • Multiplex such as duplex, real-time RT-PCR enables simultaneous quantification of 2 targets in the same reaction, which saves time, reduces costs, and conserves samples.
  • These advantages of multiplex, real-time RT-PCR make the technique well-suited for high-throughput gene expression analysis.
  • Multiplex qPCR assay in a realtime format facilitates quantitative measurements and minimizes the risk of false-negative results. It is essential that multiplex PCR is optimized so that amplicons of all samples are compared insub-plateau phase of PCR. Yun, Z., I. Lewensohn-Fuchs, P. Ljungman, L. Ringholm, J. Jonsson, and J. Albert. 2003.
  • the primers and probes contained within the kit may include those able to recognize any of genes of the gene signature described herein.
  • a primer which "selectively hybridizes" to a target polynucleotide is a primer which is capable of hybridizing only, or mostly, with a single target polynucleotide in a mixture of polynucleotides consisting of RNA in a sample, or consisting of cDNA complementary to RNA within the sample.
  • a gene expression profile for breast cancer found in a sample at the RNA level of one or more genes comprising, but preferably not limited to, any of the genes described herein, can be identified or confirmed using many techniques, including but preferably not limited to PCR methods, as for example discussed further in the working examples herein, Northern analyses and the microarray technique, NanoString® and quantitative sequencing.
  • This gene expression profile can be measured in a sample, using various techniques including e.g. microarray technology.
  • fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from a sample. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array.
  • Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. For example, with dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et al., Proc. Natl. Acad. Sci. USA 93(2): 106-149 (1996)). Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip technology, or Incyte's microarray technology.
  • the BR9601 trial (clinicaltrials.gov NCT00003012) recruited 374 pre- and postmenopausal women with completely excised, histologically confirmed breast cancer and a clear indication for adjuvant chemotherapy. Patients were randomized to receive either eight cycles of CMF (i.v. cyclophosphamide 750mg/m 2 , methotrexate 50mg/m 2 and 5-fluorouracil 600mg/m 2 ) every 21 days, or E-CMF (four cycles of epirubicin 100mg/m 2 every 21 days followed by four cycles of the above CMF regimen) 17 (see FIG. 1 ).
  • CMF i.v. cyclophosphamide 750mg/m 2 , methotrexate 50mg/m 2 and 5-fluorouracil 600mg/m 2
  • E-CMF four cycles of epirubicin 100mg/m 2 every 21 days followed by four cycles of the above CMF regimen 17 (see FIG. 1 ).
  • the MA5 trial included 710 premenopausal or perimenopausal women with axillary node-positive breast cancer who had undergone surgery. Patients were randomized to receive CMF (cyclophosphamide 100 mg/m 2 on days 1-14, methotrexate 40 mg/m 2 and fluorouracil 600 mg/m 2 on days 1-8) or CEF (cyclophosphamide 75 mg/m 2 on days 1 -14, epirubicin 60 mg/m 2 and fluorouracil 500 mg/m 2 on days 1-8).
  • CMF cyclophosphamide 100 mg/m 2 on days 1-14, methotrexate 40 mg/m 2 and fluorouracil 600 mg/m 2 on days 1-8) or CEF (cyclophosphamide 75 mg/m 2 on days 1 -14, epirubici
  • RNA from formalin fixed paraffin embedded (FFPE) breast cancer tissue samples (2 x 10 ⁇ full sections) was extracted using the RecoverAII Total Nucleic Acid Isolation kit (Life Technologies, Burlington, Canada) following the manufacturer's protocol. Sample concentrations were determined with the NanoDrop ND-1000 spectrophotometer (ThermoScientific, Wilmington, USA). nCounter gene expression codeset were designed to include a panel of 38 immune-function genes and six housekeeping genes (see Table 1). The codesets were processed on nCounter according to manufacturer's instructions (NanoString Technologies, Seattle, USA).
  • Table 1 All 38 immune-function genes and 6 housekeeping genes included on a
  • AIC 2K- 2 ⁇ n ⁇ L) (1 ) where k is the number of parameters and L is the maximum value of the likelihood function.
  • the selected genes were then used to derive a multifeature signature score.
  • the patients were dichotomized into low/high expression groups based on the median expression values of the training patients within that fold. Each patient is then given +1 or -1 depending on whether they fall into the low or high expression group, respectively. Each gene iterated through, assigning +1 or -1 for the patients. Finally, the sum of scores for all genes was calculated using equation (2) below:
  • Preprocessing schemes were subsequently ranked based on inter-batch variation as measured by five replicates of a cell line control sample.
  • a mixed effects linear model was used and residual estimates were extracted as an estimate of inter-batch variation (nlme v3.1 -1 17). Cumulative ranks based on these two criteria were estimated using RankProduct [19] resulting in selection of an optimal pre-processing scheme of normalization to the geometric mean derived from all genes for sample content followed by quantile normalisation.
  • MADCAM1 1.121 0.755 1.663 0.572
  • VCAM1 0.934 0.63 1 .386 0.735
  • MADCAM1 1.74 3.876 0.781 0.176 CD48 0.57 1.285 0.255 0.176
  • VCAM1 0.65 1.451 0.289 0.292
  • the BR9601 trial was used as a training cohort for signature development.
  • the resulting multi-gene signature included the following 9 genes: GZMB, PRF1 , SELL, CCL22, CXCL10, CXCL13, IL8, IRF1 and STAT3.
  • a 9-immune gene signature score was calculated and each patient was sorted into either low immune-signature score group (below the population median) or high immune-signature score group (above the population median).
  • FIG. 3 shows the directionality of gene expression for each gene in the signature.
  • the immune signature included genes that are involved in cell killing and trafficking, as well as chemoattractants responsible for recruiting immune cells to the homing site, it was assessed whether these genes correlate with CD4 (Th phenotype), CD8 (CTL phenotype) and CD3 (total T-cell phenotype) gene expression (see Table 6) GZMB and PRF1 , which encode for lymphocyte effector molecules involved in cellular killing, correlated with CD8 and CD3 gene expression but not CD4. Similarly, IRF1 , a transcription factor involved in interferon response signaling correlated with CD8 and CD3 expression, but not CD4.
  • CD3:CD4 correlation 0.392**
  • CD3:CD8 correlation 0.725**
  • the immune biomarker contained genes that correlate to cytotoxic T lymphocytes (GZMB, PRF1 , IRF1 and SELL), as well as STAT3 and chemokines (IL8, CXCL10, CXCL13 and CCL22) that are likely to be expressed by other stromal or tumour cells. Therefore, the signature encompasses immune features from the entire tumour microenvironment, reflecting that immune, tumour and stromal cells engage in a complex interplay during development of drug resistance.
  • anthracyclines and cyclophosphamide can cause transient depletion of lymphocytes including immunosuppressive T regulatory cells and exhausted T cells in the tumour site; 19" 2 a subsequent homeostatic expansion and recruitment of tumour-antigen specific T cells would lead to a more effective antitumour immune response following chemotherapy treatment.
  • anthracyclines specifically have been shown to induce translocation of calreticulin from ER to the cell membrane as well as a release of an endogenous ligand HMGB1 (high mobility group box 1 ), both of which act as danger signals eliciting an immune response. 23"25
  • CTLA4 an inhibitory molecule expressed by T regulatory and activated T cells, competes with CD28 for interaction with the co-stimulatory ligands CD86/80 that are necessary for T-cell activation.
  • PD1 is expressed on activated lymphocytes as well as exhausted lymphocytes 26 and functions by binding to antigen- presenting cells and tumour cells, thereby reducing T-cell activation. 27 Therefore, the mechanism of action of these drugs would involve multiple avenues, ranging from blocking inhibitory molecules on tumour cells and T regulatory cells, to directly activating cytotoxic T cells.
  • TILs tumor-infiltrating lymphocytes

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Immunology (AREA)
  • Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Biotechnology (AREA)
  • Biomedical Technology (AREA)
  • Urology & Nephrology (AREA)
  • Hematology (AREA)
  • Zoology (AREA)
  • Wood Science & Technology (AREA)
  • Physics & Mathematics (AREA)
  • Hospice & Palliative Care (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Oncology (AREA)
  • Microbiology (AREA)
  • Genetics & Genomics (AREA)
  • General Physics & Mathematics (AREA)
  • Biophysics (AREA)
  • Cell Biology (AREA)
  • Medicinal Chemistry (AREA)
  • Food Science & Technology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne un procédé permettant de prédire les bienfaits d'une thérapie à base d'anthracycline chez un sujet atteint d'un cancer du sein, le procédé comprenant : a) la fourniture d'un échantillon d'une tumeur de cancer du sein du sujet ; b) l'estimation du niveau d'expression dans l'échantillon pour un groupe de gènes comprenant au moins 3 parmi les suivants : GZMB, PRF1, SEL1, CCL22, CXCL10, CXCL13, IL8, IRF1 et STAT3 ; c) la comparaison des niveaux d'expression à un niveau d'expression de référence du groupe de gènes provenant d'échantillons témoins d'une population ; et d) l'estimation des bienfaits d'une thérapie à base d'anthracycline pour le sujet ; une différence ou une similarité statistiquement significative dans l'expression du groupe de gènes par rapport au niveau d'expression de référence étant en corrélation avec une note immunitaire ; une note immunitaire relativement faible étant associée à des bienfaits plus importants d'une thérapie à base d'anthracycline, et une note immunitaire relativement élevée étant associée à des bienfaits moindres d'une thérapie à base d'anthracycline.
PCT/CA2016/000305 2015-12-07 2016-12-07 Signature génique immunitaire prédictive des bienfaits de l'anthracycline WO2017096458A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US201562263831P 2015-12-07 2015-12-07
US201562264029P 2015-12-07 2015-12-07
US62/263,831 2015-12-07
US62/264,029 2015-12-07

Publications (1)

Publication Number Publication Date
WO2017096458A1 true WO2017096458A1 (fr) 2017-06-15

Family

ID=59012492

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CA2016/000305 WO2017096458A1 (fr) 2015-12-07 2016-12-07 Signature génique immunitaire prédictive des bienfaits de l'anthracycline

Country Status (1)

Country Link
WO (1) WO2017096458A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019226514A3 (fr) * 2018-05-21 2019-12-26 Nanostring Technologies, Inc. Signatures génétiques moléculaires et leurs méthodes d'utilisation

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005100606A2 (fr) * 2004-04-09 2005-10-27 Genomic Health, Inc. Marqueurs d'expression genique permettant de predire la reponse a la chimiotherapie
WO2006138275A2 (fr) * 2005-06-13 2006-12-28 The Regents Of The University Of Michigan Compositions et procedes de traitement et de diagnostic de cancer
US20130259858A1 (en) * 2012-03-14 2013-10-03 University Health Network Signature for Predicting Clinical Outcome in Human HER2+ Breast Cancer
WO2014009535A2 (fr) * 2012-07-12 2014-01-16 INSERM (Institut National de la Santé et de la Recherche Médicale) Procédés de prédiction de la durée de survie et de la réponse au traitement d'un patient souffrant d'un cancer solide avec une signature d'au moins 7 gènes
WO2014071109A1 (fr) * 2012-11-01 2014-05-08 Infinity Pharmaceuticals, Inc. Traitement de cancers à l'aide de modulateurs d'isoforme de pi3 kinase

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005100606A2 (fr) * 2004-04-09 2005-10-27 Genomic Health, Inc. Marqueurs d'expression genique permettant de predire la reponse a la chimiotherapie
WO2006138275A2 (fr) * 2005-06-13 2006-12-28 The Regents Of The University Of Michigan Compositions et procedes de traitement et de diagnostic de cancer
US20130259858A1 (en) * 2012-03-14 2013-10-03 University Health Network Signature for Predicting Clinical Outcome in Human HER2+ Breast Cancer
WO2014009535A2 (fr) * 2012-07-12 2014-01-16 INSERM (Institut National de la Santé et de la Recherche Médicale) Procédés de prédiction de la durée de survie et de la réponse au traitement d'un patient souffrant d'un cancer solide avec une signature d'au moins 7 gènes
WO2014071109A1 (fr) * 2012-11-01 2014-05-08 Infinity Pharmaceuticals, Inc. Traitement de cancers à l'aide de modulateurs d'isoforme de pi3 kinase

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
LEE ET AL.: "Prognostic and predictive value of NanoString-based immune-related gene signatures in a neoadjuvant setting of triple-negative breast cancer: relationship to tumor-infiltrating lymphocytes''.", BREAST CANCER RESEARCH AND TREATMENT, vol. 151, 26 May 2015 (2015-05-26), pages 619 - 627, XP055389671, ISSN: 1573-7217 *
WAGGOT ET AL.: "NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data''.", BIOINFORMATICS, vol. 28, no. 11, 17 April 2012 (2012-04-17), pages 1546 - 1548, XP055389668, ISSN: 1460-2059 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019226514A3 (fr) * 2018-05-21 2019-12-26 Nanostring Technologies, Inc. Signatures génétiques moléculaires et leurs méthodes d'utilisation

Similar Documents

Publication Publication Date Title
Hao et al. Immunogenomic analyses of advanced serous ovarian cancer reveal immune score is a strong prognostic factor and an indicator of chemosensitivity
US10597729B2 (en) Use of gene expression profiling to predict survival in cancer patient
Marcucci et al. IDH1 and IDH2 gene mutations identify novel molecular subsets within de novo cytogenetically normal acute myeloid leukemia: a Cancer and Leukemia Group B study
Gaedcke et al. Mutated KRAS results in overexpression of DUSP4, a MAP‐kinase phosphatase, and SMYD3, a histone methyltransferase, in rectal carcinomas
EP2258874B1 (fr) Procédé d'identification si un patient est réactif ou non à l'immunothérapie
JP6995091B2 (ja) 癌患者をスクリーニングするための方法及びキット
US7741035B2 (en) Use of gene expression profiling to predict survival in cancer patient
KR20140105836A (ko) 다유전자 바이오마커의 확인
WO2011109637A1 (fr) Procédés pour classer et traiter les cancers du sein
EP3119908A2 (fr) Détermination de l'agressivité d'un cancer, de son pronostic et de sa sensibilité à un traitement
JP2006506945A (ja) 遺伝子発現プロフィールを使用する非小細胞肺癌の診断および処置のための方法および組成物
WO2016044207A1 (fr) Biomarqueurs utilisables pour prédire la réponse à un traitement basé sur l'inhibition de pd-1
EP2247756A2 (fr) Procédé et trousse de détection des gènes associés à la mutation du pik3ca et impliqués dans l activation de la voie pi3k/akt dans les sous-types er-positifs et her2-positifs avec des implications cliniques.
JP7043404B2 (ja) 早期乳癌における内分泌処置後の残留リスクの遺伝子シグネチャー
US20100316629A1 (en) Use of gene expression profiling to predict survival in cancer patient
WO2017096458A1 (fr) Signature génique immunitaire prédictive des bienfaits de l'anthracycline
JP2022174309A (ja) がんの重症度を評価するためのｔｉｍ－３
US20230257825A1 (en) Breast cancer biomarkers and methods of use
US20220333193A1 (en) Determining individual hla patterns, use as prognosticators, target genes and therapeutic agents
US20100015620A1 (en) Cancer-linked genes as biomarkers to monitor response to impdh inhibitors
EP3255433A1 (fr) Procédés utilisant blm comme un marqueur du myélome multiple
Kortekaas Towards a tailored therapeutic approach for vulvar cancer patients
EP3169815A1 (fr) Procédés et dispositifs permettant de prédire l'efficacité d'un traitement à l'anthracycline
WO2024112967A1 (fr) Méthodes de traitement du cancer par immunothérapie
EP4214334A1 (fr) Biomarqueurs pour le traitement d'inhibiteurs de points de contrôle immunitaires

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16871847

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16871847

Country of ref document: EP

Kind code of ref document: A1