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WO2024127053A1 - Procédé de prédiction d'une réponse à des inhibiteurs de point de contrôle immunitaire chez un patient atteint d'un cancer du type msi - Google Patents

Procédé de prédiction d'une réponse à des inhibiteurs de point de contrôle immunitaire chez un patient atteint d'un cancer du type msi Download PDF

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WO2024127053A1
WO2024127053A1 PCT/IB2022/000719 IB2022000719W WO2024127053A1 WO 2024127053 A1 WO2024127053 A1 WO 2024127053A1 IB 2022000719 W IB2022000719 W IB 2022000719W WO 2024127053 A1 WO2024127053 A1 WO 2024127053A1
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ici
patient
response
cancer
msi
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Inventor
Alex DUVAL
Toky RATOVOMANANA
Aurélien DIEHL
Rémy Nicolle
Thierry Andre
Romain COHEN
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Assistance Publique Hopitaux de Paris APHP
Institut National de la Sante et de la Recherche Medicale INSERM
Sorbonne Universite
Universite Paris Cite
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Assistance Publique Hopitaux de Paris APHP
Institut National de la Sante et de la Recherche Medicale INSERM
Sorbonne Universite
Universite Paris Cite
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Priority to PCT/IB2022/000719 priority Critical patent/WO2024127053A1/fr
Priority to PCT/EP2023/085678 priority patent/WO2024126609A1/fr
Publication of WO2024127053A1 publication Critical patent/WO2024127053A1/fr
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • 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
    • C12Q2600/156—Polymorphic or mutational 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
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer comprising determining the microsatellite (MS) variation status of a set of selected genes and using a machine learning algorithm.
  • ICI immune checkpoint inhibitors
  • MSI Mismatch repair deficient tumors display a molecular phenotype characterized by the genetic instability of numerous microsatellite repeated sequences throughout the genome (Microsatellite Instability, MSI) (1-3). MSI was first observed in inherited tumors associated with Lynch syndrome and later in a large spectrum of primary tumors, in particular sporadic colorectal cancers (CRC) (4-6). Being highly genetically unstable, MSI cancers are highly immunogenic and generally show a strong infiltration with cytotoxic T-cell lymphocytes (7). Recently, it was reported that MSI tumors resist this hostile immune microenvironment by overexpressing immune checkpoint (ICK)-related proteins to allow immune-escape (8).
  • ICK immune checkpoint
  • MSI status was shown to predict clinical benefit from ICK inhibitors (ICIs) in patients with metastatic cancer including CRC (mCRC) (9,10).
  • CRC CRC
  • dMMR/MSI mCRC CRC
  • the objective response rate ranges from 33% to 65% and the 1-year overall survival rate ranges from 34% to 71%.
  • First-line pembrolizumab anti-PD-1
  • anti-PD-1 has been associated with significant improvement of progression-free survival compared with standard of care chemotherapy.
  • up to 15-46% of patients with dMMR/MSI mCRC exhibit primary resistance to ICIs while 5%-25% of responders develop acquired resistance to these treatments, although this estimation might increase with longer follow-up (11-14).
  • markers predicting the efficacy of ICIs have been previously proposed in metastatic dMMR/MSI cancer settings (15-22). However, it is fair to say that these results lack independent validation, being based on the analysis of only limited series of invasive dMMR/MSI tumor samples with heterogeneous tumor origins.
  • markers include quantitative genomic indexes measuring the level of MSI within the tumor bulk such as MSIsensor or the tumor mutation burden (TMB) whose association to more dense immune infiltration of the cancer in the highly immunogenic dMMR/MSI cancer setting remains uncertain as it has not yet been carefully investigated.
  • RNA level it was hypothesized that the estimated abundance of some specific cell populations in the tumor microenvironment could be of particular clinical relevance, e.g., some immune cell populations such as antigen-presenting macrophages interacting with T-cells (21).
  • some immune cell populations such as antigen-presenting macrophages interacting with T-cells (21).
  • deregulated activity of some cancer- related pathways more or less associated with the adaptative T-cell antitumor immunity were also proposed, e.g., the reduced activity of Wnt/Wingless signaling, deregulation of the interferon gamma pathway and/or of several immune escape processes (21).
  • the inventors addressed the issue of response to ICIs based on two independent prospective cohorts of 44 and 73 patients with dMMR/MSI mCRC, respectively the multicentric NIPICOL clinical trial (NCT03350126) and the prospective ImmunoMSI cohort (26). Following central reassessment for dMMR/MSI status using gold standard methods to discard misdiagnosed mCRC cases, combined DNA and RNA sequencing of the tumor tissues from these patients was performed. Following supervised analysis of the molecular profiles data which failed to confirm previously proposed DNA/RNA indicators for response to treatment, the use of innovative methods allowed them to identify robust independent DNA and RNA signatures for predicting resistance to ICI.
  • the present invention relates to a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer comprising determining the microsatellite (MS) variation status of a set of selected genes and using a machine learning algorithm.
  • ICI immune checkpoint inhibitors
  • MS microsatellite
  • a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer comprising i) extracting DNA from a tumoral sample from said patient, ii) sequencing the DNA of said tumoral sample, iii) determining the microsatellite (MS) variation status of a set of selected genes, and iv) determining a response to the ICI in said patient based on the determined microsatellite variation status of the set of selected genes, wherein said determining is performed by application of a machine learning algorithm configured to output, from microsatellite variation status of the set of selected genes of a patient with an MSI cancer, a response to the ICI of said patient.
  • a machine learning algorithm configured to output, from microsatellite variation status of the set of selected genes of a patient with an MSI cancer, a response to the ICI of said patient.
  • the machine learning algorithm is configured to calculate a score from the MS variation status of the selected genes, and the method further comprises v) concluding that the patient will not response to the ICI when the score obtained at the step iv) is superior than a calculated threshold value.
  • the machine learning algorithm is a random forest algorithm.
  • the machine learning algorithm has been preliminarily trained by supervised learning on a training dataset comprising, for each of a plurality of patients with MSI cancer, a microsatellite variation status of each gene of the set of selected genes, and an indicator of the response of the patient to a treatment using ICI.
  • the indicator of the response of the patient to a treatment using ICI is a relapse status of the patient.
  • a relapse status of a patient may be determined from a progression-free survival considered after a determined period of time has elapsed since the beginning of the treatment.
  • a microsatellite variation status comprises either presence or absence of a variation.
  • determining the microsatellite variation status of a gene comprises: computing an indicator of a difference in a number of reads in normal tissue and in tumoral tissue, and when the indicator of difference exceeds a predetermined threshold, concluding that a variation is present for the corresponding microsatellite, else concluding that a variation is absent for the corresponding microsatellite.
  • the method comprises a preliminary step of determining the set of selected genes, comprising: for each of a plurality of genes, computing a correlation between a variation status of a microsatellite and a survival criterion of a patient with MSI cancer under ICI treatment, selecting the genes for which the correlation exceeds a predetermined threshold.
  • the set of selected genes consists of MAC01, PPRC1, C0MMD3, IGDCC4, RNF43, EDAR, RWDD4, TTN AS1, SUCO, 0CA2, IQCA1, MTMR10, NLK, CCDC158, MLIP, CANX, TSEN54, LYST and ADGRE1.
  • the invention relates to a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer
  • the method comprising i) extracting DNA from a tumoral sample from said patient, ii) sequencing the DNA of tumoral sample, iii) determining the microsatellite (MS) variation status of a set of selected genes, and iv) determining a response to the ICI in said patient based on the determined microsatellite variation status of the genes MAC01, PPRC1, C0MMD3, IGDCC4, RNF43, EDAR, RWDD4, TTN AS1, SUCO, 0CA2, IQCA1, MTMR10, NLK, CCDC158, MLIP, CANX, TSEN54, LYST and ADGRE1, wherein said determining is performed by application of a machine learning algorithm configured to output, from microsatellite variation status of the set of selected genes of a patient with an MSI cancer, a response to
  • the response of a patient with an MSI cancer to immune checkpoint inhibitors is determined based on the MS variation status of a set of selected genes, using a trained machine learning algorithm, such as a random forest algorithm or naive Bayes classifiers.
  • the MS variation status will depend on the presence or not of variations like SNVs (Single Nucleotide Variations) or small insertions/deletions (up to 20bp) in the MS of the patient.
  • SNVs Single Nucleotide Variations
  • small insertions/deletions up to 20bp
  • the selected MS are used to train, test and validate a predictive model (such as random forest) able to predict a risk score for a patient.
  • the score according to the method of the invention will be then calculated by the predictive model on the basis of the MS variation status of set of selected genes of new patients.
  • a threshold optimizing the best separation of the two groups in the test cohort was determined based on an ROC function. For example, the threshold is 0,1 (10%) but can vary in function of the algorithm model used.
  • microsatellite has the same meaning than “repeat”.
  • the term “repeat” denotes the number of nucleic acids (or nucleic bases) repeated for a specific locus/gene. So the term “repeat” denotes a length of nucleic acids. For example, if the repeat is 12 for the nucleic acids A (adenine), this means that the nucleic acids A is repeated 12 time consecutively in a specific locus.
  • mutated repeat denotes that the repeat is mutated (deletion or addition of one or several nucleic acids or Single Nucleotide Variations) compared to the normal repeat.
  • a repeat can be mutated in a context of MSI cancer in the 19 genes of the invention.
  • the MS variation status will be obtained after DNA sequencing and obtention of reads.
  • read denotes a DNA fragment produced by a sequencer instrument which are a partial or exact copy of a locus (or in the present case in a gene, one of the 19 genes of the invention) to be sequenced and are used to determine the content and sequential order of its nucleic acids.
  • the reads counts per locus/gene after sequencing is between 10 and 5000, between 10 and 4000, particularly between 100 and 4000, particularly between 1000 and 3000 and more particularly between 1500 and 2500.
  • the reads counts per locus after sequencing is 20, 30, 40, 50, 100, 150, 200, 250; 300, 350 or 400.
  • the 19 genes are ACO1, PPRC1, COMMD3, IGDCC4, RNF43, ED AR, RWDD4, TTN AS1, SUCO, OCA2, IQCA1, MTMR10, NLK, CCDC158, MLIP, CANX, TSEN54, LYST and ADGRE1.
  • the MS in the gene MACO1 as a position chr 1.2544883 and a NCBI Entrez Gene number 55219.
  • the MS in the gene PPRC1 has a position chrlO.102145006 and a NCBI Entrez Gene number 23082.
  • the MS in the gene COMMD3 has a position chrlO.22318940 and a NCBI Entrez Gene number 23412.
  • the MS in the gene IGDCC4 has a position chrl5.65388901 and a NCBI Entrez Gene number 57722.
  • the MS in the gene RNF43 has a position chrl7.58370936 and a NCBI Entrez Gene number 54894.
  • the MS in the gene ED AR has a position chr2.108906291 and a NCBI Entrez Gene number 10913.
  • the MS in the gene RWDD4 has a position chr4.183641472 and a NCBI Entrez Gene number 201965.
  • the MS in the gene TTN-AS1 has a position chr2.178598719 and a NCBI Entrez Gene number 100506866.
  • the MS in the gene SUCO has a position chr 1.172600036 and a NCBI Entrez Gene number 51430.
  • the gene OCA2 has a position chrl5.27955158 and a NCBI Entrez Gene number 4948.
  • the MS in the gene IQCA1 has a position chr2.236486815 and a NCBI Entrez Gene number 79781.
  • the MS in the gene MTMR10 has a position chrl5.30959130 and a NCBI Entrez Gene number 54893.
  • the MS in the gene NLK has a position chrl 7.28132599 and a NCBI Entrez Gene number 51701.
  • the MS in the gene CCDC158 has a position chr4.76384668 and a NCBI Entrez Gene number 339965.
  • the MS in the gene MLIP has a position chr6.54160727 and a NCBI Entrez Gene number 90523.
  • MS in the gene CANX has a position chr5.179723787 and a NCBI Entrez Gene number 821.
  • the MS in the gene TSEN54 has a position chrl 7.75518974 and a NCBI Entrez Gene number 283989.
  • the MS in the gene LYST has a position chrl.235663082 and a NCBI Entrez Gene number 1130.
  • the MS in the gene ADGRE1 has a position chrl9.6908664 and a NCBI Entrez Gene number 2015.
  • machine learning method of the invention may be chosen from Adaboost, GradientBoosting, MRMR, neural network methods, decision trees, k-nearest neighbors method, carrier vector machines, algorithm based on a linear model, a generalized linear model discriminant, a factor regression model, a partial least square model, a factor analysis, a support vector machine, a support vector regression, a graphical model, a tree-based model, a random forest model, a random fems model, a naive Bayes model, a linear discriminant analysis, a quadratic linear discriminant analysis, a perceptron model, a neural network model, nearest neighbor model, a nearest prototype model, an ensemble model, a prototype-based supervised algorithm, a bagged model, a Bayesian model, a regularized linear model, a polynomial model, a rule -based model, a Gaussian process model, a mixture discriminant model, a regression spline model, a rule induction
  • the methods of the present invention can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.
  • the algorithm can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).
  • processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer.
  • a processor will receive instructions and data from a read-only memory or a random access memory or both.
  • the essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data.
  • a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks.
  • data e.g., magnetic, magneto-optical disks, or optical disks.
  • a computer need not have such devices.
  • a computer can be embedded in another device.
  • Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.
  • processors and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
  • a computer having a display device, e.g., in non-limiting examples, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer.
  • a display device e.g., in non-limiting examples, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • keyboard and a pointing device e.g., a mouse or a trackball
  • feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.
  • the algorithm can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the invention, or any combination of one or more such back-end, middleware, or front-end components.
  • the components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet.
  • the computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
  • sample refers to any biological sample obtained from the patient that is liable to contain DNA, particularly germinal DNA and particularly cancerous DNA (DNA from cancerous cell).
  • samples include but are not limited to solid sample (e.g. biopsy) or to body fluid samples, such as blood, plasma or serum.
  • tumor sample refers to any biologic sample that contains tumor DNA, in particular circulating tumor DNA primary blood cells (PBCs).
  • the sample is tumor circulating cells or is tumor solid mass.
  • germinal DNA obtained from PBMCs or PBCs will be used to diagnose MSI cancer.
  • the sample can be frozen or not and the sample can come from primary tumor or metastatic tumor.
  • a patient or ‘subject” denotes a mammal.
  • a patient according to the invention refers to any subject (particularly human) afflicted with a MSI cancer.
  • nucleic acid or “nucleic base” has its general meaning in the art and refers to a coding or non-coding nucleic sequence.
  • Nucleic acids include DNA (deoxyribonucleic acid) and RNA (ribonucleic acid) nucleic acids.
  • Example of nucleic acid thus include but are not limited to DNA, mRNA, tRNA, rRNA, tmRNA, miRNA, piRNA, snoRNA, and snRNA. Nucleic acids thus encompass coding and non-coding region of a genome (i.e. nuclear or mitochondrial).
  • the immune checkpoint inhibitor can be an anti-CTLA4, anti-PDl, anti- PD-L1 like anti-CTLA4, anti-PDl, anti-PD-Ll.
  • the anti-PDl can be the pembrolizumab, the nivolumab or the Dostarlimab (TSR-042).
  • the anti-CTLA4 can be the ipilimumab.
  • the tumor sample corresponds to a solid tumor.
  • solid tumor has its general meaning in the art and relates to an abnormal mass of tissue that usually does not contain cysts or liquid areas (e.g. biopsy). Solid tumors may be benign (not cancer), or malignant (cancer). Different types of solid tumors are named for the type of cells that form them. Examples of solid tumors are sarcomas and carcinomas.
  • the tumor sample corresponds to a liquid tumor.
  • liquid tumor has its general meaning in the art and relates to a tumor that occurs in the blood, bone marrow or lymph nodes. Different liquid tumors include types of Leukaemia, Lymphoma and Myeloma.
  • MSI cancer denotes that an instability is detected in at least 2 microsatellite markers. On the contrary, if instability is detected in one or no microsatellite marker, then said cancer is a “MSS cancer” This definition is valuable only if the diagnostic is done by the pentaplex method (see for example Suraweera N et al., Evaluation of tumor microsatellite instability using five quasimonomorphic mononucleotide repeats and pentaplex PCR. Gastroenterology. 2002 or Buhard O et al., Multipopulation analysis of polymorphisms in five mononucleotide repeats used to determine the microsatellite instability status of human tumors. J Clin Oncol.2006).
  • a “MSS cancer” denotes to a cancer having stable microsatellite.
  • a “MSI cancer” refers to a cancer having microsatellite instable.
  • cancer has its general meaning in the art and includes, but is not limited to, solid tumors and blood borne tumors.
  • the term cancer includes diseases of the skin, tissues, organs, bone, cartilage, blood and vessels.
  • the term “cancer” further encompasses both primary and metastatic cancers. Examples of cancers include, but are not limited to, cancer cells from the bladder, blood, bone, bone marrow, brain, breast, colon, esophagus, gastrointestine, gum, head, kidney, liver, lung, nasopharynx, neck, ovary, prostate, skin, stomach, testis, tongue, or uterus.
  • the cancer may specifically be of the following histological type, though it is not limited to these: neoplasm, malignant; carcinoma; carcinoma, undifferentiated; giant and spindle cell carcinoma; small cell carcinoma; papillary carcinoma; squamous cell carcinoma; lymphoepithelial carcinoma; basal cell carcinoma; pilomatrix carcinoma; transitional cell carcinoma; papillary transitional cell carcinoma; adenocarcinoma; gastrinoma, malignant; cholangiocarcinoma; hepatocellular carcinoma; combined hepatocellular carcinoma and cholangiocarcinoma; trabecular adenocarcinoma; adenoid cystic carcinoma; adenocarcinoma in adenomatous polyp; adenocarcinoma, familial polyposis coli; solid carcinoma; carcinoid tumor, malignant; branchiolo-alveolar adenocarcinoma; papillary adenocarcinoma; chromophobe carcinoma; acid
  • the cancer is a metastatic cancer.
  • the cancer is a metastatic colorectal cancer.
  • the metastatic colorectal cancer is a MSI metastatic colorectal cancer.
  • a further step of communicating the result to the patient may be added to the methods of the invention.
  • the methods are ex-vivo methods or in-vitro methods.
  • the invention in another aspect, relates to a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer is disclosed, the method comprising i) extracting RNA from a tumoral sample from said patient, ii) determining in said sample the expression level of selected RNAs iii) comparing said expression level determined at step i) with their predetermined reference value and iv) providing that the patient will not response to the ICI when the expression level determined at step ii) is higher than their predetermined reference values, or providing that the patient will response to the ICI when the expression level determined at step ii) is lower than their predetermined reference values.
  • ICI immune checkpoint inhibitors
  • the determination of the expression level of the RNAs of the invention are done by nanostring or RNAseq or all method useful to determine the expression level of an RNA.
  • the selected RNAs are the RNAs of the table 1.
  • RNAs of the invention are indicated by the name of their corresponding genes.
  • the two signature can be combined to predict a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer.
  • ICI immune checkpoint inhibitors
  • the invention also relates to a method of predicting a response to immune checkpoint inhibitors (ICI) in a patient with an MSI cancer is disclosed, wherein the DNA and RNA methods as disclosed above are applied and combined to determine if the patient will respond to immune checkpoint inhibitors.
  • ICI immune checkpoint inhibitors
  • multivariate analysis combining DNA and RNA signatures of the present invention can be performed together.
  • Predetermined reference values used for comparison of the score obtained by the method of the invention or for comparison of the expression level of the RNAs of the invention may comprise “cut-off’ or “threshold” values that may be determined as described herein.
  • Each reference (“cut-off’) value for the score may be, for example, predetermined by carrying out a method comprising the steps of: a) providing a collection of samples from patients suffering of a cancer; b) determining the score or expression level of RNAs for each sample contained in the collection provided at step a); c) ranking the tumor tissue samples according to said score or expression level d) classifying said samples in pairs of subsets of increasing, respectively decreasing, number of members ranked according to their level, e) providing, for each sample provided at step a), information relating to the actual response to ICI for the corresponding cancer patient; f) for each pair of subsets of samples, obtaining a Kaplan Meier percentage of survival curve; g) for each pair of subsets of samples calculating the statistical significance (p
  • the score or expression level has been assessed for 100 cancer samples of 100 patients.
  • the 100 samples are ranked according to their score or expression level for the RNAs.
  • Sample 1 has the best expression level and sample 100 has the worst expression level.
  • a first grouping provides two subsets: on one side sample Nr 1 and on the other side the 99 other samples.
  • the next grouping provides on one side samples 1 and 2 and on the other side the 98 remaining samples etc., until the last grouping: on one side samples 1 to 99 and on the other side sample Nr 100.
  • Kaplan Meier curves are prepared for each of the 99 groups of two subsets. Also for each of the 99 groups, the p value between both subsets was calculated.
  • the reference value is selected such as the discrimination based on the criterion of the minimum p value is the strongest.
  • the expression level corresponding to the boundary between both subsets for which the p value is minimum is considered as the reference value. It should be noted that the reference value is not necessarily the median value of expression levels.
  • the reference value (cut-off value) may be used in the present method to discriminate pancreatic cancer samples and therefore the corresponding patients.
  • Kaplan-Meier curves of percentage of survival as a function of time are commonly used to measure the fraction of patients living for a certain amount of time after treatment and are well known by the man skilled in the art.
  • the sequencing step may be accomplished by any method, including without limitation chemical sequencing, using the Maxam-Gilbert method (Methods in Enzymology 65, 499-560 (1980)); by enzymatic sequencing, using the Sanger method Proc. Natl. Acad. Sci. USA 74, 5463-67 (1977)).; mass spectrometry sequencing; sequencing using a chip-based technology; real-time quantitative PCR and RNA Sequencing (RNASeq).
  • chemical sequencing using the Maxam-Gilbert method (Methods in Enzymology 65, 499-560 (1980)
  • enzymatic sequencing using the Sanger method Proc. Natl. Acad. Sci. USA 74, 5463-67 (1977)
  • mass spectrometry sequencing sequencing using a chip-based technology
  • real-time quantitative PCR and RNA Sequencing RNASeq
  • the four base specific sets of DNA fragments are formed by starting with a primer/template system elongating the primer into the unknown DNA sequence area and thereby copying the template and synthesizing a complementary strand by DNA polymerases, such as Klenow fragment of E. coli DNA polymerase I, a DNA polymerase from Therm us aquaticus, Taq DNA polymerase, or a modified T7 DNA polymerase, Sequenase (Tabor et al., Proc. Natl. Acad. Scl. USA 84, 4767-4771 (1987)), in the presence of chainterminating reagents.
  • DNA polymerases such as Klenow fragment of E. coli DNA polymerase I, a DNA polymerase from Therm us aquaticus, Taq DNA polymerase, or a modified T7 DNA polymerase, Sequenase (Tabor et al., Proc. Natl. Acad. Scl. USA 84, 4767-4771 (1987)
  • HTS High-throughput sequencing
  • the sequencing according to the method of the invention is an ultra-deep sequencing like Second-Generation Sequencing (NGS) or Third-Generation Sequencing, performed using targeted massive parallel sequencing approcah, by the mean of which a specified panel of regions in the genome, are sequenced (see for example Goodwin, S and all, 2016. Coming of age: Ten years of next-generation sequencing technologies. Nature Reviews Genetics).
  • NGS Second-Generation Sequencing
  • Third-Generation Sequencing performed using targeted massive parallel sequencing approcah, by the mean of which a specified panel of regions in the genome, are sequenced (see for example Goodwin, S and all, 2016. Coming of age: Ten years of next-generation sequencing technologies. Nature Reviews Genetics).
  • the invention also relates to a method for treating a cancer in a patient identified has having no response or partial response with an ICI according to the methods of the invention comprising administering to said patient a therapeutically effective amount of radiotherapy, chemotherapy, immunotherapy or a combination thereof.
  • treatment refers to both prophylactic or preventive treatment as well as curative or disease modifying treatment, including treatment of subjects at risk of contracting the disease or suspected to have contracted the disease as well as subjects who are ill or have been diagnosed as suffering from a disease or medical condition, and includes suppression of clinical relapse.
  • the treatment may be administered to a subject having a medical disorder or who ultimately may acquire the disorder, in order to prevent, cure, delay the onset of, reduce the severity of, or ameliorate one or more symptoms of a disorder or recurring disorder, or in order to prolong the survival of a subject beyond that expected in the absence of such treatment.
  • therapeutic regimen is meant the pattern of treatment of an illness, e.g., the pattern of dosing used during therapy.
  • a therapeutic regimen may include an induction regimen and a maintenance regimen.
  • the phrase “induction regimen” or “induction period” refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the initial treatment of a disease.
  • the general goal of an induction regimen is to provide a high level of drug to a subject during the initial period of a treatment regimen.
  • An induction regimen may employ (in part or in whole) a "loading regimen", which may include administering a greater dose of the drug than a physician would employ during a maintenance regimen, administering a drug more frequently than a physician would administer the drug during a maintenance regimen, or both.
  • maintenance regimen refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the maintenance of a subject during treatment of an illness, e.g., to keep the subject in remission for long periods of time (months or years).
  • a maintenance regimen may employ continuous therapy (e.g., administering a drug at a regular intervals, e.g., weekly, monthly, yearly, etc.) or intermittent therapy (e.g., interrupted treatment, intermittent treatment, treatment at relapse, or treatment upon achievement of a particular predetermined criteria [e.g., disease manifestation, etc.]).
  • chemotherapeutic agent refers to chemical compounds that are effective in inhibiting tumor growth.
  • examples of chemotherapeutic agents include alkylating agents such as thiotepa and cyclosphosphamide; alkyl sulfonates such as busulfan, improsulfan and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethylenimines and methylamelamines including altretamine, triethylenemelamine, trietylenephosphoramide, triethylenethiophosphaoramide and trimethylolomelamine; acetogenins (especially bullatacin and bullatacinone); a camptothecin (including the synthetic analogue topotecan); bryostatin; callystatin; CC-1065 (including its adozelesin, carzelesin and bizelesin synthetic analogues); cryptophycins (particularly crypto
  • calicheamicin especially calicheamicin (11 and calicheamicin 211, see, e.g., Agnew Chem Inti. Ed. Engl. 33:183-186 (1994); dynemicin, including dynemicin A; an esperamicin; as well as neocarzinostatin chromophore and related chromoprotein enediyne antiobiotic chromomophores), aclacinomysins, actinomycin, authramycin, azaserine, bleomycins, cactinomycin, carabicin, canninomycin, carzinophilin, chromomycins, dactinomycin, daunorubicin, detorubicin, 6- diazo-5-oxo-L-norleucine, doxorubicin (including morpholino-doxorubicin, cyanomorpholinodoxorubicin, 2-pyrrolino-dox
  • paclitaxel (TAXOL®, Bristol-Myers Squibb Oncology, Princeton, N.].) and doxetaxel (TAXOTERE®, Rhone-Poulenc Rorer, Antony, France); chlorambucil; gemcitabine; 6- thioguanine; mercaptopurine; methotrexate; platinum analogs such as cisplatin and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitomycin C; mitoxantrone; vincristine; vinorelbine; navelbine; novantrone; teniposide; daunomycin; aminopterin; xeloda; ibandronate; CPT-1 1 ; topoisomerase inhibitor RFS 2000; difluoromethylomithine (DMFO); retinoic acid; capecitabine; and phannaceutically acceptable salts, acids or derivatives of any of the above.
  • antihormonal agents that act to regulate or inhibit honnone action on tumors
  • anti-estrogens including for example tamoxifen, raloxifene, aromatase inhibiting 4(5)-imidazoles, 4-hydroxytamoxifen, trioxifene, keoxifene, LY117018, onapristone, and toremifene (Fareston); and anti-androgens such as flutamide, nilutamide, bicalutamide, leuprolide, and goserelin; and phannaceutically acceptable salts, acids or derivatives of any of the above.
  • the physician can take the choice to administer the patient with a targeted therapy.
  • Targeted cancer therapies are drugs or other substances that block the growth and spread of cancer by interfering with specific molecules ("molecular targets") that are involved in the growth, progression, and spread of cancer.
  • Targeted cancer therapies are sometimes called “molecularly targeted drugs,” “molecularly targeted therapies,” “precision medicines,” or similar names.
  • the targeted therapy consists of administering the subject with a tyrosine kinase inhibitor.
  • tyrosine kinase inhibitor refers to any of a variety of therapeutic agents or drugs that act as selective or non-selective inhibitors of receptor and/or non-receptor tyrosine kinases. Tyrosine kinase inhibitors and related compounds are well known in the art and described in U.S Patent Publication 2007/0254295, which is incorporated by reference herein in its entirety.
  • a compound related to a tyrosine kinase inhibitor will recapitulate the effect of the tyrosine kinase inhibitor, e.g., the related compound will act on a different member of the tyrosine kinase signaling pathway to produce the same effect as would a tyrosine kinase inhibitor of that tyrosine kinase.
  • tyrosine kinase inhibitors and related compounds suitable for use in methods of embodiments of the present invention include, but are not limited to, dasatinib (BMS-354825), PP2, BEZ235, saracatinib, gefitinib (Iressa), sunitinib (Sutent; SU11248), erlotinib (Tarceva; OSI-1774), lapatinib (GW572016; GW2016), canertinib (CI 1033), semaxinib (SU5416), vatalanib (PTK787/ZK222584), sorafenib (BAY 43-9006), imatinib (Gleevec; STI571), leflunomide (SU101), vandetanib (Zactima; ZD6474), MK-2206 (8-[4- aminocyclobutyl)phenyl] -9-phenyl- 1 ,2,4-triazolo [3 ,
  • the tyrosine kinase inhibitor is a small molecule kinase inhibitor that has been orally administered and that has been the subject of at least one Phase I clinical trial, more preferably at least one Phase II clinical, even more preferably at least one Phase III clinical trial, and most preferably approved by the FDA for at least one hematological or oncological indication.
  • inhibitors include, but are not limited to, Gefitinib, Erlotinib, Lapatinib, Canertinib, BMS- 599626 (AC-480), Neratinib, KRN-633, CEP-11981, Imatinib, Nilotinib, Dasatinib, AZM- 475271, CP-724714, TAK-165, Sunitinib, Vatalanib, CP-547632, Vandetanib, Bosutinib, Lestaurtinib, Tandutinib, Midostaurin, Enzastaurin, AEE-788, Pazopanib, Axitinib, Motasenib, OSI-930, Cediranib, KRN-951, Dovitinib, Seliciclib, SNS-032, PD-0332991, MKC-I (Ro- 317453; R-440), Sorafenib, ABT
  • the physician can take the choice to administer the patient with an immunotherapeutic agent (a different from the first used).
  • immunotherapeutic agent refers to a compound, composition or treatment that indirectly or directly enhances, stimulates or increases the body's immune response against cancer cells and/or that decreases the side effects of other anticancer therapies. Immunotherapy is thus a therapy that directly or indirectly stimulates or enhances the immune system's responses to cancer cells and/or lessens the side effects that may have been caused by other anti-cancer agents. Immunotherapy is also referred to in the art as immunologic therapy, biological therapy biological response modifier therapy and biotherapy. Examples of common immunotherapeutic agents known in the art include, but are not limited to, cytokines, cancer vaccines, monoclonal antibodies and non-cytokine adjuvants. Alternatively the immunotherapeutic treatment may consist of administering the patient with an amount of immune cells (T cells, NK, cells, dendritic cells, B cells. ..).
  • Immunotherapeutic agents can be non-specific, i.e. boost the immune system generally so that the human body becomes more effective in fighting the growth and/or spread of cancer cells, or they can be specific, i.e. targeted to the cancer cells themselves immunotherapy regimens may combine the use of non-specific and specific immunotherapeutic agents.
  • Non-specific immunotherapeutic agents are substances that stimulate or indirectly improve the immune system.
  • Non-specific immunotherapeutic agents have been used alone as a main therapy for the treatment of cancer, as well as in addition to a main therapy, in which case the non-specific immunotherapeutic agent functions as an adjuvant to enhance the effectiveness of other therapies (e.g. cancer vaccines).
  • Non-specific immunotherapeutic agents can also function in this latter context to reduce the side effects of other therapies, for example, bone marrow suppression induced by certain chemotherapeutic agents.
  • Non-specific immunotherapeutic agents can act on key immune system cells and cause secondary responses, such as increased production of cytokines and immunoglobulins. Alternatively, the agents can themselves comprise cytokines.
  • Non-specific immunotherapeutic agents are generally classified as cytokines or non-cytokine adjuvants.
  • cytokines have found application in the treatment of cancer either as general non-specific immunotherapies designed to boost the immune system, or as adjuvants provided with other therapies.
  • Suitable cytokines include, but are not limited to, interferons, interleukins and colony-stimulating factors.
  • Interferons contemplated by the present invention include the common types of IFNs, IFN-alpha (IFN-a), IFN-beta (IFN-beta) and IFN-gamma (IFN-y).
  • IFNs can act directly on cancer cells, for example, by slowing their growth, promoting their development into cells with more normal behaviour and/or increasing their production of antigens thus making the cancer cells easier for the immune system to recognise and destroy.
  • IFNs can also act indirectly on cancer cells, for example, by slowing down angiogenesis, boosting the immune system and/or stimulating natural killer (NK) cells, T cells and macrophages.
  • NK natural killer
  • IFN-alpha is available commercially as Roferon (Roche Pharmaceuticals) and Intron A (Schering Corporation).
  • Interleukins contemplated by the present invention include IL-2, IL-4, IL-11 and IL-12. Examples of commercially available recombinant interleukins include Proleukin® (IL-2; Chiron Corporation) and Neumega® (IL-12; Wyeth Pharmaceuticals).
  • Zymogenetics, Inc. (Seattle, Wash.) is currently testing a recombinant form of IL-21, which is also contemplated for use in the combinations of the present invention.
  • Interleukins alone or in combination with other immunotherapeutics or with chemotherapeutics, have shown efficacy in the treatment of various cancers including renal cancer (including metastatic renal cancer), melanoma (including metastatic melanoma), ovarian cancer (including recurrent ovarian cancer), cervical cancer (including metastatic cervical cancer), breast cancer, colorectal cancer, lung cancer, brain cancer, and prostate cancer.
  • Interleukins have also shown good activity in combination with IFN-alpha in the treatment of various cancers (Negrier et al., Ann Oncol. 2002 13(9): 1460-8; Touranietal, J. Clin. Oncol. 2003 21(21):398794).
  • Colony-stimulating factors contemplated by the present invention include granulocyte colony stimulating factor (G-CSF or filgrastim), granulocyte-macrophage colony stimulating factor (GM-CSF or sargramostim) and erythropoietin (epoetin alfa, darbepoietin).
  • G-CSF or filgrastim granulocyte colony stimulating factor
  • GM-CSF or sargramostim granulocyte-macrophage colony stimulating factor
  • erythropoietin epoetin alfa, darbepoietin
  • colony stimulating factors are available commercially, for example, Neupogen® (G-CSF; Amgen), Neulasta (pelfilgrastim; Amgen), Leukine (GM-CSF; Berlex), Procrit (erythropoietin; Ortho Biotech), Epogen (erythropoietin; Amgen), Amesp (erytropoietin).
  • Colony stimulating factors have shown efficacy in the treatment of cancer, including melanoma, colorectal cancer (including metastatic colorectal cancer), and lung cancer.
  • Non-cytokine adjuvants suitable for use in the combinations of the present invention include, but are not limited to, Levamisole, alum hydroxide (alum), Calmette-Guerin bacillus (ACG), incomplete Freund's Adjuvant (IF A), QS-21, DETOX, Keyhole limpet hemocyanin (KLH) and dinitrophenyl (DNP).
  • Non-cytokine adjuvants in combination with other immuno- and/or chemotherapeutics have demonstrated efficacy against various cancers including, for example, colon cancer and colorectal cancer (Levimasole); melanoma (BCG and QS-21); renal cancer and bladder cancer (BCG).
  • immunotherapeutic agents can be active, i.e. stimulate the body's own immune response, or they can be passive, i.e. comprise immune system components that were generated external to the body.
  • Passive specific immunotherapy typically involves the use of one or more monoclonal antibodies that are specific for a particular antigen found on the surface of a cancer cell or that are specific for a particular cell growth factor.
  • Monoclonal antibodies may be used in the treatment of cancer in a number of ways, for example, to enhance a subject's immune response to a specific type of cancer, to interfere with the growth of cancer cells by targeting specific cell growth factors, such as those involved in angiogenesis, or by enhancing the delivery of other anticancer agents to cancer cells when linked or conjugated to agents such as chemotherapeutic agents, radioactive particles or toxins.
  • Monoclonal antibodies currently used as cancer immunotherapeutic agents that are suitable for inclusion in the combinations of the present invention include, but are not limited to, rituximab (Rituxan®), trastuzumab (Herceptin®), ibritumomab tiuxetan (Zevalin®), tositumomab (Bexxar®), cetuximab (C-225, Erbitux®), bevacizumab (Avastin®), gemtuzumab ozogamicin (Mylotarg®), alemtuzumab (Campath®), and BL22.
  • Monoclonal antibodies are used in the treatment of a wide range of cancers including breast cancer (including advanced metastatic breast cancer), colorectal cancer (including advanced and/or metastatic colorectal cancer), ovarian cancer, lung cancer, prostate cancer, cervical cancer, melanoma and brain tumours.
  • Other examples include anti-CTLA4 antibodies (e.g. Ipilimumab), anti-PDl antibodies, anti-PDLl antibodies, anti-TIMP3 antibodies, anti-LAG3 antibodies, anti-B7H3 antibodies, anti-B7H4 antibodies or anti-B7H6 antibodies.
  • a patient diagnosed as having a CMMRD or a MSI leukemia/lymphoma according to the invention can be treated by immunotherapy like immune checkpoint blockade involving anti-CTLA4, anti-PDl, anti-PD-Ll alone or in combination, or anti-cancer vaccines or dendritic cells vaccines based on tumour specific antigens.
  • immunotherapy like immune checkpoint blockade involving anti-CTLA4, anti-PDl, anti-PD-Ll alone or in combination, or anti-cancer vaccines or dendritic cells vaccines based on tumour specific antigens.
  • Cancer vaccines have been developed that comprise whole cancer cells, parts of cancer cells or one or more antigens derived from cancer cells. Cancer vaccines, alone or in combination with one or more immuno- or chemotherapeutic agents are being investigated in the treatment of several types of cancer including melanoma, renal cancer, ovarian cancer, breast cancer, colorectal cancer, and lung cancer. Non-specific immunotherapeutics are useful in combination with cancer vaccines in order to enhance the body's immune response.
  • the immunotherapeutic treatment may consist of an adoptive immunotherapy as described by Nicholas P. Restifo, Mark E. Dudley and Steven A. Rosenberg “Adoptive immunotherapy for cancer: harnessing the T cell response, Nature Reviews Immunology, Volume 12, April 2012).
  • the subject In adoptive immunotherapy, the subject’s circulating lymphocytes, or tumor infiltrated lymphocytes, are isolated in vitro, activated by lymphokines such as IL-2 or transuded with genes for tumor necrosis, and readministered (Rosenberg et al., 1988; 1989).
  • the activated lymphocytes are most preferably be the subject’s own cells that were earlier isolated from a blood or tumor sample and activated (or “expanded”) in vitro.
  • This form of immunotherapy has produced several cases of regression of melanoma and renal carcinoma.
  • the physician can take the choice to administer the patient with a radiotherapeutic agent.
  • radiotherapeutic agent as used herein, is intended to refer to any radiotherapeutic agent known to one of skill in the art to be effective to treat or ameliorate cancer, without limitation.
  • the radiotherapeutic agent can be an agent such as those administered in brachytherapy or radionuclide therapy.
  • Such methods can optionally further comprise the administration of one or more additional cancer therapies, such as, but not limited to, chemotherapies, and/or another radiotherapy.
  • Kits or devices of the present invention are provided.
  • a further object of the present invention relates to a kit or device for performing the methods of the present invention, comprising means for extracting and sequencing DNA from a sample.
  • the kit or device comprises at least one couple of primer per gene.
  • FIGURES are a diagrammatic representation of FIGURES.
  • FIG. 1 Workflow and Study Design. MSS, microsatellite stable; mCRC, metastatic colorectal cancer; ICI, immune checkpoint inhibitors; IHC, Immunohistochemistry; QC, quality control; pMMR, mismatch repair proficient.
  • Figure 2 MS selection and random Forest analysis on somatic variants. Kaplan- Meier curves of iPFS are shown accordingly to risk probability in ImmunoMSI only. “Predicted group High” curve corresponds to patients with low probability ( ⁇ 10%) and “Predicted group Low” curve corresponds to patients with high probability (>10%) RF probability. Log-rank test p-value between the group equals 0.00312.
  • Figure 3 C) Kaplan-Meier estimates using the third quantile threshold of the stromal signature.
  • MSIsensor version 0.6
  • MSICare MSIsensor score threshold of 10% or more was used to classify the MSI-H tumor (MSI-High) and a MSICare threshold of 20% was used to define MSI status as previously described 30.
  • somatic mutations used for the mutational load were filtered as follows: Somatic score > 3, Mutated Allele Frequency in Tumor tissue > 5%, Mutated Allele Count in Tumor tissue > 3, Mutated Allele Frequency in Constitutional tissue ⁇ 4%.
  • ICA Independent Component Analysis
  • the intra-tumor proportion of the consensus molecular subtypes of colorectal cancer were estimated using the centroids of the original study 32 and the WISP deconvolution method (cit-bioinfo . github . io/WI SP/) .
  • FIG.1A targeted next-generation-sequencing (NGS) and RNASeq were performed on 66 and 73 mCRC +/- matched normal colonic mucosa paraffin-embedded samples, respectively, after removing unqualified samples for similar reasons, i.e., insufficient quantity and/or low-quality level (FIG.1A).
  • NGS next-generation-sequencing
  • RNASeq RNASeq
  • FIGURE 1 also summarizes the flow chart (FIG. 1 A) and the current design of the study (FIG. IB).
  • FPS progression-free survival
  • iRECIST RECIST for Response Evaluation Criteria in Solid Tumor
  • the level of MSI and TMB in tumor DNA does not predict response to ICI in patients following exclusion of ICI-treated mCRC with misdiagnosed dMMR/MSI status.
  • MSI-driven somatic events at microsatellites i.e., mononucleotide repeats
  • microsatellites i.e., mononucleotide repeats
  • RNAseq analysis fails to identify established phenotypic markers associated with response to ICI in MSI mCRC patients.
  • Three types of markers were applied to and systematically assessed in both discovery (Cl) and validation (C2) cohorts, i.e., signatures quantifying cellular components of the tumor microenvironment, single gene expression levels, and pathway-level estimations of expression.
  • TME tumor microenvironment
  • components previously associated to differential response to ICI such as the infiltration levels of T or B lymphocytes, of the monocyte lineage or of fibroblasts could not be reproducibly associated to iPFS in the two ICI-treated MSI mCRC cohorts (data not shown).
  • RNA signatures of cellular component of the TME were tested encompassing various immune and stromal phenotypes, none of which had a significant association with iPFS in either cohort (FDR 5%) (data not shown). Similar results were obtained with the estimated expression activity of 3,365 pathways (data not shown).
  • gene sets involved in angiogenesis, epithelial-to-mesenchymal transition, related TGF-beta and Wnt/Wingless signaling pathways, as well as TNF, interferon, KRAS or mTOR had either a minor and unreproduced association with iPFS in one cohort but more generally no significant correlation with survival in any of the two ICI-treated MSI mCRC cohorts (data not shown).
  • the gene-level expression association (10,515 genes tested) identified 5 genes with significant association to iPFS in C2 with either no association with iPFS in Cl and often an opposite hazard-ratio (data not shown).
  • signatures previously established in generic contexts or associated to response to ICI in MSS tumors failed to show any signal in MSI mCRC.
  • RNA signatures i.e., phenotypic descriptors effectively observable in MSI mCRC
  • an unsupervised blind source separation approach was applied to the 44 NIPICOE transcriptome profiles (Cl).
  • Ten independent components were extracted, four of which were significantly associated to objective response as evaluated by iRECIST in Cl (data not shown) (29). Two of these were also associated to shorter iPFS in this cohort of patients treated with a combination of ICI suggesting a long-term predictive value of these signatures. Finally, only one of these was also associated to iPFS in C2 (data not shown).
  • This signature was associated to a tendon-like phenotype, extracellular matrix (ECM)- producing and interacting genes and was considered as an RNA signature of malignant- associated fibrosis and to be referred to as a stromal signature.
  • the signature was significantly correlated to an RNA-based quantification of fibroblasts (P ⁇ 0.001) and anti-correlated to the tumor cellularity (P ⁇ 0.001) confirming its stromal origin (data not shown).
  • a transcriptomic deconvolution model of the consensus molecular subtypes of CRC (CMS1 to CMS4) was applied to Cl identifying most samples as mainly CMS1 (72%) as well as a substantial number of samples as predominantly CMS4 (22%) (32).
  • the stromal signature was also significantly correlated with the intra-tumor CMS4 proportion, suggesting to specifically quantify the stromal counterpart of the CMS4 subtype.
  • Kaplan-Meier analyses of the stromal signature and its significant clinical impact regarding response to ICI in patients from Cl and C2 are also shown in FIGURE 3.
  • the signature was applied to five series of nonmetastatic or metastatic MSI CRC that did not receive ICI (data not shown).
  • stromal signature was not associated to disease-free survival (DFS) or progression-free survival (PFS) in any of the five series, both in metastatic (PFS) and nonmetastatic (DFS) settings, suggesting a strong specific predictive value of this RNA indicator for the efficacy of immune checkpoint inhibitors in MSI mCRC.
  • FFS disease-free survival
  • PFS progression-free survival
  • DFS nonmetastatic
  • RNA signature was reduced to 182 genes and no learning process was applied to retrain weights for prediction.
  • spearman correlation with the original signature was 0.98 in NIPICOL and 0.96 in immunoMSI. Both were associated with iPFS as continuous scores.
  • Figures 4A and4 B show the Kaplan- Meier curves of iPFS using the same cut-off as with the original signature.

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Abstract

La présente invention concerne la prédiction d'une réponse à des inhibiteurs de point de contrôle immunitaire (ICI). Dans cette étude, les inventeurs ont abordé le problème de la réponse aux ICI sur la base de deux cohortes prospectives indépendantes de 44 et 73 patients avec un cancer colorectal métastatique (mCRC) du type dMMR/MSI, respectivement l'essai clinique NIPICOL multicentrique et la cohorte ImmunoMSI prospective. Après une réévaluation centrale concernant le statut dMMR/MSI à l'aide de procédés de référence pour éliminer les cas de mCRC mal diagnostiqués, un séquençage d'ADN et D'ARN combiné des tissus tumoraux de ces patients a été effectué. Suite à une analyse supervisée des données de profils moléculaires qui n'ont pas réussi à confirmer des indicateurs d'ADN/ARN précédemment proposés pour la réponse à un traitement, l'utilisation de procédés innovants leur a permis d'identifier des signatures d'ADN et d'ARN indépendantes robustes pour prédire la résistance aux ICI. Des tests de plusieurs cohortes rétrospectives et prospectives regroupant 446 patients avec un cancer colorectal (CRC) du type MSI métastatique ou non métastatique non traité par ICI ont également été effectués pour évaluer la spécificité de la nature prédictive de ces indicateurs, c'est-à-dire dans le contexte d'une thérapie de blocage de point de contrôle immunitaire. Ainsi, la présente invention concerne un procédé de prédiction d'une réponse à un inhibiteur de point de contrôle immunitaire (ICI) chez un patient atteint d'un cancer MSI consistant à déterminer l'état de variation au niveau des microsatellites (MS) d'un ensemble de gènes sélectionnés et l'utilisation d'un algorithme d'apprentissage automatique.
PCT/IB2022/000719 2022-12-14 2022-12-14 Procédé de prédiction d'une réponse à des inhibiteurs de point de contrôle immunitaire chez un patient atteint d'un cancer du type msi Ceased WO2024127053A1 (fr)

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PCT/EP2023/085678 WO2024126609A1 (fr) 2022-12-14 2023-12-13 Procédé de prédiction d'une réponse à des inhibiteurs de point de contrôle immunitaire chez un patient atteint d'un cancer msi

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