NZ725780B2 - Method for selecting personalized tri-therapy for cancer treatment - Google Patents

Abstract

The present invention relates to a method for determining the best combinations of at least three drugs for treating cancer, which is based on the determination of the most relevant intervention points for an individual.

Description

METHOD FOR SELECTING PERSONALIZED TRl-THERAPY FOR CANCER TREATMENT FIELD OF THE INVENTION The present invention relates to the field on gy, especially to personalized medicine in cancer therapy. More particularly, it relates a new concept of therapeutic approach, the triple regimen therapy and method for selecting the most appropriate combinations of drugs for treating cancer in a ular subject.

BACKGROUND OF THE INVENTION Lung cancer is the most common malignancy worldwide with a staggering 1.8 million cases diagnosed per year. Over half of NSCLC are diagnosed at the metastatic stage. Even utilizing the standard of care in the Western world, consisting mainly of chemotherapeutic agents and radiation therapy, there has been little impact on mortality, with only 30% of all patients diagnosed (regardless of stage) alive at one year, and a dismal 1 and 5 year survival rates of about 8-15% and 4%, tively for those with metastatic disease. For patients that have failed first line therapy, the median survival is only about 7 months.

Progress brought by targeted therapies such as matching EGFR activating mutations or ALK ocation have shown substantial response rates, demonstrating the potency of molecularly-matched targeted therapy, but erapies such as these apply to only small subsets of patients, and virtually all patients develop resistance and succumb to their disease. This is s not cted, as patients often harbor multiple lar aberrations that require prosecution. The power of combination therapy has been illustrated in diseases such as Hodgkin’s lymphoma where cure was effected by combinations. Further in the modern era of targeted therapy, combinations targeting the same pathway (e.g. trametanib (MEK) inhibitor er with dabrafenib (BRAF inhibitor) in BRAF-mutant ma, or resistance pathways ning PIK3CA and MEK inhibitors) are y being tested and have shown efficacy, in some cases, but no cure and no significant impact on survival. Combinations of targeted therapy in NSCLC have, however, to date, been very limited in scope.

Personalized medicine today offers modest benefits in advanced metastatic disease (especially lung cancer). Mono-therapies have failed to cure advanced diseases. Most combination herapies lack an underlying biologic or molecular rationale.

Therefore, there is a strong need to define, for each ic patient, the best combinations of drugs for treating cancer.

SUMMARY OF THE ION The ors present a novel concept of therapy in cancer, in particular metastatic lung cancer, based on tri therapy associating three ed drugs. They created a fied interventional mapping system (SIMS) merging knowledge from drugs and rks of . An interventional point means a target/gene, or a group of targets/genes, activated and that can be blocked by a drug. They described 24 interventional points based on a collection of 183 genes. Method of investigation of status of activation of the interventional points is based on complete genomics investigation of dual tumor and normal biopsies matched from strictly the same points, and preferably comprise sequencing, copy number variation gene expression and miRNA expression. An algorithm was developed to create a scoring , e.g. from 1 to 10, enabling the ranking of the activated interventional points in each patient.

Based on score and trends of co-activation of interventional points, the invention presents a new scientific rationale to associate combination of therapiesAccordingly, the present invention relates to a method for determining in a patient having a cancer a classification of intervention points according to their activation status, wherein - the intervention points comprise the group consisting of the HER, , PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, JAK-STAT, Hedgehog, NOTCH pathway, DNA Repair and RET, ALK, ROS1 and UB1, or any subgroup thereof of at least 10 intervention points; and the genes of each intervention point are defined according to Table 1 or 9; - the method ses - characterizing a tumor sample in comparison to a normal histologically matched sample from the same t, including - for each pathway of the group or subgroup of intervention points, determining the mRNA expression level of the genes of the intervention point as disclosed in Table 1 or 9, y determining a fold change of mRNA expression of tumor vs normal, (referred as mRNA TvN fold change» wholly or partially sequencing genes of Table 1 or 9, thereby identifying the ce of ting mutation in the tumor ; optionally, for each intervention point of the group or subgroup of intervention points, determining the level of miRNAs of the genes of the intervention point as disclosed in Table 1 or 9, thereby determining a fold change of miRNAs level of tumor vs normal, (referred as miRNA TvN fold change» optionally, for each intervention point of the group or subgroup of intervention points, determining the copy number variation of the genes of the intervention point as disclosed in Table 1 or 9, thereby determining a tumor vs normal fold change for the amplified genes; — calculating a score for each pathway based on the characterization data, wherein — if, in the tumor sample, the presence of an activating mutation of a gene of an intervention point is detected, then a maximal score is given to the intervention point, in particular a score of 10 if the g if from 1 to 10; a score, preferably from 1 to 10, is calculated based on the arithmetic mean of the mRNA TvN fold changes of the genes for each intervention point of the group or subgroup of ention points, provided that the mRNA TvN fold change of a gene is taken into consideration only if its value is at least 1.3; and — the score of each intervention point of the group or up of ention points is either a) the sum of the score due to the presence of an activating mutation and the score calculated by the average of the mRNA TvN fold changes; or b) the score due to the presence of an activating mutation if there is a mutation or the score calculated based on the arithmetic mean ofthe mRNA TvN fold changes in absence of mutation; and — classifying the intervention points ing to the calculated scores.

W0 2015/193212 Preferably, the genes of Table 10 are sequenced for detecting the presence of mutations as defined in Table 10 and p53 gene is ced.

Preferably, for each intervention point of the group or subgroup of intervention points, the method comprises determining the miRNAs level of the genes of the pathway as disclosed in Table 1 or 9, in particular the level of miRNAs of the genes of the pathway as disclosed in Table 11. More preferably, before the step of score calculation, a mean miRNAs fold change for each gene is calculated as the average of the miRNA TvN fold changes for the gene, a corrected mRNA TvN fold change is calculated by dividing the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold change) by the mean fold change for the miRNAs of the gene (mean miRNA TvN fold change), and the corrected mRNA TvN fold change of the gene is then used to calculate the arithmetic mean of the mRNA TvN fold changes of the genes for each intervention point. In a red embodiment, the level of miRNAs is determined and used to calculate a corrected mRNA TvN fold change for the genes of the following intervention points: mTOR-AKT-PTEN, RAS, ERK, P|3K and Immune Modulators. ably, for each intervention point of the group or subgroup of intervention points, the method comprises ining the copy number variation of the genes of the pathway as disclosed in Table 1 or 9. More preferably, before the step of score calculation, a corrected mRNA TvN fold change of a gene of an intervention point is calculated by multiplying the mRNA TvN fold change of the gene by the CNV fold change of the gene, and the corrected mRNA TvN fold change of the gene is then used to calculate the arithmetic mean of the mRNA TvN fold changes of the genes for each intervention point.

Preferably, the subgroup of intervention points consists in the following group: Her, CDK4,6, PLK/AURK/Kinesins, enesis, Immune tors, P|3K, MET, MEK, ERK, Anti- Apoptosis, FGF, mTOR, Ras/Raf, IGF/glycolysis, Wnt, PARP, and DNA .

Preferably, it further comprise selecting a group of three activated or bed intervention points in a patient having a cancer, wherein three intervention points are selected among the intervention points having the t scores, preferably the three intervention points having the highest scores.

The present invention also relates to a method for selecting a combination of three drugs useful for treating a patient having a , wherein a group of three activated or disturbed ention points are selected by the method of claim 9 and a drug is selected for each or disturbed intervention point, thereby providing a combination of three drugs.

In addition, the present invention relates to the use of a kit for classifying pathways according to their activation , wherein the kit comprises means for ing the mRNA expression level of the genes of Table 1 or 9 for intervention points comprising the group consisting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, poptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, JAK-STAT, Hedgehog, NOTCH pathway, DNA Repair and Others’ (namely RET, ALK, R051 and U81), or any up thereof of at least 10 intervention points. Preferably, the kit further ses means for detecting the mutations of Table 10. More preferably, the kit further comprises means for measuring the miRNA level of miRNA of Table 11 for intervention points comprising the group consisting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, JAK-STAT, Hedgehog, NOTCH, DNA Repair and Others’ (namely RET, ALK, R051 and U81), or any subgroup thereof of at least 10 intervention points. Optionally, the kit further comprises means for determining the copy number variation of the genes of Table 1 or 9 for pathways comprising the group consisting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, AT, og, NOTCH, DNA Repair and Others’ (namely RET, ALK, R051 and U81), or any subgroup thereof of at least 10 intervention points.

Finally, the present invention s to a drugs combination for use in the treatment of cancer, n the drugs combination is selected amoung the combinations disclosed in Table 6, Table 7, Table 8 or selected in the group consisting of anti PD1L + Pan RAF inhibitor + MtorP|3K inhibitor anti PD1L + Pan RAF inhibitor + angiogenesis inhibitor anti PD1L + Pan RAF inhibitor + MET inhibitor anti PD1L + Pan RAF inhibitor + CDK4,6 inhibitor anti CTLA4 + Pan RAF inhibitor + MtorP|3K inhibitor anti CTLA4 + Pan RAF inhibitor + angiogenesis inhibitor anti CTLA4 + Pan RAF inhibitor + MET inhibitor anti CTLA4 + Pan RAF tor + CDK4,6 inhibitor anti PD1L + MEK inhibitor + MtorP|3K dual inhibitor WO 93212 anti PD1L + MEK inhibitor + angiogenesis inhibitor anti PD1L + MEK inhibitor + MET inhibitor anti PD1L + MEK inhibitor + CDK,-6 inhibitor anti CTLA4 + MEK inhibitor + MtorP|3K dual inhibitor anti CTLA4 + MEK inhibitor + MET inhibitor anti CTLA4 + MEK inhibitor + angiogenesis inhibitor, and anti CTLA4 + MEK tor + CDK4,6 inhibitor.

Preferably, the drugs included in the combination are selected from those sed in Table More ably, the drugs combination is selected in the group consisting of Medi-4736 (Astra Zeneca) + 0 (Takeda) + PF-384 (Pfizer) Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + Axitinib (Pfizer) or Motesanib (Takeda) Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + Crizotinib (Pfizer) Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + Palbociclib (Pfizer) Tremelimumab (Astra Zeneca) + MLN2480 (Takeda) + PF-384 (Pfizer) Tremelimumab (Astra Zeneca) + MLN2480 a) + Axitinib (Pfizer) or Motesanib (Takeda) Tremelimumab (Astra Zeneca) + MLN2480 (Takeda) + Crizotinib (Pfizer) imumab (Astra ) + MLN2480 (Takeda) + Palbociclib (Pfizer) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + PF-384 (Pfizer) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + Axitinib (Pfizer) or Motesanib (Takeda) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + Crizotinib (Pfizer) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + Palbociclib (Pfizer) Tremelimumab (Astra Zeneca) + Selumetinib (Astra Zeneca) + PF-384 (Pfizer) Tremelimumab (Astra Zeneca) + Selumetinib (Astra Zeneca) + Crizotinib (Pfizer) imumab (Astra Zeneca) + Selumetinib (Astra Zeneca) + Axitinib (Pfizer) or Motesanib (Takeda), and Tremelimumab (Astra Zeneca) + Selumetinib v + Palbociclib r).

Preferably, the cancer is a lung , more preferably a NSCLC.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1. The framework for cPCM. The problem is divided into 3 parts: A. Mapping eutic efficacy to cellular components; B. Scoring the status of ic nodes in the interventional maps defined in (A) and (C) predicting combination efficacy Figure 2. Flowchart of the scoring .

Figure 3. In Y: Mean fold change of differential gene expression between T and N in each patient. In X: number of patients NB: for each graph, the order of patients is different. This series serve as calibrator for calculation of deciles.

Figure 4. Representation 3D of the scoring system. Axis Z shows score from 1 to 10. Axis X represents and example of interventional points, axis y represents each patiennt DETAILED DESCRIPTION OF THE INVENTION General Concept Since monotherapies fails to cure metastatic lung cancer diseases, and dual ations reported today on other es does not imact significantly survival, the inventors envision applying tri-therapy, following the ical success in AIDS.

The challenge raised by the invention is choosing triple drug combinations that can benefit a patient. 0 Single drugs are doing poorly; patients respond but ably relapse, often within a few months. Based on the molecular complexity of metastatic disease, combinations are needed. This situation may be analogous to that with AIDS, wherein single agents resulted in incremental effects, but ation of three drugs has demonstrated long-term benefit. 0 Unlike viruses, which always depend on the same ns, tumors are heterogeneous and the biology is too complex for a single tri-therapy combination to work on all tumors. 0 As a result, combinatorial precision cancer medicine (cPCM) is needed. 0 A d number of pathways may be abnormal in metastatic tumors.

The proposed approach The inventors assert that, by reasonable assumptions, a realistic framework can be established today that would allow useful drug combinations to be identified in a personalized way (i.e. ng the combination to the patient based on the tumor properties).

The main idea is to divide and conquer — proposing 3 steps: 1. Find a set of markers that are tive for specific interventional points of every class of drugs: 24 markers covering 183 genes 2. Find a score that summarizes the behavior of these markers in a given patient that is both comparable to other classes and is proportional to the probability that this drug would work; and 3. Figure out how to e drugs such that the combination is common enough to allow clinical testing yet we retain the ability to match combinations to patients with sufficient precision.

Based on these assumptions, the inventors propose the SIMS (Simplified interventional points mappins gystem) framework for ion combinational cancer medicine e 1). 0 First, they propose to reduce the enormous complexity of biological ys and pathway cross-talk by devising a fied map that only concentrates on the genes that are most indicative of drug target status. They propose to define "intervention points", which consists of drug targets or group of targets as well as genes upstream of the targets that together reflect a specific biological ty that is actionable through therapeutic interventions. For example, pan-HER therapies define the HER group of receptors and their ligands as a single intervention point (Figure 1a). 0 The second part of the work, the inventors propose a very simple approach for prioritizing intervention points for a specific patient. The basic premise behind the score is that, when the genes associated with an ention point are more disturbed (in terms of sequence and/or expression level), the intervention point is more likely to be crucial to the tumor. From this, it stems that the more disturbed the genes of an intervention point, the more likely it is that therapeutics targeted at that points will benefit the patient. The inventors are in the process of developing a family of simple scores that e the level of gene sion in the tumor (relative to matched normal control), the aberrations found in the intervention points' genes, CNVs and miRNAs expression levels. Rank ization (in the example, using deciles) is used to make the scores of different intervention points comparable.

Finally, given a le system for determining which drugs are more likely to benefit the patient, a method is needed for choosing combinations that are likely to benefit the patients. Here the inventors propose a tical approach, using a panel of 123 lung cancer patients as an e. Using the methods described above, they describe the status of 24 intervention points in the 123 patients. From this, they applied a knowledge-driven approach to look for drug combinations that are likely to synergistically benefit the patient. Using a panel of experts, they fied those pathways that ur frequently in the patients and are mechanistically independent. To further improve the efficacy of the ed combinations, the inventors propose augmenting the combined targeted therapies with immunomodulating therapies (i.e. anti-CDlL and anti-CTLA). The rational behind this combination is to reduce the chance of intolerable side effects while maintain the predicted efficacy of a triple y regimen Table 1 summarizes the interventional points presenting genes involved and main classes of drugs Interventional ents of the inteventional points Drugs acting on node interventional points _EGF,TGFA,AREG,EREG,HBEGF,BTC,NRGl, Dacomitinib-Panher NRGZ,NRG4,EGFR ,ERBBZ inhibitor Pfizer , ERBBB,ERBB4 CDK4, CDK6,CCND1, CCND2,CCND3, Palbociclib CDK4, 6 CDKN2A, CDKNZB, CCNEl, CCNE2, CCNE3, RBl inhibitor Pfizer PLK / PLK1,AURKA,BORA,|LK,K|F11 MLN8237 (Aurora A AURK/Kine kin inhib) Takeda VEGFA,VEGFB,VEGFC,VEGFD,VEGFR1,VEGFR2, Axitinib GFR VEGFR3,PDGFA,PDGFB,PDGFRA,PDGFRB,Kit Pfizer Motesanib anti VEGFR/PDGFR/kit Takeda Angiopoietins THBSl, TGFBl, ANGPTl, ANGPT2, ANGPTLl, - ANGPT4, TlEl, TEK PDlL, PDCDlLGZ, PDCDl, CTLA4, LAG3 Medi-4736 (PDLl) AZ (Astra Zeneca) AMP514 (PD1) AZ Tremelimumab (CTLA4) AZ PF-05082566 (4-1 P|K3CA,P|K3CB,P|K3CD,P|K3CG,P|K3CZB,PRKCB, PF-384 PI3K/mTOR- PRKCA,PRKCB,P|K3R1,P|K3R2,P|K3R3 inhibitor Pfizer AZD8186 (Pl3Kb)AZ MLN1117 (Pl3Kalpha tor) Takeda MET HGF,MET,AXL,MST1R inib Pfizer nib (cMet) AZ MLN1117, MLN0128 Takeda MAP2K1, MAP2K2, MAP2K3, MAP2K4, MAP3K1, Selumetinib (MEK) MAP3K2, MAP3K3, MAP3K4 AZ MAPK3,MAPK1,KSR1,MAPK11 Anti-apoptosis BCL2,BCLXL,B|RC5,X|AP,BAK1 ,TP53 FGFl to FGF18, FGFRl, FGFR2, FGFR3, FGFR4 7 (FGFRl, 2, 3) AZ mTOR mTor,AKT1,AKT2,PTEN PF-384 Pl3K/mTOR ,TSC1,TSC2,STK11,P|M 1,P| M2,P|M3 inhibitor Pfizer AZD2014 (TOR kinase) AZ AZD5363 (AKTl, 2 ,3) AZ AZD1208 (PIM1, 2) MLN0128 (TORCl/TORCZ) Takeda Ras/Raf KRAS,NRAS ,HRAS ,RAFl ,BRAF, CRAF MLN2480 (Pan-RAF inhibitor) Ta keda Telomerase TERT,TERC,TEP1,HSP90AA1,DKC1,PTGE53 IGF / glycolysis IGFl,|GF2,|GF1R,|GF2R,|NSR,IRSl,PKM 73 (IGF) AZ CDHl, CTNNAl, CTNNBl, WNT 1, FZDl, WNT5A, B, FZD5, WlFl, DKKl PARP PARPl, BRCAl, XRCCl, RAD54L, RAD54B, ATM, Olaparib (PARP) AZ ATR, CHEKl, CHEK2, WEEl AZD1775 (Weel) AZ AZD6738 (ATR) AZ HDAC HDACl, HDAC2, HDAC3, HDAC4, HDAC5 JAK-STAT JAK1,JAK2,STAT1,STAT2,STAT3,SOCSl Hedgehog SHH,PTCH1,SMO,STK36,PRKACA,SUFU,GL|1 NOTCH NOTCH1,Adam17,PSEN1,NCSTN,JAGl,SRRT,APH1A DNA Repair ERCC1,RAD52,XRCC4,RAD51,BRCA1,NEDD8,NAE1 MLN 4924 (NEDD8 AE) Takeda RET, ALK, ROSl, UBl Conclusion The inventors propose a new therapeutic approach of triple n therapies aiming at blocking aneously three different biologic abnormalities and reducing the chance of developing the secondary ance. In addition, for defining a combination of drugs, the inventors identified specific interventional points of drugs based on the pathways specifically up-regulated in one particular patient having a cancer. They defined a simplified interventionanl mapping system within the hallmarks of cancer including only signaling and regulatory pathways that can be targeted with therapeutic agents. The principle of fication is based on the activating signal that can be blocked by a class of drugs.

Indeed, the inventors reduce the enormous complexity of biological pathways and pathway cross-talk by devising a simplified map that only concentrates on the gens that are most indicative of drug target status defined as vention points”. These ention points consist of drug targets or group of drug targets and some genes upstream of the drug targets that er reflect a specific biological activity which is actionable through therapeutic interventions. By upstream is referred to genes encoding a protein having an extracellular activity. For ce, pan-HER therapies define the HER group of receptors and their ligands as a single intervention point.

The inventors propose a very simple approach for prioritizing intervention points for a specific patient. The basic premise is that, when the genes associated with an intervention point are more disturbed (in terms of sequence and/or expression level), the intervention point is more likely to be crucial or critical to the tumor. From this, it stems that the more disturbed the genes of an intervention point are, the more likely it is that therapeutics targeting that points will t the patient. Accordingly, the inventors have developped a family of simple scores that combine the level of gene expression in the tumor (relative to matched normal control), the ons found in the intervention points' genes, CNVs and miRNAs expression .

Therefore, the inventors propose a method allowing the tumor terization of one particular subject by considering its own tumor vs normal status in the most efficient way for identifying the bed or activated intervention points and ranking them. The inventors developed a new mathematical modelling and scoring system to give a score (e.g., of 1 to 10) based on integration of omics data, especially gene expression, sequencing, miRNA analysis and copy number variation ination.

Then, when the intervention points are ranked, it is possible to define one or several combinations of drugs targeting a combination of disturbed or activated intervention points so as to obtain the optimized therapy of cancer for this particular t. Preferably, the combined therapy comprises or consists of three drugs targeting the most disturbed or ted intervention points. The method may further comprise the administration of the zed combination of drugs to said patient. Accordingly, the method leads to rational combination therapies which are scientifically reliable and clinically feasible.

Tumour characterization The method comprises a step of characterizing the tumor in one patient of interest. In ular, the patient suffers from a cancer for which no effective therapy is established or admitted by physicians. The reasons of this situation could be an ed stage of cancer, for instance a stage with metastases, a relapsed cancer after one or several lines of treatment, or even a cancer for which no established and ent treatment is associated with. In particular, the cancers or tumors more ularly considered in the present invention are lung cancer, especially NSCLC (non-small cell lung cancer), breast cancer (in particular the triple negative breast cancer), colorectal cancers, kidney cancer, mas, brain cancers, liver cancers, head and neck cancers, stomach cancers and ovary cancers.

Therefore, the method comprises an l step of providing samples for the t. Two samples are necessary, namely one tumor sample and one normal sample from the same patient. Preferably, the tumour sample and the normal sample provides from the same type of tissue. More particularly, the tumor and normal samples are histologically d tissues. Typically, the samples can be provided by biopsies. Non-exhaustively, examples of pairs oftumor with corresponding histological normal reference tissue are the followings: 1. lung cancer adenocarcinomas or d metastases - bronchial normal mucosa 2. breast cancer tumors or derived metastases - normal epithelial breast cells colon s adenocarcinomas or derived metastases - normal colon mucosa EOP°>|FDP1PP° kidney cancers or derived metastases - normal kidney cells melanomas or derived metastases - synchronous naevi rhabdomyosarcomas or derived metastases - normal muscle tissue liver carcinomas or derived metastases - normal liver cells haryngeals tumors (ORL) - normal buccal mucosa Stomach carcinomas or derived metastases - normal stomach mucosa . Ovary cancer — normal Fallope tube mucosa 11. pancreatic cancers — normal parenchimatous tissue from pancreas In order to optimize the tumor characterization, the inventors selected parameters that have to be analysed in order to establish the status of the intervention points that can be targeted by a class of drugs.

The inventors defined the main intervention points of interest, namely HER (Human Epithelial Growth Factor Receptor), CDK4,6 (Cyclin-Dependent Kinase), PLK/AURK/Kinesins (Polo-Like kinase/ Aurora Kinase/Kinesins), Angiogenesis, Angiopoietins, Immune tors, P|3K (Phosphoinositide-3 Kinase), MET (cMET), MEK, ERK, Anti-Apoptosis, FGF (Fibroblast Growth Factor), mTOR (mammalian target of rapamycin), Ras/Raf, Telomerase, IGF/glycolysis (Insulin-like growth factor), Wnt, PARP (poly ADP ribose polymerase), HDAC (histone deacetylase), AT (Janus tyrosine Kinase- Signal Transducer and Activator of Transcription), Hedgehog, NOTCH, DNA Repair and Others’ intervention point (namely RET, ALK, R051 and U81). These ention points have been selected because they can be associated with an activation in a cancer. The rule that guides the choice of the invention in this selection is to select the activation signals that can be blocked.

Optionally, in an alternative method, a subgroup of intervention points can be ed among the above mentioned list of intervention points (i.e., a subgroup of 10, 12, 14, 16 or 18 intervention points). For instance, in a particular embodiment, a subgroup of intervention points of interest includes the intervention points for which drugs are available. For instance, such a subgroup may include or consist in the following group: Her, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Immune tors PD1L and CTL14, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, IGF/glycolysis, Wnt, PARP, and DNA .

In addition, for each intervention point, the ors carried out a ion of genes useful for characterizing this intervention point. The list of genes is sed in Table 1 or 9.

In order to define the status of these intervention points in the tumor, several parameters have to be defined based on the d list of genes that need to be investigated for each patient.

In a first , expression levels of the genes of Table 1 or 9 are determined in the tumor and normal samples. The sion levels are determined by measuring mRNA level. The determination of the expression level variation for these mRNA is carried out by comparing the expression levels in a tumor tissue and in the corresponding normal tissue. The gene expression analysis allows the study of independent deregulations or deregulations due to chromosomal aberrations. Indeed, the regulation of the transformational activity of genes is complex and involves many levels of regulation: trans/cis transcription factors, promoters, chromatin regulation, and the like. Generally, all lations (over-expression) are ered with a ratio tumour/normal of at least 1.3. For each deregulated gene (i.e., gene with a different mRNA expression when tumor and normal samples are compared), a fold change and/or intensity of signal (proportional to the mRNA expression level) is determined.

Technologies that can be used comprise Northern analysis, mRNA or cDNA microarrays, RT- PCT (in particular tative RT-PCR) and the like. Alternatively, the level of expression can be determined with a ship comprising a set of primers or probes specific for the list of genes of Table 1 or 9 or a set specific of genes of a subgroup of 10, 12, 14, 16 or 18 intervention points as sed in Table 1 or 9. Expression levels ed from cancer and normal samples may be normalized by using expression levels of proteins which are known to have stable expression such as RPLPO (acidic ribosomal phosphoprotein PO), TBP (TATA box binding protein), GAPDH (glyceraldehyde 3-phosphate dehydrogenase) or n.

It is important to note that the method according to the t invention is clearly distinct from a method of global or whole analysis of gene sion. Even if some genes can be added to the list of genes of Table 1 or 9, the gene expression is determined for less than 200, 250, or 300 genes.

In a second aspect, some genes of the list of genes of Table 1 and 9 are analyzed by sequencing (partial or whole sequencing) or by hybridization for detecting the presence or absence of mutations. For instance, exons of the genes of Table 1 or 9 can be sequenced by any method available, preferably by a method of high throughput cing such as |||umina or |on Torrent method or equivalent. Alternatively, only genes with known activating mutation(s) can be analyzed. Such list of genes and mutations can change depending on the considered cancer. In a particular ment, the genes of Table 10 can be analyzed for the presence of mutations. More preferably, the method includes the sequencing of p53, the most frequent d gene in solid tumors. For instance, the method may include the determination of the presence/absence of mutations in the genes p53, KRAS or NRAS rably KRAS), EGFR, EBBR2, P|K3CA and BRAF. Indeed, the presence of mutation leading to a onal gain or loss has an important effect on biology of the tumour without being always connected to variations of gene expression or of gene copy . Many mutations are known to have a direct effect on the activity of a treatment by inducing increased sensitivities or resistances. For example, the ons in the tyrosine kinase domain of EGFR are often associated with sensitivity to the small molecules inhibiting EGFR, the mutations in KRAS gene are associated with ance to the treatment by monoclonal antibodies targeting EGFR. The mutational status can be determined by any method known in the art, for ce by sequencing, microsequencing or hybridization. In on, the gene mutations are listed in in www.sangerac.ungeneticsZCGPZcosmicz.

In a third aspect, the copy number variation of genes are defined for the tumor sample of the subject. This is can be carried out by CGH (Comparative Genomic Hybridization) which makes it possible to e the tumor DNA with the normal DNA of the same individual to detect chromosomal aberrations, i.e. copy number variation such as chromosomal losses or gains. This technology is well-known by the man skilled in the art. As an illustration of this knowledge, the following reviews or reference books can be cited: Davies et al. (2005, Chromosome ch, 13, 237-248). This technology is useful to identify translocations. It can be easily carried out with frozen biopsies or tumor paraffin-included material. CGH results are expressed as the ratios of copy numbers in the tumor material and in normal tissue. A threshold of 0.5 is been acknowledged to describe a gain or a loss. More this ratio is high, more the amplitude of the anomaly is important. Thus, an important anomaly is likely to have a real impact at the biological level. In a preferred embodiment, a fold change ofthe copy number variation is determined.

In a fourth , levels of miRNAs or microRNAs for the genes of Table 1 or 9 are determined in the tumor and normal s. More preferably, the levels of 5 miRNAs for each gene is determined. In a preferred embodiment, the miRNAs of Table 11 are analyzed.

The method for measuring miRNA are well-known in the art.

Then, a fold change Tumor versus Normal tissue is determined for the 5 miRNAs and a mean fold change for each gene is calculated as the average of the fold changes ofthe 5 miRNAs.

Then, after the characterization step, the following parameters for the tumor of each specific patient have been determined: — A list of genes among the list of Table 1 or 9 with a deregulated expression with a d fold-change.

— A list of mutated genes.

— Optionally, a list of genes having a Copy Number ion and a value (fold- change) for this CNV. In a preferred embodiment, only the genes presenting an amplification are taken into consideration.

— Optionally, a list of lated miRNA, in particular with an averaged fold change based on the 5 miRNA fold-change.

In a first embodiment, the characterization method includes the gene expression analysis and the mutated genes. In a second embodiment, the characterization method includes the gene expression analysis, the mutated genes and the Copy Number Variation. In a third embodiment, the characterization method includes the gene expression analysis, the d genes and the miRNA analysis. In a fourth embodiment, the characterization method includes the gene expression analysis, the mutated genes, the Copy Number Variation and the miRNA analysis. The choice of the combination of criteria can be different for each intervention point.

For instance, for some intervention points, the impact of miRNA has a major influence whereas for other intervention points, miRNA has a minor influence. As shown in the example section, for patients having NSCLC, miRNAs have a major impact on the intervention points mTOR-AKT-PTEN, RAS, ERK, P|3K and Immune Modulators, whereas the impact is minor for the intervention points Her, CDK4,6, Angiogenesis, MET, MEK, FGFR, RAF, IGF-Warburg, and PARP. In on, for ts having NSCLC, the impact of CNV has been determined as quite low.

From these ters, the method comprises that determination of the disturbed or activated intervention points in the tumor of the patient and the ranking of them by calculating a score for each intervention point.

Mathematical modeling/algorithm The principles of the algorithm for calculating a score for each intervention point are the followings: 1- The score is designed to ate with the likelihood that an intervention point is (abnormally) activated or disturbed in the tumor, in particular in comparison to the normal matched tissue of the same patient. It ranges from 1 to 20, the t is the score, the most activated or disturbed is the pathway. In a preferred ment, the score ranges from 1 to 10. However, the scale of the score has no impact on the results. 2- The score may combine evidence from 4 data sources: — Mutations; — Mean fold change in gene ently expressed in the tumor vs. normal; — Optionally, Mean fold change in expression of miRNA oftumor vs. normal; and, — Optionally, Copy number variation.

Activating mutation and the score calculation The different data sources may carry different weights in the score. Indeed, activating mutation (e.g. K-RAS in the RAS pathway) may have decisive weight.

Then, in a first approach of the method, the maximal score is given to each intervention point comprising a gene with an activating on. In a red embodiment, the mutations associated with a l score are listed in Table 10. It may further include the p53 mutations. For instance, if the score ranges from 0 to 10, the maximal score of 10 is given to every intervention point comprising a gene with an activating mutation. In the absence of a mutation, the score is based on an average of the mRNA mean fold changes, optionally weighted with the level of expression of miRNAs and to a lesser extent CNV abnormalities.

In a second ch, the rules of the first approach are carried out, but the score is the sum of two scores, a first one based on mutation and a second one based on the arithmetic mean of the mRNA mean fold changes. Preferably, the range/scale of the two scores is the same.

For instance, the two scores each range from 0 to 10.

In a third approach, the score is the sum of two scores, a first one based on mutation and a second one based on the mRNA mean fold change. However, a different weight/score can be given to mutations. In particular, instead of giving a score of 10 as soon as an activating mutation is ed, a lower score can be given to the activating mutation, for instance a score of 3. Accordingly, one mutation in a gene of an intervention point gives a score of 3, two mutations a score of 6, three mutations a score of 9, more mutations the maximal score of 10. In addition, ing on the impact of the activating mutations, a different weight can be given. For instance, an activating mutation of KRAS gives a score of 10, whereas a mutation with less functional impact will count for 3. Accordingly, mutations listed in Table may have a higher weight, for instance may count 10. ating the mean fold-change of differentially expressed genes: The global expression pattern is used to ate a fold-change W of the expression of a gene i in the tumor and in the matched normal tissue. This fold change can be referred as mRNA TvN fold . It is calculated as the ratio of the sion of a gene in tumor on the expression ofthe gene in a normal tissue.

For calculating the mean/average fold change of intervention point k, denoted as Ek, the fold changes of differentially expressed genes with a fold change of at least 1.3 are used. In other words, for each intervention point, an e fold-change of the genes iof the intervention point k is calculated, trimming values with a threshold of 51.3.

Formally, we calculate Ek as the ing: let Mk denote the set of genes that belong to intervention point k, and mk denote the subset of Mk that includes only differential expressed genes with an absolute fold change 31.3. Ek is the average of the fold change of the genes mk. 711,, = {aili E Mk and ngl 3:: 1.3} We then calculate the mean expression level for all the genes in mk: 13,, = 3; wherein a? Emk In other words, the fold change for a particular intervention point is the average or etic mean of the fold changes of genes belonging to the intervention point as defined in Table 1 or 9 and having a fold change T vs N of 1.3 or more.

In particular, in order to compare the fold changes of different intervention points, a relative scoring, e.g., from 1 to 10, is generated based on the percentile calculation.

Combining mRNA and miRNA ements To adjust for possible miRNA intervention in translation, the inventors propose to penalize discordance between miRNA and its target mRNA. For each of the genes of Table 1 or 9 that belong to the intervention points or a set thereof, the inventors determined the miRNAs most likely to be involved in their regulation using Target scan {http://www.targetscan.org/}, ing the top 5 miRNAs for each gene. Table 11 provides a list of the top 5 miRNAs for the genes of Table 1 or 9.

For each gene i, a mean miRNA fold-change can be calculated, which is denoted A,-, by averaging the fold changes of the 5 miRNAs (or less if less than 5 miRNAs are identified) that are most likely to target gene i. Then, for each gene, a mean miRNA TvN fold change is determined.

Then, a corrected fold change of a gene of an intervention point is calculated by dividing the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold change) by the mean fold change for the miRNAs of the gene (mean miRNA TvN fold change). The ted fold change of a gene is then used to calculate the fold change for a particular pathway by using it in the calculation of the e fold changes of the genes ing to the pathway as d in Table 1 or 9 and having a fold change T vs N of 1.3 or more. Based on the corrected fold change of pathways, a corrected score, e.g., a score 1 to 10 is generated based on percentiles.

Combining mRNA and CNV measurements Only genes with amplification are taken into account. Preferably, genes with 2-fold or higher amplification are ered as amplified. Then, a corrected fold change of a gene of an intervention point is calculated by multiplying the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold change) by the CNV fold change of the gene. The corrected fold change of a gene is then used to calculate the fold change for a particular intervention point by using it in the calculation of the average fold changes of the genes belonging to the intervention point as defined in Table 1 or 9 and having a fold change T vs N of 1.3 or more.

Based on the corrected fold change of pathways, a corrected score, e.g., a score 1 to 10 is generated based on percentiles.

Score calculation To compare intervention , a score is given to each ention point, taking into account mRNA expression and activating mutation. Optionally, 3 or 4 variables can be considered: activating mutations, the Fold change of mRNAs in Tumor vs. Normal, the fold change of miRNAs in Tumor vs. Normal and the copy number variation (amplifications, deletions). In a preferred embodiment, the score is given to each intervention point, taking into account ting mutations, mRNA expression, and miRNA sion. In a ular ment, the miRNA is considered when calculating the score at least for the following intervention points: mTOR-AKT-PTEN, RAS, ERK, P|3K and Immune Modulators.

To summarize, in a first aspect, the score for each pathway is calculated as follow: 1- If an ting mutation is detected in one gene of the intervention point, then the score of the intervention point is the maximal score, e.g. 10 when scoring from 1 to 10.

Otherwise, the score is calculated based on the average of the fold changes tumor vs normal of the genes having an absolute fold change of at least 1.3 and belonging to the list of genes of Table 1 or 9 for the considered intervention point.

Optionally, if the miRNA level of the genes of Table 1 or 9 is measured, in particular those of Table 11, a mean miRNA fold change for each gene is calculated as the arithmetic mean of the fold change of 5 miRNAs of this gene.

Then a corrected mRNA fold change for the gene is calculated by dividing the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold change) by the mean fold change for the miRNAs of the gene (mean miRNA TvN fold change).

For calculating the mean of the mRNA tumor vs normal fold changes of the genes of an intervention point, the corrected mRNA TvN fold change for the gene is used.

Optionally, if the CNV of the genes of Table 1 or 9 (or some genes thereof) is measured with 2-fold or higher amplification, then a corrected mRNA fold change for the gene is calculated by multiplying the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold ) by the CNV fold change for the gene.

For calculating the mean of the mRNA tumor vs normal fold changes of the genes of an intervention point, the corrected mRNA TvN fold change for the gene is used. atively, it can also be chosen to attribute less weight to mutations, in particular when considering the sequencing of all genes of Table 1 or 9. Accordingly, in a first alternative, the score is the sum of the score due to mutational status and the score due to the mRNA differential TvN expression. In a second alternative, in order to graduate the impact of the mutations, a score of 3 is given by activating mutation. Then, for instance, the score of a pathway is a score based on activating mutations with a maximal score of 10 added to a score based on mRNA expression is calculated above with a l score of 10.

Accordingly, for each ention point, the score will be comprised between 0 and 20.

Based on the scores of the intervention points, the intervention points are ranked. The pathway ranking can allow the one skilled in the art to select one or several combinations of three activated or bed ention points, especially the combination of the three most activated or disturbed intervention points according to the scores.

The pathways have been selected because drugs ic to each ention point are already or soon available for treating a patient (see Table 1). Accordingly, based on the combination of selected intervention points, a combination of drugs targeting these intervention points can be selected and proposed for treating the t.

Therefore, the present invention relates to a method for selecting a combination of three drugs useful for treating a patient having a cancer, wherein a group of three activated or disturbed ention points are selected by the method of the present invention and a drug is selected for each activated or disturbed intervention point, y providing a combination of three drugs.

Prior any administration to a patient, the efficacy of the drugs combination can be tested ex vivo. For instance, the combination can be tested on a model based on a biopsy of the tumor from the patient. It can be tested on an animal model on which tumor cells from the tumor has been grafted. Alternatively, it can be tested in a pre-clinical model called Metastatic Ex Vivo Assay (MEVA). It is an in vitro 3D tissue culture through an anchorage independent system.

Then, the present invention relates to a method of treatment of a patient having a cancer or a method for selecting a combination of drugs for treating a patient having a cancer, comprising: — ing a tumor sample and an histologically matched normal tissue from the patient; — Characterizing the tumor sample in comparison to the normal sample as detailed above; — Calculating a score for each ention point as detailed above; — Selecting three activated or disturbed intervention , preferably the three most activated or disturbed intervention points; — Selecting a combination of drugs targeting the three selected activated or disturbed intervention points; — Optionally, administrating to the patient the selected combination of drugs. ally, the method of the present invention can provide several combinations of three drugs. Indeed, in order to prevent any drug resistance, the combinations can be used sequentially.

In addition, the present invention relates to a kit and the use of such a kit for classifying intervention points according to their status and for selecting a combination of three drugs chosen as targeting the most activated or bed ention points, wherein the kit comprises means for measuring the mRNA expression level of the genes of Table 1 or 9. In particular, such means can be primers and/or probes ic for each gene of Table 1 or 9.

Optionally, the kit may r comprise means for detecting the mutations in genes of Table 1 or 9. These means could be suitable for the whole sequencing of the genes of Table 1 or 9.

More preferably, the kit comprises means for detecting the mutations of Table 10. Means can be probes specific of the nucleic acid sequence encoding a fragment including the mutation. They can also be primers allowing the amplification and sequencing ofthe genes.

Optionally, the kit may further comprise means for determining the level of miRNA of genes of Table 1 or 9, in particular those of Table 11. Finally, the kit may further comprise means for ining the copy number variation ofthe genes of Table 1 or 9.

Finally, the present ion relates to drugs combinations of interest identified by the method of the present invention. In a particular embodiment, the present invention relates to a drugs combination including one drug targeting PDL1 or CTLA4 and two drugs selected from the group consisting of an inhibitor of RAF, an inhibitor of Angiogenesis, an inhibitor of MEK; an tor of MET and an inhibitor of CDK 4,6.

The main reason to define triple nt therapies as a combination of an immunomodulator (anti PD1L or anti CTLA4) and two ed ies is to contain toxicity of associations. Indeed, the main problem of combining targeted therapies might be the additive toxicity. Whilst containing toxicity of dual combination was already demonstrated, adding a third drug such as anti PD1L may contribute to an effective tolerated therapy, in particular for metastatic NSCLC.

Accordingly, the present invention relates to a drugs combination for use in the treatment of cancer, wherein the drugs combination is selected amoung the combinations disclosed in Table 6, Table 7, Table 8.

Preferably, the drugs ation is the combination of three drugs. Optionally, it may include additional drugs.

In a more specific ment, the present invention relates to a drugs combination including a drug targeting PDL1, an inhibitor of RAF and a third targeted drug such as an inhibitor of MEK6, an inhibitor of MET, an inhibitor of CDK4,6 or an inhibitor of angiogenesis.

Based on analysis of frequency of occurrence of activated entional points, and based on is of trends of co-activation, the most important combinations are the following: 1. anti PD1L (e.g., AZ) + Pan RAF inhibitor (e.g., Takeda)* + MtorP|3K tor (e.g., Pfizer) 2. anti PD1L (e.g., AZ) + Pan RAF inhibitor (e.g., Takeda)* + angio- inhibitor (e.g., Pfizer) 3. anti PD1L (e.g., AZ) + Pan RAF inhibitor (e.g., Takeda)* + met inhibitor (e.g., Pfizer) 4. anti PD1L (e.g., AZ) + Pan RAF inhibitor (e.g., Takeda)* + CDK4,6 inhibitor (e.g., Pfizer) these for combinations covers 51 % of patients with NSCLC as determined in the analysis of the retrospective collection of 123 patients.

In on to these 4 combinations, the inventors determined that ing PD1L with CTL14 fulfils the criteria of combining an immunomodulator with two others targeted drugs.

Four additional combinations can be oned, increasing the coverage of patients to 72% . anti CTLA4 (e.g., AZ) + Pan RAF tor (e.g., Takeda)* + MtorP|3K inhibitor (e.g., Pfizer) 6. anti CTLA4 (e.g., AZ) + Pan RAF inhibitor (e.g., Takeda)* + angio- inhibitor (e.g., Pfizer) 7. anti CTLA4 (e.g., AZ) + Pan RAF tor (e.g., Takeda)* + met inhibitor (e.g., Pfizer) 8. anti CTLA4 (e.g., AZ) + Pan RAF tor (e.g., Takeda)* + CDK4,6 inhibitor (e.g., It is worthwile to mention that the Pan RAF inhibitor could be replaced with a MEK inhibitor in most ofthe patients. This replacement generates 8 combinations: 9. anti PD1L (e.g., AZ) + MEK inhibitor + MtorP|3K dual inhibitor (e.g., Pfizer) 10. anti PD1L (e.g., AZ) + MEK inhibitor + angio-inhibitor (e.g., Pfizer or Takeda) 11. anti PD1L (e.g., AZ) + MEK inhibitor + met inhibitor (e.g., Pfizer) 12. anti PD1L (e.g., AZ) + MEK inhibitor + CDK,-6 inhibitor (e.g., Pfizer) 13. anti CTLA4 (e.g., AZ) + MEK inhibitor + MtorP|3K dual inhibitor (e.g., Pfizer) 14. anti CTLA4 (e.g., AZ) + MEK inhibitor + metinhibitor (e.g., Pfizer) . anti CTLA4 (e.g., AZ) + MEK inhibitor + angio_inhibitor (e.g., Pfizer or Takeda) 16. anti CTLA4 (e.g., AZ) + MEK inhibitor + CDK4,6 inhibitor (e.g., Pfizer) In a preferred embodiment, the above-mentioned drugs can be selected among those disclosed in Table 1.

More preferably, the drugs combination is selected in the group consisting of Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + PF-384 r) Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + Axitinib (Pfizer) or nib (Takeda) Medi-4736 (Astra Zeneca) + MLN2480 (Takeda) + Crizotinib (Pfizer) Medi-4736 (Astra Zeneca) + 0 (Takeda) + iclib (Pfizer) Tremelimumab (Astra Zeneca) + MLN2480 a) + PF-384 (Pfizer) Tremelimumab (Astra Zeneca) + 0 (Takeda) + Axitinib (Pfizer) or Motesanib (Takeda) Tremelimumab (Astra Zeneca) + MLN2480 a) + Crizotinib (Pfizer) Tremelimumab (Astra Zeneca) + MLN2480 (Takeda) + Palbociclib (Pfizer) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + PF-384 (Pfizer) Medi-4736 (Astra Zeneca) + tinib (Astra Zeneca) + Axitinib (Pfizer) or Motesanib (Takeda) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + inib (Pfizer) Medi-4736 (Astra Zeneca) + Selumetinib (Astra Zeneca) + iclib (Pfizer) Tremelimumab (Astra Zeneca) + tinib (Astra Zeneca) + PF-384 (Pfizer) Tremelimumab (Astra Zeneca) + Selumetinib (Astra Zeneca) + Crizotinib (Pfizer) Tremelimumab (Astra Zeneca) + Selumetinib (Astra Zeneca) + Axitinib (Pfizer) or Motesanib (Takeda), and Tremelimumab (Astra Zeneca) + Selumetinib v + iclib (Pfizer).

By a ”drugs ation”, it is ed to a pharmaceutical composition comprising the drugs of the combination or to a kit or product comprising the drugs of the combination as a combined preparation for simultaneous, separate or sequential use.

The present invention relates to — a pharmaceutical composition comprising the drugs of the ation, and a pharmaceutically acceptable carrier, in particular for use in the treatment of cancer; and/or — a product or kit containing the drugs of the combination, as a combined ation for aneous, separate or sequential use, in particular in the treatment of cancer; and/or — a combined preparation which ses the drugs of the combination, for simultaneous, separate or sequential use, in ular in the treatment of cancer; and/or — a pharmaceutical composition comprising the drugs of the combination for the use in the treatment of cancer in combination with radiotherapy and/or or an additional anti-tumoral agent; and/or — the use of a pharmaceutical ition comprising the drugs of the combination for the manufacture of a medicament for the treatment of cancer; and/or — the use of a pharmaceutical composition comprising the drugs of the combination for the manufacture of a medicament for the treatment of cancer in combination with herapy, and/or or an additional anti-tumoral agent; and/or — a method for treating a cancer in a t in need thereof, comprising administering an effective amount of a pharmaceutical composition comprising the drugs of the combination, and a pharmaceutically acceptable carrier; and/or — a method for treating a cancer in a subject in need f, comprising administering an effective amount ofthe drugs of the combination; and/or — a method for treating a cancer in a subject in need thereof, comprising administering an effective amount of a pharmaceutical ition sing the drugs of the combination in combination with radiotherapy.

In a preferred embodiment, the cancer is a lung cancer, and more preferably a NSCLC.

The following r, describes material, methods and results presenting full investigation of possibilities of combinations, based on magnitude and frequency of occurrence of interventional points of activation as determined by the scoring system. In addition, selection of combinations takes into account the trends of co-activation EXAMPLES Methods Patients and Tissue Samples The present study was organized by the CHEMORES initiative (Chemotherapy resistance consortium), which is an EU funded (FP6) Integrated Project involving 19 academic s, organizations for cancer research, and research-oriented biotechnology companies in 8 European countries.

Tissue samples from a cohort of 123 patients who underwent complete surgical ion at the Institut Mutualiste Montsouris (Paris, France) between 30 January 2002 and 26 June 2006 were analysed. Clinical characteristics are given in Table 4 below. The median age of patients was 63 years (range 41-85), 34 (28%) were female and 89 (72 %) were male. The histopathology of all tumors was reviewed by the same ogist (Jde): 50 patients had SCC, 57 AC, 13 LCC and 3 unclassified. Using the new 7th edition TNM staging 56 were stage I, 25 stage II, 28 stage III and 4 stage IV. Adjuvant platinum based chemotherapy was stered to 61 patients. Fifty-nine patients experienced a e. Two-year relapse-free survival was 64%, and the median time to recurrence for the cohort was 5.2 years. After a median follow up of 40 months (range 0-92) 36 patients had died and 23 patients were alive with ence.

This study was performed using rozen tumor and nt normal lung tissue. Samples were handled according to the Tumor Analysis Best Practices Working Group (Nat Rev Genet 2004; 52229-237). Haematoxylin and eosin d frozen sections, taken before and after the cutting of slides for analysis, revealed a median cell content of 85% (an inter-quartile range of 65% to 95%). All tissues were banked after written informed patient consent, and the study was approved by the Ethics Committee of Institut Gustave Roussy (IGR). Genomic investigations were performed at IGR, leader of the Genomic work-package of es consortium, in the genomic center core facility certified |SO9001, labelled European reference and training center for Agilent technologies. Analyses were performed at IGR and Karolinska Institute, the leader of integrated analyzes work-package.

Table 2 - Characteristics of the patients in the study population n=123 (100%) Age median (range) 63 84.6) Males n (%) 89 (72%) Smoking Current 64 (52%) Former 51 (42%) Never 7 (6%) Histology AC 57 (46%) scc 50 (41%) LCC 13 (11%) Other 3 (3%) Stage 1 56 (50%) 2 25 (22%) 3 28 (25%) 4 4 (4%) Adjuvant Chemo (%) 61 (50%) Data availability The microarray data related to this study have been submitted to the Array Express data repository at the European Bioinformatics Institute (http://www.ebi.ac.uk/arrayexpress/) under the accession numbers E-MTAB-1132 (GE), E-MTAB-1133 (CGH) and E-MTAB-1134 (MIR).

Oligonucleotide aCGH DNA samples were extracted from tissues using Qiagen QlAamp DNA Mini kit n, Hilden, Germany). In each case, the normal tissue sample was used as the reference to its corresponding tumor sample. DNA was restriction digested and controlled by Agilent Bioanalyzer on DNA 7500 chips (Agilent Technologies, Santa Clara, CA, USA). The fragmented nce and test DNA were labelled with Cy3-dUTP or TP, respectively, using Agilent Genomic DNA Labelling Kit PLUS. Samples were purified using Microcon YM-30 filters (Millipore, Billerica, MA). ization was carried out on t 244K arrays for 24 hours at 65°C in a rotating oven (Robbins Scientific, Mountain View, CA) at 20rpm, followed by appropriate g steps. Scanning was performed with an Agilent 62505C DNA Microarray scanner using default parameters. Quantification of Cy5 and Cy3 signals from scans was performed with Feature Extraction v10.5.1.1 (Agilent Technologies) using default parameters.

CGH data processing and analysis Resulting raw signals and log2 (ratio) profiles were normalized and centered according to their dye composition (Cy5/Cy3) and local GC content. These profiles were segmented with the Circular Binary Segmentation algorithm (Olshen et al. Biostatistics 2004 Oct;5(4):557-72) through its implementation in the DNAcopy package for R v2.8.1 using default parameters.

DNA copy number imbalances were detected considering a minimum of 3 consecutive probes and a minimal te amplitude threshold that was specific for each profile, ingly with its internal noise. This specific internal noise was computed as one-fourth of the median of the absolute log2 (ratio) distances across utive probes on the genome.

Of the 128 aCGH izations performed, 17 were discarded: 7 due to their clinical annotations, 2 due to anomalies in their normal reference, and 8 due to the bad quality of their profile, resulting in 111 usable profiles. All aCGH nates in this study are mapped against the human genome as defined by the UCSC build hg18.

To assess the discovery of the genomic regions with differential ies between the AC, LCC and SCC tions, ANOVA tests were med on the segmented aCGH dataset. To account for multiple g, p-values were transformed to false ery rate (FDR) (Benjamini et al. J Royal Statist Soc B 1995; 57:289-300).

Gene expression and microRNA microarray assay The lysis of 40 to 50 frozen sections of 10 micron-thickness, cut from each NSCLC tissue sample was done using a Polytron homogenizer (Ultraturrax, IMLAB, Lille, France). The RNA extraction was performed with TR|zo|® Reagent protocol (Invitrogen, Carlsbad, CA, USA).

Total RNA was fied and qualified with Nanodrop ND-1000 spectrometer and Bioanalyzer-2100 (Agilent Technologies).

For dual color Cy3 (normal s) and Cy5 (tumor samples) labelling, Agilent Fluorescent Low Input Linear Amplification kit adapted for small amounts of total RNA (500 ng total RNA per reaction) was used, followed by purification of labelled probes by Qiagen RNeasy Mini kit and by a protocol provided by Agilent. Gene expression profiling was performed with dye- swap, using dual-color 244K Human exon array from Agilent (custom design with the content of the 44K Human genome plus 195000 probes, one for each exon as defined in refGene list of UCSC build hg18 (http://genome.ucsc.edu/)). Hybridization was carried out for 17 hours at 65°C at 10 rpm, followed by washing steps. d microarray images were analyzed by using Feature Extraction software version 10.5.1.1 (Agilent).

For the NA analysis, normal and tumor samples were hybridized on separate arrays.

Agilent miRNA Microarray System with miRNA complete labelling and hybridization kit was used for Cy3 labelling. Briefly, isolated total RNAs were phorylated, labelled with pCp- Cy3 and hybridized to Agilent 8x15K arrays for 20h at 55°C in a rotating oven (Robbins Scientific) at 20 rpm. Slides were washed and scanned for gene expression using an Agilent G2565C DNA microarray scanner using defaults parameters.

Gene mutations analysis Sequencing was performed at IGR and at the Royal Institute of Technology (Stockholm, Sweden). DNA was extracted with QIAamp DNA Mini Kit (Qiagen, Hilden, Germany). After PCR amplification of target exons, sequencing reactions were carried out using the BigDye® Terminator Cycle Sequencing Kit (Applied Biosystems, Forster City, CA). The primer sequences are available on t. Sequencing reactions were run on a 48—capillary 3730 DNA Analyzer®. Sequence is and alignment was med with Sechape® software (Applied Biosystems). All detected mutations were confirmed in at least one independent PCR reaction. In all 123 samples, full coding sequences of exons including oncogenic mutational hotspots were analyzed corresponding to: TP53 (NM_000546.4) exons 5-8; KRAS (NM_004448.2) exons 2 and 3; EGFR (NM_005228.3) exons 18—21; P|K3CA (NM_006218.2) exons 10 and 21,- BRAF (NM_004333.4) exon 15,- ERBBZ (NM_004448.2) exons 18, 20-24; KDR 2253.1) exons 2, 26, 27 and 30,- and AKT1(NM_005163.2)exon 4. xpression data processing and normalisation All processing s used for gene sion analysis were performed on the median signal from Agilent Feature Extraction raw data files using functions and packages collected in the R Bioconductor project (Gentleman et al. Genome y, 5: R80) as well as custom written routines.

For gene expression data, dye-swap arrays were first combined (by taking the average of intensities) to obtained only one array per condition. This combination has the result of 2015/063263 ing the M values (log2ratios) on zero. Then, flagged spots as well as control spot were d. ization was then performed using the izeWithinArrays function from R package LIMMA (Smyth GK tical Applications in cs and Molecular Biology 2004, vol3: N°1, article3).

For miRNA data, control spots were systematically removed, and flagged spots (gIsFeatNonUnifOL and gIsSaturated columns from raw files) were considered as missing values (”NA”). Array normalization was performed using the least-variant-set method (Suo et al. RNA 2010 Dec,’ 16(12): 03).

Differential expression analyses of miRNA sion To assess differentially-expressed miRNA, the inventors first estimated the fold changes and standard errors between two groups of samples by fitting a linear model for each probe with the lmFit function of LIMMA package in R. Then they applied an empirical Bayes smoothing to the standard errors from the linear model previously computed with eBayes function.

Scoring/ ranking of activated interventional points The algorithm The mathematical ing and scoring system aims to give a score (1 to 10) based on integration of omics data, cing, gene expression, miRNA and copy number variations determined as differences between tumor and normal, individually for each patients.

SPRING scoring enables identification and ranking of activated pathways, and the overall concept is that such activated pathways should be blocked with combined targeted therapies.

The first mathematical model was established on the basis of a retrospective dataset from 123 patients with NSCLC for whom sequencing, Copy Number Variation, and tumor vs. normal gene expression were available. Using these data, an algorithm that provides a score of activation for each of the simplified pathway for the patient and factors in all of the above-mentioned structural and functional results has been established. The principle of the algorithm is disclosed in Figure 2.

Scoring is based on an intuitive algorithm that ates 4 types of genomic igations of Tumor and Normal biopsies 1. ons: in V.1 the inventors used a very limited set of sequencing data, including only the genes/mutations used currently in clinical care of NSCLC: EGFr, kRAS, BRAF, PI3KCA, and HER2. Additionally they sequenced p53, the most frequent mutated gene in lung (and all solid tumors). a. When a mutation is detected, the algorithm assign the maximal score 10 in the corresponding fied pathway. 2. Gene Expression: For each simplified pathway, mRNA steady state level in Tumor vs.

Normal is used to calculate a mean fold change of the pathway. a. Values of individual Fold Change are trimmed at the threshold 1.3. b. Values of individual mean fold s for each simplified y are ranked in the retrospective set of data of 123 NSCLC, used as a calibrator. c. As shown in 3 examples below, the range of Fold s is different from one to other pathway. In order to compare them, the inventors ted a relative scoring from 1 to 10 based on the percentile calculation. 3. miRNA expression: For each gene, the inventors selected top 5 matched miRNA from TargetScan data base. a. The fold changes T vs. N steady state level for each miRNA was used to generate a mean fold change. b. Fold change T vs. N for each gene was divided by the mean Fc T/N of the 5 corresponding miRNAs. c. They generated then a corrected mean Fold change for each simplified pathway. d. They generated a corrected score 1 to 10 based on percentiles. 4. Copy Number Variation. When amplification is detected, the inventors multiplied the value of the mRNA expression fold change for each gene by the value of the fold change amplification. Then they generate the corrected mean fold change of pathways and the percentiles score.

Table 3 summarises scores obtained for all patients of the 123 NSCLC, for a selection of interventional points P|3 ME ER FG mTO PAR JAK_STA CTLA patient Histo Hre K | K X X ‘l'l 70 03? ‘1? PDL1 P T AGG60071 6 AC 1 3 5 [\J J> (0 O1 01 CD co oo ANO42052 0 AC 5 6 7 \l _\ O N (.0 [\3 \l 4> 01 10 ARC27051 7 SCC 9 4 1 _\ _\ (.0 8 2 3 \l N O) 3N moo AZE45021 3 AC 8 10 9 J> \l \I 2 3 2 co co 10 BAR33112 3 SCC 8 7 10 _\ 0 CD .h (0 O) O) co \l 10 BAS26051 2 AC 10 1 3 _\ (.0 O1 _\ J> J> 01 c» BAS26072 4 AC 5 10 8 (.0 CO CD N _\ CD 01 4> 10 BEM29112 9 SCC 5 1 1 CD O1 J> CD [\J 01 4> —\ BEN48070 7 SCC 1 1 2 .h 01 0) N (.0 CO c» [\3 10 BEN41052 9 LCC 7 3 9 01 O1 \l CD [\J _\ O _\ O 01 BER52043 0 AC 7 2 4 B|E410219 SCC 10 9 7 \IN O'l(.0 \l(.0 (OCT) \IN _\0‘l J>(.0 (ON BOU48091 0 AC 9 3 6 N 01 O) \I 01 CD J> (.0 BOU29112 9 SCC 2 9 1 _\ O CO (.0 01 \I _\ _\ _\ O BOU52011 1 AC 6 5 5 01 CD N G) \l _\ CD 01 10 BRO52112 7 AC 4 8 8 [\J \I (0 _\ [\J [\J 01 CD 10 10 BRZ47032 6 AC 10 9 9 oo _\ O _\ o CD _\ O N —\ 00 10 CAM52010 1 oo _\ o “3 \l .h N _\ _\ 10 CAP46021 LCC 1 4 1 (.0 _\ 0 [\J [\J 01 (.0 _\ O CO 4 AC 8 5 2 —\00 co .h _\ (.0 J> O1 (.0 8 LCC 8 5 5 CD [\J [\J _\ (.0 [\3 O1 CHA47071 8 LCC 4 6 10 co co \l CD _\ O (.0 \I [\3 CHE51122 AC 6 9 1 [\J 0) CD 3 9 3 CO _\ O COU42020 1 AC 2 10 1 _\ O .h 01 _\ O _\ O CRE42042 3 SCC 6 10 10 CD O) CD 10 10 9 DAM20041 SCC 2 10 9 \I N _\ O 3 6 10 (001 J>J> 10 UL) UL) DAV32040 7 SCC 1 5 10 N N co _\ [\3 N CD DEL33082 1 AC 7 8 7 5‘ 5‘ co HIEIIEHflflflflfllfliflflflflfllflfl-Hflflflfl (.0CDGD(.00 (04> _\ O N J> 10 10 DEP35112 1 SCC 5 9 6 oo c» c» _\ O [\3 DES58041 8 AC 10 6 3 \I co \1 0) _\ 0 10 06 AC 5 4 6 4> N co (.00) (7201 CD N DHE32121 4 CD _\ O J> O1 _\ O CD DOM5907 29 SCC 3 10 3 co N .h ODCO O1 ODCO J> _\ O 10 DUV33071 3 SCC 6 5 10 J> J> 0) N CO [\J O) _\ O 10 ECU52071 3 AC 3 10 8 A G) [\3 co _\ O 00 oo co ED030081 2 SCC 7 5 2 (O G) N co co N 01 co ELA54080 9 LCC 4 8 4 A A (.0 _\ 5 01 co _\ O 4> ELB33072 8 AC 10 3 6 N N O1 [\3 —\ N c» 5‘ FER47103 1 AC 4 2 8 [\3 J> (.0 co co 4> c» \n FER46123 0 SCC 3 5 7 6 5 7 6 6 5 6 7 10 _\50-: (.04 FLA49071 1 AC 5 5 8 1 2 2 5 8 1 _\ _\ O 1 AC 7 6 9 CD _\ O 01 J> J> _\ oo —\ FOR41072 7 SCC 6 7 4 _\ 0 (.0 _\ O (.0 N CD 4> c» FRO44080 6 AC 2 2 3 01 CD (0 _\ (.0 CD 00 N GAN35081 1 SCC 10 8 4 _\ CO CD CD CD _\ N 00 GAR41081 3 SCC 6 7 6 C00 c» _\ (Tl J> J> —\ 5‘ GAR45081 9 SCC 10 7 3 0) J> J> [\J J> 4> 5‘ 6 AC 10 7 8 _\ O (.0 (0 oo _\ o 4> 4> GEO27011 4 SCC 3 6 2 O1 _\ O O1 J> _\ _\5mm) c» N G|D49022 4 AC 7 7 10 (.0 G) A O _\”o G|L230901 SCC 3 1 2 CO(.0 NCD coco (7201 G|R22060 6 AC 9 1 3 N J> .h .h 00 co N GOE19120 AC 10 4 7 O) —\ J> [\J N co co GOM4502 27 SCC 9 4 6 _\ _\ O J> CD co co GR025010 8 AC 10 7 10 8 4 8 10 6 —EIII___—n2 —m-2 —n-—————n2 CDJ>NCO HAM64072 9 SCC 3 2 10 5 1 10 10 9 1 9 -fl 6 —-I5I____1 s N—\ HOU50110 6 AC CD _\ O 6 —--_7 NO‘ILO 0301 -l> _\\|_\¢o 4 —m-e JAY440311 AC a m —n10 —--m 9 KON381027 AC nu— 2 928 AC 4 LAM380228 \IcncoOo-nwoocoogco—x ooco©4>oo©0 —\—\LOO'ICOJ>—\CD AC “-—llcoco—\NNNOJAODCOO‘INN s J>CO—\COO'ICDO'IJ>—\CD —-E_ 8 —-M_ 1o _\_\ OO —fl-_ m 5 —-M_ _\Oco—xo 2 —\—\<.o —m- 2 "I!“ _\ 1 10 1 —fl-_0 2 LER460716 scc O1 co N—\ (no: cow coo-1 —n e oomco—xcogco—x MAC46010 1 AC 7 _\ O) _\ —x 01 00 N [\3 4> 6 MAC38122 0 (DOO 4 4 4 [\J \n —‘ O oo 0-1 \l 0-1 6 MAR24091 1 (DOO 5 2 01 N —x c» \I —‘ O 0-: 01 6 MAR491 12 6 (DOO 7 J> (.0 4> N —‘ O co oo \l 6 MAR43072 6 AC co 0-1 c» 01 co N 6 MAR35050 7 (DOO 7 a: 5 10 co \l co —\ mm 6 MAR47032 2 LCC 3 5 7 2 -fl 4>o~1 0100 \IN \IO'I 6 _\0“ 0-101 4 GDCO MER49031 8 AC In co 5‘ 6 NEG410311 AC 10 2 O) s NI N270409 AC _\ 0 7 (.0 —m-2 PAN390607 AC (O (.0 .n—xwa‘oooo As—xcoa‘oo COCOO'INN J>—\-l>-l>l\)<.o wN!-l>\l(040)“) 1 PAQ470203 '_OO 1 01 \I 1 PEC481 1 13 AC 10 2 5 CD O1 N 2 J> Other PER401217 C - N —\ N —\ \I (0 —x .h -- 8 (.0 PER510713 AC [\J \l J> CD O) _\ J> O1 \l 8 2 6 7 906 SCC 5 1 9 1 1 7 7 2 6 4 2 4 1 5 2 —EE5 10"M2 2 RAM53032 1; all-- 7---83 —-nm———-m3 5 —-u—————m6 10 —mm10 10 —-l%l_____“5 3 6AI360426 Ac -fl_____“ 6 3 1 1 7 2 6113171101 Ac m—————— 6 7 7 5 TAI320613 Ac 7 1 2 3 TAT400301 Ac nu—————— 3 6 3 3 —--_____l-10 6 1 3 —--———mmn3 5 —n-m————m3 10 6 —mn7 10 —n-—————n3 2 In the next step, the inventors made the selection of all activated interventional points.

Scores 8, 9 and 10 were considered designating an important/high activation, s scores 6 and 7 were considered designating medium tion. Scores <6 were considered as designating non activated interventional points.

Table 4 shows the complexity of co-activation of interventional points. Each patient’s tumors shows multiple activations, suggesting multiple possibilities of combinations. All 24 interventional points were analysed High activation score: 8, 9 and 10 Medium activation score: 6 and 7 1:; 6s -1; -:_1 -;:~ -:_1 -éNG' [PTKP RAF .PARP PDL1 GEF54 Ant AURK ANGI mTKP ModM TELOM CTLA Her AGPT PI3K MEK FGF RAs -PDL1 1216 ia A o T TKT KON38 Ant CDK ANGI mTKP PLAU TELO HDA 1027 iap 4_6 o T ' WO 93212 LAM , RCD . IAAAG IGF‘ CDK SCDK . RA HDA ANGI |GF_ AAAIII Z|T4 AN _ . IGF_ HDA JAK_ CDK AV'2 ER JAK NOT mTK 3091mm MEK FGF RAs RAE K STAT PDL1 PI3K WNT HDAC CH PT AZE AN CDK AGP TELO JAK_ CTLA AAAI A r BAS HED 2605 Her PARP GEH 12 G BAS AN 4CD“ . _ Am‘a TELO CM HDA 2607 AURKA GI MET PDL1 MEK RAS ~65 p M 4 C 24 O BER mT HED 5204 Her FGF KP RAS GEH T IGF 0G 3%; ME ANGI |GF_ JAK_ NOTC CTLA Her AGPT WNT FGF RAS K O War STAT H 4 BOU CT AURK Ant'a. HDA DNA— 5201 AGF'T FGF LA Her MET RAF PDL1 A p C REP 11 4 BRO JAB; 5211 ED“: ME CTLA ANGIQ STA j K 4 27 T BRZ AU . 4703 Her 23%": RK SNG' Anna DNA PIBK MET MEK TFTKP PARP PDL1 CTLA4 FGF 26 _ p _REP 2805 Her PISK ERK AGPT WNT CHE IAAAA IAAT CDK ME mTKP TELO IGF_ DNA_ NOT Antla.

CDK ME Anna. mTKP M_M TELO JAK_ ME mTKP TELO HDA JAK_ DNA RA IGF CTLA W44 ANGIO MET RAF War— PDL1 s 4 0406 . IGF_W PA HDA DN/L CTLA 'AURK ANGI JAK_ FLA mT TEL IGF_ HDA DNA_ PLAU AS1307 ANGIO AGPT WNT PARP OM War -ANGIO Her CDK P|3K CTLA WO 93212 4403 46 STAT REP CTLA 4408 MET Antiap DNEA RAF CDK mTKP DNA_ NOTC 4902 AMGIO MEK RAF WNT Her S 4_6 T REP H GI R HED 2206 Her ERK RAF AGPT MET GEH 06 0G GOE AN HED 1912 Her AGPT GI RAS EDA GEH 05 O OG CDK , , mTKP HDA JAIL CTLA 1008 GRY JAK_ TELO CTLA STA RAS G6U| |GF_~ JAK_ NOT CDK HDA ME HDA Her PISK RAS RAF CTLA4 ME mTKP JAK_ 5011 Her ANGIO EHO AGPT P|3K STAT IANGIOgGL3 HED mTK lGF.

AGPT . GEH 4403 ANGIO Her AGPT AGPT 4209-1111310KRA mTKP IGF‘ JAK~ DNA CTLA MET ERK CDK ER Anna mTKP DNA_ CTLA AURK 4507 MET 4_6 K REP 4 CTLA 5605 .Amero PIBK MET RAF PT 4 MAC F—a AURK TELO ANGIO ERK WNT Her PARP PDL1 4601 M MAR HED AG |GF_ 4307 Her ANGIO P|3K ERK AF PARP GEH PDL1 PT War CDK AG mTKP JAK NOT 1103 PIBK MET MEK RAF T IrGF_Wa EDK ME JAK_ ANGI CTLA 2704 Her MEK RAF PDL1 _5 T TAT ER HDA 3906 ANGID AGPT Her K C P|3 NOT 4811 Her ERK JAK_ PDL1 STAT CDK ME ANG' mTKP 'GF- 5303 Her PDL1 AGPT FGF WNT ALE K O T War R|T4 Au CDK . HEDG “'3 DNA NQTC CTLA 3110 Her RK PIBK MET ERK RAS RAF EHO 4~6 p 8 A G CDK AG NOT AURK mTK TELO IGF Wa JAK 2042 ANGIO PIBK MET FGF RAs — 4‘6 PT CH PDLflA PT r STAT S|K4 ANGIO é? MET ERK RAS {SE .RAF CTLA PDL1 TA|3 HED |GF_ DNA s c 3 OG TAT AN Anna. mTKP TELO DNA CTLA CDK 4009 Her AURKA GI RAS 01 o l IT IIIME JAK_ CTLA CDK Antla mTKP PAR DNA_ ARC AU HEDG 17 A HOG BOU AU HED CDK DNA NOTC 2911 Antiap RR. PIBK MET WNT PARP REP Q'T'I-KMTELO HDAC 29 _ A HOG DEP AU HEDG 21 ' A . ME CDK HDA JAK_ ”*8 RAF .533;K AU IGF_ HEDGE DNA_ M59 PISK ERK FGF .IAELO WNT HDAC War HOG REP 0729 — A HEDG - GAN . K AUR TELO DNA NOTC Antlap Her PI3K PARP EH0 MEK FGF 3508 4‘ KA GEO HED ME “DA JAK— DNA_ NOTC CDK |GF_Wa 2701 Antiap AURKA ERK RAs GEH WNT T c STAT 14 OS HAM AN ASP TELO 6407 Antiap AURKA GI MEK ERK FGF RAS 1m T M :5;— 29 0 P13 mTKP TELO 3206 Antiap Her MET MEK FGF RAF RAS K $111 LEF - AN lGF. DNA_ HDAC War :EgGE REP 9%: ANGI mTKP HDA DNA_ FGF PARP REP New 11 . A LEN HED mTKP TELO DNA_ NOT FGF GEH IGF NOT 3‘: War mTKP ERK RAF PARP R ATDNA_REP REC CDK K AGF’ Antiap PIEK 5907 46 4 T SAU HED TELO FGF RA GEH PARP OG “0T ER IGF TELO NOT 3008 Antiap ANGIO RAF PDL1 K War v1L3 AN HED 1030 Antiap AUBKA G! PISK MET 9 0 0G BAR AN HED AGP Antia mTKP TELO 3311 Her AURKA GI PI3K RAB RAF HDAC GEH B:E1M MKS ER Antia ONT CTLA PI3K FGF TAT CH 4 BEN JAK_ 4807 PDL1 STA 4105 ANGIO AGPT RAS RAF A C B1E4 Au IAntia (I);I}: DNA CTLA ANGI mTKP TELO IGF M War 01 _ CAP HED 4602 AUBKA MET .Am GEH AGPT 18113 OG IGF_ CTLA mTKP CTLA CDK G|F_ DNAR ANGIO AGPT ERK CRE HEDG CDK AG mTKP TELO |_GF NOT 4204 ANG10 MET FGF EHO PDL1 CTLA4 4_6 PT T CDK AG JAK_ NOT CTLA mTK 404 RAS RAF STAT DAV HED 3204 ANGIO Ant IGF NOT AURKA FGF 1 :24 MET .PARP PDL1 lap War CH ETLA 07 0G -ANGIO AGPT Anna TKP RAF PARP DNA NOTC PDL1 3307 T War E3DO PAR TELO NOT CTLA I152LA HED 5408 53%" NOT FGF RAF LEE HDA WNT GEH PDL1 s ar 09 _ FER AN 4612 AGPT EEEGEW'PBK PI3K MEK WNT HDAC 'AURKAFOR JAK HED PISK ISTA NOT .T.4_6CDK GEH ERK ETTK .TELOM PARP G7AR OG TE HED HED 4108 AURKA PTBK LO WNT RARR GEH GEH ggfi‘mNOT PDL1 .2323K ANGIO AGPT 13 M 06 GAR Ant HED 4508 Her PISK iap 5% SEQC”OT HDA WNT RARR GEH 19 AlumcCTLACDK opt OG GI L2 HEDG IGFJN HD mTKP TELO JAK_ DNARE AU - HED “ma TELO 'GF~ HDA NOT ANG' ME GOM45 Her RK AGRT PISK FGF RARR GEH p M War C CH 0227 A Au HED mTKP TELO ”DA DNA NOT CDK HAR331 Her RK P13K MEK WNT RARR GEH T M c RER CH GINO 217 A 06 Anti JAK- TELO DNA |SA3009 ERK RAS 2E3 ERK PARP 3p STAT M REP 17 06 _3T AGPT P|3K MEK ERK RAF PDL1 31 AT .PIBKAG mTKP CTLA NOT MET MEK 16 T PDL1-FGF RAS O CH $131: .

, Anna LAN041 Her K AURKA MET MEK FGF RARR p 2m: RAF Km {SE a’ :0C 130 4_6 JAK- DNA CTLA RA LAN510 Her K AURKA PIBK MEK FGF RAS GEH PDL1 p 6 AT RER 4 F 426 46 013 LEJ501 JAK_ AG Antia 1 15 STAT LEM351 Her. D mTK TELO IGF HDA DNA PARP .06GEH P|3K ERK M War REP LER460 gNG'RA JAK CTLA4 RAF — GEH PDL1 S STAT 716 OG MAR240 I.RAF ME TELO |GF_ DNA NOT M W” .35;H Au HED cm“ Am'a. mTKP DNA CTLA TEL WWEW:WRW...EMIMMAR491 RK AGPT FGF WNT GEH Her RAS p T RER 4 OM 126 06 HDA JAK_ DNA CTIA AURK ANGI Antla. mTKP TEL CDK Antia mTKP TELO HDA JAK_ DNA CTLA MAT230 RK RISK PDL1 T STAT REP CDK Anna. mTKP TELO HDA DNA NUT PAQ470 RK PM WNT P|3K PARP p REP CH lGF HED PIQ340 HDAC MEK ERK GEH PDL1 CDK P13 TELD lGF HDA DNA NOT RAB330 Antiap RAS — WNT PARP GEH Her M war C 06 REP CH AU . CD 005 A 4_6 ar ANGI DNA NOT mTKP HDA SUT470 Antiap WNT PARF’ GEH MEK PDL1 REP CH T C Anti HDA NOT CDK TAR290 ERK FGF PARP GEH ANG' TELO NOT THU220 AGPT IGF_War PDL1 FGF WNT PARP GEH 8 o M CH 630 - OG T|L4202 ER JAK_ST CTLA |GF_ HD AGPT PI3K .MEK FGF RAF 28 Hr:-- PDL1 4 War PARP- 36K PAR gm W SE” 3.2: [Am W VAL271 JAK_ Antia mTKP |GF_ NOT FGF .TELOM WNT PARP 009 STAT PDL1-ERK popt T War . HED AURK Pl3 Antla TELO HDA JAK‘ DNA NOT PDL In a preferred embodiment, the frequence of activation of inteventional points (score>5), enabling determination of the most rationale combinations is the following Table 5. Trends of cooactivation of entional points CTL PD me mT pi3 E}? m AkAur cdk4 HRE Aing FFG PA RasF/R IG DNAR mtorK/PI Histo patient 61 63 54 59 55 57 51 55 56 47 47 88 44 56 83 123 Table 6. Selection of most frequent combinations taking into account trends of coactivation.

For each of the first and second drug number of patients (upper case) and % (lower case) are showed. For each of the third drug number ents out of 123 and % are shown.

Firstdru NBI% Seconddru NBI% % “SW“ “SR” RAS/RAF 19 PD1 L N C) 16 FGF 15 PARP 13 RAS/RAF 28 CTLA4 20 DNARepair 19 CDK4,6 17 ANGIO 17 mTor/PI3K AURKA 16 IGF 15 FGF 15 MET 13 PARP 12 CTLA4 24 PD1 L 23 mTor/PI3K 23 CDK4,6 15 ANGIO 15 RAS/RAF IGF 15 AURKA 13 FGF 13 DNARepair 12 parp 9 RAS/RAF 26 AURKA 26 DNARepair 26 CTLA4 24 parp 21 mTor/PI3K FGF 19 MET 18 PD1 L 17 ANGIO 16 IGF 12 CTLA4 26 mTor/PI3K 22 PD1 L 18 ANGIO 17 MEK 15 RAS/RAF AURKA 14 FGF 14 DNARepair 12 IGF 11 PARP 10 I3K 22 PD1 L 20 MET 16 MEK 15 AURKA 15 RAS/RAF IGF 14 CDK4,6 13 FGF 12 DNARepair AA_\_\_\_\NNN_\_\_\_\_\_\MNN004NNNNNNQJQJQ)AAA—\AAANNNAAAANNNNNQJAA #CTIO‘JNCOCOO-PNNOOCTINNCO—‘N\INCJ‘IC)ANWO‘JCONMN—‘CNO‘JO‘JCOCOCOCOCOCOCNO‘JCOCOO—‘Awm#O‘Jw 11 PARP \l 6 Table 7 summarizes the mostfrequent triple ations mum-m“ “um—n ————”-m- ————”-m- ————”-m- ______n ——————m- "mm- ___“_m- "mm- "mm- ——————m- Table 8. Summarizes the most ent combinations involving and immunomodulator mum-m“ ____-_-_ ——————m- mum-m“ ______n ——————n ____n ——————m- "mm- ——————m- TABLE 9: Detailed List of genes Symbol Genel Pathwa D EGF 1950 epidermal growth factor NM_001963 TGFA 7039 transforming growth factor, alpha 236 AREG 374 EREG 2069 HBEGF 1839 BTC 685 NRG1 3084 NM_004495 NRG2 9542 83H 29; NM_013982 NRG4 14595 EGFR 1956 NM_201282; NM_005228 ERBB2 2064 v-erb-b2 avian erythroblastic leukemia viral ne NM_001005862; homo|00 2 AB025286 ERBB3 2065 v-erb-b2 avian erythroblastic leukemia viral oncogene NM_001982; homo|00 3 NM_001005915 ERBB4 2066 homolo. 4 CDK4 44$83m—xco cyclin-dependent kinase 4 NM_000075 CDK6 cyclin-dependent kinase 6 NM_001259 CCND1 cyclin D1 NM_053056 CCND2 894 cyclin D2 759 9‘l7MGO CCND3 896 cyclin D3 NM_001760 , 1029 NM_000077 CDKN2B 1030 NM_004936 CCNE1 898 cyclin E1 NM_001238 CCNE2 9134 cyclin E2 NM_057749 RB1 5925 retinoblastoma 1 321 polo-like kinase 1 NM_005030 M'Id sugsaum aurora kinase A NM_198433 MHnV bora, aurora kinase A activator NM_024808 ILK 3611 integrin-linked kinase NM_001014795 / K|F11 3832 kinesin family member 11 NM_004523 SISHNHSOISNV VEGFA 7422 vascular endothelial growth factor A NM_001025370; 025366 VEGFB 7423 vascular endothelial growth factor B NM_003377 VEGFC 7424 vascular endothelial growth factor C NM_005429 VEGFD 2277 c-fos induced growth factor (vascular endothelial growth NM_004469 factor D FLT1 2321 fms-related tyrosine kinase 1 NM_001160031; NM_002019 KDR 3791 kinase insert domain receptor (a type I” receptor tyrosine NM_002253 kinase FLT4 2324 68; NM_002020 PDGFA 5154 NM_033023 PDGFB platelet-derived growth factor beta polypeptide NM_002608 PDGFRA platelet-derived growth factor receptor, alpha polypeptide NM 006206 PDGFRB platelet-derived growth factor receptor, beta polypeptide NM_002609 Kit 3815 homo|00 NM_001093772 thrombospondin 1 NM_003246 transforming growth factor, beta 1 NM_000660 SNIlHIOdOISNV angiopoietin 1 NM_001146 angiopoietin 2 NM_001147 angiopoietin-like 1 NM_004673 angiopoietin 4 NM 015985 T|E1 7075 tyrosine kinase with immunoglobulin-like and EGF-like NM_005424 domains 1 TEK 7010 TEK tyrosine , endothelial NM_000459 CD274 or 29126 PDL1 pr0orammed cell death lioand 1 J012|np0w 'OanNINI PDCD1LG2 80380 programmed cell death 1 ligand 2 NM_025239 PDCD1 5133 programmed cell death 1 NM_005018 CTLA4 1493 cytotoxic T-lymphocyte-associated n 4 NM_005214 LAG3 3902 lymphocyte-activation gene 3 NM_002286 P|K3CA 5290 phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic NM_006218 subunit aloha P|K3CB 5291 atidylinositol-4,5-bisphosphate 3-kinase, catalytic 219 subunit beta P|K3CD 5293 phosphatidylinositol-4,5-bisphosphate 3-kinase, tic, NM_005026 catal tic subunit delta P|K3CG 5294 phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic 649 subunit oamma P|3K B 5287 phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic 646; subunit type 2 beta ENST000003671 PRKCB 5579 protein kinase C, beta PRKCA 5578 protein kinase C, alpha P|K3R1 5295 phosphoinositidekinase, regulatory subunit 1 (alpha) P|K3R2 5296 phosphoinositidekinase, regulatory subunit 2 (beta) P|K3R3 8503 oinositidekinase, regulatory t 3 (gamma) HGF 3082 hepatocyte growth factor (hepapoietin A; scatter factor) NM_001010934; NM_001010931 MET 4233 met proto-oncogene AXL 558 AXL receptor tyrosine kinase MST1 R 4486 hage stimulating 1 receptor (c-met-related tyrosine NM_002447 kinase 2015/063263 MAP2K1 5604 mitogen-activated protein kinase kinase 1, E3 ubiquitin NM_002755 orotein Iioase MAP2K2 5605 n-activated protein kinase kinase 2 NM_030662 MAP2K3 5606 mitogen-activated n kinase kinase 3 NM_145109; ENST00000534743 MEK MAP2K4 mitogen-activated protein kinase kinase 4 MAP3K1 4214 n-activated protein kinase kinase kinase 1 MAP3K2 10746 mitogen-activated protein kinase kinase kinase 2 MAP3K3 4215 mitogen-activated protein kinase kinase kinase 3 MAP3K4 4216 mitogen-activated protein kinase kinase kinase 4 NM_005922; NM_006724 mitogen-activated protein kinase 3 mitogen-activated protein kinase 1 kinase suppressor of ras 1 MAPK11 5600 mitogen-activated protein kinase 11 BCL2 596 B-cell CLL/lymphoma 2 NM:000633; SlSOldOdV NM_000657 'llNV BCL2L1 598 BCL2-Iike1 BIRC5 332 baculoviral|APrepeatcontaining5 XIAP 331 X-Iinked inhibitorof apoptosis BAK1 578 BCL2-antagonist/killer 1 FGF1 2246 fibroblast growth factor 1 (acidic) NM_000800; NR_026696 fibroblast growth factor 2 (basic) fibroblast growth factor 3 fibroblast growth factor 4 FGF5 2250 fibroblast growth factor 5 NM_004464; FGF6 2251 fibroblast growth factor 6 FGF7 2252 fibroblast growth factor 7 FGF8 2253 fibroblast growth factor 8 gen-induced) fibroblast growth factor 9 FGF fibroblast growth factor 10 fibroblast growth factor 11 fibroblast growth factor 12 fibroblast growth factor 13 FGF14 2259 fibroblast growth factor 14 FGFR1 2260 fibroblast growth factor receptor 1 ENST00000496296; NM_023110; NM_001174066 FGFR2 2263 fibroblast growth factor or 2 ENST00000359354; fibroblast growth factor receptor 3 FGFR4 2264 fibroblast growth factor receptor 4 2475 mechanistictargetofrapamycin(serine/threonine kinase) NM_004958 mTOR - AKT1 v-akt murine thymoma viral oncogene homolog 1 NM_005163 AKTAKT2 v-akt murine a viral oncogene homolog 2 NM_001626 PTEN- PTEN 5728 phosphatase and tensin homolog NM_000314 TSC1 7248 tuberous sclerosis 1 NM_000368; Sicieinpow ENST00000403810 NM_001077183 serine/threonine kinase 11 NM_000455 ldMllN pim-1 oncogene NM_002648 pim-2 oncogene NM_006875 pim-3 oncogene NM_001001852 ””3336“ NM_004985 NRAS 4893 neuroblastoma RAS viral (v-ras) oncogene homolog NM_002524 HRAS 3265 Harvey rat a viral oncogene homolog NM_005343 RAF RAF1 5894 v-raf-1 murine leukemia viral oncogene homolog 1 NM 002880 v-raf murine sarcoma viral oncogene homolog B NM_004333 telomerase reverse riptase NM_198253 HSVHHINO'IEL telomerase RNA component NR_001566 telomerase-associated protein 1 NM_007110 ”ll—001017963; NM_005348 dyskeratosis ita 1, dyskerin NM_001363 prostaglandin E synthase 3 NM_006601 insulin-like growth factor1 omedin C) NM_000618 insulin-like growth factor 2 (somatomedin A) NM_000612 :IEJI insulin-like growth factor1 receptor 875 5mqu insulin-like growth factor 2 receptor NM_000876 INSR 3643 insulin receptor NM_000208 |RS1 3667 insulin receptorsubstrate 1 NM_005544 PKM 5315 pyruvate kinase, muscle NM 001206796 1 cadherin 1, type 1, erin (epithelial) NM_004360 catenin (cadherin-associated protein), alpha 1, 102 kDa NM_001903 catenin (cadherin-associated protein), beta 1, 88 kDa NM_001904; 098210 wingless-type MMTV integration site family, member 1 NM_005430 WNT FZD1 8321 frizzled class receptor 1 NM_003505 wingless-type MMTV integration site family, member 5A NM_003392 ss-type MMTV integration site , member 5B NM_030775 frizzled class receptor 5 NM_003468 WNT inhibitory factor1 191 dickkohWNT signaling pathway tor 1 NM_012242 PARP1 142 poly (ADP-ribose) polymerase 1 NM_001618; ENST00000366790 breast cancer 1, early onset NM_007300 XRCC1 7515 X-ray repaircomplementing defective repairin Chinese NM_006297 PARP hamster cells 1 RAD54L 8438 RAD54-like (S. cerevisiae) NM_003579 RAD54B 25788 RAD54 homolog B (S. cerevisiae) 415; NM_001205262 ATM 472 ataxia telangiectasia mutated NM_000051; ENST00000389511 ATR 545 ataxia telangiectasia and Rad3 related NM_001184 checkpoint kinase1 NM_001114121 NM_001005735 WEE1 G2 checkpoint kinase NM_003390 histone ylase 1 NM_004964 histone deacetylase 2 NM_001527 HDAC histone deacetylase 3 NM_003883 e deacetylase 4 037 histone ylase 5 NM 001015053 JAK1 3716 Janus kinase 1 NM_002227 JAK2 3717 Janus kinase 2 NM_004972 E signal transducerand activator of transcription 1, 91 kDa NM_139266 'g signal transducerand activator of transcription 2, 113 kDa NM_005419 :3. signal transducer and activator of transcription 3 (acute- NM_213662 phase response factor ssor of cytokine signaling 1 NM_003745 SHH 6469 sonic hedgehog NM_000193 ENST00000375290 g SMO 6608 smoothened, frizzled class receptor NM_005631 fl serine/threonine kinase 36 NM 015690 é protein kinase, cAMP-dependent, tic, alpha 730 NM_001178133 GLI family zinc finger 1 NM_005269 excision repair cross-complementation group 1 NM_202001 RAD52 g (s. cerevisiae) NM_134424; ENST00000545967 g; hamster cells 4 g RAD51 recombinase NM_002875 2—; breast cancer 1, early onset NM_007300 re ulated 8 NEDD8 activating enzyme E1 subunit 1 NM 001018159 notch 1 NM_017617 ADAM metallopeptidase domain 17 NM_003183 ENST00000394157 g nicastrin NM_015331 ' JAG1 182 jagged 1 NM_000214 NM_015908; NM_001128854 NM_001077628 2015/063263 R081 6098 c-ros oncogene 1 , receptor tyrosine kinase ENSTOOOOO403284 ; NM_002944 anaplastic lymphoma receptor tyrosine kinase 304 RET 5979 ret oncogene NM_020630; NM_020975 UBA1 7317 ubiquitin-like modifier activating enzyme 1 334 TABLE 10 : List of genes mutations BRAF c.1799 T>W p.Va|6OOG|u V600E c. 1798 G>R p.Val600LyS V600K c.1799 T>W c.1799 T>W c.1SOOG>R p.Va|6OOG|u V600E EGFR Nucleotide Protein IEffect on EGFR inhibitors c.2156G>C p.Gly719Ala G719A ility c.2155 G>K p.Gly719CyS G719C Sensibility c.2117 T>Y p.||e706Thr I706T Sensibility c.2125 G>R p.G|u709LyS E709K Sensibility c.2126 A>M p.G|u709AIa E709A Sensibility c.2174 C>Y p.Thr725Met T725M Sensibility c.2165C>M p.A|a7ZZG|u A722E Sensibility Delet'on E746" 'l'ty c.2235_2249 del p.G|u746_Ala750del A750 Delet'on E746" sens'b'l'ty c.2236_2250 del p.G|u746_Ala750del A750 Delet'on L747" 'l'ty c.2240_2254del p.Leu747_Thr751del T751 Deletion L747- Sensibility c.2240_2257 del p.Leu747_Pro753delinSSer P753 Insertion S Deletion E746- Sensibility c.2237_2251de| p.G|u746_Thr751de|inSA|a T751 Insertion A Deletion L747- Sensibility c.2239_2248de|inSC p.Leu747_Ala750delinSPro A750 Insertion P Deletion L747- Sensibility c.2239_2251de|inSC p.Leu747_Thr751delinSPro T751 Insertion P Deletion E746- Sensibility c.2237_2255 delinST p.G|u746_Ser752delinSVal S752 Insertion V c.2214_2231dup 40_LyS745dup Duplication I740- Sensibility K745 Deletion S752- Sensibility C.2254_2277 del p.Ser752_|le759del I759 K745-E746 Sensibility c.2219_2236dup p. _Glu746insValProValAla||eLys Insertion VPVAIK c.2277 c>s p.||e759 Met I759M ility Deletion L747- Sensibility C.2239_2256de|insCAA p.Leu747_Ser752delinsGln S752 Insertion Q c.2369C>Y p.Thr790Met T790M Resistance C.2317_2318insACC 73dup Duplication H773 Resistance 773 Resistance c.2317_2318in512 p.Pro772_His773insLeuGlyAsnPro insertion LGNP Duplication P772- Resistance c.2315_2326dup p.Pro772_Cys775dup C775 Duplication A767- Resistance _2308 clup 67_Va|769dup V769 Duplication S768- Resistance c.2303_2311 clup p.Ser768_Asp770dup D770 Duplication S768- Resistance c.2303_2311dup p.Ser768_Asp770dup D770 C.2335G>T p.Gly779Cys G779C Resistance c.2573 T>K p.Leu858Arg L858R Sensibility c.2582 T>W p.Leu86lGln L861Q ility KRAS-NRAS Nucleotide Protein c.34 G>K p.Gly12Cys 612C c.35 G>R p.Gly12Asp GlZD c.35 G>K p.Gly12Val GlZV c.35 G>S p.Gly12Ala 612A c.34 G>R p.Gly12Ser GlZS c.34 G>S p.Gly12Arg 612R c.38 G>R p.Gly13Asp 613D c.37 G>K 3Cys 613C c.182 A>W p.G|n61Leu Q61L c.182 A>R p.G|n61Arg Q61R c.183 A>M p.G|n61His Q61H c.176 C>S p.A|a59Gly A59G c.175 G>R p.A|a59Thr A59T c.176 C>M p.A|a59Glu A59E ERBBZ c.2313_2324dup p.Tyr772_Ala775dup Duplication Y772-A775 c.2318_2319insGATGGCATACGT p.Tyr772_Ala775dup Duplication Y772-A775 Deletion G776 c.2326_2327|nsTGT. p.Gly776delinsVaICys. c2331_2339dup p.G|y778_Pro780dup Duplication G778-P780 FUK3CA Nucleotide Protein c.1624 G>R p.G|u542Lys E542K c.1633G>R p.G|u545Lys E545K c.3140A>R p.Hile47Arg H1047R c.3140A>W p.Hile47Leu H1047L c.2959 G>R p.Ala987Thr A987T c.30526>A p.Asp1018Asn D1018N c.3080 C>Y p.Ala1027Val A1027V c.3131A>R p.Asn1044Ser N1044S TABLE 11 : List of miRNA Symbol Pathwa EGF 1950 hsa-miR-4673; hsa-miR5p; hsa-miR-647 ; hsa-miR5p ; hsa-miR5p TGFA 7039 hsa-miR-3147; hsa-miR-1178; hsa-miR-626; hsa-miR-148a; hsa-miR-1182 AREG 374 hsa-miR-517a ; hsa-miR-34c-5p ; hsa-miR3p ; hsa-miR5p ; hsa-miR- 517b EREG 2069 hsa-miR5p ; hsa-miR5p ; hsa-miR-130a ; hsa-miR-3661 ; hsa-miR-192 HBEGF 1839 hsa-miR-4736; hsa-miR5p; hsa-miR-4710; hsa-miR5p; hsa-miR-1271 BTC CD0) O1 hsa-miR3p; hsa-miR-1200; hsa-miR5p; hsa-miR-934; hsa-miR-488 NRG1 3084 hsa-miR-4632; hsa-miR-1203; hsa-miR-552; hsa-miR-4736; hsa-miR-183 HEIH NRG2 9542 hsa-miR-3196; hsa-miR-3934; hsa-miR5p; R5p; hsa-miR5p NRG4 145957 hsa-miR-608; hsa-miR-1301; hsa-miR3p; hsa-miR-516b; hsa-miR-3681; EGFR 1956 hsa-miR-4417; hsa-miR-608; hsa-miR3p; hsa-miR3p; hsa-miR-7; ERBB2 2064 hsa-miR3p; hsa-miR5p; R-1972; hsa-miR-4533; hsa-miR-1296; ERBB3 2065 R-3199; hsa-miR-4505; hsa-miR-1287; hsa-miR-3153; hsa-miR-4290; ERBB4 2066 hsa-miR-4469; hsa-miR-193a-3p; hsa-miR-642a; hsa-miR-3907; hsa-miR3p; CDK4 1019 hsa-miR5p; hsa-miR-198; hsa-miR5p; hsa-miR-765; hsa-miR-4280; CDK6 1021 R-3680; R3p; hsa-miR-621; hsa-miR-644; hsa-miR-4252; CCND1 R3p; hsa-miR-3170; hsa-miR-1193; hsa-miR3p; hsa-miR-4632; CCND2 894 R-1468; R-103b; hsa-miR-1205; hsa-miR3p; hsa-miR-4718; 9‘VMGO CCND3 896 hsa-miR5p; hsa-miR-4739; hsa-miR-138; hsa-miR5p; hsa-miR-3154; CDKN2A, 1029 hsa-miR-663b; hsa-miR-675; hsa-miR-663; hsa-miR-1291; hsa-miR-621; CDKN2B 1030 hsa-miR-4308; hsa-miR-718; hsa-miR-1914; hsa-miR-451; hsa-miR-346; CCNE1 898 hsa-miR-16; hsa-miR-874; hsa-miR-146b-3p; hsa-miR-4524; hsa-miR-3190; CCNE2 9134 hsa-miR-449a; hsa-miR-370; hsa-miR-4460; R-30b; hsa-miR5p; RB1 5925 hsa-miR5p; R-4801; R-4432; hsa-miR-7; hsa-miR5p; .PLK1 5347 hsa-miR5p; hsa-miR-4660; hsa-miR-3665; hsa-miR-3166; hsa-miR5p; aum l)l unv l ‘AURKA 6790 hsa-miR-3941; R5p; R5p; R3p; hsa-miR- 4757-5p; BORA 79866 hsa-miR3p; hsa-miR3p; hsa-miR5p; hsa-miR3p; hsa-miR- 3189-5p; ILK 361 1 hsa-miR-1908; hsa-miR-4505; hsa-miR-744; hsa-miR-4425; hsa-miR-3150a-3p; K|F1 1 3832 VEGFA 7422 hsa-miR-3668; hsa-miR-939; hsa-miR-29a; hsa-miR5p; hsa-miR-16; VEGFB 7423 hsa-miR3p; hsa-miR3p; hsa-miR3p; hsa-miR-193a-5p; hsa-miR- 1275; VEGFC 7424 hsa-miR-711; hsa-miR5p; hsa-miR3p; R-128; hsa-miR-4318; VEGFD 2277 hsa-miR-320e; hsa-miR-135a; hsa-miR-7; hsa-miR-1184; hsa-miR-513b; SISEINEIEJOIEJNV FLT1 2321 hsa-miR-148a; R-5095; hsa-miR-335; hsa-miR3p; hsa-miR-149; KDR 3791 hsa-miR-4435; hsa-miR-665; hsa-miR-370; R-136; hsa-miR-138; FLT4 2324 hsa-miR3p; hsa-miR-2861; hsa-miR5p; hsa-miR3p; hsa-miR- 4783-5p; PDGFA 5154 hsa-miR5p; hsa-miR-3917; hsa-miR-4706; hsa-miR5p; hsa-miR-412; PDGFB 5155 hsa-miR-3202; hsa-miR-1909; hsa-miR-3689d; hsa-miR-4271; hsa-miR-625; PDGFRA 5156 hsa-miR3p; hsa-miR-4471; hsa-miR-34a; hsa-miR-663b; hsa-miR3p; PDGFRB 5159 hsa-miR-1915; hsa-miR-4292; hsa-miR5p; hsa-miR-637; hsa-miR3p; Kit 3815 hsa-miR-4254; hsa-miR5p; hsa-miR-1193; R-222; hsa-miR-4485; THBS1 7057 hsa-miR5p; hsa-miR3p; hsa-miR5p; hsa-miR-634; hsa-miR-4443; TGFB1 7040 hsa-miR-3196; hsa-miR-663; hsa-miR5p; hsa-miR-3943; hsa-miR-3183; SNIlEIIOdOISNV ANGPT1 284 hsa-miR-153; hsa-miR-4643; hsa-miR5p; hsa-miR3p; hsa-miR3p; ANGPT2 285 hsa-miR-135a; hsa-miR-1182; hsa-miR-513c; hsa-miR-597; hsa-miR-4251; 1 9068 hsa-miR5p; hsa-miR-586; hsa-miR-4480; hsa-miR-544; R-194; ANGPT4 51378 R5p; hsa-miR3p; hsa-miR-422a; hsa-miR-431; hsa-miR-665; T|E1 7075 hsa-miR-3151; hsa-miR-4447; hsa-miR5p; R3p; hsa-miR-4287; TEK 7010 hsa-miR5p; hsa-miR-300; R3p; hsa-miR-150; hsa-miR-148a; CD274 or 29126 hsa-miR-4443; hsa-miR3p; hsa-miR-138; hsa-miR5p; hsa-miR-1273; PDL1 Joaempow OanNINI PDCD1LG2 80380 hsa-miR-20a; hsa-miR-548an; hsa-miR5p; hsa-miR-3133; hsa-miR-3910; PDCD1 5133 hsa-miR-4290; hsa-miR-1291; hsa-miR5p; hsa-miR-2861; hsa-miR-661; CTLA4 1493 hsa-miR5p; hsa-miR5p; hsa-miR-4254; R5p; hsa-miR-1587; LAG3 3902 hsa-miR-4515; hsa-miR-1269; hsa-miR3p; hsa-miR-4270; hsa-miR5p; P|K3CA 5290 hsa-miR-4450; hsa-miR3p; hsa-miR-302d; hsa-miR-3910; hsa-miR5p; P|K3CB 5291 P|K3CD 5293 hsa-miR-4537; hsa-miR5p; hsa-miR-523; hsa-miR-7; hsa-miR-484; P|K3CG 5294 hsa-miR-370; hsa-miR-3135b; R-1976; hsa-miR-1276; hsa-miR-3672; B 5287 hsa-miR3p; R5p; hsa-miR3p; hsa-miR-3612; hsa-miR-4314; P|3K PRKCB 5579 R5p; hsa-miR-448; hsa-miR-7; hsa-miR-668; hsa-miR-27a; PRKCA 5578 hsa-miR5p; hsa-miR5p; hsa-miR-4706; hsa-miR-1275; hsa-miR-4525; P|K3R1 5295 R3p; hsa-miR5p; R3p; hsa-miR-1184; hsa-miR- 4660; P|K3R2 5296 hsa-miR5p; hsa-miR-3180; hsa-miR-4447; hsa-miR-3960; hsa-miR-3151; P|K3R3 8503 hsa-miR3p; hsa-miR-4435; hsa-miR5p; hsa-miR-2115; hsa-miR-4313; HGF 3082 hsa-miR-4520a-3p; hsa-miR-764; hsa-miR3p; hsa-miR-1288; hsa-miR-4710; MET 4233 R5p; R-2682; hsa-miR-34c—5p; hsa-miR-182; hsa-miR-1269b; AXL 558 hsa-miR-3142; R5p; hsa-miR-924; hsa-miR-3689c; hsa-miR-432; MST1 R 4486 hsa-miR5p; R-218; hsa-miR-1286; R5p; hsa-miR-4284; WO 93212 MAP2K1 5604 hsa-miR-4323; hsa-miR3p; hsa-miR-758; hsa-miR-34a; hsa-miR-15b; MAP2K2 5605 hsa-miR-1181; hsa-miR3p; hsa-miR-744; hsa-miR-663; hsa-miR5p; MAP2K3 5606 hsa-miR-4313; hsa-miR-3151; hsa-miR-4283; hsa-miR-4540; hsa-miR-4270; MAP2K4 6416 hsa-miR-4663; hsa-miR-25; R3p; hsa-miR5p; hsa-miR-627; MEK MAP3K1 4214 hsa-miR-4286; hsa-miR3p; hsa-miR3p; hsa-miR-544; hsa-miR-887; MAP3K2 10746 hsa-miR-519d; hsa-miR-651; hsa-miR-587; hsa-miR-34c-3p; hsa-miR-2909; MAP3K3 4215 hsa-miR-661; hsa-miR3p; hsa-miR-544b; hsa-miR3p; hsa-miR-4505; MAP3K4 4216 hsa-miR-1204; R5p; hsa-miR-5047; R3p; hsa-miR MAPK3 5595 hsa-miR-4270; hsa-miR3p; hsa-miR5p; hsa-miR-608; hsa-miR-1291; MAPK1 5594 hsa-miR5p; hsa-miR-4459; hsa-miR-4271; hsa-miR5p; hsa-miR-2110; KSR1 8844 hsa-miR3p; hsa-miR-4440; hsa-miR-4291; hsa-miR-4660; hsa-miR3p; MAPKT 5600 hsa-miR3p; hsa-miR5p; hsa-miR-4292; hsa-miR-4532; hsa-miR5p; BCL2 596 hsa-miR-448; hsa-miR3p; hsa-miR-3199; hsa-miR-3943; hsa-miR3p; OdV BCL2L1 598 hsa-miR-4447; hsa-miR-608; hsa-miR5p; hsa-miR3p; hsa-miR5p; 'llNV ERC5 332 hsa-miR3p; hsa-miR3p; hsa-miR-4660; hsa-miR3p; hsa-miR-1273; MAP 331 R-377; hsa-miR-3150a-3p; hsa-miR-3175; hsa-miR-5095; hsa-miR5p; BAK1 578 hsa-miR-4419a; hsa-miR-125b; hsa-miR5p; hsa-miR-1909; hsa-miR-4739; FGF1 2246 hsa-miR-4297; hsa-miR-3155; hsa-miR-1909; hsa-miR-566; R5p; FGF2 2247 hsa-miR-195; hsa-miR-4524; hsa-miR-503; hsa-miR-646; hsa-miR5p; FGF3 2248 hsa-miR5p; hsa-miR-4487; R-760; hsa-miR3p; hsa-miR3p; FGF4 2249 hsa-miR5p; hsa-miR3p; hsa-miR-4290; hsa-miR3p; hsa-miR ;hEa-miR-4435; FGF5 2250 hsa-miR5p; hsa-miR-4288; hsa-miR-4463; hsa-miR3p; FGF6 2251 hsa-miR3p; hsa-miR-548q; hsa-miR-138; hsa-miR-639; hsa-miR-1322; FGF7 2252 hsa-miR5p; R5p; hsa-miR-195; hsa-miR-3920; hsa-miR-1253; FGF8 2253 hsa-miR3p; hsa-miR-545; hsa-miR5p; hsa-miR3p; hsa-miR ;hEa-miR-1273c; FGF9 2254 hsa-miR5p; hsa-miR3p; hsa-miR5p; hsa-miR-3683; FGF10 2255 FGF11 2256 hsa-miR3p; hsa-miR-4469; R-3192; hsa-miR-3661; R-3649; FGF12 2257 hsa-miR5p; hsa-miR-3202; hsa-miR-4533; hsa-miR3p; hsa-miR-197; FGF13 2258 hsa-miR-1262; hsa-miR5p; R-1185; hsa-miR3p; hsa-miR-4421; FGF14 2259 hsa-miR-4663; hsa-miR3p; R-4299; hsa-miR5p; hsa-miR3p; FGFR1 2260 hsa-miR-4530; hsa-miR5p; hsa-miR3p; hsa-miR-1208; hsa-miR5p; FGFR2 2263 hsa-miR5p; hsa-miR3p; hsa-miR3p; hsa-miR3p; hsa-miR- 3675-5p; FGFR3 2261 hsa-miR5p; hsa-miR3p; hsa-miR3p; hsa-miR-3918; hsa-miR-1291; FGFR4 2264 R3p; hsa-miR5p; hsa-miR3p; hsa-miR-378g; hsa-miR-564; mTor 2475 hsa-miR3p; R3p; hsa-miR-496; hsa-miR-1233; hsa-miR-1229; AKT1 207 R-1915; hsa-miR-4721; R3p; hsa-miR5p; hsa-miR mTOR -AKT- PTEN- AKT2 [\3O O) hsa-miR3p; hsa-miR-29b; hsa-miR-4278; hsa-miR-3943; hsa-miR3p; PTEN 5728 hsa-miR-642b; hsa-miR5p; hsa-miR-148a; hsa-miR5p; hsa-miR5p; TSC1 7248 hsa-miR-130a; hsa-miR-1537; hsa-miR-637; R-3141; R-3684; ldMllN Joaempow TSC2 7249 hsa-miR-4420; hsa-miR3p; hsa-miR5p; hsa-miR5p; hsa-miR STK11 6794 hsa-miR-663; hsa-miR-744; hsa-miR5p; hsa-miR-3960; hsa-miR5p; P|M1 5292 hsa-miR3p; hsa-miR-761; hsa-miR-3689a-3p; hsa-miR3p; hsa-miR- 4436b-3p; P|M2 11040 hsa-miR3p; hsa-miR-4532; hsa-miR-3654; hsa-miR5p; R3p; P|M3 415116 hsa-miR-3195; hsa-miR5p; hsa-miR5p; hsa-miR-4467; hsa-miR-637; KRAS 3845 hsa-miR-3923; hsa-miR-4323; hsa-miR-4447; hsa-miR-513a-5p; hsa-miR-548ag; NRAS 4893 hsa-miR5p; hsa-miR-1296; hsa-miR-1324; hsa-miR3p; hsa-miR-4271; HRAS 3265 hsa-miR3p; hsa-miR5p; hsa-miR-4292; hsa-miR-4532; hsa-miR-663; RAF1 5894 RAF hsa-miR-1291; hsa-miR-7; hsa-miR5p; hsa-miR5p; hsa-miR-764; BRAF 673 hsa-miR-617; hsa-miR-2110; hsa-miR-3977; hsa-miR-1182; R-1289; TERT 7015 hsa-miR5p; hsa-miR5p; hsa-miR-4651; hsa-miR-3687; hsa-miR-4292; EISVHEIINO'IEIJ. TERC 7012 TEP1 7011 hsa-miR-1911; hsa-miR-3132; hsa-miR-136; hsa-miR-2861; hsa-miR-31; HSP90AA1 3320 hsa-miR5p; hsa-miR-632; hsa-miR-519e; hsa-miR3p; hsa-miR-134; DKC1 1736 hsa-miR3p; hsa-miR-621; R-3620; hsa-miR-646; hsa-miR-4279; PTGES3 10728 hsa-miR5p; hsa-miR-3135; hsa-miR-4266; hsa-miR3p; hsa-miR-4286; |GF1 3479 hsa-miR3p; hsa-miR-1275; R-4435; hsa-miR-488; hsa-miR-625; |GF2 3481 hsa-miR-4447; R5p; hsa-miR-210; hsa-miR-3191; hsa-miR5p; :l9l |GF1R 3480 hsa-miR3p; hsa-miR-4784; hsa-miR3p; hsa-miR-4327; hsa-miR ’9 5p; BanJeM |GF2R 3482 hsa-miR3p; hsa-miR-653; hsa-miR3p; hsa-miR-4736; hsa-miR-548an; INSR 3643 hsa-miR5p; hsa-miR-3975; hsa-miR-3188; hsa-miR3p; hsa-miR-4290; |RS1 3667 hsa-miR-660; hsa-miR-541; hsa-miR-4462; hsa-miR-544b; hsa-miR-183; PKM2 5315 hsa-miR-762; hsa-miR-625; R-612; hsa-miR-4675; hsa-miR5p; CDH1 hsa-miR3p; hsa-miR5p; hsa-miR-3689c; hsa-miR5p; hsa-miR- 1296; CTNNA1 1495 hsa-miR-1288; hsa-miR-4440; hsa-miR-4515; hsa-miR-4705; hsa-miR-9; CTNNB1 1499 hsa-miR5p; hsa-miR3p; R5p; R-4496; R- 3619-3p; WNT 1 7471 hsa-miR-4488; hsa-miR-4784; hsa-miR5p; hsa-miR-4644; hsa-miR-4689; WNT FZD1 8321 R-4269; hsa-miR5p; hsa-miR-1275; hsa-miR-1324; hsa-miR-4279; WNT5A 7474 hsa-miR-2110; hsa-miR5p; hsa-miR5p; R3p; R-4656; WNT5B 81029 hsa-miR-4316; hsa-miR-4258; hsa-miR-2909; hsa-miR-1296; hsa-miR3p; FZD5 7855 hsa-miR5p; hsa-miR-3943; R3p; hsa-miR-3661; hsa-miR-3672; WI F1 11197 hsa-miR-1972; hsa-miR-3938; hsa-miR-548v; hsa-miR3p; hsa-miR-3977; DKK1 22943 hsa-miR-493; hsa-miR3p; hsa-miR5p; hsa-miR-4678; hsa-miR-934; PARP1 142 hsa-miR-891b; hsa-miR-4536; R-4451; R-555; R-7; BRCA1 672 hsa-miR5p; hsa-miR3p; hsa-miR3p; hsa-miR-760; hsa-miR-4656; XRCC1 RAD54L 8438 hsa-miR5p; hsa-miR3p; hsa-miR-3918; hsa-miR3p; hsa-miR- 1291 ; RAD54B 25788 hsa-miR-587; hsa-miR-4268; hsa-miR-548s; hsa-miR-3926; hsa-miR-1; PARP ATM J>7 [\J hsa-miR-892b; R-193a-3p; hsa-miR3p; hsa-miR-4736; hsa-miR-4262; ATR 545 hsa-miR5p; hsa-miR-383; hsa-miR5p; hsa-miR3p; hsa-miR-586; CHEK1 1 1 1 1 hsa-miR5p; hsa-miR-541; hsa-miR-1286; hsa-miR3p; hsa-miR-16; CHEK2 11200 hsa-miR-3118; hsa-miR-759; hsa-miR-4276; hsa-miR-3938; R-943; WEE1 7465 hsa-miR3p; hsa-miR5p; hsa-miR-424; hsa-miR3p; hsa-miR-4278; HDAC HDAC1 3065 hsa-miR-4284; hsa-miR-4292; hsa-miR-4271; R5p; hsa-miR-584; HDAC2 3066 hsa-miR5p; hsa-miR-3977; hsa-miR3p; hsa-miR-4662a-5p; hsa-miR- 4720-5p; HDAC3 8841 hsa-miR3p; hsa-miR-1261; R-326; hsa-miR-1302; hsa-miR-4308; HDAC4 9759 hsa-miR-4292; hsa-miR-4313; hsa-miR5p; hsa-miR3p; hsa-miR-4316; HDAC5 10014 hsa-miR3p; hsa-miR5p; hsa-miR-4498; hsa-miR5p; hsa-miR-4505; JAK1 3716 hsa-miR-4252; hsa-miR-4437; hsa-miR-4520a-3p; hsa-miR-323b-5p; hsa-miR-4674; JAK2 3717 hsa-miR5p; hsa-miR-4468; R3p; hsa-miR3p; hsa-miR-568; lVlS'MVP STAT1 6772 hsa-miR-4682; hsa-miR-1252; hsa-miR-3119; hsa-miR3p; hsa-miR-2682; STAT2 6773 R-665; hsa-miR-3202; hsa-miR-4292; hsa-miR-4313; hsa-miR-1289; STAT3 6774 hsa-miR-1299; hsa-miR5p; hsa-miR-1184; hsa-miR-874; hsa-miR-5047; SOCS1 8651 hsa-miR5p; hsa-miR3p; hsa-miR3p; hsa-miR3p; hsa-miR- 324-5p; SHH 6469 hsa-miR-1471; hsa-miR3p; hsa-miR-4313; PTCH1 5727 hsa-miR5p; hsa-miR-564; hsa-miR-1262; hsa-miR3p; hsa-miR-125a-3p; 90HE|EJGEIH SMO 6608 hsa-miR-370; hsa-miR3p; hsa-miR3p; hsa-miR3p; hsa-miR-1915; STK36 27148 hsa-miR-571; hsa-miR-3192; hsa-miR-581; hsa-miR-920; hsa-miR5p; PRKACA 5566 hsa-miR5p; hsa-miR5p; R-608; hsa-miR5p; R-625; SUFU 51684 hsa-miR-3184; hsa-miR-4487; hsa-miR-4688; R5p; hsa-miR-4741; GL|1 2735 R-3943; hsa-miR-4279; hsa-miR-4292; hsa-miR3p; hsa-miR-4533; ERCC1 2067 hsa-miR-661; hsa-miR-1913; hsa-miR5p; R-1972; hsa-miR-1268; RAD52 5893 hsa-miR3p; R3p; R3p; hsa-miR3p; hsa-miR- 4303; VNG XRCC4 7518 hsa-miR5p; hsa-miR-380; hsa-miR-4520a-3p; hsa-miR5p; hsa-miR- HIVdEIH 2355-3p; RAD51 5888 hsa-miR-198; hsa-miR3p; hsa-miR-606; hsa-miR-4430; hsa-miR-4432; BRCA1 672 hsa-miR5p; hsa-miR3p; hsa-miR3p; hsa-miR-760; hsa-miR-4656; NEDD8 4738 hsa-miR3p; hsa-miR5p; hsa-miR-665; hsa-miR-1285; hsa-miR-1322; NAE1 8883 R-4524; hsa-miR-646; R-4660; hsa-miR5p; hsa-miR-603; NOTCH1 4851 hsa-miR-4313; hsa-miR-4268; hsa-miR-449a; hsa-miR5p; R5p; Adam17 6868 R-507; hsa-miR-3918; hsa-miR5p; hsa-miR-3651; hsa-miR-1827; PSEN1 5663 hsa-miR3p; hsa-miR3p; hsa-miR5p; hsa-miR-4303; hsa-miR-488; HOlON NCSTN 23385 hsa-miR5p; hsa-miR-4654; hsa-miR-1321; hsa-miR-4648; hsa-miR-3657; JAG1 182 hsa-miR-4692; hsa-miR-1273g; hsa-miR-920; hsa-miR5p; hsa-miR-4283; SRRT 51593 hsa-miR3p; hsa-miR-3190; hsa-miR-487b; hsa-miR-520f; hsa-miR-3929; APH1A 51107 hsa-miR3p; hsa-miR-198; hsa-miR3p; R5p; hsa-miR-3131; ROS1 6098 hsa-miR3p; hsa-miR3p; hsa-miR-33a; hsa-miR-606; R-3659; memo ALK 238 hsa-miR-642a; hsa-miR-646; hsa-miR3p; hsa-miR-1271; hsa-miR3p; RET 5979 hsa-miR-544; hsa-miR5p; hsa-miR-510; hsa-miR-31; R-3622b-5p; UBA1 7317 hsa-miR3p; hsa-miR-762; hsa-miR5p; hsa-miR-3202; hsa-miR-31; Table 12: Mutational status _ P53 80_SNP_A>G_R-Arg_exon6, —| —| 102_de|etion_C_exon8 p.G|y12Va| 39_G>A_Met>||e_exon7, (G12V) WT E_l E_l 75_G>C_exon7 Ii 47_G>T_Ser>||e_exon7, WT E_| 51_C>A_Ser>Ser_exon7 c.2883T>G p.||e961 Met (I961 M) AGVGD:C|ass E_l E_l C0_exon 24 —| c.34G>K p.G|y12Cys G12C WT —| —| —| —| c.35G>R G12D —| —| E —| 3_C>T_G| >G| _exon7 p.G|y12Cys G12C WT —| —| —| —| c.35G>K p.G|y12Va| G12V WT WT E_| E_| c.3075C>T WT WT rST 7849079 WT WT 139_A>G_G|u>G| _eX0n5 p.G|y12Va| G12V WT WT WT W—| WT T iT T 17_G>T_exon10 c.35G>R p.G|y12Asp (G12D) WT WT WT WT WT WT i—| —| WT _Asp>Tyr_exon5 WT —| WT (0—\6_G>C_Va|>Leu_exon5 62_G>A_G|y>Asp_exon7, and WT nd 88_insertion_G_exon7 c.34G>K p.G|y12Cys (G12C) WT WT WT c.34G>K p.G|y12Cys G12C —| WT 94_G>A_Aro xon5 WT T WT 55_G>C_G| >A|a_exon8 p.G|y12Va| (G12V) WT WT WT c.2184+19G>R WT NonCodant 7107 WT WT 57_A>T_Aro >Stop_exon8 c.2184+19G>R é Non Codant rs17337107 WT WT WT 58_insertion_G, €34 i—| WT WT 75_SNP_G>A_Aro >Aro_exon7 WT WT 42_A>G_Lys>G|u_exon5 +19G>R Non Codant 7107 Codant c.1799T>W p.Val600Glu WT WT WT (V600E) WT 61 58_G>A_G|y>Ser_exon6 65_T>A_Met>Lys_exon7, 70_G>A?_Gly?>Arg?_exon7, 129_C>T_exon7 -c2184+19G>A_Non Codant rs17337107 47_G>T_Ser>||e_exon7 51_C>A_Ser>Ser_exon7, WT wt wt wt 83_C>A?_Pro?>His?_exon7 p.Val774delinsAIaLeu exon 20 c.35G>S p. G|y12A|a G12A WT 152_insertion_T_exon5 Non Codant rs17337107 WT WT WT WT 83_T>C_exon7 55_A>G_Tyr>Cys_exon6 p.G|y12Cys G12C WT WT WT WT WT 163__A>THis>Leu_exon5 p. G|y12Cys (G12C) WT WT WT WT WT 96_G>T_VaI>Phe_exon5 158_C>G_ex0n7 91 80_SNP_A>G_R-Arg_exon6, . 101_A>G_G|u>G|y_exon7, p. G|y12Cys c.2184+19G>R 106_T>A_Ser>Thr_exon7 Non Codant rs17337107 142_C_>Gexon7 ----—pLS739Ala743deexon20 c.2156G>C p. G|y719A|a ) VAR_026086 exon 18 c.2303G>T p. Ser768lle (S768I) WT AGVGD:Class C65 exon 20 WT WT WT WT 94 c.34G>K p. G|y12CysW G12C c.34G>K p. G|y12Cys c. 2184+19G>R (G12C) Non Codant rs17337107 WT WT WT W_T>C_Tyr>HiS_exon6 103 c.2184+19G>R Non Codant rs17337107 c.35G>K p. G|y12Va| G12V WT WT WT WT WT 70_C>T_Arg>Trp_exon7 71_SNP_G>A_exon7 108 WT 26de|etion_T_exon9 111 c.2313_2314in59bp (CCCCAGGCG) p.Pr0772_Hi5773insGlnAIaPro_eXpn WT 20 WT WT WT WT p.G|y12Cys (G12C) WT WT WT WT WT 115 c.2184+19G>R WT Non Codant rs17337107 WT WT WT WT WT 99 ->G| _exon5 c.183A>W p.Gln61 His (Q61 H) 92_C>T_exon5, rs17851045 104_C<T_exon5, exon 3 WT WT WT WT 128_C>G_Ser>Arg_exon8, Table 13: Calculated scores Wherein P means t, (1) refers to a score calculated based on mRNA expression, (2) refers to a score calculated based on mutation and mRNA expression, (3) refers to a score calculated based on mutation, mRNA expression, and miRNA expression, and (4) refers to a score ated based on mutation, mRNA expression, miRNA expression and Copy Number Variation. 8 4 P PLK_ URKA_Kinesins ANGIOGENESIS ANGIOPOIETINS 1 2 2 2 --—_-—-ElEl5 5 3mm1 4 Ifl-I—__-lfl8 8 EIE__-—Elflfl8 8 8 Hnn8 8 7 5 5 8 mum—”n2 2 8mm1 8 8 11 0 10 12 --—_-—-ElEl5 5 18 III—mu1 1 14 Elfl__—Ellln10 10 1 4 18 ElEl__—El-Elll10 10 17 --—_-—flElEl8 8 18 ---__l_-El7 7 18 --—_-E-=IEI8 8 [HI—mun7 7 21 l__-—--l"fl8 8 22nun—m5 5 281010 24mm1 2 m 1 1 2 uua mm 28 ---—2 2 1 003mV 5 003mV 31 III— 1 1 32 ---—5 5 %M% manmannun 8m669433m8 7m589646m5 89646m5 36 anan 1 1 0 1 0 1 0 w33 uun 9 10--—62175mm59363_/4wnlV 5003 m 4 4 4 4 2 41 ---—5 5 3 3 .5 42 8m669433m8047525m45719687442153937148396211 m414m73347135 m414m73347135 %M% manmanman 576 W567 1 1 446 5 5 3 2 2 7 10--—47100 47100 w uuu 49 II- 5 5 50 III51 1 51 III3 &%M%% mannagunmanmanna m6mm3739 57 ---1O4 58 10 In 9 59 “10 m 1324700221 an n 0d 0221 61 an 3 62 Im— w nnn 8 87776711449672263 64 III—2 2 1 1 _/ %%m manmanman 317m49m6mm8711 4 35512 35512 1 114 2 2 oO15oOOu_/;.n|u3;.nlV 5;.n|V4_5_/10u6oo_/4421539.371400396211100150097wnluoownlV .5832.5m5672oo7776711449672263742114oo1_/000u5;.n|u2;.n|V 817 u2wnlV 42mm782 42mm782 74m6mw514m733461367582885m9142488221884641272633mm7927 W84663521m9247889884255492123757422m52m35938m7m11m761 m8m663521m9247889884255492m23757422m5mm35938m7m11m761 m9m763632m8246879894346382m23767433m5m925839m8m11m851 mnmn“nunnmnnnnumnnnnmnnnnnmnnnunnnmmnmnnmnmnmnmnmmnmn mnnn“mannmnnnnannmnnmnannnnnnnunnnmnnnnmnnnnnnnmnnnnn mnnn“mannmnnnnannmnnmnannnnnnnunnnmnnnnmnnnnnnnmnnnnn 1093780516927184940435367934569005476827826628389044463 10937000.516003710049404352679345600005476927826628399034463 80 --_ 71 2 2 417 41;.nlV 1 82 --_11 3 3 10 10 7 1 1 1 84 III5 5 5 4 4 85 III4 4 5 2 8888 6789 sunm4sunm4-4nnm 4003 4003 90 a 0 91 ---—2 92 I“— 93“—71421 71421 9945 ananan 1 1 96 ---—7 99 789m man“nun“nnnn 01 “Ell! 253472 253472 %M%%W% 1 4mmna 8W5 8W5 1 1 0 75300 75300 1111111111 4;.nlu44;.nlu_/oo;.n|V 4;.nlu44;.nlu_/oo;.n|V 1 1 22 9012345678901 .n-nnnnannmnaannnnn 4mnnnnnnamnmnmamnnnn 79734mmm61m125694mm253284m392m156228 439272m27719262397m5958762368646m59275 439272m27719262397m5958762368646m59275 429465m2881924318996m6854335763493m387 00001924318896m68543357634m3m377 1730512289554592033282179174.0819914307476206 5 982377582m691431m14236299m66543753m44m68955 936400461526W46379677537m4W8974963279139 936400461526W46379677537m4W8974963279139 1mwmwOo454005726279452795764_.G_/;.n|u2wnluoo953;.nlu741r0914;.nlV nnmmumannananannaaannannnnnmnmnnmnmnnnnnnnm nnmammannnmanmmmnnannunnnmnmnmnnnmnmnmnnnmn annnmanmmmnnannunnnmnmnmnnnmnmnmnnnmn mm522299554592033283179174.08198143074763061 nmnnnmmnnmmnnmmnnmmn IMMUNO-Modulator P|3K 8 8 8 1 46954 1 7004762 7004652 1 m7 2 21 W823 3 22 ”--5 1 7 1 1 26 _m-4 5 10 7 7 5 5 9565453858mmm98972214m797 4 4 m m 669 ananmmnunnmmmnnnnnmnnmnnnmnmn 37 mmn 3 3 1 1 3W1 man 1m222866121m465988567739181781 .364223200629939142mw6oo3m6oo470051wnlull_/27_/269_.G;.n|u6oo;.n|u647557;.nlV 3645272W528oo3oo132W672m874694191726616m5m98m536449mm79 9565453858mmm98972214m797m6697184681m159561000057006.6949 6001 2 4 4 a 3 8 3 3 n 756mV 700 99 7m 4 9 nunnmmnnnnmnnnnnmnnmn anaammaunnmmmnnnannnnmnnnmnnnununmnnmnnnnnmmnnnnnnnmn umnnanamnnnnnnnaannnnannnmnmmmnunnmnmmnnnnnmmnnnmnmnn 0039759551000092725544002576231m352628m25m861693m74118369 740043.loo329mwgz527656mm300673440027.3537m2_.G;.HIV96;|496;.nlu64110026;.nlV 640073700329ng2427656mm39673440027.3537m2_.G;.HIV96;|49_.G;.nlu64110026;.nlV 2614530014400934oo4W652mm4636157648288673176739531 4422522614530014400934oo4W652mm4636157648288673176739531 EnflmmnmmnHEnEmumum"MEEmumum“Innmnnmmflflnflmnflmflmmmnflmmfl 61 1 1 5 1 5 3 3 10 8 10 1o 10 u- 62 3 3 2 2 8 8 8 8 8 63 8 8 ——nnn9 9 9 1 1 64 1 1_-5 3 5 5 5 3 3 3 8 8 an 65 7 7 1 1 1 9 9 m 88 mm-10 7 7 3 3-_-- 67 5 5 _-—---—--4 4 1 1 1 68 8 8 ——nnn9 8 8 8 8 89m- 0 70 112 1 1 1 1 3 2 2 1 1 71 _7 7 n—n-n7 7 7 10 10 72 2 2_-3 8 5 3 3 3 5 2 [6|- 73 8 8 1o 10 -_--8E 9 9 -- 74 1o 10 _—--I§I8 9 598132221 298189141147511778 8 -- 75 3 3 __flfl-3 1100 I“ 76 1 1 _--2 3 8 an 77 mm_---4 2 9 II- 78_--2 0 10 n7n 79 1 4 8 3 2 80 __--fl-3 2 1 0 --10 1 0 ___fl--5 4 3 3 I5 3 3 3 -- 83 __-_1---8 7 5 5 an 84 ___fl--2 10 10 1O In 85 __E5—£21g2 8 8 8 II“ 88 mm-2 3 2 3 2 2 00 1“-I]- 87”mm4 5 5 an 88 4 4 4 4-10 10 10 7 7 In“ 6 6 6 In 89 3 3 1 3 2 4 4 III-fl—6 8 8 14m14750m778 90 7 7 7 8E8 9 1 0 3 -2 912_n——--nnn6 92 92 5—n—“_-n- 93 7—-—--n9 9 9 [6]- 941__---1 1 95 1__---10 10 110 98 3_-—---4 1 110 32853 an--I- 97 m_-m---1 1 1 5-- 98 mm“8 5 “EE8 8 8 3-- 99 3__--n9 7 7 I- 11111111111111002__--- 5 4 4 1 an 012__---10 10 9 -- 10 10 an 032__---7 7 7 In 04m10 10 I] 9 9 9 8 8 an- 1 4 4 an 05 --75 9 9 n- 083__flfl-44 4 -- 072__---7 5 5 an 08 __-_8---10 7 7 an 09murm-5 5 5 an __-_3---7 8 8 8--3:0288297599 111__---5 4 4 2mm 12 __-_1---1 1 1 10““ 13 __-_---4 3 3 9232853539028829759962011 1-- -5 annannnnannnnnnnn I!I!nmnnnnnnn I]I] -3 “Immunnnnnnu 1 2 4 1 3 1 2 3 2 mn_4 D. mTOR AKT Modulators mF Telomerase AntlapoptOSIs PTEN MTKPT RAS 1234567009 10 mmm42m2 10 6 mm4292 10 34210 0 .554 1111111111 012345670090 1 1 0 0 1002;.nlV nlV 13441 1 1 2 8 0 0 2345 2 458m45 7m182457m45 5111.527 150 0 28 0 444678724841635519392364675589 77 333345 9m41mm mm41mm 140 0 W218m3 W218m3 0 373m974486 444678724841635519392364675589m373m974486 522730041232775772m4531m98m649m83559m95186 685m24475mm8m511212563325892934697396m855 673m284659m7m6112223433369m2m25690020079745 748868245121647m257m1849m73479m2297341663 88682m512m647m257m18m9m734m9mm297341mm3 73m284659m7m6112223433369m2m25690020079745 342m985737m44315311m7369m5886684937979855 .510 0 .5 150059929421372744708551099299891102874462 43 an 7635 1 5743 1 455 nan 21770063930000.3400 11421778639388.3400 4004_/364401674240016001;.nlvwnlV 412752328mm8875m7m6m13 953 1 1mm" 39 1 0 m 392mm 1 0 “4 004006165574731m9m9139m584m3595m6312121 34 mnmmnnm 7 nus "flmm 9m1161954287m1m61 953m397392mm29m1161954287m1m61 5258m984938m19m9232758387m3931 99963128281141166m667711349833 311661429mm7876m6m891530000966149591131165945582155m743 500632m76653111931117W8383562765m88m5m9743m46929524279 5863mm76653111931117W838356276mm88m5m9743m4692952m27m 311661429mm7876m6m891530000966149591131165945582155m743 65889693269m2 30047208883371206614005561500373205m35390226466137054611111111 1 0 nn 9265m28m7m4m185521867265295 9265m28m7m4m185521867265295 9215626m6147124731655669367 25 2 4W3 234 0 34 aInna 7 2 7 0 1 05 35113 35 00 1 0 0 1 8 8 5517100 55m7m m 0 669442377979483m84479m75 4843277985m482m84359m77 4332mm52m956m891938554671498 m52m9m6m891938m5467149m 985m482m84359m77 2m77344725616m74122481m2278 937188409176062563765784934 ----1 3 4 2 3 1 3 4 2 m3 4 1 2 F WNT PARP HDAC JAK_STAT HEDGEHOG 6 4 4 WO 93212 24 unn_--n9 9 10 8 1o 9 1o 10 1 1 n 28 n-_nnn7 7 I] 27 1---—---n—9 9 28 10 2 2 I! 29 3 8 5 5 4 110 10 10 “II 8 1o 9 9 10 2 2 I! 31 -”I7 9 1o 10 10“10 10 32 “MEI—I“—3 2 33 1--I_---—-8 8 34 4 I!” 9 9 10 1o 10 Ill]- 2 4 n 10 "I! 4 4 1o 10 8 flfl_-4 38 10 --—---n3 3 I] 37 3 10 4 9 9 8 flfl_- 38 10 ---—---—ll3 3 39 nun-I—nnn—8 7 40 1---—----—2 2 41 m-8 4 1 1 5 “fl- 4 4 I! 42 “In“ 5 3 3 3 410 10 [6] 43 “nun—"n 44 4 8 4 1 1 2---—- 45 1 I! 48 2 ---—----—69928286529591933953481 86529591933953481 47 5 10 1o 8 8 8 an- 10 10n 48 2m—”—- 1 49 3 “El 9 7 1o 10 7 “I‘ll! 8n 50mm 8n 51 5 III—null 52 fl"_---—- 53 10 3 8 8 8 8 nn_- 54 5 --—---I=I 8 fl 55 “I4 4 3 3 8 flfl_- 58 unn- 5 9 7 8 9 an- 17831674956241 8 57 “III—“fl10 11783167585624109868203994941 0067176700432 7nI!4 58 4m—”—-9 59 “nun—“In—8 60 1 10 1 2 2 6 --_-1 2 81man“5 1 82 5 --—---El2 1o 10 n 83 10 10 1 7 7 fl 84 nunI_---3 1010- 65 Elm—III]9 9 9 n 88 1 m—”—-9 4 87 2 2 2 1 1 1 88 -“l=l 1 8 5 5 2 ---l_ 69 2 4 3 70 3 1 71 “_l=ll=l10 10 8 8 72 “In—II-3 3 3 3 73 “III—II-4 4 1o 10- 74 2 --l=_---—llo o 75 10“—u—Ifln4 3 78 2 1 9 9 9 8 nn_- 77 5 1 6 4 4 1 “I! 6 78 5 fl” 7 8 6 6 1 2 79 10 10 80 1 ---—--I§I 9 I] 82 “II—“fl 6 [6| 83 “nun—“In—3 84 flflfl- 3 3 3 3 9 85 -fl_---EI—-7 86 “HI9 4 7 7 8 “In 9 87 ---—---fl 5 [6] 88 2 2 8 8 8 10nn_-62m946357951 89 flflfl- 5 7 10 10 7 l 9O 1---—-flflfl—1 91 -“l=l 5 2 3 3 4 nn_- 92 In“10 3 6 6 7M1 1 6 1361 [6| 93 2“W 94 7 ---4 1 1 1 8 flfl_- 95 3 ---7 9 7 7 10nn_- 96 4 --—---—2 97 -El-—--—nfl-127 98 2 ---—-_ 99 7 ---1 4 4 4 8 7 [6| 1111111111111111111111 00 flflfl- 9 8 9 8 “El- 10 1 01 7 02 5 ---1 10 9 10 007151672275997408134861231 [6] 03 32 --El4 7 8 8 10 10 04-fl_---1 10 47.01767 I! 05fl--_7 77 7 8 4 III3 3 5 6 7 -7 06 ----—flflfl—fl7 7 9 6 5 07fl-II—n—I-4 4 5 4 97 1 1 W ---—-4 4 5 5 6 0 53 5 1111111111 90123456789 nunnnnnnnmnzIII—I-fl—I599 57 57 57 nnnnnnnnnnz unnnnnnnngfl—---—-7 8 5 5 2m an1 9 8 9 3 1 0 6 7 69 "a 3 1 810 an1 8 7 5 4 8 5 6 4 3 5 7 9 fl—EEI—I71 0 1 0 1723998567988963 4 4 1 0 n—---—-99 8 4 5 5 7 8 4 4 7 6 8 38 5 5 7 --—“n1 1 0 I! m---_--n—-2 2 2 3 2 5 110071516722759974081348612318066155633459487009 9 176775062m80375m48834 883 3 21 unn_nnn—-9 9 9 4 5 -------------1 2 4 DNA REPAIR NOTCH OTHERS PDL1 CTLA4 nunmmnnnnnn“n 6 0 1 1 1 0123456789 nunnnmnnnmnmnmngnnnn nunnnmnnnmnmnmn 815314181974845447 m26726274814151332 m26726274814151332 0300750020061 1 10 1 10 21 --—3 mBM% m7 8m693m31 8m693m31 0 m um 1 w m65oo1 0 33 4 4 3 5 %%w%w 0 %M%%M%mwm mnnnnnnngnnnnnnnmngnnnnn mnnnnnmunnmnnnsunnmnnnnngnnnnn W8523824296769 mwmw/I4772594384;.nlV mwmw/I4772594384;.nlV 0 52 --— wM%%w 0069672357 9100433394 9100433394 58 --—2 2 2 2 2 96914m4521599m92168m791686862m34m3379835731847m156693 96914m4521599m92168m791686862m34m3379835731847m156693 9400654175636m9347m22892m685682184735927m69mm1m6626198 9400654175636m9347m22892m685682184735927m69mm1m6626198 75m6m8433476m3215761997958553m545673m34m5188943614182 82871mm97446975mm7m37555417295382667369m74632198 874469759070375554172953002667368074632197 111 11 w aa m w 4700 60071 7 % amaama 27-7 8W2 456 5 5 0d wm mmmaaammaa 31 ma 95 10 %m%9 mamamama 1134 000 123 maa 29 45695694729m52 5694729m52 maammmmm- 00 789085m3 7 1146126145659194001349136841487598467122382235009312751 o9 mamm- 5 m6 m3 aaaaammmaaaammama mmaamaaamammammaaaaaamaaammaaam aaaammaamamaaammaaaaaammaamaaamammaamaaaaaamaaammaaam 9824mm13132865m152357232293m58m64m6244574597897118867 9824mm13132865m152357232293m58m64m6244574597897118867 6327737W3882733m43m91555m112654744712459.351129361009001 6327737W3882733m43m91555m112654744712459.351129361009001 223344369m92438m52721126673466949581128752886m5817677 aaaammaaaaaamaaaaamammaaamamaaamaammmaamaaaaaaaammamm maammmamaaaaaamaamammmamamaaammammamaamamaamaaamaaaaa maammmamaaaaaamaamammmamamaaammammamaamamaamaaamaaaaa 61271456591040013491368414875984681223822365m9312751 4633m46m73 82937 00175482937 173562754wn|V 173562754wn|V 8444295m85 8444295m85 248119mm790 m57m73 m7

Claims (15)

1. A method for determining in a patient having a cancer a classification of intervention points according to the intervention points activation status, wherein 5 - the intervention points comprise the group consisting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, rase, IGF/glycolysis, Wnt, PARP, HDAC, JAK-STAT, Hedgehog, NOTCH pathway, DNA Repair, RET, ALK, ROS1 and UB1, or subgroup thereof of at least 10 10 intervention ; and the genes of each intervention point are d according to Table 1 or 9; - the method comprises - characterizing a tumor sample in ison to a normal histologically matched sample from the same patient, including 15 - for each y of the group or up of intervention points, determining the mRNA expression level of the genes of the intervention point as disclosed in Table 1 or 9, y determining a fold change of mRNA expression of tumor vs normal, (referred as mRNA TvN fold change); 20 - wholly or partially cing genes of Table 1 or 9, thereby identifying the presence of activating mutation in the tumor sample; - for each intervention point of the group or subgroup of intervention points, determining the level of miRNAs of the 25 genes of the intervention point as disclosed in Table 11, thereby determining a fold change of miRNAs level of tumor vs normal, (referred as miRNA TvN fold change); - -calculating a mean miRNAs fold change for each gene as the average of the miRNA TvN fold changes for the gene; 30 - calculating a corrected mRNA TvN fold change by dividing the mRNA fold change Tumor versus Normal of the gene (mRNA TvN fold change) by the mean fold change for the miRNAs of the gene (mean miRNA TvN fold change), the ted mRNA TvN fold change of the gene being used to calculate the arithmetic mean of the mRNA TvN fold changes of the genes for each intervention point; - calculating a score for each pathway based on the characterization 5 data, wherein - if, in the tumor sample, the ce of an ting mutation of a gene of an intervention point is detected, then a maximal score is given to the ention point; - a score is calculated based on the arithmetic mean of the 10 mRNA TvN fold changes of the genes for each intervention point of the group or subgroup of intervention points, provided that the mRNA TvN fold change of a gene is taken into consideration only if its value is at least 1.3; and - the score of each intervention point of the group or subgroup 15 of intervention points is either a. the sum of the score due to the presence of an activating mutation and the score calculated by the average of the mRNA TvN fold changes; or b. the score due to the presence of an activating mutation 20 if there is a mutation or the score calculated based on the arithmetic mean of the mRNA TvN fold changes in absence of mutation; and - classifying the intervention points according to the calculated scores. 25

2. The method according to claim 1, n the genes of Table 10 are sequenced for detecting the presence of mutations as defined in Table 10 and p53 gene is sequenced.

3. The method according to claim 1 or 2, wherein, for each ention point of the 30 group or subgroup of intervention points, the method comprises determining the miRNAs level of the genes of the pathway as disclosed in Table 11.

4. The method according to any one of claims 1-3, n the score is from 1 to 10 and the l score given to the ention point is 10.

5. The method according to claim 3 or 4, wherein the level of miRNAs is determined and 5 used to calculate a corrected mRNA TvN fold change for the genes of the following intervention points: mTOR-AKT-PTEN, RAS, ERK, PI3K and Immune Modulators.

6. The method according to any one of claims 1-5, wherein for each intervention point of the group or subgroup of intervention points, the method comprises determining 10 the copy number variation of the genes of the pathway as disclosed in Table 1 or 9, thereby determining a tumor vs normal fold change for the amplified genes.

7. The method according to any one of claims 1-6, wherein the subgroup of intervention points consists in the following group: Her, CDK4,6, PLK/AURK/Kinesins, 15 Angiogenesis, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, IGF/glycolysis, Wnt, PARP, and DNA Repair.

8. The method according to any one of claims 1-7, wherein it further comprise selecting a group of three activated or disturbed intervention points in a patient having a 20 cancer, n three intervention points are selected among the intervention points having the highest scores.

9. The method according to claim 8, wherein the three intervention points are the three intervention points having the highest scores.

10. A method for selecting a combination of three drugs useful for treating a patient having a cancer, wherein a group of three activated or disturbed ention points are selected by the method of claim 8 or 9 and a drug is selected for each or disturbed intervention point, thereby providing a combination of three drugs.

11. Use of a kit for classifying pathways according to the intervention points tion status according to the method of claim 1, wherein the kit comprises means for measuring the mRNA expression level of the genes of Table 1 or 9 for intervention points sing the group ting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti- sis, FGF, mTOR, Ras/Raf, rase, IGF/glycolysis, Wnt, PARP, HDAC, JAKSTAT , Hedgehog, NOTCH pathway, DNA Repair, RET, ALK, ROS1 and UB1, or subgroup 5 thereof of at least 10 intervention points.

12. The use of claim 11, wherein the kit further ses means for detecting the mutations of Table 10. 10

13. The use of claim 11 or 12, wherein the kit further comprises means for measuring the miRNA level of miRNA of Table 11 for intervention points comprising the group ting of the HER, CDK4,6, PLK/AURK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti-Apoptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, JAK-STAT, Hedgehog, NOTCH, DNA 15 Repair, RET, ALK, ROS1 and UB1, or subgroup f of at least 10 intervention points.

14. The use of any one of claims 11-13, wherein the kit further comprises means for determining the copy number variation of the genes of Table 1 or 9 for pathways 20 comprising the group consisting of the HER, CDK4,6, RK/Kinesins, Angiogenesis, Angiopoietins, Immune Modulators, PI3K, MET, MEK, ERK, Anti- Apoptosis, FGF, mTOR, Ras/Raf, Telomerase, IGF/glycolysis, Wnt, PARP, HDAC, JAKSTAT , Hedgehog, NOTCH, DNA Repair, RET, ALK, ROS1 and UB1, or up thereof of at least 10 intervention points.

15. The method of claim 1, substantially as herein described with reference to any one of the Examples and/or