WO2018146148A1

WO2018146148A1 - A method for predicting the response to checkpoint blockade cancer immunotherapy

Info

Publication number: WO2018146148A1
Application number: PCT/EP2018/053073
Authority: WO
Inventors: Jérôme GALON; Bernhard Mlecnik; Gabriela BINDEA
Original assignee: Assistance Publique Hopitaux de Paris APHP; Institut National de la Sante et de la Recherche Medicale INSERM; Universite Paris Descartes; Universite Paris Diderot Paris 7; Sorbonne Universite
Current assignee: Assistance Publique Hopitaux de Paris APHP; Institut National de la Sante et de la Recherche Medicale INSERM; Universite Paris Descartes; Universite Paris Diderot Paris 7; Sorbonne Universite
Priority date: 2017-02-07
Filing date: 2018-02-07
Publication date: 2018-08-16
Anticipated expiration: 2019-08-07

Abstract

Blockade of immune checkpoints is one of the most promising approaches for activating therapeutic antitumor immunity. However, the overall benefits of checkpoint blockade cancer immunotherapy vary among individuals. The present inventors have indeed demonstrated that MET-mutated patients have a better adaptive immune response than non-MET-mutated patients. Accordingly, MET-mutated patients are more likely to respond to a checkpoint blockade cancer. Accordingly, the present invention relates to a method for predicting the response of a patient suffering from cancer to a checkpoint blockade cancer immunotherapy, by determining if the MET gene is mutated in a tumor sample of said patient, wherein a mutation of the MET gene is predictive of a response to the checkpoint blockade cancer immunotherapy.

Description

A METHOD FOR PREDICTING THE RESPONSE TO CHECKPOINT BLOCKADE

CANCER IMMUNOTHERAPY

FIELD OF THE INVENTION

The present invention relates to a method for predicting the response of a patient to checkpoint blockade cancer immunotherapy. BACKGROUND OF THE INVENTION

As explained by Pardoll (Nat Rev Cancer. 2012 Mar 22;12(4):252-64), among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors.

However, the overall benefits of checkpoint blockade cancer immunotherapy vary among individuals. It is therefore necessary to define reliable predictive biomarkers in an effort to better identify patients who are most likely to benefit from such a treatment. SUMMARY AND DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to a method for predicting the response of a patient suffering from cancer to a checkpoint blockade cancer immunotherapy, said method comprising the step of determining if a MET gene is mutated in a tumor sample of said patient, wherein a mutation of the MET gene is predictive of a response to the checkpoint blockade cancer immunotherapy. The present invention also relates to a checkpoint blockade cancer immunotherapy agent for use in a method for treating a patient which has been selected to have a tumor cell which harbors a mutated MET gene.

The present inventors have indeed demonstrated that MET-mutated patients have a better adaptive immune response than non-MET-mutated patients. Accordingly, MET- mutated patients are more likely to respond to a checkpoint blockade cancer immunotherapy (i.e. they are good candidates for this type of therapy).

The method according to the present invention is thus particularly suitable for discriminating responder from non-responder. As used herein the term "responder" refers to a patient that will achieve a response, i.e. a patient where the cancer is eradicated, reduced or stabilized. A non-responder or refractory patient includes patients for whom the cancer does not show reduction or stabilization after the immune checkpoint therapy.

The present invention also relates to a method for treating a patient suffering from cancer, wherein said method comprises the steps of:

-determining if a MET gene is mutated in a tumour sample of said patient; and

-administering to said patient a checkpoint blockade cancer immunotherapy agent if said patient has a tumour cell which harbors a mutated MET gene. The MET gene is frequently mutated in many human cancers. The official full name of MET is MET proto-oncogene, receptor tyrosine kinase. MET is also known as HGFR; AUTS9; RCCP2; c-Met; or DFNB97. The proto-oncogene MET product is the hepatocyte growth factor receptor. MET is a tyrosine-kinase receptor.

The present invention provides methods of determining whether or not a cancer patient has a mutated MET gene (point mutations, deletions, or additions, including the absence of the gene by complete deletion and promoter silencing) and thereby determining whether or not the patient is a candidate for checkpoint blockade cancer immunotherapy. The determination involves detecting MET DNA, RNA, or protein and determining whether or not the molecule is mutated, thereby determining whether or not the gene is mutated. Any method known to those of skill in the art to detect mutations can be used, including PCR (e.g., Taqman), sequencing techniques, Southern, western, and northern blots, microarrays, immunohistochemical techniques, ELISA, mass spectroscopy, enzymatic, binding or functional assays, and the like. Typically, the patient suffering from cancer is a mammalian, preferably a human.

The cancer may be a solid cancer or a cancer affecting the blood. In a preferred embodiment, the cancer is a solid cancer.

In a further embodiment, the cancer is a solid cancer affecting one of the organs selected from the group consisting of colon, rectum, skin, endometrium, lung, uterus, liver, kidney, esophagus, stomach, bladder, pancreas, cervix, brain, ovary, breast, head and neck region, testis, prostate and the thyroid gland.

Particularly, in a most preferred embodiment, the cancer is a solid cancer affecting an organ selected from the group consisting of skin, endometrium, lung, uterus and liver. These cancers are those in which MET mutations are the most frequently observed in patients; i.e., in which the percentage of MET-mutated patients among a cohort is higher than 3% (see Example below).

Typically the tumor sample of the patient may be obtained by biopsy or resection. The biopsy technique applied will depend on the tissue type to be evaluated, the size and type of the tumor, among other factors. Representative biopsy techniques include, but are not limited to, excisional biopsy, incisional biopsy, needle biopsy, surgical biopsy, and bone marrow biopsy. An "excisional biopsy" refers to the removal of an entire tumor mass with a small margin of normal tissue surrounding it. An "incisional biopsy" refers to the removal of a wedge of tissue that includes a cross-sectional diameter of the tumor. As used herein the term "immune checkpoint protein" has its general meaning in the art and refers to a molecule that is expressed by T cells in that either turn up a signal (stimulatory checkpoint molecules) or turn down a signal (inhibitory checkpoint molecules). Immune checkpoint molecules are recognized in the art to constitute immune checkpoint pathways similar to the CTLA-4 and PD-1 dependent pathways (see e.g. Pardoll, 2012. Nature Rev Cancer 12:252-264; Mellman et al., 201 1 . Nature 480:480- 489). Examples of inhibitory checkpoint molecules include A2AR, B7-H3, B7- H4, BTLA, CTLA-4, CD277, IDO, KIR, PD-1 , LAG-3, TIM-3 TIGIT and VISTA. The Adenosine A2A receptor (A2AR) is regarded as an important checkpoint in cancer therapy because adenosine in the immune microenvironment, leading to the activation of the A2a receptor, is negative immune feedback loop and the tumor microenvironment has relatively high concentrations of adenosine. B7-H3, also called CD276, was originally understood to be a co-stimulatory molecule but is now regarded as co- inhibitory. B7-H4, also called VTCN1 , is expressed by tumor cells and tumor-associated macrophages and plays a role in tumour escape. B and T Lymphocyte Attenuator (BTLA) and also called CD272, has HVEM (Herpesvirus Entry Mediator) as its ligand. Surface expression of BTLA is gradually downregulated during differentiation of human CD8+ T cells from the naive to effector cell phenotype, however tumor-specific human CD8+ T cells express high levels of BTLA. CTLA-4, Cytotoxic T-Lymphocyte-Associated protein 4 and also called CD152. Expression of CTLA-4 on Treg cells serves to control T cell proliferation. IDO1 , Indoleamine 2,3-dioxygenase 1 , is a tryptophan catabolic enzyme. A related immune-inhibitory enzymes. Another important molecule is TDO, tryptophan 2,3-dioxygenase. IDO1 is known to suppress T and NK cells, generate and activate Tregs and myeloid-derived suppressor cells, and promote tumour angiogenesis. KIR, Killer-cell Immunoglobulin-like Receptor, is a receptor for MHC Class I molecules on Natural Killer cells. LAG3, Lymphocyte Activation Gene-3, works to suppress an immune response by action to Tregs as well as direct effects on CD8+ T cells. PD-1 , Programmed Death 1 (PD-1 ) receptor, has two ligands, PD-L1 and PD-L2. This checkpoint is the target of Merck & Co.'s melanoma drug Keytruda, which gained FDA approval in September 2014. An advantage of targeting PD-1 is that it can restore immune function in the tumor microenvironment. TIM-3, short for T-cell Immunoglobulin domain and Mucin domain 3, expresses on activated human CD4+ T cells and regulates Th1 and Th17 cytokines. TIM-3 acts as a negative regulator of Th1/Tc1 function by triggering cell death upon interaction with its ligand, galectin-9. VISTA. Short for V-domain Ig suppressor of T cell activation, VISTA is primarily expressed on hematopoietic cells so that consistent expression of VISTA on leukocytes within tumors may allow VISTA blockade to be effective across a broad range of solid tumors. TIGIT (also called T cell immunoreceptor with Ig and ITIM domains) is an immune receptor on some percentage of T cells and Natural Killer Cells(NK).TIGIT inhibits T cell activation in vivo.

As used herein, the expression " checkpoint blockade cancer immunotherapy agent" or "immune checkpoint inhibitor" (both expressions will be used interchangeably) has its general meaning in the art and refers to any compound inhibiting the function of an immune inhibitory checkpoint protein. Inhibition includes reduction of function and full blockade. Preferred immune checkpoint inhibitors are antibodies that specifically recognize immune checkpoint proteins. A number of immune checkpoint inhibitors are known and in analogy of these known immune checkpoint protein inhibitors, alternative immune checkpoint inhibitors may be developed in the (near) future. The immune checkpoint inhibitors include peptides, antibodies, nucleic acid molecules and small molecules. In particular, the immune checkpoint inhibitor of the present invention is administered for enhancing the proliferation, migration, persistence and/or cytoxic activity of CD8+ T cells in the subject and in particular the tumor-infiltrating of CD8+ T cells of the subject. As used herein "CD8+ T cells" has its general meaning in the art and refers to a subset of T cells which express CD8 on their surface. They are MHC class l-restricted, and function as cytotoxic T cells. "CD8+ T cells" are also called CD8+ T cells are called cytotoxic T lymphocytes (CTL), T-killer cell, cytolytic T cells, CD8+ T cells or killer T cells. CD8 antigens are members of the immunoglobulin supergene family and are associative recognition elements in major histocompatibility complex class l-restricted interactions. The ability of the immune checkpoint inhibitor to enhance T CD8 cell killing activity may be determined by any assay well known in the art. Typically said assay is an in vitro assay wherein CD8+ T cells are brought into contact with target cells (e.g. target cells that are recognized and/or lysed by CD8+ T cells). For example, the immune checkpoint inhibitor of the present invention can be selected for the ability to increase specific lysis by CD8+ T cells by more than about 20%, preferably with at least about 30%, at least about 40%, at least about 50%, or more of the specific lysis obtained at the same effector: target cell ratio with CD8+ T cells or CD8 T cell lines that are contacted by the immune checkpoint inhibitor of the present invention, Examples of protocols for classical cytotoxicity assays are conventional.

Typically, the checkpoint blockade cancer immunotherapy agent is an agent which blocks an immunosuppressive receptor expressed by activated T lymphocytes, such as cytotoxic T lymphocyte-associated protein 4 (CTLA4) and programmed cell death 1 (PDCD1 , best known as PD-1 ), or by NK cells, like various members of the killer cell immunoglobulin-like receptor (KIR) family, or an agent which blocks the principal ligands of these receptors, such as PD-1 ligand CD274 (best known as PD-L1 or B7-H1 ).

Typically, the checkpoint blockade cancer immunotherapy agent is an antibody. In some embodiments, the checkpoint blockade cancer immunotherapy agent is an antibody selected from the group consisting of anti-CTLA4 antibodies, anti-PD1 antibodies, anti-PDL1 antibodies, anti-PDL2 antibodies, anti-TIM-3 antibodies, anti- LAG3 antibodies, anti-IDO1 antibodies, anti-TIGIT antibodies, anti-B7H3 antibodies, anti-B7H4 antibodies, anti-BTLA antibodies, and anti-B7H6 antibodies.

Examples of anti-CTLA-4 antibodies are described in US Patent Nos: 5,81 1 ,097; 5,81 1 ,097; 5,855,887; 6,051 ,227; 6,207,157; 6,682,736; 6,984,720; and 7,605,238. One anti-CDLA-4 antibody is tremelimumab, (ticilimumab, CP-675,206). In some embodiments, the anti-CTLA-4 antibody is ipilimumab (also known as 10D1 , MDX- D010) a fully human monoclonal IgG antibody that binds to CTLA-4.

Examples of PD-1 and PD-L1 antibodies are described in US Patent Nos. 7,488,802; 7,943,743; 8,008,449; 8,168,757; 8,217,149, and PCT Published Patent Application Nos: WO03042402, WO2008156712, WO201008941 1 , WO2010036959, WO201 1066342, WO201 1 159877, WO201 1082400, and WO201 1 161699. In some embodiments, the PD-1 blockers include anti-PD-L1 antibodies. In certain other embodiments the PD-1 blockers include anti-PD-1 antibodies and similar binding proteins such as nivolumab (MDX 1 106, BMS 936558, ONO 4538), a fully human lgG4 antibody that binds to and blocks the activation of PD-1 by its ligands PD-LI and PD-L2; lambrolizumab (MK-3475 or SCH 900475), a humanized monoclonal lgG4 antibody against PD-1 ; CT-01 1 a humanized antibody that binds PD-1 ; AMP-224 is a fusion protein of B7-DC; an antibody Fc portion; BMS-936559 (MDX- 1 105-01 ) for PD-L1 (B7- H1 ) blockade.

Other immune-checkpoint inhibitors include lymphocyte activation gene-3 (LAG-3) inhibitors, such as IMP321 , a soluble Ig fusion protein (Brignone et al., 2007, J. Immunol. 179:4202-421 1 ).

Other immune-checkpoint inhibitors include B7 inhibitors, such as B7-H3 and B7-H4 inhibitors. In particular, the anti-B7-H3 antibody MGA271 (Loo et al., 2012, Clin. Cancer Res. July 15 (18) 3834).

Also included are TIM3 (T-cell immunoglobulin domain and mucin domain 3) inhibitors (Fourcade et al., 2010, J. Exp. Med. 207:2175-86 and Sakuishi et al., 2010, J. Exp. Med. 207:2187-94). As used herein, the term "TIM-3" has its general meaning in the art and refers to T cell immunoglobulin and mucin domain-containing molecule 3. The natural ligand of TIM-3 is galectin 9 (Gal9). Accordingly, the term "TIM-3 inhibitor" as used herein refers to a compound, substance or composition that can inhibit the function of TIM-3. For example, the inhibitor can inhibit the expression or activity of TIM- 3, modulate or block the TIM-3 signaling pathway and/or block the binding of TIM-3 to galectin-9. Antibodies having specificity for TIM-3 are well known in the art and typically those described in WO201 1 155607, WO2013006490 and WO20101 17057. In some embodiments, the immune checkpoint inhibitor is an Indoleamine 2,3-dioxygenase (IDO) inhibitor, preferably an IDO1 inhibitor. Examples of IDO inhibitors are described in WO 2014150677. Examples of IDO inhibitors include without limitation 1 -methyl- tryptophan (IMT), β- (3-benzofuranyl)-alanine, -(3-benzo(b)thienyl)-alanine), 6-nitro- tryptophan, 6- fluoro-tryptophan, 4-methyl-tryptophan, 5 -methyl tryptophan, 6-methyl- tryptophan, 5-methoxy-tryptophan, 5 -hydroxy-tryptophan, indole 3-carbinol, 3,3'- diindolylmethane, epigallocatechin gallate, 5-Br-4-CI-indoxyl 1 ,3-diacetate, 9- vinylcarbazole, acemetacin, 5-bromo-tryptophan, 5-bromoindoxyl diacetate, 3- Amino- naphtoic acid, pyrrolidine dithiocarbamate, 4-phenylimidazole a brassinin derivative, a thiohydantoin derivative, a β-carboline derivative or a brassilexin derivative. Preferably the IDO inhibitor is selected from 1 -methyl-tryptophan, β-(3- benzofuranyl)-alanine, 6- nitro-L-tryptophan, 3-Amino-naphtoic acid and β-[3- benzo(b)thienyl] -alanine or a derivative or prodrug thereof.

In some embodiments, the immune checkpoint inhibitor is an anti-TIGIT (T cell immunoglobin and ITIM domain) antibody.

In a preferred embodiment, the checkpoint blockade cancer immunotherapy agent is a CTLA4 blocking antibody, such as Ipilimumab, or a PD-1 blocking antibody, such as Nivolumab or Pembrolizumab, or a combination thereof. The invention will further be illustrated in view of the following example.

Brief description of the Figures:

Figure 1 : Analysis of the gene expression profile in patients displaying a MET mutation. Figure 2: Influence of MET mutation on the expression of immune genes: the light grey bin categories represent the expression in MET mutants/ the white bin categories represent the expression in wild types (non-MET mutated). Figure 3: Evaluation of immune cells infiltration in MET-mutant and non-MET mutant patients.

Figure 4: Mean intra-tumor expression of CXCL13 in MET-mutated and non-MET mutated patients.

Figure 5: Determination of the frequency of high densities of infiltrating T-cells in MET- mutated and non-MET mutated patients.

Figure 6: In vitro stimulation of colorectal tumor cells (HCT1 16) with MET's ligand, hepatocellular growth factor (HGF) on several immune responsive factors (CXCL13, CX3CL1 , CCL26, IL-2, IL-1 b, CCL22, CXCL9 and IL-16).

EXAMPLE

Abstract

Here we show that mutations of MET were correlated with an increase in the T-cell proliferation, antigen presentation functions and high levels of immune checkpoints molecules. This important pre-existing antitumor immune response is a prerequisite for a checkpoint blockade cancer immunotherapy. Thus, these findings identify MET gene mutation as a biomarker for the response of a patient to checkpoint blockade cancer immunotherapy.

Material, methods for MET mutation detection: sequencing using the Ion Torrent technology

Genomic DNA from 214 patients has been extracted from frozen tumors using QIAmp DNA mini kit (Qiagen, Courtaboeuf, France) or, if frozen samples were not available, from two 5um thick FFPE slides using QIAmp DNA FFPE kit (Qiagen). Quantity of double strand DNA have been evaluated using qubit 2.0 fluorometer (Invitrogen, life Technologies, Saint Aubin, France) and 10ng (or 20ng if FFPE) of extracted DNA were amplified using Ion AmpliSeq Cancer HotSpot Panel V2 (Ion Torrent, Life Technologies) according to manufacturer's protocol. Briefly, "hotspot" regions of 50 oncogenes or tumour suppressor genes, including MET were amplified using a panel of 207 primer pairs in a 17 cycles PCR reaction (20 cycles for FFPE samples). Amplicon were then digested with FuPa Reagent and samples were separately barcoded with Ion Xpress Barcodes. lonAmpliSeq Adapters were then added to each sample. DNA banks were then purified using Agencourt AMPure XP Reagent (Beckman Coulter, Villepinte, France) and purified library obtained were amplified using Platinum PCR supermix High fidelity enzyme and purified again with Agencourt process, following the manufacturer's instructions (Ion AmpliSeq Library kit 2.0, Ion Torrent, Life Technologies). Quality and Quantity of each libraries have been evaluated thanks to High Sensitivity DNA chip (Agilent technologies, Courtaboeuf , France). Patients were then mixed and libraries obtained were amplified and enriched using the ion OneTouch 2 system (Ion PGM Template OT2 200, life technologies). Sequencing was performed with the Ion Torrent PGM system using lon316 or lon318 chip and the Ion PGM sequencing 200 kit V2 in a 520 cycles run. Runs were aligned using Variant Caller (V4.2.1 .0) plugin compared to Hg19 database, and results were analysed using Alamut 2.4.1 software (interactive biosoftware, Rouen, France).

• MET mutation is correlated with an increase in the expression of Th1 , cytotoxic T-celis and chemokines - associated genes

Material, methods for gene expression: Low density array (LDA) Real-Time Taqman qPCR

Tissue sample material (n=125 patients) was snap-frozen within 15 minutes after surgery and stored in liquid nitrogen. Frozen tumour specimens were randomly selected for RNA extraction. The total RNA was isolated by homogenization with the RNeasy isolation kit (Qiagen, Valencia, CA). A bioanalyzer (Agilent Technologies, Palo Alto, CA) was used to evaluate the integrity and the quantity of the RNA. The RT qPCR experiments were all performed according to the manufacturer's instructions (Applied- Biosystems, Foster City, CA). The quantitative real-time TaqMan qPCR analysis was performed using Low Density Arrays and the 7900 robotic real-time PCR-system (Applied Biosystems). As internal control 18S ribosomal RNA primers and probes were used. The data was analyzed using the SDS Software v2.2 (Applied Biosystems). The t-test and the Wilcoxon-Mann-Whitney test were the parametric and non-parametric tests used to identify markers with a significantly different expression among patient groups. P-value smaller than 0.05 was considered as significant.

As shown in Figures 1 and 2, patients displaying a MET mutation present an increase in the expression of several genes of the adaptive immunity, particularly with genes associated to Th1 cells, cytotoxic T-cells and chemokines. MET mutation was associated with an increase in the expression of 75 genes and with a down regulation in the expression of WNT4 and ZXC2. * MET mutation significantly increases the density of tumor-infiitrating memory T c-cells (CD45RO+), cytotoxic T-cell (CD8), FoxP3+ and PD1 + cells, and decreases the density of infiltrating immature dendritic cells (CD1a)

Material, methods for immune densities: Tissue Microarray (TMA) immunohistochemistry

Tissue microarray from the center (CT) and invasive margin (IM) of colorectal tumors (n=415) were constructed. Assessment of the invasive margin area was performed on standard paraffin sections and was based on the histomorphological variance of the tissue. The invasive margin was defined as a region centered on the border separating the host tissue from malignant glands, with the extend of 1 mm. TMA sections were incubated (60 min. at room temperature) with monoclonal antibodies against CD8 (4B1 1 , DAKO), CD45RO (OPD4), CD1A (Ab-5), FOXP3 (236A/E7, Abeam) and PD1 (NAT105, Ventana). Envision+ system (enzyme-conjugated polymer backbone coupled to secondary antibodies) (Dako, Glostrup, Denmark) and DAB-chromogen were applied (Dako, Glostrup, Denmark). Double stainings were revealed with phosphate-conjugated secondary antibodies and FastBlue-chromogen. For single stainings, tissue sections were counterstained with Harris hematoxylin (Sigma Aldrich Saint Louis, MO). Isotype- matched mouse monoclonal antibodies were used as negative controls. Slides were analyzed using an image analysis workstation (Spot Browser, Excilone, Elancourt, France). Polychromatic high-resolution spot-images (740x540 pixel, 1 .181 μηη/pixel resolution) were obtained (x200 fold magnification). The density was recorded as the number of positive cells per unit tissue surface area. The t-test and the Wilcoxon-Mann-Whitney test were the parametric and non-parametric tests used to identify markers with a significantly different cell density among patient groups. P-value smaller than 0.05 was considered as significant. As shown in Figure 3, patients displaying a MET mutation present a significantly increased density of infiltrating memory T-cells (CD45RO+), cytotoxic T-cell (CD8), FoxP3+ and PD1 + cells within the tumor and a decreased density of infiltrating- immature dendritic cells (CD1 a). * MET-mutated patients present an increased expression of CXCL13 (see Figure 4).

Material, methods for gene expression: Affymetrix Human Genome U133 Plus 2.0 Array

The tissue sample material (n=105) was snap-frozen within 15 minutes after surgery and stored in liquid nitrogen. Frozen tumour specimens were randomly selected for RNA extraction. The total RNA was isolated by homogenization with the RNeasy isolation kit (Qiagen, Valencia, CA). A bioanalyzer (Agilent Technologies, Palo Alto, CA) was used to evaluate the integrity and the quantity of the RNA. From this RNA, 1 10 Affymetrix gene chips were done on the same platform (HG-U133A plus) than the Immunome using the HG-U133A GeneChip 3' IVT Express Kit. The raw data was normalized using the GCRMA algorithm. Finally, the log2 intensities of the gene expression data were used for further analysis.

The t-test and the Wilcoxon-Mann-Whitney test were the parametric and non-parametric tests used to identify markers with a significantly different expression among patient groups. P-value smaller than 0.05 was considered as significant.

• MET-mutated patients and frequency of tumor-infiltrating T-cells

Material, methods for Immunoscore®

"Immunoscore®" is a novel scoring system, based on the quantification of two T cell subpopulations in the core of the tumor (CT) and in the tumor invasive margin (IM) (Galon et al, 2014). Immunohistochemistry on tissue-microarray sections was performed to characterize and quantify the tumor immune infiltrate (n=415). Specifically, the Immunoscore (CD3+CD8 or CD8+CD45RO) was quantified using CD3 and CD45RO staining in the CT and IM. Immunoscore I4 is when two markers (CD3 and CD45) have high density in both tumor regions (CT, IM). Immunoscore I0 is when a patient has low density for two markers in both tumor regions, Immunosocores 10-1 -2 and I3-4 represent low and high Immunoscore patients, respectively {Galon, Med Sci (Paris). 2014 Apr;30(4):439-44}.

The overrepresentation of MET mutation in patients with high or low Immunoscore was assessed with the Fisher Exact Test. P-value smaller than 0.05 was considered significant.

As shown in Figure 5, Patients with MET mutations present a significant increased frequency of High CD3+CD45RO (I3-4) or High CD8+CD45RO (I3-4) infiltrating T-cells within tumors.

• In vitro stimulation of colorectal tumor cells (HCT116) with MET's ligand, hepatocellular growth factor (HGF), increases secretion of immune responsive factors: CXCL13, CX3CL1 , CCL26, IL-2, IL-1 b, CCL22, CXCL9 and decreases IL-16

CXCL13, CX3CL1 , CCL26, IL-2, IL-1 b, CCL22, CXCL9 and IL-16 levels were quantified in colorectal tumor cell (HCT1 16) culture supernatant using a multiplex human chemokine/cytokine magnetic bead panel (EMD Millipore, Billerica, MA, USA) according to the manufacturer's instructions. Levels of cytokines and chemokines were measured in the supernatant after the stimulation with the hepatocellular growth factor (HGF) as well as in the presence of an inhibitor. Briefly, the supernatant samples (25 μΙ) were incubated with a chemokine-/cytokine-specific capture antibody attached to magnetic beads. Then a detection antibody was added, followed by streptadavin-phycoerythrin acting as a reporter molecule. Data were acquired using the Luminex 200 system (Luminex, Austin, TX, USA ) and analyzed with Bio-Plex Manager software (Bio-Rad Laboratories, Hercules, CA, USA).

• Frequency of MET mutations depending on the type of cancer

Material, methods for Pancancer MET frequency

Publicly available cancer data from the The Cancer Genome Atlas (TCGA) was downloaded (February 15, 2015). TCGA somatic mutations compiled from all cohorts with somatic mutation calls available (UCSC Xena, TCGA_PANCAN_mutation_xena_gene dataset) was used. TCGA pan-cancer somatic mutation data was compiled from all cohorts with mutation calls available. Non-silent somatic mutations (nonsense, missense, frame-shift indeis, splice site mutations, shif codon readthroughs) were identified in the protein coding region of a gene. Mutations were identified also in non-coding genes. Additionally, TCGA PANCAN strictly filtered maf files downloaded from Synapse, processed into gene by sample matrix at UCSC into eg Data repository (TCGA PANCAN AWG, TCGA_PANCAN_mutation dataset) were investigated. Details on the TCGA data processing were previously described (Kandoth et al., 2013). In the same time, clinical information was downloaded for all cohorts included in the Pan-Cancer dataset.

The number and the percentage of patients with and without mutations were calculated for each cancer type from the Pan-Cancer dataset.

Kandoth C et al., Mutational landscape and significance across 12 major cancer types., Nature. 2013 Oct 17;502(7471 ):333-9.

Anatomical origin cohort # notMutated # mutated % Not Mutated % Mutated

Skin 376 334 42 88.83 1 1.17

Endometrium 248 233 15 93.95 6.05

Lung 731 704 27 96.31 3.69

Uterus 57 55 2 96.49 3.51

Liver 202 95 7 96.53 3.47

Kidney 686 666 20 97.08 2.92

Esophagus 184 179 5 97.28 2.72

Colon 372 362 10 97.31 2.69

Stomach 421 411 10 97.62 2.38

Bladder 238 233 5 97.90 2.10

Pancreas 147 144 3 97.96 2.04

Cervix 199 196 3 98.49 1.51

Rectum 150 148 2 98.67 1.33

Brain 818 808 10 98.78 1.22

Ovary 452 448 4 99.12 0.88

Breast 995 987 8 99.20 0.80

Head. and. eck. region 512 508 4 99.22 0.78

Testis 156 155 1 99.36 0.64

Prostate 425 423 2 99.53 0.47

Thyroid. Gland 429 428 1 99.77 0.23

REFERENCES

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

Claims

1 . A method for predicting the response of a patient suffering from cancer to a checkpoint blockade cancer immunotherapy, said method comprising the step of determining if a MET gene is mutated in a tumor sample of said patient, wherein a mutation of the MET gene is predictive of a response to the checkpoint blockade cancer immunotherapy.

2. A checkpoint blockade cancer immunotherapy agent for use in a method for treating a patient which has been selected to have a tumor cell which harbors a mutated MET gene.

3. The method according to claim 1 or the checkpoint blockade cancer immunotherapy agent for use according to claim 2, wherein the blockade cancer immunotherapy agent is an antibody selected from the group consisting of anti-CTLA4 antibodies, anti-PD1 antibodies, anti-PDL1 antibodies, anti-PDL2 antibodies, anti-TIM-3 antibodies, anti- LAG3 antibodies, anti-IDO1 antibodies, anti-TIGIT antibodies, anti-B7H3 antibodies, anti-B7H4 antibodies, anti-BTLA antibodies, and anti-B7H6 antibodies.

4. The method according to claim 1 or the checkpoint blockade cancer immunotherapy agent for use according to claim 2, wherein the blockade cancer immunotherapy agent is an antibody selected from the group consisting of anti-CTLA4 antibodies and anti- PD1 antibodies.