Method for predicting response of metastasis to immunotherapy in metastatic colorectal cancer patients

Abstract

The present disclosure relates to methods for predicting the response of metastasis to immunotherapy in metastatic colorectal cancer patients. The disclosure also encompasses immunotherapy for the treatment of metastatic colorectal cancer in a patient in need thereof, which patient has been previously identified as having metastasis responsive to immunotherapy, and immunostimulatory agents for the treatment of metastatic colorectal cancer in a patient in need thereof, the patient is thus identified as having metastasis that is non-responsive to immunotherapy. The present disclosure also relates to a pharmaceutical composition comprising an immunostimulatory agent and retinoic acid for use in the treatment of metastatic colorectal cancer in a patient in need thereof.

Description

Technical Field

[0001] The present disclosure relates to a method for predicting the response of metastasis to immunotherapy in patients with metastatic colorectal cancer. The present disclosure also encompasses immunotherapy and immunostimulants for treating metastatic colorectal cancer in patients in need, the patients having been previously identified as having metastasis that is responsive to immunotherapy, and immunostimulants for treating metastatic colorectal cancer in patients in need, the patients having been previously identified as having metastasis that is unresponsive to immunotherapy. The present disclosure also relates to a pharmaceutical composition comprising an immunostimulant and retinoic acid for treating metastatic colorectal cancer in patients in need. Background Art

[0002] Primary colorectal tumors are located in the intestine, and their distal metastases occur mainly in the liver. Up to 25% of colorectal cancer (CRC) patients are diagnosed with stage IV metastatic disease, and another 40% are diagnosed with only localized disease at an early stage and eventually develop metastases (S. Vatandoust, T. J. Price, C. S. Karapetis, World J. Gastroenterol. 21, 11767–11776 (2015)). CRC metastases are difficult to cure, and 13.5% of metastatic (m) CRC patients survive 5 years after standard treatment (J. Ferlay, I. et al. Int. J. Cancer. 136, E359-386 (2015)). The immune microenvironment of primary colon tumors is one of the core determinants of the outcome of the disease. In fact, the immune score summarizes the primary CRC infiltrating effector CD8 + The type, location, and density of T cells are associated with better relapse-free survival (J. Galon, et al. Science. 313, 1960–1964 (2006); F. Pagès, B. et al. Lancet Lond. Engl. 391, 2128–2139 (2018)). Other lymphocyte or myeloid cell populations, including regulatory CD4 + T cells (Treg), CD4 + Th17 cells, macrophages or myeloid suppressor cells (MDSCs) can promote or hinder effector immune responses, although their prognostic value in mCRC has not been clearly confirmed (M. Schmitt, FR Greten. Nat. Rev. Immunol. 21, 653–667 (2021); D. Bruni, HK Angell, J. Galon. Nat. Rev. Cancer. 20, 662–680 (2020)).

[0003] The inventors previously used a syngeneic orthotopic mouse model of CRC to reveal the ability of intracolonic (IC) tumors to promote opposite and mutually exclusive polarization of their microenvironment towards pro-tumor or anti-tumor immune responses (G. Trimaglio, et al., Oncoimmunology. 9, 1790125 (2020)). The spontaneous anti-tumor polarization of orthotopic IC tumors is characterized by a high proportion of tumor-infiltrating CD8 + T cells, leading to IC tumor regression (G. Trimaglio, et al., Oncoimmunology. 9, 1790125 (2020)). Although immunotherapy directly targets CD8 + T cells, but the efficacy of immunotherapy through immune checkpoint blockade (ICB) has clinical benefits in a variety of malignancies (TF Gajewski, T. Schumacher, Cancer immunotherapy. Curr. Opin. Immunol. 25, 259–260 (2013)) and also depends on the overall immune microenvironment (JM Pitt, M ​​et al. Immunity. 44, 1255–1269 (2016); MM Gubin, E et al. Cell. 175, 1443 (2018)).

[0004] Although the primary CRC immune microenvironment has an impact on disease outcome, mCRC is largely unresponsive to ICB (SL Topalian, et al. N. Engl. J. Med. 366, 2443–2454 (2012); C. Eng, et al. Lancet Oncol. 20, 849–861 (2019)). Specific liver metastases of CRC metastases have been shown to be involved in inhibiting the efficacy of ICB (J. Yu, M et al. Nat. Med. 27, 152–164 (2021)).

[0005] Therefore, there remains a need to develop methods for determining the potential response to immunotherapy in patients with mCRC.

[0006] The intestine is a unique barrier site that continuously maintains effector and suppressive immune processes to tolerate microbiota and dietary antigens, control pathogens and maintain homeostasis (S. Shalapour, et al. Annu. Rev. Immunol. 38, 649–671 (2020)). The intestinal immune response involves different components, including key lymphocyte populations such as effector CD8 + T cells and tolerance CD4 +T cells that express the gut-homing α4β7 integrin (A. Habtezion, et al. Gastroenterology. 150, 340–354 (2016)). Although intestinal immunity develops locally, it may affect extra-intestinal sites throughout the body. For example, intestinal and liver immunity are connected through the so-called gut-liver axis, which refers to the bidirectional relationship between the intestinal microbiota and the liver (A. Albillos, A. et al. J. Hepatol. 72, 558–577 (2020)). It has been shown that the transport of intestinal-specific antigens to the liver via the portal circulation is involved in the regulation of liver immunity, leading to shared memory T cell responses to mucosal antigens (D. H. Adams, et al. Nat. Rev. Immunol. 6, 244–251 (2006)). In addition, pathological intestinal-derived α4β7 + CD8 + T cells play a role in the development of liver disorders associated with inflammatory bowel disease (IBD) (DHAdams et al. Nat. Rev. Immunol. 6, 244–251 (2006); B. Eksteen, et al. J. Exp. Med. 200, 1511–1517 (2004)), and it is speculated that gut-derived immune cells can be recruited to extra-intestinal sites, although this concept requires further verification.

[0007] In a proof-of-concept study, the inventors previously revealed that immune communication between two concomitant tumors located at different sites could affect tumor outcome. In fact, preclinical orthotopic renal tumors were able to modulate the immune microenvironment of distant concomitant lesions (C. Devaud, et al. Oncoimmunology. 4, e975572 (2015)).

[0008] Brief description of the invention

[0009] In this article, the inventors studied whether the intestinal-derived immune response for primary colon tumors may participate in the systemic immune surveillance of extraintestinal metastasis. They proved that colon tumors exert immune-dependent systemic anti-metastatic effects that can affect distal metastasis. This anti-metastatic effect can be predicted by microenvironment scoring (ME scoring).

[0010] The present invention relates to a method for determining the response of metastases to immunotherapy in mCRC patients, the method comprising:

[0011] i) Determine the CD8 + T cells, preferably enterotropic CD8 + T cells, more preferably α4β7 + CD8 +The density of T cells, dendritic cells and macrophages,

[0012] ii) Calculate the corresponding CD8 + The microenvironment score (ME score) is the ratio of the density of T cells and dendritic cells to the density of macrophages.

[0013] A higher ME score value compared to the control value indicates that the patient's metastasis is responsive to immunotherapy.

[0014] In a preferred embodiment, the method further comprises:

[0015] i) determining the density of B cells, NK cells and / or regulatory T cells in a patient sample, ii) based on CD8 + The microenvironment score (ME score) is calculated by comparing the density of T cells, dendritic cells, B cells and / or NK cells to the density of macrophages and preferably regulatory T cells.

[0016] In this application, the inventors demonstrated that in multiple tumor mouse models and mCRC patients, the enterotropic tumor-specific α4β7 + CD8 + Effector T cells influence the fate of distal extraintestinal tumors and their response to immunotherapy.

[0017] The present invention also relates to a method for determining the response of metastasis to immunotherapy in a patient with metastatic colorectal cancer, the method comprising determining the presence of enterotropic CD8 + T cells, preferably α4β7 + CD8 + The density of T cells, including the intestinal tropic CD8 + T cells, preferably α4β7 + CD8 + A higher density of T cells indicated that the patient's transfer was responsive to immunotherapy.

[0018] In a preferred embodiment, according to the method of the present disclosure, at the protein level, the dendritic cells (DC) are CD11c + cells and / or said macrophages are CD68 + cell.

[0019] According to the method of the present invention, cell density is preferably determined by flow cytometry, immunofluorescence, immunohistochemistry, bulk RNA sequencing, qRT-PCR or single cell RNA sequencing. In a preferred embodiment, the patient sample is a tumor tissue or a biological fluid sample, preferably a metastatic tumor tissue or a patient blood sample, such as a patient's peripheral blood mononuclear cells.

[0020] In another aspect, the invention relates to an immunotherapy for treating metastatic colorectal cancer in a patient in need thereof, wherein the immunotherapy is administered to a patient previously identified in the above method as having metastases responsive to the immunotherapy.

[0021] The present invention also relates to a pharmaceutical composition comprising an immunostimulant for treating metastatic colorectal cancer in a patient in need thereof, wherein the immunostimulant is administered to a patient previously identified in the above method as having metastases that are unresponsive to immunotherapy. Preferably, the immunostimulant is a colorectal cancer vaccine, preferably capable of inducing tumor antigen-specific α4β7 + CD8 + T cells. In a preferred embodiment, the pharmaceutical composition comprises retinoic acid.

[0022] In another aspect, the present invention relates to a pharmaceutical composition comprising an immunostimulant, preferably a colorectal cancer vaccine and retinoic acid, for treating metastatic colorectal cancer in a patient in need thereof.

[0023] The present invention also relates to a kit for determining the response of metastasis to immunotherapy in patients with metastatic colorectal cancer, comprising an anti-CD8 antibody, preferably an anti-α4β7 and an anti-CD8 antibody, preferably an anti-CD8, anti-CD11c and / or anti-CD68 antibody, more preferably an anti-α4β7, anti-CD8, anti-CD11c and / or anti-CD68 antibody, or a kit for determining the response of metastasis to immunotherapy in patients with metastatic colorectal cancer, comprising a primer pair for amplifying CD8 + At least one gene replacement marker for T cells, including CD8A and / or CD8B, preferably CD8 + At least one gene marker of T cells and α4β7 + At least one gene marker of cells, including ITGA4 and ITGB7, more preferably CD8 + At least one gene marker of T cells, including CD8A and / or CD8B, at least one gene marker of dendritic cells, including ITGAX, and at least one gene marker of macrophages, including CD68, and more preferably CD8 + At least one gene marker of T cells and α4β7 + At least one gene marker of cells, at least one gene marker of dendritic cells and at least one gene marker of macrophages. DETAILED DESCRIPTION OF THE INVENTION

[0025] The terms "subject" and "patient" are used interchangeably herein and refer to humans and non-human animals. As used herein, the term "patient" refers to mammals, such as rodents, felines, canines, and primates. Preferably, the patient according to the present invention is a human, preferably a human metastatic cancer patient, preferably a human metastatic colorectal cancer patient.

[0026] The terms "cancer" and "tumor" are used interchangeably herein and refer to cells that exhibit relatively abnormal, uncontrolled and / or autonomous growth, such that they exhibit an abnormal growth phenotype characterized by a significant loss of control over cell proliferation.

[0027] The terms "metastatic cancer," "metastatic tumor," or "metastasis" are used interchangeably herein to refer to secondary tumors that form as a result of cancer cells invading other sites and tissues in the body through the bloodstream or lymphatic vessels.

[0028] As used herein, the term "colorectal cancer" or "CRC" is understood to refer to colorectal cancer. The term includes colon cancer and rectal cancer, in which malignant cells form in the tissue of the colon or rectum. Colorectal cancer usually begins as a small, noncancerous mass of cells called polyps that form inside the colon or rectum, and over time, some of these polyps may become colon cancer. Cancer cells can break away from the tumor in the colon or rectum and spread to other parts of the body through the bloodstream or lymphatic system. Therefore, colorectal cancer that spreads or metastasizes to the lungs, liver, or any other organ is called metastatic colorectal cancer. The most common site of colorectal cancer metastasis is the liver, but colorectal cancer cells may also spread to any other organ, such as, by way of non-limiting example, the lungs, bones, brain, or spinal cord.

[0029] The term "patient sample" refers to any biological sample derived from a patient. Examples of such samples include tissue samples, biological fluid samples, cell samples, organs, biopsy specimens. In a preferred embodiment, the patient sample is a tumor tissue (such as a metastatic tumor tissue) or a biological fluid sample (such as a blood patient sample), preferably a peripheral blood mononuclear cell.

[0030] Methods for determining the response of metastases to immunotherapy in patients with metastatic colorectal cancer

[0031] In the present application, the inventors found that compared with the control value, based on CD8 + Higher ME score values ​​calculated from the ratio of the density of T cells and dendritic cells to that of macrophages indicated that metastases were responsive to immunotherapy in patients with metastatic colorectal cancer.

[0032] According to the present disclosure, the term "determining the response of metastasis to treatment" or "determining the responsiveness of metastasis to treatment" refers to the ability to assess whether a treatment (e.g., immunotherapy) is effective (e.g., provides a quantifiable benefit or a positive medical response) for a patient's metastasis before and / or after administration of the treatment. In other words, according to the present disclosure, determining the response to immunotherapy refers to the ability to assess whether metastasis is responsive to immunotherapy, such as whether the number of metastatic cancer cells or the size of metastatic tumors is reduced after immunotherapy, whether the progression of metastatic cancer to a more aggressive form (i.e., maintaining the cancer in a form that is sensitive to the therapeutic agent) is slowed, whether the proliferation of metastatic cancer cells or the rate of metastatic tumor growth is slowed, whether metastatic cancer cells are killed, or whether the likelihood of recurrence of a subject's metastatic cancer is reduced.

[0033] The present disclosure relates to methods for determining the response of metastases to immunotherapy in patients with metastatic colorectal cancer.

[0034] Immunotherapy is a cancer treatment method that activates the immune system to fight diseases such as cancer. Non-limiting examples of immunotherapies that can be used to treat cancer include: immunosuppressive checkpoint inhibitors, which are drugs that block inhibitory immune checkpoint proteins, T cell transfer therapy, monoclonal antibodies, or immune system activators.

[0035] As used herein, the term "immune checkpoint protein" has its general meaning in the art, and refers to molecules expressed by T cells and NK cells and regulating the immune system. According to the present disclosure, immune checkpoint proteins are preferably inhibitory immune checkpoint proteins that inhibit effector immune responses. Inhibitory immune checkpoint molecules are considered in the art to constitute immune checkpoint pathways similar to CTLA-4 and PD-1 dependent pathways (see, e.g., Pardoll, 2012. Nature Rev Cancer 12: 252-264; Mellman et al., 2011. Nature 480: 480-489).

[0036] As used herein, the term "inhibitory immune checkpoint inhibitor" or "immune checkpoint inhibitor" has its general meaning in the art and refers to any compound that inhibits the function of an immunosuppressive checkpoint protein. Inhibition includes both reduced function and complete blockade. In particular, immune checkpoint inhibitors are particularly useful for enhancing CD8 + The proliferation, migration, persistence and / or cytotoxic activity of T cells, and in particular the patient's CD8 + Tumor infiltration of T cells.

[0037] In one embodiment, the immune checkpoint inhibitor of the immune cell (T and B lymphocyte) is selected from the group consisting of anti-PD-L1, anti-PD-1, anti-CTLA-4, anti-HVEM, anti-BTLA, anti-TIGIT, anti-TIM-1 / 3, anti-LAG-3 and anti-OX40 agonists, anti-CD40 agonists, CD40-L, TLR agonists and B cell receptor agonists, particularly selected from the group consisting of anti-PD-L1, anti-PD-1 and anti-CTLA-4. In a specific embodiment of the present disclosure, the immune checkpoint inhibitor is an anti-PD-L1 antibody.

[0038] In a specific embodiment, examples of immune checkpoint inhibitors are inhibitors that affect the PD-1 / PDL-1 and CTLA-4 pathways and can be selected from the group consisting of Ipilimumab, Nivolumab, Pembrolizumab, Atezolizumab, Avelumab, and Durvalumab.

[0039] According to the present disclosure, the immunotherapy can be T cell transfer therapy. As used herein, T cell transfer therapy (also referred to as adoptive cell therapy, adoptive immunotherapy or immune cell therapy) has its general meaning in the field and refers to a treatment method that enhances the natural anti-cancer ability of T cells. In this treatment, immune cells are taken from patient tumors. T-cell transfer therapy can be tumor infiltrating lymphocytes or CART-cell therapy.

[0040] According to the present disclosure, immunotherapy can be a monoclonal antibody that binds to a specific target on cancer cells, such as anti-CD20, anti-HER2, anti-EGFR, anti-VEGF, anti-CD52 or anti-CD33, or an immune system activator (such as a cytokine), including the following non-limiting examples: interferon α (IFN-α), interleukin-2 (IL-2), interleukin-11 (IL-11), interleukin-21 (IL-21), erythropoietin, granulocyte-macrophage colony stimulating factor (GM-CSF) or granulocyte colony stimulating factor (G-CSF).

[0041] The present disclosure relates to a method for determining the response of metastases to immunotherapy in a patient with metastatic colorectal cancer, the method comprising:

[0042] i) Determine the CD8 + The density of T cells, dendritic cells and macrophages, ii) calculated corresponding to CD8 + The microenvironment score (ME score) is the ratio of the density of T cells and dendritic cells to the density of macrophages.

[0043] A higher ME score indicated that the patient's metastasis was responsive to immunotherapy.

[0044] In a preferred embodiment, the CD8 + T cells are enterotropic CD8 + T cells. In CD8 + Among the T cell population, enterotropic cells expressing α4β7 integrin are key factors in the anti-metastatic effect of the colon. Enterotropism is the tendency toward the intestine and / or the gut. In a more preferred embodiment, the CD8 + T cells are α4β7 + CD8 + T cells.

[0045] Integrin α4β7 has been described as an enterotropic molecule because it can only be acquired by T cells when activated by enteric dendritic cells in the mesenteric lymph nodes. It binds mucosal addressable cell adhesion molecule-1 (MAdCAM-1), which is constitutively expressed on high endothelial venules (HEVs) of the gut-associated lymphoid tissue (GALT), including Peyer's patches and mesenteric (m)LNs, as well as on postcapillary venules of the intestinal lamina propria.

[0046] In a preferred embodiment, the method according to the present disclosure further comprises:

[0047] i) determining the density of B cells and / or NK cells in a patient sample, and

[0048] ii) Calculate the corresponding CD8 + The microenvironment score (ME score) is the ratio of the density of T cells, dendritic cells, B cells, and / or NK cells to the density of macrophages.

[0049] A higher ME score indicates that the patient's metastasis is responsive to immunotherapy.

[0050] In a more preferred embodiment, the method according to the present disclosure further comprises:

[0051] i) determining the density of regulatory T cells in a patient sample, and

[0052] ii) Calculate the corresponding CD8 + The microenvironment score (ME score) is the ratio of the density of T cells and dendritic cells to the density of macrophages and regulatory T cells.

[0053] A higher ME score indicates that the patient's metastasis is responsive to immunotherapy.

[0054] In another more preferred embodiment, the method according to the present disclosure further comprises:

[0055] i) determining the density of B cells, NK cells and regulatory T cells in a patient sample, and

[0056] ii) Calculate the corresponding CD8 + The microenvironment score (ME score) is the ratio of the density of T cells, dendritic cells, B cells, and / or NK cells to the density of macrophages and regulatory T cells.

[0057] A higher ME score indicates that the patient's metastasis is responsive to immunotherapy.

[0058] The method according to the present disclosure comprises the step of determining the density of said cells in a patient sample.

[0059] Cell density can be assessed by determining the quantity of every kind of cell type in the patient sample using specific cell markers. Specific cell markers are well known in the art and are used to distinguish a kind of cell type, such as T cells, B cells, NK cells, dendritic cells, regulatory T cells or macrophages from other cells. The specific cell marker can be a cell surface protein (also referred to herein as cell surface antigen), an intracellular protein or a gene specifically expressed by the cell type. In a preferred embodiment, the gene is a transcript (such as mRNA) of a gene specifically expressed by the cell type.

[0060] Each cell type can be identified by using one specific cell marker or a combination thereof. Specific cell markers are well known in the art, and some examples are provided below.

[0061] As used herein, the term "hematopoietic cell" has its general meaning in the art and refers to cells derived from hematopoiesis, including red blood cells, lymphocytes, and bone marrow cells. Hematopoietic cell surface antigen markers that can be used to detect hematopoietic cells are well known in the art, and for example, can be the cell surface antigen CD45. Several antibodies that specifically bind to CD45 have been described in the prior art and are commercially available.

[0062] As used herein, the term "T cell" has its general meaning in the art and includes cells within the T cell lineage, including thymocytes, immature T cells, mature T cells, etc. According to the present disclosure, the T cell is a CD8 + In a preferred embodiment, the CD8 surface antigen is detected by one of several antibodies that specifically bind to CD8, which are described in the prior art and are commercially available. In another embodiment, the CD8 + T cells can be identified by detecting at least one gene marker, preferably involved in CD8+ T cell activation and / or effector cytotoxic function, as non-limiting examples, selected from the group consisting of CD8A, CD8B, AHNAK, CX3CR1, GZMM, CCL5, ITGB1, GZMB, ID2, CD226, CXCR3, TNFSF1, PRF1, GZMA and CCL3, preferably CD8A (CD8A isoform, NCBI reference numbers NM_001145873.1, NM_001382698.1, NM_171827.4 or NM_00176 8.7, all last revised on June 12, 2022) and CD8B (CD8B isoform, NCBI reference number NM_004931.5, last revised on January 30, 2022; NM_172101.5, last revised on April 17, 2022; NM_172102.5, last revised on April 17, 2022; NM_172213.5, last revised on April 17, 2022 or NM_001178100.2, last revised on January 30, 2022).

[0063] In a preferred embodiment, the T cells are α4β7 + CD8 + In a preferred embodiment, the α4β7 + Cells were expressed by using anti-α4β7 antibodies known in the art or by detecting the major surrogate marker α4β7 at the transcriptome level. + CD8 + T cells are identified by ITGA4 (ITGA4 transcript variant 1 or 2, NCBI reference number NM_000885.6, last revised on June 12, 2022, and NM_001316312.2, last revised on June 12, 2022), ITGB7 (ITGB7 transcript variant 1, NCBI reference number NM_000889.3, last revised on June 2, 2022), CD8A and / or CD8B mRNA.

[0064] As used herein, the terms "regulatory T cells", "Treg" (formerly known as suppressor T cells) have the general meaning of the art, including T cell subsets that regulate the immune system, maintain tolerance to self-antigens, and prevent autoimmune diseases. TREG can be distinguished from other cells by detecting surface antigen markers, for example, selected from the group consisting of CD4, FOXP3 and CD25 or a combination thereof. In another embodiment, the Treg can be identified by detecting at least one gene marker, which is selected from the group consisting of CD4, FOXP3 and CD25 as a non-limiting example.

[0065] As used herein, the term "dendritic cell" has its general meaning in the art and refers to an antigen presenting cell that presents antigens on the cell surface to T cells. Dendritic cells can be distinguished from other cells by detecting surface antigen markers, which are, for example, selected from the group consisting of CD11c (ITGAX), HLA-DR, CLEC9A, CD141, CD1c, or a combination thereof, preferably CD11c. The surface antigen can be detected by one of several antibodies that specifically bind to the surface antigen, which have been described in the prior art and are commercially available. In a preferred embodiment, the dendritic cells are conventional DC1 dendritic cells and plasmacytoid dendritic cells. The conventional DC1 dendritic cells can be distinguished from other cells by detecting surface antigen markers, which are, for example, selected from the group consisting of CCR7, CD45RA, CD209, CLEC4C, LILRB4, NRP1, B220, and SiglecH, or a combination thereof. The plasmacytoid cells can be distinguished from other cells by detecting surface antigen markers, for example, selected from the group consisting of BLTA4, CADM1, CD8A, CLEC9A, ITGAE, ITGAX, LY75, THBC, and XCR1, or a combination thereof. In a specific embodiment, the dendritic cells are identified by detecting at least one mRNA selected from the group consisting of CLEC9A, SIGLECH, LY6C2, BST2, TCF4, IRF8, ITGAX, and BCL11A, preferably ITGAX (ITGAX transcript variant 1 or 2, NCBI reference number NM_001286375.2, last revised on June 6, 2022, NCBI reference number NM_000887.5, last revised on June 7, 2022). In a preferred embodiment, ITGAX is the primary surrogate marker for DC at the transcriptome level.

[0066] As used herein, the term "macrophage" has its general meaning in the art and refers to a cell with phagocytic activity. Surface antigen markers that can be used to distinguish macrophages from other cell types are well known in the art and can be selected from the following group as non-limiting examples: CD80, CD86, CCR5, CD11b, CD11c, CD14, EMR1, CD11a, CD33, CD15, CD68, CD163, CD64, CD32, CD16, CD16 / 32, CD115, CD369 (dectin-1), CD204, CD206, CD209, FceR1, VSIG4 or a combination thereof, preferably CD68. In a preferred embodiment, the macrophage is an immunosuppressive type 2 macrophage. In a specific embodiment, the macrophage is identified by detecting the mRNA of at least one gene marker selected from the group consisting of TGM2, CHIL3, FN1, TGFB1, TGFBI, ARG1, IL10, CD163, CD206, IL-1decoyR, IL-1RA, CD68 and MMP12, preferably CD68 (CD68 transcript variant 1 or 2, NCBI reference number NM_001251.3, last revised on January 23, 2022 and NCBI reference number NM_001040059.2, last revised on January 23, 2022, respectively). In a specific embodiment, the macrophage is an immunosuppressive type 2 macrophage M2a, M2b, M2c or M2d macrophage. In a specific embodiment, the M2a macrophages can be identified by detecting the mRNA of at least one gene marker selected from the group consisting of CD163, MHCII, CD206, CD200R, TGM2, decoyr, IL10, TFGB, IL1ra, CCL17, CCL22, and CCL24, the M2b macrophages can be identified by detecting the mRNA of at least one gene marker selected from the group consisting of CD86, MHCII, IL1, IL6, IL10, TNFα, and CCL1, the M2c macrophages can be identified by detecting the mRNA of at least one gene marker selected from the group consisting of CD163, TLR1, TLR8, IL10, TGFβ, and CCR2, and the M2d macrophages can be identified by detecting the mRNA of at least one gene marker selected from the group consisting of VEGF, IL10, IL12, TNFalpha, TGFB, CCL5, CXCL10, and CXCL15. In a preferred embodiment, CD68 is the primary surrogate marker for macrophages at the transcriptome level.

[0067] As used herein, the term "natural killer cell" or "NK cell" has its general meaning in the art and refers to a cytotoxic lymphocyte that is essential to the innate immune system, has an intrinsic cytotoxic potential and the ability to produce cytokines. Surface antigen markers of NK cells that can be used to distinguish NK cells from other cell types are well known in the art and can be, for example, selected from the group consisting of CD56, CD94, CD122, CD16, NKG2D, NKG2A, NKp30 / 44 / 46 / 80, KIR family receptors or a combination thereof, preferably the marker is CD56. In a specific embodiment, the NK cell is identified by detecting the mRNA of at least one gene marker selected from the group consisting of CD56, CD94, CD122, CD16, NKG2D, NKG2A, NKp30 / 44 / 46 / 80, KIR family receptors, IFNG, PRF1, GZMA, PRF1, EOMES, NKG7, NCR1 and GZMB.

[0068] As used herein, the term "B cell" or "B lymphocyte" has its general meaning in the art and refers to an immune cell that produces antibodies and generates immune memory, acts as an antigen presenting cell and secretes regulatory cytokines. B cell surface antigen markers that can be used to distinguish B cells from other cell types are well known in the art and can be selected from the following group as non-limiting examples: CD19, B220 (CD45R), CD20 (memory B cells), IgD (follicular B cells), IgA, IgG and IgE (memory B cells), CD27 (memory and marginal zone B cells), CD38 and CD138, CD78, IgG, CD27 (plasma cells), CD24 (regulatory B cells), CD25 and CD30 (activated B cells) or a combination thereof, preferably the marker is CD19. In a specific embodiment, the B cells are identified by detecting mRNA of at least one gene marker selected from the group consisting of CD19, B220 (CD45R), CD20, IgD, IgA, IgG, IgE, CD27, CD38, CD138, CD78, CD24, CD25, and CD30.

[0069] In a specific embodiment, any known method in the art, such as immunofluorescence, immunohistochemistry or flow cytometry described in Example 1.6 of the present application, can be used to detect the above-mentioned specific cell markers, such as surface antigen markers, with antibodies, such as polyclonal antibodies, monoclonal antibodies, antigen-binding fragments or antibody mimetics. The reaction usually includes a display marker, such as fluorescence, chemiluminescence, radioactivity, enzyme markers or dye molecules, or other methods for detecting the formation of complexes between antigens and antibodies or antibodies reacting therewith.

[0070] Several antibodies that specifically bind to the above surface antigens have been described in the prior art and are commercially available, for example as listed in antibody databases such as the online database Antibody pedia (Kiermer V. (2008) “Antibodypedia—A webportal to share antibody validation data” Nature Methods. 5:860).

[0071] In another specific embodiment, the mRNA of the above gene markers can be detected using probes that specifically hybridize to the mRNA of the gene marker using any method known in the art, such as in situ hybridization.

[0072] In another specific embodiment, the above-mentioned gene markers can be detected using primers designed to specifically amplify the products of the gene markers, such as the above-mentioned mRNA or complementary DNA, such as the bulk RNA sequencing, qRT-PCR and single-cell RNAseq described in the Examples (Example 1.7) of the present application.

[0073] According to the present disclosure, in certain embodiments, cell density can be defined as the number of cells per unit cross-sectional area of ​​a metastatic tumor sample and can be determined, for example, by immunohistochemistry, immunofluorescence or in situ hybridization. Cell density can be expressed as the number of cells per cm2 of a metastatic tumor patient sample. 2 or mm 2 The number of cells counted by surface area, or the number of cells per unit volume of sample, e.g. per cm 3 Cell number of metastatic tumor tissue samples.

[0074] In another specific embodiment, the cell density can also be defined as the total cells, preferably the total hematopoietic cells (e.g. CD45 + ) and can be determined by, for example, flow cytometry or single-cell RNA sequencing. In a specific embodiment, the ME score can therefore be based on the total hematopoietic cells (e.g., CD45 + )CD8 + The percentage of T and dendritic cells compared with total hematopoietic cells (e.g. CD45 + In a preferred embodiment, the CD8 + Enterotropic CD8 T cells + T cells, more preferably α4β7 + CD8 + T cells.

[0075] In a preferred embodiment, the ME score is based on total hematopoietic cells (e.g., CD45 + )CD8 + The percentage of T cells, dendritic cells, B cells and / or NK cells compared with the total hematopoietic cells (e.g., CD45 + ) was calculated based on the ratio of the percentage of macrophages and / or regulatory T cells in the cells.

[0076] In another specific embodiment, cell density can also be defined by determining the total amount of surrogate marker gene transcripts in a cell subject sample, in particular by determining ITGA4, ITGB7, CD8A and / or CD8B as α4β7 at the transcriptome level. + CD8 + The main surrogate markers for T cells, ITGAX and CD68 at the transcriptomic level, serve as the main surrogate markers for DCs and macrophages, e.g., bulk RNAseq or qRT-PCR. In fact, the inventors have found that the transcript levels of the above surrogate markers are proportional to the density of each cell type, and thus it is possible to deduce CD8 + T cells, preferably α4β7 + CD8 + Cell density of T cells, DCs and macrophages.

[0077] According to the present disclosure, immunotherapy response of metastasis in patients with metastatic colorectal cancer is assessed by determining a ME score in a patient sample and comparing the ME score to a control value.

[0078] A high ME score in the patient sample compared to the control value indicates that the metastasis of the colorectal cancer patient is responsive to immunotherapy. A low ME score in the patient sample compared to the control value indicates that the metastasis of the colorectal cancer patient is not responsive to immunotherapy.

[0079] According to the present methods, therapeutic response can be assessed prior to immunotherapy or throughout the course of immunotherapy to monitor therapeutic response over time.

[0080] The inventors have demonstrated that α4β7 + CD8 + T cells play a central role in mediating the elimination of metastatic tumors when they migrate to metastatic sites. They demonstrated that α4β7 + CD8 + A higher density of T cells indicates that the patient's metastasis is responsive to immunotherapy.

[0081] The present application also relates to a method for determining the response of metastasis to immunotherapy in a patient with metastatic colorectal cancer, the method comprising determining the expression of α4β7 in a patient sample, preferably a patient tumor sample or a biological fluid sample, preferably a blood cell sample (such as peripheral blood mononuclear cells). + CD8 + The density of T cells, wherein the higher density of the α4β7 + CD8 + T cells indicate that the patient's transfer is responsive to immunotherapy. + CD8 + The density of T cells may preferably be determined as described above, for example by immunohistochemistry, immunofluorescence, flow cytometry or single cell or bulk RNA sequencing and qRT-PCR.

[0082] In a specific embodiment, α4β7 + CD8 + The density of T cells can be determined by measuring the α4β7 + CD8 + The number of T cells can be measured, for example, by immunohistochemistry or immunofluorescence as described above. + CD8 + The density of T cells is determined by measuring the α4β7 expression in total cells in a patient sample, such as a tumor tissue sample (e.g., metastatic tumor tissue), or a biological fluid sample, such as a blood sample (e.g., peripheral blood mononuclear cells). + CD8 + T cells, preferably by measuring the percentage of α4β7 T cells in the total hematopoietic cells (e.g., CD45+) in the patient sample. + CD8 + In another embodiment, α4β7 + CD8 + The density of T cells can be measured by determining the expression level of ITGA4, ITGB7, CD8A and / or CD8B mRNA, for example by qRT-PCR or bulk RNA sequencing.

[0083] According to the present disclosure, by determining the α4β7 + CD8 + The density of T cells and comparison of said density with control values ​​were used to assess the immunotherapy response of metastases in patients with metastatic colorectal cancer.

[0084] Compared with control values, the higher density of α4β7 in patient samples + CD8 +T cells indicate that metastasis is responsive to immunotherapy in patients with metastatic colorectal cancer. Compared with control values, lower density of α4β7 in patient samples + CD8 + T cells indicate metastasis in patients with colorectal cancer unresponsive to immunotherapy.

[0085] According to the present methods, therapeutic response can be assessed prior to immunotherapy and / or throughout the course of immunotherapy to monitor the therapeutic response over time.

[0086] According to the present disclosure, the terms "threshold value", "control value" or "cut-off value" are used interchangeably and can be determined experimentally, empirically or theoretically. A control value refers to a ME score or α4β7 in a biological sample obtained from the general population or from a selected subject population. + CD8 + T cell density. For example, the general population can include apparently healthy subjects, such as individuals who have not previously had any signs or symptoms indicating the presence of cancer. As used herein, the term "healthy subjects" refers to a population of subjects who do not suffer from any known illness, particularly any cancer.

[0087] In a preferred embodiment, the control value refers to the ME score or α4β7 in a biological sample obtained from a source other than patient data. + CD8 + T cell density, for example, in cancer patients who do not respond to immunotherapy or have a poor prognosis (e.g., short disease-free survival time).

[0088] The control value can be based on a comparative measurement between patients with metastatic colorectal cancer that respond to immunotherapy and patients with metastatic colorectal cancer that do not respond to immunotherapy, and the ME score or α4β7 of the patient sample set is calculated. + CD8 + The statistical significance between T cell density and the corresponding response of the metastatic colorectal cancer patient from which the sample is derived to immunotherapy is determined. The predetermined reference value (cutoff value) can be composed of the value with the highest statistical significance calculated. The control value can also be determined based on comparative measurements between metastatic colorectal cancer patients with poor or good prognosis (e.g., longer disease-free survival time). Typically, the control value can be determined based on experimental data using a receiver operating characteristic (ROC) curve. For example, in determining the ME score or α4β7 in a group of references, the control value can be determined by comparing the control value with the control value of the sample. + CD8 + After the T cell density is determined, an algorithm can be used to perform statistical processing on the measured values ​​in the sample to be tested, thereby obtaining a classification standard that is significant for the sample classification. In a specific embodiment, a receiver operating characteristic (ROC) analysis is performed using patient samples with known clinical status to calculate the ME score or α4β7 + CD8+ T cell density. Choose the ME score or α4β7 with the highest sensitivity and specificity + CD8 + T cell density is used as the critical point. The algorithm method is preferably performed by computer. Existing software or systems in the art can be used to draw the ROC curve, such as: MedCalc 9.2.0.1 medical statistics software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER.SAS, CREATE-ROC.SAS, GB STAT VI0.0 (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc.

[0089] Therapeutic Uses

[0090] In another aspect, the present disclosure relates to an immunotherapy for treating metastatic colorectal cancer in a patient in need thereof, wherein the immunotherapy is administered to a patient previously identified in a method as described above as having metastases responsive to the immunotherapy.

[0091] Immunotherapies useful for this therapeutic use may be selected from the group consisting of immune checkpoint inhibitors, which are drugs that block inhibitory immune checkpoint proteins, T cell transfer therapy, monoclonal antibodies, and immune system activators as described above.

[0092] In a specific embodiment, the present disclosure relates to a method of treating metastatic colorectal cancer in a patient in need thereof, comprising:

[0093] i) Determine the CD8 + the density of T cells, dendritic cells and macrophages, preferably B cells and / or NK cells, more preferably regulatory T cells,

[0094] ii) Calculate the corresponding CD8 + a microenvironment score (ME score) of the ratio of the density of T cells and dendritic cells, preferably B cells and / or NK cells, to the density of macrophages, and preferably regulatory T cells,

[0095] A higher ME score compared to the control value indicates that the patient's metastasis is responsive to immunotherapy.

[0096] iii) administering a therapeutically effective amount of an immunotherapy in said patient, said patient having previously been identified as having metastasis responsive to the immunotherapy.

[0097] In a preferred embodiment, the CD8 + T cells are enterotropic CD8 +T cells, preferably α4β7 + CD8 + T cells.

[0098] In the context of the present disclosure, as used herein, the terms "treating" or "treatment" means to reverse, alleviate, inhibit the progression of, or prevent the disorder or condition to which the term applies, or to reverse, alleviate, inhibit the progression of, or prevent one or more symptoms of a disorder or condition to which the term applies.

[0099] Such treatments are intended to improve the clinical condition of an animal or human patient by eliminating or reducing symptoms associated with cancer, particularly metastatic colorectal cancer.

[0100] As used herein, "therapeutically effective amount" or "effective amount" refers to the amount of a composition that is sufficient to achieve treatment when administered to a subject to treat a condition, disorder or condition. The therapeutically effective amount will vary depending on the composition, the disease and its severity, and the age, weight, physical condition and responsiveness of the subject to be treated.

[0101] In another specific embodiment, the present disclosure relates to a method of treating metastatic colorectal cancer in a patient in need thereof, comprising:

[0102] i) Determination of α4β7 in patient samples + CD8 + The density of T cells,

[0103] Compared with the control value, the higher α4β7 + CD8 + The T density value indicates that the patient's metastasis is responsive to immunotherapy.

[0104] ii) administering a therapeutically effective amount of an immunotherapy in said patient, said patient having previously been identified as having metastasis responsive to the immunotherapy.

[0105] The present disclosure also relates to the use of an immunotherapy in the preparation of a medicament for treating metastatic colorectal cancer in a patient in need thereof, the patient having previously been identified in the above method as having metastases responsive to the immunotherapy.

[0106] In another embodiment, the present disclosure relates to a pharmaceutical composition comprising an immunostimulatory agent, preferably retinoic acid, for treating metastatic colorectal cancer in a patient in need thereof, wherein the immunotherapy is administered to a patient previously identified in the above method as having metastases that are unresponsive to the immunotherapy.

[0107] The present disclosure relates to methods of treating metastatic colorectal cancer in a patient in need thereof, comprising:

[0108] i) Determine the CD8 + The density of T cells, dendritic cells and macrophages, preferably B cells and / or NK cells, more preferably Tregs,

[0109] ii) Calculate the corresponding CD8 + a microenvironment score (ME score) of the ratio of the density of T cells and dendritic cells, preferably B cells and / or NK cells, to the density of macrophages, preferably Tregs,

[0110] A lower ME score compared to the control value indicates that the patient's metastasis is not responsive to immunotherapy.

[0111] iii) administering to said patient a therapeutically effective amount of an immunostimulant, preferably retinoic acid,

[0112] The patient was previously identified as having metastases that were unresponsive to immunotherapy.

[0113] In a preferred embodiment, the CD8 + T cells are enterotropic CD8 + T cells, preferably α4β7 + CD8 + T cells.

[0114] In another specific embodiment, the present disclosure relates to a method of treating metastatic colorectal cancer in a patient in need thereof, comprising:

[0115] i) Determine the expression of α4β7 in patient samples + CD8 + The density of T cells,

[0116] Compared with the control value, the lower α4β7 + CD8 + The T density value indicates that the patient's metastasis is not responsive to immunotherapy.

[0117] ii) administering to said patient a therapeutically effective amount of an immunostimulant, preferably retinoic acid,

[0118] The patient was previously identified as having metastases that were unresponsive to immunotherapy.

[0119] The present disclosure also relates to the use of a pharmaceutical composition comprising an immunostimulant and preferably retinoic acid in the preparation of a medicament for treating metastatic colorectal cancer in a patient in need thereof, the patient having previously been identified in the above method as having metastases that are unresponsive to immunotherapy.

[0120] Immunostimulants are able to induce tumor antigen-specific α4β7 + CD8 +The immunostimulatory agent according to the present disclosure can be an antibody that blocks an immunosuppressive checkpoint or any molecule involved in immunosuppression, the blockade of which can trigger α4β7 + CD8 + Tumor-specific immune responses of T cells, such as antibodies targeting any component of the tumor microenvironment (immune cells) and stroma (fibroblasts, endothelial cells); direct or indirect stimulation of tumor-specific α4β7 + CD8 + T cell agonist antibody; tumor-specific α4β7 based + CD8 + Adoptive cell therapy with infusion of T cells, therapeutic cancer vaccines targeting tumor antigens (including overexpressed, tissue differentiated, testicular cancer, carcinoembryonic antigens, oncogenic antigens and neoantigens).

[0121] The vaccines according to the present disclosure may comprise immune adjuvants, including TLR agonists (Poly-ICLC, MPL, CpGODN, Imiquimod), DC-targeted monoclonal antibodies (DEC205, agonist CD40 specific), saponin-based adjuvants, GM-CSF, tetanus or diphtheria toxoids, and / or delivery vehicles, including emulsions, liposomes, virosomes, and nanodiscs.

[0122] In a preferred embodiment, the immunostimulatory agent is a cancer vaccine.

[0123] Vaccines can be based on preparations including those based on proteins or peptides, preparations based on anti-idiotypic antibodies, preparations based on heat shock proteins and preparations based on nucleic acids (DNA or mRNA), preparations based on cells (whole tumor cells, DC loaded with antigens) and preparations based on vectors (viruses, bacteria). Vaccines based on viral vectors include but are not limited to vaccines based on poxviruses, based on adenoviruses, based on herpesviruses (e.g., herpes simplex virus type 1) and based on adeno-associated viruses. When the vaccine is a vaccine based on poxviruses, the poxvirus can be any suitable poxvirus, such as avian pox (e.g., fowl pox, canary pox and pigeon pox) or orthopox (vaccinia (vaccinia) (e.g., MVA, NYVAC and ProstVac), cowpox (cowpox), camelpox and monkeypox).

[0124] In a specific embodiment, the cancer vaccine comprises a nucleic acid sequence encoding a peptide or a peptide derived from a tumor-associated antigen, which is expressed only in cancer cells and not in normal cells and is presented only on the surface of cancer cells. Peptides derived from TAAs bind to human leukocyte antigens (HLA) and can be recognized by T cells that induce an anti-cancer immune response.

[0125] In a specific embodiment, the cancer vaccine can be a neoantigen cancer vaccine, which is achieved by measuring peptide-specific cytotoxic T lymphocyte precursors in patient samples, screening for peptide-specific IgG, and then vaccinating with CTL-reactive peptides.

[0126] In a specific embodiment, the TAA that can be used to induce an anti-colorectal cancer immune response according to the present disclosure is selected from the group consisting of CEA, MAGE, MUC1, Survivin, WT1, RNF43, TOMM34, FOXM1, MELK, HJURP, KOC1, KRAS, AIM2, HT001 and TAF1B, cypB, Ick, SART1-3, ART-4, Lck, WHS, HNR, MRP3, PAP, EZH2, CEA, PSCA, UBE, Her2 / neu, PSA, Cynb, EIF4EBP and WHCS2, as described in Wagner S, Mullins CS, Linnebacher M. World J Gastroenterol. 2018. Dec 28; 24(48): 5418-5432. In a preferred embodiment, the TAA is a new antigen.

[0127] In a preferred embodiment, the stimulated tumor-specific α4β7 + CD8 + T cells can be directed to the intestine by administering an intestinal driver. In a preferred embodiment, the intestinal driver is retinoic acid (Hammerschmidt et al, J Clin Invest, 2011Aug; 121(8): 3051-61), which is known to confer intestinal tropism to effector T cells. In addition to natural retinoic acid agonists, synthetic retinoic acid agonists can also be used. Exemplary retinoic acid agonists include, but are not limited to, Ro13-7410, Ro19-0645, and N-retinoyl-D-glucosamine.

[0128] In this application, the inventors demonstrate that α4β7 + CD8 + The intestinal T cell-induced immune response has an anti-metastatic effect. + CD8 + The T cell responsive pharmaceutical composition can be used to treat metastatic colorectal cancer in a patient in need thereof.

[0129] The present disclosure relates to pharmaceutical compositions comprising an immunostimulant and retinoic acid for use in treating metastatic colorectal cancer in a patient in need thereof.

[0130] The present disclosure also relates to methods of treating metastatic colorectal cancer in a patient in need thereof, comprising administering to the patient a therapeutically effective amount of an immunostimulant and retinoic acid.

[0131] The present disclosure relates to the use of a pharmaceutical composition comprising an immunostimulant and retinoic acid in the preparation of a medicament for treating metastatic colorectal cancer in a patient.

[0132] The pharmaceutical composition may include one or more pharmaceutically acceptable excipients, diluents or carriers. As used herein, the term "pharmaceutically acceptable" refers to a pharmaceutical composition approved by a regulatory agency or generally recognized pharmacopoeia (such as the European Pharmacopoeia) for use in animals and / or humans. The term "excipient" refers to a diluent, adjuvant, carrier or vehicle used together with a therapeutic agent.

[0133] Any suitable pharmaceutically acceptable carrier, diluent or excipient can be used to prepare a pharmaceutical composition (see, for example, Remington: The Science and Practice of Pharmacy, Alfonso R. Gennaro (Editor) Mack Publishing Company, April 1997)). Pharmaceutical compositions are typically sterile and stable under manufacturing and storage conditions. Pharmaceutical compositions can be formulated into solutions (e.g., saline, glucose solutions or buffered solutions, or other pharmaceutically acceptable sterile fluids), microemulsions, liposomes, or other ordered structures (e.g., microparticles or nanoparticles) suitable for accommodating high product concentrations. The carrier can be a solvent or dispersion medium containing, for example, water, ethanol, polyols (e.g., glycerol, propylene glycol, and liquid polyethylene glycol, etc.) and suitable mixtures thereof. Appropriate fluidity can be maintained, for example, by using a coating (such as lecithin), by maintaining the desired particle size in the case of a dispersion, and by using a surfactant. In many cases, it is preferred to include an isotonic agent, such as a sugar, a polyol (such as mannitol, sorbitol), or sodium chloride in the composition.

[0134] Compositions (e.g., immunotherapy, immunostimulants, retinoic acid or the above-mentioned pharmaceutical compositions) can be administered by any means known to those skilled in the art, including but not limited to intravenous, oral, intratumoral, intralesional, intradermal, local, intraperitoneal, intramuscular, parenteral, subcutaneous and topical administration. Therefore, compositions can be formulated into injectable, local or edible preparations. According to the disclosure, administration of compositions to subjects can show beneficial effects in a dose-dependent manner. Therefore, within a wider limit, it is expected that administration of a larger amount of compositions can obtain higher beneficial biological effects than administration of a smaller amount of compositions. In addition, efficacy is also expected at dosage levels lower than those at which toxicity occurs.

[0135] It will be understood that the specific dose administered in any given case will be adjusted, as is well known to those skilled in the art, depending on the composition being administered (e.g., an immunotherapeutic, an immunostimulant, retinoic acid, or a pharmaceutical composition as described above), the volume of the composition that can be effectively delivered to the site of administration, the disease to be treated or inhibited, the condition of the subject, and other relevant medical factors that may alter the activity of the composition or the subject's response.

[0136] For example, the specific dosage of a composition (e.g., immunotherapy, immunostimulant, retinoic acid or the above-mentioned pharmaceutical composition) for a particular subject depends on age, body weight, general health, diet, time and mode of administration, excretion rate, the drug used in combination, and the severity of the specific condition to which the treatment is applied. The dosage for a given patient can be determined using conventional considerations, such as by conventionally comparing the different activities of immunotherapy and pharmaceutical compositions described herein with known agents, such as by appropriate conventional pharmacological protocols. Compositions (e.g., immunotherapy, immunostimulant, retinoic acid or the above-mentioned pharmaceutical composition) can be administered in a single dose regimen or a multiple dose regimen.

[0137] Suitable dosage ranges for compositions (e.g., immunotherapeutics, immunostimulants, retinoic acid, or pharmaceutical compositions described above) can be on the order of several hundred micrograms of the agent, ranging from about 0.001-10 mg / kg, preferably about 0.01-1 mg / kg, more preferably about 1-10 mg / kg, and even more preferably 10 mg / kg.

[0138] Reagent test kit

[0139] In another aspect, the present disclosure relates to a kit for determining the response of metastasis to immunotherapy in a patient with metastatic colorectal cancer, comprising a set of reagents capable of determining a ME score.

[0140] In a specific embodiment, the kit comprises anti-CD8 antibodies, preferably anti-α4β7 and anti-CD8, more preferably anti-CD8, anti-CD11c and anti-CD68 antibodies, even more preferably anti-α4β7, anti-CD8, anti-CD11c and anti-CD68 antibodies.

[0141] In another specific embodiment, the kit comprises a primer pair for amplifying the CD8 + At least one gene marker of T cells, including CD8A and / or CD8B, preferably a primer pair, the primer pair is used to amplify the above CD8 + α4β7 + At least one gene marker of T cells, including ITGA4, ITGB7CD8A and / or CD8B, more preferably a primer pair for amplifying the above CD8 +at least one gene marker of T cells, including CD8A and / or CD8B, a primer pair for amplifying at least one gene marker of the dendritic cells, including ITGAX, and a primer pair for amplifying at least one gene marker of the macrophages, including CD68, and more preferably, a primer pair for amplifying the CD8 + At least one gene marker of T cells, including CD8A and / or CD8B and the above-mentioned α4β7 + At least one gene marker for T cells, including ITGA4 and / or ITGB7, a primer pair for amplifying at least one gene marker for the above-mentioned dendritic cells, including ITGAX and a primer pair for amplifying at least one gene marker for the above-mentioned macrophages, including CD68.

[0142] In a more preferred embodiment, the kit may further comprise a primer pair for amplifying at least one of the above-mentioned gene markers of B and / or NK cells.

[0143] In another specific embodiment, the kit may include probes that hybridize to at least one of the above-mentioned gene markers under standard low stringency conditions.

[0144] Preferably, the kit comprises containers, each container comprising one or more compounds, the concentration or amount of which is conducive to the reconstitution and / or use of the reagent set, preferably a primer or an antibody, preferably an antibody coupled to a marker, preferably a fluorescent (fluorophore) or chemiluminescent (chromophore) compound, which can determine the ME score and implement the method according to the present disclosure.

[0145] The kit may also include instructions for preparing and / or using the reagents according to the methods of the present disclosure to determine the expression level of the gene. BRIEF DESCRIPTION OF THE DRAWINGS

[0146] Figure 1: Systemic anti-metastatic effect of colon tumors. (AC) B6 mice (n = 6-19 mice, two representatives per experimental group) (A, B) intrahepatic (IH) injection of MC38-luc cells alone (IH alone, IH al.) or simultaneous (IH + IC) intracolonic (IC) injection of MC38 cells. (A) Representative photos of bioluminescence emission of IH tumors alone and (B) bioluminescence of one mouse in each group of IH alone, progression (IH + IC Progr.) and rejection (IH + IC Rej.) groups. [Representative individual results]. A representative experiment of two independent experiments is described. (C) MC38 cells were injected subcutaneously (SC) on each side of B6 mice, with simultaneous injection of MC38-luc cells IC (n = 26) or without injection of MC38-luc cells IC (n = 6). On day 10 after tumor implantation, one SC tumor was excised for future analysis, and the remaining SC and IC tumor growth were monitored using calipers and IVIS cameras, respectively. Graphs of SC tumor size (left axis) and IC tumor bioluminescence emission (right axis) show one representative mouse from the progression (Progr.), rejection-relapse (Rej.-Rel.), and complete rejection (Rej.) groups. Mann-Whitney statistical test was used: *p<0.05, **p<0.01, ***p<0.001.

[0147] Figure 2 : Microenvironment (ME) score predicts the occurrence of colon anti-metastatic effect. (AG) B6 mice were injected with MC38-luc cells alone IH (IH alone, n=10) or MC38 cells simultaneously IC (IH+IC, n=33). The bioluminescent emission of IH tumors (tum.) of mice was monitored from day (D) 2 to D9 and D10, and IH and IC tumors were analyzed by flow cytometry. For each group, two representatives of one experiment are described. (A) Based on CD8 + Percentage (%) of T cells (CD8) *% of dendritic cells (DC) / % of macrophages (MΦ) ME scores were established in individual IH tumors from the IH+IC group. Light gray indicates the lowest ME score < 25th percentile (low; n = 8), black indicates the intermediate ME score (medium; n = 17), and dark gray indicates the highest ME score > 75th percentile (high; n = 8). (B) CD8 infiltrating IH or IC tumors (tum.) according to ME score + T cells, (C) DC, (D) MΦ, (E) PD-1 + CD8 +T cell percentages and percentages of cells in tumors of the IH control group alone (IH al.). (F) Correlation between IH-tumor bioluminescence (Biolum) emission and ME score in the IH+IC mouse group (n=27) at D7; one point represents one mouse. (G) Individual IH-tumor bioluminescence emission in IH+IC mice at D2 and D9 according to ME score (low n=7; medium n=13 and high n=7). (H) ME scores of IH tumors and D10 dissociated tumors described in the previous group (AE) after IH injection of TC1 (n=10), MOC1 (n=7), HEPA (n=9) and CT26 (n=10) in B6 and BALB / c mice. (I and J) MC38 cells were injected subcutaneously (SC) alone on each side of B6 mice (SC alone, n=6) or IC injected with MC38-luc cells (SC+IC, n=26). At D10, one SC tumor was excised and analyzed by flow cytometry, and the remaining SC and IC tumor growth was monitored (e.g. Figure 1 E described). (I) Figure 1 E shows the ME score of SC tumors in the experiment, and (J) after SC injection of MOC1 (n=7), HEPA (n=7) and CT26 (n=10) in B6 and BALB / c mice, the ME score of D10 dissociated tumors. The legends of Figure AE are after Group E, the legends of Figure FH are after Group H, and the legends of Figures I and J are after Group J. Each result is represented by median and interquartile range in (A), by minimum to maximum value and median and interquartile range (box) in (B, C, D, E, I), and by median only in (H, J). Using Spearman test (F), Student T-test or Mann-Whitney test (other groups): *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0148] Figure 3 :Systemic tumor-specific CD8 + T cell responses are involved in anti-metastatic effects in the colon. (A) B6 mice were injected with MC38-Luc IH and MC38 cells (n=20) or B16F10 (n=19) were injected IC. The graph represents mouse survival. (BE) B6 mice were injected with MC38-luc cells IH and MC38 cells IC. On day (D) 10, the ME-score was determined in the IH tumor. Tumors (tum.) and peripheral areas (spleen, blood, IH tumor-draining lymph nodes (LN IH) and IC tumor-draining lymph nodes (LN IC)) were analyzed by flow cytometry. Adpgk-dextramer infiltration in IH or IC tumors from mice carrying IH tumors with low and high ME scores + CD8+ (B) Representative dot plots (Dextramer vs CD8 staining) and (C) percentages of T cells (Dextra+). [Individual results are presented as mean ± SEM]. (D) ME-score vs dextramer in IH and IC tumors of mice bearing low and high ME-score IH tumors + CD8 + Correlation between T cell % (E) Dextramer in IC tumor, spleen, blood, LN IC, LN IH + CD8 + T cell % and dextramer in IH tumors + CD8 + Correlation between T cell % . Results are from the summary of two independent experiments (B, C IH tum.) or from a representative experiment representing two independent experiments. On the linear regression curve, one point represents one mouse. Log-rank Mantel-cox statistical test (A), Mann-Whitney and Pearson statistical tests were used: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0149] Figure 4 .α4β7 + CD8 + T cells are a key component of ME score and anti-metastatic effect in the colon. (AG) ME score of IH tumors from IH+IC implanted mice (MC38-luc IH and MC38 IC; n=59) and from control mice implanted with IH alone (n=10) was assessed at day 10. Single-cell RNA sequencing analysis was performed on 7 IH tumors per group with low, medium (Int.) and high ME-scores (IH+IC group) and from the control group. (A and C) (A) Total CD45 + Cells and (C)CD8 + T(CD8_c#), conventional CD4 + T(Tconv_c#), regulatory CD4 + Uniform manifold approximation and projection (UMAP) of clusters of T (Treg), NK (NK_c#), and NKT (NKT_c#) cells infiltrating IH tumors by (A) CD45 + Identified cell types and (C) T lymphocyte / NK identified clusters are stained. Macrophages: MΦ; CD8 + T lymphocytes: CD8; monocytes: mono; conventional dendritic cells: cDC; plasmacytoid DC: pDC; neutrophils: neutro. (B and D) The combined group (B) single CD45 +Percentages of cell subsets and (D) CD8 + The percentage of T lymphocyte clusters. Each bar represents a single-cell RNA sequencing sample. (E) In CD8 + Normalized expression of Itga4 and Itgb7 in seven clusters (c1-c7) of T cells. (F) Mean and (G) UMAP imaging (expression of normalized counts) of normalized expression of Itga4 or Itgb7 in CD8_c1, _c2, _c3, NK_c1, and Treg clusters in low and high ME score tumors. (F) The number of detected cells (counts) expressing each gene in each cluster is represented by the dot size, and the gene expression level (normalized counts) is represented by the gray scale. (HK) B6 mice were injected IH with MC38-luc and IC with MC38 cells. Adpgk-dextramer infiltrating IH tumors + CD8 + T cells (Dextra + α4β7 integrin + (H) Representative dot plots (Dextramer vs α4β7 integrin staining) and (I) percentages of circulating CD8 + α4β7 integrin in T cells + (J) Representative dot plots and (K) percentages. Results are from two independent experiments (I, n = 12; K, n = 14) pooled. (L and M) B6 mice were injected with MC38-luc IH and MC38 cells IC at the same time, and treated with anti-α4β7 integrin antibody (anti-α4β7, n = 25) or PBS as a control (Ctl, n = 25), as described in Materials and Methods. (L) Survival of mice at different time points and (M) the proportion of live and dead mice. Likelihood ratio test was used for single cell gene expression (E), Log-rank Mantel-cox statistical test was used for survival analysis (L), Student T-test or Mann-Whitney statistical test was used for groups (H) and (J): *p<0.05, **p<0.01, ****p<0.0001.

[0150] Figure 5 .α4β7 in colon tumors + CD8 +T cells have therapeutic advantages in immunotherapy. (A and B) B6 mice were injected with MC38-luc cells alone IH (groups: IH al. (n = 14); IH + αPD-L1 (n = 26)) or MC38 cells were injected with IC at the same time (groups: IH + IC (n = 29); IH + IC + αPD-L1 (n = 29)). One group of mice was injected with MC38-luc cells alone IC (IC + αPD-L1 (n = 14)). On days (D) 12 and 15, anti-PD-L1 antibodies (αPD-L1) were injected in the group. Depicted are (A) the proportion of mice in which IH transfers were rejected (Rej.) or performed (Progr.) and (B) the survival of mice. (CF) (C) IC (al.)-rejection-recipient (rec.) mice (n = 20) were re-stimulated by performing IH injections of MC38-luc cells 46 days after the initial IC injection and rejection. In parallel, naive B6 mice (C and D; n=6) (control: Ctl) were IH injected with MC38-luc cells. (C and E) Representative photos of individual IH bioluminescent emissions at (C) early time points and (E) long term, and (D) one mouse from each group of re-challenged mice. One representative experiment of two independent experiments is depicted. (F) IC-alone reject-recipient mice were sacrificed on D84 days after IH re-challenge (post-rechallenge) and organ analysis was performed by flow cytometry. Figures show IH tumor (tum.) injection site liver (post-rejection scar), spleen, blood and LN IH, post-rech. or Adpgk-Dextramer in low and high ME score tumor mice compartments + CD8 + T cell (Dextra+) infiltration%. (G) Lane graphs represent the time (T0) before (months) and after (weeks) treatment of 17 mCRC patients in the analysis. Patients 1-10 are non-responders and 11-17 are responders. (H) Mean values ​​of standardized expression of ITGA4 and ITGB7 in non-responders (blue background) and responders (red background). The percentage of patients in each group is represented by point size and gene expression level (transcripts per million) is represented by purple scale. (I) Progression-free survival curves of 17 mCRC patients. The median expression levels of ITG4 and ITGB7 genes in RNA sequencing analysis were used to determine low (Lo.) and high (Hi.) ITG4 and ITGB7 groups. CD8 in mCRC patients before treatment (T0) + (J) Representative dot plots and (K) percentage of α4β7 integrin+ in T cells. (L) Overall survival curves of mCRC patients. + α4β7 integrin in T cells +The median of the percentages was used to determine the low (Lo.) and high (Hi.) α4β7CD8 groups. [Individual results are presented as mean ± SEM in C, F, and K]. Groups (B), (I), and (L) used the Log-rank Mantel-cox statistical test, and groups (C), (F), and (K) used the Mann-Whitney statistical test: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. DETAILED DESCRIPTION

[0151] 1. Materials and Methods

[0152] 1.1 Cell culture, reagents, and tumor cell lines

[0153] MC38 (parental and firefly-luciferase+ (Luc)) (C57BL / 6 (B6) background colorectal carcinoma, RRID: CVCL_0A67), B16F10 (B6 melanoma, RRID: CVCL_0159), HEPA1-6 (B6 hepatocellular carcinoma, ATCC Cat#CRL-1830) and CT26 (BALB / c colorectal carcinoma, ATCC Cat#CRL-2638) cell lines were cultured in Dulbecco's modified Eagle's medium (DMEM) (Sigma, Cat#6429) supplemented with 10% fetal bovine serum (FBS; gibco, catalog number 10270106). MC38-Luc was generated as previously described (C. Devaud, et al. Cancer Immunol. Immunother. CII. 62, 1199–1210 (2013)). TC1 cells (B6 background, generated by HPV16E6 / E7 and cH-ras retroviral transduction of lung epithelial cells) were kindly provided by Pr. TCWU (Johns Hopkins Medical Institutions, Baltimore, MD) and cultured in Roswell Park Memorial Institute (RPMI)-1640 (Thermo Fisher Scientific, Cat#61870044) with 10% FBS, 1% sodium pyruvate solution (Sigma, Cat#S8636-100mM), MEM non-essential amino acids (NEAA) solution 1X (solution 100X, Thermo Fisher Scientific, Cat#11140035), HEPES 10mmol / L (ThermoFisher Scientific, Cat#15630056). MOC1 (B6 mouse oral cancer cell line, Kerafast Cat#EWL001) was cultured in Iscove's modified Dulbecco's medium (IMDM) (Sigma, Cat#I3390) containing 10% FBS, insulin (5 mg / ml; Sigma, Cat#I6634-50 mg), hydrocortisone (0.08 μg / ml; Sigma, Cat#H0135-1 mg), epidermal growth factor (EGF, 0.01 μg / ml Millipore, Cat#01-107), 2% penicillin-streptomycin (Sigma, Cat#P0781-100ML), 1% L-glutamine (Thermo Fisher Scientific, Cat#25030024). All cells were cultured at 37°C and 5% CO2 for 2-6 generations and tested for mycoplasma.

[0154] 1.2 Mice.

[0155] Six-week-old female B6 (JRj) or BALB / c mice were purchased from Janvier Laboratories (Le Genest-Saint-Isle, France). Mice were housed under specific pathogen-free conditions at the Centre Régional d'Exploration Fonctionnelle et de Ressources Experimentales (CREFRE, Toulouse, France). All experimental protocols were approved by the Regional Ethics Committee of the Toulouse Biological Research Federation (C2EA-01, FRBT) and the French Ministry for Higher Education and Research (Permit No. 23093-2019112715157467). For animal welfare guidelines, we followed the European Directive 2010 / 63 / EU. The mice used were 7–10 weeks old.

[0156] 1.3 Tumor vaccination, monitoring and treatment.

[0157] Mice were inoculated with one or two concomitant tumors (one or two tumor models).

[0158] For the intrahepatic (IH) tumor model (IH alone), anesthetized mice were injected IH with 2.5 × 10 5 MC38-luc, 5.10 4 TC1, 5×10 6 MOC1, 2×10 6 HEPA 1-6 or 10 6 CT26 cells were inoculated in the right flank of mice as described previously (C. Devaud, et al. Mol. Ther. J. Am. Soc. Gene Ther. 22, 18–27 (2014)). For the subcutaneous (SC) tumor model (SC alone), 2×10 6 MC38, 5×10 6 MOC1, 2×10 6 HEPA 1-6 or 10 6 For the intrarenal (IK) tumor model (IK alone), anesthetized mice were injected with 5 × 10 5 MC38 cells were grown as described previously (C. Devaud, et al. Mol. Ther. J. Am. Soc. Gene Ther. 22, 18–27 (2014). For the intracolonic (IC) tumor model (IC alone), anesthetized mice were injected with 5 × 105 MC38-luc, as previously described (G. Trimaglio, et al. Oncoimmunology. 9, 1790125 (2020), C. Devaud, et al. Cancer Immunol. Immunother. CII. 62, 1199–1210 (2013)). For both IH+IC tumor models, 2.5×10 5 MC38-luc or 5×10 5 B16F10 cells, 5 × 10 5 MC38 cells. For the SC+IC dual tumor model, 2×10 MC38 cells were inoculated SC in the right and left flank of mice. 6 MC38 cells, 5×10 5 MC38-luc cells (one SC tumor was collected for analysis at day (D) 10). For the IH+IK dual tumor model, 2.5×10 5 MC38 cells, 5×10 5 MC38 cells.

[0159] For the rechallenge experiment, mice rejected by IH+IC or IC alone were injected with 2.5×10 5 MC38-luc cells were re-stimulated. After intraperitoneal (IP) injection of 150 mg / kg D-luciferin (Oz Bioscience, Cat#LN10000), the cells were re-stimulated weekly. MC38-Luc IH and IC tumor progression was monitored in vivo using a spectral in vivo imaging system (PerkinElmer). Quantitative analysis was performed using IVIS Living Image 4.7.3 software (PerkinElmer). Bioluminescent signal intensity was expressed as mean radiance (photons / sec / cm 2 SC tumor progression was monitored using a caliper and expressed in mm 2 Calculate tumor size. When the endpoint time (defined in the ethical protocol) is reached in the survival experiment, the SC tumor size reaches the ethically defined 250 mm 2 When the tumors and tissues need to be collected and analyzed, the mice were euthanized.

[0160] For α4β7 integrin (LPAM-1) blockade, 100 μl of anti-LPAM-1 (clone DATK32, BioxCell, Cat#BE0034) or 100 μl of phosphate buffered saline (PBS) as control were injected IP after tumor implantation, first at 350 μg / dose daily (D1-D8), then at 200 μg / dose every 3 days until D17. For immune checkpoint blockade therapy, 100 μg / dose of anti-PD-L1 (clone 10F.9G2, BioXcell, Cat#BE0101) or rat IgG2b isotype control (clone LTF-2, BioXcell, Cat#BE0090) were injected IP at D12 and D15.

[0161] 1.4 Metastatic (m)CRC patient cohort.

[0162] Seventeen patients with mismatch repair (pMMR) or microsatellite stable (MSS) mCRC were enrolled in the cohort after written informed consent under the MINER protocol (NCT03514368) of the Toulouse Cancer University Research Institute. The protocol was approved by the Institutional Review Board, the French National Medicines Agency (Agence Nationale de Sécurité du Médicament et desproduits de santé, ANSM), and the Patient Protection Committee (Comité de Protection de Personnes, CPP). After two or more standard therapies, patients received immunotherapy in combination with other agents. Treatment included oral tyrosine kinase inhibitors (TKIs) with antiangiogenic activity combined with anti-PD-1 / PD-L1 immunotherapy (12 patients); anti-CTLA-4 and anti-PD-L1 immunotherapy (2 patients) or anti-PD-L1 immunotherapy combined with other immunomodulators (3 patients). Thirteen patients developed synchronous metastases (metastatic lesions detected at the time of initial diagnosis) and four patients developed secondary metastases (metastases diagnosed after initial diagnosis and surgical treatment of the primary tumor). Of the 17 patients, seven responded to immunotherapy and ten did not respond. Responders were defined as patients who showed an objective response (OR) or stable disease (SD) for 6 months or longer for at least one lesion by the RECIST (Response Evaluation Criteria in Solid Tumors) 1.1 criteria. Metastatic biopsies obtained before the start of treatment (baseline) were formalin-fixed paraffin-embedded (FFPE) or frozen, and blood samples at baseline (T0) were used to prepare PBMCs. Metastatic lesions were located in the liver (13 patients), lungs (2 patients), lymph nodes (1 patient), and peritoneum (1 patient).

[0163] 1.5 Cell isolation and cryopreservation.

[0164] For mouse tumor treatment, D10 tumors were collected after mice were killed. The tumor was cut into small pieces, and digested for 40 minutes at 37°C with stirring using a tumor dissociation kit (Miltenyi Biotech, Cat#130-096-730), followed by filtration through a 70 μM cell strainer. After mice were killed, spleen and lymph nodes (LN) were also collected, and organs were directly separated by filtration through a 70 μM cell strainer. Blood was collected by intracardiac puncture using a 37G needle, 1ml syringe and 100ul heparin (SIGMACat#9041-08-1) at the time of killing. Potassium ammonium chloride (ACK) buffer (BD BiosciencesCat#555899) erythrocyte lysis step (5 minutes at room temperature) was performed on spleen and blood cell suspension. All cell suspensions were frozen in FBS, 10% dimethyl sulfoxide (DMSO) (SIGMACat#D2650). For human blood samples, peripheral blood mononuclear cells (PBMCs) were isolated by density gradient sedimentation using Ficoll-Paque (Cytiva, Cat# 17144003). Blood cells were cryopreserved in FBS, 10% DMSO.

[0165] 1.6 Flow cytometry

[0166] For mouse samples, cells were thawed and suspended in PBS, 2.5% FBS (staining buffer) containing anti-mouse CD16 / CD32 monoclonal antibody (mAb) (clone 2.4G2, BD Biosciences 553142, 1:100) and incubated on ice for 10 minutes. To exclude dead cells, cells were centrifuged and suspended in PBS containing Fixable Viability Stain 700 (BD Biosciences 564997, 1:1000) or Stain 780 (BD Biosciences 565388, 1:1000) for 10 minutes at room temperature in the dark. Then, cells were washed twice in PBS. For MHC I / peptide dextramer staining, cells were incubated with 20 μl of 5% FBS in PBS containing the PE marker H-2Db / ASMTNMELM dextramer (mutant peptide of the Adpgk gene (26), Immudex) for 30 min in the dark at room temperature. When dextramers were used, no washing was required prior to subsequent mAb surface staining. For surface staining, cells were incubated in the dark at 4°C for 20 min with a combination of anti-mouse mAbs as described below in staining buffer: CD45.2 (clone 104, BD Biosciences, 1:100) with FITC (553772), BUV396 (564616) or BV650 (740490), CD3 (clone 145-2C11, BD Biosciences, 1:100) BV786 (564379) or BUV496 (564661), TCR β chain FITC (clone H57-597, BD Biosciences 553170, 1:100), CD8a (clone 53-6.7 ... Biosciences) BUV737 (564297, 1:300) or BUV496 (750024, 1:100), CD4 BUV496 (clone GK1.5, BD Biosciences564667, 1:300), TIGIT PerCP-eF710 (clone GIGD7, ThermoFisher 46-9501-82, 1:75), TIM-3BV421 (clone RMT3-23, BD Biosciences 747626, 1:100), PD-1BUV396 (clone J43, BD Biosciences 744549, 1:75), CD25 BV650 (clone PC61, BD Biosciences 564021, 1:100), CD11b PE (clone M1 / 70, Thermofisher12-0112-81, 1:200), F4 / 80BV786 (clone BM8, Biolegend123141, 1:100), CD11c BV650 (clone NA418, Biolegend 117339, 1:100), Gr1 (Ly6G / C) AF700 (clone RB6-8C5, Biolegend 108422, 1:200), CD80 PECF594 (clone 16-10A1, BD Bioscience562504, 1:200), I-Ab PE / Cy7 (clone AF6-120.1, Biolegend 116419, 1:100), CD49d (α4 integrin) BV711 (clone 9C10, BD Biosciences 740672, 1:100), β7 integrin BUV396 (clone M293, BD Biosciences 743793, 1:100), FR4 BV510 (clone 12A5, BD Biosciences Biosciences744120, 1:100), LPAM-1 (α4β7 integrin) APC (clone DATK32, Miltenyi Biotech 130-123-565, 1:100) and NK1.1PeCF-594 (clone PK136, BD Biosciences 562964, 1:100). For intracellular / intranuclear staining, cells were permeabilized for 30 minutes at 4°C using the FOXP3 / Transcription Factor Staining Buffer Kit (Thermo Fisher Scientific, Cat#00-5523-00), followed by dextramer staining, where cells were permeabilized for 20 minutes at 4°C using the Fixation / Permeabilization Kit (BD Biosciences, Cat#554714). Then, staining was performed at 4°C for 30 minutes with mAbs against intracellular / intranuclear markers: FOXP3 PE (clone FJK-16S, eBioscience 12-5773-82, 1:100) and CTLA-4 PeCy7 (clone UC10-4B9, eBioscience 25-1522-82, 1:75). Flow cytometry analysis was performed using a BD LSR FortessaTM X20 (BD Biosciences), and data were analyzed using Flowlogic software (Miltenyi).

[0167] For human samples, CD8 T cells were enriched from thawed cells by positive magnetic selection (CD8 microbeads, human, Miltenyi Biotec, 130-045-201) using MS columns (Miltenyi Biotec, 130-042-201). Dead cells were excluded using Fixable Viability Stain 700 (20 min in PBS at 4°C) and cells were stained with the following anti-human mAbs: CD3 BUV496 (clone UCH-T1, BD Biosciences 612940, 1:50), CD8 V500 (clone RPA-T8, BD Biosciences 560774, 1:100), CD197 PE-Vio770 (clone REA546, Miltenyi Biotec 130-117-396, 1:50), CD45RA BUV395 (clone HI100, BD Biosciences 740298, 1:25), LPAM-1 (α4ββ7 integrin) Alexa Fluor 405 (clone Hu117, R&D systems FAB10078V-100UG, 1:20), CD279 BUV737 (clone EH12.1, BD Biosciences 612791, 1:50), TIGIT PE (clone MBSA43, eBioscience 12-9500-42, 1:50), in PBS containing 5% FBS, incubated at 4°C for 15 minutes.

[0168] 1.7 Droplet-based single-cell RNA sequencing and single-cell gene expression analysis.

[0169] CD45.2 was positively selected and enriched from tumor cell suspension by magnetic cell sorting (Miltenyi Biotec, Cat#130-110-618). + Cells. Cells from mice were pooled based on their ME scores (four samples prepared with IH tumors with low, medium, and high ME scores and a single IH control group). 16,500 cells were started from each sample pool and 3' gene expression single cell libraries were generated using the Chromium Controller Instrument and Chromium Next GEM Single Cell 3'Kit v3 and Dual Index TT Set A according to the manufacturer's instructions (10×Genomics). Library size and quality were confirmed on a fragment analyzer (Agilent). The library was quantified using the KAPA Quantification Kit for the Illumina platform (KAPA Biosystems, Roche). Samples were pooled in an equimolar manner. The library was sequenced on a NextSeq 550 (Illumina) using double-end sequencing 28bp (read1) × 90bp (read2) and dual index 10bp sequencing. The raw base call files were demultiplexed using CellRanger mkfastq, with barcode matches exceeding 97% and Q30 base matches exceeding 91%. Subsequently, the FASTQ files of the four samples were processed with Cellranger counting to align with the mm10 reference and quantify the genes. The four samples were analyzed in R using the Seurat package. For each sample, the barcoded cells were retained when the barcoded cells expressed less than 10% of the mitochondrial genes and 1000-6000 total genes. Then, the four samples were merged and the RNA counts were standardized using the SCTransform method. Barcoded cells that did not express Ptprc (CD45) and simultaneously expressed Trac, Trbc1 and Trbc2 (TCR constant chain) or Adgre1 (F4 / 80) or Ighd (BCR constant chain) were removed. Principal component analysis (PCA) was performed on 3000 genes with the RunPCA function. Then, the first 15 principal components of PCA were used to perform uniform manifold approximation and projection (UMAP) size reduction on the scaled data. Using the FindNeighbors and FindClusters functions on the 15 principal components, 18 clusters were identified. To characterize each cluster, the FindAllMarkers function was used in ImmGen and significant genes with an average log2 fold change greater than 1 were used. From these analyses, 12 major lineages were identified: CD8+ and CD4 + T cells (Tconv (conventional) and Treg (regulatory)), NK cells, NKT cells, B cells, monocytes, macrophages, dendritic cells (DC: conventional type 1 (cDC1), conventional type 2 (cDC2) and plasmacytoid (pDC)) and neutrophils. To more accurately characterize macrophage and monocyte subtypes, the FindMarkers function was used to compare macrophage and monocyte clusters and identify differentially expressed genes in 6 macrophage and monocyte clusters. T lymphocytes, NKT and NK cells (T / NKT / NK cells) were separated from the previous data set of 12 major lineages, and the expression data were rescaled on this new T / NKT / NK cell data set. For all CD45 cells, PCA was performed on the T / NKT / NK cell data set using the RunPCA function, and the first 8 main components were used for UMAP analysis and each cluster was found. Finally, 15 clusters were identified using the specific markers described in the results. To characterize the clusters in detail, the FindAllMarkers function was used, and each cluster was compared to other clusters of similar cell types (compared to CD8 clusters, compared to Tconv and Treg clusters, compared to NK and NKT clusters). Likelihood ratio tests were performed on single-cell gene expression using the FindAllMarkers and FindMarkers functions. Marker genes were visualized on UMAP using standardized data, and differentially expressed genes were visualized on Heatmap using the average value of standardized counts for each sample.

[0170] 1.8 RNA extraction from human tissue samples and analysis of bulk RNA sequencing data.

[0171] After the fresh frozen (FF) tumor samples were broken and homogenized, RNA was extracted using Qiagen RNeasy Plus Mini kit (Qiagen, Hilden, Germany, Cat#74134). Formalin-fixed paraffin-embedded (FFPE) tissue blocks were sliced ​​to prepare unstained sections (5 μm thick) on slides for RNA extraction. For FFPE samples, after scraping the tumor tissue on 15 slides with a razor blade, the samples were dewaxed using Qiagen dewaxing solution (Qiagen, Germany, Cat#19093), and RNA was extracted using Qiagen RNeasy FFPE kit (Qiagen, Hilden, Germany, Cat#73504). RNA yield and purity were determined using NanoDrop (Thermo Scientifc) and Qubit Fluorometer (Thermo Fisher Scientific). RNA quality was analyzed using Fragment Analyzer System (Agilent). Total RNA libraries were prepared using Illumina stranded Total RNA prep ligation and ribo-zero plus kit (Illumina, 20040525), with an initial input of 200 ng total RNA. Library size and quality were confirmed on a fragment analyzer system (Agilent). The KAPA quantitative kit (KAPA Biosystems, Roche) of the Illumina platform was used to quantify the library. Samples were pooled in an equimolar manner. The 10pb double index library was sequenced using a 74 base length read chemistry in a double-end mode on a NextSeq 550 instrument (Illumina). For each patient, the FASTQ raw file was trimmed using Trimgalore and then aligned with the hg38 genome using STAR. PCR duplicates were removed using MarkDuplicates (PicardTools). Genes were quantified using Htseq-counts (HTSeq), and the counts were standardized to TPM (transcripts per million per kilobase).

[0172] 1.9 Statistical analysis

[0173] The sample size for animal studies was guided by previous mouse studies in our laboratory. Tumor growth, flow cytometry, and survival data were analyzed using GraphPad Prism software. For comparisons between groups, Student T-test, MannWhitney test, and normality were assessed using the Shapiro-Wilk normality test. The Spearman test was used for correlation curve analysis. Overall survival (OS) and progression-free survival (PFS) of patients were calculated from the start of immunotherapy. Survival curves were compared using the log-rank test (Mantel-Cox). For all determinations, P<0.05 was considered statistically significant, and individual P values ​​were expressed as follows: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Statistical analysis of single-cell RNA sequencing data is described in the corresponding materials and methods paragraph above.

[0174] 2. Results

[0175] 2.1 Colon tumors exert systemic anti-metastatic effects that can be predicted by immune microenvironment scoring.

[0176] The inventors implanted MC38-luc cells into the liver (IH) of mice as the primary metastatic site, with or without simultaneous implantation of MC38 IC (intracolonic) of the primary tumor. Tumor progression was monitored by measuring bioluminescent emission that was positively correlated with tumor size (G. Trimaglio, et al. Oncoimmunology. 9, 1790125 (2020), C. Devaud, et al. Cancer Immunol. Immunother. CII. 62, 1199–1210 (2013)).

[0177] All mice implanted with IH tumors alone developed lethal liver tumors, however, when injected with IC tumors in addition to IH tumors (IH+IC group), half of the mice rejected both IH and IC tumors between days 8 and 14, despite similar initial tumor incidence ( Figure 1 , A and B). IH tumor regression was only observed when the concomitant IC tumor also regressed, indicating that IC tumor rejection exerted an anti-metastatic effect and triggered concomitant rejection of distal liver tumors. The inventors previously demonstrated that MC38 colon tumor rejection depends on anti-tumor immune response, meaning that the anti-metastatic effect may be immune-dependent (G. Trimaglio, A.-F. et al. Oncoimmunology. 9, 1790125 (2020). In addition, when concomitant tumors were injected at locations other than IC, such as intrarenal (IK), IH tumor rejection was not observed, indicating that the occurrence of spontaneous tumor rejection and the ensuing anti-metastatic effect are colon-specific.

[0178] To assess the breadth of the systemic colon antimetastatic effect, the inventors implanted MC38-tumors subcutaneously (SC) instead of IH, with or without IC tumors. All control mice that received SC alone developed lethal SC tumors. When injected SC and IC simultaneously, 66% of the mice spontaneously rejected both IC and SC tumors ( Figure 1 C). That is, when IC tumors develop, SC tumors also develop, and rejection of IC tumors systemically affects distant SC tumors ( Figure 1 C). However, in contrast to rejected IH tumors, no recurrence occurred during long-term follow-up ( Figure 1 A), SC tumor rejection was prolonged in 42% of mice, whereas relapse occurred in 24% of mice ( Figure 1 C). These results further confirm that the antimetastatic effect is dependent on IC tumor rejection and suggest that it can also affect distant tumors in locations other than IH. The differences between IH and SC rejection signatures can infer that differences between the skin and liver immune microenvironments can locally influence the colon imprinting immune mechanisms underlying systemic antimetastatic effects (JM Pitt, et al. Immunity. 44, 1255–1269 (2016). In summary, these results demonstrate an immune-dependent, systemic, colon-specific antimetastatic effect that can affect distant tumors.

[0179] (D) Analysis of tumor-infiltrating immune cell populations from day 10 samples showed that CD8 + Considering the increase in the infiltration of T lymphocytes, + The central anti-tumor role of T lymphocytes in CRC immune response (J. Galon, et al. Science. 313, 1960–1964 (2006)), the inventors based on the tumor infiltrating CD45 + CD8 + The proportion of T cells separated mice from the IH+IC group. When affected by IC tumors, mice with a high proportion of CD8 + IH tumors with T lymphocytes showed a high proportion of DCs and a low proportion of macrophages. The inventors considered that IH tumors were infiltrated by CD8 + The proportion of T cells, DCs and macrophages was used to calculate the microenvironment score (ME score) ( Figure 2 A) CD8 + The proportions of TILs and DCs were positively correlated with the ME score, while the proportion of macrophages was negatively correlated with the ME score, and all correlations were established in IH tumors and concomitant IC tumors for which ME scores were calculated ( Figure 2 , BD). CD8 T cell exhaustion was negatively correlated with ME score ( Figure 2E). In addition, high ME scores were associated with increased CD8 / Treg ratios, and conventional (Foxp3neg) CD4 + The increased proportion of T cells (Tconv) and increased MHC-II expression in macrophages and the decreased proportion of MDSC and decreased CD80 expression in macrophages were associated with the ME score. At early time points, i.e., days 7 and 9, there was a significant negative correlation between the ME score and IH tumor bioluminescence emission ( Figure 2 F), suggesting that ME score may be an early predictor of progression and rejection of CRC. Indeed, low ME scores were significantly associated with an early increase in IH tumor bioluminescence, implying future progression of CRC outcome, whereas high ME scores were associated with a decrease in bioluminescence, potentially indicating the onset of tumor elimination ( Figure 2 G). Notably, IH implantation of multiple syngeneic tumor cell lines alone resulted in tumor progression in all implanted mice, and subsequent tumors systematically exhibited low ME scores ( Figure 2 H).

[0180] To clearly confirm the predictive value of the ME score, the SC+IC model ( Figure 1 C), the inventors implanted two SC tumors into mice, one of which was surgically removed on day 10 for evaluation of ME score, while the other was monitored for tumor growth in the contralateral flank. The latter could distinguish the three groups of mice observed previously (i.e., progression, rejection-relapse, and rejection groups, Figure 1 C) Based on these arrangements, tumors removed from the same mouse for immune infiltration analysis were named Future Progression, Future Rejection-Relapse, and Future Rejection. Future Rejection SC tumors were CD8 + T cells and DCs were highly infiltrated and showed reduced infiltration of macrophages, with high ME scores. + PD-1 expression in T cells, CD8 / Treg ratio, and Tconv infiltration in future-rejecting SC tumors resembled high ME score IH tumors ( Figure 2 E), we did not observe a complete parallel in immune infiltration between IH and SC tumors affected by distant IC tumors. All tumors of future progression type showed low ME scores, while ME scores were higher in tumors of future rejection-relapse and future rejection groups ( Figure 2 I). Finally, for IH tumors ( Figure 2H), all individual SC tumors generated by implantation of other isogenic cell lines, which never resulted in spontaneous regression (L. Tran, et al. Cancer Immunol. Res. 5, 1141–1151 (2017); C. Devaud, et al. Mol. Ther. J. Am. Soc. Gene Ther. 22, 18–27 (2014); T. Kimura, et al. Cancer Sci. 109, 3993–4002 (2018)), all showed low ME scores ( Figure 2 J) In conclusion, the present results reveal a colon-dependent and immune-mediated anti-metastatic effect that can be predicted by the ME score.

[0181] 2.2 The tumor-specific systemic immune response triggered by the colon is associated with anti-metastatic effects.

[0182] Given that effective anticancer immune surveillance requires systemic immunity (MHSpitzer, et al. Cell. 168, 487-502.e15 (2017)), and that anti-metastatic effects of colon control form distant tumor sites, the inventors analyzed peripheral (non-tumor) immune responses in spleen, blood, and lymph nodes (LN). In IH+IC mice with high ME score tumors, an increased proportion of CD8 + T cells. Although similar to CD8 + Compared with TIL, in peripheral CD8 + Lower levels of exhaustion were detected in T cells ( Figure 2 E), but in mice with low ME score tumors + There appeared to be an increase in immune checkpoint expression in T cells. Total CD8 + The proportion of T cells, which may have a low ME score in the early stage, did not show an increase in proportion over time, either in the tumor or in the periphery. In addition, as in the early low ME score tumors, CD8 + T cells remain exhausted at high levels.

[0183] MC38 colon tumors do not induce rejection of distal B16F10 IH tumors ( Figure 3 A), indicating that the anti-metastatic effect depends on antigen specificity, possibly through colon-derived tumor-specific T cells. Therefore, the inventors used fluorescent MHC-peptide dextramers to assess tumor infiltration and systemic MC38 neoantigen-specific CD8 in mice bearing low and high ME score tumors. +T cells (M. Yadav, et al. Nature. 515, 572–576 (2014)). In high ME score IH and IC tumors, CD8 + The frequency of dextramer+ cells in T cells increased ( Figure 3 , B, and C), and were positively correlated with ME scores ( Figure 3 D), indicating MC38-specific CD8 + T cells are important in IH and IC tumor rejection. Tumor-specific CD8 + TILs showed high expression of immune checkpoints, indicating that their antitumor function was suppressed, and accumulated in late-stage progressive tumors without mediating tumor rejection. + No significant differences were detected between IH+IC mice bearing low or high ME score tumors when looking at the proportion of CD8 T cells in infiltrating IH tumors. + The proportion of dextramer+ cells in T cells was positively correlated with that detected in IC tumors and peripheral locations including spleen, blood, and mesenteric LNs ( Figure 3 E) Tumor-specific CD8 in IH tumors + The proportion of T cells was not correlated with its proportion in liver LNs ( Figure 3 E), further emphasizing the involvement of CD8 + The T cells may originate from the colon.

[0184] 2.3 Anti-metastatic effect in colon involves tumor-specific α4β7 + CD8 + T lymphocytes

[0185] The inventors used single-cell RNA sequencing to sort the CD45 + Cells were subjected to high-dimensional profiling to assess the transcriptional profiles of immune populations infiltrating low, intermediate, and high ME score IH MC38 tumors as well as IH control tumors alone.

[0186] D10 IH MC38-tumors from IH+IC mice were analyzed by flow cytometry and selected to pool 7 high ME scores, 7 medium ME scores, and 7 low ME scores. Seven tumors from IH alone control mice were also pooled. Single-cell RNA sequencing analysis was performed on CD45 cells isolated from the subsequent 4 samples, resulting in 2500-5600 analyzable cells per sample, with each cell covered by approximately 20,000 reads.

[0187] DCs in high ME score tumors are likely to be conventional (c)DC1 (expressing Clec9a) and plasmacytoid (p)DC (expressing Siglech, Ly6c2, Bst2, Tcf4, Irf8, and Bcl11a).

[0188] The inventors identified six macrophage clusters (mΦ_c) and one monocyte cluster. In control and low ME score tumors, approximately 30% of CD45 + Tumor infiltrating cells were mΦ_c1, reaching 60% when mΦ_c2 and mΦ_c3 were added. mΦ_c1, mΦ_c2, and mΦ_c3 expressed the highest levels of immunosuppressive type 2 macrophage-related markers, including Tgm2, Chil3 (mainly in mΦ_c1 and monocytes), Fn1, Tgfb1, Tgfbi, and Arg1 and Mmp12 (higher in mΦ_c3). MΦ_c4 was CD45 in medium and high ME score tumors. + The only cluster that was increased among tumor-infiltrating cells, which were negative for Cx3cr1, expressed high levels of Cd51, Clec4f, Vsig4, and Timd4, all markers for mouse Kupffer cells.

[0189] Among the lymphoid cell clusters, NK_c1 expressed cytotoxicity-related genes (Gzma, Prf1, Eomes, Nkg7, Ncr1, Gzmb), while NK_c2 expressed Xcl1. Tregs, which infiltrated high control and low ME score tumors, expressed high levels of Gzmb, Ctla4, and Il10, supporting their high suppressive capacity in these tumors.

[0190] High ME score tumors were mainly infiltrated by CD8_c1, which expressed high levels of activation and cytotoxic markers, including Ccl5, Itgb1, Ahnak, Cx3cr1, and Gzmm. CD8_c3, also a highly infiltrative high ME score tumor, expressed high levels of CD8 + Genes related to T cell effector and cytotoxic functions (Gzmb, Id2, Cd226, Ccl5, Cxcr3, Tnfsf10, Ccl3) Figure 4 D). Finally, CD8_c5 is characterized by the expression of naive T cell markers (Sell, Il7r, Tcf7, Lef1, Klf2, Ccr7, Id3) as well as typical T cell intestinal homing markers including Itgae and Ccr9. In contrast, CD8_c2 represents the main CD8 +T cell subsets infiltrated control and low ME score tumors and expressed the highest levels of exhaustion markers (Lag3, Pdcd1, Ctla4, Havcr2, Tox, Nr4a2, Nfat5, Batf, Prdm1) in addition to increased expression of cytotoxic markers (Tnfrsf9, Prf1, Nkg7, Ifngr1, Tnfrsf18). Low ME score tumors were also highly infiltrated by proliferating cells expressing Mki67 (CD8_c4) and also expressed genes associated with dividing cells ( Figure 4 D).

[0191] The inventors identified 12 transcriptomes corresponding to lymphoid and myeloid cell subsets, including components from the ME score ( Figure 4 , A and B). The inventors confirmed at the transcriptional level that the ratio of ME score components to RNA ME scores included CD8 + Increased T cell and DC infiltration and decreased macrophage proportion ( Figure 4 B). These analyses revealed that the proportions of other immune cell populations varied with ME score. That is, the proportions of anti-tumor B, Tconv, NK, and NKT cells were higher in intermediate and high ME score tumors compared with low ME score and control tumors ( Figure 4 B). In-depth analysis of the identified cell populations revealed that DCs in high ME score tumors were enriched in conventional (c) DC1 and plasmacytoid (p) DC subsets. In addition, the inventors identified macrophage clusters that highly infiltrated low ME score tumors ( c2 and c3), and expressed the highest levels of markers associated with immunosuppressive type 2 macrophages. Clustering of T and NK cells revealed seven CD8 + T cell clusters, including CD8_c1, CD8_c3, and CD8_c5, were increased in tumors with intermediate to high ME scores ( Figure 4 , C and D). Both clusters of NK and NKT cells were more abundant in high ME score tumors, while Treg and Tconv infiltration was more abundant in control and low ME score tumors compared with high ME score tumors. High expression of CD8_c1 and CD8_c3 was associated with CD8 +Genes related to T cell activation and effector cytotoxic function, including Ccl5, Itgb1, Gzmb, and Id2 (AM vander Leun, Det al. Nat. Rev. Cancer. 20, 218–232 (2020); D. Matza, et al. Proc. Natl. Acad. Sci. USA 106, 9785–9790 (2009); BP Nicolet, et al. Proc. Natl. Acad. Sci. USA 117, 6686–6696 (2020)), while CD8_c2 (the major CD8 cluster infiltrating control and low ME score tumors) showed depleted CD8 + Characteristics of T cells (Z. Chen, et al. Immunity. 51, 840-855.e5 (2019); N. Chihara, et al. Nature. 558, 454–459 (2018)) ( Figure 4 D). CD8_c1 expressed Itga4 and Itgb7 at higher levels than other CD8 clusters ( Figure 4 E).

[0192] Itga4 and Itgb7 encode α4β7 integrins, whose expression in T cells is restricted to T cells primed by the gut-associated lymphoid tissue (GALT) (JR Mora, et al. Nature. 424, 88–93 (2003)), suggesting that CD8_c1 cells in high ME score IH tumors originate from the colon. Integrin α4β7 has been described as an enterotropic molecule because it is only acquired by T cells upon activation of intestinal DCs in mesenteric LNs (N. Wagner, J. Lohlert, EJ Kunkel, K. Ley, K. Rajewsky, W. Muller, Critical role for P7 integrins in formation of the gut-associated lymphoid tissue. 382, ​​5 (1996); C. Berlin, et al. Cell. 74, 185–195 (1993); A. Stock, et al. Cell Biol. 91, 240–249 (2013)). It binds to mucosal addressable cell adhesion molecule-1 (MAdCAM-1), which is constitutively expressed on high endothelial venules (HEV) of the GALT, including Peyer's patches and mesenteric (m) LNs, and on postcapillary venules of the intestinal lamina propria (C. Berlin, et al. Cell. 74, 185–195 (1993)). Compared with all lymphoid clusters, the expression of Itga4 and Itgb7 genes was most prominent in cytotoxic CD8_c1 and CD8_c3 and NK_c1 of high ME score tumors, while they were mainly expressed by exhausted CD8_c2 and Treg in low ME score tumors ( Figure 4 , F and G). The inventors extended these findings at the protein level by performing flow cytometric analysis, showing that tumor antigen-specific CD8 + The expression of α4β7 in T cells is high ( Figure 4 H and I), and revealed that circulating CD8 + Increased expression of α4β7 in T cells ( Figure 4 J and K). Furthermore, although increased proportions of Treg and NK cells were detected in low- and high-ME score tumors, respectively, no difference in α4β7 integrin expression was detected in these cells between low- and high-ME score tumors, confirming the single-cell RNA sequencing results ( Figure 4 F). The above results revealed that α4β7 + CD8 +T cells may play a key role in the spontaneous rejection of colon tumors and the concomitant anti-metastatic effects. Treatment with depleting anti-α4β7 mAbs resulted in a decrease in α4β7 in both tumors and peripheral compartments of treated mice compared with untreated control mice. + The proportion of cells decreased, and the survival of IC+IH mice was significantly reduced ( Figure 4 , L and M).

[0193] These results support the concept that colon tumors are able to generate specific effector α4β7 + CD8 + The anti-tumor immune response of T cells, when they migrate to liver metastases, mediates the elimination of metastatic tumors.

[0194] 2.4 Colon Tumors and α4β7 + CD8 + T cells confer therapeutic benefit to immune checkpoint blockade-mediated control of liver metastases.

[0195] Liver metastases are particularly resistant to immunotherapy, significantly reducing ICB efficacy. Thus, in this model, MC38 liver metastases systemically gave rise to progressive, lethal tumors with limited response to anti-PD-L1 proof-of-concept immunotherapy, whereas IC-localized MC38 tumors were completely sensitive to anti-PD-L1 therapy ( Figure 5 , A and B). IH+IC mice had prolonged survival compared with IH mice treated with anti-PD-L1 ( Figure 5 , A and B) and a reduction in tumor size, confirming that the presence of a distant IC primary tumor is more effective in initiating IH metastatic rejection than immunotherapy. The highest efficacy of immunotherapy was observed when mice with IH tumors also had IC tumors during treatment ( Figure 5 , A and B), indicating that IC tumors play a beneficial role in the response of IH tumors to immunotherapy. The efficacy of ICB immunotherapy depends on pre-existing antitumor effects and memory responses ((ADWaldman, et al. Nat. Rev. Immunol., 1–18 (2020)). To study the memory immune response generated by IC tumors, the inventors re-challenged the tumor rejection group of IH+IC mice by IH implantation of MC38 cells, which remained tumor-free for at least 41 days. Although all mice were initially infected with tumors, 100% of the mice quickly and completely rejected the IH tumors, supporting the persistence of long-term memory responses after the initial rejection. Rejection of IC tumors implanted in the absence of concomitant IH tumors was sufficient to protect mice from IH tumor re-challenge ( Figure 5In these rechallenged rejecting mice, MC38 neoantigen-specific CD8 T cells were detected in the liver, rejected IH tumor scars, and in the spleen, blood, and liver LNs compared to the same compartments analyzed at D10 in IH+IC mice bearing low- and high-ME score tumors. + The proportion of T cells increased ( Figure 5 F), indicating their involvement in protecting the liver from tumor attack.

[0196] To investigate the relationship between ME score and α4β7 expression in patients with immunotherapy + CD8 + T cells, the inventors analyzed the metastatic lesions of MSS mCRC patients treated with ICB combined with targeted agents by RNA sequencing ( Figure 5 G). Seven of the 17 patients in the cohort achieved clinical benefit ( Figure 5 G) Expression levels of ITGB7 and ITGA4 encoding human α4β7 integrin are correlated with CD8 + The expression of T cell toxicity and exhaustion-related genes was positively correlated, and according to previous descriptions, the expression levels were increased in primary lesions that responded to immunotherapy (TN Gide, et al. Cancer Cell. 35, 238-255.e6 (2019); C.-C. et al. Cancer Immunol. Res. 8, 869–882 (2020). In fact, in patients who responded to treatment, the proportion of metastatic tumors expressing ITGB7 and ITGA4 was higher than that of patients who did not respond to treatment, and the expression levels of both genes were higher in responding metastases ( Figure 5 H). In addition, patients expressing higher levels of ITGA4 in metastases had increased progression-free survival (PFS), and the same trend was found for ITGB7 ( Figure 5 I), indicating that CD8 + T cells play a beneficial role in the patient's response to immunotherapy. Finally, the inventors found that pre-treatment circulating CD8 + α4β7 expression in T cells + The proportion of cells increased ( Figure 5 , J and K). Circulating α4β7 + CD8 + Increased proportion of T cells was associated with improved overall survival (OS) ( Figure 5 L). Data from clinical cohorts support conclusions from preclinical models regarding the effect of colon-derived α4β7 + CD8 +T cells are involved in metastatic response to immunotherapy and patient outcome.

[0197] Together, these results suggest that α4β7 + CD8 + Colon-primed immune responses of T cells provide systemic protection in immunotherapy settings.

[0198] discuss

[0199] This study reveals the potential of mucosal immunity to exert systemic functions on intestinal tumors and to shape the extraintestinal tumor microenvironment and outcome. The dual tumor model, in which liver metastases thus regress as a colon-dependent immune-mediated process, lays the foundation for this concept. The colon memory immune response protects the liver from tumor attack, and the ability of colon tumors to increase the response of liver metastases to immunotherapy further supports the anti-metastatic effect of the colon. In liver metastases, the ME score reflecting the anti-metastatic effect is determined by anti-tumor and pro-tumor immune cell populations. In CD8 + Among the T cell population, enterotropic cells expressing α4β7 integrin are key factors in the anti-metastatic effect of the colon. The intestinal tropism of this lymphocyte subset has been previously determined, which can be explained by the intestinal vascular-specific expression of the α4β7 integrin ligand MAdCAM-1 (N. Wagner, J. Lohlert, EJ Kunkel, K. Ley, K. Rajewsky, W. Muller, Critical role for P7 integrins information of the gut-associated lymphoid tissue. 382, ​​5 (1996); C. Berlin, et al. Cell. 74, 185–195 (1993); M. Briskin, et al. Am. J. Pathol. 151, 97–110 (1997)). Considering its intestinal metastasis, α4β7 has been widely studied. + CD8 +T cells play a role in driving pathological inflammation in inflammatory bowel disease (IBD) (PE Hesterberg, et al. Gastroenterology. 111, 1373–1380 (1996); DK Podolsky. N. Engl. J. Med. 325, 1008–1016 (1991); DK Podolsky, et al. J. Clin. Invest. 92, 372–380 (1993)). Their impact on gastrointestinal cancers remains virtually unexplored. Nevertheless, two recent studies described the impact of cells expressing β7 integrin in promoting inflammatory CRC tumorigenesis (S. Das, et al. PloS One. 13, e0204181 (2018)) and controlling the growth of established primary CRC tumors (Y. Zhang, R. et al. Cancer Immunol. Res. 9, 967–980 (2021)), without exploring the role of intestinal-derived α4β7 + CD8 + The potential role of T lymphocytes in cancer immune surveillance. According to this study, α4β7 + CD8 + T lymphocyte migration to the liver, IBD-related extraintestinal symptoms (including incidental liver inflammation) and inflammatory α4β7 + CD8 + The influx of T cells is related to the destruction of the T cells (D. H. Adams, et al. Nat. Rev. Immunol. 6, 244–251 (2006); B. Eksteen, et al. J. Exp. Med. 200, 1511–1517 (2004)). + CD8 + The mechanism of T cell migration to the liver remains unclear, but pathological upregulation of MAdCAM-1 in liver endothelial cells is induced (D. H. Adams, et al. Nat. Rev. Immunol. 6, 244–251 (2006)). + CD8 +T cells may transfer to extraintestinal tumors, highlighting the key role of local intestinal immunity in cancer immunosurveillance. The intestine contains the largest number of immune cells in the body and has long been considered to be a host intestinal-restricted immune process (S. Shalapour, et al. Annu. Rev. Immunol. 38, 649–671 (2020)). However, increasing evidence shows that the intestine has an impact on physiological and pathological processes throughout the body, for example, depending on the intestinal microbiota or dietary components (A. Albillos et al. J. Hepatol. 72, 558–577 (2020); D. H. Adams, et al. Nat. Rev. Immunol. 6, 244–251 (2006); B. Eksteen, A et al. J. Exp. Med. 200, 1511–1517 (2004)). The results of this study provide new insights into the extraintestinal impact of the intestine through mucosal immune cell populations involved in systemic cancer immunosurveillance.

[0200] In preclinical settings, spontaneous rejection of implanted tumors was not observed in any location other than the colon (G. Trimaglio, et al. Oncoimmunology. 9, 1790125 (2020), C. Devaud, et al. Mol. Ther. J. Am. Soc. Gene Ther. 22, 18–27 (2014)), emphasizing the intestinal tropism of α4β7 + CD8 + T cells play a key role in this phenomenon and a potent role in the subsequent anti-metastatic effect. + CD8 + T cells may represent a biomarker of systemic anti-metastatic effects of colonic origin. + CD8 + T cells migrate from concomitant colon tumors to liver metastases, increasing the latter's response to ICB, supporting α4β7 + CD8 +Research on T cells as predictive biomarkers for the response of cancer patients to immunotherapy. Consistent with this hypothesis, high expression of the ITGB7 gene in tumors is associated with response to treatment and survival in patients with lung and urothelial carcinoma receiving ICB (Y. Zhang, et al. Cancer Immunol. Res. 9, 967–980 (2021)). ICB has poor therapeutic effect on patients with mCRC (K. Ganesh, et al. Nat. Rev. Gastroenterol. Hepatol. 16, 361–375 (2019)), and its use in the neoadjuvant setting of early stage CRC is associated with pathological response (M. Chalabi, et al. Nat. Med. 26, 566–576 (2020)). In this case, α4β7 + CD8 + Evaluation of T cells will determine their role in tumor rejection and their significance as response biomarkers. This will also provide new insights into T cells carrying α4β7-rich + CD8 + The results of this study provide a new basis for neoadjuvant immunotherapy of advanced CRC patients with colon tumors using T cells, and ICB will enhance their anti-metastatic potential. Finally, based on this model, a vaccine strategy to induce tumor-specific enterotropic α4β7 + CD8 + T cells (SI Hammerschmidt, et al. J. Clin. Invest. 121, 3051–3061 (2011)), can enhance tumor rejection and sensitivity to ICB in primary and metastatic colon sites. Given the good correlation between response to ICB and ITGB7 gene expression in other tumor types, the relevance of these strategies can be extended beyond CRC (Y. Zhang, et al. Cancer Immunol. Res. 9, 967–980 (2021)).

Claims

1. A method for determining the response of metastases to immunotherapy in a patient with metastatic colorectal cancer, the method comprising: i) Determine the CD8 + The density of T cells, dendritic cells and macrophages, ii) Calculate the corresponding CD8 + The microenvironment score (ME score) is the ratio of the density of T cells and dendritic cells to the density of macrophages. A higher ME score value compared to the control value indicates that the patient's metastasis is responsive to immunotherapy.

2. The method of claim 1, further comprising: i) determining the density of B cells, NK cells and / or regulatory T cells in a patient sample, ii) CD8-based + The microenvironment score (ME score) is calculated by comparing the density of T cells, dendritic cells, B cells and / or NK cells to the density of macrophages and preferably regulatory T cells.

3. The method of claim 1 or 2, wherein the CD8 + T cells are enterotropic CD8 + T cells, preferably α4β7 + CD8 + T cells.

4. A method for determining the response of metastases to immunotherapy in a patient with metastatic colorectal cancer, the method comprising determining the presence of colon-derived T cells, preferably α4β7 T cells, in a patient sample. + CD8 + The density of T cells, wherein the colon-derived T cells, preferably α4β7 + CD8 + A higher density of T cells indicated that the patient's transfer was responsive to immunotherapy.

5. The method according to any one of claims 1 to 4, wherein the dendritic cells are CD11c + cell.

6. The method according to any one of claims 1 to 5, wherein the macrophages are CD68 + cell.

7. The method according to any one of claims 1-6, wherein the cell density is determined by flow cytometry, immunofluorescence, immunohistochemistry, single cell RNA sequencing, bulk RNA sequencing and qRT-PCR.

8. The method according to any one of claims 1 to 7, wherein the patient sample is a tumor tissue or a biological fluid sample, preferably a metastatic tumor tissue or a patient blood sample, such as a patient peripheral blood mononuclear cells.

9. An immunotherapy for treating metastatic colorectal cancer in a patient in need thereof, wherein the immunotherapy is administered to the patient who has previously been identified as having metastases responsive to the immunotherapy according to the method of any one of claims 1-8.

10. A pharmaceutical composition comprising an immunostimulatory agent for use in treating metastatic colorectal cancer in a patient in need thereof, wherein the immunostimulatory agent is administered to a patient who has previously been identified as having metastases that are unresponsive to immunotherapy according to the method of any one of claims 1-9.

11. The pharmaceutical composition for use according to claim 10, wherein the immunostimulant is a colorectal cancer vaccine, preferably capable of inducing tumor antigen-specific α4β7 + CD8 + T cells.

12. The pharmaceutical composition for use thereof according to claim 10 or 11, comprising retinoic acid.

13. A pharmaceutical composition comprising an immunostimulant, preferably a colorectal cancer vaccine and retinoic acid, for use in treating metastatic colorectal cancer in a patient in need thereof.

14. A kit for determining the response of metastasis to immunotherapy in patients with metastatic colorectal cancer, comprising anti-α4β7 and anti-CD8 antibodies, preferably anti-α4β7, anti-CD8, anti-CD11c and / or anti-CD68 antibodies.

15. A kit for determining the response of metastasis to immunotherapy in patients with metastatic colorectal cancer, comprising a primer pair for amplifying CD8 + At least one genetic marker of T cells, preferably CD8 + At least one gene marker of T cells and α4β7 + At least one gene marker of cells, more preferably CD8 + At least one gene marker of T cells, at least one gene marker of dendritic cells and at least one gene marker of macrophages, more preferably CD8 + At least one gene marker of T cells and α4β7 + At least one gene marker of cells, at least one gene marker of dendritic cells and at least one gene marker of macrophages.

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