Biomarker of immunosuppressive fibroblast populations, ANTXR1, and its use in predicting response to immunotherapy

Abstract

The present invention provides an in vitro method for detecting immunosuppressive fibroblasts, in particular cancer-associated fibroblasts (CAFs), in a cancer sample from a subject suffering from cancer, wherein the method comprises detecting ANTXR1 + fibroblasts in a cancer sample from the patient The present invention also relates to an in vitro method for predicting the response of a subject suffering from cancer to an immunotherapy treatment, an immunotherapy treatment for treating cancer in a patient, the use of ANTXR1 as a biomarker for identifying immunosuppressive fibroblasts, in particular immunosuppressive CAFs, an agent targeting ANTXR1 + fibroblasts for treating cancer in a patient, and a product or kit comprising: a) an agent targeting ANTXR1 + fibroblasts and b) an immunotherapy treatment.

Description

Technical Field

[0001] This invention relates to the medical field, particularly oncology. It provides novel biomarkers for immunosuppressive cell populations and their applications. Background Technology

[0002] Cancer has become the second leading cause of death worldwide, causing 9.6 million deaths in 2018. Its prevalence is also extremely high, with over 15 million new cases diagnosed annually, and this number is projected to rise by approximately 70% over the next 20 years.

[0003] There are many treatment options available for cancer today, including surgery, chemotherapy, radiation therapy, hormone therapy, targeted therapy, and palliative care. The best treatment choice for a patient depends on the type, location, and grade of the cancer, as well as the patient's health and preferences.

[0004] Over the past few decades, immunotherapy has become an important part of cancer treatment strategies. Cancer immunotherapy relies on utilizing the immune system to treat cancer. Among the various immunotherapies that have been developed, immune checkpoint inhibitor therapy has shown particular promise. However, despite encouraging results, many patients with advanced cancer do not respond to immune checkpoint inhibitors, and the mechanisms of primary resistance are poorly understood. In particular, some cancers develop an immunosuppressive microenvironment, leading to resistance to immunotherapy.

[0005] Therefore, it is necessary to identify biomarkers that can reliably distinguish between responding and non-responding patients before starting treatment in order to select patients who are likely to benefit from immuno-oncology drugs.

[0006] Cancer-associated fibroblasts (CAFs) are an abundant component of cancer, playing a crucial role in promoting tumorigenesis. CAFs are now recognized as heterogeneous, and different subsets can be defined based on the expression of specific biomarkers. Currently, four subsets of CAFs have been identified in human breast and ovarian cancers, termed CAF-S1 to CAF-S4 (Costa A et al., Cancer Cell 2018; 33(3):463-79 e10). While CAF-S2 and CAF-S3 fibroblasts are detectable in healthy tissues and reminiscent of normal fibroblasts, CAF-S1 and CAF-S4 myofibroblasts are confined to cancerous and metastatic lymph nodes. Both CAF-S1 and CAF-S4 promote metastasis through complementary mechanisms. In contrast, while CAF-S1 promotes immunosuppression in human cancers, CAF-S4 does not. CAF subgroups remain heterogeneous, thus requiring the identification of CAFs that play a specific role in primary resistance to immunotherapy in cancer patients, particularly new biomarkers for detecting immunosuppressive CAFs in cancer.

[0007] New strategies are still needed to overcome the immunosuppressive environment, making immunotherapy, especially immune checkpoint inhibitor therapy, more effective and available to all patients.

[0008] This invention seeks to satisfy these and other needs. Summary of the Invention

[0009] Cancer is a systemic disease comprising multiple components, including both tumor cells themselves and host stromal cells. It is now clear that stromal cells within the tumor microenvironment play a crucial role in cancer development. The cancer stroma includes fibroblasts, particularly cancer-associated fibroblasts (CAFs), vascular endothelial cells, immune cells, and the extracellular matrix. CAFs are the most abundant component of the tumor stroma, constituting its bulk and influencing the tumor microenvironment, thereby promoting cancer initiation, angiogenesis, invasion, and metastasis.

[0010] The inventors have discovered novel CAF subsets that play a crucial role in establishing an immunosuppressive microenvironment at the tumor site. The inventors used scRNA-seq to address the heterogeneity of CAF-S1 immunosuppressive subsets and identified eight distinct CAF-S1 clusters. Three of these CAF-S1 clusters (1, 2, 5) belong to the inflammatory (“iCAF”) subgroup, and five CAF-S1 clusters (0, 3, 4, 6, 7) belong to the myofibroblast (“myCAF”) subgroup. The iCAF and myCAF subgroups have previously been described in pancreatic cancer (Ohlund D et al., J Exp Med 2017; 214(3):579-96).

[0011] The eight CAF-S1 clusters identified by the inventors are characterized by high expression of the following encoding genes: extracellular matrix (ECM) proteins (cluster 0), detoxification pathway (cluster 1), interleukin signaling (cluster 2), transforming growth factor β (TGFβ) signaling pathway (cluster 3), wound healing (cluster 4), interferon γ (cluster 5), interferon αβ (cluster 6), and actomyCAF pathway (cluster 7). Therefore, the inventors have annotated them as follows: ecm-myCAF (cluster 0), detoxification-iCAF (cluster 1), IL-iCAF (cluster 2), TGFβ-myCAF (cluster 3), wound-myCAF (cluster 4), IFNγ-iCAF (cluster 5), IFNαβ-myCAF (cluster 6), and acto-myCAF (cluster 7).

[0012] By analyzing publicly available scRNA-seq data, the presence of these CAF-S1 clusters was confirmed in head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC), demonstrating the association of these CAF-S1 clusters across different cancer types.

[0013] Furthermore, the inventors discovered that the abundance of two CAF-S1 clusters in the myCAF subgroup—namely ecm-myCAF (cluster 0) and TGFβ-myCAF (cluster 3)—was significantly correlated with the immunosuppressive environment, while the levels of detoxification-iCAF and IL-iCAF were not correlated.

[0014] In fact, it has a high level of PD-1 + CTLA-4 + and TIGIT + CD4 + T lymphocytes (which are themselves rich in Tregs) and a small fraction of CD8 + Tumors containing T lymphocytes are rich in ecm-myCAF (cluster 0) and TGFβ-myCAF (cluster 3) clusters. Interestingly, the ecm-myCAF (cluster 0) specific signature contains the LRRC15 gene, which has recently been identified as a determinant of patients responding to immunotherapy for pancreatic cancer (Dominguez et al., Cancer Discov 2020; 10(2):232-53).

[0015] Unlike ecm-myCAF (cluster 0) and TGFβ-myCAF (cluster 3), trauma-myCAF (cluster 4) is not associated with an immunosuppressive environment but is associated with highly pervasive T lymphocyte infiltration. Therefore, given the abundance of the trauma-myCAF cluster (cluster 4) in tumors of patients unresponsive to immunotherapy, the trauma-myCAF cluster may serve as a novel surrogate marker for primary resistance to this type of treatment in hyperinvasive tumors that are typically sensitive to immunotherapy. Consequently, assessing the content of specific CAF-S1 clusters within tumors at diagnostic time provides added value for predicting primary resistance to immune checkpoint inhibitors.

[0016] The inventors have specifically demonstrated that, at the time of diagnosis, these specific CAF-S1 clusters are associated with primary resistance to immunotherapy in both melanoma and NSCLC patients. In particular, ecm-myCAF (cluster 0) increases FOXP3 levels. 高 T cell fractionation and stimulation of CD4 + CD25 +The protein levels of both PD-1 and CTLA-4 on the surface of T lymphocytes were increased, which in turn increased the proportion of TGFβ-myCAF (cluster 3). This reveals a positive feedback loop between the immunosuppressive ecm-myCAF (cluster 0) and TGFβ-myCAF (cluster 3) CAF-S1 clusters and Tregs that promote immunosuppression and participate in resistance to immunotherapy. Therefore, these data support the development of strategies that combine PD-1 and / or CTLA-4 blockade with therapies targeting specific CAF-S1 cluster components to overcome primary resistance to immune checkpoint blockade.

[0017] Accordingly, the inventors' data support the identification of novel tumor samples containing ANTXR1. + FAP + A subset of patients with coronary atrophy (CAF) who exhibit immunosuppression and have resistance or poor response to immunotherapy. Therefore, targeting ANTXR1 is appropriate for this specific patient subset. + CAF thus inhibits or reduces ANTXR1 + FAP + Agents targeting the immunosuppressive effects of CAF can provide therapeutic benefits. Furthermore, combining these agents with immunotherapeutic agents can prevent the development of resistance to immunotherapies or restore their response. Additionally, even when all CAF-S1 cells express FAP, treatment with FAP inhibitors on ANTXR1... + FAP + Patients will still have greater treatment benefits because of ANTXR1 + FAP + CAF is immunosuppressive and associated with resistance to immunotherapy, while ANTXR1 + FAP - CAF is different. In this case, the benefit / risk trade-off supports this treatment in this particular subset of patients, especially in combination with immunotherapy.

[0018] Finally, the inventors identified ANTXR1 as a specific marker for CAF-S1 clusters 0, 3, and 4, allowing for the identification of CAFs associated with immunosuppressive effects.

[0019] In a first aspect, the present invention relates to an in vitro method for detecting immunosuppressive fibroblasts in a cancer sample from a cancer patient, wherein the method comprises detecting anthrax toxin receptor 1 (ANTXR1) positive fibroblasts in the cancer sample from the patient, ANTXR1 + The presence of fibroblasts is an indicator of immunosuppressive CAF.

[0020] In a second aspect, the present invention relates to an in vitro method for predicting the response of a cancer patient to an immunotherapy agent, wherein the method includes detecting ANTXR1 in a cancer sample from the patient. + Fibroblasts, wherein ANTXR1 in the cancer sample + Fibroblasts predict the patient's responsiveness to immunotherapy agents.

[0021] In a third aspect, the present invention relates to an immunotherapeutic agent for treating cancer in a patient, wherein the cancer sample provided by the patient has (a) a low amount or low percentage of ANTXR1. + Fibroblasts; or (b) no ANTXR1 + Fibroblasts.

[0022] Specifically, the method for predicting a subject's response to an immunotherapeutic agent further includes determining ANTXR1. + Percentage of fibroblasts, ANTXR1 + The percentage of fibroblasts is ANTXR1 + The number of fibroblasts relative to the total number of fibroblasts in the cancer sample or relative to the total number of cells in the cancer sample.

[0023] Specifically, ANTXR1 + Fibroblasts are FAP + ANTXR1 + Fibroblasts. Preferably, ANTXR1 + Fibroblasts are ANTXR1 + Cancer-associated fibroblasts (CAFs), preferably FAP + ANTXR1 + CAF.

[0024] More preferably, ANTXR1 + Fibroblasts were selected from: FAP + ANTXR1 + LAMP5 - SDC1 + Fibroblasts, preferably CAF; FAP + ANTXR1 + LAMP5 + SDC1 + / - Fibroblasts, preferably CAF; and ANTXR1 + SDC1 - LAMP5 - CD9 + Fibroblasts, preferably CAF.

[0025] In a fourth aspect, the present invention relates to the use of ANTXR1 as a biomarker in the identification of immunosuppressive fibroblasts, preferably immunosuppressive CAFs. The invention also relates to the use of ANTXR1 in a fibroblast population, preferably a CAF population, as a biomarker in the tumor of a cancer patient in predicting the patient's response to immunotherapy.

[0026] In a fifth aspect, the present invention relates to a targeted ANTXR1 for treating cancer in patients. + Fibroblast-derived agents, wherein the patient has ANTXR1 in a tumor sample from the patient. + FAP + Fibroblasts, preferably CAF, and the agent inhibits or reduces ANTXR1 + The immunosuppressive effect on fibroblasts, preferably the agent is selected from: (i) an anti-ANTXR1 antibody optionally conjugated with a cytotoxic drug, a multispecific molecule containing an anti-ANTXR1 moiety, an anti-ANTXR1 T cell receptor (TCR) and an anti-ANTXR1 chimeric antigen receptor (CAR), and (ii) immune cells expressing an anti-ANTXR1 TCR or an anti-ANTXR1 CAR, preferably T cells or natural killer cells; or any combination thereof.

[0027] Specifically, the target ANTXR1 + Fibroblast-specific drugs are used in combination with immunotherapeutic agents.

[0028] In a sixth aspect, the present invention relates to an FAP inhibitor for treating cancer in a patient, wherein the patient has ANTXR1 in a tumor sample from the patient. + FAP + Fibroblasts, preferably CAFs. In one particular aspect, the FAP inhibitor is used in combination with an immunotherapeutic agent.

[0029] Preferably, the FAP inhibitor is selected from: talabostat or PT-100 (CAS No. 149682-77-9, [(2R)-1-[(2S)-2-amino-3-methylbutyryl]pyrrolidone-2-yl]boronic acid), linagliptin (Tradjenta) (CAS No. 668270-12-0; 8-[(3R) FAP inhibitors with an N-(4-quinolinyl)-glycyl-(2-cyanopyrrolidine) skeleton, FAPI-02 (CAS No. 2370952-98-8; (S)-2,2',2”-(10-(2-(4-(3-((4-aminopiperidin-1-yl)-7-but-2-ynyl-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]purine-2,6-dione), FAPI-02 (CAS No. 2370952-98-8; (S)-2,2',2”-(10-(2-(4-(3-((4-))-(4-)-(5-)-(6-)-(7-)-(8 ... -((2-(2-cyanopyrrolidone-1-yl)-2-oxoethyl)carbamoyl)quinoline-6-yl)oxy)propyl)piperazin-1-yl)-2-oxoethyl-1,4,7,10-tetraazacyclododecane-1,4,7-triyl)triacetic acid), FAPI-04(CAS#2374782-02-0; (S)-2,2',2”-(10-(2-(4-(3-((4-((2 -(2-cyano-4,4-difluoropyrrolidine-1-yl)-2-oxoethyl)carbamoyl)quinoline-6-yl)oxy)propyl)piperazin-1-yl)-2-oxoethyl-1,4,7,10-tetraazacyclododecane-1,4,7-triyl)triacetic acid), and FAPI-46 (CAS No.: 2374782-04-2), peptide targeting radionuclides such as FAP-2286, and any combination thereof.

[0030] In a seventh aspect, the present invention relates to a product or kit comprising: a) targeting ANTXR1 + Fibroblast agents and a) immunotherapeutic agents, as combination preparations used simultaneously, separately or sequentially in the treatment of patients with cancer.

[0031] Specifically, the immunotherapeutic agent is selected from therapeutic treatments that stimulate the patient's immune system to attack malignant tumor cells, immunization of the patient with tumor antigens, molecules that stimulate the immune system such as cytokines, therapeutic antibodies, adoptive T-cell therapy, CAR cell therapy, immune checkpoint inhibitors, and any combination thereof, preferably immune checkpoint inhibitors.

[0032] Preferably, the checkpoint inhibitor is selected from antibodies against cytotoxic T-lymphocyte-associated protein (CTLA-4), programmed cell death protein 1 (PD-1), programmed cell death ligand (PD-L1), T-cell immune receptor with Ig and ITIM domains (TIGIT), lymphocyte activation gene 3 (LAG-3), T-cell immunoglobulin and mucin domain protein-3 (TIM-3), B and T-lymphocyte attenuation factor (BLTA), IDO1, or any combination thereof. It is more preferably selected from antibodies against CTLA-4, PD-1, PD-L1, and TIGIT or any combination thereof, and more preferably from antibodies against PD-1 or CTLA-4 or combinations thereof.

[0033] Specifically, the immunotherapeutic agent is selected from ipilimumab, nivolumab, BGB-A317, pembrolizumab, atezolizumab, avelumab, or duvalumab, BMS-986016 and epacadostat, or any combination thereof.

[0034] Specifically, the cancer is selected from prostate cancer, lung cancer, non-small cell lung cancer (NSCLC), breast cancer, gastric cancer, kidney cancer, ovarian cancer, hepatocellular carcinoma, osteosarcoma, melanoma, hypopharyngeal cancer, esophageal cancer, endometrial cancer, cervical cancer, pancreatic cancer, liver cancer, colon or colorectal cancer, adenocarcinoma, sarcoma, non-squamous cell carcinoma, squamous cell carcinoma, neuroendocrine tumors, muscle cancer, adrenal cancer, thyroid cancer, uterine cancer, skin cancer, melanoma, metastatic melanoma, bladder cancer, and head and neck cancer. Preferably, the cancer is selected from head and neck cancer, breast cancer, ovarian cancer, NSCLC, melanoma, and metastatic melanoma. More preferably, the cancer is selected from head and neck cancer, NSCLC, melanoma, and metastatic melanoma. Attached Figure Description

[0035] Figure 1 Identification of different cell clusters in CAF-S1 fibroblasts. Unified manifold approximation and projection (UMAP) of 18,296 CAF-S1 fibroblasts from 7 BC patients visualized 8 CAF-S1 clusters (0 to 7). Colors indicate the different CAF-S1 clusters defined by graph-based clustering in a space bounded by 30 first principal components.

[0036] Figure 2 Validation of the five most abundant CAF-S1 clusters in different cancer types. The percentage (%) of different clusters among CAF-S1 fibroblasts is based on FACS data. Each entry represents one patient (N=44).

[0037] Figure 3: Detection of CAF-S1 cell clusters in lung and head and neck cancers. (A) Combination of 18,296 CAF-S1 fibroblasts from BC (red, top left) and FAP from HNSCC. + Fibroblasts (data from (30), n = 603 FAPs) + UMAP plot of cells (blue, top left). Scores were calculated using the average z-score of genes that constitute the specific signature of each CAF-S1 cluster. (B) Same as (A), from NSCLC (data from (31), n ​​= 959 FAPs). + Cells, blue, top left image).

[0038] Figure 4: Correlation between CAF-S1 clusters and immune cells in breast cancer. (A) Detailed correlation curves between the two variables are shown in the figure. Each point represents one tumor (N=37). P-values ​​are from the Pearson correlation test. (B) Correlation curve between CAF-S1 cluster signature and FOXP3 in the TCGA group. Each point represents one tumor (N=1221). P-values ​​are from the Pearson correlation test. (C) Same as (B), correlation curve between CAF-S1 cluster signature and cell lysis index as defined by Rooney et al., Cell 2015;160(1-2):48-61.

[0039] Figure 5: Interaction between CAF-S1 cluster and Treg. (A) Representative histogram of FOXP3-specific mean fluorescence intensity (speMFI) (left), alone (green), or in the presence of iCAF (orange) or ecm-myCAF (red). FOXP3 was evaluated after 24 h of co-culture at a 10:1 ratio (T:CAF-S1). + Cell percentage (medium) and CD4 + CD25 + FOXP3 protein levels in T cells (right). P-values ​​are from Welch t-tests (N = 7 CAF-S1 primary cell lines for each condition; n = 3 independent experiments). (BG) is the same as (A), targeting FOXP3. + CD4 + CD25 + The following immune checkpoints in Treg cells: PD-1 (B), CTLA-4 (C), TIGIT (D), TIM3 (E), and LAG3 (F). P-values ​​were derived from Welch's t-test (N = 7 CAF-S1 primary cell lines per condition; n = 3 independent experiments). (G)CD4 + CD25 +The effect of T lymphocytes on CAF-S1 cluster identity. The dot plot shows the protein levels of CAF-S1 cluster markers on the surface of primary CAF-S1 cell lines. For each marker, surface protein levels are expressed as specific MFIs, calculated as follows: in the absence (-) or presence (+) of CD4... + CD25 + Under T cell conditions, specific MFI = MFI from specific antibody – MFI from isotype control (N = 7 CAF-S1 cell lines per condition; n = 3 independent experiments). P-values ​​were obtained from the Mann-Whitney test.

[0040] Figure 6: The effect of CAF-S1 clusters on immunotherapy resistance. (A) Gene set enrichment analysis (GSEA) was applied to RNA-Seq data from 28 pre-PD-1-treated melanomas using specific signatures from each CAF-S1 cluster, showing significant enrichment of CAF-S1 gene signatures (top 100 genes) in non-responders (N=13) compared to responders (N=15). Groups from (33). Below, same as above, for normal fibroblast signatures). GSEA analysis showed that clusters 0 (ecm-myCAF), 3 (TGFβ-myCAF), and 4 (trauma-myCAF) were significantly associated with non-responders (above), while clusters 1 (detoxification-iCAF), 2 (IL-iCAF), and 5 (IFN-iCAF) were not associated (below). (B) Expression was assessed by mean z-score of each CAF-S1 cluster signature in responders and non-responders of melanoma. (C, D) Same as (B), using normal fibroblast signature and cell lysis index. (E) Responders and non-responders were stratified by low and high expression of CAF-S1 clusters (based on the third quartile of CAF cluster z-score). (F, G) Same as (E), using normal fibroblast signature and cell lysis index. (H) Same as (A), analyzing NSCLC patient cohorts.

[0041] Figure 7. Identification of CAF-S1 clusters. (A) Representative FACS plot showing the gating strategy used to isolate CAF-S1. Cells were first gated with DAPI-EPCAM-CD45-CD31-CD235a- to exclude dead cells, epithelial cells, hematopoietic cells, endothelial cells, and erythrocytes, respectively. FAPHigh CD29Med cells were then selected as CAF-S1 fibroblasts. (B) UMAP plot of 18,296 CAF-S1 fibroblasts (as shown in Figure 7). Figure 1 The average z-score of the specific gene signatures of the five most abundant CAF-S1 clusters was shown.

[0042] Figure 8Identification of CAF-S1 cluster markers for FACS analysis and selection of CAF-S1 from HNSCC and NSCLC scRNA-seq data. A violin plot shows the expression distribution of six genes encoding the five most abundant CAF-S1 cluster-specific surface markers (RNA levels from scRNA-seq of 18,296 CAF-S1 fibroblasts from seven BC patients).

[0043] Figure 9 Correlation between CAF-S1 clusters and immune cells. A detailed correlation plot between CAF clusters and immune cells is shown (N = 37 BCs). P-values ​​are derived from the Pearson correlation test.

[0044] Figure 10. CAF-S1 properties obtained by dispersing and culturing fibroblasts isolated from tumors in plastic culture dishes. (A) Dot plot showing intracellular specific mean fluorescence intensity (speMFI) of FOXP3, PD-1, CTLA-4, and TIGIT in CD4+CD25+ T cells cultured alone (left) or in the presence of ecm-myCAF (right). P values ​​were obtained from the Mann-Whitney test (N = 4 primary CAF-S1 cell lines). (B) Box plot showing the mRNA levels of FOXP3, CTLA-4, and TIGIT in CD4+CD25+ T cells cultured alone (right) or in the presence of ecm-myCAF (left). P values ​​were obtained from DESeq2 analysis (N = 8). (C) Same as (B), for STAT and NFAT family members.

[0045] Figure 11. (A) UMAP of 18,296 CAF-S1 fibroblasts (as shown in Figure 11). Figure 1 This visualizes eight CAF-S1 clusters (0 to 7). Three clusters predictive of immunotherapy response—cluster 0 = ECM-myCAF, cluster 3 = TGFβ-myCAF, and cluster 4 = trauma-myCAF—are indicated by arrows. (B) Violin plot (left) and UMAP plot (right) show some of the most differentially expressed genes defining the CAF-S1 signature. The expression of these genes in each CAF-S1 cluster is shown using violin plots and UMAP representations. Of these most representative CAF-S1 genes, none are specifically expressed in clusters 0, 3, and 4, thus predicting immunotherapy response. Detailed Implementation

[0046] definition

[0047] As used herein, the term "cancer" or "tumor" refers to cells exhibiting typical characteristics of cancerous cells, such as uncontrolled proliferation and / or immortality, and / or metastatic potential, and / or rapid growth, and / or proliferation rate, and / or certain characteristic morphological features. The term refers to any type of malignant tumor (primary or metastatic) in any type of object. It can refer to solid tumors as well as hematopoietic system tumors.

[0048] As used herein, the term "cancer sample" refers to any sample containing tumor cells and cancer stromal cells, particularly fibroblasts such as cancer-associated fibroblasts (CAFs), derived from the subject. Cancer tissue, in addition to the extracellular matrix, is specifically composed of cancer cells and surrounding cancer stromal cells, including CAFs, vascular endothelial cells, and immune cells. Preferably, the cancer sample contains nucleic acids and / or proteins. The sample may be processed prior to use.

[0049] As used in this article, "cancer-associated fibroblasts" or "CAF" refers to fibroblasts present in the cancer stroma. They are one of the most abundant stromal components and morphologically resemble myofibroblasts. CAF is CD45 - EpCAM - CD31 - CD29 + Interstitial cells.

[0050] As used herein, the term "immunosuppressive fibroblasts" refers to fibroblasts in tumors that cause and / or contribute to immunosuppression, that is, fibroblasts that cause and / or contribute to the partial or complete suppression or inhibition of an individual's immune response to cancer cells. Optionally, the fibroblasts may be malignant, particularly in sarcomas, or normal.

[0051] As used herein, “immunosuppressive cancer-associated fibroblasts” or “immunosuppressive CAF” refers to CAFs in tumors that create and / or contribute to an immunosuppressive or immunosuppressive microenvironment, that is, CAFs that create and / or contribute to the partial or complete suppression or inhibition of an individual’s immune response to cancer cells. “Tumor microenvironment” or “TME” is the environment surrounding a tumor, including surrounding blood vessels, immune cells, fibroblasts, signaling molecules, and the extracellular matrix (ECM).

[0052] The term "immune response" refers to the action of, for example, lymphocytes, antigen-presenting cells, phagocytes, granulocytes, and soluble macromolecules (including antibodies, cytokines, and complement) produced by these cells or the liver, which results in selective damage, destruction, or elimination of invading pathogens, pathogen-infected cells or tissues, cancer cells, or normal human cells or tissues in cases of autoimmunity or pathological inflammation.

[0053] As used herein, the terms “anthrax toxin receptor 1,” “ANTXR cell adhesion molecule 1,” “ANTXR,” “ANTXR1,” “tumor endothelial marker 8,” “TEM8,” “ATR,” or “GAPO” are equivalent and refer to the product of the human ANTXR1 gene, as described, for example, under Gene ID: 84168 and UniProt Q9H6X2 reference numbers. The ANTXR1 protein plays a role in cell attachment and migration.

[0054] As used herein, the terms “fibroblast activating protein,” “FAP,” “prolyl endopeptidase FAP,” “dipeptidyl peptidase FAP,” “surface-expressed protease,” “Sepras,” “serine integrated membrane protease,” “SIMP,” “integrated membrane serine protease,” and “proline post-lyase” are used interchangeably to refer to the product of the human FAP gene, as described, for example, under GeneID:2191 and UniProt Q12884 reference numbers. FAP is a cell surface glycoprotein serine protease involved in the degradation of the extracellular matrix and in many cellular processes, including tissue remodeling, fibrosis, wound healing, inflammation, and tumor growth.

[0055] As used herein, the terms “lysosome-associated membrane glycoprotein 5,” “lysosome-associated membrane protein 5,” “LAMP5,” “brain and dendritic cell-associated LAMP,” and “brain-associated LAMP-like protein” are equivalent and refer to the product of the human LAMP5 gene, as described, for example, under reference numbers Gene ID 24141 and UniProt Q9UJQ1.

[0056] As used herein, the terms “co-glycan-1,” “SDC1,” “SYND1,” and “CD138” are used interchangeably and refer to the product of the human SDC1 gene, as described, for example, under GeneID:6382 and UniProt P18827 reference numbers. SDC1 is a cell surface proteoglycan that combines heparan sulfate and chondroitin sulfate and connects the cytoskeleton to the interstitial matrix.

[0057] As used herein, the terms “CD9,” “5H9 antigen,” “cell growth inhibitory gene 2 protein,” “leukocyte antigen MIC3,” “motor-associated protein,” “MRP-1,” “tetraspan-29,” “Tspan-29,” and “p24” are used interchangeably and refer to the product of the human CD9 gene, as described, for example, under reference numbers GeneID:928 and UniProt P21926. CD9 is an integrative membrane protein associated with integrins that regulate various processes.

[0058] "+" indicates cells expressing the biomarker. For example, ANTXR1+ This refers to cells that express ANTXR1. Alternatively, a "-" indicates cells that do not express the marker. For example, ANTXR1 - This refers to cells that do not express ANTXR1.

[0059] As used herein, the terms “object,” “individual,” or “patient” are interchangeable and refer to animals, preferably mammals, and more preferably humans. However, the term “object” can also refer to non-human animals, particularly mammals such as dogs, cats, horses, cattle, pigs, sheep, and non-human primates.

[0060] As used in this article, the term "marker" or "biomarker" refers to a measurable biological parameter that helps predict the occurrence of cancer, the effectiveness of cancer treatment, or the presence of immunosuppressive cells.

[0061] As used in this article, the term "diagnosis" refers to determining whether a person is likely to have cancer. Technicians often make diagnoses based on one or more diagnostic markers, the presence or amount of which indicates the presence or absence of cancer. "Diagnosis" also aims to provide information useful for diagnosis.

[0062] As used herein, the term "treatment" refers to any action aimed at improving a patient's health, such as treating, preventing, inhibiting, and delaying a disease. In some embodiments, such a term refers to improving or eradicating a disease or disease-related symptoms. In other embodiments, the term refers to minimizing the spread or worsening of the disease as a result of administering one or more therapeutic agents to a subject suffering from such a disease.

[0063] As used herein, the terms "immunotherapy," "immunotherapy agent," or "immunotherapy treatment" refer to cancer treatments that utilize the immune system to fight off cancer. This treatment stimulates the patient's immune system to attack malignant tumor cells. It includes immunizing the patient with tumor antigens (e.g., administering a cancer vaccine), in which case the patient's own immune system is trained to recognize tumor cells as targets to destroy; administering molecules that stimulate the immune system, such as cytokines; or administering therapeutic antibodies as drugs, in which case the therapeutic antibody recruits the patient's immune system to destroy tumor cells. Specifically, antibodies target specific antigens, such as unusual antigens presented on the surface of a tumor.

[0064] A crucial part of the immune system is its ability to distinguish between normal cells in the body and those it perceives as "foreign," particularly cancer cells. This allows the immune system to attack cancer cells without affecting normal cells. To this end, the immune system uses "checkpoints," molecules on certain immune cells that need to be activated (or deactivated) to initiate an immune response. Cancer cells sometimes find ways to exploit these checkpoints to evade attack by the immune system. As used in this article, "immune checkpoint inhibitor therapy" refers to immunotherapy that targets these checkpoints to allow or promote the immune system's attack on cancer cells.

[0065] The terms “percentage,” “quantity,” “number,” and “level” are used interchangeably in this document and can refer to an absolute quantification of molecules or cells in a sample, or a relative quantification of molecules or cells in a sample, i.e., relative to another value, such as a reference value as taught herein.

[0066] As used herein, “pharmaceutical composition” refers to a formulation of one or more active agents with optional other chemical components such as physiologically suitable carriers and excipients. The purpose of a pharmaceutical composition is to facilitate administration of the active agent to a living organism. The compositions of the present invention may be in forms suitable for any conventional route of administration or use. In one embodiment, “composition” generally means a combination of an active agent, such as a compound, or a composition with a naturally occurring or non-naturally occurring inert carrier (e.g., a detectable reagent or label) or an active carrier such as an adjuvant, diluent, binder, stabilizer, buffer, salt, lipophilic solvent, preservative, auxiliaries, etc., and includes pharmaceutically acceptable carriers. As used herein, “acceptable medium” or “acceptable carrier” refers to any known compound or combination of compounds known to those skilled in the art for use in formulating pharmaceutical compositions.

[0067] As used herein, the terms “active element,” “active ingredient,” “active pharmaceutical ingredient,” “therapeutic agent,” “antitumor compound,” and “antitumor agent” are equivalent and refer to components that have therapeutic effects.

[0068] As used herein, the term "therapeutic effect" refers to the effect caused by the active ingredients or pharmaceutical compositions of the present invention that can prevent or delay the onset or development of cancer, or cure or reduce the effects of cancer.

[0069] As used herein, “effective amount” or “therapeutic effective amount” refers to the amount of active agent, alone or in combination with one or more other active agents, required to impart a therapeutic effect to a subject, such as the amount of active agent needed to treat a target disease or condition, or to produce the desired effect. “Effective amount” varies depending on the active agent, the disease and its severity, the characteristics of the subject being treated, including age, physical condition, body type, sex, and weight, the duration of treatment, the nature of any concurrent therapies (if any), the specific route of administration, and similar factors within the knowledge and expertise of a healthcare practitioner. These factors are well known to those skilled in the art and can be resolved through routine experimentation alone. Generally, the maximum dose of the single component or its combination is preferred, i.e., the highest safe dose based on reasonable medical judgment.

[0070] As used herein, the terms “kit,” “product,” or “combination formulation” are defined, particularly in the sense that combination partners (a) and (b) as defined herein can be administered independently or by using different fixed combinations of different amounts of combination partners (a) and (b), i.e., simultaneously or at different time points. The parts of the kit can then be administered simultaneously or staggered over time, i.e., any part of the kit is administered at different time points. The ratio of the total amount of combination partner (a) to combination partner (b) to be administered in the combination formulation can vary. Combination partners (a) and (b) can be administered via the same route or via different routes.

[0071] As used herein, the term "simultaneously" refers to the pharmaceutical composition, kit, product, or combination formulation of the present invention, wherein the active ingredient is used or administered simultaneously, i.e., at the same time.

[0072] As used herein, the term "sequential" refers to the pharmaceutical compositions, kits, products, or combinations of the present invention, wherein the active ingredients are used or applied sequentially, i.e., one after another. Preferably, when applied sequentially, all active ingredients are applied within less than about 1 hour, preferably within less than about 10 minutes, and more preferably within less than about 1 minute.

[0073] As used herein, the term "separately" refers to the pharmaceutical compositions, kits, products, or combinations of the present invention, wherein the active ingredient is used or applied at different times of the day. Preferably, when applied separately, the active ingredient is applied at intervals of about 1 hour to about 24 hours, more preferably at intervals of about 1 hour to 15 hours, more preferably at intervals of about 1 hour to 8 hours, and even more preferably at intervals of about 1 hour to 4 hours.

[0074] As used herein, the term “and / or” should be regarded as a specific disclosure of each of two specified features or components together or apart from the other. For example, “A and / or B” should be regarded as a specific disclosure of each of (i) A, (ii) B, and (iii) A and B, as if each were listed individually.

[0075] The term “an” or “a” can refer to one or more of the elements it modifies (e.g., “a reagent” can refer to one or more reagents), unless the context clearly describes one or more of the elements.

[0076] As used herein, the term "about" in conjunction with any and all numerical values ​​(including the lower and upper ends of a range) refers to any numerical value with an acceptable deviation of up to + / - 10% (e.g., + / - 0.5%, + / - 1%, + / - 1.5%, + / - 2%, + / - 2.5%, + / - 3%, + / - 3.5%, + / - 4%, + / - 4.5%, + / - 5%, + / - 5.5%, + / - 6%, + / - 6.5%, + / - 7%, + / - 7.5%, + / - 8%, + / - 8.5%, + / - 9%, + / - 9.5%). Using the term "about" at the beginning of a series of numerical values ​​modifies each value (i.e., "about 1, 2, and 3" means about 1, about 2, and about 3). Furthermore, when a list of numerical values ​​is described in this document (e.g., approximately 50%, 60%, 70%, 80%, 85%, or 86%), the list includes all its intermediate and fractional values ​​(e.g., 54%, 85.4%).

[0077] The methods of the present invention disclosed below can be in vivo, in vitro, or extracorporeal methods, preferably extracorporeal or in vitro methods.

[0078] Detection of new fibroblast subsets, especially CAF subsets

[0079] In a first aspect, the present invention relates to an in vitro method for detecting immunosuppressive fibroblasts, particularly cancer-associated fibroblasts (CAFs), in cancer samples from a cancer patient, wherein the method includes detecting ANTXR1 in the cancer sample from the patient. + Fibroblasts, especially ANTXR1 + CAF, ANTXR1 + Fibroblasts, especially ANTXR1 + The presence of CAF is an indicator of immunosuppressive fibroblasts, particularly immunosuppressive CAF. Therefore, this invention envisions the use of ANTXR1 as a biomarker to identify immunosuppressive fibroblasts, particularly immunosuppressive CAF, in cancer samples from cancer patients. This invention also relates to ANTXR1 and immunosuppressive ANTXR1.+ Fibroblast populations, especially ANTXR1 + The use of the CAF population as a novel biomarker in cancer treatment. In particular, the present invention envisions the immunosuppressive ANTXR1... + Fibroblast populations, especially ANTXR1 + The invention also relates to the use of the CAF population as a novel biomarker for response to immunotherapy. ANTXR1, preferably from the CAF population, is used as a biomarker in the tumors of cancer patients in predicting their response to immunotherapy, particularly their susceptibility to immunotherapy.

[0080] In one embodiment, the present invention relates to an in vitro method for detecting immunosuppressive fibroblasts, particularly cancer-associated fibroblasts (CAFs), in cancer samples from a cancer patient, wherein the method includes detecting ANTXR1 in the cancer sample from the patient. + Fibroblasts, especially ANTXR1 + CAF.

[0081] Optionally, the method may also include a preliminary step of providing a cancer sample from the patient.

[0082] Preferably, the CAF of the present invention belongs to the CAF-S1 subgroup, as described in, for example, Costa et al., 2018, Cancer Cell, Vol. 33, No. 3, pp. 463-479.e10 or WO2019 / 020728, the disclosure of which is incorporated herein by reference. The CAF-S1 population specifically expresses one or more biomarkers selected from CD29, FAP, αSMA, PDGFRβ, and FSP1. In particular, the CAF-S1 of the present invention is FAP. + .

[0083] As used in this article, the term "FAP" + "Fibroblasts" refers to a subset of fibroblasts that express FAP. As used in this article, "FAP" + CAF or FAP + "Cancer-associated fibroblasts" refers to a subset of cancer-associated fibroblasts (CAFs) that express FAP. Not all CAFs express FAP. Therefore, in a preferred embodiment, FAP... + Detection of CAF depends on the detection of CAF expressing FAP, preferably the detection of FAP mRNA and / or protein. However, FAP + Other specific markers of CAF can also be used to detect them.

[0084] As used in this article, the term "ANTXR1"+ "Fibroblasts" refers to a subset of fibroblasts that express ANTXR1. As used in this article, "ANTXR1" is a more general term. + CAF or ANTXR1 + "Cancer-associated fibroblasts" refers to a subset of cancer cells (CAFs) that express ANTXR1. Not all fibroblasts or CAFs express ANTXR1. Therefore, in a preferred embodiment, ANTXR1... + The detection of fibroblasts, especially CAFs, depends on the detection of ANTXR1-expressing fibroblasts, particularly CAFs, preferably the detection of ANTXR1 mRNA and / or protein. In a preferred aspect, the detection of ANTXR1 is performed at the protein level, particularly using an anti-ANTXR1 antibody.

[0085] In one aspect, the present invention relates to an in vitro method for detecting immunosuppressive fibroblasts, particularly cancer-associated fibroblasts (CAFs), in cancer samples from cancer patients, wherein the method includes detecting FAPs in cancer samples from said patients. + ANTXR1 + Fibroblasts, especially CAFs.

[0086] However, ANTXR1 + Other specific markers of fibroblasts, especially CAFs, can also be used to detect them.

[0087] As used in this article, the terms "ecm-myCAF", "CAF-S1 cluster 0", and "ANTXR1" are as follows: + SDC1 + LAMP5 - CAF and FAP + ANTXR1 + SDC1 + LAMP5 - "CAF" is used interchangeably and refers to a subgroup of CAF, specifically a cluster of the CAF subgroup CAF-S1. Such a group expresses FAP, ANTXR1, and SDC1, but not LAMP5. Therefore, in a preferred embodiment, ANTXR1 + SDC1 + LAMP5 - The detection of CAFs depends on the detection of CAFs that express ANTXR1 and SDC1 but not LAMP5. ANTXR1, LAMP5, and SCD1 can be detected at the mRNA and / or protein levels, preferably at the protein level, particularly via antibodies.

[0088] As used in this article, the terms "TGFb-myCAF", "CAF-S1 cluster 3", and "ANTXR1" are similar to those used in this article. + LAMP5 + SDC1 + / - "and FAP" + ANTXR1 + LAMP5 + SDC1 + / - "These terms are used interchangeably and refer to a subgroup of CAF, specifically a cluster of the CAF subgroup CAF-S1. Such a population expresses FAP, ANTXR1, and LAMP5 and optionally SDC1. Therefore, in a preferred embodiment, ANTXR1..." + LAMP5 + SDC1 + / - The detection of CAFs depends on the detection of CAFs expressing ANTXR1, LAMP5, and optionally SDC1. ANTXR1, LAMP5, and SCD1 can be detected at the mRNA and / or protein levels, preferably at the protein level, particularly via antibodies.

[0089] As used in this article, the terms "trauma-myCAF", "CAF-S1 cluster 4", and "ANTXR1" are similar. + SDC1 - LAMP5 - CD9 + "and FAP" + ANTXR1 + SDC1 - LAMP5 - CD9 + "These terms are used interchangeably and refer to a subgroup of CAF, specifically a cluster of the CAF subgroup CAF-S1. Such a population expresses FAP, ANTXR1, and CD9 but not LAMP5 and SDC1. Therefore, in a preferred embodiment, ANTXR1..." + SDC1 - LAMP5 - CD9 + The detection of CAFs relies on the detection of CAFs that express ANTXR1 and CD9 but not SDC1 and LAMP5. Detection of ANTXR1, LAMP5, CD9, and SCD1 can be performed at the mRNA and / or protein level, preferably at the protein level, particularly via antibodies.

[0090] In one aspect, the present invention relates to an in vitro method for detecting immunosuppressive fibroblasts, particularly cancer-associated fibroblasts (CAFs), in cancer samples from cancer patients, wherein the method includes detecting ecm-myCAF (ANTXR1) in cancer samples from said patients. + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and / or trauma-myCAF(ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5 + SDC1 + / - )CAF. Optionally, the method includes detecting trauma-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5+ SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0091] In one implementation, fibroblasts, particularly CAFs, are considered to express FAP, ANTXR1, LAMP5, SDC1, and / or CD9 if their mRNA levels and / or protein levels are significantly different from the levels of corresponding background noise, such as those measured under the same conditions but without cells, and / or significantly different from the levels of RNA or protein corresponding to control conditions or references, such as those measured under the same conditions but with cells known not to express FAP, ANTXR1, LAMP5, SDC1, and / or CD9.

[0092] The expression levels of FAP, ANTXR1, LAMP5, SDC1, and / or CD9 in fibroblasts, particularly CAFs, can be measured using various techniques known to those skilled in the art. In particular, the measurement of the expression levels of FAP, ANTXR1, LAMP5, SDC1, and / or CD9 in CAFs can rely on the detection of FAP, ANTXR1, LAMP5, SDC1, and / or CD9 mRNA (messenger RNA) or proteins.

[0093] In one aspect, the expression of FAP, ANTXR1, LAMP5, SDC1, and / or CD9 in fibroblasts, particularly CAFs, is determined by measuring their mRNA expression. Methods for determining the amount of mRNA in cells are well known to those skilled in the art. mRNA can be detected by hybridization (e.g., Northern blot analysis), particularly by nanostring methods, and / or by amplification (e.g., RT-PCR), particularly by quantitative or semi-quantitative RT-PCR. Other amplification methods include ligase chain reaction (LCR), transcription-mediated amplification (TMA), strand displacement amplification (SDA), and nucleic acid sequence-based amplification (NASBA).

[0094] Real-time quantitative or semi-quantitative RT-PCR is particularly advantageous. Taqman probes specific to the target protein transcripts can be used. In a preferred embodiment, the expression levels of FAP, ANTXR1, LAMP5, SDC1 and / or CD9 and any other target proteins are determined by measuring the amount of their mRNA, preferably by quantitative or semi-quantitative RT-PCR or by real-time quantitative or semi-quantitative RT-PCR.

[0095] As used herein, the terms “quantitative RT-PCR,” “qRT-PCR,” “real-time RT-PCR,” and “quantitative real-time RT-PCR” are equivalent and can be used interchangeably. Any of a variety of published quantitative RT-PCR protocols can be used (and modified as needed) for this method. Suitable quantitative RT-PCR procedures include, but are not limited to, those set forth in U.S. Patent No. 5,618,703 and U.S. Patent Application No. 2005 / 0048542, which are hereby incorporated by reference.

[0096] Optionally, ANTXR1, FAP, LAMP5, SDC1, and / or CD9 can be determined from tumor samples or from a subset of tumors containing fibroblasts, particularly CAF. Therefore, tumors can be pretreated before detecting ANTXR1, FAP, LAMP5, SDC1, and / or CD9 to separate fibroblasts, particularly CAF, from other cells in the tumor, particularly tumor cells. Thus, the present invention relates to a method for detecting immunosuppressive fibroblasts, particularly CAF, in a cancer sample from a cancer patient, wherein the method includes isolating fibroblasts, particularly CAF, from a cancer sample of the patient, particularly from tumor cells, and detecting ANTXR1 in the isolated fibroblasts, particularly CAF. + Fibroblasts, especially CAFs.

[0097] In another aspect, the expression levels of ANTXR1, FAP, LAMP5, SDC1 and / or CD9 in fibroblasts, especially CAFs, were determined by measuring their corresponding protein expression.

[0098] The amount of protein can be measured by any method known to those skilled in the art. Typically, these methods involve contacting a sample with a binding partner capable of selectively interacting with a protein present in the sample. The binding partner is typically a polyclonal or monoclonal antibody, preferably a monoclonal antibody. Such antibodies can be produced by methods known to those skilled in the art. These antibodies particularly include those produced by hybridomas and those produced by genetic engineering using host cells transformed with a recombinant expression vector carrying the antibody-encoding gene. Hybridomas that produce monoclonal antibodies can be obtained by immunizing the protein or an immunogenic fragment thereof as an antigen according to conventional immunization methods. The resulting immune cells are then fused with known parental cells according to conventional cell fusion methods, thereby screening the fused cells for cells that produce the antibody using conventional screening methods.

[0099] The antibodies of the present invention can be labeled and / or fused with a detection entity. Preferably, the antibodies of the present invention are labeled or fused with a detection entity.

[0100] In a preferred embodiment, the antibody is labeled. The antibody can be labeled using a label selected from radiolabelers, enzyme labels, fluorescent labels, biotin-avidin labels, chemiluminescent labels, etc. The antibodies of the present invention can be labeled using standard labeling techniques known to those skilled in the art, and the labeled antibodies can be visualized using known methods. In particular, the label typically provides a signal detectable by fluorescence, chemiluminescence, radioactivity, colorimetry, mass spectrometry, X-ray diffraction or absorption, magnetism, enzyme activity, etc.

[0101] Preferably, the detectable marker can be a luminescent marker. For example, fluorescent markers, bioluminescent markers, chemiluminescent markers, and colorimetric markers can be used in the practice of this invention, with fluorescent markers being more preferred. Preferably, the marker is attached to the C-terminus of the antibody.

[0102] In another preferred embodiment, the antibody may be fused with a detection entity. The detection entity may be selected from a tag, enzyme, or fluorescent protein. Preferably, the detection entity is located at the C-terminus of the antibody.

[0103] The levels of ANTXR1, FAP, LAMP5, SDC1, and / or CD9 can be measured by semi-quantitative Western blotting, enzyme labeling, and mediated immunoassays such as ELISA, biotin / avidin typing, radioimmunoassay, immunohistochemistry, immunoelectrophoresis or immunoprecipitation, protein or antibody arrays, or flow cytometry such as fluorescence-activated cell sorting (FACS). These reactions typically involve displaying markers such as fluorescent markers, chemiluminescent markers, radiolabels, enzyme markers, or dye molecules, or other methods for detecting complexes formed between antigens and their reacting antibodies. Preferably, protein expression levels are assessed by FACS or by immunohistochemistry.

[0104] Fluorescence-activated cell sorting (FACS) is a special type of flow cytometry. It provides a method for sorting heterogeneous mixtures of biological cells, one cell at a time, into two or more containers based on the specific light scattering and fluorescence properties of each cell. The cell suspension is entrained in the center of a narrow, rapidly flowing stream of liquid. The stream is arranged such that there is a large spacing between cells relative to their diameter. Vibrational mechanisms cause the cell stream to break down into individual droplets. A conditioning system is used to minimize the probability of each droplet containing more than one cell. Before the stream breaks down into droplets, it is passed through a fluorescence measurement station where the fluorescence properties of each target cell are measured. A charging ring is positioned precisely where the stream breaks down into droplets. Before measuring the fluorescence intensity, a charge is applied to the ring so that, as the droplets break down from the stream, an opposite charge is captured on them. The charged droplets then fall through an electrostatic deflection system that deflects them into containers based on their charge.

[0105] Immunohistochemistry (IHC) is the process of selectively imaging antigens (such as proteins) in the cells of tissue sections by utilizing the principle of specific binding of antibodies to antigens in biological tissues. Visualizing antibody-antigen interactions can be achieved through various methods known to those skilled in the art. In the most common cases, antibodies are conjugated to enzymes that catalyze chromogenic reactions, such as peroxidases, or tagged with fluorophores such as fluorescein or rhodamine. Immunohistochemistry can be divided into two stages: sample preparation and sample labeling.

[0106] Sample preparation is crucial for maintaining cell morphology, tissue structure, and the antigenicity of target epitopes. This requires proper tissue collection, fixation, and sectioning. Paraformaldehyde solution is frequently used for tissue fixation, but other methods can also be used. The tissue can then be sectioned or used intact, depending on the experimental purpose or the tissue itself. Before sectioning, tissue samples can be embedded in media such as paraffin or cryoprotectants. Sections can be cut on various instruments, most commonly microtome, cryostat, or compresstome. Specimens are typically cut in the range of 3 μm–50 μm. The sections are then mounted on glass slides and dehydrated using alcohol detergents of increasing concentrations (e.g., 50%, 75%, 90%, 95%, 100%), and cleaned with detergents such as xylene before microscopic imaging. Depending on the fixation and tissue preservation methods, samples may require additional steps to make epitopes available for antibody binding, including deparaffining and antigen retrieval. For formalin-fixed paraffin-embedded tissues, antigen retrieval is often necessary and involves pretreatment of the sections with heat or proteases. These steps can cause differences between stained and unstained target antigens. Depending on the tissue type and antigen detection method, it may be necessary to block or quench endogenous biotin or enzymes, respectively, before antibody staining. While antibodies exhibit preferential affinity for specific epitopes, they can also partially or weakly bind to sites on similar nonspecific proteins (also known as reactive sites) that are homologous binding sites on the target antigen. To reduce background staining in IHC, samples are incubated with a buffer that blocks reactive sites that would otherwise bind to the first or second antibody. Common blocking buffers include normal serum, skim milk powder, BSA, or gelatin. Methods to eliminate background staining include diluting the first or second antibody, varying the incubation time or temperature, and using different detection systems or different first antibodies. Quality control should at least include tissues known to express the antigen as positive controls, tissues known not to express the antigen as negative controls, and test tissues that are tested in the same manner but without the first antibody (or better yet, with the first antibody absorbed).

[0107] For immunohistochemical detection strategies, antibodies are classified as primary or secondary reagents, as necessary. Primary antibodies are produced against the target antigen and are typically unconjugated (i.e., unlabeled), while secondary antibodies are produced against immunoglobulins of the same class as primary antibodies. Secondary antibodies are usually labeled and / or fused to the detection entity as described above.

[0108] The direct method is a one-step staining method that involves labeled antibodies reacting directly with antigens in tissue sections. While this technique utilizes only one antibody and is therefore simple and rapid, it is less sensitive due to minimal signal amplification, unlike indirect methods.

[0109] The indirect method involves an unlabeled primary antibody (first layer) that binds to the target antigen in the tissue and a labeled secondary antibody (second layer) that reacts with the primary antibody. The secondary antibody must be produced against the IgG of the animal species that produced the primary antibody. This method is more sensitive than direct detection strategies because if the secondary antibody is conjugated to a fluorescent or enzyme reporter molecule, the signal is amplified due to the binding of several secondary antibodies to each primary antibody. Further amplification can be achieved if the secondary antibody is conjugated to several biotin molecules, which can recruit complexes of avidin-, streptavidin-, or neutral avidin protein-binding enzymes.

[0110] Preferably, the presence of immunosuppressive CAF is determined by assessing protein expression levels using FACS as described in the experimental section or by immunohistochemistry.

[0111] Antibodies that can be used to measure FAP expression levels in CAF by FACS or immunohistochemistry include, for example: anti-human FAP antibody (R&D systems) with reference number MAB3715, ab53066 (abcam), ABIN560844, and Vitatex-MABS1001.

[0112] Antibodies that can be used to measure ANTXR1 expression levels in CAFs by FACS or immunohistochemistry include, for example: anti-ANTXR1-AF405 antibody (Novus Biological) with reference number NB-100-56585, human TEM8 / ANTXR1 antibody MAB3886 (R&Dsystem), ABIN252539, ANTXR1 antibody (15091-1-AP, Thermo Fischer), NB-100-56585 (Novus), MA1-91702 (Thermo Fischer), ab21270 (Abcam), LS-B13896 (Life spanbioscience), rb158588 (Biorbyt), bs-5210R (Bioss), or any of these antibodies with alternative markers, particularly fluorescent markers.

[0113] Antibodies that can be used to measure LAMP5 expression levels in CAFs by FACS or immunohistochemistry include, for example, the anti-LAMP5-PE antibody (Miltenyi Biotech) of reference number 130-109-156.

[0114] Antibodies that can be used to measure SDC1 expression levels in CAFs by FACS or immunohistochemistry include, for example, the anti-SDC1-BUV737 antibody (BD Biosciences) with reference number BD-564393, and ABIN5680139.

[0115] Antibodies that can be used to measure CD9 expression levels in CAF by FACS or immunohistochemistry include, for example, the anti-CD9-BV711 antibody (BD Biosciences) with reference number BD-743050, LS-B5962 (LSBio), or AB_2075893 (BioLegend).

[0116] In a preferred embodiment, ANTXR1 in a patient's cancer sample is detected by FACS. + CAF may include the following steps:

[0117] - Exclude non-CAF cells, for example by excluding CD45 cells. + Cells, EpCAM + Cells and CD31 + Cells, thereby selecting CD45 - EpCAM - CD31 - Cells; and / or

[0118] - Select CAF cells, for example by selecting CD29. + Cells and / or PDGFRb + Cells, preferably selected by CD29 + cell;

[0119] -Optional selection of CAF-S1 cells, for example by selecting CD29 + FAP + αSMA + PDGFRβ + and / or FSP1 + Cells, preferably FAP + cell,

[0120] - Optionally, dead cells may be excluded, for example by using intracellular dyes such as purple LIVE / DEAD dye or DAPI and excluding stained cells; and

[0121] - Detect ANTXR1 in the cells obtained in the previous step + CAF,

[0122] - Optional detection of LAMP5, SDC1 and / or CD9 positive or negative cells.

[0123] In another preferred embodiment, ANTXR1 in the patient's cancer sample is detected by immunohistochemistry. + CAF may include the following steps:

[0124] - Identify CAF in cancer samples, for example, based on morphological criteria;

[0125] - Detect ANTXR1 in CAF + CAF, preferably based on ANTXR1 antibody immunostaining;

[0126] -Optional detection of FAP in CAF + CAF, preferably based on FAP antibody immunostaining;

[0127] - Optional detection of LAMP5, SDC1 and / or CD9 positive or negative cells.

[0128] In one respect, the presence of immunosuppressive fibroblasts, especially CAFs, refers to the amount of immunosuppressive fibroblasts, especially CAFs, in a tumor sample or any fraction thereof, ANTXR1. + Fibroblasts, especially ANTXR1 + The ratio or percentage of CAF cells to the total number of cells in the sample or any fraction thereof, ANTXR1 + Fibroblasts, especially ANTXR1 + The ratio or percentage of CAF cells to the total number of mesenchymal cells in the sample or any fraction thereof, ANTXR1 + The ratio or percentage of fibroblasts to the total number of fibroblasts in the sample, ANTXR1 + The ratio or percentage of fibroblasts to the total number of fibroblasts in the sample, ANTXR1 + The ratio or percentage of CAF cells to the total number of CAF cells in the sample or any fraction thereof, or ANTXR1 + The ratio or percentage of the number of CAF cells to the total number of CAF-S1 cells in the sample or any fraction thereof.

[0129] Preferably, the term "percentage of ANTXR1+ fibroblasts in a tumor" can refer to ANTXR1. + The number of fibroblasts is used as the numerator (nominator) and any ratio of the number of reference cells is used as the denominator. Preferably, the term "ANTXR1 in tumors" refers to any ratio of fibroblasts as the numerator (nominator) and reference cells as the denominator. + The percentage of CAF can refer to ANTXR1. +Any ratio with the number of CAF cells as the numerator and the number of reference cells as the denominator. In cancer samples, such reference cells can be specifically selected from: all cells in the cancer sample, cancer cells, stromal cells, CAF cells, and CAF-S1 cells.

[0130] ANTXR1 + "Low percentage of fibroblasts" or "low percentage of ANTXR1+ fibroblasts" is equivalent to less than 20%, 10%, 5%, 2%, 1%, 0.5%, or 0.1%.

[0131] ANTXR1 + "High percentage of fibroblasts" or "high percentage of ANTXR1+ fibroblasts" is equivalent to greater than 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90%.

[0132] Therefore, in the first aspect, ANTXR1 + The presence of fibroblasts, especially CAFs, in a patient's cancer sample indicates the proportion of ANTXR1 in the total number of cells in the cancer sample. + The number of fibroblasts, especially CAF cells. Preferably, ANTXR1 + The presence of fibroblasts, especially CAFs, corresponds to a percentage of at least 0.001%, 0.01%, 0.1%, 1%, 5%, 10%, 20%, or 30%.

[0133] In the second aspect, ANTXR1 + The presence of fibroblasts, especially CAFs, in a patient's cancer sample indicates the total number of ANTXR1 cells in the cancer sample. + The number of fibroblasts, especially CAF cells. Preferably, ANTXR1 + The presence of fibroblasts, especially CAFs, corresponds to a percentage of at least 0.001%, 0.01%, 0.1%, 1%, 5%, 10%, 20%, or 30%.

[0134] Thirdly, ANTXR1 + The presence of fibroblasts, especially CAFs, in a patient's cancer sample indicates the proportion of ANTXR1 in the total number of CAF cells in the cancer sample. + The number of fibroblasts, especially CAF cells. Preferably, ANTXR1 + The presence of fibroblasts, especially CAFs, corresponds to a percentage of at least 0.1%, 1%, 5%, 10%, 20%, 30%, 40%, or 50%.

[0135] Fourthly, ANTXR1 +The presence of fibroblasts, especially CAFs, in the patient's cancer sample indicates the total number of ANTXR1 cells in the CAF-S1 cells of the cancer sample. + The number of fibroblasts, especially CAFs. Preferably, ANTXR1 + The presence of fibroblasts, especially CAFs, corresponds to a percentage of at least 0.1%, 1%, 5%, 10%, 20%, 30%, 40%, or 50%.

[0136] In one aspect, the presence of ANTXR1+ fibroblasts, especially CAFs, in cancer samples, for example, ANTXR1 in cancer samples + The percentage of fibroblasts, especially CAFs, is inversely proportional to the patient's response to immunotherapy; and optionally, the method also includes selecting cancer samples without ANTXR1. + Fibroblasts, especially CAFs or those with a low percentage of ANTXR1 + Patients with fibroblasts, especially CAF, are suitable for immunotherapy and / or those with a moderate to high percentage of ANTXR1 in their cancer samples are preferred. + Patients with fibroblasts, especially CAF, should undergo replacement therapy, such as anticancer treatments other than immunotherapy, or therapy that reduces ANTXR1. + Immunotherapy combined with treatment of fibroblast-induced immunosuppression, especially CAF-induced immunosuppression.

[0137] "Inversely proportional" means that ANTXR1 in cancer samples + The more fibroblasts, especially CAFs, the less likely a cancer patient is to respond to immunotherapy. These terms do not necessarily imply a direct and measurable correlation.

[0138] In one aspect, the present invention relates to an in vitro method for predicting the response of a cancer patient to immunotherapy, wherein the method includes detecting ANTXR1 in a cancer sample from the patient. + Fibroblasts, especially CAF, wherein ANTXR1 in the cancer sample + Fibroblasts, especially CAFs, indicate or predict the patient's unresponsiveness to immunotherapy. In particular, ANTXR1 in cancer samples... + The more fibroblasts, especially CAFs, a patient is less likely to respond to immunotherapy.

[0139] Optional, ANTXR1 + Fibroblasts are ANTXR1 + CAF. Optional, ANTXR1 + Fibroblasts are FAP + Fibroblasts. Optionally, ANTXR1+ CAF is FAP + ANTXR1 + CAF.

[0140] In fact, the present invention relates to the use of ANTXR1 in fibroblast populations, particularly CAF populations, as a biomarker in tumors of cancer patients in predicting the response of said patients to immunotherapy.

[0141] Optionally, the present invention relates to an in vitro method for predicting the response of a cancer patient to immunotherapy, wherein the method comprises: (a) detecting ANTXR1 in a cancer sample from the patient. + Fibroblasts, especially ANTXR1 + CAF, wherein ANTXR1 in the cancer sample + Fibroblasts, especially CAFs, indicate or predict the patient's unresponsiveness to immunotherapy.

[0142] (b) Optionally, select no ANTXR1 + Fibroblasts, especially ANTXR1 + Patients with CAF are suitable for immunotherapy and / or choose those with ANTXR1. + Fibroblasts, especially ANTXR1 + Patients with CAF should undergo alternative therapies, such as anticancer treatments other than immunotherapy, or those that reduce ANTXR1. + Fibroblasts, especially ANTXR1 + Treatment of immunosuppression caused by CAF combined with immunotherapy.

[0143] Optionally, the method includes detecting FAP in a cancer sample from the patient. + ANTXR1 + Fibroblasts or CAFs. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and / or trauma-myCAF(ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1+ LAMP5 - CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5 + SDC1 + / - )CAF. Optionally, the method includes detecting trauma-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0144] In one aspect, the CAF subset is detected through specific gene signatures. A "gene signature" or "gene expression signature" is a single gene or a group of genes that has a unique and characteristic gene expression pattern in cells, particularly fibroblasts. In particular, a gene signature corresponds to the dysregulation of a specific gene, especially the overexpression of that gene.

[0145] In one respect, the ecm-myCAF gene signature includes the following genes:

[0146] ASPN, COL3A1, THY1, SFRP2, COL10A1, COL6A3, LRRC17, CILP, GRP, ITGBL1, COL8A1, COL14A1, ADAM12, OLFML2B, ELN, PLPP4, CREB3L1, FBN1, LOXL1, MATN3, LRRC15, COMP, ISLR, P3H1, COL11A1, SEPT11, NBL1, SPON1, SULF1, FNDC1, CNN1, MIAT, MMP23B, CPXM1, FIBIN, P4HA3, GXYLT2, CILP2, P3H4, and CCDC80. In one particular aspect, the ecm-myCAF gene signature also includes the following genes: FAP and / or ANTXR1.

[0147] In one respect, the TGFβ-myCAF gene signature includes the following genes:

[0148] CST1, LAMP5, LOXL1, EDNRA, TGFB1, TGFB3, TNN, CST2, HES4, COL10A1, ELN, THBS4, NKD2, OLFM2, COL6A3, LRRC17, COL3A1, THY1, HTRA3, TMEM204, SEPT11, COMP, TNFAIP6, ID4, GGT5, INAFM1, CILP, and OLFML2B. In one particular aspect, the TGFβ-myCAF gene signature also includes the following genes: FAP and / or ANTXR1.

[0149] In one respect, the trauma-myCAF genetic signature includes the following genes:

[0150] SFRP4, CCDC80, OGN, DCN, PTGER3, SFRP2, PDGFRL, SMOC2, MMP23B, CPXM2, COL14A1, ITGBL1, WISP2, CILP2, COL8A1, GAS1, COL3A1, OMD, COL11A1, CILP, NEXN, ASPN, RARRES2, FIBIN, TMEM119, KERA, ID4, GRP, COMP, DPT, ELN, FBLN2, IGF1, and IGF2. In one particular aspect, the trauma-myCAF genetic signature also includes the following genes: FAP and / or ANTXR1.

[0151] Therefore, in the method of this disclosure, ecm-myCAF, TGFβ-myCAF, and / or trauma-myCAF are detected by determining the expression of genes containing gene signatures specific to ecm-myCAF, TGFβ-myCAF, and / or trauma-myCAF, where overexpression of said genes indicates the presence of these CAF subsets. Optionally, said gene signature may contain additional genes, but no more than 50 genes, and particularly no more than 40 genes.

[0152] The present invention also relates to the use of these gene signatures in the detection of ecm-myCAF, TGFβ-myCAF and / or trauma-myCAF subsets, particularly in the detection of the presence of immunosuppressive CAFs and / or in predicting therapeutic response to immunotherapy.

[0153] Optionally, samples can be processed to remove non-CAF cells before determining the expression of the gene signature.

[0154] "Overexpression" refers to the expression level measured at the nucleic acid level, particularly the mRNA level. It can be measured by any method known to those skilled in the art. A gene is considered overexpressed when its expression increases by at least log2 compared to a reference level. The reference level can be the gene's expression in control cells, such as a fibroblast population, particularly a CAF population, preferably FAP. + CAF populations. In one particular aspect, control cells are CAF clusters that are not ecm-myCAF (cluster 0), TGFβ-myCAF (cluster 3) and / or trauma-myCAF (4), such as detoxification-iCAF (cluster 1), IL-iCAF (cluster 2), IFNγ-iCAF (cluster 5), IFNαβ-myCAF (cluster 6) and acto-myCAF (cluster 7), or any combination thereof.

[0155] These gene signatures, specific to the ecm-myCAF, TGFβ-myCAF, and / or trauma-myCAF subsets, can be used in combination with other gene signatures known to those skilled in the art, particularly those relevant to response prediction or cancer diagnosis.

[0156] In another embodiment, the present invention relates to an in vitro method for predicting the response of a cancer patient to immunotherapy, wherein the method comprises:

[0157] (a) Detection of ANTXR1 in cancer samples from the patient + Fibroblasts, especially ANTXR1 + CAF;

[0158] (b) Identify ANTXR1 in the cancer sample + Fibroblasts, especially ANTXR1 + The percentage of CAF, wherein the patient's responsiveness to immunotherapy treatment is correlated with the ANTXR1 in the cancer sample. + Fibroblasts, especially ANTXR1 + The percentage of CAF is inversely proportional;

[0159] (c) Optionally, select ANTXR1 with a low percentage. + Fibroblasts, especially ANTXR1 + Patients with CAF, especially those without any ANTXR1 + Fibroblasts, especially ANTXR1 + Patients with CAF who are suitable for immunotherapy and who have a moderate to high percentage of ANTXR1 were selected. + Fibroblasts, especially ANTXR1 + Patients with CAF should undergo alternative therapies, such as anticancer treatments other than immunotherapy, or those that reduce ANTXR1. + Fibroblasts, especially ANTXR1 + Treatment of immunosuppression caused by CAF combined with immunotherapy.

[0160] Optionally, the method includes detecting FAP in a cancer sample from the patient. + ANTXR1 + Fibroblasts or CAFs. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1+ / - ) and / or trauma-myCAF(ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5 + SDC1 + / - )CAF. Optionally, the method includes detecting trauma-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting TGFb-myCAF (ANTXR1) in a cancer sample from the patient. + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method includes detecting ecm-myCAF (ANTXR1) in a cancer sample from the patient. + SDC1 + LAMP5 -), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the method may further include a step of providing a cancer sample from the patient prior to step (a).

[0161] Optionally, the method may further include processing ANTXR1 with a low percentage. + The procedure involves administering immunotherapy to patients with fibroblasts or CAF. Alternatively, the method may also include treatment with a high percentage of ANTXR1. + The procedure for administering alternative anticancer therapies to patients with fibroblasts or CAF, wherein the alternative therapy is an anticancer therapy other than immunotherapy, or is associated with reducing ANTXR1. + Immunotherapy combined with treatment for immunosuppression caused by fibroblasts or CAF. The treatment administered may be selected from surgery, chemotherapy, radiation therapy, hormone therapy, targeted therapy, and palliative care, or any combination thereof. Alternatively or additionally, the method may also include administration of medications that reduce ANTXR1. + The steps of immunotherapy treatment are combined with fibroblast or CAF-induced immunosuppression.

[0162] In another particular aspect, the invention also relates to a method for selecting a patient with a tumor for immunotherapy or for determining whether a patient with a tumor is likely to benefit from immunotherapy, wherein the method includes determining ANTXR1 in a cancer sample from the patient. + The presence of fibroblasts or CAFs and the optional absence of ANTXR1 + Fibroblasts or CAFs or cells with a low percentage of ANTXR1 + Patients with fibroblasts or CAF undergo immunotherapy.

[0163] Optionally, the method further includes a preliminary step of providing a cancer sample from the patient.

[0164] In yet another specific aspect, the invention also relates to a method for selecting patients with tumors for alternative therapies such as anticancer treatments other than immunotherapy or those that reduce ANTXR1. + Immunotherapy combined with treatment for immunosuppression caused by fibroblasts or CAF, or determining whether a patient with a tumor is susceptible to alternative therapies such as anticancer treatments other than immunotherapy or those that reduce ANTXR1. +Methods of benefiting from immunotherapy combined with treatment of immunosuppression caused by fibroblasts or CAF, wherein said methods include identifying ANTXR1 in a cancer sample from said patient. + The presence of fibroblasts or CAFs and the optional selection of those with ANTXR1 + CAF or with a high percentage of ANTXR1 + This replacement therapy is given to patients with fibroblasts or CAF.

[0165] Optionally, the ANTXR1 + Fibroblasts or CAFs are FAPs + ANTXR1 + Fibroblasts or CAFs. Preferably, ANTXR1 + CAF is selected from FAP + ANTXR1 + CAF, FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and ANTXR1 + SDC1 - LAMP5 - CD9 + FAP is preferred. + ANTXR1 + LAMP5 - SDC1 + CAF and / or FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF.

[0166] Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - CAF. Optionally, the ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - CAF. Optionally, the ANTXR1 + CAF is trauma-myCAF (ANTXR1) + SDC1- LAMP5 - CD9 + CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0167] In yet another embodiment, the present invention relates to a method for selecting a patient for immunotherapy, wherein the method includes:

[0168] (a) Detection of ANTXR1 in cancer samples from the patient + Fibroblasts or CAF;

[0169] (b) Identify ANTXR1 in the cancer sample + The percentage of fibroblasts or CAFs, and of which ANTXR1 + A percentage of CAF less than 25%, preferably less than 20%, more preferably less than 10%, even more preferably less than 5%, even more preferably less than 1%, and even more preferably less than 0.5% is predicted to indicate that the patient is responsive to immunotherapy.

[0170] The method may further include step c) of administering immunotherapy, preferably an immune checkpoint inhibitor.

[0171] Optionally, the method further includes a preliminary step of providing a cancer sample from the patient.

[0172] In yet another embodiment, the present invention relates to a method for selecting alternative anticancer therapies for patients, particularly anticancer therapies other than or including immunotherapy, wherein the method comprises:

[0173] (a) Detection of ANTXR1 in cancer samples from the patient + Fibroblasts or CAF;

[0174] (b) Identify ANTXR1 in the cancer sample + The percentage of fibroblasts or CAFs, and of which ANTXR1 + A percentage of CAF greater than 1%, preferably greater than 5%, more preferably greater than 10%, even more preferably greater than 20%, even more preferably greater than 30%, and even more preferably greater than 40% indicates or predicts the patient's non-responsiveness to immunotherapy.

[0175] The method may further include step c) administering an alternative treatment selected from surgery, chemotherapy, radiotherapy, hormone therapy, targeted therapy, and palliative care, or any combination thereof. Alternatively or additionally, the method may also include administering medication to reduce ANTXR1. + The steps of immunotherapy treatment are combined with fibroblast or CAF-induced immunosuppression.

[0176] Optionally, the method further includes a preliminary step of providing a cancer sample from the patient.

[0177] The present invention also relates to an immunotherapy for treating cancer in patients, wherein the cancer sample of the patient presents (a) a low amount or a low percentage of ANTXR1. + Fibroblasts or CAF; or (b) no ANTXR1 +Fibroblasts or CAFs. It also relates to the use of immunotherapy in the manufacture of drugs for treating patients with cancer, wherein the cancer sample from said patients presents (a) a low number or low percentage of ANTXR1. + Fibroblasts or CAF; or (b) no ANTXR1 + Fibroblasts or CAFs. The invention also relates to a method for treating a patient with cancer, wherein the method includes selecting a patient having (a) a low number or low percentage of ANTXR1. + Fibroblasts or CAF; or (b) no ANTXR1 + Fibroblasts or CAFs, and treatment with immunotherapy in therapeutically effective doses.

[0178] Optionally, the ANTXR1 + Fibroblasts or CAFs are FAPs + ANTXR1 + Fibroblasts or CAFs. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - CAF. Optionally, the ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - CAF. The ANTXR1 + CAF is trauma-myCAF (ANTXR1) + SDC1 - LAMP5 - CD9 + CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9+ CAF. Optionally, the ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optionally, the ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0179] Immunotherapy

[0180] The immunosuppressive fibroblasts of the present invention, particularly immunosuppressive CAFs, can be used to predict or evaluate responses to immunotherapy.

[0181] Preferably, the immunotherapy is selected from: therapeutic treatments that stimulate the patient's immune system to attack malignant tumor cells, immunization of the patient with tumor antigens, such as by administering a cancer vaccine, administration of molecules that stimulate the immune system, such as cytokines, administration of therapeutic antibodies, preferably monoclonal antibodies as drugs, particularly antibodies against antigens specifically presented or overexpressed on tumor cell membranes or against cell receptors that inhibit tumor growth, adoptive T-cell therapy, immune checkpoint inhibitor therapy, and any combination thereof; preferably immune checkpoint inhibitor therapy.

[0182] In a preferred embodiment, the immunotherapy is an immune checkpoint inhibitor therapy, preferably selected from: antibodies against CTLA-4 (cytotoxic T-lymphocyte-associated protein 4) such as ipilimumab, antibodies against PD-1 (programmed cell death protein 1) such as nivolumab, pembrolizumab, or BGB-A317, antibodies against PDL1 (programmed cell death ligand) such as atezolizumab, avermab, or durvalumab, antibodies against LAG-3 (lymphocyte activation gene 3) such as BMS-986016, antibodies against TIM-3 (protein-3 containing T-cell immunoglobulin and mucin domains), antibodies against TIGIT (T-cell immune receptor with Ig and ITIM domains), antibodies against BLTA (B and T lymphocyte attenuation factor), IDO1 inhibitors such as icardostab, or combinations thereof.

[0183] In a most preferred aspect, the immunotherapy is an immune checkpoint inhibitor, wherein the immune checkpoint is selected from antibodies against cytotoxic T-lymphocyte-associated protein (CTLA-4), programmed cell death protein 1 (PD-1), programmed cell death ligand (PD-L1), T-cell immune receptor with Ig and ITIM domains (TIGIT), lymphocyte activation gene 3 (LAG-3), T-cell immunoglobulin and mucin domain protein-3 (TIM-3), B and T-lymphocyte attenuation factor (BLTA), IDO1 inhibitors, or any combination thereof, preferably selected from antibodies against CTLA-4, PD-1, and TIGIT, or any combination thereof, more preferably antibodies against PD-1 or CTLA-4, or combinations thereof.

[0184] Several anti-PD-1 antibodies have received clinical approval, while others are still in clinical development. For example, anti-PD-1 antibodies may be selected from: pembrolizumab (also known as Keytruda lambrolizumab, MK-3475), nivolumab (Opdivo, MDX-1106, BMS-936558, ONO-4538), pitilizumab (CT-011), cimiplimab (LIBTYO), camrelizumab, AUNP12, AMP-224, AGEN-2034, BGB-A317 (tisleizumab). PDR001 (Spartalizumab), MK-3477, SCH-900475, PF-06801591, JNJ-63723283, genolimzumab (CBT-501), LZM-009, BCD-100, SHR-1201, BAT-1306, AK-103 (HX-008), MEDI-0680 (also known as AMP-514), MEDI0608, JS001 (see Si-Yang) Liu et al., J. Hematol. Oncol. 10:136 (2017)), BI-754091, CBT-501, INCSHR1210 (also known as SHR-1210), TSR-042 (also known as ANB011), GLS-010 (also known as WBP3055), AM-0001 (Armo), STI-1110 (see WO 2014 / 194302), AGEN2034 (see WO 2017 / 040790), MGA012 (see WO 2017 / 19846), or IBI308 (see WO 2017 / 024465, WO 2017 / 025016, WO 2017 / 132825 and WO 2017 / 133540), WO Monoclonal antibodies 5C4, 17D8, 2D3, 4H1, 4A11, 7D3, and 5F4 are described in 2006 / 121168. Bifunctional or bispecific molecules targeting PD-1 are also known, such as RG7769 (Roche), XmAb20717 (Xencor), MEDI5752 (AstraZeneca), FS118 (F-star), SL-279252 (Takeda), and XmAb23104 (Xencor).

[0185] Antibodies against CTLA-4 and bifunctional or bispecific molecules targeting CTLA-4 are also known, such as ipilimumab, tremelimumab, MK-1308, AAGEN-1884, XmAb20717 (Xencor), and MEDI5752 (AstraZeneca).

[0186] Antibodies against TIGIT are also known in the art, such as BMS-986207 or AB154, BMS-986207CPA.9.086, CHA.9.547.18, CPA.9.018, CPA.9.027, CPA.9.049, CPA.9.057, CPA.9.059, CPA.9.083, CPA.9.089, CPA.9.093, CPA.9.101, CPA.9.103, CHA.9.536.1, CHA.9.536.3, CHA.9.536.4, CHA.9.536.5, CHA.9.536.6, CHA.9.536.7, CHA.9.536.8, and CHA.9.56 as disclosed in WO19232484. 0.1, CHA.9.560.3, CHA.9.560.4, CHA.9.560.5, CHA.9.560.6, CHA.9.560.7, CHA.9. 560.8, CHA.9.546.1, CHA.9.547.1, CHA.9.547.2, CHA.9.547.3, CHA.9.547.4, CHA. 9.547.6, CHA.9.547.7, CHA.9.547.8, CHA.9.547.9, CHA.9.547.13, CHA.9.541.1, C HA.9.541.3, CHA.9.541.4, CHA.9.541.5, CHA.9.541.6, CHA.9.541.7 and CHA.9.541.8. Anti-TIGIT antibodies have also been disclosed in WO16028656, WO16106302, WO16191643, WO17030823, WO17037707, WO17053748, WO17152088, WO18033798, WO18102536, WO18102746, WO18160704, WO18200430, WO18204363, WO19023504, WO19062832, WO19129221, WO19129261, WO19137548, WO19152574, WO19154415, WO19168382, and WO19215728.

[0187] Preferably, the immunotherapy is selected from ipilimumab, nivolumab, BGB-A317, pembrolizumab, atezolizumab, avitumab, or durvalumab, BMS-986016 and icocadorstat, or any combination thereof.

[0188] ANTXR1 + Fibroblast or CAF targeting agents

[0189] In another aspect, the present invention also relates to targeting ANTXR1. + Fibroblast-targeting agents or FAP-targeting agents + A fibroblast-derived agent or a pharmaceutical composition comprising said agent, for use in combination with immunotherapy to treat or for use in cancer patients having ANTXR1. + Fibroblasts, especially those with ANTXR1 in tumor samples from said subjects. + Fibroblasts.

[0190] In fact, reducing ANTXR1 + Fibroblasts, especially ANTXR1 + Treatment for CAF-induced immunosuppression could include, for example, targeting ANTXR1. + Drugs targeting fibroblasts or CAF, or FAP inhibitors.

[0191] This invention also relates to targeting ANTXR1 + CAF or FAP + A drug agent of CAF or a pharmaceutical composition containing said drug agent, for use in combination with immunotherapy to treat cancer patients or for use in cancer patients having ANTXR1. + CAF, especially in tumor samples from said subjects with ANTXR1 + CAF. More specifically, when using FAP inhibitors, the target has ANTXR1. + FAP + Fibroblasts, especially ANTXR1 + FAP + CAF.

[0192] This invention also relates to targeting ANTXR1 + CAF or FAP + CAF drugs are used in the manufacture of drugs for the treatment of cancer patients, especially those with ANTXR1. + Fibroblasts or CAFs, especially those with ANTXR1 in tumor samples from the subjects. +Use in a medicament targeting fibroblasts or CAFs, said medicament optionally in combination with immunotherapy. In a further aspect, the present invention relates to targeting ANTXR1. + CAF or FAP + Combinations of CAF drugs are used to treat cancer patients, especially those with ANTXR1. + Fibroblasts or CAFs, especially those with ANTXR1 in tumor samples from the subjects. + Use in fibroblasts or CAF subjects. It relates to a method for treating subjects with cancer, including selecting those with ANTXR1. + Patients with fibroblasts or CAF who are treated with a therapeutically effective dose of targeted ANTXR1 + CAF or FAP + The method also includes administering a therapeutically effective amount of immunotherapy. The invention also relates to a product or kit containing a) a target ANTXR1. + CAF or FAP + CAF medications and b) immunotherapy, as combination formulations, are available for simultaneous, separate, or sequential use to treat patients, especially those with ANTXR1. + Cancer in patients with fibroblastic or CAF. Specifically, the tumor samples of the subjects have a moderate to high percentage of ANTXR1 in the cancer samples. + Fibroblasts or CAFs.

[0193] This invention also relates to a method for selecting cancer patients to use targeted ANTXR1 + CAF or FAP + A method of drug treatment for CAF, the method comprising detecting immunosuppressive fibroblasts or CAF as disclosed above and selecting those with ANTXR1 in cancer samples from patients. + Patients with fibroblasts or CAF.

[0194] Specifically, the agent inhibits or reduces ANTXR1 + Immunosuppressive effects of fibroblasts or CAFs.

[0195] Preferably, the agent is selected from: ANTXR1 inhibitors, optionally anti-ANTXR1 antibodies conjugated with cytotoxic drugs, multispecific molecules containing an anti-ANTXR1 moiety, anti-ANTXR1 T cell receptors (TCRs), anti-ANTXR1 chimeric antigen receptors (CARs), and immune cells, preferably T cells, expressing anti-ANTXR1 TCRs or anti-ANTXR1 CARs, or any combination thereof.

[0196] Additionally or alternatively, the agent is selected from: FAP inhibitors, anti-FAP antibodies optionally conjugated with cytotoxic drugs, multispecific molecules containing an anti-FAP moiety, anti-FAP T cell receptors (TCRs), anti-FAP chimeric antigen receptors (CARs), and immune cells, preferably T cells, expressing anti-FAP TCRs or anti-FAP CARs, or any combination thereof.

[0197] In particular, ANTXR1 inhibitors can be, for example, ebselen or phenylmercuric acetate.

[0198] FAP inhibitors (FAPI) may be selected from: tarabuxostat, PT-100, liralistin (Tradjenta), such as Jansen et al., ACS Med Chem Lett. May 9, 2013; 4(5):491–496; FAP inhibitors having an N-(4-quinolinyl)-glycyl-(2-cyanopyrrolidine) skeleton, such as MIP-1232 described in Mueller et al., J Biol Chem 1999; 274:24947-52; and FAP inhibitors such as FAPI-02 and FAPI-04 described in Lindner et al., EJNMMI Radiopharmacy and Chemistry (2019) 4:16 and Lidner et al., Journal of Nuclear Medicine, April 6, 2018. For example, FAP inhibitors are described in WO20081522, WO20132661, WO20245173, WO21005125, WO21005131, US2020246383, WO19154859, WO19083990, WO19118932, WO18111989, WO17189569, WO13107820, WO08116054, or WO07085895, the disclosures of which are incorporated herein by reference. FAP inhibitors can also be FAP-binding peptides linked to a radionuclide (e.g., lutetium-177), such as the FAP inhibitor FAP-2286 developed by Clovis Oncology.

[0199] In one particular embodiment, the present invention relates to the use of FAP inhibitors in treating or for treating cancer subjects, said subjects including ANTXR1. + Fibroblasts or CAFs, especially those with ANTXR1 in tumor samples from said subjects or in the tumor microenvironment. + Fibroblasts or CAFs.

[0200] In one embodiment, the agent is an anti-ANTXR1 or anti-FAP antibody. The antibody of the present invention can be any type of antibody. In particular, the antibody can comprise, consist of, or be substantially composed of a classic Y-shaped antibody having two heavy chains and a light chain or fragments thereof. Preferably, the fragment comprises the antigen-binding or variable region of the antibody. The fragment may be selected from, but is not limited to, Fv, Fab, Fab', F(ab)2, F(ab')2, F(ab)3, Fv, single-chain Fv (scFv), di-scFv or sc(Fv)2, dsFv, Fd, dAb, CDR, VH, VL, VHH, V-NAR, nanobodies, microbodies, bispecific antibodies, and multispecific antibodies formed from antibody fragments.

[0201] The antibodies of the present invention can be monomeric antibodies or polysodium antibodies. In particular, the antibodies of the present invention are monomeric antibodies.

[0202] The antibodies of the present invention can be monoclonal or polyclonal. Preferably, the antibodies of the present invention are monoclonal.

[0203] In another preferred embodiment, the targeting agent is an anti-ANTXR1 or anti-FAP antibody, or a peptide binding to ANTXR1 or FAP, conjugated to a drug, preferably a cytotoxic drug. Optionally, the anti-ANTXR1 or anti-FAP antibody may have inhibitory or antagonistic activity.

[0204] The medicament of the present invention is preferably a cytotoxic drug. As used herein, the term "cytotoxic drug" refers to a molecule that, upon contact with a cell, is ultimately internalized into the cell and, in a harmful manner, alters cell function (e.g., cell growth and / or proliferation and / or differentiation and / or metabolism such as protein and / or DNA synthesis) or causes cell death. As used herein, the term "cytotoxic drug" includes toxins, particularly cytotoxins.

[0205] The cytotoxic drugs of this invention may be selected from: dolastatins such as dolastin 10, dolastin 15, auristatin E, auristatin EB (AEB), auristatin EFP (AEFP), monomethyl auristatin F (MMAF), monomethyl auristatin-D (MMAD), monomethyl auristatin E (MMAE), and 5-benzoylvaleric acid-AE ester (AEVB); maytansines such as ansamitocin, mertansine (also known as emtansine or DM1), and ravtansine (also known as soravtansine or DM4); and anthracyclines such as daunorubicin, epirubicin, pirarubicin, idarubicin, and zorubicin. Doxorubicin, cerubidin, aclarubicin, adriblastin, doxorubicin, mitoxantrone, daunoxome, nemorubicin, and PNU-159682; calicheamicins such as calicheamicin β1Br, calicheamicin γ1Br, calicheamicin α2I, calicheamicin α3I, calicheamicin β1I, calicheamicin γ1L, calicheamicin δ1I, and ozogamicin; esperamicins such as esperamicin A1; neocarzinostatins; bleomycin; docalamycins such as CC-1065 and docalamycin A; and pyrrolobenzodiazepines. Examples include antramycin, abbeymycin, chicamycin, DC-81, mazethramycin, neothramycin A and B, porothramycin, prothracarcin, sibanomicin (DC-102), sibiromycin, and tomamycin, as well as pyrrolobenzodiazepines. Dimers (or PBDs), indo-benzodiazepines Class, indo-benzodiazepine Dimers, α-Amanitain derivatives, abraxane, actinomycin, aldesleukin, altretamine, alitretinoin, amsacrine, anastrozole, arsenic, asparaginase, azacitidine, azathioprine, bexarotene, bendamustine, bicalutamide, bortezomib, busulfan ( Busulfan, Capecitabine, Carboplatin, Carmustine, Chlorambucil, Cisplatin, Cladribine, Clofarabine, Cyclophosphamide, Cytarabine, Chloramphenicol, Cyclosporin, Cidofovir, Coal tar-containing products, Colchicine, Dacarbazine, Actinol Scutellaria D, danazol, dasatinib, diethylstilbestrol, dinoprostone, dithranol, dutasteride, dexrazoxane, docetaxel, doxifluridine, erlotinib, estramustine, etoposide, exemestane, finasteride, flutamide, fluorouridine, flucytosine Pyridine, Fludarabine, Fluorouracil, Ganciclovir, Gefitinib, Gemcitabine, Goserelin, Hydroxyurea, Hydroxycarbamide, Ifosfamide, Irinotecan, Imatinib, Lenalidomide, Leflunomide, Letrozole, Leuprorelin Acetate, Lomustine, DichloromethyldiethylamineMelphalan, thiopurine, methotrexate, mitomycin, mitotane, gonadotropins, mifepristone, nafarelin, nelarabin, nitrogen mustard, nitrosourea, oxaliplatin, ozogamicin, paclitaxel, podophyllyn, polyethylene glycol asparaginase, pemetrexed, pentamidine. Pentostatin, procarbazin, raloxifene, ribavarin, raltitrexed, rituximab, romidepsin, sorafenib, streptozocin, sunitinib, sirolimus, streptozocin, temozolomide Temsirolimus, teniposide, thalidomide, thioguanine, thiotepa, topotecan, tacrolimus, taxotere, tafluposide, toremifene, tretinoin, trifluridine, triptorelin, valproic acid Acyclovir, valrubicin, vinblastine, vidaradine, vincristine, vindesine, vinorelbine, vemurafenib, vismodegib, vorinostat, zidovudine, vedotine, and their derivatives and combinations. The cytotoxic agents may also be radionuclides, such as lutetium-177, iodine-131, samarium-153, and yttrium-90, or astatine-211, bismuth-212, lead-212, bismuth-213, actinium-225, radium-223, and thorium-227.

[0206] In a preferred embodiment, the antibody-drug conjugate of the present invention comprises a linker between an antibody and a drug. The linker of the present invention may be cleavable or non-cleavable; preferably, the linker is cleavable. Examples of cleavable linkers of the present invention include, but are not limited to, disulfides, hydrazones, and peptides. Examples of non-cleavable linkers of the present invention include, but are not limited to, thioethers.

[0207] In one particular embodiment, the drug is linked to a cysteine ​​or lysine residue of the antibody. Preferably, the drug or antigen is linked to a non-natural amino acid already incorporated into the antibody.

[0208] Methods for preparing antibody-drug conjugates are well known to those skilled in the art.

[0209] In one embodiment, the agent is an anti-ANTXR1 or anti-FAP CAR cell. As used herein, the terms "chimeric antigen receptor" (CAR), "engineered cell receptor," "chimeric cell receptor," or "chimeric immune receptor" (ICR) refer to an engineered receptor that transplants antigen-binding specificity (e.g., antibodies) onto immune cells (e.g., T cells or NK cells), thereby combining the antigen-binding properties of the antigen-binding domain with the immunogenic activity of the immune cell, such as its lysis capacity and self-renewal. CAR cells targeting ANTXR1 are available to those skilled in the art. For example, anti-ANTXR1 CAR T cells are described in patent applications KR1020190013612, US2016264662A, US2017114133A and CN108707199A, and in publications such as Byrd et al. (Cancer Res. 2018; 78(2):489–500.10.1158 / 0008-5472.CAN-16-1911).

[0210] The present invention also relates to a pharmaceutical composition comprising an ANTXR1 and / or a FAP CAF target, preferably an FAP inhibitor, an ANTXR1 inhibitor, an anti-FAP antibody, an anti-ANTXR1 antibody, or any combination thereof, wherein the antibody is optionally conjugated to a drug, preferably a cytotoxic drug as described above, or a combination thereof. In particular, such a pharmaceutical composition comprises at least one pharmaceutically acceptable excipient. For this formulation, conventional excipients may be used according to techniques known to those skilled in the art.

[0211] The formulation can be sterilized and, if desired, mixed with adjuvants such as pharmaceutically acceptable carriers, excipients, salts, antioxidants, and / or stabilizers that do not adversely interact with the ANTXR1 and / or FAP CAF targeting agents.

[0212] Optionally, the pharmaceutical composition may also contain additional therapeutic agents, particularly, for example, the immunotherapeutic agents described above.

[0213] Those skilled in the art will understand that the formulations of the present invention are isotonic with human blood, meaning that the formulations of the present invention have substantially the same osmotic pressure as human blood. Such isotonic formulations typically have an osmotic pressure of about 250 mOSm to about 350 mOSm. Isotonicity can be measured, for example, by vapor pressure or a cryo-osmometer.

[0214] The ANTXR1 of the present invention + CAF and / or FAP + The dosage of the CAF-targeting agent or the pharmaceutical composition of the present invention can be determined by standard procedures known to those skilled in the art. The patient's physiological data (e.g., age, body size, and weight) and route of administration must be taken into account to determine an appropriate dosage so that the patient is given a therapeutically effective amount.

[0215] When the combination formulations, kits, or products of the present invention are administered separately or sequentially, especially when administered separately, it is preferred to use the ANTXR1 of the present invention prior to immunotherapy. + CAF and / or FAP + Treatment with CAF-targeting agents. The treatment method may also include the following steps: applying the ANTXR1 of the present invention. + CAF and / or FAP + ANTXR1 is identified after CAF-targeted therapy and preferably before immunotherapy. + CAF and / or FAP + The percentage of CAF only in ANTXR1 + The percentage of CAF is low or there is no ANTXR1 + Immunotherapy is only used in cases of coronary artery disease (CAF).

[0216] Uses of immunotherapy as a treatment and therapy

[0217] In one particular aspect, the invention also relates to an immunotherapy for treating a patient with cancer, preferably an immune checkpoint inhibitor therapy, wherein the cancer sample from the patient presents with:

[0218] (a) Low levels or low percentages of ANTXR1 + Fibroblasts, especially ANTXR1 + CAF; or

[0219] (b) No ANTXR1 + Fibroblasts, especially those without ANTXR1 + CAF.

[0220] The present invention also relates to the use of immunotherapy, preferably immune checkpoint inhibitor therapy, in the manufacture of a medicament for treating cancer, wherein the cancer sample of said patient presents with:

[0221] (a) Low levels or low percentages of ANTXR1 + Fibroblasts or CAFs; or

[0222] (b) No ANTXR1 + Fibroblasts or CAFs.

[0223] The present invention also relates to a method for treating a patient with cancer, wherein the patient is selected if the following conditions are present in a cancer sample from the patient:

[0224] (a) ANTXR1 in tumors + The percentage of fibroblasts or CAFs is low.

[0225] (b) No ANTXR1 was found in the tumor. + Fibroblasts or CAFs, and the method includes the step of administering immunotherapy to the patient, preferably immune checkpoint inhibitor therapy.

[0226] ANTXR1 + The percentage of fibroblasts or CAFs is as described above. ANTXR1 + Fibroblasts or CAFs are as described above, cancer is as defined below, and immunotherapy is as defined above.

[0227] Preferably, ANTXR1 + CAF is selected from FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and ANTXR1 + SDC1 - LAMP5 - CD9 + FAP is preferred + ANTXR1 + LAMP5 - SDC1 + CAF and / or FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF.

[0228] Optional, ANTXR1 + CAF is FAP + ANTXR1 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - CAF. Optional, ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - CAF. Optional, ANTXR1 + CAF is trauma-myCAF (ANTXR1) + SDC1 - LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 -), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0229] Preferably, the immunotherapy is an immune checkpoint inhibitor immunotherapy, preferably selected from anti-CTLA-4 antibody, anti-PD-1 antibody and anti-TIGIT antibody or any combination thereof, more preferably anti-CTLA-4 antibody and / or anti-PD-1 antibody.

[0230] The present invention also relates to a method for treating a cancer in a subject, wherein a therapeutically effective dose of the ANTXR1+CAF and / or FAP+CAF targeting agent of the present invention, or a pharmaceutical composition comprising such a targeting agent, is administered to the subject suffering from cancer, wherein the cancer of the patient or a cancer sample from the patient contains ANTXR1. + CAF, preferred FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF, and / or ANTXR1 + SDC1 - LAMP5 - CD9 + FAP is preferred + ANTXR1 + LAMP5 - SDC1 + CAF and / or FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF. Specifically, the ANTXR1 of the present invention... + CAF and / or FAP + The dosage of the CAF-targeting agent or the pharmaceutical composition of the present invention can be determined by standard procedures known to those skilled in the art. The patient's physiological data (e.g., age, body size, and weight) and route of administration must be taken into account to determine an appropriate dosage so that the patient is given a therapeutically effective amount.

[0231] In some embodiments, the immunotherapy of the present invention treats and targets ANTXR1.+ Fibroblast-targeting agents, FAP-targeting agents + Fibroblast-specific agents and / or pharmaceutical compositions are administered in combination with additional cancer therapies. In particular, the immunotherapy of the present invention targets ANTXR1. + Fibroblast-targeting agents, FAP-targeting agents + Fibroblast-based agents and / or drug compositions are used in combination with other targeted therapies, other immunotherapies, chemotherapy, and / or radiotherapy.

[0232] In some embodiments, the immunotherapy of the present invention treats and targets ANTXR1. + Fibroblast-targeting agents, FAP-targeting agents +Fibroblast-modifying agents and / or pharmaceutical compositions are administered in combination with chemotherapy to the patients. As used herein, the term "chemotherapy" has its general meaning in the art and refers to treatment involving the administration of chemotherapeutic agents to a patient. Chemotherapy agents include, but are not limited to: alkylating agents such as thiotepa and cyclophosphamide; alkyl sulfonates such as busulfan, improsulfan, and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethyleneimines and methylamelamines, including altretamine, triethylamine, triethylphosphamide, and triethylthiophosphamide. Amines and tris(hydroxymethyl)melamine; acetogenins (especially bullatacin and bullatacinone); camptothecin (including its synthetic analogue topotecan); bryostatin; callystatin; CC-1065 (including its synthetic analogues adozelesin, carzelesin, and bizelesin); cryptophycins (especially cryptophycin 1 and cryptophycin 8); Dolastatin; Docamycin (including synthetic analogs, KW-2189 and CB1-TM1); Elutherobin; Pancratistatin; Sarcodictyin; Spongistatin; Nitrogen mustards, such as chlorambucil, chlornaphazine, cholophosphamide, estradiol, ifosfamide, dichloromethyldiethylamine, dichloromethyldiethylamine hydrochloride, melphalan, novombhichin, phenesterine, and pine sulfadiazine. (prednimustine), trofosfamide, uracil nitrogen mustard; nitrosoureas, such as carmustine, chlorozotocin, formostine, lomustine, nimustine, and ranimnustine; antibiotics, such as enediyne antibiotics (e.g., calichimycin, especially calichimycin γ and calichimycin ω); dynemicin, including dynemicin A; bisphosphonates, such as clodronate disodium; esperamycin;And new carcinogen chromophores and related chromopeptide chromophores, aclacinomysins, actinomycins, authrarnycin, azaserine, bleomycin, actinomycin C, carabicin, caminomycin, carzinophilin, chromomycinis, actinomycin D, daunorubicin, detorubicin, 6-hexamethasone Nitrogen-5-oxo-L-leucine, doxorubicin (including morpholino-doxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolidinyl-doxorubicin, and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcellomycin, mitomycin C, mycophenolic acid, nogalamycin, olivomycins, peplomycin, po Tfiromycin, puromycin, quelamycin, rodorubicin, streptomycin, strepzotocin, tuberculin, ubenimex, fentostatin, zorubicin; antimetabolites, such as methotrexate and 5-fluorouracil (5-FU); folic acid analogs such as denopterin, methotrexate, pteropterin, trimethoprim. Exate; purine analogs, such as fludarabine, 6-mercaptopurine, thiamiprine, and thioguanine; pyrimidine analogs, such as ancitabine, azacitidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, docefluuridine, enocitabine, and fluorouridine; androgens, such as calusterone and dromostanolone. Propionate, epitiostanol, meandrolone, testosterone; anti-adrenergic hormones such as aminoglutethimide, mitotane, trilostane; folic acid supplements such as frolinic acid; aceglatone; aldehyde phosphoramide glycoside; aminolevulinic acid; eniluracil; amsacrine; bestrabucil; bisantrene; edatraxate; defofamine;Demecolcine; diziquone; elformithine; elliptinium acetate); epothilone; etoglucid; gallium nitrate; hydroxyurea; lentinan; lonidainine; maytansine compounds, such as metansen and anserine; mitoguazone; mitoxantrone; mopidanmol; nitraerine; pentostatin; phenamet; pirarubicin; losoxantrone; podophyllotoxin; 2-ethylhydrazine; methylhydrazine derivatives, including N-methylhydrazine (MIH) and procarbazine; PSK polysaccharide complex; razoxane; rhizoxin; sizofuran; spirogermanium; tenuazonic acid acid); triaziquone; 2,2',2"-trichlorotriethylamine; trichothecene compounds (especially T-2 toxin, verracurin) A. Baculosporins (roridin A and anguidine); urethan; vincristine; dacarbazine; mannitol mustard; dibromomannitol; dibromoeutherol; piperbbromide; gacytosine; arabinoside (“Ara-C”); cyclophosphamide; thiotepa; taxanes, such as paclitaxel and docetaxel; chlorambucil; gemcitabine; 6-thioguanine; mercaptopurine; methotrexate; platinum coordination complexes, such as cisplatin, oxaliplatin, and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; vinorelbine; novantrone; teniposide; edatrexate; daunorubicin; aminopterin Xeloda; ibandronate; irinotecan (e.g., CPT-11); topoisomerase inhibitor RFS2000; difluoromethylornithine (DMFO); retinoids such as retinoic acid; capecitabine; anthracyclines, nitrosoureas, antimetabolites, epipodophyllotoxins, enzymes such as L-asparaginase; anthraquinones; hormones and antagonists, including corticosteroid antagonists such as prednisone and its equivalents, dexamethasone and aminoglutethimide; progestins such as hydroxyprogesterone caproate, medroxyprogesterone acetate and megestrol acetate; estrogens such as diethylstilbestrol and ethinylestradiol equivalents; anti-estrogens such as tamoxifen; androgens, including testosterone propionate and fluoxymesterone / equivalents.Antiandrogens, such as flutamide, gonadotropin-releasing hormone analogs, and leuprolide; and nonsteroidal antiandrogens, such as flutamide; and any pharmaceutically acceptable salts, acids, or derivatives thereof.

[0233] In some embodiments, the present invention includes immunotherapy treatments, agents targeting ANTXR1+ fibroblasts, and agents targeting FAP. +Fibroblast-derived agents and / or pharmaceutical compositions are administered in combination with radiotherapy to the patient. Suitable examples of radiotherapy include, but are not limited to, external beam radiotherapy (such as superficial X-ray therapy, positive voltage X-ray therapy, ultra-high voltage X-ray therapy, radiosurgery, stereotactic radiotherapy, fractionated stereotactic radiotherapy, cobalt therapy, electron therapy, fast neutron therapy, neutron capture therapy, proton therapy, intensity-modulated radiotherapy (IMRT), three-dimensional conformal radiotherapy (3D-CRT), etc.); brachytherapy; unsealed source radiotherapy; helical tomotherapy; and so on. Gamma rays are another form of photon used in radiotherapy. Gamma rays are spontaneously generated when certain elements (such as radium, uranium, and cobalt-60) release radiation upon their decomposition or decay. In some embodiments, radiotherapy may be proton therapy or proton microbeam radiotherapy. Proton therapy is a form of ultra-precise radiotherapy using proton beams (Prezado Y, Jouvion G, Guardiola C, Gonzalez W, Juchaux M, Bergs J, Nauraye C, Labiod D, De Marzi L, Pouzoulet F, Patriarca A, Dendale R. Tumor Control in RG2 Glioma-Bearing Rats: A Comparison Between Proton Minibeam Therapy and Standard Proton Therapy. Int J Radiat Oncol Biol Phys. 2019 1 1; 104(2):266-271. doi:10.1016 / j.ijrobp.2019.01.080; Prezado Y, Jouvion G, Patriarca A, Nauraye C, Guardiola C, Juchaux M, Lamirault C, Labiod D, Jourdain L, Sebrie C, Dendale R, Gonzalez W, Pouzoulet F. Proton minibeam radiation therapy widens the therapeutic index for high-grade gliomas. Sci Rep. 2018 Nov 7; 8(1):16479. doi:10.1038 / s41598-018-34796-8). Radiation therapy can also be FLASH radiotherapy (FLASH-RT) or FLASH proton irradiation.FLASH radiotherapy involves delivering radiation therapy at ultra-high dose rates (ultra-high dose rates) that are several orders of magnitude higher than current routine clinical practice. (Favaudon V, Fouillade C, Vozenin MC. The radiotherapy FLASH to save healthy tissues. Med Sci (Paris) 2015; 31:121-123. DOI:10.1051 / medsci / 20153102002); Patriarca A., Fouillade CM, Martin F., Pouzoulet F., Nauraye C. et al. Experimental setup for FLASH protonirradiation of small animals using a clinical system. Int J Radiat Oncol Biol Phys, 102 (2018), 619-626. doi:10.1016 / j.ijrobp.2018.06.403. e.g. July 11, 2018).

[0234] Patients, protocols and administration

[0235] Patients are animals, preferably mammals, and even more preferably humans. However, patients can also be non-human animals requiring treatment, especially mammals such as dogs, cats, horses, cattle, pigs, sheep, donkeys, rabbits, ferrets, gerbils, hamsters, gray rats, rats, mice, guinea pigs, and non-human primates.

[0236] The human patients of the present invention can be prenatal humans, newborns, children, infants, adolescents or adults, especially adults who are at least 30 or at least 40 years old, preferably adults who are at least 50 years old, more preferably adults who are at least 60 years old, and even more preferably adults who are at least 70 years old.

[0237] In one implementation, the patient is an active smoker or a former smoker.

[0238] Preferably, the patient has been diagnosed with cancer. In another specific embodiment, the patient has metastatic or advanced cancer. In one embodiment, the patient has been diagnosed with stage III or IV cancer.

[0239] In one implementation, the patient with cancer has metastases, particularly to the brain, liver, bones, and / or adrenal glands.

[0240] In one particular implementation, the patient has received at least one treatment regimen, particularly one, two, or three or more, preferably several. Alternatively, the patient has not yet received any treatment. In particular, the patient has received nivolumab, pembrolizumab, ipilimumab, or any combination thereof.

[0241] Cancer treatment, especially immunotherapy or treatment containing anti-ANTXR1 or anti-FAP agents, can be administered via any conventional route of administration, such as local, enteral, oral, parenteral, intranasal, intravenous, intramuscular, subcutaneous, or intraocular.

[0242] Specifically, cancer treatment can be immunotherapy, surgery, chemotherapy, radiotherapy, hormone therapy, targeted therapy, palliative care, treatments containing anti-ANTXR1 or anti-FAP agents, and any combination thereof.

[0243] Preferably, when determining ANTXR1 + Fibroblasts, especially ANTXR1 + Cancer treatment should begin no more than one month after the presence of CAF, preferably no more than one week later.

[0244] Cancer treatment can be administered as a single dose or in multiple doses.

[0245] Preferably, cancer treatment is administered regularly, preferably between daily and monthly, more preferably between daily and bi-weekly, and even more preferably between daily and weekly.

[0246] The duration of treatment is preferably between 1 day and 24 weeks, more preferably between 1 day and 10 weeks, and even more preferably between 1 day and 4 weeks. In one particular embodiment, treatment continues as long as the cancer persists.

[0247] The dosage of cancer treatment, particularly immunotherapy or treatments involving anti-ANTXR1 or anti-FAP agents, is determined by standard procedures known to those skilled in the art. Patient physiological data (e.g., age, body type, weight, and general physical condition) and route of administration must be taken into account to determine an appropriate dosage so that the patient is given a therapeutically effective amount.

[0248] In the case of a combination of active ingredients, the active ingredients can be administered to the target via the same or different routes of administration. The route of administration generally depends on the pharmaceutical composition used.

[0249] cancer

[0250] The method of the present invention is intended to select and / or treat patients with tumors.

[0251] In one embodiment, the tumor originates from a selection of cancers including: leukemia, seminoma, melanoma, teratoma, lymphoma, non-Hodgkin's lymphoma, neuroblastoma, glioma, adenocarcinoma, mesothelioma (including pleural mesothelioma, peritoneal mesothelioma, pericardial mesothelioma, and terminal mesothelioma), rectal cancer, endometrial cancer, thyroid cancer (including papillary thyroid carcinoma, follicular thyroid carcinoma, medullary thyroid carcinoma, undifferentiated thyroid carcinoma, type 2A multiple endocrine tumors, type 2B multiple endocrine tumors, familial adenocarcinoma, etc.). Medullary thyroid carcinoma, pheochromocytoma, and paraganglioma; skin cancer (including malignant melanoma, basal cell carcinoma, squamous cell carcinoma, Kaposi's sarcoma, keratoacanthoma, nevus, dysplastic nevus, lipoma, hemangioma, and dermatofibroma); nervous system cancers; brain cancer (including astrocytoma, medulloblastoma, glioma, low-grade glioma, ependymoma, germ histoma (pineal tumor), glioblastoma multiforme, oligodendroglioma, schwannoma, retinoblastoma, congenital tumors, spinal cord nerve fibromas). Cancers include: fibromas, gliomas, or sarcomas; skull cancers (including osteomas, hemangiomas, granulomas, xanthomas, or osteitis deformans); meningeal cancers (including meningiomas, meningeal sarcomas, or gliomatosis); head and neck cancers (including squamous cell carcinoma of the head and neck and oral cancers (such as buccal cancer, lip cancer, tongue cancer, oral cavity cancer, or pharyngeal cancer)); lymph node cancers; gastrointestinal cancers; liver cancers (including liver tumors, hepatocellular carcinoma, bile duct cancer, hepatoblastoma, angiosarcoma, hepatocellular adenoma, and hemangioma); colon cancer; stomach cancer; and esophageal cancers (including squamous cell carcinoma, laryngeal cancer, and adenocarcinoma). Leiomyosarcoma or lymphoma), colorectal cancer, bowel cancer, small bowel cancer (e.g., adenocarcinoma, lymphoma, carcinoid, Kaposi's sarcoma, leiomyoma, hemangioma, lipoma, neurofibroma or fibroma), large bowel cancer (e.g., adenocarcinoma, tubular adenoma, villous adenoma, hamartoma or leiomyoma), pancreatic cancer (including ductal adenocarcinoma, islet tumor, glucagonoma, gastrinoma, carcinoid tumor or vasoactive intestinal peptide tumor), ear, nose and throat (ENT) cancer, breast cancer (including HER2-enriched breast cancer, luminal... Type A breast cancer, luminal B breast cancer, and triple-negative breast cancer; uterine cancer (including endometrial cancers such as endometrial epithelial carcinoma, endometrial stromal sarcoma, malignant Müllerian mixed tumor, uterine sarcoma, leiomyosarcoma, and gestational trophoblastic disease); ovarian cancer (including dysgerminoma, granulosa cell-theca cell tumor, and Sertoli-Leydig cell tumor); cervical cancer; vaginal cancer (including squamous cell vaginal carcinoma, vaginal adenocarcinoma, clear cell vaginal adenocarcinoma, vaginal germ cell tumor, vaginal botryoid sarcoma, and vaginal melanoma); vulvar cancer (including squamous cell vulvar carcinoma, verrucous vulvar carcinoma, vulvar melanoma, basal cell vulvar carcinoma, Bartholin's gland carcinoma, vulvar adenocarcinoma, and erythema proliferativeis); urogenital tract cancers; kidney cancer (including clear renal cell carcinoma, chromophobe renal cell carcinoma, papillary renal cell carcinoma, adenocarcinoma, Wilms' tumor, nephroblastoma, lymphoma, or leukemia); adrenal cancer; bladder cancer.Urethra cancer (e.g., squamous cell carcinoma, transitional cell carcinoma, or adenocarcinoma), prostate cancer (e.g., adenocarcinoma or sarcoma), and testicular cancer (e.g., seminoma, teratoma, embryonal carcinoma, choriocarcinoma, sarcoma, stromal cell carcinoma, fibroma, fibroadenoma, adenoma-like tumor, or lipoma), lung cancer (including small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC) including squamous cell lung cancer, lung adenocarcinoma (LUAD), and large cell lung cancer), bronchial carcinoma, alveolar carcinoma, bronchiolar carcinoma, bronchial adenoma, pulmonary sarcoma, chondroma, hamartoma, and pleural mesothelioma), sarcoma (Including Askin's tumor, botryoid sarcoma, chondrosarcoma, Ewing's sarcoma, malignant angioendothelioma, malignant schwannoma, osteosarcoma, and soft tissue sarcoma), soft tissue sarcoma (including alveolar soft tissue sarcoma, angiosarcoma, phyllodes sarcoma, dermatofibrosarcoma protuberans, desmoid sarcoma, connective tissue proliferative small round cell tumor, epithelioid sarcoma, extraosseous chondrosarcoma, extraosseous osteosarcoma, fibrosarcoma, gastrointestinal stromal tumor (GIST), hemangiopericytoma, angiosarcoma, Kaposi's sarcoma, leiomyosarcoma, liposarcoma, lymphangiosarcoma, lymphosarcoma, malignant peripheral sarcoma, etc.) Neurofibromatosis schwannoma (MPNST), neurofibrosarcoma, plexiform fibrous histiocytoma, rhabdomyosarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma; gastric cardia cancer (including sarcomas such as angiosarcoma, fibrosarcoma, rhabdomyosarcoma or liposarcoma, myxoma, rhabdomyosarcoma, fibroma, lipoma, and teratoma); bone cancer (including osteogenic sarcoma, osteosarcoma, fibrosarcoma, malignant fibrous histiocytoma, chondrosarcoma, Ewing's sarcoma, malignant lymphoma and reticulum cell sarcoma, multiple myeloma, malignant giant cell tumor chordoma, osteochondroma). Osteochondrial exostoses, benign chondromas, chondroblastomas, chondromyxofibromas, osteoid osteomas, and giant cell tumors; hematologic and lymphatic cancers, including acute myeloid leukemia, chronic myeloid leukemia, acute lymphoblastic leukemia, chronic lymphocytic leukemia, myeloproliferative disorders, multiple myeloma, and myelodyplastic syndromes; Hodgkin's disease; non-Hodgkin's lymphoma; and hairy cell and lymphatic disorders, and their metastatic cancers.

[0252] Preferably, the tumor originates from a selection of cancers including: prostate cancer, lung cancer, non-small cell lung cancer (NSCLC), breast cancer, gastric cancer, kidney cancer, ovarian cancer, hepatocellular carcinoma, osteosarcoma, melanoma, hypopharyngeal cancer, esophageal cancer, endometrial cancer, cervical cancer, pancreatic cancer, liver cancer, colon or colorectal cancer, neuroendocrine tumors, muscle cancer, adrenal cancer, adenocarcinoma, sarcoma, non-squamous cell carcinoma, squamous cell carcinoma, thyroid cancer, uterine cancer, skin cancer, melanoma, metastatic melanoma, bladder cancer, and head and neck cancer. More preferably, the cancer is selected from ovarian cancer, breast cancer, adenocarcinoma, sarcoma, non-squamous cell carcinoma, squamous cell carcinoma, lung cancer, NSCLC, colorectal cancer, pancreatic cancer, head and neck cancer, melanoma, and metastatic melanoma. In a very specific aspect, the cancer is selected from head and neck cancer, NSCLC, melanoma, and metastatic melanoma.

[0253] In one embodiment, the cancer is ovarian cancer, preferably mesenchymal ovarian cancer, especially serous high-grade ovarian cancer, or breast cancer, preferably invasive breast cancer and / or its metastatic cancer, especially axillary metastatic cancer.

[0254] In another implementation, the cancer is NSCLC or head and neck cancer.

[0255] In one implementation, the cancer is a sarcoma, particularly a fibroblastic sarcoma.

[0256] In another implementation, the cancer is selected from adenocarcinoma, non-squamous cell carcinoma, and squamous cell carcinoma.

[0257] Specifically, the patient's cancer, or cancer samples from the patient, or the tumor microenvironment contains immunosuppressive fibroblasts, particularly immunosuppressive CAFs, especially ANTXR1. + CAF or ANTXR1 + FAP + CAF.

[0258] Preferably, the patient's cancer, or a cancer sample from the patient, contains ANTXR1. + CAF, preferred FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and / or ANTXR1 + SDC1 - LAMP5 - CD9 + FAP is preferred + ANTXR1+ LAMP5 - SDC1 + CAF and / or FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF.

[0259] Optional, ANTXR1 + CAF is FAP + ANTXR1 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - CAF. Optional, ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - CAF. Optional, ANTXR1 + CAF is trauma-myCAF (ANTXR1) + SDC1 - LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and TGFb-myCAF(ANTXR1 + LAMP5 + SDC1 + / - CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is TGFb-myCAF (ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 -LAMP5 - CD9 + CAF. Optional, ANTXR1 + CAF is ecm-myCAF(ANTXR1) + SDC1 + LAMP5 - ), TGFb-myCAF(ANTXR1) + LAMP5 + SDC1 + / - ) and trauma-myCAF (ANTXR1 + SDC1 - LAMP5 - CD9 + )CAF.

[0260] Reagent test kit

[0261] Furthermore, the present invention provides a kit for performing the methods disclosed herein, the kit comprising the ability to detect ANTXR1. + Tools for fibroblasts, the ANTXR1 + Fibroblasts, especially ANTXR1 + CAF, Preferred FAP + ANTXR1 + CAF, with a higher preference for FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and / or ANTXR1 + SDC1 - LAMP5 - CD9 + CAF.

[0262] For example, the kit contains a detection kit for ANTXR1. + CAF, Preferred FAP + ANTXR1 + CAF, with a higher preference for FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and / or ANTXR1 +SDC1 - LAMP5 - CD9 + Tools required for CAF. Those skilled in the art know which tools(s) are specifically needed to determine the presence(s) of ANTXR1, preferably FAP and ANTXR1, more preferably FAP, ANTXR1, LAMP5, and SDC1; FAP, ANTXR1, LAMP5, and SDC1; and / or ANTXR1, SDC1, LAMP5, and CD9. The presence(s) can be detected at the nucleic acid level, particularly the mRNA level, or at the protein level. For example, such a tool could be for detecting ANTXR1. + CAF, Preferred FAP + ANTXR1 + CAF, with a higher preference for FAP + ANTXR1 + LAMP5 - SDC1 + CAF, FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF and / or ANTXR1 + SDC1 - LAMP5 - CD9 + CAF-specific probes, primers, antibodies, and / or aptamers. In particular, such tools are antibodies against ANTXR1, FAP, LAMP5 and SDC1, and / or CD9, such as those disclosed herein. Alternatively, such tools may be probes and / or primers specific to ANTXR1, FAP, LAMP5 and SDC1, and / or CD9.

[0263] Additionally or alternatively, the kit comprises tools, particularly nucleic acids, probes, or primers, targeting at least one gene in the gene signatures ecm-myCAF, TGFβ-myCAF, and / or trauma-myCAF, such as those disclosed above. More specifically, it comprises tools for detecting all genes in the gene signatures ecm-myCAF, TGFβ-myCAF, and / or trauma-myCAF. In particular, the tools are primers and / or probes.

[0264] The kit may be a diagnostic kit. The components of the kit may be packaged in an aqueous medium or in lyophilized form. The container of the kit typically includes at least one vial, test tube, flask, bottle, syringe, or other container in which the components can be placed, and preferably appropriately aliquoted. In cases where the kit contains more than one component, the kit typically also includes a second, third, or other additional container in which the additional components can be placed individually. However, various combinations of components may be contained in the vial.

[0265] In some embodiments, tools may be provided for sampling and / or measuring samples from individuals. The kit may also include tools for containing sterile, pharmaceutically acceptable buffers and / or other diluents. Optionally, instructions for use of such a kit may be provided.

[0266] In another aspect, the present invention also relates to the use of the kit described above in the following:

[0267] - Detect immunosuppressive cancer-associated fibroblasts (CAFs) in cancer samples from individuals with cancer;

[0268] - Predicting the response of individuals with cancer to immunotherapy treatment;

[0269] - To choose or not to select cancer patients for immunotherapy treatment;

[0270] -Select or exclude cancer patients for targeted ANTXR1 treatment + Drug treatment for CAF;

[0271] -Select or exclude cancer patients for targeted ANTXR1 treatment + Drug and immunotherapy treatments for CAF.

[0272] Other aspects and advantages of the invention will be described in the following embodiments, which should be considered illustrative rather than limiting.

[0273] Example

[0274] The inventors used a single-cell approach to identify distinct cell clusters within the immunosuppressive CAF-S1 subset. They employed single-cell RNA sequencing (scRNA-seq) to investigate cellular heterogeneity within the CAF-S1 immunosuppressive subset. As previously described, CAF-S1 fibroblasts were isolated from human BC (see Table 1 for a description of prospective cohort 1) using FACS (Costa A et al., Cancer Cell 2018; 33(3):463-79e10). In short, the inventors first excluded debris, dead cells, diploid cells, and epithelial cells (EPCAM) from the newly excised tumor.+ ), hematopoietic cells (CD45) + ), endothelial cells (CD31) + ) and red blood cells (CD235a + ()( Figure 7A The inventor will use EPCAM. - CD45 - CD31 - CD235a - The cells were considered to be enriched with fibroblasts, and then FAP and CD29 staining was performed as previously established by Costa A et al., Cancer Cell 2018; 33(3):463-79e10. Figure 7A It can distinguish CAF-S1 (FAP) 高 CD29 中-高 ) and other CAF subgroups (CAF-S2: FAP) 阴性 CD29 低 CAF-S3: FAP 阴性 CD29 中 CAF-S4: FAP 阴性 CD29 高 The inventors then performed scRNA-seq on 18,805 CAF-S1 fibroblasts from 7 BC patients prior to any treatment. After quality control, 18,296 CAF-S1 fibroblasts, with a median of 2,428 genes detected per cell, were preserved for further analysis. Unsupervised graph-based clustering identified 8 CAF-S1 clusters, which were visualized using the Unified Manifold Approximation and Projection (UMAP) algorithm. Figure 1 All clusters were found in most patients, albeit at varying levels. As indicated by the use of G1 / S and G2 / M gene signatures, no single cluster was associated with a specific stage of the cell cycle or with high proliferation (Tirosh I et al., Science 2016; 352(6282). The inventors confirmed that these distinct CAF-S1 cell clusters were detected using the label transfer algorithm described in Stuart T et al., Cell 2019; 177(7):1888-902e21. In fact, this algorithm successfully transferred all eight cluster markers in a separate CAF-S1 scRNA-seq dataset with high predictive scores, which was newly generated from the eighth BC patient.

[0275] Differential gene expression analysis revealed that each cluster was characterized by a specific transcriptional profile. Importantly, CAF-S1 signatures published in Costa A et al., Cancer Cell 2018;33(3):463-79e10, Givel et al., Nat Commun 2018;9(1):1056, and Kieffer et al., Cancer Discov. 2020;10(9):1330-1351 contained genes not limited to specific CAF-S1 clusters (Figure 11). Cluster 0 was associated with ECM remodeling, cell-matrix adhesion, and collagen formation; cluster 1 was associated with detoxification and inflammatory responses; cluster 2 was associated with responses to growth factors, TNF signaling, and interleukin pathways; cluster 3 was associated with the TGFβ signaling pathway and the matrix; cluster 4 was associated with collagen fibrillary assembly and wound healing; cluster 5 was associated with interferon-γ (IFNγ and cytokine-mediated signaling pathways); cluster 6 was associated with IFNβα signaling; and cluster 7 was associated with the actomyosin complex. For example, the inventors found that LRRC15 (leucine-rich repeat protein 15)—a marker recently identified in CAF from pancreatic cancer—and GBJ2 (gap junction protein β2) were highly expressed in cluster 0; ADH1B (alcohol dehydrogenase 1) and GPX3 (glutathione peroxidase 3) were highly expressed in cluster 1; RGMA (antisense guide molecule BMP co-receptor) and SCARA5 (class A scavenger receptor member 5) were highly expressed in cluster 2; CST1 (cystatin) and TGFβ1 were highly expressed in cluster 3; and SEMA3C (semaphorin) was highly expressed in cluster 4. 3C) and SFRP4 (secretory coil-associated protein 4) are highly expressed in cluster 4; CCL19 and CCL5 (CC motif chemokine ligands 19 and 5) are highly expressed in cluster 5; IFIT3 (interferon-induced protein 3 with triangular tetrapeptide repeats) and IRF7 (interferon regulatory factor 7) are highly expressed in cluster 6; and GGH (gamma-glutamyl hydrolase) and PLP2 (protein lipoprotein 2) are highly expressed in cluster 7. Interestingly, in human BC, the inventors were able to distinguish between myofibroblast (“myCAF”) and inflammatory fibroblast (“iCAF”) subsets, which was previously observed in FAP in pancreatic cancer. +Identified in fibroblasts (Elyada et al., Cancer Discov 2019; 9(8):1102-23; Ohlund D et al., J Exp Med 2017; 214(3):579-96). CAF-S1 clusters 1, 2, and 5 were identified as iCAFs, and clusters 0, 3, 4, 6, and 7 were identified as myCAFs. Consistent with data from pancreatic cancer, iCAFs showed high expression of chemokines and pro-inflammatory molecules such as CXCL12 (CXC motif chemokine ligand 12) and SOD2 (superoxide dismutase 2), while myCAFs expressed myofibroblast markers, including COL1A2 (type 1 collagen α2 chain) and TAGLN (transgelin). In addition, the inventors observed that iCAF cluster 5 expressed high levels of CD74, encoding a constant chain of the major histocompatibility complex (MHC) class II. CD74 has recently been shown to be specifically expressed in antigen-presenting CAFs (“apCAFs”) of pancreatic cancer, suggesting that CAF-S1 cluster 5 may be similar to such apCAFs. In summary, the inventors identified eight distinct CAF-S1 clusters in BC. Clusters 1, 2, and 5 belong to the iCAF subgroup, with cluster 5 potentially corresponding to the apCAF cluster, while clusters 0, 3, 4, 6, and 7 belong to the myCAF subgroup. Furthermore, the iCAF clusters are characterized by detoxification (cluster 1), response to stimuli (cluster 2), IFNγ, and cytokines (cluster 5); while the myCAF clusters are characterized by ECM (cluster 0), TGFβ (cluster 3), wound healing (cluster 4), IFNαβ (cluster 6), and actomyosin (cluster 7). Therefore, the inventors identified these distinct FAPs... 高 The CAF-S1 clusters are named as follows: Cluster 0 = ecm-myCAF, Cluster 1 = detoxification-iCAF, Cluster 2 = IL-iCAF, Cluster 3 = TGFβ-myCAF, Cluster 4 = trauma-myCAF, Cluster 5 = IFNγ-iCAF, Cluster 6 = IFNαβ-myCAF, and Cluster 7 = acto-myCAF.

[0276] Finally, the inventors wanted to determine whether these CAF-S1 clusters accumulated differentially across different BC subtypes. Since the inventors analyzed patients prior to any treatment, the fresh samples collected for scRNA-seq were mostly from Luminal (Lum) patients, with HER2 and TN BC patients preferentially treated in neoadjuvant settings. Therefore, there were no HER2 patients in prospective cohort 1, only two TN BC patients (Table 1). Nevertheless, in this dataset, TN BC patients still exhibited a higher proportion of iCAF clusters than LumA BC patients, while LumA BC patients accumulated more myCAF clusters (in LumA: iCAF = 43.4%, myCAF = 56.6%; in TN: iCAF = 57.1%, myCAF = 42.9%; P = 1.29e-64 according to Fisher's exact test). Due to the small number of TN BC patients in this dataset, this problem was addressed using the TCGA database, which contains RNA-Seq data from a large number of LumA and TN BC patients. Therefore, by identifying differentially expressed genes in each cluster compared to other clusters, specific signatures were defined for the five most abundant CAF-S1 clusters (accounting for up to 91% of the sequenced CAF-S1 cells). Figure 7B Because these signatures are also used to detect these clusters in melanoma, NSCLC, and HNSCC data (see Figures 3 and 6 below), the inventors then discarded any genes in these signatures that are also expressed by melanoma, NSCLC, and HNSCC cancer cells, in order to avoid any signals from cancer cells and ensure signals that are strictly specific to the CAF-S1 cluster. Figure 7B Specificity for CAF-S1 cluster signatures). From the TCGA RNA-seq database ( https: / / portal.gdc.cancer.gov / The differential expression of CAF-S1 cluster-specific signatures between LumA and TN BC subtypes was assessed. This confirmed the accumulation of iCAF clusters in TN and myCAF clusters in LumA BC. Specifically, detoxification-iCAF and IL-iCAF were expressed higher in TN than in Lum BC, while ecm-myCAF, TGFβ-myCAF, and trauma-myCAF were expressed higher in LumA BC. This increase in iCAF content in TN BC is consistent with reports of high levels of TILs in some TN BCs. In summary, the large number of FAPs isolated from BCs... + scRNA-seq of CAF-S1 fibroblasts revealed eight clusters exhibiting distinct signatures and differential accumulation in the BC subtype.

[0277] CAF-S1 cell clusters in BC were validated by multicolor flow cytometry.

[0278] The inventors' next goal was to validate CAF-S1 clusters using multicolor flow cytometry (FACS) on fresh BC samples. By analyzing the percentage of each cluster in CAF-S1 as defined by scRNA-seq, the top 5 clusters were initially observed to account for up to 91% of the total sequenced cells. Therefore, the inventors decided to focus the FACS analysis on these 5 most abundant clusters and attempt to identify surface markers for each cluster. Using pairwise comparisons of CAF-S1 cluster expression profiles, 6 surface markers were identified with commercially available antibodies, and a gating strategy was designed to identify the 5 most abundant clusters (…). Figure 8 The inventors sought to validate the specificity of these six biomarkers in an independent CAF-S1 dataset. To this end, they investigated CAF-S1 scRNA-seq data corresponding to the 8th patient, in which cluster biomarkers were successfully transferred using a biomarker transfer algorithm. In fact, relying on these six biomarkers and a gating strategy based on seven BC patients, the five most abundant CAF-S1 clusters in this independent dataset were effectively characterized. In this way, it was confirmed that these biomarkers are specific to each CAF-S1 cluster. Therefore, fresh BC samples were analyzed using FACS with the following gating strategy applied: firstly, based on the differentiation of myCAF (ANTXR1) in BC... + Fibroblasts and iCAF (ANTXR1) - CAF-S1 fibroblasts were isolated by measuring ANTXR1 protein levels in fibroblasts (isolated as CD45). - EPCAM - CD31 - CD235a - FAP 高 CD29 中 Next, ANTXR1 was differentiated based on SDC1, LAMP5, and CD9 protein levels. + (myCAF) CAF-S1 clusters 0 (ecm-myCAF), 3 (TGFβ-myCAF), and 4 (trauma-myCAF). ANTXR1 + SDC1 + LAMP5 - Defined as cluster 0 (ecm-myCAF), ANTXR1 + LAMP5 + SDC1 + / - For cluster 3 (TGFβ-myCAF) and ANTXR1 + SDC1 - LAMP5 - CD9 + Cluster 4 (trauma-myCAF). ANTXR1 was isolated using GPC3 and DLK1 markers.- (iCAF) CAF-S1 clusters 1 (detoxification-iCAF) and 2 (IL-iCAF). ANTXR1 - GPC3 + DLK1 + / - Defined as cluster 1 (detoxification-iCAF); ANTXR1 - GPC3 - DLK1 + Cluster 2 (IL-iCAF). LAMP5, SDC1, and CD9-negative ANTXR1 were used. + CAF-S1 cells and ANTXR1 - GPC3 - DLK1 - Cells were merged and referred to as “other clusters”. The existence of these five most abundant clusters was validated in BC by applying this gating strategy to 44 fresh samples (prospective cohort 2, Table S1). Figure 2 The percentage of each cluster of CAF-S1 cells determined by FACS confirmed the single-cell results, including significant heterogeneity among CAF-S1 fibroblasts and the fact that ecm-myCAF was the most abundant population in most patients. Figure 2 The inventors then analyzed whether there were any correlations between the proportions of these five CAF-S1 clusters among patients. The relative abundances of ecm-myCAF and TGFβ-myCAF (both myCAFs) were correlated, as were detoxification-iCAF and IL-iCAF (both iCAFs). Conversely, the proportions of ecm-myCAF and TGFβ-myCAF were inversely correlated with the proportions of detoxification-iCAF and IL-iCAF. Furthermore, trauma-myCAF was negatively correlated with detoxification-iCAF, IL-iCAF, and ecm-myCAF, suggesting that these different CAF-S1 clusters may accumulate differentially in BC, but in a coordinated manner.

[0279] Identification of CAF-S1 cell clusters across cancer types

[0280] The inventors then sought to examine the presence of CAF-S1 cell clusters in other cancer types. To this end, they analyzed publicly available scRNA-seq data from head and neck squamous cell carcinoma (HNSCC) (Puram SV et al., Cell 2017; 171(7):1611-24e24) and non-small cell lung cancer (NSCLC) (Lambrechts D et al., Nat Med 2018; 24(8):1277-89), as these two studies had isolated enough CAFs to study the clusters. These published studies included 18 HNSCC patients with 5 pairs of paired primary tumors and lymph node metastases, and a total of 5902 whole cells were analyzed (Puram SV et al., Cell 2017; 171(7):1611-24e24). In addition, over 52,000 whole cells were collected from 5 different patients in the NSCLC cohort (Lambrechts D et al., Nat Med 2018; 24(8):1277-89). In these two studies, 1422 cells and 1465 cells were labeled CAF in the HNSCC and NSCLC cohorts, respectively. To rigorously analyze CAF-S1 fibroblasts, data were collected based on CAF-S1 (FAP) fibroblasts. 高 MCAM 低 ) and CAF-S4 (FAP) 低 MCAM 高 The expression of two markers, FAP and MCAM, which are regulated at the RNA level, was used to distinguish CAF-S1 from CAF-S4. Further analysis was conducted on 603 CAF-S1 cells from HNSCC and 959 CAF-S1 cells from NSCLC. Similarity between CAF-S1 cells from different cancer types was compared by mixing reference (BC) and target (HNSCC or NSCLC) datasets. Data integration was performed using "anchor" correspondences between individual cells from different datasets, based on the similarity of their expression profiles, as described in Stuart T et al., Cell 2019; 177(7):1888-902 e21 (Figure 3). The inventors used a CAF-S1 cluster-specific signature defined by genes differentially expressed in each cluster compared to other clusters. Figure 7B Notably, the CAF-S1 cluster from BC was found to be similar to that from HNSCC (…). Figure 3A ) or NSCLC ( Figure 3B Systematic correspondences between CAF-S1 clusters were confirmed using specific signature visualization, revealing the ability to detect the five most abundant clusters in HNSCC and NSCLC. Figure 3A(B). Therefore, the inventors identified five of the most abundant CAF-S1 clusters in HNSCC and NSCLC, highlighting their association in other cancers.

[0281] An immunosuppressive environment is associated with specific CAF-S1 clusters.

[0282] Since the inventors demonstrated that CAF-S1 fibroblasts exert immunosuppressive effects in breast and ovarian cancers, they next investigated whether this function could be exerted by all CAF-S1 clusters or was limited to specific clusters (Figure 4). The inventors first tested whether they could detect a correlation between CAF-S1 cluster levels and immune cells. To this end, fresh BC samples (prospective cohort 2, Table 1) were characterized for CAF-S1 cluster levels and immune cell infiltration, including CD4+ cells. + CD8 + T lymphocytes and natural killer (NK) cells. The inventors tested the association between stromal cells and immune cells and analyzed variables that showed a significant correlation with at least one other variable. The correlation matrix obtained through unsupervised hierarchical clustering showed that ecm-myCAF and TGFβ-myCAF clustered together, while detoxification-iCAF and IL-iCAF clustered together, and trauma-myCAF was completely separated, suggesting that these different clusters interact differentially with T cells. Interestingly, ecm-myCAF, TGFβ-myCAF, and trauma-myCAF showed specific associations with T lymphocytes. In fact, for the first time, the proportion of ecm-myCAF in CAF-S1 fibroblasts was observed to be correlated with CD45. + Significantly associated with hematopoietic cell infiltration ( Figure 9 More specifically, the abundance of ecm-myCAF is related to PD-1. + CTLA-4 + and TIGIT + CD4 + It is associated with T lymphocyte infiltration, but not with CD8. + T lymphocytes were negatively correlated. Similarly, although no correlation was shown between TGFβ-myCAF levels and CD45 levels. + Any overall association of hematopoietic cells, but their abundance is related to CTLA-4. + CD4 + T lymphocyte infiltration is positively correlated with CD8 and is associated with CD8. +T lymphocytes are negatively correlated. Therefore, these data suggest that the abundance of ecm-myCAF and TGFβ-myCAF is associated with an immunosuppressive environment rich in Tregs. In contrast to the ecm-myCAF and TGFβ-myCAF clusters, the abundance of detoxification-iCAF and IL-iCAF is associated with CD8+. + T cell infiltration is associated with trauma-myCAF clusters and CD45. + T lymphocytes within cells are related to the whole body ( Figure 9 ) and CTLA-4 + TIGIT + PD-1 + and NKG2A + CD4 + T lymphocytes were negatively correlated. Enrichment of trauma-myCAF was also associated with CTLA-4. + CD8 + TIGIT CD8 + CD244 + CD8 + CD244 + The inverse correlation between NK cell and exhaustion markers suggests that this cluster is associated with a high T lymphocyte infiltration and an overall protective immune environment. Importantly, the CAF-S1 signatures published in Costa A et al., Cancer Cell 2018; 33(3):463-79e10, Giver et al., Nat Commun 2018; 9(1):1056, and Kieffer et al., Cancer Discov. 2020; 10(9):1330-1351 failed to specifically identify CAF-S1 immunosuppressive clusters (i.e., ECM-myCAF, TGFβ-myCAF, and trauma-myCAF) associated with immunotherapy response. These clusters are ANTXR1+. Instead, we demonstrated that the most differentially expressed CAF-S1 genes were not specifically expressed in these clusters (Fig. 11), suggesting that identifying ANTXR1 as a marker for these clusters in the top CAF-S1 genes is unlikely to be a coincidence.

[0283] To validate these data in independent and large cohorts of BC patients, the association between the CAF-S1 cluster and T-cell signatures in the publicly available TCGA database was next tested. RNA-seq data from the TCGA database were able to confirm that the expression of the ecm-myCAF and TGFβ-myCAF clusters is associated with FOXP3, a major Treg marker. Figure 4B The expression of ) was positively correlated. Additionally, although trauma-myCAF did not show a true association with FOXP3, the detoxification-iCAF and IL-iCAF clusters were negatively correlated with FOXP3. Figure 4BConsistent with these data, a positive correlation was observed between the T cell cytolysis index and the detoxification-iCAF and IL-iCAF clusters, but not with ecm-myCAF, TGFβ-myCAF, or trauma-myCAF. Figure 4C In summary, while detoxification-iCAF and IL-iCAF are associated with an immune-active environment, ecm-myCAF and TGFβ-myCAF are both associated with an immunosuppressive environment, which lacks CD8+. + T lymphocytes rich in CD4 cells expressing high levels of immune checkpoints, including PD-1 and CTLA-4. + T lymphocytes.

[0284] ecm-myCAF and TGFβ-myCAF with PD-1 + and CTLA-4 + Positive feedback loop between Tregs

[0285] As stated above, the inventors observed that the abundance of ecm-myCAF and TGFβ-myCAF, rather than the abundance of detoxification-iCAF and IL-iCAF, was associated with PD-1 in BC. + and / or CTLA-4 + CD4 + The abundance of T lymphocytes is correlated. The inventors studied the role of the CAF-S1 cluster in the production of CD4-rich cells. + CD25 + The role of CAF-S1 in an immunosuppressive environment. Therefore, they established primary cultures of CAF-S1 clusters for in vitro functional assays. Although they did not achieve the establishment of every CAF-S1 cluster in culture, they successfully isolated ecm-myCAF and iCAF clusters by applying two different methods: (1) allowing CAF-S1 fibroblasts to escape and spread directly from BC samples seeded in plastic culture dishes, and (2) sorting FAPs by FACS. 高 CD29 中 The cells were expanded by culturing them in plastic culture dishes. After expansion over several weeks, these different cells were compared under the same culture conditions, i.e., with CD4+. + CD25 + T lymphocytes were co-cultured for functional assays (see below) under compatible conditions. High levels of the myCAF gene were observed in CAF-S1 cells acquired through dissemination, while high levels of the iCAF gene were observed in CAF-S1 cells isolated by sorting. The inventors therefore applied a cluster-specific signature (CSC) derived from scRNA-seq data. Figure 7BThe inventors found that disseminated CAF-S1 fibroblasts were rich in ecm-myCAF, while sorted CAF-S1 were rich in detoxification-iCAF, IL-iCAF, and IFN-iCAF clusters (see Methods section # RNA sequencing of primary CAF-S1 cell lines isolated from BC). The inventors previously demonstrated that total CAF-S1 subsets are effective against CD4+. + CD25 - T cells have no direct effect, but increase CD4. + CD25 + FOXP3 in T lymphocytes + The ratio of Tregs. Because the levels of ecm-myCAF and TGFβ-myCAF in BC are related to the levels of CD4-rich cells. + The immunosuppressive microenvironment is involved, while the iCAF cluster is not. Therefore, the inventors used previously performed functional assays, such as those by Costa A et al. (Cancer Cell 2018; 33(3):463-79 e10) and Givel et al. (Nat Commun 2018; 9(1):1056 doi 10.1038 / s41467-018-03348-z.), to compare the effects of these myCAF and iCAF clusters on CD4. + CD25 + The function of T cells.

[0286] First, the effects of myCAF and iCAF clusters on CD4 were tested in vitro. + CD25 + FOXP3 + The effect of T lymphocyte content ( Figure 5A ecm-myCAF adds CD4 + CD25 + FOXP3 in the group + The percentage of T cells and increasing the FOXP3 protein level in these T cells ( Figure 5A Conversely, iCAF clusters support CD4. + CD25 + FOXP3 + The percentage of T lymphocytes had no effect on FOXP3 protein levels. Figure 5A The inventors also tested the effects of culture on the identity and immunosuppressive activity of normal fibroblasts. Fibroblasts isolated from healthy tissue upon dissemination were FAP. 阴性-低 Furthermore, it did not exhibit immunosuppressive activity at early stages, but transformed into FAP during later passages. 阳性-高 And immunosuppressive, suggesting that long-term maintenance of CAFs on plastic culture dishes can activate them. Based on the fact that ecm-myCAF can increase CD4... + CD25 +FOXP3 + T lymphocytes, the inventors then compared the regulation of CD4 by the CAF-S1 cluster. + CD25 + FOXP3 + PD-1 on T lymphocytes + CTLA-4 + TIGIT + TIM3 + and LAG3 + The ability to measure proportions takes into account the percentage of positive cells and the surface protein levels of these immune checkpoints. Figure 5B -F). ecm-myCAF significantly increases PD-1. + and CTLA-4 + CD4 + CD25 + FOXP3 + The percentage of T lymphocytes and the level of immune checkpoints on their surface ( Figure 5B (C). In contrast to ecm-myCAF, iCAF clusters do not affect PD-1. + and CTLA-4 + The percentage of T cells does not affect CTLA-4 protein levels. Figure 5B (C). Furthermore, although the iCAF cluster increased PD-1 protein levels, the efficiency of this effect was lower than that of ecm-myCAF. Both myCAF and iCAF clusters increased CD4+. + CD25 + FOXP3 + TIGIT + Cell ratio ( Figure 5D ), and they are related to TIM3 + and LAG3 + T cells had no effect. Figure 5E Therefore, compared with ecm-myCAF observed in BC and PD-1 + and CTLA-4 + CD4 + The correlations among T lymphocytes are consistent, suggesting that CAF-S1 from ecm-myCAF enhances CD4+. + CD25 + FOXP3 + The PD-1 and CTLA-4 immune checkpoints on the surface of T lymphocytes have a direct effect on Tregs, while iCAF clusters have no or minimal effect on these cells. Finally, CD4+ was observed to have a negative effect when co-cultured with ecm-myCAF. + CD25 + Upregulation of immune checkpoints on the surface of T cells was also detected intracellularly. Figure 10A This suggests that ecm-myCAF increases total protein levels in T cells. Furthermore, the inventors found that co-culturing with ecm-myCAF increased CD4+ levels. + CD25 + The expression of FOXP3, CTLA-4, and TIGIT in T cells was also upregulated at the mRNA level. Figure 10B PD-1 RNA was almost undetectable in in vitro T cells. Furthermore, the inventors observed that CD4+ was significantly reduced when co-cultured with ecm-myCAF. + CD25 + The mRNA levels of NFAT and STAT family members in T lymphocytes were also elevated. Figure 10C Since NFAT and STAT are well-known transcriptional regulators of immune checkpoints in T cells, these data suggest that ecm-myCAF may promote CD4+ expression by activating the NFAT / STAT signaling pathway. + CD25 + Upregulation of immune checkpoints in T lymphocytes at the RNA level.

[0287] Considering the influence of the CAF-S1 cluster on Tregs, the inventors next wanted to know whether T lymphocytes could subsequently modulate CAF-S1 cluster identity. Therefore, the inventors evaluated CD4... + CD25 + Did T lymphocyte co-culture have any effect on the levels of marker clusters on the surface of CAF-S1 fibroblasts? During co-culture, to avoid any contamination from T cells, CAF-S1 cells were isolated by FACS and the cluster markers expressed on their surface were analyzed. CD4 was observed. + CD25 + Co-culture of T cells significantly increased the expression of LAMP5, a TGFβ-myCAF-specific marker, on the surface of ecm-myCAF fibroblasts. Figure 5G This suggests a connection to CD4. + CD25 + TGFβ-myCAF levels increased during T lymphocyte co-culture. This effect was detected only in myCAF and not in iCAF fibroblasts. Figure 5G This is consistent with the observation that TGFβ-myCAF and ecm-myCAF CAF-S1 fibroblasts belong to the myCAF subgroup. + CD25 + When T cells were co-cultured, the level of ANTXR1 protein in ecm-myCAF fibroblasts also showed an increasing trend (although not statistically significant), while the protein level remained strictly unchanged and low in iCAF cells. Figure 5G Quite surprisingly, the IL-iCAF biomarker DLK1 also increased during co-culture, suggesting potential plasticity between ecm-myCAF and IL-iCAF. Conversely, other biomarkers showed no significant changes during co-culture and remained high (SDC1) or low (GPC3 and CD9), as expected based on their respective cluster identities. Figure 5G These observations suggest that CD4 + CD25 + T lymphocytes may promote ecm-myCAF (ANTXR1) + SDC1 + LAMP5 - CD9 + / - ) is converted to TGFβ-myCAF(ANTXR1) + LAMP5 + SDC1 + / - CD9 + / - Both of these clusters are myCAF. In summary, the inventors found that ecm-myCAF can directly affect FOXP3. + Protein levels of PD-1 and CTLA-4 on the surface of T lymphocytes. In turn, Tregs can promote the conversion of ecm-myCAF to TGFβ-myCAF, thereby increasing the levels of these two clusters in relation to CD4. + CD25 + PD-1 + Or CTLA-4 + The establishment of positive feedback loops between T cells can explain the positive correlation observed in BC.

[0288] ecm-myCAF and TGFβ-myCAF are associated with primary resistance to immunotherapy.

[0289] Given the direct effects of specific CAF-S1 clusters on PD-1 and CTLA-4 protein levels on Treg cells, the inventors next wanted to know if some CAF-S1 clusters might be associated with immunotherapy resistance. Since they did not have data from immunotherapy-treated BCs, they utilized publicly available data from patients with metastatic melanoma treated with anti-PD-1 (pembrolizumab) therapy (Hugo W et al., Cell 2016; 165(1):35-44), a revolutionary approach to melanoma treatment. As defined in the aforementioned study, the inventors considered patients “non-responsive” to anti-PD-1 if they exhibited progressive disease, and “responsive” if they showed a complete or partial response. Through gene set enrichment analysis, they first observed that, at diagnosis, tumors in non-responsive patients were significantly rich in CAF-S1-specific gene expression, rather than in normal fibroblasts. Using a CAF-S1 cluster-specific signature, the inventors observed that, compared to responders, non-responders were enriched in ecm-myCAF, TGFβ-myCAF, and trauma-myCAF gene expression, but not in detoxification-iCAF, IL-iCAF, and IFN-iCAF clusters. Figure 6A Next, they compared the levels of each CAF-S1 cluster in responders versus non-responders. They confirmed that ecm-myCAF, TGFβ-myCAF, and trauma-myCAF expression were significantly higher in non-responders than in responders, while detoxification-iCAF and IFN-iCAF expression were similar between the two patient subgroups. Figure 6B Furthermore, the normal fibroblast content, or the cell lysis index defined in Rooney et al., Cell 2015;160(1-2):48-61, differs between reactants and non-reactants. Figure 6C Consistent with these observations, reciprocal analysis (i.e., determining the number of responders and non-responders based on low or high expression of CAF-S1 clusters) confirmed that, at diagnosis, the number of non-responders was significantly associated with tumors showing high expression of ecm-myCAF, TGFβ-myCAF, or trauma-myCAF, while other CAF-S1 clusters, total CAF content, or cell lysis index did not provide information about patient response to immunotherapy. Figure 6EIn summary, these data indicate that three specific CAF-S1 clusters (ecm-myCAF, TGFβ-myCAF, and trauma-myCAF) indicate an anti-PD-1 response in patients with metastatic melanoma at diagnosis, while other CAF-S1 clusters (detoxification-iCAF, IL-iCAF, and IFN-iCAF), total CAF content, or cell lysis index do not. Finally, the inventors sought to verify the impact of CAF-S1 clusters, particularly ecm-myCAF, TGFβ-myCAF, and trauma-myCAF, on primary immunotherapy resistance in a range of patients with metastatic NSCLC, another recently identified clinical indication for immunotherapy (here, in a second- or third-line setting with nivolumab; detailed descriptions of NSCLC group 4 are shown in Table 2). Similar to melanoma, the inventors verified that the CAF-S1 signature assessed in tumor samples taken at diagnosis was significantly enriched in unresponsive patients. Conversely, the number of normal fibroblasts was higher in responders than in non-responders, suggesting a significant enrichment of CAF-S1 in non-responders. Importantly, the inventors confirmed that ecm-myCAF, TGFβ-myCAF, and trauma-myCAF were associated with non-responders in NSCLC patients, while the detoxification-iCAF, IL-iCAF, and IFNγ-iCAF clusters were not (Figure 6I). In summary, unlike the detoxification-iCAF, IL-iCAF, and IFNγ-iCAF clusters, the abundance of ecm-myCAF and TGFβ-myCAF at diagnosis was associated with resistance to immunotherapy in both melanoma and NSCLC, which is related to their increased PD-1 content in Tregs. + and CTLA-4 + The ability to maintain protein levels is consistent.

[0290] Materials and methods

[0291] patient groups

[0292] BC patients:The studies conducted here are based on samples extracted from surgical remnants that are usable after histopathological analysis, rather than those required for diagnosis. There is no interference with clinical practice. Analysis of primary tumor samples is conducted in accordance with relevant national laws protecting the participation of biomedical researchers. All patients hospitalized at the Curie Institute (BC patients) received a welcome booklet explaining that their samples may be used for research purposes. Therefore, all patients included in the study were informed by their consulting oncologist that biological samples collected through standard clinical practice may be used for research purposes, and that they could object to such use if they wished. Remaining tumor samples were not included in the study if the patient could express their objection verbally or in writing. The human experimental procedures for analyzing the tumor microenvironment by the F. Mechta-Grigoriou laboratory were approved by the Curie Hospital Institute Group (approved February 12, 2014) and the Institutional Review Committee and Ethics Committee of CNIL (French National Commission for Information and Liberty) (Approval No.: 1674356, delivered March 30, 2013). The “Biological Resource Centre” (BRC) is part of the Pathology Department of the Diagnostic and Theragnostic Medicine Department, led by Dr. A. Vincent-Salomon. Under French law, the BRC has the authority to store and manage human biological samples. The BRC has declared its defined sample collection procedures, continuously increasing upon obtaining patient consent (Declaration No. #DC-2008-57). The BRC complies with all currently required national and international ethical guidelines, including the Declaration of Helsinki. BRC has also received AFNOR NFS-96-900 quality label certification (renewed, currently valid until 2021). Luminal (Lum) tumors are defined by positivity for ER (estrogen receptor) and / or PR (progesterone receptor) immunostaining. The cutoff for defining hormone receptor positivity is 10% of stained cells. Ki67 (proliferation) scores further differentiate Lum A from Lum B (below 15%: Lum A, above 15%: Lum B). HER2-amplified cancers are defined based on ERBB2 immunostaining using ASCO guidelines. TN immunophenotypes are defined as follows: ER expressing at least one of the following markers. - PR - ERBB2 - KRT5 / 6 + or EGF-R + .

[0293] NSCLC patients: NSCLC samples were obtained from routine diagnostic samples stored in the pathology department of Bichat Hospital, from patients treated with immuno-oncology drugs in the thoracic oncology department of Bichat Hospital, led by Dr. G. Zalcman. In accordance with French regulatory rules for observational clinical studies, de-identified clinical data were drawn from a portion of the thoracic oncology database of lung cancer patients at the Clinical Research Center (CIC-1425 / CLIP2) of Bichat Hospital (Regional Health Authority No. 17-1381, led by Dr. G. Zalcman). Patients received checkpoint inhibitors as first- or second-line treatment based on chemotherapy after progression, depending on the registered immuno-oncology drug. During this study phase, the anti-PD-1 nivolumab monoclonal antibody was the most frequently used drug in this setting. The efficacy of immuno-oncology therapy was assessed weekly by a multidisciplinary oncology committee, including thoracic radiologists, thoracic oncologists, and pulmonologists, every 8 to 12 weeks via whole-body CT scans. Target responders (OR), stable disease (SD), and patients showing tumor progression (Progr) with a tumor volume increase of more than 20% without any clinical benefit were defined according to RECIST v.1.1 criteria. This study used the best response status observed at 4 months. SD patients who received immuno-oncology therapy for more than 6 months due to clinical benefit at 4-month evaluation and without any progressive disease (i.e., long-term SD) were included in the responder group of this study. The date of progression assessed by CT scan was recorded. Some patients showed early clinical progression requiring early (within 8 weeks) CT scan evaluation. In these series, according to the above criteria, there were 22 responders and 48 progression patients, both receiving less than 4 months of treatment. The date of progression was retained as the date of RECIST progression shown on CT scan. The date and cause of death, or the date of the last known vital signs, were systematically recorded. Second- or third-line treatment was registered after progression. There was no loss of balance based on post-progression treatment. PD-L1 staining and interpretation were performed on 4μm paraffin-embedded sections by AG using commercially available Cell Signaling Technology E1L3N clones on the Leica Bond platform. These sections were derived from diagnostic, pre-treatment biopsy samples containing at least 200 tumor cells. All patients, except for 5 patients (with fewer than 200 tumor cells in residual pathological blocks), underwent PD-L1 immunohistochemical analysis.

[0294] CAF-S1 RNA sequencing at the single-cell level

[0295] Separate CAF-S1 from BC:CAF-S1 fibroblasts were isolated from a total of 8 primary BCs (surgical remnants prior to any treatment) (details of the prospective cohort are shown in Table S1). Preliminary studies were conducted on 7 BCs. Additionally, another BC sample was added to validate the CAF-S1 cluster using the marker transfer algorithm in the Seurat R package. BDFACS ARIA III was used. TM CAF-S1 fibroblasts are isolated from BC using a sorting machine (BD Biosciences). Fresh human BC primary tumors are collected directly from the operating room after a pathologist performs a macroscopic examination of the surgical specimen and selects the region of interest. The sample is then cut into small pieces (approximately 1 mm). 3 Cells were then digested for 40 minutes at 37°C with shaking (180 rpm) in CO2-independent medium (Gibco #18045-054) supplemented with 150 μg / ml release enzyme (Roche #05401020001) and DNase I (Roche #11284932001). Cells were then filtered through a 40 μm cell filter (Fisher Scientific #223635447) and digested in 50 μl at 5 × 10⁻⁶ ppm. 5 and 10 6 The final cell concentrations were determined by resuspending the cells in PBS+ solution (PBS, Gibco #14190; EDTA 2mM, Gibco #15575; human serum 1%, BioWest #S4190-100). To isolate CAF-S1 fibroblasts, the inventors first applied selection to exclude epithelial cells (EPCAM). + ), hematopoietic cells (CD45) + ), endothelial cells (CD31) + ) and CD235a +(Red blood cells) were then used with CAF-S1 markers (FAP and CD29). For this purpose, the cells in the suspension were then stained with an antibody mixture for flow cytometry cell sorting containing anti-EpCAM-BV605 (BioLegend, #324224), anti-CD31-PECy7 (BioLegend, #303118), anti-CD45-APC-Cy7 (BDBiosciences, #BD-557833), anti-CD235a-PerCP / Cy5.5 (Biolegend, #349109), anti-CD29-AlexaFluor 700 (BioLegend, #303020), and anti-FAP-APC (first antibody, R&D Systems, #MAB3715) for single-cell RNA sequencing. All antibodies except FAP were purchased pre-conjugated with fluorescent dyes. Anti-FAP antibodies were conjugated using the Zenon APC mouse IgG1 fluorescent dye labeling kit (ThermoFisher Scientific, #Z25051). The isotype control antibodies used for each CAF marker were: isotype anti-CD29 (BioLegend, #400144) and isotype anti-FAP (first antibody, R&D Systems, #MAB002).

[0296] Immediately after dissociating BC tumor samples in PBS+ solution at room temperature for 15 minutes, cell suspensions were stained with the antibody mixture. 2.5 μg / ml DAPI (Thermo Fisher Scientific, #D1306) was added prior to flow cytometry sorting. The cells were then processed using a BDFACS ARIA III cytometer for cell sorting. TM Signals were acquired on a sorter (BD biosciences). At least 5 × 10⁻⁶ signals were recorded. 5 One event. Single staining was used to compensate for anti-mouse IgG and negative control beads (BD biosciences, #552843) for each antibody. Data analysis was performed using FlowJo version X10.0.7r2. Cells were first gated based on forward (FSC-A) and side (SSC-A) scatterers (measuring cell size and granularity, respectively) to exclude debris. Dead cells were excluded based on positive staining of dead cells for DAPI. Single cells were then selected based on SSC-A versus SSC-W parameters. Gating included EPCAM. - CD45 - CD31 - CD235a - Cells, to exclude epithelial cells (EPCAM) + ), hematopoietic cells (CD45)+ ), endothelial cells (CD31) + ) and red blood cells (CD235a) + ).

[0297] Single-cell CAF-S1 RNA sequencing: After separation, CAF-S1 cells were directly collected into ribonuclease-free tubes (ThermoFisher Scientific, #AM12450) pre-coated with DMEM (GE Life Sciences, #SH30243.01) supplemented with 10% FBS (Biosera, #1003 / 500). At least 6,000 cells were collected per sample. Cell concentrations in control samples were examined under these conditions at 200,000 cells / mL. Chromium from 10X Genomics was used. TM The system used the following kit for single-cell capture, lysis, and cDNA library construction: Chromium TM SingleCell 3'Library & Gel Bead Kit v2 (10X Genomics, #120237) and Chromium TM SingleCell A Chip Kit (10X Genomics, #1000009). Gel bead (GEM) generation in emulsion, coding, post-GEM-RT (reverse transcription) cleanup, and cDNA amplification were performed according to the manufacturer's instructions. Target cells were recovered at 3,000 cells per sample to obtain sufficient cells while maintaining a low multicellularity rate. Cells were loaded onto Chromium SingleCell A chips accordingly and subjected to 12 cycles for cDNA amplification. The quality and quantity of cDNA were checked using the Agilent High Sensitivity DNA Kit (Agilent, #5067-4626) on an Agilent 2100 Bioanalyzer, and libraries were constructed according to the 10X Genomics protocol. The libraries were then run on Illumina HiSeq (for patients P5-7) and NovaSeq (for patients P1-4) at a sequencing depth of 50,000 reads per cell. Raw data processing was performed using the 10X Cell Ranger pipeline version 2.1.1, including demultiplexing of raw base identification (BCL) files into FASTQ files, alignment, filtering, encoding, and unique molecular identifier (UMI) counting. Readings were then aligned with the Homo sapiens (human) genome assembly GRCh38 (hg38).

[0298] scRNA-seq data processing

[0299] scRNAseq: Preprocessing of raw data was initially performed using the Cell Ranger software pipeline (version 2.1.1). This step included demultiplexing the raw base recognition (BCL) files into FASTQ files, aligning reads to the human genome assembly GRCh38 using STAR, and counting unique molecular identifiers (UMIs). A first set of 18,805 CAF-S1 cells from seven BC patients (corresponding to seven sequencing runs, patients 1–7) was analyzed using the Seurat R package (version 3.0.0) (Butler et al., Nat Biotechnol 2018; 36(5):411-2). A second set of 1,646 CAF-S1 cells from one BC patient (patient 8) was used for validation (see #). Marker transfer And analyze it using the same method.

[0300] Quality control: As a quality control step, low-quality cells, empty droplets, and multicellular traps were first filtered out based on the distribution (non-zero count) of unique genes detected in each cell of each patient. Cells with fewer than 200 genes and more than 6000 genes detected (for patient 1), more than 5000 genes detected (for patients 3, 5, and 6), more than 4500 genes detected (for patients 2, 7, and 8), or more than 4000 genes detected (for patient 4) were excluded. Cell distribution was also plotted based on the score of expressed mitochondrial genes. Cells with a mitochondrial gene score higher than 5% were discarded to eliminate dying cells or low-quality cells with extensive mitochondrial contamination. For each patient, the mitochondrial score was calculated using Seurat's PercentageFeatureSet function with argument mode = "^MT-". Following these QC standards, 18,296 CAF-S1 cells (patient 1 = 1,825 cells; patient 2 = 3,300 cells; patient 3 = 2,810 cells; patient 4 = 3,153 cells; patient 5 = 2,486 cells; patient 6 = 3,179 cells and patient 7 = 1,543 cells) and 1,582 CAF-S1 cells (patient 8) were ultimately stored in the first and second datasets, respectively, for downstream analysis.

[0301] Normalization and data integration:After normalizing the library size for each cell using the NormarizeData function with default parameters, the seven BC scRNA-Seq results from the first dataset were integrated using the Seurat functions FindIntegrationAnchors and IntegrateData. Canonical correlation analysis (CCA) was performed using 30 dimensions, and 30 principal components (PCs) were used for weighting in the IntegrateData function. The data was scaled using the ScaleData function, and regression was performed using the variables 'nUMI' and 'percent.mt'. The same parameters were used for normalization of the second dataset.

[0302] Clustering and data visualization: PCA dimensionality reduction was performed using default parameters. The number of included components (PCs) was evaluated using the JackStraw program, implemented with the functions JackStraw and ScoreJackStraw. 30 PCs were saved. Cells from the first dataset were clustered using a graph-based clustering method using the FindNeighbours (k=20) and FindClusters functions (res=0.35). Ten CAF-S1 clusters were obtained at this resolution. For data visualization, the non-linear dimensionality reduction technique UMAP was applied using Seurat's RunUMAP function.

[0303] Analysis of differential gene expression and signal transduction pathways: Pairwise differential analysis was used to identify specifically upregulated genes in each of the 10 clusters in the first dataset. While the median number of differentially expressed genes in each pair was 126, the number of differentially expressed genes provided by the two pairs was very limited, with only 9 genes between clusters 0 and 5, and only 22 genes between clusters 3 and 6. The biological significance of each cluster was also determined using the Metascape tool (http: / / metascape.org) using all genes significantly upregulated in each of the 10 initial clusters (one cluster versus all other clusters; the function FindAllMarkers has the following parameters: logfc.threshold = 0.25, test = Wilcox test for Wilcoxon rank-sum test). Consistent with the pairwise analysis, the biological pathways identified on one side for clusters 0 / 5 and on the other side for clusters 3 / 6 were redundant and therefore merged. Therefore, clusters 0 and 5 were defined as cluster 0 / ecm-myCAF, and clusters 3 and 6 were defined as cluster 3 / TGFβ-myCAF, thus ultimately identifying 8 biologically distinct CAF-S1 clusters.

[0304] Gene signatures of CAF-S1, CAF-S1 clusters, and normal fibroblasts:Specific gene signatures for CAF-S1 clusters 0 through 5 were defined by performing differential analysis (Wilcoxon rank-sum test) among clusters 0 through 5. Differentially expressed genes (one cluster relative to all other clusters) between clusters with adjusted p-values ​​<0.05 were selected. Since these signatures were used to detect CAF-S1 clusters in single-cell and whole-cell RNA-seq data from different cancer types, including melanoma, NSCLC, and HNSCC, the inventors excluded genes expressed in tumor cells using scRNA-seq data from tumor cells of melanoma (27), NSCLC (31), and HNSCC (30). The inventors defined a gene as expressed in tumor cells (and thus excluded from the CAF-S1 cluster signature) if more than 10% of the tumor cells in any of the aforementioned scRNA-seq data showed an expression level greater than 1. The global signature of CAF-S1 was first published in Costa A et al., Cancer Cell 2018;33(3):463-79e10 and submitted to the same type of analysis, excluding genes detected in tumor cells to make them suitable for global analysis. The top 100 most prominent genes were considered to be CAF-S1 specific signatures. Compared with CAF-S1 fibroblasts isolated from BC, normal fibroblasts (FAP) isolated from healthy adjacent tumor tissues showed a higher proportion of CAF-S1-specific signatures. 阴性 CD29 中 SMA 阴性 Genes significantly upregulated in tumor cells defined the signature of normal fibroblasts. Following the same strategy described above, genes expressed in tumor cells were excluded from the signature. The cell lysis index was defined as the geometric mean of granzyme A (GZMA) and perforin (PRF1) gene expression, as described by Rooney et al., Cell 2015; 160(1-2):48-61.

[0305] Marker transfer

[0306] To validate the CAF-S1 clusters identified in the first dataset, a second dataset corresponding to 1582 CAF-S1 fibroblasts collected from additional BC samples after quality control was analyzed using the Seurat pipeline. The label transfer algorithm, described in Stuart T et al., Cell 2019;177(7):1888-902e21 and implemented in the Seurat V3.0 R package, was implemented using the functions FindTransferAnchors and TransferData. The first dataset of 18296 CAF-S1 cells was used as the reference, and the second dataset of 1582 CAF-S1 cells was used as the query. Dimensionality reduction was performed by projecting PCA from the reference onto the query when searching for anchors. Thirty dimensions were used.

[0307] Single-cell data integration from BC, HNSCC and NSCLC

[0308] Integration between BC and HNSCC or BC and NSCLC single-cell data was accomplished using the method described in Stuart T et al., Cell 2019;177(7):1888-902 e21 and implemented in the Seurat V3.0 R package. In short, identifying cell-pair correspondences (called “anchors”) between single cells across datasets allows the datasets to be transformed into a shared space. Dimensionality reduction was performed on both datasets using diagonalized canonical correspondence analysis (CCA), and L2 normalization was applied to the canonical correlation vectors prior to anchor identification. The FindIntegrationAnchors and IntegrateData functions in the Seurat V3.0 package used default parameters.

[0309] Flow cytometry analysis of the five most abundant CAF-S1 clusters and immune cells

[0310] Forty-four BCs were cut into small fragments and digested for 45 minutes at 37°C with shaking (180 rpm) in CO2-independent medium (Gibco, #18045-054) supplemented with 5% fetal bovine serum (FBS, PAA, #A11-151), 2 mg / ml collagenase I (Sigma-Aldrich, #C0130), 2 mg / ml hyaluronidase (Sigma-Aldrich, #H3506), and 25 mg / ml DNase I (Roche, #11284932001) with shaking (Gibco, #18045-054). After tissue digestion, cells were filtered through a cytometer (40 mm, Fischer Scientific, #223635447) and washed with PBS solution (Gibco, #14190) supplemented with 2 mM EDTA (Gibco, #15575) and 1% human serum (BioWest, #S4190-100). The cells were then separated into two groups for analysis, one for the CAF-S1 cluster panel and the other for the immune cell panel.

[0311] CAF-S1 cluster panel:Cells were stained in PBS with Live Dead NIR (1:1000, BD Bioscience#565388) for 20 minutes. Cells were then washed and stained with an antibody cocktail for 45 minutes. The antibody cocktail contained anti-CD235a-APC-Cy7 (1:20, BioLegend, #349115), anti-EpCAM-BV605 (1:25, Biolegend, #324224), anti-CD31-PECy7 (1:50, BioLegend, #303118), anti-CD45-BUV395 (1:25, BD Biosciences, #BD-563792), and anti-CD29-Alexa Fluor 700 (1:50, BioLegend, #303020), conjugated with the fluorescent dye Zenon APC Mouse IgG1 Labeling Kit (Thermo Fisher Scientific, #Z-25051) to anti-FAP (1:100, R&DSystems, #MAB3715) and anti-ANTXR1-AF405 (1:33, Novus). Biological, #NB-100-56585), anti-LAMP5-PE (1:10, Miltenyi Biotech, #130-109-156), anti-SDC1-BUV737 (1:25, BD Biosciences, #BD-564393), anti-GPC3-AF594 (1:20, RnD, #FAB2119T, 100UG), anti-DLK1-AF488 (1:25, RnD, #FAB1144G-100) and anti-CD9-BV711 (1:200, BD Biosciences, #BD-743050). The isotype control antibodies used for each CAF cluster marker were: mouse IgG1 isotype control - BV711 (1:200, BD Bioscience, #563044), mouse IgG1 isotype control - AF405 (1:3, Novus Biological, #IC002V), mouse IgG1 isotype control - BUV737 (1:25, BD Bioscience, #564299), mouse IgG2B isotype control - AF488 (1:12.5, RnD, #IC0041G), mouse IgG2A isotype control - AF594 (1:5, RnD, #IC003T), and REA control - PE (1:10, Miltenyi Biotech, #130-113-462).Cells were then washed and acquired on the same day using an LSR FORTESSA analyzer (BD Bioscience), or fixed in 4% paraformaldehyde (PFA, Electron Microscopy Sciences, #15710) for 20 minutes, washed, and stored overnight in PBS+ solution for acquisition the following day. Records were taken at least 5 × 10⁻⁶ cells. 5 One event. Single staining was used to compensate for anti-mouse IgG and negative control beads (BD bioscience #552843) for each antibody and for cells used for Live / Dead staining. Data analysis was performed using FlowJo version 10.4.2 (LLC, USA). Cells were first gated based on forward (FSC-A) and side-scroll (SSC-A) scatterers (measuring cell size and granularity, respectively) to exclude debris. Dead cells and erythrocytes were excluded based on positive staining for Live / Dead NIR and CD235a, respectively. Single cells were then selected based on SSC-H versus SSC-A parameters. Cells were then targeted to EPCAM. - CD45 - CD31 - Cells perform gating to exclude epithelial cells (EPCAM). + ), hematopoietic cells (CD45) + ) and endothelial cells (CD31) + According to FAP and CD29, DAPI - EPCAM - CD45 - CD31 - Cells were isolated into four subsets (CAF-S1 to CAF-S4). The CAF-S1 subset was first gated according to ANTXR1. + The cells are then gated according to SDC1 and LAMP5. ANTXR1 + SDC1 + LAMP5 - Defined as cluster 0 / ecm-myCAF, ANTXR1 + SDC1 - LAMP5 + For cluster 3 / TGFβ-myCAF. ANTXR1 + SDC1 - LAMP5 - Gating is performed based on CD9, and ANTXR1 is... + SDC1 - LAMP5 - CD9 + Defined as cluster 4 / trauma-myCAF. ANTXR1 - / 低Cells are gated based on DLK1 and GPC3. Cluster 1 / detoxification-iCAF is defined as ANTXR1. - GPC3 + DLK1 - / + Cluster 2 is ANTXR1 - GPC3 - DLK1 + ANTXR1 - GPC3 - DLK1 - and ANTXR1 + SDC1 - LAMP5 - CD9 - Specify other clusters.

[0312] Immune panel: CAF-S1 clusters were analyzed in 44 BC samples, of which 37 also characterized immune contents. Cell type analysis was performed on the live dead negative fraction, defined as hematopoietic cells (CD45). + CD4 + / CD8 + T lymphocytes; B lymphocytes (CD45) + CD14 - CD3 - CD19 + ); NK(CD45) + CD14 - CD3 - CD56 + ), cytotoxic NK (CD56) + CD16 + ) and non-cytotoxic NK (CD56) + CD16 - (CD45) + CD14 - CD3 + CD4 + / CD8 + ) and bone marrow cells (CD45) + CD14 +For each identified population, the percentage of positive cells at the following checkpoints was also assessed: PD-1, CTLA-4, NKG2A, TIGIT, CD244, CD158K, CD69, and CD161. Cells were stained with Live Dead (1:1000, Thermo Fisher Scientific, #L34955) in PBS for 20 minutes. The cells were then washed and stained with an antibody cocktail for 45 minutes. The antibody cocktail contained anti-CD45-APC-cy7 (1:20, BD Biosciences, #BD-557833), anti-CD14-BV510 (1:50, BD Biosciences, #563079), anti-CD56-BUV395 (1:25, BD Biosciences, #563554), anti-CD16-BV650 (1:25, BD Biosciences, #563692), anti-PD-1-BUV 737 (1:20, BD Biosciences, #565299), anti-CD3-AF700 (1:25, BD Biosciences, #557943), anti-NKG2A-BV786 (1:20, BD Biosciences, #747917), and anti-TIGIT-BV605 (1:20, BD Biosciences, #BD-557833). Bioscience, #747841), Anti-CD158K-PE (1:10, Miltenyi Biotech, #130-095-205), Anti-CD244-FITC (1:10, BD Bioscience, #550815), Anti-CTLA-4-Pe-cy5 (1:10, BD Bioscience, #555854), Anti-CD19-Percp-cy5.5 (1:20, BD Bioscience, #561295), Anti-CD4 APC (1:25, Miltenyi Biotec, #130-092-374), Anti-CD8-PE-TexasRred (1:100, Life Technologies, #MHCD0817), Anti-CD69-BV710 (1:25, BD Bioscience, #747841), Anti-CD158K-PE (1:10, Miltenyi Biotech, #130-095-205), Anti-CD244-FITC (1:10, BD Bioscience, #550815), Anti-CTLA-4-Pe-cy5 (1:10, BD Bioscience, #555854), Anti-CD19-Percp-cy5.5 (1:20, BD Bioscience, #561295), Anti-CD4 APC (1:25, Miltenyi Biotech, #130-092-374), Anti-CD8-PE-TexasRred (1:100, Life Technologies, #MHCD0817), Anti-CD69-BV710 (1:25, BD Bioscience, #747841), Anti-CD158K-PE (1:10, Miltenyi Biotech, #130-095-205), Anti-CD244-FITC (1:10, BD Bioscience, #550815), Anti-CD69-BV Bioscience, #563836), anti-CD161-PE-VIO770 (1:100, Miltenyi, #130-113-597). Cells were then washed and acquired on the same day using an LSR FORTESSA analyzer (BD Bioscience), or fixed in 4% paraformaldehyde (PFA, Electron Microscopy Sciences, #15710) for 20 min, then washed and stored overnight in PBS+ solution and acquired the next day. Record at least 5 × 10⁶ cells.5 One event. Single staining was used to compensate for anti-mouse IgG and negative control beads (BD bioscience, #552843) for each antibody and cells for Live / Dead staining. Data analysis was performed using FlowJo version 10.4.2 (LLC, USA).

[0313] RNA sequencing of the CAF-S1 primary cell line isolated from BC

[0314] RNA was extracted from CAF-S1 fibroblasts using the Qiagen miRNeasy kit (QIGEN, #217004) according to the manufacturer's instructions. Of the seven primary CAF-S1 cell lines studied, three were isolated by sorting and four by dissemination. These seven primary CAF-S1 cell lines were derived from seven different BC patients. RNA integrity and quality were analyzed using the Agilent RNA6000 Pico kit (Agilent Technologies, #5067-1513). cDNA libraries were prepared using the TruSeq Stranded mRNA kit (Illumina, #20020594) and then sequenced on NovaSeq (Illumina). Readings were plotted on the human reference genome (hg38; Gencode Release 26) and quantified using STAR (version 2.5.3a) with the following parameters: "outFilterMultimapNmax = 20; alignSJoverhangMin = 8; alignSJDBoverhangMin = 1; outFilterMismatchNmax = 999; outFilterMismatchNoverLmax = 0.04; alignIntronMin = 20; alignIntronMax = 1000000; alignMatesGapMax = 1000000; outMultimapperOrder = Random". Only genes with at least one reading in at least 5% of all samples were retained for further analysis. Normalization was performed using the DESeq2 R package, and the raw reading matrix was transformed using log2. To identify the primary CAF-S1 cell lines, the score of each CAF-S1 cluster signature was calculated by the average expression of genes constituting the iCAF / myCAF signature (as defined in Ohlund et al., J Exp Med 2017; 214(3):579-96). P-values ​​were obtained from DESeq2 analysis.

[0315] Functional testing

[0316] CD4 + CD25 + Isolation of T lymphocytes: Through an agreement with the Curie Institute (Paris, France), the Paris "National Blood Service" ( CD4+ isolated from peripheral blood of healthy donors obtained from the Saint-Antoine blood bank (du Sang) + CD25 + T lymphocytes. In short, peripheral blood mononuclear cells (PBMCs) were isolated using Lymphoprep (Stemcell, #07861), as previously described in Costa A et al., Cancer Cell 2018;33(3):463-79e10. They were isolated using magnetic cell separation (MACS) with CD4+. + CD25 + Treg isolation kit (Miltenyi Biotec, #130-091-301) from 5 × 10 according to the manufacturer's instructions. 8 PBMC purified CD4 + CD25 + CD4 was determined by flow cytometry. + CD25 + The purity of T lymphocytes, as described in Costa A et al., Cancer Cell 2018;33(3):463-79e10.

[0317] Isolation of CAF-S1 clusters from cultures: To isolate different CAF-S1 clusters, the inventors first began sorting cells based on cell-specific markers, but they failed to make the cells survive with different identities. They then tested two different isolation methods: dissemination and sorting. For the “dissemination” method, tumors were cut into small pieces and incubated in plastic culture dishes (Falcon, #353003) in DMEM (HyClone, #SH30243.01) supplemented with 10% FBS (Biosera, #FB-1003 / 500), streptomycin (100 μg / ml), and penicillin (100 U / ml) (Gibco #15140-122) in a humidified 1.5% O2 and 5% CO2 incubator to allow fibroblasts to disseminate and expand at 37°C for at least 2–3 weeks. To isolate fibroblasts using the “sorting” method, tumors were... #Separate CAF-S1 from BC) The enzyme cocktail described in the text is digested and used in ( #Single-cell CAF-S1 RNA sequencing The gating strategy described in [the document] was tested in 48-well plastic culture dishes (TPP plates, #192048) pre-coated with FBS using BDFACS ARIA III [method / technology]. TMSorting was performed for 2 hours. CAF-S1 sorted cells were then incubated in a humidified 1.5% O2 and 5% CO2 incubator in pericyte culture medium (ScienCell, #1201) supplemented with 2% FBS (ScienCell, #0010) in plastic culture dishes (TPP plates, #192048). To compare the cell identity of sorted and disseminated CAF-S1 fibroblasts under identical conditions for functional assays, both types of fibroblasts (disseminated and sorted) were transferred in DMEM (HyClone, #SH30243.01) to plastic culture dishes (Falcon, #353047) at 20% O2, as these culture conditions are similar to those used for in vitro functional assays of CD4+. + CD25 + T-lymphocyte co-culture compatibility was achieved. Using these protocols, seven distinct CAF-S1 cell lines were isolated from seven different patients, three by sorting and four by dispersal. To avoid any in vitro activation, these primary CAF-S1 cell lines isolated by sorting and dispersal were used no later than passage 5. Furthermore, in each experiment, the properties of dispersed and sorted cells from the same passages were compared.

[0318] Treg-CAF-S1 cluster function determination: 5×10 4 CAF-S1 cells (dispersed and sorted) were seeded overnight in DMEM (HyClone, #SH30243.01) with 10% FBS (Biosera, #FB-1003 / 500) under 1.5% O2 in 24-well plates (Falcon, #353047) to ensure complete adhesion. Then, 5 × 10⁶ cells were added to 500 μl of DMEM with 1% FBS (ratio 1–10). 5 CD4 + CD25 + T lymphocytes were incubated overnight at 37°C and 20% O2 (for RNA analysis) or for 24 hours (for FACS). For FACS analysis, non-adherent cells (CD4+) were harvested. + CD25 +Wash, and stain at room temperature for 30 minutes with the following markers: Live Dead (1:1000, BD Bioscience, #562247), anti-CD45-BUV395 (1:50, BD Biosciences, #BD-563792), anti-CD4-APC (1:50, Miltenyi Biotec, #130-092-374), anti-CD25PE-cy7 (1:33, BD Bioscience, #557741), anti-FOXP3-FITC (1:33, ebioscience, #53-4776-42), anti-CTLA-4-Pe-cy5 (1:20, BD Bioscience, #555854), anti-PD-1-BUV737 (BD Bioscience, #565299), anti-TIGIT-BV605 (1:50, BD Bioscience, #BD Bioscience, #562247), anti-CD45-BUV39 ... Bioscience, #747841), anti-LAG3-BV510 (1:50, BD Bioscience, #744985), anti-TIM3-BV711 (1:50, BD Bioscience, #565566). Adherent cells were trypsinized, washed, and stained for CAF-S1 cluster markers (ANTXR1, CD9, SDC1, LAMP5, GPC3, DLK1). LiveDead NIR staining was used to remove dead cells, and CD45 staining was used to remove residual Tregs. Cells (Treg panel and CAF-S1 panel) were obtained using a ZE5 cell analyzer (Bio-Rad) and analyzed using Flowjo version 10.4.2. For RNA analysis, non-adherent cells (CD45) were harvested by pipetting. + CD25 +The RNA was then rotated and settled. RNA was then extracted using a single-cell RNA purification kit (Norgen Biotek Corp., #51800) according to the manufacturer's recommendations. RNA integrity and quality were analyzed using the Agilent RNA6000 Pico kit (Agilent Technologies, #5067-1513). cDNA libraries were prepared using the TruSeq RNA Exome kit (Illumina, #20020189) and subsequently sequenced on NovaSeq (Illumina). Readings were plotted on the human reference genome (hg38; Gencode Release 29) and quantified using STAR (version 2.6.1a) with the following parameters: "outFilterMultimapNmax = 20; alignSJoverhangMin = 8; alignSJDBoverhangMin = 1; outFilterMismatchNmax = 999; outFilterMismatchNoverLmax = 0.04; alignIntronMin = 20; alignIntronMax = 1000000; alignMatesGapMax = 1000000; outMultimapperOrder = Random". Only genes with at least one reading in at least 5% of all samples were retained for further analysis. Normalization was performed using the DESeq2 R package.

[0319] Intracellular staining of Treg-CAF-S1 clusters: 5×10 4 CAF-S1 cells (dispersed) were seeded overnight in 24-well plates (Falcon, #353047) with 10% FBS (Biosera, #FB-1003 / 500) in DMEM (HyClone, #SH30243.01) at 1.5% O2 to ensure complete adhesion. The culture medium was then removed, and 5 × 10⁶ cells were added to 500 μl of DMEM with 1% FBS (ratio 1-10). 5 CD4 + CD25 + T lymphocytes were incubated overnight at 37°C and 20% O2. Then, non-adherent cells (CD4+) were harvested. + CD25 +After washing, the cells were stained with Live Dead (1:1000, BD Bioscience, #562247) for 30 minutes at room temperature. After washing, the cells were divided into two groups (one group was fixed and permeabilized, and the second group was not fixed / permeabilized and stained with FOXP3 only) and stained with the following markers: anti-CD45-BUV395 (1:50, BD Biosciences, #BD-563792), anti-CD4-APC (1:50, Miltenyi Biotec, #130-092-374), anti-CD25 PE-cy7 (1:33, BD Bioscience, #557741), anti-CTLA-4-Pe-cy5 (1:20, BD Bioscience, #555854), anti-PD-1-BUV737 (BD Bioscience, #565299), and anti-TIGIT-BV605 (1:50, BD Bioscience, #562247). Bioscience, #747841), anti-LAG3-BV510 (1:50, BDBioscience, #744985), anti-TIM3-BV711 (1:50, BD Bioscience, #565566), anti-FOXP3-FITC (1:33, ebioscience, #53-4776-42).

[0320] Comparison of fibroblasts from normal healthy tissue with CAF-S1 from BC

[0321] Primary fibroblasts were collected from adjacent tissue, i.e., tissue defined as healthy by a pathologist, using a dispersive method (see above). Adjacent tissue was cut into small pieces and placed in plastic culture dishes (Falcon, #353003) and cultured at 37°C for 2–3 weeks in DMEM (HyClone, #SH30243.01) supplemented with 10% FBS (Biosera, #FB-1003 / 500), streptomycin (100 μg / ml), and penicillin (100 U / ml) (Gibco #15140122) at early and late passages. Dispersed fibroblasts were then analyzed at early and late passages (passage 2 and passage 5, respectively) to validate CAF-S1 marker expression. Primary cells were trypsinized, resuspended in PBS, and subjected to LIVE / DEAD diluted in PBS at room temperature. TMCells were stained with Fixable Aqua dead cell staining dye (ThermoFisher Scientific, #L34957) for 20 min and fixed in 4% PFA at room temperature for 20 min. After rapid washing in PBS+, cells were stained with anti-FAP antibody (1:100, R&D Systems, #MAB3715) or isotype control (1:100, R&D Systems, #MAB002) in PBS+ at room temperature for 40 min. Both antibodies and the isotype control were conjugated using the Zenon APC mouse IgG1 labeling kit (ThermoFisher Scientific, #Z-25051). Cells were acquired using an LSR FORTESSA analyzer (BD Bioscience). 50,000 events were recorded per sample.

[0322] RNA sequencing of NSCLC samples

[0323] Formalin-fixed paraffin-embedded (FFPE) biopsy tissues (N=120) from immature NSCLC tissues of any treatment were processed according to the manufacturer's instructions using the High FFPET RNA Isolation Kit (Roche, #06650775001). RNA integrity and quality were analyzed using the Agilent RNA6000 Pico Kit (Agilent Technologies, #5067-1513). Samples with a DV200 greater than 40% were selected for RNA sequencing (N=70). cDNA libraries were prepared using the Nextera XT Sample Preparation Kit (Illumina, #FC-131-10) and subsequently sequenced on NovaSeq (Illumina). Readings were plotted on the human reference genome (release hg19 / GRCh37) and quantified using STAR (version 2.5.3a) with the following parameters: "outFilterMultimapNmax = 20; alignSJoverhangMin = 8; alignSJDBoverhangMin = 1; outFilterMismatchNmax = 999; outFilterMismatchNoverLmax = 0.04; alignIntronMin = 20; alignIntronMax = 1000000; alignMatesGapMax = 1000000; outMultimapperOrder = Random". Only genes with at least one reading in at least 5% of all samples were retained for further analysis. Normalization, unsupervised analysis (PCA), and differential analysis between responding and non-responding patients were performed using the DESeq2 R package.

[0324] Statistical analysis

[0325] All statistical analyses and graphical representations of the data were performed in the R environment (https: / / cran.r-project.org, version 3.5.3) or using GraphPad Prism software (version 8.1.1). The statistical tests used were consistent with the data distribution: the Shapiro-Wilk test was first used to check for normality, and parametric or nonparametric two-tailed tests were performed based on normality, as shown in each figure. Figure 1 , 2 3, Figure 7 and Figure 8 The scRNA-seq data presented were analyzed using the Seurat R package (version 3.0). Figure 2The correlation matrices shown in Figure 4 were calculated using the `cor` function from the `stats` R package with `method="pearson"` and `use="pairwise.complete.obs"`. The `Corrplot` R function is used for clustering and visualization of the correlation matrices with the following parameters: `order="hclust"` and `hclust.method="ward.D2"`. The quantitative results of the FACS analysis shown in Figure 5 are displayed using mean ± sem. Figure 10 shows CD4 clusters, either individually or in the presence of ecm-myCAF. + CD25 + Differential analysis among T cells was performed using the DESeq2 R package. Figure 6 uses Gene Set Enrichment Analysis (GSEA) software version 3.0 (Broad Institute). For melanoma RNA-seq data, the following parameters were applied: Enrichment statistic = 'weighted', Metric for ranking genes = 'Signal2Noise'. For NSCLC RNA-seq data, GSEAPreranked and log2-fold change according to DESeq2 differential analysis were used as measures of gene ranking, and enrichment scoring was performed using the 'classic' mode.

[0326] Table 1. Description of BC prospective cohorts

[0327]

[0328]

[0329] NSCLC samples were obtained from routine diagnostic samples stored in the pathology department of Bichat Hospital from patients receiving immuno-oncology drug therapy. All patients received the first cycle of second- or third-line immunotherapy between July 28, 2015, and February 20, 2018, according to the drug registration and the clinical trials to be conducted at the time. Efficacy of immuno-oncology therapy was assessed every 8–12 weeks via whole-body CT scans according to RECIST v.1.1 criteria. All clinical data were retrieved from patient electronic files. Histological subtypes of non-small cell lung cancer samples were determined on formalin-fixed paraffin-embedded tissue sections stained with hematoxylin, derived from bronchoscopic or CT-guided transthoracic biopsy samples, according to the current World Health Organization classification of 2015. The diagnosis of squamous cell carcinoma was supported by positive P40 and negative TTF-1 (thyroid transcription factor 1) immunostaining. Non-squamous squamous cell lung cancer included adenocarcinoma showing positive Alcian blue staining (for myxoma cell content) and / or positive nuclear TTF-1 immunostaining, and large cell carcinoma without mucin secretion that was negative for p40 and TTF-1 immunostaining. Both samples showed mixed features of squamous cell carcinoma and adenocarcinoma differentiation. Both stage IIIB patients had unresectable lung tumors and contraindications to radiotherapy according to the 8th edition TNM staging system. *PD-L1 staining and interpretation were performed on 4 μm paraffin-embedded sections by AG using commercially available Cell Signaling Technology E1L3N clones on the Leica Bond platform, the sections being from diagnostic, pre-treatment biopsy samples containing at least 200 tumor cells. **According to Oken et al., Am J Clin Oncol 1982;5(6):649-55, EOCG (Eastern Cooperative Oncology Group) performance was evaluated at the first immunotherapy cycle.

[0330] Table 2. Description of a retrospective cohort of NSCLC patients treated with immunotherapy (Group 4)

[0331]

[0332]

Claims

1. Use of a means capable of detecting anthrax toxin receptor 1 (ANTXR1) and fibroblast activation protein (FAP) positive fibroblasts in the manufacture of a kit for detecting immunosuppressive fibroblasts in a cancer sample from a subject suffering from cancer, wherein ANTXR1 + FAP + The presence of fibroblasts is indicative of immunosuppressive cancer associated fibroblasts (CAFs).

2. Capable of detecting ANTXR1 + FAP + The use of fibroblast-based tools in the preparation of kits for predicting the response of cancer subjects to immunotherapy, wherein ANTXR1 in cancer samples + FAP + Fibroblasts predict a patient's responsiveness to immunotherapy agents.

3. The use according to claim 2, wherein the ANTXR1 + FAP + Fibroblasts are FAP + ANTXR1 + CAF.

4. The use according to claim 1 or 2, wherein the ANTXR1 + FAP + Fibroblasts were selected from: FAP + ANTXR1 + LAMP5 - SDC1 + Fibroblasts; FAP + ANTXR1 + LAMP5 + SDC1 + / - Fibroblasts; and FAP + ANTXR1 + SDC1 - LAMP5 - CD9 + Fibroblasts.

5. The use according to claim 1 or 2, wherein the ANTXR1 + FAP + Fibroblasts were selected from: FAP + ANTXR1 + LAMP5 - SDC1 + CAF; FAP + ANTXR1 + LAMP5 + SDC1 + / - CAF; and FAP + ANTXR1 + SDC1 - LAMP5 - CD9 + CAF.

6. The use according to claim 1 or 2, wherein the cancer is selected from prostate cancer, lung cancer, breast cancer, gastric cancer, kidney cancer, ovarian cancer, osteosarcoma, melanoma, hypopharyngeal cancer, esophageal cancer, endometrial cancer, cervical cancer, pancreatic cancer, liver cancer, colon cancer, sarcoma, non-squamous cell carcinoma, squamous cell carcinoma, neuroendocrine tumor, muscle cancer, adrenal cancer, thyroid cancer, uterine cancer, skin cancer, bladder cancer, and head and neck cancer.

7. The use according to claim 1 or 2, wherein the cancer is selected from non-small cell lung cancer (NSCLC), hepatocellular carcinoma, colorectal cancer, adenocarcinoma, and metastatic melanoma.

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