Methods for collecting data to predict the effectiveness of administering immune checkpoint inhibitors to cancer patients.

Abstract

To provide a novel technique of predicting administration effectiveness of an immune checkpoint inhibitor.SOLUTION: A method for collecting data for predicting administration effectiveness of an immune checkpoint inhibitor to a cancer patient, which includes a process of measuring an expression level of a marker gene or a marker protein in a biological sample derived from the cancer patient. In the method, the marker gene or marker protein includes NELL2 gene or protein, AMICA1 gene or protein, CLEC11A gene or protein, CLECL1 gene or protein or CMTM7 gene or protein, the expression level is data for predicting the effectiveness, and the fact that the expression level is higher than a reference value indicates that administration of the immune checkpoint inhibitor to the cancer patient is effective.SELECTED DRAWING: None

Description

Technical Field

[0001] The present invention relates to a method for collecting data for predicting the effectiveness of administering an immune checkpoint inhibitor to cancer patients. More specifically, the present invention relates to a method for collecting data for predicting the effectiveness of administering an immune checkpoint inhibitor to cancer patients, a kit for predicting the effectiveness of administering an immune checkpoint inhibitor to cancer patients, a method for screening an anticancer agent, and an anticancer agent.

Background Art

[0002] In recent years, it has been shown that treatment methods using immune checkpoint inhibitors typified by nivolumab (anti-PD-1 antibody) can cure advanced solid cancers. However, the response rate of treatment using immune checkpoint inhibitors remains at about 5 to 30%. Therefore, a technique for accurately predicting the effectiveness of immune checkpoint inhibitors before administration is required.

[0003] For example, Patent Document 1 describes using an anti-PD-L1 antibody to predict the effectiveness of a therapeutic agent targeting the PD-L1:PD-1 pathway.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] An object of the present invention is to provide a new technique for predicting the effectiveness of administering an immune checkpoint inhibitor.

Means for Solving the Problems

[0006] The present invention includes the following aspects. [1] A method for collecting data to predict the effectiveness of administering an immune checkpoint inhibitor to a cancer patient, comprising the step of measuring the expression level of a marker gene or marker protein in a biological sample derived from the cancer patient, wherein the marker gene or marker protein includes the NELL2 gene or protein, the AMICA1 gene or protein, the CLEC11A gene or protein, the CLECL1 gene or protein, or the CMTM7 gene or protein, the expression level is data for predicting the effectiveness, and a higher expression level than a reference value indicates that the administration of the immune checkpoint inhibitor to the cancer patient is effective. [2] The method according to [1], wherein the marker gene or marker protein is (i) a combination of the NELL2 gene or protein and the SLAMF6 gene or protein, the CD44 gene or protein or the IL7R gene or protein, or (ii) a combination of the AMICA1 gene or protein and the SELL gene or protein, the IL7R gene or protein or the CCR7 gene or protein. [3] The method according to [1] or [2], wherein the biological sample is CD8-positive T cells, cancer tissue section, plasma, or serum. [4] The method according to any one of [1] to [3], wherein the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody. [5] A kit for predicting the efficacy of immune checkpoint inhibitor administration to cancer patients, comprising a specific binding agent for NELL2 protein, AMICA1 protein, CLEC11A protein, CLECL1 protein, or CMTM7 protein; a primer for amplifying the cDNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene; or a probe for hybridizing to the mRNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene. [6] The kit according to [5] further comprising a specific binding agent for the CD8 protein, a primer for amplifying the cDNA of the CD8 gene, or a probe for hybridizing to the mRNA of the CD8 gene. [7] A method for screening anticancer drugs, comprising the steps of: incubating CD8-positive T cells in the presence of a test substance; and measuring the expression level of a marker gene or marker protein in the CD8-positive T cells, wherein the marker gene or marker protein includes the NELL2 gene or protein, the AMICA1 gene or protein, the CLEC11A gene or protein, the CLECL1 gene or protein, or the CMTM7 gene or protein, and the increase in the expression level compared to the expression level in the absence of the test substance indicates that the test substance is an anticancer drug. [8] An anticancer agent containing as an active ingredient NELL2 protein or its expression vector, AMICA1 protein or its expression vector, CLEC11A protein or its expression vector, CLECL1 protein or its expression vector, or CMTM7 protein or its expression vector. [Effects of the Invention]

[0007] According to the present invention, a novel technique can be provided for predicting the effectiveness of administering immune checkpoint inhibitors. [Brief explanation of the drawing]

[0008] [Figure 1] This is a diagram showing the experimental schedule for Experiment Example 1. [Figure 2](a) is a graph showing the results of analyzing the expression levels of the NELL2 gene in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 2. (b) is a graph showing the results of analyzing the proportion of cells with high NELL2 gene expression and high SLAMF6 gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 2. (c) is a graph showing the results of analyzing the proportion of cells with high NELL2 gene expression and high CD44 gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 2. (d) is a graph showing the results of analyzing the proportion of cells with high NELL2 gene expression and high IL7R gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 2. [Figure 3] This graph shows the results of the prognosis analysis of melanoma patients in Experimental Example 2. [Figure 4] This graph shows the results of quantifying the amount of IFN-γ produced by cancer antigen-specific cytotoxic T cells in Experimental Example 2. [Figure 5] (a) is a graph showing the results of analyzing the expression levels of the AMICA1 gene in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 3. (b) is a graph showing the results of analyzing the percentage of cells with high AMICA1 gene expression and high SELL gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 3. (c) is a graph showing the results of analyzing the percentage of cells with high AMICA1 gene expression and high IL7R gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 3. (d) is a graph showing the results of analyzing the percentage of cells with high AMICA1 gene expression and high CCR7 gene expression in CD8-positive T cells of patients who responded well to nivolumab administration and those who did not in Experimental Example 3. [Figure 6] (a) and (b) are graphs showing the results of the prognosis analysis of melanoma patients in Experimental Example 3. [Figure 7] This graph shows the results of quantifying the amount of IFN-γ produced by cancer antigen-specific cytotoxic T cells in Experiment Example 3. [Figure 8] This graph shows the results of analyzing the expression levels of the CLEC11A gene in CD8-positive T cells from patients who responded well to nivolumab administration and those who did not, in Experimental Example 4. [Figure 9] This graph shows the results of the prognosis analysis of melanoma patients in Experimental Example 4. [Figure 10] (a) to (d) are graphs showing the results of flow cytometry analysis in Experimental Example 4. [Figure 11] This graph shows the results of analyzing the expression levels of the CLEC1L1 gene in CD8-positive T cells from patients who responded well to nivolumab administration and those who did not, in Experimental Example 5. [Figure 12] This graph shows the results of analyzing the expression levels of the CMTM7 gene in CD8-positive T cells from patients who responded well to nivolumab administration and those who did not, in Experimental Example 6. [Figure 13] This graph shows the results of the prognosis analysis of melanoma patients in Experimental Example 6. [Modes for carrying out the invention]

[0009] [Methods for collecting data] In one embodiment, the present invention provides a method for collecting data for predicting the efficacy of administering an immune checkpoint inhibitor to a cancer patient, the method including a step of measuring the expression level of a marker gene or a marker protein in a biological sample derived from the cancer patient, wherein the marker gene or the marker protein includes the NELL2 gene or protein, the AMICA1 gene or protein, the CLEC11A gene or protein, the CLECL1 gene or protein, or the CMTM7 gene or protein, the expression level being data for predicting the efficacy, and a higher expression level than a reference value indicating that the administration of the immune checkpoint inhibitor to the cancer patient is effective.

[0010] As will be described later in the examples, the inventors have clarified that the NELL2 gene or NELL2 protein, the AMICA1 gene or AMICA1 protein, the CLEC11A gene or CLEC11A protein, the CLECL1 gene or CLECL1 protein, or the CMTM7 gene or CMTM7 protein can be used as a marker gene or a marker protein for predicting the efficacy of administering an immune checkpoint inhibitor to a cancer patient.

[0011] When the expression level of these genes or proteins in a biological sample derived from a cancer patient is higher than a reference value, it can be determined that the administration of an immune checkpoint inhibitor to the cancer patient is effective.

[0012] Therefore, the method of the present embodiment can be said to be a method for predicting the efficacy of administering an immune checkpoint inhibitor to a cancer patient. Alternatively, the method of the present embodiment can also be said to be a method for diagnosing whether the administration of an immune checkpoint inhibitor to a cancer patient is effective.

[0013] Here, the reference value may be, for example, the expression level of the above-mentioned gene or protein in a biological sample derived from a cancer patient for whom administration of immune checkpoint inhibitors has already been shown to be ineffective. Alternatively, the reference value may be a predetermined value.

[0014] Examples of biological samples include CD8-positive T cells, cancer tissue sections, plasma, and serum. Among these, CD8-positive T cells are preferred as the biological sample.

[0015] The method for measuring the expression level of marker genes is not particularly limited and includes, for example, RNA-Seq, quantitative RT-PCR, and DNA microarray methods. Similarly, the method for measuring the expression level of marker proteins is not particularly limited and includes, for example, flow cytometry, ELISA, and protein array methods.

[0016] In the method of this embodiment, examples of immune checkpoint inhibitors include anti-PD-1 antibodies or anti-PD-L1 antibodies. More specifically, examples of anti-PD-1 antibodies include nivolumab and pembrolizumab. More specifically, examples of anti-PD-L1 antibodies include avelumab and atezolizumab.

[0017] The NCBI accession numbers for the mRNA of the human NELL2 gene are NM_001145107.1, NM_001145108.1, NM_001145109.1, etc. The NCBI accession numbers for the human NELL2 protein are NP_001138580.1, NP_001138579.1, NP_006150.1, etc.

[0018] The NCBI accession numbers for the mRNA of the human AMICA1 gene are NM_001098526.1, NM_001286570.1, NM_001286571.1, NM_153206.2, etc. The NCBI accession numbers for the human AMICA1 protein are NP_001273500.1, NP_001273499.1, NP_001091996.1, NP_694938.2, etc.

[0019] The NCBI accession number for the mRNA of the human CLEC11A gene is NM_002975.3, etc. The NCBI accession number for the human CLEC11A protein is NP_002966.1, etc.

[0020] The NCBI accession numbers for the mRNA of the human CLECL1 gene are NM_001253750.1, NM_001267701.1, NM_172004.3, etc. The NCBI accession numbers for the human CLEC11A protein are NP_001240679.1, NP_742001.1, NP_001254630.1, etc.

[0021] The NCBI accession numbers for the mRNA of the human CMTM7 gene are NM_138410.4, NM_181472.3, etc. The NCBI accession numbers for the human CMTM7 protein are NP_852137.1, NP_612419.1, etc.

[0022] The above marker gene or marker protein may be (i-1) a combination of the NELL2 gene or protein and the SLAMF6 gene or protein, (i-2) a combination of the NELL2 gene or protein and the CD44 gene or protein, or (i-3) a combination of the NELL2 gene or protein and the IL7R gene or protein.

[0023] As described later in the examples, measuring combinations of NELL2 gene or protein expression levels, compared to measuring the expression levels of the NELL2 gene or protein alone, allows for a more accurate prediction of whether or not administering immune checkpoint inhibitors to cancer patients is effective.

[0024] The NCBI accession numbers for the mRNA of the human SLAMF6 gene are NM_001184714.1, NM_001184715.1, NM_001184716.1, NM_052931.4, etc. The NCBI accession numbers for the human SLAMF6 protein are NP_001171644.1, NP_443163.1, NP_001171645.1, etc.

[0025] The NCBI accession numbers for the human CD44 gene mRNA are NM_000610.4, NM_001001389.2, NM_001001390.2, etc. The NCBI accession numbers for the human CD44 protein are NP_001001391.1, NP_001001390.1, NP_001189485.1, etc.

[0026] The NCBI accession number for the human IL7R gene mRNA is NM_002185.3, etc. The NCBI accession number for the human IL7R protein is NP_002176.2, etc.

[0027] Alternatively, the above-mentioned marker gene or marker protein may be (ii-1) a combination of the AMICA1 gene or protein and the SELL gene or protein, (ii-2) a combination of the AMICA1 gene or protein and the IL7R gene or protein, or (ii-3) a combination of the AMICA1 gene or protein and the CCR7 gene or protein.

[0028] As described later in the examples, measuring combinations of AMICA1 gene or protein expression levels, compared to measuring the expression levels of the AMICA1 gene or protein alone, allows for a more accurate prediction of whether or not administering immune checkpoint inhibitors to cancer patients is effective.

[0029] The NCBI accession number for the human SELL gene mRNA is NM_000655.4, etc. The NCBI accession number for the human SELL protein is NP_000646.2, etc.

[0030] The NCBI accession numbers for the human IL7R gene or protein are as described above.

[0031] The NCBI accession numbers for the mRNA of the human CCR7 gene are NM_001301714.1, NM_001301716.1, NM_001301717.1, NM_001301718.1, NM_001838.3, etc. The NCBI accession numbers for the human CCR7 protein are NP_001288645.1, NP_001288647.1, NP_001288646.1, NP_001288643.1, NP_001829.1, etc.

[0032] [kit] In one embodiment, the present invention provides a kit for predicting the efficacy of administering immune checkpoint inhibitors to cancer patients, comprising a specific binding agent for NELL2 protein, AMICA1 protein, CLEC11A protein, CLECL1 protein, or CMTM7 protein; a primer for amplifying the cDNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene; or a probe for hybridizing to the mRNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene.

[0033] The kit of this embodiment may contain a specific binding agent for NELL2 protein, AMICA1 protein, CLEC11A protein, CLECL1 protein, or CMTM7 protein. Examples of specific binding agents include antibodies, antibody fragments, aptamers, etc. Examples of antibody fragments include F(ab')2, Fab', Fab, Fv, scFv, etc. The specific binding agent is not particularly limited as long as it can detect NELL2 protein, AMICA1 protein, CLEC11A protein, CLECL1 protein, or CMTM7 protein. The specific binding agent may be bound to a solid phase to constitute, for example, a protein array.

[0034] The kit of this embodiment may include primers for amplifying the cDNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene. Typically, the primers are a set of sense primers and antisense primers. The base sequence and length of the primers are not particularly limited, as long as they can amplify the cDNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene.

[0035] The kit of this embodiment may include a probe that hybridizes to the mRNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene. Typically, the probe is a nucleic acid fragment. The base sequence of the probe is not particularly limited as long as it can detect the mRNA of the NELL2 gene, AMICA1 gene, CLEC11A gene, CLECL1 gene, or CMTM7 gene. The probe may constitute a nucleic acid array.

[0036] The kit of this embodiment may further include a specific binding agent for the CD8 protein, a primer for amplifying the cDNA of the CD8 gene, or a probe for hybridizing to the mRNA of the CD8 gene. This allows for the measurement of the expression level of the marker gene or marker protein in CD8-positive T cells derived from cancer patients.

[0037] The kit of this embodiment may further include a specific binding agent for SLAMF6 protein, CD44 protein, IL7R protein, SELL protein, or CCR7 protein; a primer for amplifying the cDNA of the SLAMF6 gene, CD44 gene, IL7R gene, SELL gene, or CCR7 gene; or a probe for hybridizing to the mRNA of the SLAMF6 gene, CD44 gene, IL7R gene, SELL gene, or CCR7 gene.

[0038] As described above, by measuring the expression levels of the NELL2 gene or protein in combination with the expression levels of the SLAMF6 gene or protein, CD44 gene or protein, or IL7R gene or protein, it is possible to more accurately predict whether or not the administration of immune checkpoint inhibitors to cancer patients will be effective. Furthermore, by measuring the expression levels of the AMICA1 gene or protein in combination with the expression levels of the SELL gene or protein, IL7R gene or protein, or CCR7 gene or protein, it is possible to more accurately predict whether or not the administration of immune checkpoint inhibitors to cancer patients will be effective.

[0039] [Screening methods for anticancer drugs] In one embodiment, the present invention provides a method for screening anticancer drugs, comprising the steps of: incubating CD8-positive T cells in the presence of a test substance; and measuring the expression level of a marker gene or marker protein in the CD8-positive T cells, wherein the marker gene or marker protein includes the NELL2 gene or protein, the AMICA1 gene or protein, the CLEC11A gene or protein, the CLECL1 gene or protein, or the CMTM7 gene or protein, and an increase in the expression level compared to the expression level in the absence of the test substance indicates that the test substance is an anticancer drug.

[0040] In the screening method of this embodiment, the test substance is not particularly limited, and for example, a natural compound library, a synthetic compound library, an existing drug library, etc., can be used. Furthermore, the CD8-positive T cells may be cells derived from healthy individuals, cells derived from cancer patients, or established cell lines.

[0041] In the screening method of this embodiment, the method for measuring the expression level of marker genes is the same as described above, and examples include RNA-Seq, quantitative RT-PCR, and DNA microarray methods. Similarly, the method for measuring the expression level of marker proteins is the same as described above, and examples include flow cytometry, ELISA, and protein array methods.

[0042] Test substances that increase the expression levels of the NELL2 gene or NELL2 protein, AMICA1 gene or AMICA1 protein, CLEC11A gene or CLEC11A protein, CLECL1 gene or CLECL1 protein, or CMTM7 gene or CMTM7 protein in CD8-positive T cells can be considered anticancer agents that can be used as alternatives to conventional immune checkpoint inhibitors. Alternatively, such test substances can be considered drugs that improve the effectiveness of administering conventional immune checkpoint inhibitors to cancer patients.

[0043] In the screening method of this embodiment, the above-mentioned marker gene or marker protein may be (i-1) a combination of the NELL2 gene or protein and the SLAMF6 gene or protein, (i-2) a combination of the NELL2 gene or protein and the CD44 gene or protein, or (i-3) a combination of the NELL2 gene or protein and the IL7R gene or protein.

[0044] Compared to measuring the expression levels of the NELL2 gene or protein alone, measuring combinations of these allows for a more accurate prediction of the anticancer effects of the test substance.

[0045] Alternatively, the above-mentioned marker gene or marker protein may be (ii-1) a combination of the AMICA1 gene or protein and the SELL gene or protein, (ii-2) a combination of the AMICA1 gene or protein and the IL7R gene or protein, or (ii-3) a combination of the AMICA1 gene or protein and the CCR7 gene or protein.

[0046] Compared to measuring the expression levels of the AMICA1 gene or protein alone, measuring combinations of these allows for a more accurate prediction of the anticancer effects of the test substance.

[0047] [Anticancer drugs] In one embodiment, the present invention provides an anticancer agent containing NELL2 protein or its expression vector, AMICA1 protein or its expression vector, CLEC11A protein or its expression vector, CLECL1 protein or its expression vector, or CMTM7 protein or its expression vector as an active ingredient. The AMICA1 protein is preferably solubilized and may be in the form of a fusion protein with an antibody constant region (AMICA1-Fc), or a part of the AMICA1 protein (e.g., an extracellular domain). Plasmid vectors, adenovirus vectors, retrovirus vectors, etc., can be used as expression vectors. The anticancer agent of this embodiment can be used in combination with, for example, chimeric antigen receptor (CAR)-T cell preparations, TCR-T cell preparations, tumor-infiltrating T cell (TIL) therapy, etc.

[0048] As described later in the examples, the inventors have revealed that NELL2 has the function of increasing the production of IFN-γ by cancer antigen-specific cytotoxic T cells. Therefore, the NELL2 protein or an expression vector for the NELL2 protein can be used as an anticancer agent. The expression vector is the same as described above. For example, the NELL2 protein can be expressed and used in chimeric antigen receptor (CAR)-T cell preparations, TCR-T cell preparations, tumor-infiltrating T cells (TILs), etc.

[0049] Furthermore, as will be described later in the examples, the inventors have revealed that the AMICA1 protein (AMICA1-Fc) has the function of increasing the production of IFN-γ by cancer antigen-specific cytotoxic T cells. Therefore, the AMICA1 protein or the AMICA1 protein expression vector can be used as an anticancer agent. When the AMICA1 protein is used as an anticancer agent, it is preferable that the AMICA1 protein is solubilized, and may be in the form of AMICA1-Fc, for example, or as a part of the AMICA1 protein. The expression vector is the same as described above. For example, AMICA1-Fc can be expressed in chimeric antigen receptor (CAR)-T cell preparations, TCR-T cell preparations, tumor-infiltrating T cells (TILs), etc., or these cells can be contacted with the AMICA1-Fc protein and used.

[0050] Furthermore, as will be described later in the examples, the inventors have revealed that the CLEC11A protein is a functional molecule that maintains the undifferentiated state of T cells. Undifferentiated T cells may improve the effectiveness of immune checkpoint inhibitor administration (see, for example, Kurtulus S., et al., Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1-CD8+ Tumor-Infiltrating T Cells, Immunity, 50 (1):181-194, 2019). Therefore, the CLEC11A protein or the CLEC11A protein expression vector can be used as an anticancer agent. The expression vector is the same as described above. For example, the CLEC11A protein can be expressed and used in chimeric antigen receptor (CAR)-T cell preparations, TCR-T cell preparations, tumor-infiltrating T cells (TILs), etc.

[0051] The anticancer agent of this embodiment is preferably formulated as a pharmaceutical composition mixed with a pharmaceutically acceptable carrier. The anticancer agent of this embodiment may also be formulated in the form of, for example, an intravenous infusion, an injection, or a topical skin preparation and administered parenterally. Examples of topical skin preparations include ointments and patches.

[0052] Examples of pharmaceutically acceptable carriers include infusion solvents, injection solvents, and adhesives. Infusion solvents and injection solvents can be those commonly used in infusions and injections, without any particular limitations. Examples include, but are not limited to, physiological saline, glucose, D-sorbitol, D-mannose, D-mannitol, and isotonic solutions containing adjuvants such as sodium chloride. Infusion solvents and injection solvents may also contain alcohols such as ethanol; polyalcohols such as propylene glycol and polyethylene glycol; and nonionic surfactants such as polysorbate 80 (trademark) and HCO-50.

[0053] The adhesive can be any adhesive commonly used in adhesive patches, etc., without any particular limitations. Examples include rubber-based adhesives and silicone-based adhesives, but it is not limited to these.

[0054] Anticancer drugs can be administered to patients by methods such as intravenous infusion, intravenous injection, intradermal administration, subcutaneous administration, or application of transdermal patches. The dosage can be adjusted as appropriate depending on the patient's age, weight, symptoms, and method of administration. For a typical adult (60 kg), a single dose may be, for example, 0.001 mg to 1000 mg, 0.001 mg to 1000 mg, or 0.1 mg to 10 mg of the active ingredient (protein or expression vector). The number of doses of anticancer drugs administered to a patient may be one or multiple times. If multiple doses are administered, the interval between doses may be, for example, several days to several months.

[0055] [Other embodiments] In one embodiment, the present invention provides a method for treating cancer, comprising the steps of: collecting a biological sample from a cancer patient; measuring the expression level of a marker gene or marker protein in the biological sample; and, if the expression level is higher than a reference value, administering an immune checkpoint inhibitor to the cancer patient, wherein the marker gene or marker protein includes the NELL2 gene or NELL2 protein, the AMICA1 gene or AMICA1 protein, the CLEC11A gene or CLEC11A protein, the CLECL1 gene or CLECL1 protein, or the CMTM7 gene or CMTM7 protein.

[0056] In one embodiment, the present invention provides a method for treating cancer, comprising administering an effective amount of NELL2 protein or its expression vector, AMICA1 protein or its expression vector, CLEC11A protein or its expression vector, CLECL1 protein or its expression vector, or CMTM7 protein or its expression vector to a patient in need of treatment.

[0057] In one embodiment, the present invention provides NELL2 protein or its expression vector, AMICA1 protein or its expression vector, CLEC11A protein or its expression vector, CLECL1 protein or its expression vector, or CMTM7 protein or its expression vector for the treatment of cancer.

[0058] In one embodiment, the present invention provides the use of NELL2 protein or its expression vector, AMICA1 protein or its expression vector, CLEC11A protein or its expression vector, CLECL1 protein or its expression vector, or CMTM7 protein or its expression vector for producing an anticancer agent. [Examples]

[0059] The present invention will now be described in more detail with reference to examples, but the present invention is not limited to the following examples.

[0060] [Experimental Example 1] (Single-cell RNA sequencing (scRNA-Seq)) Blood samples were collected from nine melanoma patients before nivolumab administration and 7 weeks after the start of nivolumab administration. Figure 1 shows the experimental schedule. In Figure 1, "PD1 Ab" represents nivolumab, "Pre PBMC" represents peripheral blood mononuclear cells before nivolumab administration, and "After PBMC" represents peripheral blood mononuclear cells after nivolumab administration. "0W", "3W", "6W", and "7W" represent week 0 (start of nivolumab administration), week 3, week 6, and week 7, respectively.

[0061] Table 1 below shows the breakdown of melanoma patients. In Table 1, "PR" means a state in which the sum of tumor sizes has decreased by 30% or more (Partial Response), "LSD" means a state in which the tumor size has not changed for more than 6 months (Long Stable Disease), and "PD" means a state in which the sum of tumor sizes has increased by 20% or more and the absolute value has increased by 5 mm or more, or a state in which new lesions have appeared (Progressive Disease).

[0062] [Table 1]

[0063] Next, peripheral blood mononuclear cells were prepared from each blood sample, and CD8-positive T cells were collected one per well in a 96-well plate using a cell sorter (model "SH800S", Sony).

[0064] Next, a cDNA library for next-generation sequencing was prepared from each of the recovered CD8-positive T cells using a commercially available kit (product name "SMART-Seq(R)v4 3'DE Kit," Clontech). Subsequently, the prepared cDNA library was sequenced (RNA-seq) using a next-generation sequencer (product name "NovaSeq6000," Illumina).

[0065] In silico analysis revealed that of the 3,456 cells subjected to RNA-Seq analysis, 3,206 cells had a mitochondrial content of 10% or less, thus passing quality control (QC). As a result, we successfully detected 2.7 million reads per cell, averaging 6,000 genes (types) per cell.

[0066] Based on these analysis results, we focused on NELL2, AMICA1, CLEC11A, and CLECL1 as marker genes that can predict the efficacy of nivolumab administration, and conducted the following investigations.

[0067] [Experimental Example 2] (Consideration of NELL2) 《scRNA-Seq》 Figure 2(a) is a graph showing the results of an analysis of NELL2 gene expression levels in CD8-positive T cells before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients who responded well to nivolumab (PR or LSD) and patients who did not respond well to nivolumab (PD). The vertical axis of the graph represents the number of NELL2 reads per million reads.

[0068] As a result, both before (Pre) and after (Post) nivolumab administration, patients who responded well to nivolumab tended to have higher NELL2 gene expression levels than patients who did not respond well to nivolumab. Therefore, the NELL2 gene or NELL2 protein can be used as a marker to predict the effectiveness of nivolumab administration.

[0069] Figure 2(b) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high NELL2 gene expression and SLAMF6 gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0070] In this experiment, the expression level of the NELL2 gene was normalized, and cells showing an expression level of the first quartile or higher were defined as NELL2 high-expression cells. Similarly, the expression level of the SLAMF6 gene was normalized, and cells showing an expression level of the first quartile or higher were defined as SLAMF6 high-expression cells.

[0071] As a result, in the pre-administration (Pre) period, patients who responded well to nivolumab tended to have a higher proportion of cells with high NELL2 gene expression and high SLAMF6 gene expression compared to patients who did not respond well to nivolumab. Furthermore, analyzing the combined expression of NELL2 and SLAMF6 genes tended to predict the effectiveness of nivolumab administration with greater accuracy than analyzing the expression of the NELL2 gene alone.

[0072] Therefore, the SLAMF6 gene or SLAMF6 protein can be used in combination with the NELL2 gene or NELL2 protein as a marker to predict the efficacy of nivolumab administration.

[0073] Figure 2(c) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high NELL2 gene expression and CD44 gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0074] As described above, cells showing an expression level of the NELL2 gene at or above the first quartile after normalizing the expression level were defined as NELL2 high-expression cells. Similarly, cells showing an expression level of the CD44 gene at or above the first quartile after normalizing the expression level were defined as CD44 high-expression cells.

[0075] As a result, in the pre-administration (Pre) period, patients who responded well to nivolumab tended to have a higher proportion of cells with high NELL2 gene expression and CD44 gene expression compared to patients who did not respond well to nivolumab. Furthermore, analyzing the combined expression of NELL2 and CD44 genes tended to predict the effectiveness of nivolumab administration with greater accuracy than analyzing the expression of the NELL2 gene alone.

[0076] Therefore, the CD44 gene or CD44 protein can be used in combination with the NELL2 gene or NELL2 protein as a marker to predict the efficacy of nivolumab administration.

[0077] Figure 2(d) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high NELL2 gene expression and IL7R gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0078] As described above, cells showing an expression level of the NELL2 gene at or above the first quartile after normalizing the expression level were defined as NELL2 high-expression cells. Similarly, cells showing an expression level of the IL7R gene at or above the first quartile after normalizing the expression level were defined as IL7R high-expression cells.

[0079] As a result, in the pre-administration (Pre) period, patients who responded well to nivolumab tended to have a higher proportion of cells with high NELL2 gene expression and high IL7R gene expression compared to patients who did not respond well to nivolumab. Furthermore, analyzing the combined expression of NELL2 and IL7R genes tended to predict the effectiveness of nivolumab administration with greater accuracy than analyzing the expression of NELL2 gene alone.

[0080] Therefore, the IL7R gene or IL7R protein can be used in combination with the NELL2 gene or NELL2 protein as a marker to predict the efficacy of nivolumab administration.

[0081] Prognostic analysis using publicly available databases Using the publicly available database The Cancer Genome Atlas (TCGA), we investigated the association between NELL2 gene expression and the prognosis of melanoma (Skin Cutaneous Melanoma) patients. Specifically, based on the expression levels of the CD8 and NELL2 genes, each melanoma patient was divided into four groups: (i) high CD8A gene expression, high NELL2 gene expression group, (ii) high CD8A gene expression, low NELL2 gene expression group, (iii) low CD8A gene expression, high NELL2 gene expression group, and (iv) low CD8A gene expression, low NELL2 gene expression group, and prognosis analysis was performed.

[0082] Figure 3 is a graph showing the results of the prognosis analysis of melanoma patients. In Figure 3, "CD8A+ / NELL2+" indicates the results of the group with high CD8A gene expression and high NELL2 gene expression, "CD8A+ / NELL2-" indicates the results of the group with high CD8A gene expression and low NELL2 gene expression, "CD8A- / NELL2+" indicates the results of the group with low CD8A gene expression and high NELL2 gene expression, and "CD8A- / NELL2-" indicates the results of the group with low CD8A gene expression and low NELL2 gene expression.

[0083] The results revealed that the group with high CD8A gene expression and high NELL2 gene expression had the best prognosis.

[0084] 《Response of cancer antigen-specific cytotoxic T cells》 The MART-1 antigen is a protein known to be present on the surface of melanoma cells. First, we have T cells expressing a T cell receptor (MART-1 TCR) that recognizes the MART-1 antigen in an HLA-A201-restricted manner (hereinafter sometimes referred to as "MART-1 TCR-T cells") 6 × 10 6 Each individual was infected with a retrovirus expressing human NELL2.

[0085] Next, on day 4 of culture after infection, cells expressing HLA-A201 from the melanoma cell line MEL888 (hereinafter sometimes referred to as "MEL888 HLA A201 cells") were mixed in a 1:1 ratio (10 cells each). 4 Co-culturing was performed using MEL888 cells, and the amount of interferon (IFN)-γ in the culture supernatant was measured 24 hours after the start of co-culturing. In addition, a control group was prepared using MEL888 cells instead of MEL888 HLA A201 cells.

[0086] Figure 4 is a graph showing the results of quantifying IFN-γ production. In Figure 4, "Control" indicates the result of infecting MART-1 TCR-T cells with an empty retrovirus, "NELL2" indicates the result of infecting MART-1 TCR-T cells with a retrovirus expressing human NELL2, "Mel888" indicates the result using MEL888 cells, and "Mel888 HLA A201" indicates the result using MEL888 cells expressing HLA-A201 (MEL888 HLA A201 cells).

[0087] As a result, it was revealed that overexpression of NELL2 in cancer antigen-specific cytotoxic T cells (MART-1 TCR-T cells) using a retrovirus increased the production of IFN-γ by these cancer antigen-specific cytotoxic T cells. This result indicates that the NELL2 protein has anticancer activity. Therefore, the NELL2 protein can be used as an anticancer agent.

[0088] [Experimental Example 3] (Consideration of AMICA1) 《scRNA-Seq》 Figure 5(a) is a graph showing the results of an analysis of the percentage of AMICA1 gene-highly expressing cells in CD8-positive T cells before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%). In this experimental example, the expression level of the AMICA1 gene was normalized, and cells showing an expression level of the first quartile or higher were defined as AMICA1 gene-highly expressing cells.

[0089] As a result, both before (Pre) and after (Post) nivolumab administration, patients who responded well to nivolumab tended to have a higher proportion of cells expressing the AMICA1 gene compared to patients who did not respond well to nivolumab. Therefore, the AMICA1 gene or AMICA1 protein can be used as a marker to predict the effectiveness of nivolumab administration.

[0090] Figure 5(b) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high AMICA1 gene expression and high SELL gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0091] As described above, cells showing an expression level of the AMICA1 gene at or above the first quartile after normalizing the expression level were defined as AMICA1 high-expression cells. Similarly, cells showing an expression level of the SELL gene at or above the first quartile after normalizing the expression level were defined as SELL high-expression cells.

[0092] As a result, it was revealed that in the pre-administration (Pre) period, patients who responded well to nivolumab had a significantly higher proportion of cells with high AMICA1 gene expression and high SELL gene expression compared to patients who did not respond well to nivolumab. Furthermore, it was found that analyzing the combined expression of AMICA1 and SELL genes allowed for a more accurate prediction of the effectiveness of nivolumab administration than analyzing the expression of AMICA1 gene alone.

[0093] Therefore, the SELL gene or SELL protein can be used in combination with the AMICA1 gene or AMICA1 protein as a marker to predict the efficacy of nivolumab administration.

[0094] Figure 5(c) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high AMICA1 gene expression and IL7R gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0095] As described above, cells showing an expression level of the AMICA1 gene at or above the first quartile after normalizing the gene expression level were defined as AMICA1 high-expression cells. Similarly, cells showing an expression level of the IL7R gene at or above the first quartile after normalizing the gene expression level were defined as IL7R high-expression cells.

[0096] As a result, in the pre-administration (Pre) period, patients who responded well to nivolumab tended to have a higher proportion of cells with high AMICA1 gene expression and high IL7R gene expression compared to patients who did not respond well to nivolumab. Furthermore, analyzing the combined expression of AMICA1 and IL7R genes tended to predict the effectiveness of nivolumab administration with greater accuracy than analyzing the expression of AMICA1 gene alone.

[0097] Therefore, the IL7R gene or IL7R protein can be used in combination with the AMICA1 gene or AMICA1 protein as a marker to predict the efficacy of nivolumab administration.

[0098] Figure 5(d) is a graph showing the results of an analysis of the percentage of CD8-positive T cells with high AMICA1 gene expression and high CCR7 gene expression before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the percentage (%).

[0099] As described above, cells showing an expression level of the AMICA1 gene at or above the first quartile after normalizing the gene expression level were defined as AMICA1 high-expression cells. Similarly, cells showing an expression level of the CCR7 gene at or above the first quartile after normalizing the gene expression level were defined as CCR7 high-expression cells.

[0100] As a result, it was revealed that in the pre-administration (Pre) period, patients who responded well to nivolumab had a significantly higher proportion of cells with high AMICA1 gene expression and high CCR7 gene expression compared to patients who did not respond well to nivolumab. Furthermore, it was found that analyzing the combined expression of AMICA1 and CCR7 genes allowed for a more accurate prediction of nivolumab administration's effectiveness than analyzing the expression of AMICA1 gene alone.

[0101] Therefore, the CCR7 gene or CCR7 protein can be used in combination with the AMICA1 gene or AMICA1 protein as a marker to predict the efficacy of nivolumab administration.

[0102] Prognostic analysis using publicly available databases 1 Using the publicly available database The Cancer Genome Atlas (TCGA), we investigated the association between AMICA1 gene expression and the prognosis of melanoma (Skin Cutaneous Melanoma) patients. Specifically, based on the expression levels of the CD8 gene and AMICA1 gene, each melanoma patient was divided into four groups: (i) high CD8A gene expression, high AMICA1 gene expression group, (ii) high CD8A gene expression, low AMICA1 gene expression group, (iii) low CD8A gene expression, high AMICA1 gene expression group, and (iv) low CD8A gene expression, low AMICA1 gene expression group. Prognostic analysis was then performed for each group.

[0103] Figure 6(a) is a graph showing the results of the prognosis analysis of melanoma patients. In Figure 6(a), "CD8A+ / AMICA1+" indicates the results of the group with high CD8A gene expression and high AMICA1 gene expression, "CD8A+ / AMICA1-" indicates the results of the group with high CD8A gene expression and low AMICA1 gene expression, "CD8A- / AMICA1+" indicates the results of the group with low CD8A gene expression and high AMICA1 gene expression, and "CD8A- / AMICA1-" indicates the results of the group with low CD8A gene expression and low AMICA1 gene expression.

[0104] The results revealed that the group with high CD8A gene expression and high AMICA1 gene expression had the best prognosis.

[0105] Prognostic Analysis Using Publicly Available Databases 2 We investigated the association between AMICA1 gene expression and the prognosis of melanoma (Skin Cutaneous Melanoma) patients using the publicly available database, The Cancer Genome Atlas (TCGA). Specifically, we divided each melanoma patient into two groups: a high-expression AMICA1 gene group and a low-expression AMICA1 gene group, and performed prognostic analysis.

[0106] Figure 6(b) is a graph showing the results of the prognosis analysis of melanoma patients. In Figure 6(b), "AMICA1+" indicates the results for the group with high AMICA1 gene expression, and "AMICA1-" indicates the results for the group with low AMICA1 gene expression.

[0107] As a result, it was revealed that the prognosis was significantly better in the group with high AMICA1 gene expression.

[0108] 《Response of cancer antigen-specific cytotoxic T cells》 The above-mentioned MART-1 TCR-T cells 6 × 10 6 A fusion protein of human AMICA1 protein and the constant region of an antibody (AMICA1-Fc, R&D Inc.) was added to each culture medium to a final concentration of 400 ng / mL. As a control, a group was also prepared to which the constant region of an antibody (IgG1-Fc) was added to a final concentration of 400 ng / mL.

[0109] Next, on day 4 of culture, cells expressing HLA-A201 in MEL888 cells (MEL888 HLA A201 cells) were mixed in a 1:1 ratio (10 cells each). 4 Co-culture was performed using MEL888 cells, and the amount of IFN-γ in the culture supernatant was measured 24 hours after the start of co-culture. In addition, a control group was prepared using MEL888 cells instead of MEL888 HLA A201 cells.

[0110] Figure 7 is a graph showing the results of quantifying IFN-γ production. In Figure 7, "IgG1-Fc" indicates the result of adding IgG1-Fc to the culture medium of MART-1 TCR-T cells, "AMICA1-Fc" indicates the result of adding AMICA1-Fc to the culture medium of MART-1 TCR-T cells, "Mel888" indicates the result using MEL888 cells, and "Mel888 HLA A201" indicates the result using cells expressing HLA-A201 (MEL888 HLA A201 cells) in which MEL888 cells express HLA-A201.

[0111] The results showed that adding AMICA1 protein to the culture medium increased the production of IFN-γ by cancer antigen-specific cytotoxic T cells (MART-1 TCR-T cells). This indicates that AMICA1 protein possesses anticancer activity. Therefore, AMICA1 protein can be used as an anticancer agent.

[0112] [Experimental Example 4] (Consideration of CLEC11A) 《scRNA-Seq》 Figure 8 is a graph showing the results of an analysis of CLEC11A gene expression levels in CD8-positive T cells before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients in whom nivolumab administration was effective (PR or LSD) and patients in whom nivolumab administration was not effective (PD). The vertical axis of the graph represents the expression level per million reads. CLEC11A This is the number of reads.

[0113] As a result, it was revealed that patients who responded well to nivolumab administration had significantly higher expression levels of the CLEC11A gene than patients who did not respond well to nivolumab administration, both before (Pre) and after (Post) nivolumab administration. Therefore, the CLEC11A gene or CLEC11A protein can be used as a marker to predict the effectiveness of nivolumab administration.

[0114] Prognostic analysis using publicly available databases Using the publicly available database The Cancer Genome Atlas (TCGA), CLEC11AWe investigated the relationship between gene expression and the prognosis of melanoma (Skin Cutaneous Melanoma) patients. Specifically, based on the expression levels of the CD8 and CLEC11A genes, each melanoma patient was divided into four groups: (i) high CD8A gene expression, high CLEC11A gene expression group, (ii) high CD8A gene expression, low CLEC11A gene expression group, (iii) low CD8A gene expression, high CLEC11A gene expression group, and (iv) low CD8A gene expression, low CLEC11A gene expression group. Prognostic analysis was then performed for each group.

[0115] Figure 9 is a graph showing the results of the prognosis analysis of melanoma patients. In Figure 9, "CLEC11Ahigh_CD8Ahigh" indicates the results for the group with high CD8A gene expression and high CLEC11A gene expression, "CLEC11Alow_CD8Ahigh" indicates the results for the group with high CD8A gene expression and low CLEC11A gene expression, "CLEC11Ahigh_CD8Alow" indicates the results for the group with low CD8A gene expression and high CLEC11A gene expression, and "CLEC11Alow_CD8Alow" indicates the results for the group with low CD8A gene expression and low CLEC11A gene expression.

[0116] The results revealed that the group with high CD8A gene expression and high CLEC11A gene expression had the best prognosis.

[0117] 《Investigating the effects of CLEC11A on T cell differentiation》 We investigated the effects of overexpressing or knocking down the CLEC11A gene on T cell differentiation in peripheral blood mononuclear cells. Specifically, mononuclear cells isolated from human peripheral blood were first cultured and stimulated with CD3 / CD28 antibody. Subsequently, on day 3 from the start of culture, they were infected with various retroviruses (a retrovirus that overexpresses human CLEC11A, a retrovirus that expresses shRNA against human CLEC11A, and a control retrovirus).

[0118] Next, CD3 / CD28 antibody stimulation was performed on days 7, 14, and 21 from the start of culture. On day 24 from the start of culture, population analysis of the cell fraction of virus-infected CD8 T cells (GFP-positive) was performed using the expression of CD62L and CD45RA as indicators.

[0119] Figures 10(a) to (d) are graphs showing the results of flow cytometry analysis. In Figures 10(a) to (d), CD8-positive and GFP-positive cells were gated. In Figures 10(a) to (d), the horizontal axis shows the expression level of CD62L, and the vertical axis shows the expression level of CD45RA.

[0120] Figure 10(a) is a graph showing the results of analyzing the differentiation state of CD8-positive T cells into which a control vector was introduced. Figure 10(b) is a graph showing the results of analyzing the differentiation state of CD8-positive T cells in which the CLEC11A gene was overexpressed.

[0121] The results showed that overexpression of CLEC11A reduced the proportion of CD62L-negative CD45RA cells. This suggests that overexpression of the CLEC11A gene suppresses the differentiation of CD8-positive T cells.

[0122] Figure 10(c) is a graph showing the results of analyzing the differentiation state of CD8-positive T cells into which a control vector was introduced. Figure 10(d) is a graph showing the results of analyzing the differentiation state of CD8-positive T cells in which the CLEC11A gene was knocked down.

[0123] The results showed that knockdown of the CLEC11A gene increased the proportion of CD62L-negative CD45RA cells. This suggests that knockdown of the CLEC11A gene promotes the differentiation of CD8-positive T cells.

[0124] These results indicate that the CLEC11A protein is a functional molecule that maintains the undifferentiated state of T cells. The presence of undifferentiated T cells is thought to improve the effectiveness of immune checkpoint inhibitor administration. Therefore, the CLEC11A protein or substances that increase the expression of the CLEC11A protein in T cells can be used as drugs to improve the effectiveness of immune checkpoint inhibitor administration.

[0125] [Experimental Example 5] (Consideration of CLECL1) 《scRNA-Seq》 Figure 11 is a graph showing the results of an analysis of CLECL1 gene expression levels in CD8-positive T cells before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients who responded well to nivolumab (PR or LSD) and patients who did not respond well to nivolumab (PD). The vertical axis of the graph represents the number of CLECL1 reads per million reads.

[0126] As a result, it was revealed that patients who responded well to nivolumab administration had significantly higher expression levels of the CLEC1L1 gene than patients who did not respond well to nivolumab administration, both before (Pre) and after (Post) nivolumab administration. Therefore, the CLEC1L1 gene or CLEC1L1 protein can be used as a marker to predict the effectiveness of nivolumab administration.

[0127] [Experimental Example 6] (Consideration of CMTM7) 《scRNA-Seq》 Figure 12 is a graph showing the results of an analysis of CMTM7 gene expression levels in CD8-positive T cells before (Pre) and after (Post) nivolumab administration, based on the RNA-Seq results of Experimental Example 1, for patients who responded well to nivolumab (PR or LSD) and patients who did not respond well to nivolumab (PD). The vertical axis of the graph represents the number of CMTM7 reads per million reads. The numbers in Figure 12 represent the p-values.

[0128] As a result, it was revealed that patients who responded well to nivolumab administration had significantly higher expression levels of the CMTM7 gene than patients who did not respond well to nivolumab administration, both before (Pre) and after (Post) nivolumab administration. Therefore, the CMTM7 gene or CMTM7 protein can be used as a marker to predict the effectiveness of nivolumab administration.

[0129] Prognostic analysis using publicly available databases Using the publicly available database The Cancer Genome Atlas (TCGA), we investigated the association between CMTM7 gene expression and the prognosis of melanoma (Skin Cutaneous Melanoma) patients. Specifically, based on the expression levels of the CD8 and CMTM7 genes, each melanoma patient was divided into four groups: (i) high CD8A gene expression, high CMTM7 gene expression group, (ii) high CD8A gene expression, low CMTM7 gene expression group, (iii) low CD8A gene expression, high CMTM7 gene expression group, and (iv) low CD8A gene expression, low CMTM7 gene expression group. Prognostic analysis was then performed for each group.

[0130] Figure 13 is a graph showing the results of the prognosis analysis of melanoma patients. In Figure 13, "CD8A+ / CMTM7+" indicates the results of the group with high CD8A gene expression and high CMTM7 gene expression, "CD8A+ / CMTM7-" indicates the results of the group with high CD8A gene expression and low CMTM7 gene expression, "CD8A- / CMTM7+" indicates the results of the group with low CD8A gene expression and high CMTM7 gene expression, and "CD8A- / CMTM7-" indicates the results of the group with low CD8A gene expression and low CMTM7 gene expression.

[0131] The results revealed that the group with high CD8A gene expression and high CMTM7 gene expression had the best prognosis. [Industrial applicability]

[0132] According to the present invention, a novel technique can be provided for predicting the effectiveness of administering immune checkpoint inhibitors.

Claims

1. A method for collecting data to predict the effectiveness of administering immune checkpoint inhibitors to cancer patients, The process includes measuring the expression level of a marker gene in CD8-positive T cells derived from the cancer patient, or the expression level of a marker protein in plasma or serum derived from the cancer patient. The marker gene or marker protein includes the CLEC11A gene or protein. A method wherein the expression level is data for predicting the efficacy, and a higher expression level than a reference value indicates that administration of the immune checkpoint inhibitor to the cancer patient is effective.

2. The method according to claim 1, wherein the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody.

3. A specific binding agent for the CLEC11A protein, Primers for amplifying the cDNA of the CLEC11A gene, or It contains a probe that hybridizes to the mRNA of the CLEC11A gene, A kit for predicting the effectiveness of administering immune checkpoint inhibitors to cancer patients, used to measure the expression level of the CLEC11A gene in CD8-positive T cells derived from cancer patients, or the expression level of a marker protein in plasma or serum derived from said cancer patients.

4. A specific binding agent for the CD8 protein, Primers for amplifying the cDNA of the CD8 gene, or The kit according to claim 3, further comprising a probe that hybridizes to the mRNA of the CD8 gene.

Images