Technique for predicting pathology, prognosis, and therapeutic effect of t-cell-related disease

Abstract

The present disclosure provides a biomarker for predicting and diagnosing the pathology, the prognosis, and the therapeutic effect of a T-cell-related disease. More specifically, the present disclosure provides: a marker that is a binding-type soluble PD-L1 (bsPD-L1 / sPD-L1 with PD-1-binding capacity) for use in predicting the pathology, the prognosis, and the therapeutic effect of cancer and / or T-cell related diseases, as well as a factor, an agent, an element, or a composition that interacts with the marker; a factor that interacts with an agent, an element, or a composition for predicting the pathology, the prognosis, and the therapeutic effect of T-cell related diseases or with a host T-cell immune marker, the factor including factors that interact with at least one matrix metalloproeinase (MMP / matrix metalloproteinase) in a group A; and (2) a combination of a condition diagnostic marker and a factor that interacts therewith.

Description

Techniques for predicting the pathology, prognosis, and therapeutic effects of T cell-related diseases

[0001] The present disclosure relates to biomarkers for predicting the pathology, severity, prognosis, and / or efficacy of treatment (e.g., therapeutic or preventive) of T cell-related diseases, as well as factors, agents, compositions, reagents, systems, devices, etc. for detecting the biomarkers. Furthermore, the present disclosure relates to methods, reagents, kits, etc. for detecting and quantifying biomarkers in biological samples obtained from patients before and after treatment, and examining the fluctuations thereof, thereby enabling stratification of patients with regard to responsiveness to treatment of T cell-related diseases.

[0002] Immune checkpoint molecules are molecules that are expressed in immunocompetent cells such as lymphocytes and transmit signals that suppress the immune system. They play roles such as maintaining the body's self-tolerance and excessive immunosuppression during infection. However, during the onset of cancer, cancer cells escape from the host's immune surveillance via immune checkpoint molecule signals, ultimately causing cancer proliferation. Immune checkpoint inhibitors (ICIs / Immune Checkpoint Inhibitors) are anticancer drugs that exert antitumor effects by suppressing the function of immune checkpoint molecules (e.g., programmed cell death protein) 1 (PD-1), PD-L1, and CTLA-4) (Patent Documents 1 and 2; Non-Patent Documents 1 to 3). In recent years, ICIs have been approved as new drugs, significantly changing cancer treatment. Currently, PD-1 inhibitors (nivolumab, pembrolizumab) and PD-L1 inhibitors, elements, or compositions (atezolizumab, durvalumab) are approved as immune checkpoint inhibitors.

[0003] Problems with ICI include high medical costs (over 10 million yen per year) and a low response rate of approximately 20%. The remaining approximately 80% of cancer patients experience poor therapeutic benefit, but no effective biomarkers have yet been identified to distinguish between the two. For example, in the case of cancer, guidelines indicate that PD-L1 expression in cancer tissue should be examined by pathological testing (immunohistochemical staining) to determine suitability. However, immunohistochemical staining suffers from the following problems: 1. Tissue collection by biopsy places a heavy burden on patients. 2. PD-L1 expression results can vary depending on the tissue collection site. 3. Quantification is difficult. 4. PD-L1 expression in tissues other than cancer tissue is unknown. To ensure the appropriate use of ICI, a minimally invasive and accurate method for predicting and diagnosing its therapeutic efficacy is needed.

[0004] PD-L1 is expressed not only in tumor cells but also in vascular endothelial cells and antigen-presenting cells. When inflammation occurs, its expression is induced in various types of cells by IFN (interferon)-γ signaling. PD-L1 is expressed on the cell membrane surface as a transmembrane protein, but soluble PD-L1 is known to exist in the blood. Soluble PD-L1 (sPD-L1) can be either one that binds to the PD-1 receptor or one that does not. The present inventors have named the soluble PD-L1 that binds to the PD-1 receptor bsPD-L1 and have developed an ELISA system to specifically detect bsPD-L1 (Patent Document 3, Non-Patent Document 5). Regarding the production of sPD-L1, RNA splicing, cleavage and degradation of PD-L1 by metalloproteases, and exosomes have been reported, but the primary production mechanism in cancer patients remains unknown.

[0005] Furthermore, in comparative studies, ICI has been shown to have a superior therapeutic effect to chemotherapy (e.g., docetaxil), but the survival curves for overall survival (OS) and progression-free survival (PFS) often intersect at around 6 months, and there are many reports that the ICI-administered group performs worse until then (Non-Patent Document 4, Checkmate 057 study, etc.). Such a rapid decline in survival rate early in ICI treatment suggests that there are a certain number of patients for whom ICI treatment is ineffective or inferior to chemotherapy.

[0006] Patent No. 4409430, Patent No. 5885764, International Publication No. 2019 / 049974

[0007] Iwai Y, et al., Ishida M, Tanaka Y, Okazaki T, Honjo T, and Minato N, Proc Natl Acad Sci US A. 2002 Sep 17;99(19):12293-7. MF, and Allison JP, Science. 1996 Mar 22;271(5256):1734-6. Hellmann, Matthew D, N Engl J Med 2019; 381:2020-31. M. Takeuchi et al., Immunol Lett. 2018 Apr;196:155-160.

[0008] As a result of extensive research, the present inventors have developed and completed biomarkers for predicting the pathology, severity, prognosis, and / or efficacy of treatment (e.g., therapeutic or preventive) of T cell-related diseases, as well as factors, agents, compositions, reagents, systems, and devices for detecting the biomarkers. In particular, the recently emerged cancer immunotherapy using ICI has a clinical course completely different from that of chemotherapy, with some patients experiencing exacerbation (A) and others experiencing a marked response (B). A diagnostic method for distinguishing between these two groups is also provided. The present disclosure provides biomarkers that enable prediction of the pathology, severity, prognosis, and / or efficacy of treatment (e.g., therapeutic or preventive) of T cell-related diseases, and in particular, biomarkers for predicting and diagnosing the therapeutic efficacy of cancer immunotherapy, particularly immunotherapy involving immunomodulators (including anti-inflammatory drugs (including biologics), immunosuppressants (steroids, etc.), immunostimulants (including immune checkpoint inhibitors), etc.); methods for predicting and diagnosing the therapeutic efficacy of immunotherapy using the expression of the markers as indicators, methods for supporting the same; methods for enabling patient stratification in immunotherapy using the same, and reagents, kits, etc. for the same. The present disclosure also provides biomarkers with various functions, such as distinguishing between immunotherapy and chemotherapy. That is, the present disclosure is as follows: [Item 1] An agent, device, or composition comprising an entity that interacts with bound soluble PD-L1 (bsPD-L1 / sPD-L1 with PD-1-binding capacity), for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease. [Item 2] An agent, device, or composition comprising an entity that interacts with bound soluble PD-L1 (bsPD-L1 / sPD-L1 with PD-1-binding capacity), for use in predicting the efficacy or prognosis of cancer treatment (e.g., therapy or prevention).[Item 3] The agent, element, or composition according to any one of the above items, wherein the treatment, in the case of a T-cell-related disease, includes one selected from immunomodulators (anti-inflammatory drugs (including biologics), immunosuppressants (steroids, etc.), and immunostimulants (including immune checkpoint inhibitors)), and in the case of cancer, includes one selected from immunotherapy including immune checkpoint inhibitors, chemotherapy, radiation therapy, molecular targeted drugs, proton beams, and combinations thereof, or combinations of these with surgery or immunotherapy including ICI. [Item 4] The agent, element, or composition according to any one of the above items, wherein the agent, element, or composition is used to predict the effect and prognosis of treatment (therapeutic or preventive) for a disease or condition primarily driven by a T-cell response using an autoantigen (including cancer), a foreign antigen (including pathogens, vaccines, and transplants), or an immunomodulator. [Item 5] The agent, element, or composition according to any one of the above items, which is used for evaluating T-cell immune function and / or tissue damage in a subject, predicting cancer invasion, metastasis, or recurrence, and / or predicting the therapeutic effect of immunotherapy including immune checkpoint inhibitors, surgery, radiation therapy, chemotherapy, and molecular targeted drugs, and combinations thereof, when the treatment is for cancer. [Item 6] The agent, element, or composition according to any one of the above items, wherein the treatment includes at least one selected from chemotherapy, radiation therapy, a combination thereof, a combination of any one ... [Item 8] The agent, element, or composition according to any one of the preceding items, wherein the agent is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof, and combinations thereof, and an element for detecting protein interactions using surface plasmon resonance technology (e.g., Biacore™). [Item 9] The agent, element, or composition according to any one of the preceding items, wherein the agent is an antibody or an antigen-binding fragment thereof, or a variant thereof.[Item 10] The agent, element, or composition according to any one of the above items, wherein the factor is a carrier on which PD-1 protein is immobilized or an element for detecting protein interactions using surface plasmon resonance technology (e.g., Biacore™). [Item 11] The agent, element, or composition according to any one of the above items, wherein the agent, element, or composition is used in a method for detecting bsPD-L1 by a method comprising the steps of reacting a target substance with PD-1, and detecting and quantifying soluble PD-L1 bound to PD-1 as bsPD-L1. [Item 12] The agent, element, or composition according to any one of the above items, wherein the prediction includes prediction of the therapeutic effect of an immune checkpoint inhibitor. [Item 13] The agent, element, or composition according to any one of the above items, which is a diagnostic drug, diagnostic element, or reagent. [Item 14] A kit for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T-cell-related disease, comprising the agent, element, or composition described in any one of the above items and a substance used for detection using the agent, element, or composition. [Item 15] A kit for use in predicting the effect of treatment or prognosis of cancer, comprising the agent, element, or composition described in any one of the above items and a substance used for detection using the agent, element, or composition. [Item 16] The kit of any one of the above items, wherein the agent, element, or composition is a PD-1 protein bound to a carrier, and the substance is a labeled anti-PD-L1 antibody. [Item 17] The kit of any one of items 14 to 16, further comprising one or more features of any one of items 1 to 13. [Item 18] A system for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease, comprising the agent, element, or composition according to any one of the preceding items, and, if necessary, a substance used for detection using the agent, element, or composition, and, if necessary, an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target to be detected, and a detection means used to detect a signal resulting from the agent, element, or composition.[Item 19] A system for use in predicting the efficacy of cancer treatment or prognosis, comprising the agent, element, or composition according to any one of the preceding items, optionally a substance used for detection using the agent, element, or composition, optionally an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and detection means used to detect a signal resulting from the agent, element, or composition. [Item 20] The system according to item 18 or 19, further comprising one or more features according to any one of items 1 to 17. [Item 21] The system according to any one of the preceding items, wherein the agent, element, or composition is a PD-1 protein bound to a carrier, the substance is a labeled anti-PD-L1 antibody, the interaction portion is a container that can be placed in a state in which the agent, element, or composition and the sample can interact, and the detection means detects a signal resulting from the label. [Item 22] A method for assisting in prediction of the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, the method comprising the step of detecting bound soluble PD-L1 in a sample obtained from the subject. [Item 23] A method for assisting in prediction of the effect of treatment or prognosis of cancer in a subject, the method comprising the step of detecting bound soluble PD-L1 in a sample obtained from the subject. [Item 24] A method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, the method comprising the steps of detecting bound soluble PD-L1 in a sample obtained from the subject, and calculating an index for predicting the effect of treatment or prognosis of the T-cell-related disease in the subject from the value of bsPD-L1. [Item 25] A method for predicting the effect of cancer treatment or predicting prognosis in a subject, the method comprising the steps of detecting bound soluble PD-L1 in a sample obtained from the subject, and calculating an index related to the prediction of the effect of cancer treatment or predicting prognosis in the subject from the value of the bsPD-L1. [Item 26] The method of any one of Items 22 to 25, further comprising one or more features of any one of Items 1 to 21.<MMPs> [Item 27] ​​An agent, element, or composition for predicting the pathology, severity, prognosis, and / or effect of treatment (therapeutic or preventive) and / or predicting the prognosis of a T-cell-associated disease, or for predicting the pathology of cancer, or for use as a diagnostic marker for disease progression, comprising a factor that interacts with at least one member of the matrix metalloproteinase (MMP / matrix metalloproteinase) A group. [Item 28] An agent, element, or composition for predicting the effect of treatment (e.g., therapeutic or preventive) and / or prognosis of cancer, or for predicting the pathology of cancer, or for use as a diagnostic marker for disease progression, comprising a factor that interacts with at least one member of the matrix metalloproteinase (MMP / matrix metalloproteinase) A group. [Item 29] The agent, element, or composition according to any one of the above items, which is used to predict the effect and prognosis of treatment (therapeutic or preventive) for a disease or condition primarily driven by a T cell response using an autoantigen (including cancer), a foreign antigen (including a pathogen, a vaccine, or a transplant), or an immunomodulatory drug. [Item 30] The agent, element, or composition according to any one of the above items, which is used to evaluate T cell immune function and / or tissue damage in a subject, predict cancer invasion, metastasis, or recurrence, and / or predict the therapeutic effect of an immunomodulatory drug, including an immune checkpoint inhibitor. [Item 31] The agent, element, or composition according to any one of the above items, wherein the MMP A group comprises at least one member of the MMP B group. [Item 32] The agent, element, or composition according to any one of the above items, wherein the MMP A group comprises at least one member of the MMP C group. [Item 33] The agent, element, or composition according to any one of the above items, wherein the MMP A group comprises at least two members of the MMP C group. [Item 34] The agent, element, or composition according to any one of the preceding items, wherein the MMP A group includes MMP3 and MMP13 from the MMP C group. [Item 35] The agent, element, or composition according to any one of the preceding items, wherein the MMP A group includes at least one member from the MMP D group.[Item 36] The agent, element, or composition according to any one of the preceding items, wherein the treatment comprises chemotherapy, radiation therapy, molecular targeted drugs, proton beams, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof. [Item 37] The agent, element, or composition according to any one of the preceding items, wherein the treatment comprises ICI or surgery. [Item 38] The agent, element, or composition according to any one of the preceding items, wherein the prediction comprises cancer prognosis prediction and prediction of invasion, metastasis, and recurrence. [Item 39] The agent, element, or composition according to any one of the preceding items, wherein the factor is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, a polypeptide, a fragment thereof, a combination thereof, and a mass spectrometry element. [Item 40] The agent, element, or composition according to any one of the preceding items, wherein the factor is an antibody or an antigen-binding fragment thereof, or a variant thereof. [Item 41] The agent, element, or composition according to any one of the preceding items, wherein the factor is an antibody or an antigen-binding fragment thereof capable of specifically binding to MMP3 and / or MMP13. [Item 42] The agent, element, or composition according to any one of the preceding items, wherein the prediction includes predicting the therapeutic effect of an immune checkpoint inhibitor. [Item 43] The agent, element, or composition according to any one of the preceding items, which is a diagnostic agent, diagnostic element, or reagent. [Item 44] A kit for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease, comprising the agent, element, or composition according to any one of the preceding items and a substance used for detection using the agent, element, or composition. [Item 45] A kit for use in predicting the effect or prognosis of cancer therapy or prevention, or the prognosis, comprising the agent, element, or composition according to any one of the preceding items and a substance used for detection using the agent, element, or composition. [Item 46] The kit according to any one of the preceding items, wherein the agent, element, or composition is bound to a carrier. [Item 47] The kit according to any one of the above items, wherein the agent, element, or composition is used for detection using an antibody or a labeled substance thereof, FACS, Luminex, Hiscl (trademark), or Western blotting.[Item 48] The kit according to any one of items 44 to 47, further comprising one or more features of any one of items 27 to 43. [Item 49] A system for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease, comprising the agent, element, composition, or kit according to any one of the preceding items, a substance used for detection using the agent, element, or composition, an interaction part that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means that is used to detect a signal resulting from the agent, element, or composition. [Item 50] A system for use in predicting the effect of therapy or prevention or prognosis of cancer, comprising the agent, element, composition, or kit according to any one of the preceding items, a substance used for detection using the agent, element, or composition, an interaction part that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means that is used to detect a signal resulting from the agent, element, or composition. [Item 51] The system according to any one of the above items, wherein the agent, element, or composition is an anti-MMP group A antibody bound to a carrier, the substance is a labeled anti-MMP group A antibody, the interaction portion is a container that can create a state in which the agent, element, or composition and the sample can interact, and the detection means detects a signal caused by the label. [Item 52] The system according to any one of the above items, wherein the MMP A group includes at least one MMP B group. [Item 53] The system according to any one of the above items, wherein the MMP A group includes at least one MMP C group. [Item 54] The system according to any one of the above items, wherein the MMP A group includes at least two MMP C group members. [Item 55] The system according to any one of the above items, wherein the MMP A group includes MMP3 and MMP13 from the MMP C group. 56. The system of any one of claims 49 to 55, further comprising one or more features of any one of claims 27 to 48.<Biomarkers> [Item 57] A biomarker comprising at least one member of the MMP A group for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T-cell-related disease. [Item 58] A biomarker comprising at least one member of the MMP A group for predicting the effect and / or prognosis of cancer treatment, or predicting the pathology of cancer. [Item 59] The biomarker of any one of the above items, wherein the cancer treatment comprises chemotherapy, radiation therapy, molecular targeted drugs, proton beam, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof. [Item 60] The biomarker of any one of the above items, wherein the cancer treatment comprises an immune checkpoint inhibitor. [Item 61] The biomarker of any one of the above items, wherein the biomarker comprises at least one member of the MMP B group. [Item 62] The biomarker of any one of the above items, wherein the biomarker comprises at least one member of the MMP C group. [Item 63] The biomarker according to any one of the preceding items, wherein the biomarker comprises at least two members of the MMP C group. [Item 64] The biomarker according to any one of the preceding items, wherein the biomarker comprises MMP3 and MMP13 from the MMP C group. [Item 65] The biomarker according to any one of the preceding items, wherein the biomarker comprises at least one member of the MMP D group. [Item 66] The biomarker according to any one of items 57 to 65, further comprising one or more features of any one of items 27 to 56. [Item 67] A method for assisting in prediction of the pathology, severity, prognosis, and / or efficacy of treatment (e.g., therapeutic or preventive) of a T-cell related disease in a subject, the method comprising detecting at least one member of the MMP A group in a sample obtained from the subject. [Item 68] A method for assisting in prediction of the efficacy of treatment or prognosis of cancer in a subject, the method comprising detecting at least one member of the MMP A group in a sample obtained from the subject.[Item 69] A method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, the method comprising the steps of detecting at least one member of the MMP A group in a sample obtained from the subject, and calculating an index related to the prediction of the effect of treatment or prevention or prognosis of the T-cell-related disease in the subject from the value of at least one member of the MMP A group. [Item 70] A method for predicting the effect of treatment or prevention or prognosis of cancer in a subject, the method comprising the steps of detecting at least one member of the MMP A group in a sample obtained from the subject, and calculating an index related to the prediction of the effect of treatment or prevention or prognosis of the cancer in the subject from the value of at least one member of the MMP A group. [Item 71] The method of any one of the above items, wherein the MMP A group includes at least one member of the MMP B group. [Item 72] The method of any one of the above items, wherein the MMP A group includes at least one member of the MMP C group. [Item 73] The method of any one of the preceding items, wherein the MMP A group includes at least two of the MMP C group. [Item 74] The method of any one of the preceding items, wherein the MMP A group includes MMP3 and MMP13 from the MMP C group. [Item 75] The method of any one of items 67 to 74, further comprising one or more features of any one of items 27 to 66. <Combination of markers> [Item 76] A combination of (1) a factor that interacts with a host T-cell immunocompetence marker and (2) a factor that interacts with a disease progression diagnostic marker. [Item 77] A combination of (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker. [Item 78] A combination of (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T-cell-related disease. [Item 79] A combination of (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker for predicting the efficacy and / or prognosis of cancer treatment, or predicting the pathological condition of cancer.[Item 80] The combination according to any one of the above items, which is used to predict the effect and prognosis of treatment (therapeutic or preventive) for a disease or condition primarily driven by a T-cell response using an autoantigen (including cancer), a foreign antigen (including a pathogen, a vaccine, or a transplant), or an immunomodulatory drug. [Item 81] The combination according to any one of the above items, which is used to evaluate T-cell immune function and / or tissue damage in a subject, predict cancer invasion, metastasis, or recurrence, and / or predict the therapeutic effect of an immunomodulatory drug, including an immune checkpoint inhibitor. [Item 82] (1) The combination according to any one of the above items, wherein the host T-cell immune function marker includes at least one selected from the group consisting of bsPD-L1, MMP D group, and interferon-γ. [Item 83] (2) The combination according to any one of the above items, wherein the disease status diagnostic marker includes at least one selected from the group consisting of MMP A group. [Item 84] (2) The combination according to any one of the above items, wherein the disease status diagnostic marker comprises at least one selected from the group consisting of MMP B group. [Item 85] (2) The combination according to any one of the above items, wherein the disease status diagnostic marker comprises at least one selected from the group consisting of MMP C group. [Item 86] (2) The combination according to any one of the above items, wherein the disease status diagnostic marker comprises at least one selected from the group consisting of MMP D group. [Item 87] The combination according to any one of the above items, wherein (1) the detection of the host T-cell immunocompetence marker is performed before treatment, and (2) the detection of the disease status diagnostic marker utilizes changes in values ​​during treatment. [Item 88] The combination according to any one of the above items, wherein the combination is used for predicting the effect and / or prognosis of cancer treatment, or predicting the pathological state of cancer. [Item 89] The combination according to any one of the above items, wherein (1) is bsPD-L1 or MMP13. [Item 90] The combination according to any one of the above items, wherein (2) is MMP3 or MMP13. [Item 91] The combination according to any one of the above items, wherein (2) is MMP3 and MMP13.[Item 92] (A) The combination according to any one of the above items, wherein the host T cell immunocompetence marker in (1) is bsPD-L1 and the disease diagnostic marker in (2) is MMP3; (B) The host T cell immunocompetence marker in (1) is bsPD-L1 and the disease diagnostic marker in (2) is MMP13; (C) The host T cell immunocompetence marker in (1) is bsPD-L1 and the disease diagnostic marker in (2) is MMP3 and MMP13; (D) The host T cell immunocompetence marker in (1) is MMP13 and the disease diagnostic marker in (2) is MMP3; (E) The host T cell immunocompetence marker in (1) is MMP13 and the disease diagnostic marker in (2) is MMP13; or (F) The host T cell immunocompetence marker in (1) is MMP13 and the disease diagnostic marker in (2) is MMP3 and MMP13. [Item 93] The combination according to any one of the above items, wherein (1) the detection of the host T-cell immunocompetence marker is performed before treatment or utilizes changes in values ​​during treatment, and (2) the detection of the disease status diagnostic marker is performed before treatment or utilizes changes in values ​​during treatment, and (F) the host T-cell immunocompetence marker in (1) is MMP13, and the disease status diagnostic marker in (2) is MMP3 and MMP13. [Item 94] An agent, device, or composition, or a kit thereof, for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., treatment or prevention) of a T-cell-related disease, comprising the combination of factors according to any one of the above items. [Item 95] An agent, device, or composition, or a kit thereof, for use in predicting the effect of treatment or prevention or prognosis of cancer, comprising the combination of factors according to any one of the above items.[Item 96] A method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, the method comprising the steps of detecting (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index related to the prediction of the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of the T-cell-related disease in the subject from the values ​​of the (1) host T-cell immunocompetence marker and the (2) disease progression diagnostic marker. [Item 97] A method for predicting the effect of cancer treatment or prognosis in a subject, the method comprising the steps of detecting (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index related to the prediction of the effect of cancer treatment or prognosis in the subject from the values ​​of the (1) host T-cell immunocompetence marker and the (2) disease progression diagnostic marker. [Item 98] The method or combination of any one of the preceding items, wherein the prediction includes predicting the therapeutic effect of an immune checkpoint inhibitor, wherein the combination comprises using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (1) and (2) in the biological samples: the concentration of (1) in a biological sample obtained before treatment; the concentration of (2) in a biological sample obtained before and after treatment. [Item 99] The method or combination of any one of the preceding items, wherein the prediction includes predicting the therapeutic effect of an immune checkpoint inhibitor, wherein the combination comprises using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (a) and (b) in the biological samples: (a) the bsPD-L1 concentration and / or MMP13 concentration, which are (1), in a biological sample obtained before treatment; (b) the MMP3 concentration and / or MMP13 concentration, which are (2), in biological samples obtained before and after treatment. [Item 100] The method or combination according to any one of the above items, wherein the therapeutic effect of the immune checkpoint inhibitor is predicted to be high when bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration and / or MMP13 concentration in the biological sample are reduced before and after treatment.[Item 101] A method or combination according to any one of the preceding items, which predicts a low therapeutic effect of an immune checkpoint inhibitor when bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration in the biological sample is increased before and after treatment. [Item 102] A method or combination according to any one of the preceding items, for stratifying subjects with respect to their sensitivity to treatment with an immune checkpoint inhibitor, comprising a step of measuring the bsPD-1 concentration and / or the MMP13 concentration in a biological sample obtained from the subject before treatment. [Item 103] A method or combination according to any one of the preceding items, further comprising obtaining biological samples from the subject before and after treatment, and associating a case where the MMP3 concentration and / or the MMP13 concentration in the biological sample after treatment is lower than that before treatment with an immune checkpoint inhibitor. [Item 104] The method or combination according to any one of the preceding items further comprises obtaining biological samples from the subject before and after treatment, and correlating a case where the MMP3 concentration and / or MMP13 concentration in the biological sample after treatment is higher than that before treatment with an immune checkpoint inhibitor non-response case. [Item 105] The combination according to any one of the preceding items, wherein (1) is measured at least during or after treatment, and (2) is measured at least during or after treatment. [Item 106] The combination according to any one of the preceding items, wherein (1) is measured before and after treatment, and (2) is measured at least during or after treatment. [Item 107] The combination according to any one of the preceding items, wherein (1) is measured before treatment, and (2) is measured at least during or after treatment. [Item 108] The combination according to any one of the preceding items, wherein (1) is measured before treatment, and (2) is measured before and after treatment. [Item 109] The combination according to any one of the above items, wherein the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence. [Item 110] The combination according to any one of the above items, wherein the factor is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof and combinations thereof. [Item 111] The combination according to any one of the above items, wherein the factor is an antibody or an antigen-binding fragment thereof, or a variant thereof.[Item 112] The combination according to any one of the preceding items, wherein the prediction includes prediction of the therapeutic effect of an immune checkpoint inhibitor. [Item 113] (1) An agent, element, or composition for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., treatment or prevention) of a T-cell-related disease, comprising a factor that interacts with a host T-cell immunocompetence marker, wherein (1) is used in combination with (2) a factor that interacts with a disease status diagnostic marker. [Item 114] (1) An agent, element, or composition for predicting the effect of treatment or prevention or prognosis of cancer, comprising a factor that interacts with a host T-cell immunocompetence marker, wherein (1) is used in combination with (2) a factor that interacts with a disease status diagnostic marker. [Item 115] The agent, element, or composition according to item 113 or 114, comprising one or more features according to any one of items 76 to 112. [Item 116] (2) An agent, element, or composition for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T-cell related disease, comprising a factor that interacts with a disease diagnostic marker, wherein (2) is used in combination with (1) a factor that interacts with a host T-cell immunocompetence marker. [Item 117] (2) An agent, element, or composition for predicting the effect of cancer treatment or prognosis, comprising a factor that interacts with a disease diagnostic marker, wherein (2) is used in combination with (1) a factor that interacts with a host T-cell immunocompetence marker. [Item 118] The agent, element, or composition according to item 116 or 117, comprising one or more features according to any one of items 76 to 112. [Item 119] A method for assisting in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T cell-related disease, the method comprising the steps of detecting (1) a host T cell immunocompetence marker and (2) a disease progression diagnostic marker. [Item 120] A method for assisting in predicting the effect of cancer treatment or prognosis, the method comprising the steps of detecting (1) a host T cell immunocompetence marker and (2) a disease progression diagnostic marker.[Item 121] A method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, the method comprising the steps of detecting (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index related to the prediction of the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of the T-cell-related disease in the subject from the values ​​of the (1) host T-cell immunocompetence marker and the (2) disease progression diagnostic marker. [Item 122] A method for predicting the effect of cancer treatment or prognosis in a subject, the method comprising the steps of detecting (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index related to the prediction of the effect of cancer treatment or prognosis in the subject from the values ​​of the (1) host T-cell immunocompetence marker and the (2) disease progression diagnostic marker. [Item 123] The method, agent, element, composition, or combination according to any one of the preceding items, wherein the prediction includes predicting the therapeutic effect of an immune checkpoint inhibitor, and wherein the combination comprises using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (1) and (2) in the biological samples: the concentration of (1) in the biological sample obtained before treatment; the concentration of (2) in the biological sample obtained before and after treatment. [Item 124] The method, agent, element, composition, or combination according to any one of the preceding items, wherein the prediction includes predicting the therapeutic effect of an immune checkpoint inhibitor, and wherein the combination comprises using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (a) and (b) in the biological samples: (a) the concentration of bsPD-L1, which is (1), in the biological sample obtained before treatment; (b) the concentration of MMP3, which is (2), in the biological sample obtained before and after treatment. [Item 125] The method, agent, element, composition, or combination according to any one of the above items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be high if bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration in the biological sample decreases before and after treatment.[Item 126] The method, agent, element, composition, or combination according to any one of the preceding items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be low if bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration in the biological sample is increased before and after treatment. [Item 127] A method, agent, element, composition, or combination for stratifying a subject with respect to their sensitivity to treatment with an immune checkpoint inhibitor, which method, agent, element, composition, or combination according to any one of the preceding items, characterized by a step of measuring the concentration of bsPD-1 in a biological sample obtained from the subject before treatment. [Item 128] The method, agent, element, composition, or combination according to any one of the preceding items, further comprising obtaining biological samples from the subject before and after treatment, and associating a lower MMP3 concentration in the biological sample after treatment with a case in which the immune checkpoint inhibitor is effective. [Item 129] The method, agent, element, composition, or combination according to any one of the preceding items, further comprising obtaining biological samples from the subject before and after treatment, and associating a higher MMP3 concentration in the biological sample after treatment than that before treatment with an immune checkpoint inhibitor non-response case. [Item 130] The agent, element, composition, or combination according to any one of the preceding items, which is a diagnostic drug, diagnostic element, or reagent. [Item 131] A kit for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., treatment or prevention) of a T-cell-related disease, comprising the agent, element, or composition according to any one of the preceding items, which detects (1) a host T-cell immune function marker, (2) a disease progression diagnostic marker, or a combination thereof, and a substance used for detection using the agent, element, or composition. [Item 132] A kit for use in predicting the efficacy of cancer treatment or prognosis, comprising the agent, element, or composition according to any one of the above items, which detects (1) a host T-cell immunocompetence marker, (2) a disease progression diagnostic marker, or a combination thereof, and a substance used for detection using the agent, element, or composition. [Item 133] The kit according to Item 131 or 132, further comprising one or more features of any one of Items 1 to 130.[Item 134] A system for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T cell-related disease, comprising: (1) a factor that interacts with a host T cell immunocompetence marker; (2) a factor that interacts with a disease status diagnostic marker; a substance used for detection using the agent, element, or composition; an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. [Item 135] A system for predicting the effect of cancer treatment or prognosis, comprising: (1) a factor that interacts with a host T cell immunocompetence marker; (2) a factor that interacts with a disease status diagnostic marker; a substance used for detection using the agent, element, or composition; an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. [Item 136] The system according to Item 134 or 135, further comprising one or more features of any one of Items 1 to 133. [Item 137] A combination of (A) a factor that interacts with at least one member of the MMP D group before treatment and (B) a factor that interacts with at least one member of the MMP D group before and after treatment. [Item 138] An agent, element, or composition for predicting the effect of cancer therapy or prevention or predicting prognosis, comprising (A) a factor that interacts with at least one member of the MMP D group before treatment, wherein (B) the agent, element, composition, or combination is used in combination with a factor that interacts with at least one member of the MMP D group before and after treatment. [Item 139] An agent, element, or composition for predicting the effect of cancer therapy or prevention or predicting prognosis, comprising (B) a factor that interacts with at least one member of the MMP D group before and after treatment, wherein (A) the agent, element, composition, or combination is used in combination with a factor that interacts with at least one member of the MMP D group before and after treatment. [Item 140] A combination of (A) at least one MMP D group detected before treatment and (B) at least one MMP D group detected before and after treatment.[Item 141] An agent, element, or composition, or a combination thereof, for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease, comprising: (A) a factor that interacts with at least one member of the MMP D group before treatment, and (B) a factor that interacts with at least one member of the MMP D group before and after treatment. [Item 142] An agent, element, or composition, or a combination thereof, for predicting the effect of cancer therapy or prevention or prognosis, comprising: (A) a factor that interacts with at least one member of the MMP D group before treatment, and (B) a factor that interacts with at least one member of the MMP D group before and after treatment. [Item 143] The agent, element, or composition, or a combination thereof, according to Item 141 or 142, comprising one or more features of any one of Items 27 to 140. [Item 144] A method for assisting in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T cell-related disease, the method comprising: (A) detecting at least one member of the MMP D group before treatment; and (B) detecting at least one member of the MMP D group before and after treatment. [Item 145] A method for assisting in predicting the effect of cancer treatment or prognosis, the method comprising: (A) detecting at least one member of the MMP D group before treatment; and (B) detecting at least one member of the MMP D group before and after treatment. [Item 146] A method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, comprising the steps of: (A) detecting at least one of the MMP D group before treatment; and (B) detecting at least one of the MMP D group before and after treatment in a sample obtained from the subject; and calculating an index for predicting the effect of treatment or prevention or prognosis of the T-cell-related disease in the subject from the value of at least one of the MMP D group (A) before treatment and the value of at least one of the MMP D group (B) before and after treatment.[Item 147] A method for predicting the effect of cancer treatment or predicting prognosis in a subject, comprising the steps of (A) detecting at least one of the MMP D group in a sample obtained from the subject before treatment, and (B) detecting at least one of the MMP D group before and after treatment, and calculating an index relating to the prediction of the effect of cancer treatment or prevention or prediction of prognosis in the subject from the value of the (A) at least one of the MMP D group before treatment and the value of the (B) at least one of the MMP D group before and after treatment. [Item 148] The method of any one of items 144 to 147, comprising one or more features of any one of items 27 to 143. [Item 149] The agent, element, composition, or combination according to any one of the preceding items, which is a diagnostic agent, diagnostic element, or reagent. [Item 150] A kit for use in predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapeutic or preventive) of a T-cell-related disease, comprising the agent, element, or composition of any one of the preceding items, characterized by: (A) detecting at least one member of the MMP D group before treatment; and (B) detecting at least one member of the MMP D group, or a combination thereof, before and after treatment, and a substance used for detection using the agent, element, or composition. [Item 151] A kit for use in predicting the effect of cancer treatment or prevention or prognosis, comprising the agent, element, or composition of any one of the preceding items, characterized by: (A) detecting at least one member of the MMP D group before treatment; and (B) detecting at least one member of the MMP D group, or a combination thereof, before and after treatment, and a substance used for detection using the agent, element, or composition. [Item 152] The kit of Item 150 or 151, further comprising any one or more features of Items 1 to 149.[Item 153] A system for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T cell-related disease, comprising: (A) a factor that interacts with at least one member of the MMP D group before treatment; (B) a factor that interacts with at least one member of the MMP D group before and after treatment, or a combination thereof; a substance used for detection using the agent, element, or composition; an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. [Item 154] A system for predicting the effect of cancer treatment or predicting prognosis, comprising: (A) a factor that interacts with at least one member of the MMP D group before treatment; (B) a factor that interacts with at least one member of the MMP D group before and after treatment, or a factor that interacts with a combination thereof; a substance used for detection using the agent, element, or composition; an interaction part that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. [Item 155] The system according to Item 153 or 154, further comprising one or more features of any one of Items 1 to 152. [Item 156] A combination of biomarkers (a) and (b) below, for predicting the therapeutic effect of an immune checkpoint inhibitor: (a) bsPD-L1 or at least one member of the MMP D group; and (b) at least one member of the MMP A group. [Item 157] Use of a combination of the following biomarkers (a) and (b) to predict the therapeutic effect of an immune checkpoint inhibitor in cancer: (a) bsPD-L1 and / or MMP13; (b) MMP3 and / or MMP13.[Item 158] A method for predicting or assisting in the prediction of the therapeutic effect of an immune checkpoint inhibitor, comprising the steps of measuring the concentrations of the following biomarkers (a) and (b) in biological samples obtained before and after treatment: (a) the concentration of bsPD-L1 and / or MMP13 in the biological sample obtained before treatment; and (b) the concentration of MMP3 and / or MMP13 in the biological sample obtained before and after treatment. [Item 159] The method of any one of the above items, in which the therapeutic effect of an immune checkpoint inhibitor is predicted to be high if the biological sample obtained before treatment is positive for bsPD-L1 and / or MMP13 and the MMP3 and / or MMP13 concentrations in the biological sample before and after treatment decrease. [Item 160] The method of any one of the above items, in which the therapeutic effect of an immune checkpoint inhibitor is predicted to be low if the biological sample obtained before treatment is positive for bsPD-L1 and / or MMP13 and the MMP3 and / or MMP13 concentrations in the biological sample increase before and after treatment. [Item 161] A method for stratifying subjects with regard to their sensitivity to treatment with an immune checkpoint inhibitor, the method comprising measuring the concentration of bsPD-1 and / or MMP13 in a biological sample obtained from the subject before treatment. [Item 162] The method of any one of the above items, further comprising obtaining biological samples from the subject before and after treatment, and associating a lower concentration of MMP3 and / or MMP13 in the biological sample after treatment than that before treatment with an immune checkpoint inhibitor responder. [Item 163] The method of any one of the above items, further comprising obtaining biological samples from the subject before and after treatment, and associating a higher concentration of MMP3 and / or MMP13 in the biological sample after treatment than that before treatment with an immune checkpoint inhibitor non-responder. [Item 164] A diagnostic reagent composition for diagnosing the therapeutic effect of an immune checkpoint inhibitor, comprising the following (a) and (b): (a) a means capable of detecting bsPD-L1 and / or MMP13; and (b) a means capable of detecting MMP3 and / or MMP13.[Item 165] The composition of any one of the above items, wherein the means capable of detecting bsPD-L1 and / or MMP13 comprises an antibody that specifically binds to bsPD-L1, and the means capable of detecting MMP3 and / or MMP13 comprises an antibody that specifically binds to MMP3. [Item 166] A combination of the following biomarkers (a) and (b) for predicting the therapeutic effect of an immune checkpoint inhibitor: (a) bsPD-L1; (b) at least one of MMP A. [Item 167] Use of the combination of the following biomarkers (a) and (b) for predicting the therapeutic effect of an immune checkpoint inhibitor in cancer: (a) bsPD-L1; (b) MMP3. [Item 168] A method for predicting or assisting in the prediction of the therapeutic effect of an immune checkpoint inhibitor, comprising the steps of using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (a) and (b) in the biological samples: (a) the bsPD-L1 concentration in the biological sample obtained before treatment; (b) the MMP3 concentration in the biological sample obtained before and after treatment. [Item 169] The method of any one of the above items, which predicts that the therapeutic effect of the immune checkpoint inhibitor will be high if the biological sample obtained before treatment is positive for bsPD-L1 and the MMP3 concentration in the biological sample decreases before and after treatment. [Item 170] The method of any one of the above items, which predicts that the therapeutic effect of the immune checkpoint inhibitor will be low if the biological sample obtained before treatment is positive for bsPD-L1 and the MMP3 concentration in the biological sample increases before and after treatment. [Item 171] A method for stratifying subjects with regard to their sensitivity to treatment with an immune checkpoint inhibitor, the method comprising a step of measuring the concentration of bsPD-1 in a biological sample obtained from the subject before treatment. [Item 172] The method of any one of the above items, further comprising obtaining biological samples from the subject before and after treatment, and associating a lower MMP3 concentration in the biological sample after treatment than that before treatment with an immune checkpoint inhibitor responder. [Item 173] The method of any one of the above items, further comprising obtaining biological samples from the subject before and after treatment, and associating a higher MMP3 concentration in the biological sample after treatment than that before treatment with an immune checkpoint inhibitor non-responder.[Item 174] A diagnostic reagent composition for diagnosing the therapeutic effect of an immune checkpoint inhibitor, comprising: (a) a means for detecting bsPD-L1, and (b) a means for detecting MMP3. [Item 175] The composition according to any one of the above items, wherein the means for detecting bsPD-L1 comprises an antibody that specifically binds to bsPD-L1, and the means for detecting MMP3 comprises an antibody that specifically binds to MMP3. [Item 176] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the above items, wherein the prediction uses values ​​before treatment and / or after the start of treatment in the case of cancer, and if measurement before the start of treatment is not possible, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​are used, and if measurement before the start of treatment is not possible, they are used, and [Item 177] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein, when MMP A group, MMP B group, or MMP C group is used for the prediction, in the case of cancer, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​can be substituted at multiple points after the start of treatment; and in the case of T-cell-related diseases other than cancer, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​can be substituted at multiple points after the start of treatment.[Item 178] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein the prediction uses an MMP D group: (1) in the case of cancer, a pre-treatment value is used as an indicator of immune function, and if it cannot be measured before the start of treatment, a value after the start of treatment can be substituted; and a value before and / or after the start of treatment is used as an indicator of disease progression, but if it cannot be measured before the start of treatment, multiple points after the start of treatment can be substituted; and (2) in the case of T-cell-related disease, a value before and / or after the start of treatment is used as an indicator of immune function, and if it cannot be measured before the start of treatment, multiple points after the start of treatment can be substituted; and a value before and / or after the start of treatment is used as an indicator of disease progression, and if it cannot be measured before the start of treatment, multiple points after the start of treatment can be substituted. [Item 179] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein the prediction is: (1) in the case of cancer, using MMP13 (or bsPD-L1 as a surrogate) as an indicator of immune function, pre-treatment values ​​are used, and if measurement before the start of treatment cannot be performed, values ​​after the start of treatment can be used as a substitute; using MMP3 and MMP13 as indicators of disease progression, pre-treatment and / or values ​​after the start of treatment are used, and if measurement before the start of treatment cannot be performed, values ​​after the start of treatment can be used as a substitute; (2) in the case of T-cell-related diseases, using MMP13 (or bsPD-L1 as a surrogate) as an indicator of immune function, pre-treatment and / or values ​​after the start of treatment are used, and if measurement before the start of treatment cannot be performed, values ​​after the start of treatment can be used as a substitute; using MMP3 and MMP13 as indicators of disease progression, pre-treatment and / or values ​​after the start of treatment are used, and if measurement before the start of treatment cannot be performed, values ​​after the start of treatment can be used as a substitute. [Item 180] The combination, agent, element, composition, system, kit, biomarker or method according to any one of the above items, wherein the prediction is determined as shown in the table below:

[0009]

[0010]

[0011]

[0012]

[0013] [Item 181] The combination according to any one of the above items, wherein (1) the detection of the host T-cell immunocompetence marker is performed before treatment, and (2) the detection of the disease status diagnostic marker utilizes changes in values ​​during treatment, and (F) the host T-cell immunocompetence marker in (1) is MMP13, and the disease status diagnostic marker in (2) is MMP3 and MMP13. [Item 182] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the above items, wherein in the case of cancer, (1) and (2) use values ​​before treatment and / or after the start of treatment, and if measurements before the start of treatment are not possible, they are substituted at multiple points after the start of treatment, and in the case of a T-cell-related disease other than cancer, (1) and (2) use values ​​before treatment and / or after the start of treatment, and if measurements before the start of treatment are not possible, they are substituted at multiple points after the start of treatment. [Item 183] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein, when MMP A group, MMP B group, or MMP C group is used for the prediction, in the case of cancer, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​can be substituted at multiple points after the start of treatment; and in the case of T-cell-related diseases other than cancer, values ​​before treatment and / or after the start of treatment are used, and if measurement before the start of treatment is not possible, values ​​can be substituted at multiple points after the start of treatment. [Item 184] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein the prediction uses an MMP D group: (1) in the case of cancer, a pre-treatment value is used as an indicator of immune function, and if measurement before the start of treatment is not possible, a value after the start of treatment can be substituted; and a value before treatment and / or after the start of treatment is used as an indicator of disease progression, but if measurement before the start of treatment is not possible, multiple points after the start of treatment can be substituted; and (2) in the case of T-cell-related disease, a value before treatment and / or after the start of treatment is used as an indicator of immune function, and if measurement before the start of treatment is not possible, multiple points after the start of treatment can be substituted; and a value before treatment and / or after the start of treatment is used as an indicator of disease progression, and if measurement before the start of treatment is not possible, multiple points after the start of treatment can be substituted.[Item 185] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein the prediction is: (1) in the case of cancer, using MMP13 (or bsPD-L1 as a surrogate) as an indicator of immune function, a pre-treatment value is used, and if measurement before the start of treatment cannot be performed, a post-treatment value can be used as a substitute; using MMP3 and MMP13 as indicators of disease progression, a pre-treatment and / or post-treatment value is used, and if measurement before the start of treatment cannot be performed, a multiple-point value is used as a substitute; (2) in the case of T-cell-related diseases, using MMP13 (or bsPD-L1 as a surrogate) as an indicator of immune function, a pre-treatment and / or post-treatment value is used, and if measurement before the start of treatment cannot be performed, a multiple-point value is used as a substitute; using MMP3 and MMP13 as indicators of disease progression, a pre-treatment and / or post-treatment value is used, and if measurement before the start of treatment cannot be performed, a multiple-point value is used as a substitute; [Item 186] The combination, agent, element, composition, system, kit, biomarker or method according to any one of the above items, wherein the prediction is determined according to the following table:

[0014]

[0015] [Item 187] The combination, agent, element, composition, system, kit, biomarker, or method according to any one of the preceding items, wherein the prediction is determined according to the following table:

[0016]

[0017]

[0018]

[0019]

[0020] The present disclosure also provides the following: [Item 188] A biomarker comprising at least one member of the matrix metalloproteinase (MMP) B group for predicting the pathology, severity, prognosis, and / or therapeutic or preventive effects of a T cell-related disease. [Item 189] The biomarker according to the above items, wherein the biomarker comprises at least one or two members of the MMP C group, preferably MMP3 and MMP13. [Item 190] The biomarker according to any one of the above items, which is used to evaluate T cell immune function and / or tissue damage in a subject, to predict cancer invasion, metastasis, or recurrence and / or, in the case of cancer, to predict the therapeutic effect of treatments including immunotherapy including immune checkpoint inhibitors, surgery, radiation therapy, chemotherapy, and molecular targeted drugs, and combinations thereof, or, in the case of T cell-related diseases, to predict the therapeutic effect of treatments including immunomodulators (including anti-inflammatory drugs (including biologics), immunosuppressants (steroids, etc.), immunostimulants (including immune checkpoint inhibitors), etc.). [Item 191] An agent, element, or composition for use in predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T cell-related disease, comprising a factor that interacts with at least one of the biomarkers described in any one of the above items. [Item 192] A kit for use in predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T cell-related disease, comprising the agent, element, or composition described in any one of the above items and a substance used for detection using the agent, element, or composition. [Item 193] A system for use in predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T cell-related disease, comprising the agent, element, or composition described in any one of the above items, a substance used for detection using the agent, element, or composition, an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means used to detect a signal resulting from the agent, element, or composition.[Item 194] A method for assisting in prediction of the pathology, severity, prognosis, and / or therapeutic or preventive effects of a T cell-related disease, the method comprising the step of detecting at least one of the biomarkers described in any one of the above items in a sample obtained from the subject. [Item 195] A method for predicting the pathology, severity, prognosis, and / or therapeutic or preventive effects of a T cell-related disease in a subject, the method comprising the steps of detecting at least one of the biomarkers described in any one of the above items in a sample obtained from the subject, and calculating an index related to the prediction of the pathology, severity, prognosis, and / or therapeutic or preventive effects of the T cell-related disease in the subject from the value of at least one of the biomarkers. [Item 196] A combination of (1) a factor that interacts with a host T cell immune competence marker, and (2) a factor that interacts with a disease progression diagnostic marker. [Item 197] A combination of (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker, used to predict the pathology, severity, prognosis, and / or therapeutic or preventive effects of a T-cell-related disease. [Item 198] The combination according to any one of the above items, wherein (1) the host T-cell immunocompetence marker comprises at least one selected from the group consisting of bsPD-L1, MMP13, and interferon-γ. [Item 199] The combination according to any one of the above items, wherein (2) the disease progression diagnostic marker comprises at least one of the biomarkers described in any one of the above items. [Item 200] The combination according to any one of the above items, wherein the detection of (1) the host T-cell immunocompetence marker and / or (2) the disease progression diagnostic marker utilizes at least one or two of values ​​obtained before and / or after the start of treatment. [Item 201] The combination according to any one of the above items, wherein (1) the host T-cell immunocompetence marker is bsPD-L1 or MMP13. [Item 202] (2) The combination according to any one of the above items, wherein the disease progression diagnostic marker is MMP3 and / or MMP13.[Item 203] The combination according to any one of the above items, wherein the detection of (1) a host T-cell immunocompetence marker and / or (2) a disease status diagnostic marker utilizes at least one or two of values ​​obtained before and / or after the start of treatment, and wherein the host T-cell immunocompetence marker of (1) is bsPD-L1 or MMP 13, and the disease status diagnostic marker of (2) is MMP3 and / or MMP 13. [Item 204] An agent, device, or composition for use in predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T-cell-related disease, comprising the combination of factors according to any one of the above items, or a kit comprising the agent, device, or composition and a substance used for detection using the agent, device, or composition. [Item 205] A system for use in predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T-cell-related disease, comprising the agent, element, or composition according to any one of the above items, a substance used for detection using the agent, element, or composition, an interaction part that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means used to detect a signal resulting from the agent, element, or composition. [Item 206] A method for predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of a T-cell-related disease in a subject, the method comprising the steps of detecting (1) a host T-cell immune marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index for predicting the pathology, severity, prognosis, and / or therapeutic or preventive effect of the T-cell-related disease in the subject from the values ​​of the (1) host T-cell immune marker and the (2) disease progression diagnostic marker. [Item 207] A method for stratifying a subject regarding their sensitivity to treatment with an immune checkpoint inhibitor, the method comprising a step of measuring at least one or two of bsPD-L1 and / or MMP B in a biological sample obtained from the subject, or a method, kit, system, or combination thereof according to any one of the above items used for the method.[Item 208] The method, agent, element, composition, kit, system, or combination according to any one of the preceding items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be low when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment. [Item 209] The method, agent, element, composition, kit, system, or combination according to any one of the preceding items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be high when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment.

[0021] The present disclosure also provides the following. [Item A1] An agent or composition for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell related diseases, or for diagnosing the pathology, severity and / or prognosis, comprising at least one factor that interacts with a disease diagnostic marker, wherein the disease diagnostic marker comprises at least one member of the MMP C group. [Item A2] The agent or composition according to any one of the above items, wherein the disease diagnostic marker is MMP13. [Item A3] The agent or composition according to any one of the above items, wherein the disease diagnostic marker is MMP3. [Item A4] A combination of at least one factor that interacts with a disease diagnostic marker and at least one factor that interacts with a host T-cell immune function marker, for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell related diseases, or for diagnosing the pathology, severity and / or prognosis. [Item A5] The combination according to any one of the above items, wherein the disease diagnostic marker comprises MMP13 or MMP3, and the host T-cell immune function marker comprises MMP13 or bsPDL1. [Item A6] The agent or composition according to any one of the above items, or the combination according to any one of the above items, for predicting the efficacy of ICI. [Item A7] A kit for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell-related diseases, or for diagnosing the pathology, severity, and / or prognosis, comprising a factor that interacts with at least one selected from the group consisting of disease diagnostic markers, wherein the disease diagnostic marker is an MMP C group. [Item A8] The kit according to any one of the above items, wherein the MMP C group includes MMP13. [Item A9] The kit according to any one of the above items, wherein the MMP C group includes MMP3. [Item A10] A kit for predicting the therapeutic and / or preventive effects of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising at least one factor that interacts with a disease progression diagnostic marker and at least one factor that interacts with a host T-cell immune function marker.[Item A11] The kit according to any one of the above items, wherein the disease diagnostic marker includes MMP13 or MMP3, and the host T-cell immune function marker includes MMP13 or bsPDL1. [Item A12] The kit according to any one of the above items, for predicting the efficacy of ICI. [Item A13] The agent or composition according to any one of the above items, the combination according to any one of the above items, or the kit according to any one of the above items, wherein the treatment includes chemotherapy, radiation therapy, molecular targeted drugs, proton beams, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof. [Item A14] The agent or composition according to any one of the above items, the combination according to any one of the above items, or the kit according to any one of the above items, wherein the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence. [Item A15] The agent, composition, combination, or kit according to any one of the preceding items, wherein the factor is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, a polypeptide, a fragment thereof, a combination thereof, and a mass spectrometry element. [Item A15A] The agent, composition, combination, or kit according to any one of the preceding items, wherein, when two or more factors are included, the factors are each independently selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, a polypeptide, a fragment thereof, and a combination thereof. [Item A16] The agent or composition according to any one of the preceding items, the combination according to any one of the preceding items, or the kit according to any one of the preceding items, for stratifying cancer patients into a group that responds well to ICI treatment and a group whose cancer worsens with ICI treatment by measuring the host T-cell immune function marker before treatment and the disease progression diagnostic marker during treatment. [Item A17] The agent, composition, combination, or kit according to any one of the preceding items, wherein the host T cell immune function marker is MMP13 and / or bsPDL1, and the disease progression diagnostic marker is MMP3 and / or MMP13.[Item A18] The agent, composition, combination, or kit according to any one of the above items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be low when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment. [Item A19] The agent, composition, combination, or kit according to any one of the above items, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be high when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment. [Item A19A] The agent, composition, combination, or kit according to any one of the above items, wherein, when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, (A) the therapeutic effect of the immune checkpoint inhibitor is predicted to be low if the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are higher than those before treatment, and (B) the therapeutic effect of the immune checkpoint inhibitor is predicted to be high if the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are lower than those before treatment. [Item A20] The agent, composition, combination, or kit according to any one of the above items, wherein the cancer and / or T-cell-related disease includes at least one of lung cancer and non-small cell lung cancer.

[0022] The present disclosure also provides the following: [Item A21] A method for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathological condition, severity, and / or prognosis, comprising measuring at least one disease diagnostic marker in a subject, wherein the disease diagnostic marker comprises at least one member of the MMP C group. [Item A22] The method according to any one of the above items, wherein the disease diagnostic marker is MMP13. [Item A23] The method according to any one of the above items, wherein the disease diagnostic marker is MMP3. [Item A24] The method according to any one of the above items, further comprising measuring at least one host T-cell immune function marker. [Item A25] The method according to any one of the above items, wherein the disease diagnostic marker comprises MMP13 or MMP3. [Item A26] The method according to any one of the above items, wherein the host T-cell immune function marker comprises MMP13 or bsPDL1. [Item A27] The method of any one of the above items, wherein the treatment includes chemotherapy, radiation therapy, molecular targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof. [Item A28] The method of any one of the above items, wherein the prediction includes prediction of the effect of ICI. [Item A29] The method of any one of the above items, wherein the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence. [Item A30] The method of any one of the above items, wherein the measurement is performed using a factor that interacts with the marker. [Item A31] The method of any one of the above items, wherein the factor is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, a polypeptide, a fragment thereof, and a combination thereof. [Item A32] The method of any one of the above items, wherein the host T-cell immune function marker is measured before treatment and the disease progression diagnostic marker is measured during treatment, thereby stratifying cancer patients into a group that responds well to ICI and a group whose cancer worsens with ICI treatment.[Item A33] The method according to any one of the above items, wherein the therapeutic effect of an immune checkpoint inhibitor is predicted to be low when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment. [Item A34] The method according to any one of the above items, wherein the therapeutic effect of an immune checkpoint inhibitor is predicted to be high when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment. [Item A34A] The method according to any one of the above items, wherein, when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, (A) predicting a low therapeutic effect of an immune checkpoint inhibitor if the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment, or (B) predicting a high therapeutic effect of an immune checkpoint inhibitor if the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment. [Item A35] The method according to any one of the above items, wherein the cancer and / or T-cell-related disease includes at least one of lung cancer and non-small cell lung cancer. [Item A36] A method for treating and / or preventing cancer and / or T-cell-related disease, comprising performing a diagnosis according to the method of any one of the above items and administering a therapeutic treatment and / or preventive treatment for cancer and / or T-cell-related disease to the subject based on the prediction. [Item A37] The method for treating and / or preventing cancer and / or T-cell-related diseases according to any one of the preceding items, wherein the treatment comprises ICI. [Item A38] The method for treating and / or preventing cancer and / or T-cell-related diseases according to any one of the preceding items, wherein the treatment comprises chemotherapy, radiation therapy, molecular targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof.

[0023] It is contemplated that the present disclosure may provide one or more of the above-described features in combinations other than those explicitly stated. Still further embodiments and advantages of the present disclosure will be recognized by those skilled in the art upon reading and understanding the following detailed description, if necessary.

[0024] The present disclosure makes it possible to predict the pathology, severity, prognosis, and / or effectiveness of treatment (e.g., therapeutic or preventive) of T cell-related diseases. In particular, it makes it possible to predict the effectiveness of cancer prevention and treatment using not only ICI but also various other treatments. Therefore, for example, it becomes possible to identify cases in which ICI is ineffective, select a therapeutic agent appropriate for the patient, and create a drug administration plan for immunotherapy including immunomodulatory drugs (including anti-inflammatory drugs (including biologics), immunosuppressants (steroids, etc.), immunostimulants (including immune checkpoint inhibitors), etc.). This method is applicable to various types of cancer and is expected to have a significant impact on the market.

[0025] Figure 1 shows the detection of MMPs and bsPD-L1 in the plasma of gastric cancer (GC) patients and the discrepancy between blood bsPD-L1 levels and tumor PD-L1 expression in GC patients. The concentrations of MMPs and bsPD-L1s in plasma samples from 117 GC patients were analyzed by ELISA (A). The correlation between bsPD-L1 and MMP concentrations in GC patients (n=117) (B). r indicates the correlation coefficient. Representative images of H&E staining and anti-PD-L1 immunohistochemical staining in tumor tissues obtained from GC patients with low (CPS<5), intermediate (5≦CPS<10), and high (CPS≧10) PD-L1 expression (C) are shown. The original magnification is 20x. The scale bar represents 100 μm. Nuclei were counterstained with hematoxylin (blue). The correlation between bsPD-L1 levels and CPS in GC patients (n=25) is shown (D). Figure 2 shows a comparison of inflammatory markers and IFN-γ levels between bsPD-L1-positive and bsPD-L1-negative patients. Comparison of neutrophil count (A), lymphocyte count (B), monocyte count (C), eosinophil count (D), white blood cell count (E), platelet count (F), neutrophil-to-lymphocyte ratio (G), C-reactive protein (H), IFN-γ (I), and MMPs (J-L) levels between bsPD-L1-positive (n=17) and bsPD-L1-negative (n=100) GC patients. Horizontal lines represent mean values. Statistical significance was calculated using Student's t-test (A, B, E) or Mann-Whitney U test (C, D, F, G, H, I, J, K, L). **p<0.01; ***p<0.001; ****: p<0.0001; ns: not significant. Figure 3 shows histological analysis of T cell infiltration and extracellular matrix in tumor tissues from GC patients. Serial sections of tumor tissues from bsPD-L1-positive (n=12) or bsPD-L1-negative (n=13) GC patients were analyzed using H&E, EMG, or anti-CD3 immunohistochemical staining. Representative images are shown at low magnification (0.5x; A) and high magnification (20x; B); scale bars indicate 5 mm (A) and 100 μm (B), respectively. For immunohistochemical staining, tumor areas, T cell cluster areas, and B cell follicles are indicated by red, green, and blue lines, respectively. For EMG staining, collagen fibers, elastic fibers, red blood cells, and muscle are indicated by green, dark purple, orange, and red, respectively. Figure 4 shows that the number of tumor-infiltrating T lymphocytes was high in tumor tissues of bsPD-L1-positive GC patients.Percentage of T cell cluster area within the tumor area (A) and CD3 within the total viable cell population in bsPD-L1-positive (n = 12) and bsPD-L1-negative (n = 13) patients. ＋ Comparison of the proportion of T cells (B) and CD3 T cells (C) in the total viable cell population in the mucosal and submucosal layers. ＋Comparison of the proportion of T cells (C, left, bsPD-L1-negative patient; C, right, bsPD-L1-positive patient). Representative images of tumor tissues obtained from a bsPD-L1-positive patient and a bsPD-L1-negative patient (D). Original magnification: 20x. Scale bar indicates 100 μm. Yellow circles indicate CD3-positive nuclei, and purple circles indicate CD3-negative nuclei. Statistical significance was calculated using unpaired (A and B) or paired (C) Student's t-test. *p<0.05; ***p<0.0001; ns indicates not significant. Figure 5 shows the identification of GC patients at high risk of recurrence. Representative images of EMG staining in tumor tissues obtained from the bsPD-L1-positive MMP13-high group and the bsPD-L1-positive MMP13-low group (A). Original magnification: 20x. Scale bar indicates 100 μm. Collagen fibers are shown in green, and red blood cells are shown in orange. Asterisks and arrowheads indicate hemorrhage and blood vessels, respectively. ROC curve analysis of MMP3, MMP9, and MMP13 levels to predict DFS in bsPD-L1-positive patients (B). Pie charts (C), OS (D), and the proportion of patients who progressed two years after surgery (E) were shown for GC patients in the bsPD-L1-negative group (n=100), the bsPD-L1-positive MMP13-low group (n=12), and the bsPD-L1-positive MMP13-high group (n=5). Figure 6-1 shows the detection of MMPs and bsPD-L1 in the pretreatment plasma of NSCLC patients. (A) Pretreatment bsPD-L1 and MMP blood concentrations in 72 NSCLC patients and (B) the correlation between pretreatment bsPD-L1 and MMP levels in 72 NSCLC patients are shown. Figure 6-2 shows the changes in bsPD-L1 and MMP levels during ICI treatment in NSCLC patients. (C) The changes in bsPD-L1 and MMP levels after 2 months of ICI administration in 72 NSCLC patients are shown. Figure 7 shows the identification of NSCLC patients who were refractory to ICI treatment. Each panel shows: (A) PFS and OS in bsPD-L1-positive (n=16) and bsPD-L1-negative (n=56) NSCLC patients. (B) Comparison of PFS and OS between the MMP3-increased group (n=4) and the MMP3-decreased group (n=12) in bsPD-L1-positive patients. (C) Comparison of PFS and OS between the MMP9-increased group (n=8) and the MMP9-decreased group (n=8) in bsPD-L1-positive patients.(D) Comparison of PFS and OS between the MMP13 increase group (n=7) and the MMP13 decrease group (n=9) in bsPD-L1-positive patients. (E) PFS and OS between the MMP3 increase / MMP13 increase group (n=7), the MMP3 increase / MMP13 decrease group (n=5), the MMP3 decrease / MMP13 increase group (n=2), and the MMP3 decrease / MMP13 decrease group (n=2) in bsPD-L1-positive patients. (F) Comparison of PFS and OS between the (MMP3 and MMP13) increase group (n=7) and the (MMP3 or MMP13) decrease group (n=9) in bsPD-L1-positive patients. (G) PFS and OS in the bsPD-L1 negative group (n=56), the bsPD-L1 positive (MMP3 and MMP13) increased group (n=7), and the bsPD-L1 positive (MMP3 or MMP13) decreased group (n=9). (H) PFS and OS in the MMP13 low group (n=55), the MMP13 high (MMP3 and MMP13) increased group (n=6), and the MMP13 high (MMP3 or MMP13) decreased group (n=11). (I) PFS and OS in NSCLC patients based on TPS (≥50, n=28 vs. <50, n=44). (J) PFS and OS in NSCLC patients based on CRP levels (≥10 mg / L, n=8 vs. <10 mg / L, n=64). (K) PFS and OS of NSCLC patients based on bsPD-L1 positive (MMP3 and MMP13) elevated status (Yes, n=7 vs. No, n=65). (L) PFS and OS of NSCLC patients based on MMP13 elevated (MMP3 and MMP13) status (Yes, n=6 vs. No, n=66). Figure 8 shows the results of H&E, EMG, and anti-CD3 immunohistochemical staining of serial sections of gastric cancer tissue from patient 86. The original magnification is 20x. The scale bar represents 100 μm. Figure 9 compares the levels of inflammatory markers between bsPD-L1 positive and bsPD-L1 negative groups to assess the immunological status of NSCLC patients. Comparison of neutrophil count (A), lymphocyte count (B), monocyte count (C), eosinophil count (D), white blood cell count (E), platelet count (F), neutrophil-to-lymphocyte ratio (G), C-reactive protein (H), and MMPs (I-K) levels between bsPD-L1-positive (n=16) and bsPD-L1-negative (n=56) NSCLC patients. Horizontal lines represent mean values.Statistical significance was calculated using Student's t-test (A, B, E) or Mann-Whitney U test (C, D, F, G, H, I, J, K). *p<0.05; ****: p<0.0001; ns: not significant.

[0026] Throughout this specification, singular expressions should be understood to include the plural concept unless otherwise specified. Thus, singular articles (e.g., "a," "an," "the," etc. in English) should be understood to include the plural concept unless otherwise specified. Furthermore, it should be understood that terms used in this specification are used in the sense commonly used in the art unless otherwise specified. Therefore, unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. In case of conflict, the present specification (including definitions) will control.

[0027] (Definitions) We first explain the terms and general techniques used in this disclosure.

[0028] As used herein, the term "T cell-associated disease" refers to any disease associated with T cells. T cell-associated diseases include diseases or conditions primarily driven by T cell responses to self-antigens, diseases or conditions primarily driven by T cell responses to foreign antigens, and conditions associated with immunomodulatory drugs. Diseases or pathological conditions primarily driven by T cell responses to autoantigens include neoplasms (cancer); autoimmune diseases and related diseases (rheumatoid arthritis, polymyalgia rheumatica, ankylosing spondylitis, relapsing polychondritis, systemic lupus erythematosus, systemic sclerosis, dermatomyositis / polymyositis, Sjogren's syndrome, antiphospholipid antibody syndrome, ulcerative colitis, Crohn's disease, Takayasu's arteritis, giant cell arteritis, polyarteritis nodosa, ANCA-associated vasculitis, malignant rheumatoid arthritis / rheumatoid vasculitis, granulomatosis with polyangiitis, eosinophilic granulomatosis with polyangiitis, multiple sclerosis, neuromyelitis optica, Guillain-Barré syndrome, Behcet's disease, and adult Still's disease). Diseases or conditions primarily driven by T cell responses to foreign antigens include infectious diseases and vaccines therefor (HBV, HCV, influenza virus, measles virus, mumps, SARS coronavirus, novel coronavirus, cytomegalovirus, varicella-zoster virus, herpes simplex virus); graft-versus-host disease (GVHD); etc. Conditions associated with immunomodulatory drugs include conditions associated with immunostimulants (including immune checkpoint inhibitors), immunosuppressants (including steroids, alkylating agents, antimetabolites, and intracellular signaling inhibitors), biological agents, etc.

[0029] As used herein, "cancer" is used interchangeably with "carcinoma," "neoplasm," etc., and is interpreted in the broadest sense to refer to any cancer caused by the growth of malignant neoplastic cells, such as tumors, neoplasms, carcinomas, sarcomas, leukemias, and lymphomas. "Solid (tumor) cancers" are cancers that involve an abnormal mass of tissue, e.g., sarcomas, carcinomas, and lymphomas. "Hematologic cancers" or "liquid cancers," used interchangeably herein, are cancers present in bodily fluids, e.g., lymphomas and leukemias. Cancers that may be targeted by the present disclosure include carcinomas, squamous cell carcinomas (cancers of the cervix, eyelid, conjunctiva, vagina, lung, oral cavity, skin, bladder, tongue, larynx, esophagus, etc.), adenocarcinomas (cancers of the prostate, small intestine, endometrium, cervix, colon, lung, pancreas, esophagus, rectum, uterus, stomach, breast, ovary, etc.), and also include sarcomas (e.g., myogenic sarcoma), leukemia, neuroma, melanoma, and lymphoma, specifically lung cancer (e.g., non-small cell lung cancer (NSCLC)), bone cancer, pancreatic cancer, skin cancer, head and neck cancer, and cutaneous or intraocular melanoma. The cancer may be from, but is not limited to, chromosomes, uterine cancer, ovarian cancer, rectal cancer, cancer of the anal region, stomach cancer, colon cancer, breast cancer, fallopian tube cancer, endometrial cancer, cervical cancer, vaginal cancer, vulvar cancer, Hodgkin's disease, esophageal cancer, small intestine cancer, cancer of the endocrine system, thyroid cancer, parathyroid cancer, adrenal gland cancer, soft tissue sarcoma, urethral cancer, penile cancer, prostate cancer, chronic or acute leukemia, lymphocytic lymphoma, bladder cancer, cancer of the kidney or ureter, renal cell carcinoma, renal pelvis cancer, central nervous system (CNS) neoplasms, primary CNS lymphoma, spinal axis tumor, brain stem glioma, or pituitary adenoma, and combinations thereof.

[0030] As used herein, the term "disease" is broadly defined to refer to a state in which normal mental or physical functions are disrupted. In this specification, disorders and the like are also encompassed.

[0031] As used herein, the term "pathological condition" refers to a disease state.

[0032] As used herein, the term "treat" (or grammatical equivalents) refers to any action that directly or indirectly affects a condition (including disease) or a pre-condition (including a healthy state and pre-symptomatic conditions in traditional Chinese medicine) that precedes that condition, and includes both treatment and prevention. Treatments for cancer include, but are not limited to, surgery, radiation therapy, proton therapy, chemotherapy, molecularly targeted drugs, immunotherapy (also known as cancer immunotherapy, including but not limited to immune checkpoint inhibitors and CAR T cell therapy), and any combinations thereof (including any homogeneous or heterogeneous combinations of two or more). In the case of T-cell-related diseases, treatments include, but are not limited to, immunomodulatory agents (anti-inflammatory agents (including biologics)), immunosuppressants (such as steroids), immunostimulants (including immune checkpoint inhibitors), and any combinations thereof (including any homogeneous or heterogeneous combinations of two or more).

[0033] As used herein, "therapy" (or grammatically equivalent terms) refers to preventing, preferably maintaining the status quo, more preferably alleviating, and even more preferably eliminating, a disease or disorder from worsening when that condition has developed; if such an effect can be achieved, it may be possible to exert an effect of improving symptoms of the patient's disease or one or more symptoms associated with the disease, or an additional preventive effect. Preliminary diagnosis followed by appropriate treatment is called "companion therapy," and diagnostic agents used for this purpose are sometimes called "companion diagnostic agents."

[0034] As used herein, the term "prevention" (and grammatically equivalent terms) refers to preventing a certain disease or disorder from becoming a certain state before it occurs. Diagnosis can be performed using the agent, element, or composition of the present disclosure, and, if necessary, the agent, element, or composition of the present disclosure can be used to prevent, for example, cancer, or to take preventive measures.

[0035] As used herein, "diagnosis" (or grammatically equivalent terms) refers to identifying various parameters (e.g., the amount or properties of proteins in the body, or the number of gene copies, the presence or absence of substitutions) related to a condition (e.g., a disease or disorder) in a subject and determining the current or future state of such a condition. Using the methods, compositions, and systems disclosed herein, the internal state can be examined, and such information can be used to select various parameters, such as the condition in the subject, and the treatment or prophylactic formulation or method to be administered. In the narrow sense, "diagnosis" herein refers to assessing the current state, but in a broad sense, it also includes "early diagnosis," "predictive diagnosis," "preliminary diagnosis," etc. The diagnostic method disclosed herein is industrially useful because, in principle, it can utilize tissues excreted by the body and can be performed independently of medical professionals such as physicians. To clarify that the method can be performed independently of medical professionals such as physicians, the term "predictive diagnosis, preliminary diagnosis, or diagnosis" is sometimes referred to as "assisting." The technology disclosed herein is applicable to such diagnostic techniques.

[0036] As used herein, "prognosis" (or grammatically equivalent terms) refers to the condition of a patient after a certain treatment or the future condition of a disease or injury, particularly the outlook for such conditions; for example, in the case of cancer, it refers to the reduction in tumor volume, the suppression of tumor growth, the course or outcome of the disease (e.g., presence or absence of recurrence, life or death, etc.) after treatment for the cancer (e.g., ICI, chemotherapy, etc.), and more specifically (but not limited to) the length of survival time and the level of risk of recurrence. Determining prognosis may be, for example, a prediction of the survival time or survival rate after a certain period of time after treatment, and includes making predictions of future conditions and the appropriateness of treatment even during treatment based on measurements made during that treatment.

[0037] As used herein, the term "effect" in terms of treatment, cure, prevention, etc., is to be interpreted in the broadest sense to mean the state of a patient after a treatment or the future state of a disease or injury, particularly the eradication or amelioration of the underlying disorder that is the likely treatment of that state. Efficacy is also to be understood as being achieved by the eradication or amelioration of one or more physiological symptoms associated with the underlying disorder, such that an improvement is observed in the patient, even if the patient may still be afflicted with the underlying disorder.

[0038] As used herein, the term "prediction" is interpreted in the broadest sense and refers to calculating or preliminarily determining the effect or prognosis of a treatment, such as the effect or prognosis of cancer treatment or prevention, as typified by the present disclosure. Prediction can include, for example, predicting the state of a disease (disease stage diagnosis), the speed and degree of recovery (prognosis prediction), and the effect of a drug.

[0039] As used herein, "PD-1" is defined as a protein known as programmed cell death protein 1, which interacts with bsPD-L1 or acts as an antigen (receptor) for detecting this interaction. PD-1 may be derived from a species corresponding to the subject being evaluated, such as human, mouse, rat, rabbit, or horse, and preferably derived from a mammal. To detect interaction with human PD-L1, it is desirable to use PD-1 derived from a mammal, preferably from a human, but this is not limiting. For example, in the case of humans, a protein consisting of 288 amino acid residues identified as Q15116 in UniProtKB Accession may be used. There is no need to be any particular limitation on PD-1, and various types can be used as long as it fulfills this role. PD-1 is a membrane protein expressed on the surface of T cells and the like (JP 5-336973 A, JP 7-291996 A). PD-1 ligands, PD-L1 and PD-L2, have been identified. These molecules bind to PD-1 and suppress T cell function, thereby suppressively modulating the immune system. Furthermore, cancer and virus-infected cells are known to express PD-1 ligands and escape host immune surveillance through binding to PD-1. Among these PD-1 ligands, PD-L1 exists in membrane forms expressed on the cell surface and soluble forms present in the blood. It is known that membrane-type PD-L1 is stabilized and inhibited from degradation by N-glycosylation, increasing its binding ability to PD-1 (LiC Wet al. NatCommun. 2016Aug30;7:12632). Soluble PD-L1 is known to be glycosylated. Drugs developed focusing on PD-1 / PD-L1 signaling include anti-PD-1 antibodies (e.g., nivolumab) and anti-PD-L1 antibodies. These drugs release the brakes on the immune system by inhibiting the immune checkpoint molecule PD-1, thereby enhancing the immune response to cancer and exerting anti-tumor effects.Soluble PD-L1 (hereinafter "sPD-L1"), a protein present in blood, is available as a means for evaluating systemic immune function. Among sPD-L1, there is a bound soluble PD-L1 (PD-1-binding sPD-L1, hereinafter "bsPD-L1") that has high binding affinity to PD-1. The present invention does not intend to exclude any modifications of the PD-1. In other words, PD-1 may be modified or altered in a manner appropriate for each evaluation system, as long as the binding of bsPD-L1 and PD-1, which is the principle of the present invention, can be achieved. While it is preferable to use artificially produced PD-1, this is not intended to be limiting, and biologically derived PD-1 may also be used.

[0040] PD-1 can be artificially produced by known methods, such as by transfecting a PD-1 expression vector into cells, followed by culturing and purifying the cells (see WO2019 / 049974).

[0041] As used herein, "bound soluble PD-L1 (bsPD-L1 / sPD-L1 with PD-1-binding capacity)" refers to a bound form of soluble PD-L1 present in the blood that has high binding capacity to PD-1. Among sPD-L1 present in the blood, there is bsPD-L1, which has high binding capacity to PD-1. In addition, a similar mechanism exists for PD-L1 expressed on membrane surfaces. One aspect of bsPD-L1 is that it undergoes various glycosylation modifications, and its binding capacity to PD-1 changes depending on the site and degree of glycosylation, and its PD-1 binding capacity decreases due to deglycosylation. Thus, one aspect of bsPD-L1 is glycosylated soluble PD-L1. The binding ability of soluble PD-L1 to PD-1 depends on glycosylation, and various evaluations are possible by detecting and quantifying glycosylated PD-L1. However, the evaluation need not be particularly limited as long as it is possible to detect and quantify the binding reaction between PD-1 and bsPD-L1, and can be performed in various configurations or modes. Examples of embodiments of the methods that can be used in the present disclosure include measuring devices and instruments, and auxiliary components and component sets therefor. A representative bsPD-L1 measurement kit is described in WO 2019 / 049974, and is a system for detecting and quantifying bsPD-L1 in a test sample, the system including PD-1 protein, a means for reacting the protein with the test sample, and a means for detecting and quantifying soluble PD-L1 bound to the protein as bsPD-L1. Preferably, the system further includes an anti-PD-L1 antibody, a means for reacting the antibody with the test sample, and a means for detecting and quantifying soluble PD-L1 bound to the antibody. Measurement can typically be performed in the ELISA format, as outlined below. In this embodiment, the binding reaction between PD-1 protein and bsPD-L1 is carried out on a carrier on which PD-1 protein is immobilized, i.e., the principle of ELISA is utilized. The carrier may be the same as that used in the ELISA system of the present invention described below.The specific procedures, materials, and devices for the step of contacting the carrier with the test sample and the step of detecting and quantifying bsPD-L1 in the test sample can be similar to those of the ELISA system of the present invention described below. This method has the advantage of being less affected by the biopsy site and less variability between testing institutions compared to immunohistological testing, facilitating quantification of T cell immune function, and enabling systemic rather than localized evaluation of T cell function. In this embodiment, the system includes a carrier on which PD-1 protein is immobilized (hereinafter also referred to as a "PD-1 carrier"), a means for reacting the carrier with a test sample (preferably a biological sample), and a means for detecting and quantifying soluble PD-L1 bound to the carrier as bsPD-L1. Preferably, the system further includes a carrier on which an anti-PD-L1 antibody is immobilized (hereinafter also referred to as an "anti-PD-L1 antibody carrier"), a means for reacting the carrier with the test sample, and a means for detecting and quantifying soluble PD-L1 bound to the carrier. In this embodiment, the carrier serves as a carrier for immobilizing PD-1 protein. The carrier need not be particularly limited as long as it fulfills this role, and various materials and shapes can be used. Typical carriers include hydrophobic plastic microplates, beads, and tubes, and most preferably multi-well microplates. The PD-1 carrier can be prepared by known methods. Specifically, a solution containing PD-1 protein is added to the carrier and allowed to stand, allowing the PD-1 protein to adsorb to the carrier. The solution is then removed, and the carrier is washed and protected and washed with a blocking solution (see Experimental Example 2 in WO 2019 / 049974). In this ELISA system, the carrier is sequentially reacted with a test sample (preferably a biological sample) and a detection marker. The test sample to be reacted with the prepared PD-1 carrier is, for example, a biologically derived sample as described in the evaluation method of the present invention. There is no need to be any particular limitation as long as binding between PD-1 and bsPD-L1 on the PD-1 carrier is achieved, and the PD-1 carrier may be used as is or after pretreatment, depending on the PD-1 carrier.For example, in the case of blood, plasma components can be obtained by centrifugation, diluted if necessary, and used as a test sample. Furthermore, when reacting a PD-1 carrier with a test sample, the reaction time and reaction temperature can be adjusted depending on the PD-1 carrier and test sample used. After the reaction, the supernatant can be removed and washed with a washing solution, if necessary. After the reaction with the test sample is complete, a detection marker is reacted. The detection marker serves as a marker for detecting the binding reaction between PD-1 and bsPD-L1, and enables detection and quantification of the binding reaction through detection of the detection marker. The detection marker need not be particularly limited as long as it fulfills these roles, and can be used in various forms. For example, the detection marker can be configured as a marker for directly or indirectly detecting bsPD-L1 bound to PD-1. Direct detection can be achieved, for example, by using a radiolabeled or fluorescently labeled anti-PD-L1 antibody as the detection marker and reacting it with bsPD-L1 bound to PD-1. An example of indirect detection is to react a biotin-labeled anti-PD-L1 antibody with bsPD-L1 bound to PD-1, followed by reaction with a biotin quantification reagent as a detection marker. Furthermore, the detection marker need not be particularly limited as long as it is detectable, and can be varied appropriately depending on the nature of the PD-1 carrier and the purpose of measurement. For example, an enzyme-labeled antibody, a fluorescent label, a radiolabel, or a combination of these may be used. Regarding the ELISA system, a carrier on which an anti-PD-L1 antibody has been immobilized (hereinafter referred to as an "anti-PD-L1 antibody carrier") is reacted with a test sample containing bsPD-L1 (preferably a biological sample) and a detection marker, in that order, and the detection and quantification results are combined for evaluation. The ELISA system includes the above-mentioned PD-1 carrier, and in addition to the new ELISA system having a means for sequentially reacting a test sample and a detection marker, it also includes an anti-PD-L1 antibody carrier and has a means for sequentially reacting the test sample and a detection marker with the carrier.This enables simultaneous detection and quantification of sPD-L1 and bsPD-L1, thereby enabling more appropriate evaluation of T cell immune function. In such cases, various embodiments and configurations are possible, and are not particularly limited as long as simultaneous detection and quantification of PD-L1 and bsPD-L1 are possible. For example, half of a 96-well microplate may be immobilized with PD-1 protein, and the remainder with an anti-PD-L1 antibody. Alternatively, an ELISA kit may be configured containing a PD-1 carrier, an anti-PD-L1 antibody carrier, and an anti-PD-L1 antibody as a detection marker. By enabling simultaneous detection and quantification of sPD-L1 and bsPD-L1, it is possible to calculate the ratio of bsPD-L1 in sPD-L1. Therefore, by correlating this ratio with the suitability of various treatments, such as immunotherapy, the therapeutic efficacy, and the presence or absence of side effects, the ratio can be used as an indicator for diagnosing the suitability of various treatments (e.g., immunotherapy), and predicting the therapeutic efficacy and side effects. Therefore, in the present invention, bsPD-L1 can be a biomarker for evaluating T cell immune function. A biomarker is a biological substance, such as a protein or gene, contained in body fluids such as blood and urine or tissues, which correlates with and serves as an indicator of changes in disease or responses to treatment. Measuring the amount of a biomarker can be used as an indicator of the presence or progression of disease and the effectiveness of treatment. bsPD-L1 can be used as an indicator for evaluating the pathology, prognosis, and therapeutic efficacy of diseases involving T cell immunity. Using bsPD-L1 in combination with sPD-L1 enables more detailed evaluation. Therefore, the present invention also provides a combination of biomarkers for evaluating T cell immune function, consisting of a biomarker consisting of bsPD-L1 and a biomarker consisting of sPD-L1.

[0042] Furthermore, the degree or site of glycosylation of bsPD-L1 need not be particularly limited as long as it has high binding ability to PD-1. An example of bsPD-1 is one having a molecular weight of approximately 45 to 65 Kd and containing a glycosylation chain. BsPD-L1 can be typically measured by a method comprising the steps of reacting a target substance (also referred to as a test sample) with PD-1 and detecting and quantifying soluble PD-L1 bound to PD-1 (i.e., PD-L1 capable of binding to PD-1: bsPD-L1). Specifically, the amount or concentration of bsPD-L1 in a biological sample from a cancer patient correlates with the patient's T-cell immune response, and a high T-cell immune response can be predicted when the amount or concentration of bsPD-L1 is equal to or greater than the cutoff value in the evaluation method of the present invention. The cutoff value, also referred to as a pathological condition identification value, is a value set for the purpose of diagnosing a disease or pathological condition. The cutoff value varies depending on the type of biological sample (e.g., serum or plasma), the presence or absence and type of coagulant when the biological sample is blood, the processing method from blood collection to storage (temperature and time), storage conditions (storage temperature and storage period), etc., and an optimal value can be set as appropriate, and it is desirable to set an optimal value in advance from the viewpoint of accuracy. In a preferred embodiment, the prognosis after cancer treatment is evaluated by assessing whether the amount or concentration of bsPD-L1 is equal to or greater than the cutoff value, and the prognosis and therapeutic effect of the patient can be predicted by combining with a disease progression diagnostic marker.

[0043] The PD-1 binding ability of the above-mentioned soluble PD-L1 is mainly dependent on glycosylation. As shown in WO2019 / 049974, PD-L1 is glycosylated in a variety of ways, and the binding properties with PD-1 vary depending on the type of glycosylation.

[0044] As shown in WO2019 / 049974, the glycosylation pattern can be analyzed by treating a biological sample that may contain soluble PD-L1 with a glycosidase (e.g., PNGase F) or a sugar chain synthesis inhibitor (e.g., tunicamycin) to deglycosylate the sample, and then examining the change in molecular weight of the treated sample by Western blotting using an anti-PD-L1 antibody.

[0045] As used herein, the term "factor" refers to a means for achieving an intended purpose, and may refer to any substance or other element (e.g., energy such as light, radioactivity, heat, or electricity) as long as it is capable of achieving the intended purpose. Examples of such substances include, but are not limited to, proteins, polypeptides, oligopeptides, peptides, polynucleotides, oligonucleotides, nucleotides, nucleic acids (e.g., DNA such as cDNA and genomic DNA, and RNA such as mRNA), polysaccharides, oligosaccharides, lipids, small organic molecules (e.g., hormones, ligands, signaling substances, small organic molecules, molecules synthesized by combinatorial chemistry, small molecules that can be used as pharmaceuticals (e.g., small molecule ligands), etc.), and composite molecules thereof. Factors also include molecules that perform functions similar to antibodies, such as antibodies in the narrow sense, antigen-binding molecules, antibody-like molecules, and antibody mimetics.

[0046] As used herein, "interact" (factors that interact) refers to a state in which two or more substances interact with each other through non-covalent bonding, and is used synonymously with "binding" and "association" in the context of this specification. Detection can be performed based on the interaction, and intracellular signal transduction can also be achieved through the interaction. The interaction is expressed as a binding interaction, which is its strength, and is generally expressed as a binding interaction. －６ Under M to 10 －１５ It is characterized by, but not limited to, a dissociation constant (Kd) less than M. "Affinity" refers to the strength of binding, higher binding affinity being correlated with a lower Kd.

[0047] As used herein, the term "interacting factor" is used synonymously with "binding factor" or "associating factor," and when used for detection purposes, it is also referred to as "detecting factor," and includes, for example, an antibody or an antigen-binding fragment thereof.

[0048] As used herein, the term "antibody" collectively refers to immunoglobulins or immunoglobulin-like molecules, including, but not limited to, IgA, IgD, IgE, IgG, and IgM, combinations thereof, and similar molecules produced during the immune response in any vertebrate, e.g., mammals such as humans, goats, rabbits, and mice, and in non-mammalian species, such as shark immunoglobulins. Unless specifically stated otherwise, the term "antibody" includes intact immunoglobulins and "antibody fragments" or "antigen-binding fragments" that specifically bind to a molecule of interest (or a group of highly similar molecules of interest) to the substantial exclusion of binding to other molecules (e.g., with a binding constant at least 10 times higher than that for other molecules in a biological sample). ３ M －１ Large, at least 10 ４ M －１ Greater than or at least 10 ５ M －１(Antibodies and antibody fragments with large binding constants for molecules of interest.) The term "antibody" also includes genetically engineered forms such as chimeric antibodies (e.g., humanized murine antibodies), heteroconjugate antibodies (bispecific antibodies, etc.). See also Pierce Catalog and Handbook, 1994-1995 (Pierce Chemical Co., Rockford, IL); Kuby, J., Immunology, 3rd Ed., W.H. Freeman & Co., New York, 1997. An "antigen-binding fragment" of an antibody is a portion of an antibody that retains the ability to specifically bind to the antibody's target antigen. As used herein, the term "antigen" refers to a compound, composition, or substance that can be specifically bound by an antibody molecule or a product of specific humoral or cellular immunity, such as a T-cell receptor. Antigen-binding fragments of antibodies include Fv, dsFv, scFv, Fab, Fab', and F(ab')2. Fv fragments consist of the VL and VH domains of an antibody associated with each other through hydrophobic interactions; in dsFv fragments, the VH:VL heterodimer is stabilized by disulfide bonds; and in scFv fragments, the VL and VH domains are connected to each other via a flexible peptide linker, thereby forming a single-chain protein. Fab fragments are monomeric fragments obtained by papain digestion of antibodies and contain the entire L chain and the VH-CH1 fragment of the H chain, which are linked to each other by disulfide bonds. F(ab')2 fragments can be produced by pepsin digestion of antibodies below the hinge disulfide and contain two Fab' fragments and, additionally, a portion of the hinge region of an immunoglobulin molecule. Fab' fragments can be obtained from F(ab')2 by cleavage of the disulfide bond in the hinge region. F(ab')2 fragments are bivalent, i.e., contain two antigen-binding sites, like native immunoglobulin molecules; whereas Fv (the VH:VL dimer comprising the variable region of Fab), dsFv, scFv, Fab, and Fab' fragments are monovalent, i.e., contain a single antigen-binding site. These basic antigen-binding fragments of the invention can be combined with each other to obtain multivalent antigen-binding fragments, such as diabodies, triabodies, or tetrabodies.Multivalent antigen-binding fragments are also part of the present invention. A "mimetic" of an antibody refers to an antigen-binding antibody mimetic. Antigen-binding antibody mimetics are organic compounds that specifically bind to antigens but are not related to antibodies. They are usually artificial peptides or small proteins with a molar mass of approximately 3-20 kDa. Nucleic acids and small molecules are also sometimes considered antibody mimetics, but artificial antibodies, antibody fragments, and fusion proteins made from them are not. Common advantages over antibodies include better solubility, tissue penetration, heat and enzymatic stability, and relatively low production costs. Antibody mimetics are being developed as therapeutic and diagnostic agents. Antigen-binding antibody mimetics can also be selected from the group including affibodies, affilins, affimers, affitins, DARPins, and monobodies.

[0049] As used herein, the term "agent" refers to an agent that is used for some purpose, including factors such as antibodies, antibody-binding fragments, and mimetics. Agents used for diagnostic purposes are called diagnostic agents, and agents used for therapeutic purposes are called therapeutic agents. Agents can be specified by their intended use.

[0050] As used herein, the term "device" refers to a part of a mechanical apparatus (medical supplies, dental materials, sanitary products, etc.) that is used to diagnose, treat, or prevent a physical condition, such as a disease, in a human or animal, or that is intended to affect the structure or function of the human or animal body. For the purposes of this disclosure, when a mass spectrometer is intended, a part necessary for mass analysis (e.g., a sample separation section that separates an ionized sample) is intended. For example, for the purposes of this disclosure, if the concentration of MMP in blood is known, pathological conditions can be predicted by other methods, such as immunoassays based on antibody detection (e.g., Western and Luminex assays, as well as ELISA), or protein quantification without antibodies (e.g., mass spectrometry).

[0051] As used herein, the terms "subject" and "object" are equivalent to the term "individual," and therefore both terms can be used interchangeably herein. "Subject" refers to any individual, as well as any animal belonging to any species. Examples of subjects include, but are not limited to, animals of commercial interest, such as birds (hens, ostriches, chicks, geese, partridges, etc.), rabbits, hares, pet animals (dogs, cats, etc.), sheep, goat cattle (goats, etc.), Sus scrofa (boars, pigs, etc.), equine livestock (horses, ponies, etc.), bovine animals (bulls, cows, castrated bulls, etc.); animals of hunting interest, such as bucks, deer, reindeer, etc.; and humans. However, in certain embodiments, the subject is a mammal, and in particular, the mammal is a human of any race, sex, or age.

[0052] As used herein, the terms "sample" and "specimen" are used interchangeably and generally refer to a certain amount of material from a biological source, an environmental source, a medical source, a patient source, or a subject, which is considered to contain the target of measurement or detection (even if the target is not detected as a result of the measurement). The sample is preferably a biological sample (also referred to as a biologically derived sample). The biologically derived sample is not particularly limited as long as it is derived from a living organism, and various biologically derived samples can be used. Examples of such biologically derived samples include samples directly collected from a living organism, samples obtained by washing or crushing such samples, and the like. Examples include blood, tissue washings such as alveolar tissue washings, urine, cerebrospinal fluid, and tissue sections. Depending on the evaluation system, these biologically derived samples can be used as is, or they can be used as test samples after undergoing certain pretreatments. As biologically derived samples, blood, tissue washings such as alveolar tissue washings, urine, and cerebrospinal fluid are preferably used. This allows for measurement by ELISA or the like rather than immunohistological testing, eliminating the influence of biopsy site and variability between testing institutions.

[0053] As used herein, "detection" refers to clarifying the presence or absence of a target, and includes determining from scratch, as well as determining the presence or absence of a target by measuring or calculating a value related to the target's presence to calculate a quantitative or semi-quantitative presence value (such as, but not limited to, an amount, an activity value (U (unit)), or a ratio)).

[0054] As used herein, "quantitation" refers to determining the amount of a substance of interest. In a narrow sense, quantitation refers to determining the amount using a standard substance, and determining the amount without using a standard substance is called semi-quantitation. However, treatment in a broad sense is understood to encompass both, and when the term "quantitation" is used in this specification, it is generally understood to encompass both quantitation in the narrow sense and semi-quantitation. Quantitation may be calculated as an absolute value, or may be expressed as a relative or indirect value such as an activity value (e.g., U (unit)) or a ratio.

[0055] As used herein, the term "carrier" refers to a substance used to immobilize a factor, agent, or the like of the present disclosure, thereby facilitating detection. For example, in the case of an agent containing PD-1 protein, when the PD-1 protein is provided as a solid-phase carrier, the carrier can serve as a means for reacting the carrier with a sample and a means for interacting with, detecting, and quantifying soluble PD-L1 bound to the carrier as bsPD-L1. For example, a carrier can be prepared on which an anti-PD-L1 antibody is solidified, and this can constitute a means for reacting the carrier with a test sample and a means for interacting with, detecting, and quantifying soluble PD-L1 bound to the carrier. The carrier serves as a carrier for immobilizing the agent of the present disclosure (e.g., PD-1 protein). The carrier need not be particularly limited as long as it fulfills this role, and various materials and shapes can be used. Typical carriers include hydrophobic plastic microplates, beads (magnetic beads, fluorescent particles, etc.), tubes, etc., and most preferably, multi-well microplates. PD-1 carriers can be prepared by known methods. That is, a solution in which PD-1 protein is dissolved is added to a carrier, and the carrier is allowed to stand to allow the agent (antibody, etc.) of the present disclosure to be adsorbed onto the carrier. Thereafter, the solution is removed, and the carrier is washed and protected and washed with a blocking solution, thereby producing a PD-1 carrier (see WO2019 / 049974).

[0056] As used herein, "instructions" (including package inserts and labels used by the U.S. FDA) are written instructions to a physician or other user on how to use the present disclosure. The instructions may often be included in a kit. The instructions include instructions for administering the diagnostic method of the present disclosure or a pharmaceutical based thereon. The instructions may also include instructions for determining predictions of treatment (e.g., treatment or prevention). The instructions are prepared in accordance with a format specified by a regulatory agency of the country in which the present disclosure is implemented (e.g., the Ministry of Health, Labor and Welfare in Japan, the Food and Drug Administration (FDA) in the United States, etc.), and clearly state that they have been approved by the regulatory agency. The instructions are so-called package inserts or labels, and may be provided in paper form, but are not limited thereto, and may also be provided in the form of electronic media (e.g., a website provided on the Internet, a PDF, or email). In addition to or instead of the above, the kit may include any one or more of the following: an insert, a standard solution (calibrator), positive and negative control reagents, a washing solution, a reaction stop solution, a capture antibody and a detection antibody, and the detection antibody may be labeled.

[0057] As used herein, "metastasis," when referring to cancer or tumors, refers to the spread of cancer or tumors to tissues or organs distant from where they first originated. This process is an important factor in determining cancer morbidity and is a hallmark of malignant cancer. Predicting whether a tumor will metastasize is important, as it may enable personalized treatment at an early stage for better treatment. Therefore, markers that can predict tumor metastasis could greatly advance the possibilities of clinical cancer treatment. The metastasis cascade can be divided into three major processes: invasion, invasion, and extravasation.

[0058] As used herein, the term "invasion" refers to the spread of cancer or tumor to adjacent tissues or organs. Invasion occurs when tumor cells acquire the ability to penetrate the basement membrane or extracellular matrix and reach surrounding tissues.

[0059] As used herein, "intravasation" refers to the entry of motile tumor cells into the lymphatic and vascular systems.

[0060] As used herein, "extravasation" refers to the process by which metastatic cancer cells pass through the circulatory system and penetrate into the vascular basement membrane or extracellular matrix of the secondary metastasis destination.

[0061] As used herein, the term "host T cell immune function marker" refers to a marker that serves as an indicator of the host's T cell immune response. The host refers to a patient. Regardless of whether treatment is administered or not, the inherent T cell immune function of each patient varies greatly from person to person, and therefore, it is important to examine markers that indicate a patient's baseline T cell immune function, as this is effective in predicting various treatments. Examples of host T cell immune function markers include, but are not limited to, bsPD-L1, MMP D group, IFN-γ, etc.

[0062] As used herein, the term "disease progression diagnostic marker" (sometimes abbreviated as "disease progression marker") refers to a marker capable of diagnosing the progression of a T-cell-related disease, and includes, for example, detecting the migration of cancer or tumor from the primary tumor to other tissues or organs, and also includes predicting various non-primary events such as metastasis, infiltration, invasion, and extravasation (in this case, it is also referred to as a tumor invasion / metastasis marker in a limited sense). Cancers associated with one characteristic of the markers disclosed herein spread by proliferating in the primary tumor, infiltrating the surrounding area, and metastasizing to distant organs, and therefore it is important to be able to predict this process. Examples of "disease progression diagnostic markers" include, but are not limited to, MMP group A, group B, group C, group D, etc.

[0063] As used herein, the term "(bio)marker" refers to a substance in a living body, such as a protein or gene, contained in body fluids such as blood or urine, or in tissues, which correlates with and serves as an indicator of changes in a disease or a response to treatment. Measuring some indicator, such as the amount, concentration, or activity of a biomarker, can be used as an indicator of the presence or progression of a disease or the effectiveness of treatment.

[0064] In this specification, "matrix metalloproteinase (MMP)" is a group of metalloproteases (a general term for proteolytic enzymes in which a metal ion is located in the active center), and the active center of MMP contains a zinc ion (Zn ２＋ ) and calcium ions (Ca ２＋ Enzymes belonging to the MMP family are classified into two types: secreted and membrane-bound. Secreted MMPs function even at locations away from the secretory cell after production, while membrane-bound MMPs are expressed on the cell surface.

[0065] (Preferred Embodiments) A preferred embodiment will be described below, but it should be understood that this embodiment is an example of the present disclosure and that the scope of the present disclosure is not limited to such preferred embodiments. It should also be understood that those skilled in the art can easily make modifications, changes, etc. within the scope of the present disclosure by referring to the following preferred examples. Therefore, it is clear that those skilled in the art can make appropriate modifications within the scope of the present disclosure by taking into account the description in this specification. It should also be understood that the following embodiments of the present disclosure can be used alone or in combination.

[0066] The present inventors have begun research focusing on soluble PD-L1 (hereinafter referred to as "sPD-L1") present in the blood as a means for evaluating systemic T cell immune function. As a result, they have discovered that sPD-L1 contains a bound soluble PD-L1 (sPD-L1 with PD-1-binding capacity, hereinafter referred to as "bsPD-L1") that has high binding capacity to PD-1, and have further succeeded in developing a method for detecting and quantifying bsPD-L1 with high accuracy (Patent Document 3, Non-Patent Document 5).

[0067] The present inventors have conducted extensive research based on their findings to date, and have succeeded in overcoming the drawbacks of conventional methods, in which a portion of tissue is biopsied and subjected to pathological testing (immunohistological staining). In order to make the method as minimally invasive as possible and to enable accurate determination by anyone, the present inventors focused on sPD-L1 in the blood, and in particular, bsPD-L1, which is an indicator of T-cell immune response, as a biomarker for predicting the therapeutic effect of ICI, and have been able to provide the present disclosure. The present inventors further discovered that, although it was previously believed that cancer could be cured if a strong immune response could be induced by cancer immunotherapy, when a strong immune response occurs, metastasis becomes more likely due to tissue damage. They then completed a technology that, by combining an index of T cell immune response with an index of tissue damage, can predict patients for whom a treatment with "strong immune response but low metastasis" is effective (for example, patients for whom ICI shows a complete response (CR)) or a partial response (PR); i.e., patients for whom ICI treatment should be selected because the therapeutic effect is expected to be high) and patients for whom a treatment with "too strong an immune response is likely to cause metastasis" is ineffective (for example, patients for whom ICI progresses (PD) or remains unchanged (NC)); i.e., patients for whom ICI treatment should be avoided because the therapeutic effect is expected to be low).

[0068] <Uses of bsPD-L1> In one aspect, the present disclosure provides a method for predicting or assisting in the prediction of the efficacy or prognosis of cancer treatment or prevention in a subject, the method comprising the step of detecting bound soluble PD-L1 (bsPD-L1 / sPD-L1 with PD-1-binding capacity) in a sample obtained from the subject. The prognosis and prediction of the efficacy include monitoring during treatment of the target disease (prediction of disease progression, high risk of death, and poor OS).

[0069] In another aspect, the present disclosure provides a method for predicting the effect of cancer therapy or prevention or predicting prognosis in a subject, the method comprising the steps of detecting bound soluble PD-L1 in a sample obtained from the subject, and calculating, from the value of the bsPD-L1, an index related to the prediction of the effect of cancer therapy or prevention or the prediction of prognosis in the subject.

[0070] In one aspect, the present disclosure provides an agent, element, or composition comprising a factor that interacts with bsPD-L1 for use in predicting the efficacy or prognosis of cancer treatment or prevention. In certain embodiments, the present disclosure provides that the treatment including treatment or prevention can be any treatment including surgery, radiation therapy, proton beam therapy, chemotherapy, molecular targeted medicine, immunotherapy (including immune checkpoint inhibitors), and combinations thereof, or combinations of these with surgery or immunotherapy including ICI, etc. More particularly, in the present disclosure, the treatment including treatment or prevention includes at least one selected from chemotherapy, radiation therapy, combinations thereof, combinations of these with surgery, and combinations of these with immunotherapy, and in more specific embodiments, the treatment including treatment or prevention includes at least one selected from immunotherapy, chemotherapy, radiation therapy, or surgery, or combinations thereof (particularly, a combination of immunotherapy and chemotherapy, a combination of immunotherapy and radiation therapy, or a combination of surgery and chemotherapy).

[0071] In one embodiment, the present disclosure is for predicting the efficacy and prognosis of treatment (therapeutic or preventive) for a disease or condition primarily driven by a T cell response, such as a self-antigen (including cancer), a foreign antigen (including a pathogen, a vaccine, or a transplant), or an immunomodulatory drug. In one embodiment, the present disclosure is used to evaluate T cell immune function and / or tissue damage, predict cancer invasion, metastasis, or recurrence, and / or predict the therapeutic efficacy of an immunomodulatory drug, including an immune checkpoint inhibitor.

[0072] The factor used in the present disclosure is at least one selected from the group consisting of small molecular weight compounds, antibodies, nucleic acid molecules, and polypeptides, as well as fragments and combinations thereof, and elements that realize protein interaction detection technology using surface plasmon resonance technology (e.g., Biacore™), but is not limited thereto. Preferably, the factor is an antibody or an antigen-binding fragment thereof, or a variant thereof. The Biacore system is a device that measures interactions between all molecules, from biomolecules such as proteins, nucleic acids, peptides, sugar chains, and lipids to small molecular weight compounds such as drugs. Using SPR (surface plasmon resonance) technology as the measurement principle, real-time measurement is possible without the use of any labels.

[0073] In certain embodiments, the present disclosure provides biomarkers (markers) disclosed herein, as well as factors that interact with them, agents, elements or compositions containing such factors, or agents capable of detecting such biomarkers, kits, devices, systems, methods, etc. It is understood that some or all of these embodiments encompass various products and sales forms (e.g., measurement reagents, measurement kits, measurement devices, contract tests, multiple panels, etc.). For example, in one embodiment, a kit is intended to be sold and used in a configuration (a combination of two or more different parts) such as an agent, other necessary reagents, and an accompanying document (instructions). The system in the present disclosure is intended to encompass a measurement system, including a measurement device. (Bio)markers are typically biological molecules present in the body, and the scope of the present disclosure is intended to extend to substances present in the body or in bodily fluids such as blood extracted from the body, or any samples containing such substances, and results obtained therefrom.

[0074] In the present disclosure, it is understood that some preventive measures (for example, cancer vaccines are usually used for treatment, but can also be used for preventive measures) as well as therapeutic effects are intended as part of the present disclosure, since, for example, preventive measures may not be covered by insurance, but may be used in, for example, medical checkups and medical examinations.

[0075] In one embodiment, the present disclosure can determine whether a patient is susceptible to immunotherapy, i.e., it is possible to predict treatment options, and can determine whether a patient is prone to metastasis, or in other words, whether a patient is prone to recurrence, and can therefore take measures for early detection, such as frequent screening tests such as CT scans.

[0076] In one specific embodiment, the agent is a carrier on which PD-1 protein is immobilized. In a specific embodiment, when this carrier is used, it is used in a method for detecting bsPD-L1 by a method comprising the steps of reacting a target substance with PD-1 and detecting and quantifying soluble PD-L1 bound to PD-1 as "soluble PD-L1 capable of binding to PD-1 (bsPD-L1)." Alternatively, measurement can also be performed using Biacore protein interaction using surface plasmon resonance (SPD).

[0077] In one embodiment, the prediction comprises predicting the therapeutic efficacy of an immune checkpoint inhibitor.

[0078] In one embodiment, the agent, device or composition of the present disclosure may be provided as a diagnostic agent, device or reagent.

[0079] In one aspect, the present disclosure provides a kit for use in predicting the efficacy or prognosis of cancer treatment or prevention, comprising an agent, element, or composition of the present disclosure and a substance to be used for detection using the agent, element, or composition.

[0080] The kit may include instructions. The instructions describe a detection method. In one embodiment, the agent, element, or composition is a PD-1 protein bound to a carrier, and the substance is a labeled anti-PD-L1 antibody. In this case, for example, the instructions may describe sequentially reacting the carrier with a test sample (preferably a biological sample) and a detection marker. The reaction time and reaction temperature can be adjusted depending on the PD-1 carrier and test sample used. After the reaction, the supernatant can be removed and washed with a washing solution, if necessary. After the reaction with the test sample is complete, a detection agent can be reacted. For example, direct detection can be performed using a radiolabeled or fluorescently labeled anti-PD-L1 antibody as a detection marker and reacting it with bsPD-L1 bound to PD-1. For example, indirect detection can be performed by reacting a biotin-labeled anti-PD-L1 antibody with bsPD-L1 bound to PD-1, followed by reaction with a biotin quantitation reagent as a detection agent. The detection agent need not be particularly limited as long as it is capable of detection, and can be changed appropriately depending on the type of PD-1 carrier and the purpose of measurement. For example, an enzyme-labeled antibody, a fluorescent label, a radiolabel, or a combination of these may be used. The ELISA kit need not be particularly limited as long as the PD-1 carrier and the detection marker are essential components, and can include other reagents as needed. One example is a combination of a 96-well microplate on which PD-1 protein is immobilized as the PD-1 carrier, and a biotin-labeled anti-PD-L1 antibody and a biotin quantification reagent as the detection marker.

[0081] In one aspect, the present disclosure provides a system for use in predicting the efficacy or prognosis of cancer treatment or prevention, comprising an agent, element, or composition of the present disclosure, a substance used for detection using the agent, element, or composition, an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means used to detect the target of detection (e.g., a signal (such as a fluorescent signal), an ionized substance) resulting from the agent, element, or composition.

[0082] In this aspect, the substance used for detection using the agent, element, or composition can be appropriately selected depending on the detection method. For example, in the case of a diagnostic agent, for example, when an antibody is used, an appropriate buffer, salt, etc. is used to promote the antigen-antibody reaction. In the case of an element, it is used as part of a device or system, and other components constituting the system correspond to this substance. In the case of a composition, appropriate additives such as a pharmaceutically acceptable carrier can be added depending on the purpose.

[0083] In this aspect, the interaction part that allows the agent, element, or composition to interact with a sample expected to contain the target substance can be provided, for example, as a container that allows the agent or composition to interact appropriately with the sample. In the system, it may be a part that provides a space where the element and the test substance in the specimen can interact, or it may be a container, etc.

[0084] In this aspect, the detection means used to detect the target substance caused by the agent, element, or composition may be any means capable of detecting a signal generated by the contained factor (or, if labeled, derived from the label) in the case of the agent. If a fluorescent signal is generated, a detection device that detects fluorescence may be applicable. In the case of an element, for example, in the case of mass spectrometry, a means for detecting ionized substances using a mass spectrometer may be applicable. Alternatively, when surface plasmon resonance technology is used, a means for detecting a signal caused by surface plasmon resonance may be applicable.

[0085] In certain embodiments, in the systems of the present disclosure, the agent, element, or composition is a PD-1 protein bound to a carrier, the substance comprises a labeled anti-PD-L1 antibody, and the detecting means detects the label.

[0086] <MMPs as Disease Status Diagnostic Markers> In another aspect, the present disclosure provides an agent, element, or composition for predicting the pathology, severity, prognosis, or therapeutic effect of a T-cell-related disease, comprising a factor that interacts with at least one member of MMP A. MMPs are generally applicable to diagnosing the pathology and disease status of T-cell-related diseases, including cancer, and can be used to predict the efficacy and / or prognosis of various cancer treatments (treatment or prevention, etc.), including not only immunotherapy including immune checkpoint inhibitors (ICIs), but also surgery, other chemotherapy, radiation therapy, molecular targeted drugs, proton beams, and combinations thereof, or to predict the pathology of cancer.

[0087] The present disclosure has revealed that MMPs can be widely used as disease diagnostic markers. MMPs are proteins present in the body, and in particular, the pathology, severity, prognosis, and therapeutic effect of T cell-related diseases can be predicted based on the pre-treatment values ​​and / or changes in MMP levels in the body (e.g., comparisons between pre-treatment and post-treatment, comparisons between two time points after treatment, etc.), and in particular, the state of tissue structure destruction or tumor metastasis / infiltration can be predicted.

[0088] In particular, we have found that MMPs classified as group A, which have a structure consisting of a signal peptide, a propeptide, an enzymatically active domain, a hinge region, and a hemopexin-like domain from the amino-terminal side, excluding those with a transmembrane domain or a GPI anchor and gelatinase, can be used as disease diagnostic markers (the signal peptide is cleaved after maturation to produce a proenzyme, which exerts its enzymatic activity upon removal of the propeptide portion at the amino-terminal end). Group A MMPs are particularly important in that they can be used to assess the progression of T-cell-related diseases, but the present disclosure is not limited thereto. Therefore, while group A MMPs encompass most MMPs, it is understood that MMP2 and MMP9 do not fall within this definition.

[0089] In a preferred embodiment, the disease diagnostic marker comprises at least one member of the MMP B group.

[0090] As used herein, MMP Group B is a group of MMP molecules structurally classified as archetypal MMPs and located on chromosome 11, including MMPs 1, 3, 8, 10, 12, 13, 20, and 27. Group B is considered to be highly related to the progression of disease based on their relationship with each other in terms of chromosomal location, molecular structure, and transcriptional regulation, and is therefore particularly useful as a diagnostic marker for disease progression, as shown in the Examples.

[0091] In a preferred embodiment, the disease diagnostic marker comprises at least one of the matrix metalloproteinase (MMP) C group.

[0092] Here, MMP Group C refers to a group of MMP molecules among MMP Group B that have a STAT3 binding motif in the promoter region, and includes MMPs 3 and 13. Group C is considered to be highly relevant to the progression of disease based on their relationship with chromosomal location, molecular structure, and transcriptional control, and is useful because the relevance is particularly demonstrated in the examples.

[0093] In a preferred embodiment, the disease diagnostic marker includes at least one member of the MMP D group. Here, the MMP D group refers to a group that has the characteristics of the MMP C group as well as the function of a host T-cell immune marker. The MMP D group (typically MMP13) is particularly useful because it functions as a disease diagnostic marker as well as a host T-cell immune marker, allowing the detection of two functions at once. MMP13 may be useful as a member of the MMP D group.

[0094] In one embodiment, only one type of MMP D group may be used as a disease diagnostic marker, or MMP13 may be used.

[0095] In one embodiment, the disease diagnostic marker disclosed herein is used to predict the effect of treatment (therapeutic or preventive) and prognosis for a disease or condition primarily driven by a T-cell response due to an autoantigen (including cancer), a foreign antigen (including a pathogen, a vaccine, or a transplant), or an immunomodulatory drug. In one embodiment, the disease diagnostic marker disclosed herein is used to evaluate T-cell immune function and / or tissue damage, predict cancer invasion, metastasis, or recurrence, and / or predict the therapeutic effect of an immunomodulatory drug, including an immune checkpoint inhibitor.

[0096] In another preferred embodiment, the disease diagnostic marker used in the present disclosure includes at least two of the MMP C group. Using two different MMP C group markers allows for more precise diagnosis and prognosis. In particular, at least one of the MMP C group includes the MMP D group. In a specific embodiment, the disease diagnostic marker used includes MMP3 and MMP13. Without wishing to be bound by theory, this combination makes it possible to more efficiently predict the destruction of tissue structure or tumor metastasis / infiltration, and furthermore, to predict the state of host T-cell immunity, thereby enabling highly accurate prediction of the effectiveness and / or prognosis of treatment, particularly therapy, for T-cell-related diseases.

[0097] In another embodiment, among the combinations of MMPs, a combination of changes in MMP values ​​of MMP D group (e.g., MMP13) and MMP A group (preferably, group B, more preferably group C) measured before treatment is considered advantageous in the present disclosure. An exemplary determination method is, for example, when MMP13 levels are high in a biological sample obtained before treatment and / or when the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment, a poor prognosis (low therapeutic effect or worsening disease progression) for T cell-related diseases can be predicted. For MMP D group (e.g., MMP13), when used as a host T cell immune function marker, a cutoff value is set that results in bsPD-L1 positivity. When using MMP D group (e.g., MMP13) as a disease diagnostic marker, a cutoff value must be set depending on various diseases or pathological conditions. Since the concentration of MMP13 varies depending on the measurement kit, assay method, and device, it must be set according to the various measurement methods. The change in MMP group A (preferably group B, more preferably group C or D) is calculated based on the measured values ​​before and after the start of treatment (therapy, etc.) (it is preferable, but not limited to, to measure biological samples before and after treatment simultaneously).

[0098] More specifically, when MMP B group or MMP C group is used as a disease progression diagnostic marker, in the case of cancer diagnosis, values ​​"before treatment" and / or "after treatment initiation" can be used. In this case, if the "before treatment initiation" value cannot be measured, multiple points (e.g., two points) "after treatment initiation" can be used as a substitute, and for other T cell-related diseases, values ​​"before treatment" and / or "after treatment initiation" can be used. If the "before treatment initiation" value cannot be measured, multiple points (e.g., two points) "after treatment initiation" can be used as a substitute.

[0099] In another specific embodiment, when using the MMP D group, in the case of cancer, the "pre-treatment value" is generally used when considering immunocompetence, but if the "pre-treatment" value cannot be measured, the "post-treatment" value can be used instead. When considering disease progression, the "pre-treatment" and / or "post-treatment" values ​​can be used, but if the "pre-treatment" value cannot be measured, multiple points (e.g., two points) "post-treatment" values ​​can be used instead. In the case of T cell-related diseases, the "pre-treatment" and / or "post-treatment" values ​​can be used when considering immunocompetence, and if the "pre-treatment" value cannot be measured, multiple points (e.g., two points) "post-treatment" values ​​can be used instead. When considering disease progression, the "pre-treatment" and / or "post-treatment" values ​​can be used, and if the "pre-treatment" value cannot be measured, multiple points (e.g., two points) "post-treatment" values ​​can be used instead. The timing of measurement is not particularly limited, and disease progression diagnostic markers can be measured at any time point from immediately after the start of treatment to the completion of treatment. For example, it may be on the same day as treatment, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days after treatment, or later, and can be set arbitrarily, such as 3 weeks, 4 weeks, or 5 weeks after the start of treatment.

[0100] In embodiments of the MMP aspect of the present disclosure, in addition to the biomarkers (markers) disclosed herein, factors that interact with the biomarkers, agents containing the factors, or agents, elements or compositions, kits, devices, systems, methods, etc. that can detect the biomarkers are provided. It is understood that some or all of these embodiments encompass various products and sales forms (e.g., measurement reagents, measurement kits, measurement devices, contract tests, multiplex panels, etc.). For example, in one embodiment, a kit is intended to be sold and used in a configuration (a combination of two or more different parts) such as an agent, other necessary reagents, and an accompanying document (instructions). The system in the present disclosure is intended to encompass a measurement system, including a measurement device. (Bio)markers are typically biological molecules present in the body, and the scope of the present disclosure is intended to extend to substances present in bodily fluids such as blood extracted from the body, any samples containing such substances, and results obtained therefrom.

[0101] In the MMP aspect of the present disclosure, the present disclosure can be used for other treatments such as prevention (for example, cancer vaccines are usually used for treatment, but can also be used for preventive treatment) as well as for therapeutic effects. For example, although preventive treatments may not be covered by insurance, they can be used in, for example, medical checkups and medical examinations, and therefore are understood to be intended as the subject of the present disclosure.

[0102] In one embodiment of the MMP aspect of the present disclosure, the present disclosure can determine whether or not a patient is susceptible to immunotherapy, i.e., it is possible to predict treatment options, determine whether or not a patient is prone to metastasis, or in other words, whether or not a patient is prone to recurrence, and enable measures for early detection, such as frequent screening tests such as CT scans.

[0103] The MMPs of the present disclosure are capable of various predictions, but in one embodiment, the predictions include prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence.

[0104] In one embodiment, the agent that interacts with MMPs of the present disclosure is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, a polypeptide, a mass spectrometry element, a fragment thereof, and a combination thereof. In a specific embodiment, the agent is an antibody or an antigen-binding fragment thereof, or a variant thereof.

[0105] In one specific embodiment, the agent used in the present disclosure is an antibody or antigen-binding fragment thereof that can specifically bind to MMP3 and / or MMP13, and more particularly, can be a combination of an antibody or antigen-binding fragment thereof that specifically binds to MMP3 and an antibody or antigen-binding fragment thereof that can specifically bind to MMP13.

[0106] In one embodiment, the prediction in the present disclosure includes prediction of the therapeutic effect of an immune checkpoint inhibitor.

[0107] In one aspect, in the MMP group invention, the agent, device or composition of the present disclosure is a diagnostic agent, diagnostic device or reagent.

[0108] In one aspect, in the invention of the MMP group, the present disclosure provides a kit for use in predicting the effect of cancer treatment or prevention or prognosis, comprising an agent, element, or composition of the present disclosure and a substance used for detection using the agent, element, or composition.

[0109] In this aspect, the substance used for detection using the agent, element, or composition can be appropriately selected depending on the detection method. In the case of a diagnostic agent, for example, when an antibody is used, an appropriate buffer, salt, etc. is used to promote the antigen-antibody reaction. In the case of an element, it is used as part of a device or system, and other components constituting the system correspond to this substance. In the case of a composition, appropriate additive components such as a pharmaceutically acceptable carrier can be added depending on the purpose.

[0110] In this aspect, the detection means used to detect the target substance caused by the agent, element, or composition may be any means capable of detecting a signal generated by the agent (or a signal derived from the label if the agent is labeled) generated by the factor contained therein. In the case of a fluorescent signal, a detection device that detects fluorescence may be applicable. In the case of an element, for example, in the case of mass spectrometry, a means for detecting a substance ionized by a mass spectrometer may be applicable.

[0111] In one embodiment, the kit includes, but is not limited to, the agent, element, or composition bound to a carrier.

[0112] In one aspect, in the invention of the MMP group, the present disclosure provides a system for use in predicting the efficacy of cancer treatment or prevention or prognosis, comprising an agent, element, or composition of the present disclosure, a substance used in detection using the agent, element, or composition, an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection, and a detection means used in detection using the agent, element, or composition. Examples of such systems include magnetic bead-based multiplex assays (Luminex), fully automated immunoassay devices HISCL™ (Sysmex), and flow cytometers BD® Cytometric Bead Array (CBA). Those skilled in the art can apply such systems to the techniques of the present disclosure as appropriate based on the respective instruction manuals, etc.

[0113] In this aspect, the substance used for detection using the agent, element, or composition can be appropriately selected depending on the detection method. For example, in the case of a diagnostic agent, for example, when an antibody is used, an appropriate buffer, salt, etc. is used to promote the antigen-antibody reaction. In the case of an element, it is used as part of a device or system, and other components constituting the system correspond to this substance. In the case of a composition, appropriate additives such as a pharmaceutically acceptable carrier can be added depending on the purpose.

[0114] In one embodiment, the agent, element, or composition used in the present disclosure is an anti-MMP group A antibody bound to a carrier, the substance is a labeled anti-MMP group A antibody, and the detection means detects the label.

[0115] In one embodiment, the antibodies used in the present disclosure include antibodies capable of detecting at least one member of the MMP B group, preferably, the antibodies used in the present disclosure include antibodies capable of detecting at least one member of the MMP C group, and more preferably, the antibodies used in the present disclosure include antibodies capable of detecting at least two members of the MMP C group, and in another preferred embodiment, the antibodies used in the present disclosure include antibodies capable of detecting MMP3 and MMP13 of the MMP C group, and in yet another embodiment, an antibody capable of detecting the MMP D group.

[0116] In another aspect, the present disclosure provides a biomarker comprising at least one member of the MMP A group for predicting the pathology, severity, prognosis, and / or efficacy of treatment (e.g., therapeutic or preventive) of a T cell-related disease, or for predicting the efficacy and / or prognosis of cancer treatment (e.g., therapeutic or preventive), or for predicting the pathology of cancer. In a preferred embodiment, the marker of the present disclosure comprises at least one member of the MMP B group, preferably at least one member of the MMP C group, more preferably at least two members of the MMP C group, even more preferably MMP3 and MMP13 of the MMP C group, and even more preferably at least one member of the MMP D group. Potential treatments include, but are not limited to, immune checkpoint inhibitors (ICIs), surgery, other chemotherapy, radiation therapy, molecular targeted drugs, proton beams, surgery, other immunotherapies, and combinations thereof.

[0117] In another aspect, the present disclosure provides a method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T cell-related disease, or for assisting in predicting the effect or prognosis of cancer therapy or prevention, the method comprising detecting at least one of MMP A in a sample obtained from the subject. These prognostic and prediction effects include monitoring during treatment of the target disease (predicting disease progression, high risk of death, and poor overall survival (OS)).

[0118] In yet another aspect, the present disclosure provides a method for predicting the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in a subject, or predicting the effect of treatment (therapy or prevention) or prognosis of cancer, the method comprising the steps of detecting at least one of MMP A in a sample obtained from the subject, and calculating, from the value of at least one of the MMP A, an index relating to the prediction of the pathology, severity, prognosis, and / or effect of treatment (e.g., therapy or prevention) of a T-cell-related disease in the subject, or the prediction of the effect of treatment or prevention or prognosis of cancer.

[0119] In these prediction or prediction-assisting methods, in a preferred embodiment, the MMP A group includes at least one member of the MMP B group, preferably at least one member of the MMP C group, and more preferably at least two members of the MMP C group (preferably MMP3 and MMP13). In another embodiment, the MMP A group includes at least one member of the MMP D group.

[0120] In certain embodiments, the methods for prediction or aiding in prediction use MMP3 and MMP13 from the MMP C group.

[0121] Specifically, this can be summarized as follows. In this specification, the term "high value" refers to a value that is significantly higher than the value in a healthy individual, and since this value differs depending on the measurement kit, assay method, and device, it is necessary to set it according to the various measurement methods. The same is true for bsPD-L1, IFN-γ, and MMP A group, so it is necessary to set it individually, but those skilled in the art will be able to set it appropriately in light of the description in this specification.

[0122] In the present specification, the following values ​​are used as non-limiting examples of reference values ​​in the examples of this disclosure. (1) When used as a host T cell immune function marker: MMP13 > 985 pg / ml can be used based on the values ​​in the examples. In the examples, a cutoff value for MMP13 that indicates MMP13 positivity was set. Also, (2) when used as a disease diagnostic marker, MMP13 > 16,836 pg / ml can be set based on the examples. In the examples, the cutoff value for MMP13 was set based on the prognosis (DFS) of gastric cancer patients. These are merely examples, and the present disclosure is not limited to these values.

[0123] Furthermore, an "increase" or "decrease" is determined by whether the value at a later point is higher or lower, respectively, compared to the value at an earlier point, and is usually determined to be an increase or decrease when there is a significant change.

[0124]

[0125]

[0126]

[0127]

[0128] <Combination of a host T cell immunocompetence marker and a disease diagnostic marker> In another aspect, the present disclosure provides a combination of (1) a factor that interacts with a host T cell immunocompetence marker and (2) a factor that interacts with a disease diagnostic marker. This combination is used to predict the pathology, severity, prognosis, and / or the effect or prognosis of treatment (therapeutic or preventive) of a T cell-related disease, and is characterized in that it can make highly accurate predictions even in important aspects of the prognosis of cancer treatment, such as invasion and metastasis.

[0129] In another aspect, the present disclosure provides a combination of (1) a factor that interacts with a host T-cell immunocompetence marker and (2) a factor that interacts with a disease progression diagnostic marker. This combination is used to predict the effect or prognosis of cancer treatment (therapeutic or preventive), and is characterized by its ability to make highly accurate predictions, particularly in important aspects of the prognosis of cancer treatment, such as invasion and metastasis.

[0130] In one embodiment, the combination of the present disclosure is used to predict the effect and prognosis of treatment (therapeutic or preventive) for a disease or condition primarily driven by a T-cell response, such as an autoantigen (including cancer), a foreign antigen (including a pathogen, a vaccine, or a transplant), or an immunomodulatory drug. In one embodiment, the combination of the present disclosure is used to evaluate T-cell immune function and / or tissue damage, predict cancer invasion, metastasis, or recurrence, and / or predict the therapeutic effect of an immunomodulatory drug, including an immune checkpoint inhibitor.

[0131] In one aspect of the combination of factors of the present disclosure, the host T cell immunocompetence markers of the present disclosure include bsPD-L1, MMP D group, and interferon-γ.

[0132] In one aspect of the combination of factors of the present disclosure, the disease diagnostic marker of the present disclosure includes at least one selected from the group consisting of MMP A group.

[0133] In one aspect of the combination of factors of the present disclosure, in one embodiment, the disease diagnostic marker of the present disclosure comprises at least one selected from the group consisting of MMP B group, preferably at least one selected from the group consisting of MMP B group, more preferably at least one selected from the group consisting of MMP C group.

[0134] In a preferred embodiment, in the case of cancer, (1) the host T-cell immunocompetence marker is detected before treatment, and (2) the disease progression diagnostic marker is detected by utilizing the change in value during treatment.

[0135] In a preferred embodiment, in the case of a T cell-related disease other than cancer, (1) a host T cell immunocompetence marker and (2) a disease progression diagnostic marker are detected using changes in values ​​before and / or during treatment.

[0136] In one embodiment, the combination of the present disclosure is used to predict the efficacy and / or prognosis of cancer treatment (such as treatment or prevention), or to predict the pathology of cancer.

[0137] In one aspect of the combination of factors of the present disclosure, in one embodiment, the host T cell immunocompetence marker is bsPD-L1 or MMP13.

[0138] In one aspect of the combination of factors of the present disclosure, in another embodiment, the disease diagnostic marker is MMP3 and / or MMP13.

[0139] In one aspect of the combination of factors of the present disclosure, in a specific embodiment, the host T-cell immunocompetence marker is bsPD-L1 or MMP13, and the disease progression diagnostic marker is MMP3 and / or MMP13.

[0140] Thus, in one aspect of the combination of factors of the present disclosure, in a specific embodiment, the combination of the present disclosure is (A) (1) the host T-cell immune function marker is bsPD-L1, and (2) the disease progression diagnostic marker is MMP3; (B) (1) the host T-cell immune function marker is bsPD-L1, and (2) the disease progression diagnostic marker is MMP13; (C) (1) the host T-cell immune function marker is MMP13, and (2) the disease progression diagnostic marker is MMP3; or (D) (1) the host T-cell immune function marker is MMP13, and (2) the disease progression diagnostic marker is MMP13.

[0141] In one embodiment, (1) host T-cell immunocompetence markers and / or (2) disease progression diagnostic markers are measured before and after treatment, and / or changes can be used. In this case, "before treatment" refers to, for example, when treatment with an ICI is initiated or when values ​​are measured at the start of treatment, and these values ​​can be used. Measurements are performed so that the amount of change in the marker can be calculated from the value measured after treatment. Typically, this calculation can be performed by measuring the same marker before treatment, but is not limited to this. Even if the pre-measurement value of a post-treatment marker is not directly available, the technology of the present disclosure can be applied if the pre-treatment measurement value can be estimated using other methods (related markers, etc.). Without wishing to be bound by theory, the present disclosure has shown that host T-cell immunocompetence markers are hardly affected by immune checkpoint inhibitors and exhibit patient-specific values. Therefore, it is understood that even if pre-treatment measurement is forgotten, values ​​after treatment initiation can be used as a substitute. Even if pre-treatment measurement of a disease progression diagnostic marker is forgotten, it is possible to diagnose the worsening or improvement of disease progression using other methods, such as measuring two points after treatment initiation. As used herein, "before and after treatment (treatment or prevention)" includes measurements at one or two points, and is understood to also include measurements at two or more subsequent points. Prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high mortality risk, and poor OS by confirming increases or decreases in disease diagnostic markers such as MMPs after administration). The timing of measurement is not particularly limited, and disease diagnostic markers can be measured at any time point from immediately after the start of treatment to the completion of treatment. For example, the measurement may be performed on the same day as treatment, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days after treatment, or later, such as 3, 4, or 5 weeks after the start of treatment.

[0142] In general, the combinations of the present disclosure can be used as follows.

[0143]

[0144] ​In one embodiment of the present disclosure, the prediction in the combination, agent, element, composition, system, kit, biomarker, or method of the present disclosure is: (1) in the case of cancer, using MMP13 (or bsPD-L1 as an alternative) as an indicator of immune function, and if it cannot be measured before the start of treatment, a value after the start of treatment can be used as a substitute; using MMP3 and MMP13 as indicators of disease progression, and if it cannot be measured before the start of treatment, a value before and / or after the start of treatment can be used as a substitute at multiple points after the start of treatment; (2) in the case of T-cell-related disease, using MMP13 (or bsPD-L1 as an alternative) as an indicator of immune function, and if it cannot be measured before the start of treatment, a value before and / or after the start of treatment can be used as a substitute at multiple points after the start of treatment; using MMP3 and MMP13 as indicators of disease progression, and if it cannot be measured before the start of treatment, a value before and / or after the start of treatment can be used as a substitute at multiple points after the start of treatment.

[0145] In a specific embodiment, it can be used as follows:

[0146]

[0147]

[0148]

[0149]

[0150] In the present disclosure, these combinations are used for predicting cancer prognosis and predicting invasion, metastasis, and recurrence.

[0151] In the combination of the present disclosure, the agent of the present disclosure is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof, and combinations thereof. Specifically, in the combination of the present disclosure, the agent used in the present disclosure is an antibody or an antigen-binding fragment thereof, or a variant thereof. In the present disclosure, the antibody may be any antibody that can detect and preferably quantify the target marker, and although specificity is not necessarily required, it may be advantageous to use a specific antibody, as this reduces noise.

[0152] In a specific embodiment, in the combination of the present disclosure, the prediction comprises prediction of the therapeutic effect of an immune checkpoint inhibitor.

[0153] In another aspect of the present disclosure, the present disclosure provides a combination of (1) a host T-cell immunocompetence marker and (2) a disease progression diagnostic marker. The host T-cell immunocompetence markers in the present disclosure include bsPD-L1, MMP D group, and interferon-γ.

[0154] The disease diagnostic markers of the present disclosure include at least one selected from the group consisting of MMP A group.

[0155] In one embodiment, the disease diagnostic marker of the present disclosure comprises at least one selected from the group consisting of MMP B group, preferably at least one selected from the group consisting of MMP B group, more preferably at least one selected from the group consisting of MMP C group.

[0156] In one embodiment, the marker of host T cell immunocompetence is bsPD-L1 or MMP13.

[0157] In another embodiment, the disease diagnostic marker is MMP3 and / or MMP13.

[0158] In a specific embodiment, the host T-cell immunocompetence marker is bsPD-L1 or MMP13, and the disease progression diagnostic marker is MMP3 and / or MMP13.

[0159] In a specific embodiment, the host T cell immune function marker is bsPD-L1 or MMP13, and the disease progression diagnostic markers are MMP3 and MMP13. Without wishing to be bound by theory, MMP13 is a collagenase, which reflects the destruction of tissue structure and is thought to correlate with the risk of recurrence in cancer. On the other hand, MMP3 has a greater effect because it degrades a wider variety of substrates than MMP13, and is therefore thought to correlate with the risk of death. Therefore, it is understood that combining the two markers will result in more accurate diagnosis. For example, if only MMP13 is elevated but MMP3 is not elevated, there may be cases where patients survive long-term despite metastasis. Therefore, to accurately determine the overall prognosis, more accurate diagnosis and treatment can be achieved by using both markers rather than just one marker alone; however, the present disclosure is not limited thereto.

[0160] In a specific embodiment, the host T-cell immune function marker is MMP13, and the disease diagnostic markers are MMP3 and MMP13. Without wishing to be bound by theory, MMP13 is involved in the destruction of extracellular matrix structure and is correlated with cancer metastasis and recurrence, while MMP3 degrades various substrates and membrane proteins and has a broader range of effects than MMP13, and is therefore thought to be correlated with mortality risk. Therefore, if MMP13 is elevated but MMP3 is decreased, a situation may arise in which patients survive despite metastasis. Therefore, combining MMP13 and MMP3 makes it possible to identify high-risk groups prone to both recurrence and death, which is a preferred embodiment, but the present disclosure is not limited thereto.

[0161] Thus, in specific embodiments, the combination of the present disclosure is: (A) (1) the host T-cell immune function marker is bsPD-L1, and (2) the disease progression diagnostic marker is MMP3; (B) (1) the host T-cell immune function marker is bsPD-L1, and (2) the disease progression diagnostic marker is MMP13; (C) (1) the host T-cell immune function marker is MMP13, and (2) the disease progression diagnostic marker is MMP3; or (D) (1) the host T-cell immune function marker is MMP13, and (2) the disease progression diagnostic marker is MMP13.

[0162] In another aspect, the present disclosure provides an agent, element, or composition for predicting the effect of cancer treatment or prevention or predicting prognosis, the agent, element, or composition comprising (1) a factor that interacts with a host T-cell immune marker, wherein (1) is used in combination with (2) a factor that interacts with a disease status diagnostic marker. In this aspect of the disclosure, any of the embodiments described in <MMPs as disease status diagnostic markers>, <Uses of bsPD-L1>, and <Combination of host T-cell immune status markers and disease status diagnostic markers> herein may be employed, and any combination thereof may be employed in the agent, element, or composition. Prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high risk of death, and poor OS by confirming increases or decreases in disease status diagnostic markers such as MMPs after administration).

[0163] In yet another aspect, the present disclosure provides (2) an agent, element, or composition for predicting the effect of cancer treatment or prevention or predicting prognosis, the agent, element, or composition comprising a factor that interacts with a disease status diagnostic marker, wherein (2) is used in combination with (1) a factor that interacts with a host T-cell immune function marker. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations described in the sections <MMPs as disease status diagnostic markers>, <Uses of bsPD-L1>, and <Combination of host T-cell immune function markers and disease status diagnostic markers> herein may be employed. Prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high risk of death, and poor OS by confirming increases or decreases in disease status diagnostic markers such as MMPs after administration).

[0164] In another aspect of the present disclosure, the present disclosure provides a method for assisting in predicting the effect or prognosis of cancer treatment or prevention, the method comprising the steps of detecting (1) a host T cell immune function marker and (2) a disease diagnostic marker. The prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high mortality risk, and poor OS by confirming increases or decreases in disease diagnostic markers such as MMPs after administration).

[0165] In another aspect, the present disclosure provides a method for predicting the effect of cancer treatment or prevention or predicting the prognosis in a subject, the method comprising the steps of detecting (1) a host T-cell immune function marker and (2) a disease progression diagnostic marker in a sample obtained from the subject, and calculating an index related to the prediction of the pathology, severity, prognosis, and therapeutic effect of a T-cell-related disease in the subject from the values ​​of the (1) host T-cell immune function marker and the (2) disease progression diagnostic marker.

[0166] In one embodiment, the present disclosure provides a method for predicting the therapeutic effect of an immune checkpoint inhibitor, wherein the combination comprises using biological samples obtained before and after the treatment and measuring the concentrations of the following biomarkers (1) and (2) in the biological samples: the concentration of (1) in the biological sample obtained before the treatment and the concentration of (2) in the biological samples obtained before and after the treatment.

[0167] Without wishing to be bound by theory, immune checkpoint inhibitors (ICIs) targeting PD-1 and its ligand PD-L1 play an important role in the treatment of various solid cancers, including non-small cell lung cancer (NSCLC) and gastric cancer (GC). However, because the composition of the immune microenvironment is highly heterogeneous among patients, only a small proportion of patients respond to ICI treatment, and a significant proportion of patients who do not respond to ICI treatment are known to exhibit hyperprogressive disease (HPD) during ICI treatment. In this regard, the present disclosure provides a reliable biomarker for assessing tumor microenvironment (TME) heterogeneity and predicting the efficacy of ICI treatment.

[0168] Early studies using PD-1-deficient mice and blocking antibodies against PD-1 or PD-L1 have revealed the immunosuppressive role of PD-1 / PD-L1 signaling in anti-tumor and anti-viral immunity. PD-L1 is expressed on various types of cells, including immune cells and tumor cells, and is said to transmit negative signals by binding to PD-1 on T cells.

[0169] PD-L1 expression in tumors is known as the first predictive marker for selecting patients for cancer immunotherapy, but its predictive accuracy is insufficient. In addition to the membrane-bound form of PD-L1, a soluble form of PD-L1 (sPD-L1) is also detected in peripheral blood, and several mechanisms for its production (e.g., proteolytic cleavage, splicing, exosomal PD-L1 secretion, etc.) are known. PD-L1 is selectively cleaved in vitro by MMPs such as MMP13 and MMP9, but many conflicting results have been reported regarding the function of sPD-L1. While MMPs are known to play a role in cancer invasion and metastasis due to their ability to cleave extracellular matrix components, their role in T-cell responses remains unknown. In this disclosure, the inventors have elucidated the role of MMPs in regulating T-cell responses within the TME.

[0170] The present inventors have demonstrated that functional sPD-L1 binds to the PD-1 receptor and have developed an ELISA system to specifically detect sPD-L1 (bsPD-L1) with PD-1 binding ability. This disclosure further clarifies the plasma concentrations of bsPD-L1 and MMPs and their clinical significance in GC patients and NSCLC patients administered immune checkpoint inhibitors.

[0171] In another embodiment, in the present disclosure, the prediction includes prediction of a therapeutic effect of an immune checkpoint inhibitor, wherein the combination includes using biological samples obtained before and after the treatment and measuring concentrations of the following biomarkers (a) and (b) in the biological samples: (a) the concentration of bsPD-L1, which is (1), in the biological sample obtained before the treatment, and (b) the concentration of MMP3, which is (2), in the biological sample obtained before and after the treatment.

[0172] In one embodiment, the present disclosure predicts that the therapeutic effect of an immune checkpoint inhibitor will be high if bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration in the biological sample is reduced between before and after treatment.

[0173] In one embodiment, the present disclosure predicts that the therapeutic effect of an immune checkpoint inhibitor will be low if bsPD-L1 is positive in a biological sample obtained before treatment and the MMP3 concentration in the biological sample is increased before and after treatment.

[0174] In another embodiment, the disclosure provides a method for stratifying a subject regarding their sensitivity to treatment with an immune checkpoint inhibitor, comprising measuring the concentration of bsPD-1 in a biological sample obtained from the subject prior to treatment.

[0175] In yet another embodiment, the present disclosure further relates to obtaining biological samples from the subject before and after treatment, and associating a lower MMP3 concentration in the biological sample after treatment with a case of immune checkpoint inhibitor efficacy compared to that before treatment.

[0176] In yet another embodiment, the present disclosure further provides for obtaining biological samples from the subject before and after treatment, and correlating a higher MMP3 concentration in the biological sample after treatment compared to that before treatment with an immune checkpoint inhibitor non-response case.

[0177] In one aspect of the present disclosure, reagents, kits, systems, etc. for detecting the combination of markers disclosed herein are provided. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as diagnostic markers for disease status> and <Use of bsPD-L1> and <Combination of host T-cell immune function marker and diagnostic marker for disease status> herein may be employed.

[0178] In one aspect of the present disclosure, the present disclosure provides a kit for use in predicting the pathology, severity, prognosis, and / or efficacy of treatment (therapeutic or preventive) or prognosis of a T-cell-related disease, the kit comprising the agent, element, or composition described in any one of the above items, which detects (1) a host T-cell immune function marker, (2) a disease status diagnostic marker, or a combination thereof, and a substance used for detection using the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as disease status diagnostic markers> and <Uses of bsPD-L1> and <Combination of host T-cell immune function markers and disease status diagnostic markers> herein may be employed.

[0179] In one aspect of the present disclosure, the present disclosure provides a kit for use in predicting the efficacy or prognosis of cancer treatment or prevention, comprising the agent, element, or composition described in any one of the above items, which detects (1) a host T-cell immune marker, (2) a disease status diagnostic marker, or a combination thereof, and a substance used for detection using the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations described in the sections <MMPs as disease status diagnostic markers>, <Uses of bsPD-L1>, and <Combination of host T-cell immune marker and disease status diagnostic marker> herein may be employed. Prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high risk of death, and poor OS by confirming increases or decreases in disease status diagnostic markers such as MMPs after administration).

[0180] In one aspect of the present disclosure, the present disclosure provides a system for predicting the pathology, severity, prognosis, and / or effect of treatment (therapeutic or preventive) for a T cell-related disease, the system comprising: (1) a factor that interacts with a host T cell immunocompetence marker; (2) a factor that interacts with a disease status diagnostic marker; a substance used for detection using the agent, element, or composition; an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used for detecting a signal resulting from the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as disease status diagnostic markers> and <Uses of bsPD-L1> and <Combination of host T cell immunocompetence markers and disease status diagnostic markers> herein may be employed. The prognosis and prediction of these effects include monitoring the target disease during treatment (predicting disease progression, high risk of death, and poor OS by confirming increases and decreases in disease diagnostic markers such as MMPs after administration).

[0181] In one aspect of the present disclosure, the present disclosure provides a system for predicting the efficacy or prognosis of cancer treatment or prevention, the system comprising: (1) a factor that interacts with a host T-cell immunocompetence marker; (2) a factor that interacts with a disease status diagnostic marker; a substance used for detection using the agent, element, or composition; an interaction moiety that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations described in the sections <MMPs as disease status diagnostic markers>, <Uses of bsPD-L1>, and <Combination of host T-cell immunocompetence markers and disease status diagnostic markers> herein may be employed. Prognosis and prediction of these effects include monitoring during treatment of the target disease (predicting disease progression, high mortality risk, and poor OS by confirming increases or decreases in disease status diagnostic markers, such as MMPs, after administration).

[0182] In the combinations of the present disclosure, other embodiments than those described above can be envisioned, but it is understood that any of the embodiments and combinations thereof described in <MMPs as diagnostic markers for disease status> and <Uses of bsPD-L1> and <Combination of host T-cell immune function markers and diagnostic markers for disease status> herein can be optionally employed.

[0183] <Combination of markers measured before treatment and markers measured before and after treatment>

[0184] In another aspect, the present disclosure provides a combination of (A) an agent that interacts with at least one MMP D group "before treatment" and (B) an agent that interacts with at least one MMP D group "before and after treatment."

[0185] In another aspect, the present disclosure provides (A) an agent, element, or composition for predicting the effect of cancer treatment or prevention or predicting prognosis, comprising a factor that interacts with at least one member of the MMP D group "before treatment," and (B) the agent, element, or composition is used in combination with a factor that interacts with at least one member of the MMP D group "before and after treatment."

[0186] In yet another aspect, the present disclosure provides an agent, element, or composition for predicting the effect of cancer treatment or prevention or predicting prognosis, comprising (B) a factor that interacts with at least one member of the MMP D group "before and after treatment," wherein the agent, element, or composition is used in combination with (A) a factor that interacts with at least one member of the MMP D group "before treatment."

[0187] In another aspect, the present disclosure provides a combination of (A) at least one MMP D group detected "before treatment" and (B) at least one MMP D group detected "before and after treatment."

[0188] In one aspect of the present disclosure, reagents, kits, systems, etc. for detecting the combination of markers disclosed herein are provided. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as diagnostic markers for disease status> and <Use of bsPD-L1> and <Combination of host T-cell immune function marker and diagnostic marker for disease status> herein may be employed.

[0189] In one aspect of the present disclosure, the present disclosure provides a kit for use in predicting the efficacy or prognosis of cancer treatment or prevention, the kit comprising: (A) a step of detecting at least one member of the D MMP group before treatment; and (B) an agent, element, or composition of the present disclosure that detects at least one member of the D MMP group or a combination thereof, and a substance used for detection using the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as diagnostic markers for disease status> and <Uses of bsPD-L1> and <Combination of a host T-cell immune function marker and a diagnostic marker for disease status> herein may be employed.

[0190] In one aspect of the present disclosure, the present disclosure provides a system for predicting the efficacy of cancer treatment or prevention or prognosis, the system comprising: (A) a factor that interacts with at least one MMP D group before treatment; (B) a factor that interacts with at least one MMP D group before and after treatment, or a factor that interacts with a combination thereof; a substance used for detection using the agent, element, or composition; an interaction portion that allows the agent, element, or composition to interact with a sample expected to contain the target of detection; and a detection means used to detect a signal resulting from the agent, element, or composition. In this aspect of the present disclosure, it is understood that any of the embodiments and combinations thereof described in <MMPs as diagnostic markers for disease progression>, <Uses of bsPD-L1>, and <Combination of a host T-cell immune function marker and a diagnostic marker for disease progression> herein may be employed. (A) The factor that interacts with at least one of the MMP D group before treatment and (B) the factor that interacts with at least one of the MMP D group before and after treatment may be the same or different.

[0191] It is understood that for specific embodiments of the MMP D group, descriptions elsewhere in this specification may be adopted as specific embodiments.

[0192] Specific Embodiments In one embodiment, the present disclosure clarifies the clinical significance of PD-1-binding soluble PD-L1 (bsPD-L1) and MMPs in the microenvironment of gastric cancer (GC) and non-small cell lung cancer (NSCLC) treated with ICI. In particular, the composition of the immune microenvironment is heterogeneous among cancer patients, which affects the therapeutic efficacy of immune checkpoint inhibitors. However, until the disclosure, reliable liquid biomarkers for assessing tumor microenvironment (TME) heterogeneity had not been provided, and the present disclosure provides a means for the first time to assess this heterogeneity. Because functional soluble PD-L1 (sPD-L1) binds to the PD-1 receptor, an ELISA system that specifically detects sPD-L1 (bsPD-L1) with PD-1 binding ability is particularly useful in the present disclosure.

[0193] In one exemplary embodiment, we analyzed the levels of bsPD-L1, MMPs, and IFN-γ in plasma samples from preoperative GC patients (n=117) and NSCLC patients (n=72) by ELISA before treatment and 2 months after ICI treatment (anti-PD-1, n=48; anti-PD-L1, n=24). Extracellular matrix status, PD-L1 expression, and T cell infiltration were analyzed by Elastica Masson-Goldner staining and immunohistochemistry using serial tumor tissue sections from 25 GC patients. bsPD-L1 was detected in 17 / 117 GC patients and 16 / 72 NSCLC patients. In both GC and NSCLC patients, bsPD-L1 showed a strong correlation with MMP13 and a moderate correlation with MMP3. In GC, bsPD-L1 expression correlated with IFN-γ levels and T cell infiltration in tumor tissue. Meanwhile, MMP13 levels were associated with the loss of extracellular matrix layer structure, allowing tumor cells to access blood vessels. We discovered that MMP3 and MMP13 changes during ICI treatment in NSCLC patients. Combination analysis of bsPD-L1 and MMP levels identified two patient groups. One group, characterized by bsPD-L1 positivity and high MMP13 levels in GC and increased bsPD-L1 positivity (MMP3 and MMP13) in NSCLC, is associated with poor clinical outcomes. The other group, characterized by bsPD-L1 positivity and low MMP13 levels in GC and decreased bsPD-L1 positivity (MMP3 or MMP13) in NSCLC, is understood to be associated with favorable clinical outcomes.

[0194] Thus, in one embodiment of the present disclosure, bsPD-L1 is useful as an indicator of T cell response, and MMP13 is useful as an indicator of the state of the extracellular matrix in the TME. It is understood that the combination of bsPD-L1 and MMPs may be useful not only for predicting the efficacy of ICI treatment in NSCLC, but also as a non-invasive tool for predicting early recurrence in GC.

[0195] (Specific Embodiments) In specific embodiments, the present disclosure provides a combination of biomarkers (a) and (b) below for predicting the therapeutic effect of immune checkpoint inhibitors (ICIs) (hereinafter also referred to as the "biomarker combination" of the present disclosure): (a) bound soluble PD-L1 or at least one of MMP D group, (b) at least one of MMP A group; or (a) bound soluble PD-L1, (b) matrix metalloproteinase (MMP3 / matrix metalloproteinase) A group, preferably B group, more preferably C group, and in a specific embodiment, MMP3. More preferably, the combination may be: (a) bsPD-L1 and / or MMP13, (b) MMP3 and / or MMP13.

[0196] In this particular embodiment, one of the components of the biomarker combination of the present disclosure, (a) bsPD-L, is indicative of a T cell immune response.

[0197] PD-L1 in the embodiments of the present invention may be, for example, a protein having the sequence of SEQ ID NO: 1, or may have any other amino acid sequence known as PD-L1.

[0198] The sPD-L1 of the embodiment of the present invention may be a protein having the sequence of PD-L1-1: SEQ ID NO: 2, PD-L1-3: SEQ ID NO: 3, PD-L1-9: SEQ ID NO: 4, or PD-L1-12: SEQ ID NO: 5, or may have any other amino acid sequence known as sPD-L1.

[0199] The MMP-3 of the embodiment of the present invention may be a protein having the sequence of pro MMP-3: SEQ ID NO: 6 or mature MMP-3: SEQ ID NO: 7, or may have any amino acid sequence known as other MMP-3.

[0200] The MMP-13 according to the embodiment of the present invention may be a protein having the sequence of SEQ ID NO: 8 for pro MMP-13 or SEQ ID NO: 9 for mature MMP-13, or may have any amino acid sequence known as other MMP-13.

[0201] In this specific embodiment, bsPD-L1 refers to soluble PD-L1 that has the ability to bind to PD-1. Soluble PD-L1 may be a soluble protein obtained by removing the transmembrane domain from (membrane-type) PD-L1 having a sequence such as SEQ ID NO: 1, or may have any amino acid sequence known as soluble PD-L1 (SEQ ID NOs: 2 to 5, etc.). Various mechanisms for the production of soluble PD-L1 have been reported. Examples include selective proteolytic cleavage of PD-L1 by the matrix metalloproteinase (MMP) family and the disintegrin and metalloproteinase (ADAM) family (see [1] to [3] below). [1] Dezutter-Dambuyant C, et al., "A novel regulation of PD-1 ligands on mesenchymal stromal cells through MMP-mediated proteolytic cleavage." Oncoimmunology. 2015 Oct 29;5(3):e1091146. [2] Hira-Miyazawa M, et al. , “Regulation of programmed-death ligand in the human head and neck squamous cell carcinoma microenvironment is ”Int J Oncol. 2018 Feb;52(2):379-388. [3] Romero Y, et al. , “Proteolytic processing of PD-L1 by ADAM proteases in breast cancer cells.”Cancer Immunol Immunother. 2020 Jan; 69(1): 43-55. ).

[0202] In this specific embodiment, one aspect of bsPD-L1 in the present disclosure is glycosylated soluble PD-L1. The binding ability of soluble PD-L1 to PD-1 depends on glycosylation, but the degree or site of glycosylation of bsPD-L1 need not be particularly limited as long as it has high binding ability to PD-1. An example of bsPD-L1 is one that contains a glycosylation chain and has a molecular weight of approximately 45 to 65 Kd. Due to these properties, bsPD-L1 can be used as a host T cell immune function marker.

[0203] In this specific embodiment, (b) MMP3, another component of the biomarker combination of the present disclosure, is a proteolytic enzyme produced and secreted by synovial cells and chondrocytes, which acts to degrade tissue matrix components such as cartilage proteoglycans and collagen. Since blood levels of MMP3 increase, reflecting synovial destruction and proliferation in joints, it is useful as an indicator of synovitis in rheumatoid arthritis (RA). In the present disclosure, MMP3 also serves as an indicator of tissue damage. Therefore, MMP3 can be used as a disease diagnostic marker (tumor invasion / metastasis marker).

[0204] In this specific embodiment, (b) MMP13, another component of the biomarker combination of the present disclosure, is a proteolytic enzyme produced and secreted by chondrocytes and fibroblasts, and has the ability to degrade tissue matrix components such as collagen. This disclosure also uses it as an indicator of tissue damage. Furthermore, MMP13 has a strong correlation with bsPD-L1, and has been found to be useful not only as a disease diagnostic marker (in this case, it is also used as a marker for tumor invasion and metastasis), but also as a marker for host T-cell immunity.

[0205] In this specific embodiment, as will be shown in the Examples below, a strong immune response increases the likelihood of cancer metastasis due to tissue damage. By combining biomarkers (a) bsPD-L and / or MMP13, which are indicative of T cell immune responses, with biomarkers (b) MMP3 and / or MMP13, which are indicative of tissue damage, it becomes possible to predict patients who have a "strong immune response but are unlikely to develop metastasis" and patients who have an "overly strong immune response and are therefore likely to develop metastasis."

[0206] In this particular embodiment, the biomarker combination of the present disclosure is specifically predictive of, and can be used to predict, the therapeutic effect of immune checkpoint inhibitors (ICIs).

[0207] As described in detail herein, an "immune checkpoint inhibitor (ICI)" is a compound that can bind to an immune checkpoint molecule or its ligand, inhibiting the transmission of immunosuppressive signals, thereby relieving the suppression of T cell activation by the immune checkpoint molecule. Specific examples include compounds that inhibit PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, and / or KIR. When PD-1 expressed on activated T cells binds to PD-L1 expressed on cancer cells, antigen-presenting cells, etc., T cell activation is suppressed, thereby suppressing immunity against cancer. Examples of compounds that inhibit PD-1 include anti-PD-1 antibodies, and examples of compounds that inhibit PD-L1 include anti-PD-L1 antibodies. Anti-PD-1 antibodies bind to PD-1 on T cells and inhibit the binding of PD-1 to PD-L1, thereby blocking the transmission of inhibitory signals and maintaining T cell activation. Anti-PD-L1 antibodies bind to PD-L1 expressed on cancer cells, antigen-presenting cells, etc., thereby inhibiting interaction with PD-1 on T cells, thereby inhibiting inhibitory signaling to T cells and maintaining T cell activation. Known anti-PD-1 antibodies include nivolumab and pembrolizumab, and known anti-PD-L1 antibodies include atezolizumab, durvalumab, and avelumab.

[0208] In one embodiment, ICIs further specifically include, but are not limited to, nivolumab, pembrolizumab, durvalumab, avelumab, atezolizumab, cemiplimab, ipilimumab, and tremelimumab.

[0209] In this specific embodiment, the disease to be treated by ICI is not particularly limited as long as ICI is effective, and may be a disease involving T cells. Preferably, the target disease is cancer. Examples of cancer include carcinoma, squamous cell carcinoma (cancer of the cervix, eyelid, conjunctiva, vaginal lung, oral cavity, skin, bladder, tongue, larynx, and esophagus), and adenocarcinoma (cancer of the prostate, small intestine, endometrium, cervix, colon, lung, pancreas, esophagus, rectum, uterus, stomach, breast, and ovary). Furthermore, sarcoma (e.g., myogenic sarcoma), leukemia, neuroma, melanoma, and lymphoma are also included. A more preferred target disease is lung cancer.

[0210] (Technology for predicting, diagnosing, and assisting in the prediction of ICI treatment efficacy) In this particular embodiment, the present disclosure provides a method for predicting or assisting in the prediction of ICI treatment efficacy using a combination of biomarkers disclosed herein (hereinafter also referred to as the "ICI prediction, diagnosing, and assisting method" of the present disclosure), as well as related technologies.

[0211] In this particular embodiment, one embodiment of the predictive diagnostic / support method of the present disclosure is as follows: a method comprising steps of using biological samples obtained before and after treatment and measuring the concentrations of the following biomarkers (a) and (b) in the biological samples: (a) the concentration of bsPD-L1 and / or MMP13 in the biological sample obtained before treatment; (b) the concentration of MMP3 and / or MMP13 in the biological sample obtained before and after treatment; or (a) the concentration of bsPD-L1 in the biological sample obtained before treatment; (b) the concentration of MMP3 in the biological sample obtained before and after treatment.

[0212] Here, ICI, biomarker (a) bsPD-L1, and biomarker (b) MMP3 have the same meanings as those described elsewhere in this specification.

[0213] In this specific embodiment, the "biological sample" used in the present disclosure need not be particularly limited as long as it is a sample derived from a living organism, and various biological samples derived from a subject can be used. It is sufficient that the biomarkers (a) bsPD-L1 and / or MMP13 and (b) MMP3 and / or MMP13 may be present; it is not essential that these biomarkers are not present. Biological samples can include samples directly collected from a living organism, samples obtained by washing or crushing such samples, and the like. Examples of such samples include blood, tissue washings such as those of alveoli, urine, cerebrospinal fluid, and tissue sections. Blood is preferably used. Examples of blood include, but are not limited to, plasma and serum. Depending on the method (system) for detecting and quantifying bsPD-L1 and / or MMP13 and MMP3 and / or MMP13, these biological samples can be used directly or after certain pretreatment to prepare measurement samples. The subject need not be particularly limited as long as it is required to detect and quantify bsPD-L1 and / or MMP13, and MMP3 and / or MMP13 in a biological sample, and may be a patient whose pathology or immune response is expected to change due to the administration of an ICI, as well as a healthy subject who can serve as a control, or a patient not receiving treatment with an ICI. Patients with cancer, which is a currently applicable disease, and patients with infectious diseases, which may be applicable in the future, are preferred subjects.

[0214] In this particular embodiment, the disclosure includes measuring the concentration of bsPD-L1 and / or MMP13 and the concentration of MMP3 and / or MMP13 in a biological sample.

[0215] In this specific embodiment, the method for measuring the concentration of bsPD-L1 is not particularly limited as long as it is a method that can measure the concentration of bsPD-L1 in a biological sample. Preferably, the method is an ELISA method (Patent Document 3, Non-Patent Document 5) developed by the present inventors, which uses a carrier on which PD-1 protein is immobilized (for convenience, this method may be referred to as a new ELISA method).

[0216] In this specific embodiment, the method for measuring the concentration of MMP3 and / or MMP13 is not particularly limited as long as it can measure the concentration of MMP3 in a biological sample, and examples thereof include ELISA using a carrier on which an anti-MMP3 antibody is immobilized. Such ELISA may be provided as a kit (e.g., Human Total MMP-3 DuoSet ELISA kit (R&D#DY513) or Human Total MMP-13 DuoSet ELISA kit (R&D#DY511)).

[0217] In one embodiment, the present disclosure provides a method for predicting or assisting in predicting the therapeutic effect of an ICI in a subject, particularly the therapeutic effect on cancer (preferably lung cancer), using biological samples obtained from the subject before and / or after treatment, comprising measuring the concentration of bsPD-L1 and / or MMP13 in the biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in the biological samples obtained before and after treatment.

[0218] In this specific embodiment, as will be apparent from the examples described below, when bsPD-L1 is positive and / or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in the biological sample decrease before and after treatment, it can be predicted that the therapeutic effect of ICI will be high; and when bsPD-L1 is positive and / or MMP13 is high in a biological sample obtained before treatment and the concentrations of MMP3 and / or MMP13 in the biological sample increase before and after treatment, it can be predicted that the therapeutic effect of immune checkpoint inhibitors will be low.

[0219] (Method for stratifying patients) A method for stratifying subjects with respect to their sensitivity to ICI treatment is provided, which comprises measuring the concentrations of bsPD-L1 and / or MMP13 as biomarkers in a biological sample obtained from the subject before treatment. Preferably, the method further comprises measuring the concentrations of MMP3 and / or MMP13, which are other biomarkers, in the biological sample obtained from the subject before and after treatment.

[0220] Here, stratification of subjects means dividing a population of subjects into groups based on their sensitivity to ICI treatment, and is a method that makes it possible to extract and exclude from treatment groups subjects who are insensitive or have low sensitivity.

[0221] If bsPD-L1 is positive and / or MMP13 is elevated in a biological sample obtained before treatment, the change in MMP3 and / or MMP13 concentration in the biological sample before and after treatment can be correlated with whether the ICI inhibitor, element, or composition is effective or ineffective. Specifically, a decrease in MMP3 and / or MMP13 concentration before and after treatment can be correlated with an effective ICI case. Furthermore, an increase in MMP3 and / or MMP13 concentration before and after treatment can be correlated with an ineffective ICI case.

[0222] Therefore, according to this method, patients for whom ICI is ineffective (worsens) can be detected at an earlier stage, and can be excluded from treatment.

[0223] (Diagnostic Reagent Composition) The present disclosure provides a diagnostic reagent composition for diagnosing the therapeutic effect of ICI, comprising the following (a) and (b) (hereinafter also referred to as the "reagent composition" of the present disclosure): (a) a means capable of detecting bsPD-L1 and / or MMP13; and (b) a means capable of detecting MMP3 and / or MMP13. These compositions may be provided as multiple types of compositions in which the means are separately separated.

[0224] The reagent composition of the present disclosure is a composition and system for detecting and quantifying bsPD-L1, MMP3, and MMP13 in a biological sample obtained from a subject. (a) Examples of means for detecting bsPD-L1 include a system that contains PD-1 protein and includes a means for reacting the protein with a biological sample and a means for detecting and quantifying soluble PD-L1 bound to the protein as bsPD-L1. Suitable systems for use in this regard include the new ELISA systems described in Patent Document 3 and Non-Patent Document 5. (b) Examples of means for detecting MMP3 and / or MMP13 include systems (e.g., ELISA) that include a means for reacting an anti-MMP3 antibody and / or an anti-MMP13 antibody with a biological sample and a means for detecting and quantifying MMP3 in the biological sample bound to the antibody (e.g., Human Total MMP-3 DuoSet ELISA kit (R&D #DY513), mHuman Total MMP-13 DuoSet ELISA kit (R&D #DY511)). <MMP3 and MMP13>

[0225] In one specific embodiment, the present disclosure provides an agent or composition for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathological condition, severity and / or prognosis, comprising at least one factor that interacts with a disease diagnostic marker, wherein the disease diagnostic marker comprises at least one member of the MMP C group.

[0226] In another embodiment, the present disclosure provides a kit for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising an agent that interacts with at least one selected from the group consisting of disease diagnostic markers, wherein the disease diagnostic marker is the MMPC group.

[0227] In another embodiment, the present disclosure provides a method for predicting the therapeutic and / or prophylactic effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathological condition, severity, and / or prognosis, comprising measuring at least one disease diagnostic marker, wherein the disease diagnostic marker comprises at least one of the MMP C group, and wherein the diagnostic result can be determined by the diagnostic method and can be used as a companion diagnostic.

[0228] In this case, the present disclosure provides a method for treating and / or preventing cancer and / or T-cell related diseases, comprising administering to the subject a therapeutic and / or preventive treatment for cancer and / or T-cell related diseases based on the prediction obtained by performing the diagnosis of the present disclosure.

[0229] In one embodiment, the treatments used in this companion diagnostic-based treatment include chemotherapy, radiation therapy, molecular targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof, and in certain embodiments, ICI.

[0230] In one embodiment, the disease diagnostic marker used in the present disclosure may be MMP13 or MMP3. In one embodiment, the disease diagnostic marker used in the present disclosure is MMP3. In another embodiment, the disease diagnostic marker used in the present disclosure is MMP13.

[0231] In one embodiment, the agent is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof and combinations thereof, and a mass spectrometry element.

[0232] In one specific embodiment, the present disclosure provides an agent or composition for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising a factor that interacts with MMP3 and / or MMP13.

[0233] In certain embodiments of the agents, elements, compositions and / or kits of the present disclosure, the treatment includes chemotherapy, radiation therapy, molecular targeted drugs, proton beam, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof, and in certain embodiments may be for predicting the effectiveness of ICI. The present disclosure may be for predicting the effectiveness of ICI.

[0234] In one embodiment, the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence.

[0235] In one embodiment, the agent, element, composition, and / or kit thereof disclosed herein can be used to stratify cancer patients into a group that responds well to ICI and a group whose cancer worsens due to ICI treatment, by measuring the host T cell immune function marker before treatment and measuring the disease progression diagnostic marker during treatment. <Combination of MMP13 / MMP3 / bsPD-L1>

[0236] In one embodiment, the present disclosure provides a combination of at least one factor that interacts with a disease diagnostic marker and at least one factor that interacts with a host T-cell immune function marker, which is provided for predicting the therapeutic and / or prophylactic effect of a treatment for cancer and / or a T-cell-related disease, or diagnosing the condition, severity, and / or prognosis of the disease.

[0237] In another embodiment, there is provided a kit for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell related diseases, or diagnosing the pathology, severity and / or prognosis, comprising at least one factor that interacts with a disease progression diagnostic marker and an factor that interacts with at least one factor that interacts with a host T-cell immune competence marker.

[0238] In one embodiment of the combination disclosed herein, the disease diagnostic marker comprises MMP13 or MMP3. In one embodiment of the combination disclosed herein, the host T-cell immune function marker comprises MMP13 or bsPDL1. In one embodiment of the combination disclosed herein, the disease diagnostic marker comprises MMP13 or MMP3, and the host T-cell immune function marker comprises MMP13 or bsPDL1.

[0239] In one embodiment, the present disclosure provides a combination of an agent that interacts with at least one of MMP13 or MMP3 and an agent that interacts with at least one of MMP13 or bsPDL1. In one embodiment, the combination is provided for predicting the therapeutic and / or prophylactic effect of treatment for cancer and / or T-cell related diseases, or diagnosing the pathology, severity and / or prognosis of cancer and / or T-cell related diseases.

[0240] In certain embodiments of the combinations and / or kits of the present disclosure, the treatments include chemotherapy, radiation therapy, molecularly targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof, and in certain embodiments may be for predicting the efficacy of ICI.

[0241] In one embodiment of the combination or kit thereof of the present disclosure, the MMP C group comprises MMP 13. In one embodiment of the combination or kit thereof of the present disclosure, the MMP C group comprises MMP 3. In one embodiment of the combination or kit thereof of the present disclosure, the MMP C group comprises MMP 13 and the MMP C group comprises MMP 3.

[0242] In one embodiment of the combination or kit thereof of the present disclosure, the disease diagnostic marker comprises MMP13 or MMP3. In one embodiment of the combination or kit thereof of the present disclosure, the host T-cell immunocompetence marker comprises MMP13 or bsPDL1.

[0243] In certain embodiments of the combinations and / or kits of the present disclosure, the treatments include chemotherapy, radiation therapy, molecularly targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof, and in certain embodiments may be for predicting the efficacy of ICI.

[0244] In one embodiment, the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence.

[0245] In one embodiment, the agent is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof and combinations thereof, and a mass spectrometry element.

[0246] In one embodiment, the combination or kit of the present disclosure allows stratification of patients into a group that responds well to ICI and a group whose cancer worsens due to ICI treatment by measuring the host T cell immune function marker before treatment and measuring the disease progression diagnostic marker during treatment.

[0247] In one embodiment, in the combination or kit thereof of the present disclosure, the host T-cell immune function marker is MMP13 and / or bsPDL1, and the disease diagnostic marker is MMP3 and / or MMP13.

[0248] In one embodiment, the combination or kit of the present disclosure can predict that the therapeutic effect of an immune checkpoint inhibitor will be poor when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment.

[0249] In one embodiment, the combination or kit of the present disclosure can predict a high therapeutic effect of an immune checkpoint inhibitor when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment.

[0250] In one embodiment, the combination or kit of the present disclosure can predict that, when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, (A) the therapeutic effect of the immune checkpoint inhibitor will be low if the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are higher than those before treatment, or (B) the therapeutic effect of the immune checkpoint inhibitor will be high if the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are lower than those before treatment.

[0251] In one embodiment of the present disclosure, in the combination or kit thereof of the present disclosure, the cancer and / or T-cell related disease can include at least one of lung cancer and non-small cell lung cancer.

[0252] In one embodiment of the present disclosure, the method of the present disclosure further comprises measuring at least one marker of host T cell immunocompetence.

[0253] In one embodiment of the present disclosure, the measurement in the present disclosure is performed by a factor that interacts with the marker.

[0254] In one embodiment of the present disclosure, the therapeutic or preventive effect of treatment for cancer or T-cell-related disease, or the pathological condition, severity, and prognosis can be predicted by measuring the host T-cell immune function marker before treatment and measuring the disease progression diagnostic marker during treatment, thereby stratifying patients into a group that responds well to ICI and a group of cancer patients whose cancer worsens due to ICI treatment.

[0255] In one embodiment of the present disclosure, when bsPD-L1 is positive or MMP13 is elevated in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment, it can be predicted that the therapeutic effect of an immune checkpoint inhibitor will be low.

[0256] In one embodiment of the present disclosure, when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment, it can be predicted that the therapeutic effect of an immune checkpoint inhibitor will be high.

[0257] In one embodiment of the present disclosure, when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, (A) if the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment, it is possible to predict that the therapeutic effect of the immune checkpoint inhibitor will be low, and (B) if the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment, it is possible to predict that the therapeutic effect of the immune checkpoint inhibitor will be high.

[0258] In one embodiment of the present disclosure, the cancer and / or T-cell related disease comprises at least one of lung cancer and non-small cell lung cancer.

[0259] The detection or diagnosis of the present disclosure is carried out using CLEIA (chemiluminescent enzyme immunoassay), CLIA (chemiluminescent immunoassay), or ELISA. ELISA is known to employ competitive and sandwich antigen measurement systems, with the sandwich method being preferred. Several embodiments of the present disclosure are described below.

[0260] Specific embodiments will be described below.

[0261] (CLIA (Chemiluminescent Immunoassay)) CLEIA, like ELISA, utilizes a combination of various antigen-antibody reactions and can be performed using the factors (e.g., antibodies) of the present disclosure. For example, enzyme activity can be detected by incorporating an enzyme-labeled antigen or antibody into a reaction system. Unlike ELISA, which calculates enzyme activity by measuring absorbance, CLEIA calculates enzyme activity by measuring the amount of luminescence. CLEIA reagents use antigen (or antibody)-bound magnetic particles. For example, antibodies, which are factors of the present disclosure, can be used. Reaction of the reagent with a sample results in an antigen (or antibody)-antibody (or antigen) reaction. This complex is attracted by magnetic force and then washed to remove any unreacted material, after which the enzyme-labeled antibody is reacted. Similarly, washing is performed to remove any unreacted material, and a chemiluminescent substrate is added, which is hydrolyzed by the enzyme in the complex to emit light. The target molecule in the sample is detected by measuring the amount of luminescence.

[0262] (CLIA (chemiluminescence immunoassay)) As with CLEIA, target molecules in a sample are detected by measuring the amount of luminescence. Unlike CLEIA, which uses an enzyme-labeled antibody, CLIA uses an antibody labeled with a chemiluminescent compound.

[0263] The ELISA (sandwich method) will be explained below.

[0264] A sample is added to the microcup with the antibody immobilized, and an antigen-antibody reaction is allowed to occur. An enzyme-labeled antibody can then be added to allow the antigen-antibody reaction to occur. Here, the factor disclosed herein can be used as the enzyme-labeled antibody or the antibody in the solid phase. After washing, the sample reacts with the enzyme substrate to develop color, and the absorbance is measured to calculate the amount of antibody (or antigen) in the sample. If the sample contains an antigen, it forms a sandwich structure of solid-phase antibody + antigen + enzyme-labeled antibody; if the antigen is not present, only the solid-phase antibody remains, and the color development according to the amount of enzyme is shown in the graph in the figure.

[0265] (General Techniques) The molecular biological, biochemical and microbiological techniques used herein are well known and commonly used in the art, and can be found in, for example, Sambrook J. et al. (1989). Molecular Cloning: A Laboratory Manual, Cold Spring Harbor and its 3rd Ed. (2001); Ausubel, FM (1987). Current Protocols in Molecular Biology, Greene Pub. Associates and Wiley-Interscience; Ausubel, FM (1989). Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology, Greene Pub. Associates and Wiley-Interscience; Innis, MA (1990). PCR Protocols: A Guide to Methods and Applications, Academic Press; Ausubel, FM (1992). Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology, Greene Pub. Associates; Ausubel, FM (1995). Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology, Greene Pub. Associates; Innis, MA et al. (1995). PCR Strategies, Academic Press; Ausubel, FM (1999).These methods are described in "Short Protocols in Molecular Biology: A Compendium of Methods from Current Protocols in Molecular Biology," Wiley, and annual updates; Sninsky, JJ et al. (1999); PCR Applications: Protocols for Functional Genomics, Academic Press; and "Experimental Methods for Gene Transfer and Expression Analysis," a special edition of Experimental Medicine, Yodosha, 1997, the relevant portions of which (possibly in their entirety) are incorporated herein by reference.

[0266] Regarding DNA synthesis technology and nucleic acid chemistry for producing artificially synthesized genes, gene synthesis and fragment synthesis services such as GeneArt, GenScript, and Integrated DNA Technologies (IDT) can be used. Other examples include Gait, MJ (1985). Oligonucleotide Synthesis: A Practical Approach, IRL Press; Gait, MJ (1990). Oligonucleotide Synthesis: A Practical Approach, IRL Press; Eckstein, F. (1991). Oligonucleotides and Analogues: A Practical Approach, IRL Press; Adams, RL et al. (1992). The Biochemistry of the Nucleic Acids, Chapman & Hall; Shabarova, Z. et al. (1994). Advanced Organic Chemistry of Nucleic Acids, Weinheim; Blackburn, GM et al. (1996). Nucleic Acids in Chemistry and Biology, Oxford University Press; Hermanson, GT (1996); Bioconjugate Techniques, Academic Press, etc., the relevant portions of which are incorporated herein by reference.

[0267] As used herein, "or" is used when "at least one or more" of the items listed in the text can be employed. The same applies to "alternative." When "within the range of" two values ​​is specified herein, the range includes the two values ​​themselves. References cited herein, such as scientific literature, patents, patent applications, etc., are incorporated herein by reference in their entirety to the same extent as if each were specifically set forth.

[0268] The present disclosure has been described above by showing preferred embodiments for ease of understanding. The present disclosure will be described below based on examples. However, the above description and the following examples are provided for illustrative purposes only and are not intended to limit the present disclosure. Therefore, the scope of the present disclosure is not limited to the embodiments or examples specifically described herein, but is limited only by the scope of the claims.

[0269] The present disclosure will be described in detail using examples, but these are not intended to limit the scope of the present disclosure. In addition, unless otherwise specified, the reagents and materials used are commercially available.

[0270] <<Outline of Methods>> 1. Samples For the experiment, blood samples collected from lung cancer or stomach cancer patients, or surgically resected specimens from stomach cancer patients, were used with the approval of the Ethics Committee of the Nippon Medical School Hospital and with informed consent. Details are as follows.

[0271] Plasma samples were collected from 117 patients diagnosed with gastric cancer (GC) between 2017 and 2020 at the Department of Gastroenterology and Hepatobiliary Pancreatic Surgery, Nippon Medical School Hospital. Blood samples were collected before surgery. Surgical resection specimens were collected from 25 GC patients. Plasma samples were collected from 72 patients diagnosed with non-small cell lung cancer (NSCLC) between 2017 and 2019 at the Department of Respiratory Medicine and Medical Oncology, Nippon Medical School Hospital. Blood samples were collected from patients before and 2 months after starting checkpoint immunotherapy. Biopsy tumor tissue samples were obtained from 59 NSCLC patients. Baseline clinical and demographic data were collected from patient medical records. The study protocol was reviewed and approved by the Nippon Medical School Ethics Committee. Written informed consent was obtained from all participants. This disclosure was conducted in accordance with the Declaration of Helsinki.

[0272] Enzyme-linked immunosorbent assay (ELISA) Human bsPD-L1 concentrations were measured as previously described (Takeuchi M, Doi T, Obayashi K, Hirai A, Yoneda K, Tanaka F, et al. Soluble PD-L1 with PD-1-binding capacity exists in the plasma of patients with non-small cell lung cancer. Immunol Lett. 2018;196:155-60. See also JP 2020-148631 and WO 2019 / 049974). Plasma concentrations of MMP3, MMP9, MMP13, and interferon (IFN)-γ were measured using ELISA kits (R&D systems #DY513, #DY911, #DY511, #DY285B) according to the manufacturer's instructions.

[0273] Histological Analysis Serial sections of formalin-fixed, paraffin-embedded tumor tissues were subjected to hematoxylin and eosin (H&E) staining, Elastica-Masson-Goldner (EMG) staining, or immunohistochemical staining. To evaluate PD-L1 expression in GC, tissue sections were stained using a PD-L1 immunohistochemical assay (Agilent Technologies, Santa Clara, CA, USA, #28-8 pharmDx) according to the manufacturer's instructions. PD-L1 expression in GC was quantified using a combined positive score (CPS). CPS indicates PD-L1 expression. ＋ It was defined as the number of tumor cells and immune cells (including lymphocytes and macrophages) divided by the total number of viable tumor cells multiplied by 100.

[0274] To assess PD-L1 expression in NSCLC, tissue sections were stained using a PD-L1 immunohistochemistry assay (Agilent Technologies, Santa Clara, CA, USA, #22C3 pharmDx) according to the manufacturer's instructions. PD-L1 expression was quantified using the tumor proportion score (TPS). TPS is a PD-L1 immunohistochemistry assay. ＋It is defined as the number of tumor cells divided by the total number of viable tumor cells multiplied by 100.

[0275] To identify T and B cells, sections were incubated with anti-CD3 (Abcam #ab5690) and anti-CD20 (Leica Biosystems #NCL-L-CD20-L26) antibodies and treated with Histofine Simple Stain MAX-PO® and MAX-PO® reagents (Nichirei Biosciences, Tokyo, Japan #424141 and #424131), respectively. Peroxidase activity was visualized using diaminobenzidine. Sections were counterstained with hematoxylin.

[0276] Histological images were acquired using a virtual slide scanner (NanoZoomer-SQ, #C13140-D03, Hamamatsu Photonics, Shizuoka, Japan). The areas of the tumor and T-cell clusters were calculated using NDP view2 software (Hamamatsu Photonics). The percentage of the T-cell cluster area was calculated by dividing the total area of ​​the T-cell clusters by the total area of ​​the tumor and multiplying by 100. CD3 expression in different areas of the tumor was measured using PatholoCount software Ver. 1.2.3 (Mitani Corporation, Tokyo, Japan). ＋ and CD3 － The number of nuclei in both CD3 and CD4 was counted. ＋ The percentage of T cells is CD3 ＋ The number of T cells was calculated by dividing the number of total surviving cells by the number of total surviving cells and multiplying by 100.

[0277] Statistical Analysis: Numerical variables were compared using the Mann-Whitney U test or Student's t-test, and categorical variables were compared using the Pearson chi-square test. Logistic regression analysis was used to identify factors of bsPD-L1 expression. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate the discriminatory ability of numerical variables (e.g., MMP3, MMP9, and MMP13 levels). Youden's index was used to identify optimal cutoff values. The optimal cutoff value for MMP13 levels was subsequently used to separate bsPD-L1-positive GC patients into two subgroups. Disease-free survival (DFS) was defined as the time from surgery to recurrence, secondary cancer, or all-cause death, whichever occurred first. Progression-free survival (PFS) was defined as the time from the start of treatment to disease progression or death. Overall survival (OS) was defined as the time from surgery or the start of treatment to the date of last follow-up or death from any cause. DFS, PFS, and OS were estimated using the Kaplan-Meier method, and intergroup differences were assessed using the log-rank test. Univariate and multivariate analyses of DFS, PFS, and OS were performed using Cox regression models. Only variables univariately associated with prognosis were included in the multivariate Cox regression analysis. All tests were two-sided, and a p value of <0.05 was considered statistically significant. All statistical analyses were performed using JMP software, version 13 (SAS Institute, Cary, NC, USA) and Prism software, version 8 (GraphPad, San Diego, CA, USA).

[0278] Example 1: bsPD-L1 and MMP concentrations in blood samples from GC patients

[0279] Correlation between bsPD-L1 and MMP13 Levels To examine the relationship between bsPD-L1 and MMPs, plasma levels of bsPD-L1 were measured by ELISA in GC patients (Figure 1A). bsPD-L1 was detected in 17 of 117 GC patients (14.5%). The expression pattern of bsPD-L1 was similar to that of MMP13 but distinct from that of MMP9. A strong positive correlation was observed between bsPD-L1 and MMP13 levels, and a moderate positive correlation was observed between bsPD-L1 and MMP3 levels (correlation coefficient [r] = 0.742, p < 0.0001; r = 0.534, p < 0.0001, respectively) (Figure 1B). There was no correlation between bsPD-L1 and MMP9 levels.

[0280] (Example 2: Discordance between bsPD-L1 levels in the blood of GC patients and PD-L1 expression in gastric cancer tissues) To investigate the relationship between bsPD-L1 levels in the blood and PD-L1 expression in tumor tissues, surgical specimens from 25 GC patients were analyzed using PD-L1 immunohistochemistry. PD-L1 expression was quantified using CPS (Figure 1C). As a result, 17, 6, and 2 patients exhibited low (CPS < 5), moderate (5 ≤ CPS < 10), and high (CPS ≥ 10) PD-L1 expression levels, respectively. No significant correlation was observed between bsPD-L1 levels and CPS (Figure 1D). These data suggest that bsPD-L1 levels in the blood do not correlate with PD-L1 expression in tumor tissues.

[0281] (Example 3: bsPD-L1 expression and background of GC patients) Gastric cancer patients (117 cases) tested in Examples 1 and 2 were divided into two groups based on bsPD-L1 expression, and the patient characteristics of each group are summarized in Table 19. No significant differences were observed between the groups for any of the variables.

[0282]

[0283] Example 4: Correlation between blood bsPD-L1 and IFN-γ levels in GC patients. Correlation between blood bsPD-L1 and IFN-γ levels. To evaluate the immunological status of GC patients, we compared the levels of inflammatory markers between the bsPD-L1-positive and bsPD-L1-negative groups (Figure 2). The neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) levels tended to be lower in the bsPD-L1-positive group than in the bsPD-L1-negative group, but the differences were not significant. On the other hand, the IFN-γ levels were significantly higher in the bsPD-L1-positive group than in the bsPD-L1-negative group, suggesting that bsPD-L1 correlates with IFN-γ production. Consistent with the results shown in Figure 1B, the bsPD-L1-positive group of GC patients had higher MMP3 and MMP13 levels than the bsPD-L1-negative group, but there was no significant difference in MMP9.

[0284] (Example 5: Correlation between blood bsPD-L1 concentration and T lymphocyte infiltration into tumor sites in GC patients) The correlation between bsPD-L1 levels and immune responses in tumor tissues obtained from 25 GC patients was investigated. Analysis of H&E images revealed that tumor tissues from bsPD-L1-positive patients contained more infiltrating lymphocytes than tumor tissues from bsPD-L1-negative patients (Figure 3). Immunohistochemical analysis using an anti-CD3 antibody revealed that tumor tissues from bsPD-L1-positive patients contained more CD3 T lymphocytes than tumor tissues from bsPD-L1-negative patients. ＋ The number of T cells was significantly higher (Figs. 3B, 4A, 4B).

[0285] Because bsPD-L1-positive patients had higher blood levels of the collagenase MMP13 than bsPD-L1-negative patients (Figure 2L), we evaluated the state of the extracellular matrix in tumor tissues by EMG staining (Figures 3A and 3B). The results revealed that the layered structure of the extracellular matrix in mucosal tissues was disrupted in tumors from bsPD-L1-positive patients. Specifically, whereas collagen fibers were strongly stained in tumor samples from bsPD-L1-negative patients, staining was weaker in bsPD-L1-positive patients, particularly in the perivascular regions of the tumors. These results suggest that perivascular collagen fibers are degraded in tumors from bsPD-L1-positive patients.

[0286] The inventors demonstrated a discrepancy between bsPD-L1 levels in the blood and PD-L1 expression in tumor tissues (Figure 1D). This discrepancy is presumably due to the fact that the anti-PD-L1 antibody used in immunohistochemistry recognizes the extracellular domain of PD-L1 and therefore cannot detect cleaved PD-L1 in tumor tissues. The source of bsPD-L1, whether released from tumors or other tissues, is unknown, and the possibility cannot be ruled out that patients with diseases or complications other than cancer may produce bsPD-L1 from tissues other than tumors. In clinical practice, patients are stratified and the indication for ICI therapy is determined based on PD-L1 expression in tumor tissue (Taube JM, Klein A, Brahmer JR, Xu H, Pan X, Kim JH, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin Cancer Res. 2014;20(19):5064-74, Hino R, KabashimaK, Kato Y, Yagi H, Nakamura M, Honjo T, et al. Tumor cell expression of programmed cell death-1 ligand 1 is a prognostic factor for malignant melanoma. Cancer. 2010;116(7):1757-66, Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 2015;372(21):2018-28.) It is also important to consider the possibility that membrane-type PD-L1 is cleaved and not expressed. Evaluation of PD-L1 expression by immunohistochemistry may lead to misinterpretation of the immune status of patients' TME.

[0287] (Example 6: Effect of blood bsPD-L1 concentration on the localization of tumor-infiltrating T lymphocytes in GC patients) Whether the loss of the extracellular matrix layer structure affects the localization of T cells within the TME was examined using H&E, EMG, and anti-CD3 immunohistochemical staining of tumor tissues obtained from GC patients (Figures 4C and 4D). H&E and EMG staining were used to define the boundary between the mucosal layer and the submucosal layer, and CD3 in each region was examined. ＋ The number of T cells was counted (Figures 3B, 4C, and 4D). Results showed that tumor tissues from bsPD-L1-positive patients had a high influx of T cells into the mucosal layer (adjacent to tumor cells). In contrast, tumors from bsPD-L1-negative patients had most T cells localized in the submucosal layer, with no infiltration of the mucosal layer (Figures 4C and 4D). These data suggest that bsPD-L1 levels may affect not only the strength of T cell responses against tumors but also the location of T cells in the TME.

[0288] (Example 7: Differential Roles of bsPD-L1 and MMP13 in GC Patients) Among bsPD-L1-positive GC patients analyzed histologically, one case (patient 86) had a relatively low level of MMP13 (Figure 8). This patient had numerous T cell infiltrations, but no infiltration was observed in the compartment containing tumor cells surrounded by collagen fibers. These results suggest that bsPD-L1 and MMP13 play different roles in the TME, with bsPD-L1 regulating T cell responses and MMP13 regulating T cell infiltration by altering the structure of the extracellular matrix layer.

[0289] (Example 8: Identifying GC patients at high risk of postoperative recurrence) We investigated whether MMP13 levels affect tumor invasion and metastasis in the TME (Figure 5A). Histological analysis of tumor tissue from patients with bsPD-L1-positive and high MMP13 levels revealed that collagen fibers almost completely disappeared, particularly in perivascular regions, and tumor cells were adjacent to blood vessels. In contrast, in tumor tissue from patients with bsPD-L1-positive and low MMP13 levels, tumor cells were isolated from the bloodstream by a thick layer of collagen fibers. These results raise the possibility that MMP13 levels may affect the vascular invasiveness of tumor cells.

[0290] Given the distinct roles of bsPD-L1 and MMP13 in TME, we investigated whether the combination of bsPD-L1 and MMP13 levels could serve as a predictor of postoperative recurrence and mortality in GC patients. Patients were divided into two groups based on bsPD-L1 expression, and bsPD-L1-positive patients were further divided into two groups based on MMP13 expression. ROC analysis was performed to select the optimal cutoff value for MMP13 levels relative to DFS. The AUC for MMP13 was 0.924, and this parameter had better discriminatory ability compared with the AUCs for MMP3 and MMP9 (0.591 and 0.546, respectively) (Figure 5B). The optimal cutoff value for MMP13 levels was 16,836 pg / ml. This value can be used as an example of a "high" MMP13 level when used as a diagnostic marker for disease progression.

[0291] The bsPD-L1-positive MMP13-high group showed shorter DFS and OS than the bsPD-L1-positive MMP13-low and bsPD-L1-negative groups (p = 0.0018 and p = 0.0014, respectively; Figures 5C and 5D). The bsPD-L1-positive MMP13-low group tended to have longer DFS and OS than the bsPD-L1-negative group. The median DFS in the bsPD-L1-positive MMP13-high group was 513 days, while the median DFS in the bsPD-L1-positive MMP13-low and bsPD-L1-negative groups was not reached. Sixty percent of the bsPD-L1-positive MMP13-high group recurred within 2 years after surgery (Figure 5E). Furthermore, all patients in the bsPD-L1-positive MMP13-high group died within 5 years after surgery (Figure 5D). These results suggest that patients at high risk of recurrence are included in the bsPD-L1-positive MMP13-high group.

[0292] Multivariate analysis using Cox regression model revealed that bsPD-L1 positive, high MMP13, lymph node metastasis (+), and distant metastasis (+) were independent poor prognostic factors for DFS in GC patients (p=0.015, p=0.003, and p<0.0001, respectively; Table 20). Among these parameters, distant metastasis was the only independent poor prognostic factor for OS (p=0.001; Table 21).

[0293]

[0294]

[0295] Example 9: Pretreatment bsPD-L1 and MMP Concentrations in Blood Samples from NSCLC Patients Pretreatment bsPD-L1 and MMP concentrations in plasma samples from 72 NSCLC patients were analyzed by ELISA (Figure 6). bsPD-L1 was detected in 16 of the 72 NSCLC patients (22.2%). The expression pattern of bsPD-L1 was consistent with that of GC patients (Figure 6A), similar to that of MMP13 but distinct from that of MMP9. bsPD-L1 strongly and moderately correlated with MMP13 (r=0.821, p<0.0001) and MMP3 (r=0.372, p=0.0013), respectively (Figure 6B).

[0296] Example 10: Changes in bsPD-L1 and MMP Levels During ICI Treatment in NSCLC Patients During ICI treatment, bsPD-L1 and MMPs exhibited distinct kinetic changes (Figure 6C). Two months after the start of treatment, MMP3, MMP9, and MMP13 levels increased in 44, 38, and 15 of 72 patients (61%, 53%, and 21%, respectively). Meanwhile, MMP3, MMP9, and MMP13 levels decreased in 28, 34, and 20 patients (39%, 47%, and 28%, respectively). Meanwhile, bsPD-L1 levels increased in 12 patients (17%), but there was little decrease in bsPD-L1 levels.

[0297] (Example 11: bsPD-L1 expression and background of NSCLC patients) Non-small cell lung cancer (NSCLC) patients (72 cases) tested in Examples 9 and 10 were divided into two groups based on pre-treatment bsPD-L1 expression, and the patient characteristics of each group are summarized in Table 22. No significant differences were observed between the groups for any of the variables.

[0298]

[0299] (Example 12: Correlation between blood bsPD-L1 concentration and inflammatory markers in NSCLC patients) To evaluate the immunological status of NSCLC patients, the levels of inflammatory markers were compared between the bsPD-L1-positive group and the bsPD-L1-negative group (Figure 9). The neutrophil count and CRP value were significantly higher in the bsPD-L1-positive group than in the bsPD-L1-negative group. － The levels of MMP13 were significantly lower in the bsPD-L1-positive group than in the bsPD-L1-negative group (p=0.0433 and p=0.0260, respectively). Among MMPs, only MMP13 levels were significantly higher in the bsPD-L1-positive group than in the bsPD-L1-negative group (p<0.0001). Multivariate analysis showed that high MMP13 levels were an independent factor associated with bsPD-L1 expression (Table 23).

[0300]

[0301] Example 13: Identification of NSCLC Patients Responding to ICI Therapy To investigate the clinical significance of bsPD-L1 in NSCLC patients receiving ICI therapy, the association between bsPD-L1 levels and PFS or OS was evaluated. We noted that the OS curves crossed at day 700 (Figure 7A). Before day 600, the OS rate was lower in bsPD-L1-positive patients than in bsPD-L1-negative patients, suggesting that the bsPD-L1-positive group included patients with rapidly progressing disease. Furthermore, the OS curves for bsPD-L1-positive patients reached a plateau at day 400, and after day 700, the OS rate of bsPD-L1-positive patients was higher than that of bsPD-L1-negative patients, suggesting that the bsPD-L1-positive group included patients with long-term response. These results suggest that the bsPD-L1-positive group may include two groups: patients with rapidly progressing disease and patients with long-term response.

[0302] Because MMP3, MMP9, and MMP13 concentrations changed during ICI treatment (Figure 6C), we investigated whether changes in MMP concentrations could stratify bsPD-L1-positive patients into responders and non-responders. Based on changes in MMP concentrations, bsPD-L1-positive patients were divided into an increased MMP group and a decreased MMP group at 2 months after ICI treatment (Figures 7B-D). The bsPD-L1-positive MMP3-increased group tended to have a shorter OS than the bsPD-L1-positive MMP3-decreased group (p=0.0554). The bsPD-L1-positive MMP13-increased group tended to have a shorter PFS than the bsPD-L1-positive MMP13-decreased group (p=0.0422). Changes in MMP9 were not associated with either PFS or OS (p=0.4642 and p=0.6470, respectively). These results suggest that increased MMP13 or MMP3 is associated with poor prognosis in bsPD-L1-positive patients.

[0303] Next, we evaluated the combined changes in MMP3 and MMP13 to improve predictive accuracy (Figures 7E and 7F). By combining these two markers, bsPD-L1-positive patients were divided into four groups: (i) increased MMP3 and increased MMP13, (ii) increased MMP3 and decreased MMP13, (iii) decreased MMP3 and increased MMP13, and (iv) decreased MMP3 and decreased MMP13. As shown in Figure 7E, increased MMP13 was strongly associated with a higher risk of disease progression, whereas increased MMP3 was strongly associated with a higher risk of death. This suggests that MMP3 and MMP13 may play different roles in the tumor microenvironment. These combined analyses demonstrate that increased MMP3 and MMP13 can identify patients who are refractory to ICI treatment (Figure 7F).

[0304] Finally, we evaluated patient stratification by combining pretreatment bsPD-L1 and MMP changes (Figure 7G). NSCLC patients were divided based on pretreatment bsPD-L1 expression, and bsPD-L1-positive patients were further divided by changes in MMP3 and MMP13 levels. The bsPD-L1-positive (MMP3 and MMP13) increased group had shorter PFS and OS than the other groups (p = 0.0119 and p = 0.0053, respectively). The bsPD-L1-positive (MMP3 or MMP13) decreased group tended to have longer PFS and OS than the bsPD-L1-negative group, but the differences were not significant. The median PFS for the bsPD-L1-positive (MMP3 and MMP13) increased group, bsPD-L1-positive (MMP3 or MMP13) decreased group, and bsPD-L1-negative group was 63 days, 151 days, and 217 days, respectively. The median OS in the bsPD-L1 positive (MMP3 and MMP13) increased group, bsPD-L1 positive (MMP3 or MMP13) decreased group, and bsPD-L1 negative group was 225 days, not reached, and 726 days, respectively.

[0305] Because bsPD-L1 is strongly correlated with MMP13 (Figure 6B), we investigated whether pretreatment bsPD-L1 could be substituted for pretreatment MMP13, i.e., whether it could reduce the number of variables in the combined analysis (see Figure 7H). ROC analysis was performed to select the optimal cutoff value for MMP13 levels relative to bsPD-L1 expression. The AUC was 0.950, demonstrating good discriminatory ability. Based on the optimal pretreatment MMP13 cutoff value (985 pg / ml), NSCLC patients were divided into high and low MMP13 groups, and the high MMP13 patients were further subdivided based on changes in MMP3 and MMP13 levels. This cutoff value can be used as an example, but is not limited to, a criterion for determining whether MMP13 is "high" when used as a host T-cell immune marker. The group with elevated MMP13 levels (MMP3 and MMP13) had shorter PFS and OS than the other groups (p = 0.0432 and p = 0.0218, respectively). The group with elevated MMP13 levels (MMP3 or MMP13) decreased tended to have longer PFS and OS than the group with low MMP13 levels, but the differences did not reach significance. The median PFS for the elevated MMP13 levels (MMP3 and MMP13) group, the decreased MMP13 levels (MMP3 or MMP13) group, and the low MMP13 level group were 63 days, 198 days, and 232 days, respectively. The median OS for the elevated MMP13 levels (MMP3 and MMP13) group, the decreased MMP13 levels (MMP3 or MMP13) group, and the low MMP13 level group were 229 days, not reached, and 719 days, respectively.

[0306] Multivariate analysis using Cox regression model revealed that bsPD-L1 positive (MMP3 and MMP13) status was an independent poor prognostic factor for PFS and OS in NSCLC patients (p=0.0069 and p=0.0166, respectively; Tables 24 and 25). High MMP13 (MMP3 and MMP13) status was also an independent poor prognostic factor for PFS and OS in NSCLC patients (p=0.0219 and p=0.032, respectively; Tables 26 and 27). Low tumor PD-L1 expression (TPS<50) was an independent poor prognostic factor for PFS, and high CRP (≥10 mg / L) was an independent poor prognostic factor for OS. The bsPD-L1 positive (MMP3 and MMP13) and MMP13 high (MMP3 and MMP13) statuses were able to identify patients at high risk of disease progression and death with higher predictive accuracy than TPS and CRP (Figures 7I-L).

[0307]

[0308]

[0309]

[0310]

[0311] (Discussion) (1) 15% of gastric cancer patients and 22% of non-small cell lung cancer patients were bsPD-L1 positive. (2) bsPD-L1 had a very strong correlation with MMP13, but a weak correlation with MMP3 and no correlation with MMP9. (3) High MMP13 levels were found to be an independent factor associated with bsPD-L1 expression. (4) Blood bsPD-L1 levels did not correlate with PD-L1 expression in tumor tissue. (5) Blood bsPD-L1 correlated with host T cell responses, and bsPD-L1-positive patients had high T lymphocyte infiltration into tumor tissue. (6) High blood MMP13 levels were associated with loss of extracellular matrix layer structure in tumor tissue. (7) Fluctuations in MMP3 and MMP13 were observed during ICI treatment. (8) The bsPD-L1-positive group included two patient groups that showed extremely unique immune responses to ICI treatment. By combining "pre-treatment bsPD-L1 levels" with "changes in MMP3 and MMP13 levels before and after treatment," it was possible to stratify patients into those who responded significantly to ICI and those whose condition worsened due to ICI treatment. (9) In the combined diagnosis of (8), "pre-treatment bsPD-L1 levels" could be substituted for "pre-treatment MMP13 levels." This disclosure makes it possible to predict the therapeutic effects of ICI, and is expected to be applied to actual clinical practice.

[0312] In this study, we demonstrated that MMP3 and MMP13 have distinct clinical roles. MMP13 expression significantly impacts the extracellular matrix (ECM) status and the localization of T cells and tumor cells in the TME. Increased MMP13 expression was strongly associated with tumor invasion, metastasis, and recurrence risk (Figures 7D and 5E), while increased MMP3 expression was strongly associated with mortality risk (Figures 7B and 5E). MMP3 is upstream of MMP13 in the signaling cascade and activates a wide range of MMPs, including MMP13. The distinct roles of MMP3 and MMP13 in the TME may be explained by differences in their signaling cascades and substrates. While MMP13 is specialized in regulating the structure of the extracellular matrix layer, MMP3 may play a broader role in cancer progression.

[0313] MMPs are known to be primarily involved in cancer invasion and metastasis by degrading extracellular matrix components (Overall CM, and Lopez-Otin C. Strategies for MMP inhibition in cancer: innovations for the post-trial era. Nat Rev Cancer. 2002;2(9):657-7; Vandenbroucke RE, and Libert C. Is there new hope for therapeutic matrix metalloproteinase inhibition? Nat Rev Drug Discov. 2014;13(12):904-27). More than 50 MMP inhibitors, elements, or compositions have been tested in clinical trials in various cancer patients, but all have failed. One reason for this is the lack of knowledge about the effects of MMPs on immune checkpoint molecules. While MMP-mediated degradation of extracellular matrix components promotes cancer progression, it may also promote T cell migration from blood vessels to tumor sites. Furthermore, cleavage of immune checkpoint molecules by MMPs may enhance T cell immune responses against tumors. This disclosure reveals the opposing roles of MMPs in the TME. MMP13 has been reported to cleave and release tumor necrosis factor (TNF)-α (Vandenbroucke RE, Dejonckheere E, Van Hauwermeiren F, Lodens S, De Rycke R, Van Wonterghem E, et al. Matrix metalloproteinase 13 modulates intestinal epithelial barrier integrity in inflammatory diseases by activating TNF. EMBO Mol Med. 2013;5(7):1000-16.). Both TNF-α and IFN-γ are secreted by activated T cells and induce PD-L1 expression in tumor tissues.MMP13 and bsPD-L1 may cooperate with each other to create a positive feedback loop that activates T cells.

[0314] Discussion This disclosure investigated the plasma concentrations of bsPD-L1 and MMPs and their clinical significance in GC and NSCLC patients. In representative examples, bsPD-L1 was detected in 15% and 22% of GC and NSCLC patients, respectively. In both GC and NSCLC patients, bsPD-L1 showed a strong correlation with MMP13 and a moderate correlation with MMP3. In GC, bsPD-L1 expression correlated with blood IFN-γ levels and T cell infiltration in tumor tissue, suggesting that bsPD-L1 may be a good indicator of anti-tumor T cell responses in the TME. Meanwhile, MMP13 levels are associated with the loss of extracellular matrix layer structure, which may promote not only T cell migration into tumors but also vasoinvasiveness of tumor cells.

[0315] This disclosure differs from many other studies of sPD-L1 in cancer patients in that it focuses on sPD-L1 (bsPD-L1) that has PD-1 binding ability.Regarding the function of sPD-L1, there are many conflicting reports (Chen G, Huang AC, Zhang W, Zhang G, Wu M, Xu W, et al. Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response. Nature. 2018;560(7718):382-6, Frigola X, Inman BA, LohseCM, Krco CJ, Cheville JC, Thompson RH, et al. Identification of a soluble form of B7-H1 that retains immunosuppressive activity and is associated with aggressive renal cell carcinoma. Clin Cancer Res. 2011;17(7):1915-23., Rossille D, Gressier M, Damotte D, Maucort-Boulch D, Pangault C, Semana G, et al. High level of soluble programmed cell death ligand 1 in blood impacts overall survival in aggressive diffuse large B-Cell lymphoma: results from a French multicenter clinical trial. Leukemia. 2014;28(12):2367-75., Wang L, Wang H, Chen H, Wang WD, Chen XQ,Geng QR, et al. Serum levels of soluble programmed death ligand 1 predict treatment response and progression free survival in multiple myeloma. Oncotarget. 2015;6(38):41228-36).These discrepancies are thought to be due to qualitative differences in sPD-L1, as not all sPD-L1 can bind to the receptor. Therefore, bsPD-L1 is a better indicator of T cell responses than sPD-L1. Indeed, the present disclosure has demonstrated that bsPD-L1 levels are positively correlated with blood IFN-γ levels and T cell infiltration into tumor tissues. This finding raises the possibility that bsPD-L1 may promote T cell activation as an endogenous PD-1 inhibitor.

[0316] GC patients could be classified into three groups based on the combination of two biomarkers: a host T cell immune marker (e.g., bsPD-L1) and a disease progression diagnostic marker (representatively, MMP13): (i) the bsPD-L1-negative group (immune-silent type); (ii) the bsPD-L1-positive MMP13-low group (immune-activated type with preserved extracellular matrix layer structure); and (iii) the bsPD-L1-positive MMP13-high group (immune-activated type with disruption of the extracellular matrix layer structure). T cell infiltration into tumors was observed in both the bsPD-L1-positive MMP13-low group and the bsPD-L1-MMP13-high group. However, patients in the bsPD-L1-positive MMP13-high group had a higher risk of recurrence and death, whereas patients in the bsPD-L1-positive MMP13-low group had a better prognosis. Our results are consistent with a previous report by Giraldo et al., which showed that patients with high T cell infiltration in clear cell renal cell carcinoma (CRC) comprise two groups: those with favorable and those with poor prognosis (Giraldo NA, Becht E, Pages F, Skliris G, Verkarre V, Vano Y, et al. Orchestration and Prognostic Significance of Immune Checkpoints in the Microenvironment of Primary and Metastatic Renal Cell Cancer. Clin Cancer Res. 2015;21(13):3031-40., Giraldo NA, Becht E, Vano Y, Petitprez F, Lacroix L, Validire P, et al. Tumor-Infiltrating and Peripheral Blood T-cell Immunophenotypes Predict Early Relapse in Localized Clear Cell Renal Cell Carcinoma. Clin Cancer Res. 2017;23(15):4416-28).The technology disclosed herein has the advantage of being able to diagnose tumors non-invasively compared to conventional invasive methods that require the collection of tumor tissue, and is also able to predict prognosis with high accuracy, making it highly practical, convenient, and useful.

[0317] The present disclosure demonstrates that ICI treatment alters MMP3 and MMP13 concentrations, suggesting the possibility that ICI treatment affects the state of the extracellular matrix. Furthermore, by combining pretreatment bsPD-L1 expression (as an indicator of anti-tumor T cell response) with changes in MMP3 and / or MMP13 (as indicators of the state of the extracellular matrix), two groups were identified: a complete response group and a progression group. Specifically, NSCLC patients were divided into three groups: (i) a pretreatment bsPD-L1 negative group, (ii) a pretreatment bsPD-L1 positive (MMP3 and MMP13) increased group, and (iii) a pretreatment bsPD-L1 positive (MMP3 or MMP13) decreased group. The bsPD-L1 positive (MMP3 and MMP13) increased group had rapid cancer progression and a poor prognosis, whereas the bsPD-L1 positive (MMP3 or MMP13) decreased group had a longer survival time and a better prognosis. These results suggest that the bsPD-L1-positive group includes both patients whose disease rapidly worsens and those who respond significantly to ICI.In many clinical trials, ICI treatment has shown a characteristic survival curve, with crossover and plateau of the survival curves observed (Borghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Ready NE, et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer. N Engl J Med. 2015;373(17):1627-39., Brahmer J, Reckamp KL, Baas P, Crino L, Eberhardt WE, Poddubskaya E, et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer. N Engl J Med. 2015;373(2):123-35., Fehrenbacher L, Spira A, Ballinger M, Kowanetz M, Vansteenkiste J, Mazieres J, et al. (Al. Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicenter, open-label, phase 2 randomized controlled trial. Lancet. 2016;387(10030):1837-46., Hodi FS, O'Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363(8):711-23.) The inventors speculate that the intersection of the survival curves shown in Figure 7A is likely due to the inclusion of two groups: one with a poor prognosis and one with a good prognosis.Combined diagnosis using pretreatment bsPD-L1 and MMP alterations may be a non-invasive and powerful diagnostic tool for selecting patients for cancer immunotherapy.

[0318] This disclosure is the first to report an association between bsPD-L1 and MMP13 concentrations in vivo (Figure 1B). While it has been reported that PD-L1 is selectively cleaved by MMP13 and MMP9 in vitro, the present inventors demonstrated that bsPD-L1 levels strongly correlated with MMP13, but not with MMP9, in GC and NSCLC patients. These data suggest that MMP13 may be a key enzyme involved in bsPD-L1 production in vivo and that bsPD-L1 is primarily generated by MMP13-mediated proteolytic cleavage and subsequent release of the extracellular domain of PD-L1.

[0319] The combination of pretreatment bsPD-L1 and MMP changes is a significant advantage in clinical application for stratifying responders and non-responders because both are liquid biomarkers and do not require tumor resection or biopsy. Previous studies have shown that tumor PD-L1 expression, tumor mutation burden, and tumor-infiltrating lymphocyte phenotype can identify patients who are responsive to ICI therapy and those who are not. However, these studies require tumor tissue, which must be collected by invasive methods (Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 2015;372(21):2018-28., Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small-cell lung cancer. Science. 2015;348(6230):124-8., Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O, Gordon MS, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014;515(7528):563-7, Thommen DS, Koelzer VH, Herzig P, Roller A, Trefny M, Dimeloe S, et al.A transcriptionally and functionally distinct PD-1(+) CD8(+) T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat Med. 2018;24(7):994-1004. Hummelink K, van der Noort V, Muller M, Schouten RD, Lalezari F, Peters D, et al. PD-1T TILs as a predictive biomarker for clinical benefit to PD-1 blockade in patients with advanced NSCLC. Clin Cancer Res. 2022;28(22):4893-906. Meanwhile, the combination diagnostic disclosed herein can be diagnosed by blood testing, making it a noninvasive and powerful diagnostic tool. Furthermore, pre-treatment bsPD-L1 can be replaced by pre-treatment MMP13, further simplifying stratification (Figures 7H and 7L).

[0320] Our results indicate that blood bsPD-L1 and / or MMPs may be useful liquid biomarkers for predicting the therapeutic efficacy of immunotherapy.

[0321] (Example 14: Example of another cancer patient <Example of an NSCLC patient>) In this example, the prevalence of rheumatoid arthritis (RA) is 0.6-1.0%, but in the bsPD-L1-positive group of NSCLC patients, 1 of 16 patients developed RA, and 1 patient developed RA after ICI administration (12.5%). On the other hand, in the bsPD-L1-negative group (56 patients), neither RA nor side effects were observed (0%).

[0322] In this example, the prevalence of ulcerative colitis (UC) is approximately 100 per 100,000 people, but among NSCLC patients, 17 patients in the high MMP13 group developed UC, and 1 patient developed UC after ICI administration (11.8%).On the other hand, in the low MMP13 group (55 patients), neither UC nor side effects were observed (0%).

[0323] (Example 15: Example of another cancer patient <Example of a GC patient>) In this example, the clinical course of GC patients (5 patients) who were bsPD-L1 positive and had high MMP13 levels rapidly deteriorated, and all patients died early. Furthermore, many patients were also complicated with rare diseases involving T cell responses.

[0324] In this example, two of the five patients had stage IA and IB cancer, and after surgery, they developed a second cancer (malignant melanoma and sweat gland carcinoma) and died soon after. Both malignant melanoma and sweat gland carcinoma are extremely rare cancers. One of them had a dissecting aortic aneurysm (the incidence of dissecting aortic aneurysms is approximately 3 per 100,000 people).

[0325] In this example, one of the five patients had Stage IIB disease and died of sudden peritoneal perforation due to dissemination after surgery. Based on these observations, the combination of host T-cell immune markers and disease progression markers makes it possible to detect hidden serious underlying disease complications and predict in advance which patients are likely to develop HPD due to their underlying disease. Furthermore, even when similar predictions are made with other treatment modalities, such as ICI, chemotherapy, radiation therapy, or surgery, or combinations of these, particularly combinations of ICI and chemotherapy, ICI and radiation therapy, or surgery and chemotherapy, it is similarly possible to detect hidden serious underlying disease complications and predict in advance which patients are likely to develop HPD due to their underlying disease by using host T-cell immune markers and / or disease progression markers, either alone or in combination.

[0326] (Example 16: Examples of other diseases: autoimmune diseases and related diseases (1)) The present disclosure is used to predict the effect and prognosis of treatment (therapeutic or preventive) for diseases or conditions primarily driven by T cell responses due to autoantigens (including cancer), foreign antigens (including pathogens, vaccines, and transplants), and immunomodulatory drugs.

[0327] In this example, it is demonstrated that it is possible to predict autoimmune diseases and related diseases (rheumatoid arthritis, polymyalgia rheumatica, ankylosing spondylitis, relapsing polychondritis, systemic lupus erythematosus, systemic sclerosis, dermatomyositis / polymyositis, Sjogren's syndrome, antiphospholipid antibody syndrome, ulcerative colitis, Crohn's disease, Takayasu's arteritis, giant cell arteritis, polyarteritis nodosa, ANCA-associated vasculitis, malignant rheumatoid arthritis / rheumatoid vasculitis, granulomatosis with polyangiitis, eosinophilic granulomatosis with polyangiitis, multiple sclerosis, neuromyelitis optica, Guillain-Barré syndrome, Behcet's disease, adult Still's disease), etc.

[0328] In various autoimmune diseases, the risk of progression, disease progression, and treatment effects can be predicted. In this example, this is carried out for rheumatoid arthritis.

[0329] Method: By taking blood samples at the initial consultation (before treatment), it is possible to predict that patients with bsPD-L1 positivity or high MMP13 levels are likely to have rapid disease progression and severe disease. Furthermore, by taking blood samples over time, it is possible to predict the likelihood of disease progression if bsPD-L1 or MMP13 levels are elevated, and the likelihood of remission if levels are decreased. Similarly, it is also possible to predict relapse after remission and the therapeutic effects of various therapeutic drugs (including steroids, immunosuppressants, and biological agents).

[0330] Furthermore, blood samples taken before and during treatment can predict that patients with bsPD-L1 positivity or high MMP13 levels are likely to experience rapid cancer progression if they are administered immune checkpoint inhibitors for the treatment of malignant tumors.

[0331] (Example 17: Examples of other diseases: autoimmune diseases and related diseases (2)) This example demonstrates that it is possible to predict autoimmune diseases and related diseases (rheumatoid arthritis, polymyalgia rheumatica, ankylosing spondylitis, relapsing polychondritis, systemic lupus erythematosus, systemic sclerosis, dermatomyositis / polymyositis, Sjogren's syndrome, antiphospholipid antibody syndrome, ulcerative colitis, Crohn's disease, Takayasu's arteritis, giant cell arteritis, polyarteritis nodosa, ANCA-associated vasculitis, malignant rheumatoid arthritis / rheumatoid vasculitis, granulomatosis with polyangiitis, eosinophilic granulomatosis with polyangiitis, multiple sclerosis, neuromyelitis optica, Guillain-Barré syndrome, Behcet's disease, adult Still's disease), etc.

[0332] In various autoimmune diseases, it is possible to predict the risk of progression, disease progression, and treatment efficacy. Furthermore, some autoimmune diseases (such as dermatomyositis and polymyositis) may be complicated with malignant tumors, and this method can be used to predict these complications. In this example, this method is used with dermatomyositis and polymyositis.

[0333] Method: By taking blood samples at the initial consultation (before treatment), it is possible to predict that patients with bsPD-L1 positivity or high MMP13 levels are likely to have rapid disease progression and severe disease. Furthermore, by taking blood samples over time, it is possible to predict the likelihood of disease progression if bsPD-L1 or MMP13 levels are elevated, and the likelihood of remission if levels are decreased. Similarly, it is also possible to predict relapse after remission and the therapeutic effects of various therapeutic drugs (including steroids, immunosuppressants, and biological agents).

[0334] Furthermore, blood tests taken before and during treatment can predict that patients with bsPD-L1 positivity or high MMP13 levels are at high risk of developing malignant tumors, and that if they do develop, there is a high possibility of invasion and metastasis, and that the disease is likely to progress rapidly.

[0335] (Example 18: Examples of other diseases: autoimmune diseases and related diseases (3)) This example demonstrates that it is possible to predict autoimmune diseases and related diseases (rheumatoid arthritis, polymyalgia rheumatica, ankylosing spondylitis, relapsing polychondritis, systemic lupus erythematosus, systemic sclerosis, dermatomyositis / polymyositis, Sjogren's syndrome, antiphospholipid antibody syndrome, ulcerative colitis, Crohn's disease, Takayasu's arteritis, giant cell arteritis, polyarteritis nodosa, ANCA-associated vasculitis, malignant rheumatoid arthritis / rheumatoid vasculitis, granulomatosis with polyangiitis, eosinophilic granulomatosis with polyangiitis, multiple sclerosis, neuromyelitis optica, Guillain-Barré syndrome, Behcet's disease, adult Still's disease), etc.

[0336] In various autoimmune diseases, the risk of progression, disease progression, and treatment efficacy can be predicted. Furthermore, some autoimmune diseases may be complicated with malignant tumors, and this can be used to predict these. In this example, this is performed on ulcerative colitis and Crohn's disease.

[0337] Method: By taking blood samples at the initial consultation (before treatment), it is possible to predict that patients with bsPD-L1 positivity or high MMP13 levels are likely to have rapid disease progression and severe disease. Furthermore, by taking blood samples over time, it is possible to predict the likelihood of disease progression if bsPD-L1 or MMP13 levels are elevated, and the likelihood of remission if levels are decreased. Similarly, it is also possible to predict relapse after remission and the therapeutic effects of various therapeutic drugs (including steroids, immunosuppressants, and biological agents).

[0338] Furthermore, blood tests taken before and during treatment can predict that patients with bsPD-L1 positivity or high MMP13 levels are at high risk of developing malignant tumors, and that if they do develop, there is a high possibility of invasion and metastasis, and that the disease is likely to progress rapidly.

[0339] (Example 19: Another example of a disease: <Disease or pathological condition primarily driven by a T cell response to a foreign antigen> (1)) This example demonstrates that it is possible to predict a disease or pathological condition primarily driven by a T cell response to a foreign antigen. Examples of diseases or pathological conditions primarily driven by a T cell response to a foreign antigen include infectious diseases and vaccines therefor (HBV, HCV, influenza virus, measles virus, mumps, SARS coronavirus, novel coronavirus, cytomegalovirus, varicella-zoster virus, herpes simplex virus), septic conditions caused by infectious diseases, and graft-versus-host disease (GVHD).

[0340] First, examples of infectious diseases and vaccines are demonstrated.

[0341] It can predict the risk of severe or fulminant illness and the effectiveness of treatment for influenza, COVID-19 infection, viral hepatitis, etc. It can also predict adverse events and the risk of death from vaccinations.

[0342] Methods: Blood samples taken at the initial visit (before treatment) can predict that patients with bsPD-L1 positivity or high MMP13 levels are at high risk of developing severe, fulminant, or sepsis. Furthermore, blood samples taken over time can predict the likelihood of further progression to severe disease if bsPD-L1 or MMP13 levels are elevated, and the likelihood of recovery if levels are decreased. Similarly, it is possible to predict the therapeutic effect of immunomodulatory drugs (including steroids and biological agents) on sepsis pathology.

[0343] When it comes to vaccination, people who have a positive bsPD-L1 or high MMP13 levels in their blood samples taken before vaccination can be predicted to be at high risk of adverse events or death from vaccination.

[0344] (Example 20: Another example of a disease: <Disease or pathological condition mainly driven by a T cell response to a foreign antigen> (2)) In this example, another example is used to demonstrate that predictions regarding a disease or pathological condition mainly driven by a T cell response to a foreign antigen are possible. In this example, organ transplantation is used as an example.

[0345] In transplant medicine such as organ transplantation and bone marrow transplantation, it can be used to predict and monitor acute rejection, chronic rejection, and refractory rejection, as well as to predict the therapeutic effects of immunomodulatory drugs (including steroids and immunosuppressants).

[0346] Methods: Pre-transplant blood sampling can predict that patients with bsPD-L1 positivity or high MMP13 levels are at high risk of rejection. Furthermore, blood sampling over time can predict that an increase in bsPD-L1 or MMP13 levels indicates a high likelihood of a rejection response progressing, while a decrease indicates a high likelihood of a rejection response subsiding. Similarly, it is also possible to predict the therapeutic effect of immunomodulatory drugs (including steroids and immunosuppressants). Furthermore, long-term monitoring can predict chronic rejection.

[0347] Example 21: Prediction, diagnosis, treatment, and prevention of cancer treatment effects by ICI using CLIA / CLEIA

[0348] In this example, the effect is predicted using MMP13, MMP3 and / or bsDL1.

[0349] (Materials and Methods) - Patients undergoing ICI treatment are selected as subjects. Samples are collected either before or during treatment, or both. - As the CLIA / CLEIA reagent, the CLIA or CLEIA reagent provided by Medical and Biological Laboratories Co., Ltd. can be used. - For CLEIA, the STACIA fully automated CLEIA measuring device can be used. - As the antibody, anti-MMP3 antibody and anti-MMP13 antibody prepared by conventional methods can be prepared, or commercially available antibodies can be used. They can also be provided by Medical and Biological Laboratories Co., Ltd.

[0350] Using the antibodies against MMP3 and MMP13 thus obtained, enzyme-labeled antigens or antibodies as standard in STACIA can be incorporated into the reaction system, and enzyme activity can be detected according to the manual.

[0351] Detecting target molecules in samples by measuring the amount of luminescence

[0352] Once the detected values ​​are obtained, the concentrations of MMP3 and MMP13 in the subject can be calculated.

[0353] Furthermore, the concentration of bsPD-L1 was measured using a previously described method (Takeuchi M, Doi T, Obayashi K, Hirai A, Yoneda K, Tanaka F, et al. Soluble PD-L1 with PD-1-binding capacity exists in the plasma of patients with non-small cell lung cancer. Immunol Lett. 2018;196:155-60., also see JP 2020-148631 A and WO2019 / 049974).

[0354] (Determination) From the values ​​of MMP3, MMP13, and bsPD-L1 obtained as described above, if bsPD-L1 is positive or MMP13 is high in the biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are higher than those before treatment, it is predicted that the therapeutic effect of the immune checkpoint inhibitor will be low.

[0355] On the other hand, if bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment, the therapeutic effect of the immune checkpoint inhibitor is predicted to be high.

[0356] If the treatment effect is low, the immune checkpoint inhibitor treatment is discontinued and other anticancer drug treatments are considered. If the treatment effect is determined to be high, the use of the immune checkpoint inhibitor is continued.

[0357] Example 22: Example of predicting therapeutic effect of ICI in cancer treatment using ELISA Next, a similar test is carried out using sandwich ELISA (enzyme-linked immunosorbent assay).

[0358] (Materials and Methods) Patients undergoing ICI treatment are selected as subjects. Samples are collected either before or during treatment, or both. ELISA reagents provided by Cosmo Bio, Medical and Biological Laboratories, Inc., can be used as sandwich ELISA reagents. Antibodies can be prepared using conventional methods, such as anti-MMP3 and anti-MMP13 antibodies, or commercially available antibodies. These antibodies can also be provided by Medical and Biological Laboratories, Inc.

[0359] A sample is added to the microcup on which the antibody is immobilized, and an antigen-antibody reaction is allowed to occur. An enzyme-labeled antibody can then be added to allow the antigen-antibody reaction to occur. Here, the factor of the present disclosure can be used as the enzyme-labeled antibody or the antibody in the solid phase. After washing, the sample is reacted with the enzyme substrate to develop color, and the absorbance is measured to calculate the amount of antibody (or antigen) in the sample. For bsPD-L1, the same method as in Example 20 is used.

[0360] (Determination) From the values ​​of MMP3, MMP13, and bsPD-L1 obtained as described above, similarly to Example 20, if bsPD-L1 is positive or MMP13 is high in the biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in the biological sample obtained after the start of treatment are higher than those before treatment, it is predicted that the therapeutic effect of the immune checkpoint inhibitor will be low.

[0361] On the other hand, if bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment, the therapeutic effect of the immune checkpoint inhibitor is predicted to be high.

[0362] If the treatment effect is low, the immune checkpoint inhibitor treatment is discontinued and other anticancer drug treatments are considered. If the treatment effect is determined to be high, the use of the immune checkpoint inhibitor is continued.

[0363] (Summary) From the above examples, it can be seen that the determinations shown in Tables 15 to 18 can be made. Note that reference values ​​such as high and low values ​​can be set by appropriately referring to the above examples. These are merely examples, and the present disclosure is not limited to these values. It is necessary to set cutoff values ​​depending on various diseases or pathological conditions. Furthermore, since measured values ​​vary depending on the measurement kit, assay method, and device, they must be set according to various measurement methods.

[0364] (Note) As described above, the present disclosure has been illustrated using preferred embodiments of the present disclosure, but the present disclosure should not be construed as being limited to these embodiments. It is understood that the scope of the present disclosure should be interpreted solely by the scope of the claims. It is understood that a person skilled in the art can implement an equivalent scope based on the description of the present disclosure and common general technical knowledge from the description of specific preferred embodiments of the present disclosure. It is understood that the contents of patents, patent applications, and literature cited in this specification are incorporated by reference into this specification as if the contents themselves were specifically set forth in this specification. This application claims priority to Japanese Patent Application No. 2023-206241, filed with the Japan Patent Office on December 6, 2023, the contents of which are incorporated herein by reference in their entirety.

[0365] The present disclosure makes it possible to predict the pathology, prognosis, and therapeutic effect of T cell-related diseases (for example, predicting therapeutic effect in cancer treatment (including treatment and prevention) such as cancer immunotherapy). Therefore, it also makes it possible to identify cases in which immunotherapy is ineffective, select immunotherapy appropriate for a patient, and create drug administration plans for cancer immunotherapy using immunotherapy, for example.

Claims

1. An agent or composition for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising at least one factor that interacts with a disease diagnostic marker, wherein the disease diagnostic marker comprises at least one member of the MMPC group.

2. The agent or composition according to claim 1, wherein the disease diagnostic marker is MMP13.

3. The agent or composition according to claim 1, wherein the disease diagnostic marker is MMP3.

4. A combination of at least one factor that interacts with a disease diagnostic marker and at least one factor that interacts with a host T cell immune function marker for predicting the therapeutic and / or prophylactic effect of treatment for cancer and / or T cell-related diseases, or diagnosing the pathology, severity and / or prognosis.

5. The combination according to claim 4, wherein the disease diagnostic marker comprises MMP13 or MMP3, and the host T cell immune function marker comprises MMP13 or bsPDL1.

6. An agent or composition according to any one of claims 1 to 3 or a combination according to claim 4 or 5 for predicting the effect of ICI.

7. A kit for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising an agent that interacts with at least one selected from the group consisting of disease diagnostic markers, wherein the disease diagnostic marker is an MMPC group.

8. The kit according to claim 7, wherein the MMP C group includes MMP13.

9. The kit according to claim 7 or 8, wherein the MMP C group includes MMP3.

10. A kit for predicting the therapeutic and / or preventive effect of treatment for cancer and / or T-cell related diseases, or for diagnosing the pathology, severity and / or prognosis, comprising at least one factor that interacts with a disease progression diagnostic marker and at least one factor that interacts with a host T-cell immune function marker.

11. The kit according to claim 10, wherein the disease diagnostic marker comprises MMP13 or MMP3, and the host T cell immune function marker comprises MMP13 or bsPDL1.

12. A kit according to any one of claims 7 to 11 for predicting the effect of ICI.

13. The agent or composition according to any one of claims 1 to 3, the combination according to claim 4 or 5, or the kit according to any one of claims 7 to 11, wherein the treatment comprises chemotherapy, radiation therapy, molecular targeted drugs, proton beam, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof.

14. The agent or composition described in any one of claims 1 to 3, 6, or 13, the combination described in any one of claims 4 to 6, or 13, or the kit described in any one of claims 7 to 13, wherein the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, or recurrence.

15. The agent, composition, combination, or kit according to any one of claims 1 to 14, wherein the factor is at least one selected from the group consisting of a low molecular weight compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof, and combinations thereof.

16. An agent or composition according to any one of claims 1 to 3, 6, or 13 to 15, a combination according to any one of claims 4 to 6, or 13 to 15, or a kit according to any one of claims 7 to 15, for stratifying patients into a group in which ICI is effective and a group in which cancer worsens due to ICI treatment, by measuring the host T cell immune function marker before treatment and the disease progression diagnostic marker during treatment.

17. The agent, composition, combination or kit according to claim 16, wherein the host T cell immune function marker is MMP13 and / or bsPDL1, and the disease diagnostic marker is MMP3 and / or MMP13.

18. The agent, composition, combination, or kit according to claim 16 or 17, which predicts that the therapeutic effect of the immune checkpoint inhibitor will be low when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment.

19. The agent, composition, combination, or kit according to any one of claims 16 to 18, which predicts that the therapeutic effect of the immune checkpoint inhibitor will be high when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment.

20. The agent, composition, combination or kit according to any one of claims 1 to 20, wherein the cancer and / or T cell-related disease comprises at least one of lung cancer and non-small cell lung cancer.

21. A method for predicting the therapeutic and / or prophylactic effect of treatment for cancer and / or T-cell-related diseases, or diagnosing the pathology, severity and / or prognosis, comprising measuring at least one disease diagnostic marker in a subject, wherein the disease diagnostic marker comprises at least one member of the MMPC group.

22. The method according to claim 21, wherein the disease diagnostic marker is MMP13.

23. The method according to claim 21, wherein the disease diagnostic marker is MMP3.

24. The method of claim 21, further comprising measuring at least one host T cell immunocompetence marker.

25. The method according to claim 24, wherein the disease diagnostic marker comprises MMP13 or MMP3.

26. The method of claim 24 or 25, wherein the host T cell immunocompetence marker comprises MMP13 or bsPDL1.

27. The method of any one of claims 21 to 26, wherein the treatment comprises chemotherapy, radiation therapy, molecular targeted drugs, proton beam therapy, surgery, immunotherapy including immune checkpoint inhibitors, and combinations thereof.

28. A method according to any one of claims 21 to 26, wherein the prediction comprises a prediction of the effect of an ICI.

29. The method according to any one of claims 21 to 28, wherein the prediction includes prediction of cancer prognosis and prediction of invasion, metastasis, and recurrence.

30. The method of any one of claims 21 to 29, wherein the measurement is performed using a factor that interacts with the marker.

31. The method according to any one of claims 21 to 30, wherein the agent is at least one selected from the group consisting of a small molecule compound, an antibody, a nucleic acid molecule, and a polypeptide, as well as fragments thereof, and combinations thereof.

32. A method according to any one of claims 21 to 31, for stratifying patients into a group that responds well to ICI and a group of patients whose cancer worsens due to ICI treatment, by measuring the host T cell immune function marker before treatment and measuring the disease progression diagnostic marker during treatment.

33. The method according to any one of claims 21 to 32, wherein the therapeutic effect of the immune checkpoint inhibitor is predicted to be low when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are higher than those before treatment.

34. The method according to any one of claims 21 to 32, which predicts that the therapeutic effect of an immune checkpoint inhibitor will be high when bsPD-L1 is positive or MMP13 is high in a biological sample obtained before treatment, and the concentrations of MMP3 and / or MMP13 in a biological sample obtained after the start of treatment are lower than those before treatment.

35. The method of any one of claims 21 to 34, wherein the cancer and / or T cell related disease comprises at least one of lung cancer and non-small cell lung cancer.

Images