Biomarkers for predicting the response to checkpoint inhibitors

Abstract

This invention provides a biomarker for predicting checkpoint inhibitor responses. The inventors have demonstrated that PD-1 / PD-L1 inhibitors exert antitumor activity against tumors exhibiting low PD-L1 expression and an immune desert phenotype by blocking PD-L1 in lymph nodes. This invention provides a novel combination of intratumoral markers for antigen cross-presenting cells and T-cell chemokines, which promise to be superior efficacy predictive biomarkers compared to existing methods.

Description

[Technical Field]

[0001] This invention provides a biomarker for predicting checkpoint inhibitor responses. [Previous Technology]

[0002] Programmed death ligand 1 (PD-L1) plays a major role in suppressing the host's anti-tumor immune response (Non-Patent Literature 1). The interaction between PD-L1 on cancer cells or tumor-infiltrating immune cells and its receptors PD-1 and B7-1 (also known as CD80) on T cells transmits signals to inhibit T cell activation (Non-Patent Literature 2). PD-1 / PD-L1 inhibitors generally show greater clinical benefit in patients with high intratumoral PD-L1 expression. Interestingly, the phase 3 OAK trial (for non-small cell lung cancer) showed that atezolizumab (an anti-PD-L1 antibody and one of the PD-1 / PD-L1 inhibitors) had a survival advantage over docetaxel even when tumor cells and immune cells (TC0 / IC0) in the subgroup had low or undetectable PD-L1 levels (Non-Patent Literature 3). This result is consistent with the analysis of PD-L1 gene expression in tumor tissue (Non-Patent Reference 3). The numerical value of PD-L1 expression within tumors in predicting patient response to such treatments remains imperfect. Therefore, determining which patients can benefit from PD-1 / PD-L1 targeted therapy remains an important clinical problem. For example, biomarkers used for conventional prediction of treatment efficacy have not been adequately optimized for specific purposes in terms of marker types and combinations (Patent References 1 to 9). On the other hand, PD-L1 has also been reported to be expressed on dendritic cells (DCs) in tumor-draining lymph nodes of cancer patients (Non-Patent Reference 4). PD-1 has also been reported to be highly expressed on T cells not only in tumor tissue but also in lung tumor-draining lymph nodes (Non-Patent References 5 and 6). Furthermore, PD-L1 and CD28 have been reported to compete for antigen binding on B7-1 cells, thereby inhibiting T cell priming by overriding CD28 / B7-1 signaling (Non-Patent Reference 7). However, the role of T cell activation in tumor lymph nodes in the mechanism of action of PD-1 / PD-L1 targeted therapy remains unclear. [List of Citations] [Patent Literature]

[0003] [Patent Document 1] US 2015 / 0071910 [Patent Document 2] WO 2015 / 120382 [Patent Document 3] WO 2016 / 168133 [Patent Document 4] WO 2017 / 013436 [Patent Document 5] WO 2017 / 176925 [Patent Document 6] WO 2018 / 209324 [Patent Document 7] WO 2018 / 231771 [Patent Document 8] WO 2018 / 225063 [Patent Document 9] WO 2018 / 055145 [Non-Patent Documents]

[0004] [Non-Patent Literature 1] Zou W, Wolchok JD, Chen L., Science translational medicine 2016; 8(328):328rv4 [Non-Patent Literature 2] Butte MJ, Keir ME, Phamduy TB, Sharpe AH, Freeman GJ., Immunity 2007;27(1):111-22 [Non-Patent Literature 3] Rittmeyer A, Barlesi F, Waterkamp D, Park K, Ciardiello F, von Pawel J, et al., Lancet (London, England) 2017;389(10066):255-65 [Non-Patent Literature 4] Curiel TJ, Wei S, Dong H, Alvarez X, Cheng P, Mottram P, et al., Nature medicine 2003;9(5):562-7 [Non-Patent Literature 5] Gros A, Robbins PF, Yao X, Li YF, Turcotte S, Tran E, et al., The Journal of clinical investigation 2014;124(5):2246-59 [Non-patent literature 6] van de Ven R, Niemeijer AN, Stam AGM, Hashemi SMS, Slockers CG, Daniels JM, et al., ERJ open research 2017;3(2) [Non-patent literature 7] Butte MJ, Pena-Cruz V, Kim MJ, Freeman GJ, Sharpe AH, Molecular immunology 2008;45(13):3567-72 [Summary of the Invention]

[0005] [Technical Issues]

[0006] In traditional methods for predicting the efficacy of PD-1 / PD-L1 inhibitors (such as anti-PD-1 antibodies or anti-PD-L1 antibodies), biomarkers include the expression levels of PD-1 and PD-L1, the targets of the inhibitors, within the tumor, as well as indicators showing immune activation (such as activation of the IFN-γ pathway) in tumor samples. However, if PD-1, PD-L1, or IFN-γ is used as a marker, patients with pre-existing immune activation in the tumor can be primarily selected at the time of administration, but potential patients expected to respond to PD-1 / PD-L1 inhibitors may not be identified. In these potential patients, PD-1 or PD-L1 expression levels may be low or absent, or the IFN-γ pathway may not be activated but is poised for activation in draining lymph nodes. [Solution]

[0007] This invention is based on the concept that the main mechanism of action of PD-1 / PD-L1 inhibitors is the inhibition of the binding between PD-1 and PD-L1. Therefore, PD-1 / PD-L1 inhibitors (such as anti-PD-1 antibodies and anti-PD-L1 antibodies) are expected to provide clinical benefit even in subgroups of cancer patients with low or undetectable PD-L1 levels on tumor cells and immune cells. The inventors investigated the mechanism of action of PD-L1-negative tumors in response to PD-1 / PD-L1 targeted therapy. As a result, the inventors discovered predictive biomarkers based on the mechanism of action, which may be used to determine which patients will benefit from PD-1 / PD-L1 targeted therapy.

[0008] Specifically, the biomarker combination of the present invention includes both the presence of dendritic cells (DCs) capable of presenting tumor antigens and the presence of chemokines that accumulate in tumors to activate T cells. By detecting this combination, rather than either of the two markers alone, it is possible to detect the preparatory phase in lymph nodes and improve the accuracy of predicting patient response to treatment. Excluding markers of T cell activation, such as PD-L1 and IFN-γ, from the current genome can reduce the pressure on patients with preactivated immunity. Notably, the genome proposed by combining antigen presentation capability and T cell recruitment can select responder patients with / without preactivated immunity, also known as "inflammatory tumors / immune-desert tumors".

[0009] More specifically, the present invention provides the following. [1] A method for identifying a patient with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor, said method comprising: detecting in a sample from the patient the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells within the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor. [1a] A method for identifying a patient with or suspected of having cancer, said cancer responding to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (which may be a PD-1 inhibitor or a PD-L1 inhibitor that inhibits the binding between PD-1 and PD-L1, such as an anti-PD-1 antibody or an anti-PD-L1 antibody; this also applies to other embodiments of the invention), said method comprising: detecting in a sample from the patient the following (i) and (ii): (i) at least one marker, which is an antigen-presenting cell marker or an antigen-presenting marker; and (ii) at least one chemokine or chemoattractant. [2] The method of [1] or [1a], wherein the treatment includes administration of an effective amount of an anti-PD-L1 antibody. [3] The method of any one of [1], [1a], and [2], wherein the treatment includes administration of an effective amount of atezolizumab. [4] The method of any one of [1] to [3], wherein the cancer is selected from the group consisting of: non-small cell lung cancer, small cell lung cancer, breast cancer, bladder cancer, and alveolar soft part sarcoma. [5] The method of any one of [1] to [4], wherein each marker is not a T cell activity marker. [6] The method of any one of [1] to [5], wherein the at least one marker is one, two, three, four, five, six, or all of XCR1, Clec9, Irf8, Batf3, CD205, CD103, and CD141. [7] The method of any one of [1] to [6], wherein the at least one marker is XCR1. [8] The method of any one of [1] to [7], wherein the at least one chemokine is a CXCR3 ligand. [9] The method of any one of [1] to [8], wherein the at least one chemokine is one, two, or all of CXCL9, CXCL10, and CXCL11.

[10] The method of any one of [1] to [9], wherein the at least one chemokine is all of CXCL9, CXCL10, and CXCL11.

[11] The method of any one of [1] to

[10] , wherein the detection (i) is measuring the mRNA expression level of the marker, and wherein the detection (ii) is measuring the mRNA expression level of the chemokine.

[12] The method of any one of [1] to

[11] , wherein the detection (i) and (ii) are measuring the mRNA expression levels of the marker and one or more chemokines.

[13] The method of

[12] , wherein the marker is XCR1, and the one or more chemokines are selected from CXCL9, CXCL10, and CXCL11.

[14] The method of

[13] , wherein the chemokine is all of CXCL9, CXCL10, and CXCL11.

[15] A method for predicting the efficacy of a PD-1 inhibitor or a PD-L1 inhibitor in a cancer patient, wherein the method comprises: detecting the following (i) and (ii) in a sample from the patient: (i) at least one marker for estimating the number of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells in the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor.

[0010] In addition, the present invention provides the following.

[16] The method of [1] or [2], wherein the treatment comprises administering an effective amount of a humanized anti-PD-L1 antibody.

[17] The method of any one of [1] to

[16] , wherein the cancer is lung cancer.

[18] The method of any one of [1] to

[16] , wherein the cancer is non-small cell lung cancer.

[19] The method of any one of [1] to

[18] , wherein the sample is a lung tissue sample.

[20] The method of any one of [1] to [6], wherein the at least one label is one, two, three, or all of XCR1, Clec9, Irf8, and Batf3.

[21] The method of any one of [1] to

[12] , wherein the detection (i) and (ii) are determining the average (AP / T score) of the following (a) and (b): (a) the mRNA expression level of the label; and (b) the mRNA expression level of the one or more chemokines.

[22] The method of

[13] or

[21] , wherein the method further includes determining whether the mean (AP / T score) is equal to or greater than a threshold.

[23] The method of

[22] , wherein the method further includes identifying the patient as a patient receiving the treatment if the mean (AP / T score) is equal to or greater than the threshold.

[24] The method of

[23] , wherein the method further includes determining that the patient has received the treatment.

[25] The method of

[24] , wherein the method further includes administering the treatment to the patient.

[26] The method of

[25] , wherein the method includes administering an effective amount of a PD-1 / PD-L1 inhibitor to the patient.

[27] A method of treating cancer in a patient, the cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor, wherein the method comprises: obtaining a tissue sample from a human having or suspected of having cancer, detecting in the sample the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) capable of cross-presenting to CD8-positive T cells within a tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor; identifying a patient having or suspected of having cancer, the cancer being responsive to treatment; or determining that the patient has received the treatment; and administering an effective amount of the inhibitor to the patient.

[28] A method of detecting in a sample from an individual the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) capable of cross-presenting to CD8-positive T cells; and (ii) at least one chemokine that accumulates effector T cells.

[29] A method of selecting patients with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor, said method comprising: determining a patient cohort consisting of a group of patients with or suspected of having cancer; measuring the mean (AP / T score) of the following (i) and (ii) in a sample from each patient in said patient cohort: (i) a marker mRNA expression level used to estimate the number of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells in the tumor; and (ii) a marker mRNA expression level of one or more chemokines that accumulate effector T cells in the tumor; determining a threshold such that a specific percentage of all patients in the patient cohort has an mean (AP / T score) equal to or greater than said threshold; and selecting a patient whose mean (AP / T score) is equal to or greater than said threshold.

[30] A method for predicting the efficacy of a PD-1 / PD-L1 inhibitor for a group of cancer patients, wherein the method comprises: determining a group of patients who have or are suspected of having cancer; measuring the mean (AP / T score) of the following (i) and (ii) in a sample from each patient in the group of patients: (i) the mRNA expression level of at least one marker used to estimate the number of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells in the tumor; and (ii) the mRNA expression level of one or more chemokines that accumulate effector T cells in the tumor; determining a threshold such that a specific percentage of all patients in the group of patients has an mean (AP / T score) equal to or greater than the threshold; and indicating that the inhibitor is highly effective for patients whose mean (AP / T score) is equal to or greater than the threshold.

[31] A pharmaceutical composition for treating an individual with cancer, comprising a PD-1 / PD-L1 inhibitor, wherein the system is identified / predicted / treated / detected / selected by any of [1] to

[30] , wherein the method can predict the efficacy of the PD-1 / PD-L1 inhibitor in a patient population with cancer.

[32] A kit comprising an apparatus for performing any of [1] to

[30] and instructions for use.

[33] Use of one or more mRNA and / or protein-specific probes in the preparation of a kit for predicting the sensitivity of an individual with cancer to treatment with a PD-1 / PD-L1 inhibitor, the kit being used to perform any of [1] to

[30] .

Implementation Method

[0011] The techniques and procedures described or referenced herein are readily understood and commonly used by those skilled in the art, for example, in Sambrook et al., Molecular Cloning: A Laboratory Manual 3d edition (2001) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY; Current Protocols in Molecular Biology (FM Ausubel, et al. eds., (2003)); the series Methods in Enzymology (Academic Press, Inc.): PCR 2: A Practical Approach (MJ MacPherson, BD Hames and GR Taylor eds. (1995)), Harlow and Lane, eds. (1988); Antibodies, A Laboratory Manual, and Animal Cell Culture (RI Freshney, ed. (1987)); Oligonucleotide Synthesis (MJ Gait, ed., 1984); Methods in Molecular Biology, Humana Press; Cell Biology: A Laboratory Notebook (JE Cellis, ed., 1998) Academic Press; Animal Cell Culture (RI Freshney), ed., 1987); Introduction to Cell and Tissue Culture (JP Mather and PE Roberts, 1998) Plenum Press; Cell and Tissue Culture: Laboratory Procedures (A. Doyle, JB Griffiths, and DG Newell, eds., 1993-8) J. Wiley and Sons; Handbook of Experimental Immunology (DMThe widely used methods described in Weir and C.C. Blackwell, eds.); Gene Transfer Vectors for Mammalian Cells (J.M. Miller and M.P. Calos, eds., 1987); PCR: The Polymerase Chain Reaction, (Mullis et al., eds., 1994); Current Protocols in Immunology (J.E. Coligan et al., eds., 1991); Short Protocols in Molecular Biology (Wiley and Sons, 1999); Immunobiology (C.A. Janeway and P. Travers, 1997); Antibodies (P. Finch, 1997); Antibodies: A Practical Approach (D. Catty., ed., IRL Press, 1988-1989); Monoclonal Antibodies: A Practical Approach (P. Shepherd and C. Dean, eds., Oxford University Press, 2000); Using Antibodies: A Laboratory Manual (E. Harlow and D. Lane (Cold Spring Harbor Laboratory Press, 1999); The Antibodies (M. Zanetti and J. D. Capra, eds., Harwood Academic Publishers, 1995); and Cancer: Principles and Practice of Oncology (V.T. DeVita et al., eds., J.B. Lippincott Company, 1993).

[0012] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Singleton et al., *Dictionary of Microbiology and Molecular Biology*, 2nd ed., J. Wiley & Sons (New York, NY 1994), and March, *Advanced Organic Chemistry Reactions, Mechanisms and Structure*, 4th ed., John Wiley & Sons (New York, NY 1992) provide a general guide to many of the terms used in this application for those of ordinary skill in the art. All references cited herein, including patent applications and publications, are incorporated herein by reference in their entirety.

[0013] Programmed cell death protein 1 (PD-1; also known as CD274 or B7-H1) is a type I membrane protein belonging to the CD28 / CTLA-4 family of T cell regulators. PD-1 has two ligands, namely PD-L1 and PD-L2, which belong to the B7 family. PD-1 with ligands is thought to negatively regulate immune responses, such as T cell responses. PD-L1 and PD-1 are highly expressed in several types of cancer and are thought to play a role in cancer immune evasion. Inhibitors that suppress interactions such as those between PD-1 and PD-L1, such as "checkpoint inhibitors," can enhance T cell responses and increase anti-tumor activity.

[0014] The term “antibody” is used in the broadest sense and covers a variety of antibody structures, including but not limited to monoclonal antibodies, multiclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), chimeric antibodies, humanized antibodies, human antibodies, and the aforementioned antibody fragments, as long as they exhibit the desired antigen-binding activity.

[0015] In this article, "PD-1 / PD-L1 axis inhibitor" refers to molecules that inhibit the interaction between a PD-1 / PD-L1 axis binding partner and another binding partner, and eliminate T cell dysfunction caused by signal transduction along the PD-1 / PD-L1 axis, thereby enhancing T cell function, such as cytotoxicity and cytokine production. The term "PD-1 / PD-L1 inhibitor" refers to molecules that can inhibit the interaction between PD-1 and PD-L1, and eliminate T cell dysfunction caused by signal transduction along the PD-1 / PD-L1 axis, thereby enhancing T cell function, such as cytotoxicity and cytokine production. PD-1 / PD-L1 inhibitors include, for example, PD-L1 inhibitors and PD-1 inhibitors.

[0016] In this document, "PD-1 inhibitor" refers to a molecule that inhibits signal transduction caused by the interaction between PD-1 and its binding partner image PD-L1. In some embodiments, the PD-1 inhibitor is an anti-PD-1 antibody.

[0017] In this document, “PD-L1 inhibitor” refers to a molecule that inhibits signal transduction due to the interaction between PD-L1 and its binding partner isoform, PD-1 and B7-1. In some embodiments, the PD-L1 inhibitor is an anti-PD-L1 antibody. In some embodiments, the anti-PD-L1 antibody is a humanized anti-PD-L1 antibody. In some embodiments, the anti-PD-L1 antibody is atezolizumab (Genentech; CAS registration number: 1422185-06-5). Atezolizumab is a humanized monoclonal antibody against PD-L1. Atezolizumab binds to PD-L1, blocking its binding and activation to PD-1 expressed on activated T cells, and enhancing T cell-mediated immune responses. The Fc region of atezolizumab is modified to not induce antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC). Atezolizumab has been approved for the treatment of non-small cell lung cancer, small cell lung cancer, breast cancer, and bladder cancer such as urothelial carcinoma, and has shown efficacy against alveolar soft part sarcoma. See, for example, the National Center Institute (NCI) Drug Dictionary.

[0018] The terms "anti-PD-L1 antibody" and "antibody that binds to PD-L1" refer to antibodies capable of binding to PD-L1 with sufficient affinity, such that the antibody can be used as a diagnostic and / or therapeutic agent targeting PD-L1. In one embodiment, the degree of binding of the anti-PD-L1 antibody to unrelated non-PD-L1 proteins is less than about 10% of the antibody binding to PD-L1, as measured by, for example, radioimmunoassay (RIA). In a particular embodiment, the dissociation constant (Kd) of the antibody binding to PD-L1 is 1 μM or less, 100 nM or less, 10 nM or less, 1 nM or less, 0.1 nM or less, 0.01 nM or less, or 0.001 nM or less (e.g., 10⁻⁸ M or less, e.g., from 10⁻⁸ M to 10⁻¹³ M, e.g., from 10⁻⁹ M to 10⁻¹³ M). In certain embodiments, the anti-PD-L1 antibody binds to a conserved PD-L1 epitope in PD-L1 from different species. This also applies to other antigens such as PD-1. In a preferred embodiment, the anti-PD-L1 antibody binds to human PD-L1, the information of which is shown in, for example, UniProtKB: Q9NZQ7.1 (e.g., the nucleotide and amino acid sequences shown in SEQ ID NO: 1 and 9, respectively).

[0019] As used herein, the term “monoclonal antibody (mAb)” means an antibody obtained from a substantially homogeneous population of antibodies, i.e., the individual antibodies constituting the population are consistent and / or bind to the same antigenic determinant, except for possible variant antibodies, such as naturally occurring mutant antibodies or mutant antibodies generated during the production of a monoclonal antibody preparation, which are typically present in small quantities. In contrast to multiclonal antibody preparations, which generally include different antibodies targeting different determinants (antigenic determinants), each monoclonal antibody in a monoclonal antibody preparation targets a single determinant on an antigen. Therefore, the modifier “monoclonal” indicates that the antibody is characterized by being obtained from a substantially homogeneous population of antibodies and should not be construed as requiring the antibody to be produced by any particular method. For example, monoclonal antibodies used according to the invention can be prepared by various techniques, including but not limited to hybridoma methods, recombinant DNA methods, phage display methods, and methods using transgenic animals containing all or part of the human immunoglobulin loci, such methods and other exemplary methods for preparing monoclonal antibodies are described herein.

[0020] A “humanized antibody” refers to a chimeric antibody comprising amino acid residues from a non-human HVR and amino acid residues from a human FR. In a particular embodiment, a humanized antibody will comprise at least one and typically two variable domains, wherein all or substantially all of the HVRs (e.g., CDRs) correspond to the HVRs of the non-human antibody, and all or substantially all of the FRs correspond to the FRs of the human antibody. Optionally, a humanized antibody may include at least a portion of the antibody constant region derived from a human antibody. A “humanized form” of an antibody (such as a non-human antibody) refers to an antibody that has been humanized.

[0021] The amino acid sequence of a “human antibody” corresponds to the amino acid sequence of an antibody produced by humans or human cells, or the amino acid sequence of an antibody derived from a non-human source using a human antibody library or other human antibody coding sequences. The definition of a human antibody specifically excludes humanized antibodies that include non-human antigen-binding residues.

[0022] "Effector functions" refer to those biological activities attributed to the Fc region of an antibody, which vary with antibody isotype. Examples of antibody efficacy functions include: C1q binding and complement-dependent cytotoxicity (CDC); Fc receptor binding; antibody-dependent cell-mediated cytotoxicity (ADCC); phagocytosis; downregulation of cell surface receptors (e.g., B cell receptors); and B cell activation. Effector functions can be manifested through effector T cells.

[0023] An “effective amount” of a drug, pharmaceutical, composition (e.g., a pharmaceutical composition), or agent (e.g., a therapeutic agent or pharmaceutical formulation) means an effective amount that achieves the desired therapeutic or preventive outcome (such as cancer treatment) within the necessary dosage and time period.

[0024] In relation to “effective dose,” “therapeutic effective dose” in this document refers to the amount of a drug / medicine / pharmaceutical used to treat or prevent disorder / disease in a patient. In some embodiments, when treating cancer or tumors, a therapeutically effective dose of the agent reduces the number of cancer cells and / or the size of the tumor; inhibits the infiltration of cancer cells into surrounding organs; inhibits tumor metastasis; inhibits tumor growth; and improves cancer-related symptoms. When such cancer therapeutic agents are used, the efficacy or therapeutic effect is assessed through, for example, survival time, time to disease progression (TP), response rates (RR), response time, and quality of life (QOL).

[0025] "Patient," "subject," or "individual" (these terms are used interchangeably) is preferably a mammal. Mammals include, but are not limited to, domesticated animals (e.g., cattle, sheep, cats, dogs, and horses), primates (e.g., human and non-human primates, such as monkeys), rabbits, and rodents (e.g., mice and rats). In certain embodiments, the patient / subject is a human. In some embodiments, the patient / subject is a patient / subject with or suspected of having cancer that has responded to treatment, including the administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody).

[0026] As used herein, “therapy” or “treatment” (or grammatical variations thereof such as “treat” or “treating”) refers to a clinical intervention that attempts to alter the natural course of disease in an individual being treated, and may be performed for prevention or during the clinicopathological process. The desired effects of a treatment include, but are not limited to, preventing the onset or recurrence of disease, alleviating symptoms, reducing any direct or indirect pathological consequences of the disease, preventing metastasis, slowing the rate of disease progression, improving or alleviating the disease state, and achieving remission or improved prognosis. In some embodiments, the antibodies of the present invention are used to delay the development of disease or slow its progression.

[0027] In one aspect, the present invention provides a method for treating cancer that responds to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody). In one embodiment, the method includes administering an effective amount of a PD-1 / PD-L1 inhibitor, such as an anti-PD-1 antibody or an anti-PD-L1 antibody, to a patient / subject suffering from cancer. In such embodiments, the method further includes administering an effective amount of at least one additional therapeutic agent described herein to the patient / subject. According to any embodiment herein, "patient / subject" may be a human.

[0028] In this document, “detection” or “detecting” refers to any type of detection, i.e., direct and indirect detection. The detection may be qualitative or quantitative. In some embodiments, the method of the present invention includes detecting a marker (biomarker) or a chemokine. In some embodiments, detection is measuring the amount or level of the marker or chemokine (e.g., mRNA expression level), or measuring the average and / or total amount of such levels.

[0029] In this document, a “marker” (also called a “biomarker”) refers to an indicator that can be detected or measured in a sample from a patient for prediction, diagnosis, prognosis, etc. Markers can be used as indicators of cancers with certain pathological or clinical characteristics, such as cancers that respond to treatment including the administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody). Markers include, but are not limited to, polynucleotides (mRNA, DNA, etc.), polypeptides, polypeptide and polynucleotide modifications (e.g., post-translational modifications), carbohydrates, etc. In some embodiments, the marker is the mRNA or transcript of a gene. In this invention, such markers include dendritic cell markers and chemokines.

[0030] In some embodiments, the presence and / or performance level / quantity of markers in a sample can be measured or evaluated using conventional methods understood by those skilled in the art. These methods include, but are not limited to: RNA-Seq (a state-of-the-art RNA sequencing technology that can also detect or quantify RNA expression levels), Northern blotting, polymerase chain reaction (PCR) such as quantitative real-time PCR (qRT-PCR), and other methods such as branched DNA, nucleic acid sequence-based amplification (NASBA), transcription-mediated amplification (TMA), fluorescence in situ hybridization (FISH), microarray analysis, gene expression profiling, serial analysis of gene expression (SAGE), immunohistochemistry (IHC), Western blotting, immunoprecipitation, enzyme-linked immunosorbent assay (ELISA), enzyme-linked immunofiltration assay (ELIFA), and flow cytometry (FCM) (also known as fluorescence activated cell sorting). FACS, MassARRAY, proteomics, quantitative blood analysis (such as serum ELISA), in situ hybridization, any other analysis on RNA, proteins, genes, and any tissue array method. Guidelines for assessing gene expression can be found, for example, in Ausubel et al., eds., 1995, Current Protocols in Molecular Biology.

[0031] In some embodiments, the marker in a sample is detected or measured (e.g., quantified) by the expression of the labeled mRNA. In some embodiments, the mRNA expression is detected or measured by RNA-seq, qPCR, rtPCR, multiplex qPCR or RT-qPCR, microarray analysis, nanostring technology, SAGE, MassARRAY, FISH, etc.

[0032] The “performance level,” “level,” “amount,” or “quantity” of a marker associated with a pathological or clinical feature is a detectable level / amount in a patient’s sample. It can be measured using methods known in the art or methods described herein. The performance level of the marker can be used to predict a patient’s response to cancer therapy.

[0033] In this article, "expression level" refers to the amount of marker in a sample from a patient. The term "expression" refers to the conversion of genetic information into molecular structures in cells. Therefore, "expression" includes transcription into mRNA, translation into peptides / proteins, polynucleotide modification, peptide modification, etc. Transcription products generated through alternative splicing, degraded transcription products, and post-translational modified peptides can be included in the "expressed" molecules.

[0034] In some embodiments, increased markers associated with the development of DCs and / or chemokines indicate that patients are more likely to experience greater clinical benefit when treated with therapies using PD-1 / PD-L1 inhibitors (such as anti-PD-1 antibodies or anti-PD-L1 antibodies). In some embodiments, clinical benefit includes, for example, a relative increase in overall survival (OS), progression-free survival (PFS), complete response (CR), partial response (PR), etc.

[0035] In this document, “sample” means a substance obtained from or derived from a patient or subject, including cellular molecules that will be detected or measured based on their, for example, amount, quantity, physical, biochemical, chemical, and / or physiological characteristics. In this document, “tumor sample” or “cancer sample” means any sample obtained from a tumor or cancer of a patient to be characterized. Without any limitation, the sample includes: cells (primary or cultured), cell supernatant, cell lysate, amniotic fluid, blood-derived cells, cerebrospinal fluid, follicular fluid, lymph, plasma, breast milk, mucus, sweat, platelets, saliva, semen, serum, sputum, synovial fluid, tears, tissue culture medium, tissue extract, tissue homogenate, tumor cells, tumor cell extract, tumor tissue, tumor lysate, urine, vitreous fluid, and whole blood.

[0036] In some embodiments, the sample is a tissue sample or a tumor tissue sample from a patient. In some embodiments, the tissue sample may include tumor cells, tumor-infiltrating immune cells, stromal cells, etc. In some embodiments, the sample is a clinical sample. In some embodiments, the sample is used to identify or select a patient. In some embodiments, the sample is obtained from a patient's primary or metastatic tumor. To obtain a tissue sample, a biopsy can be used to collect representative tumor tissue.

[0037] In this document, "tissue sample" or "cell sample" refers to tissue or cells collected from the patient / subject to be tested. In this document, "tumor tissue sample" or "tumor cell sample" refers to tumor tissue or cells collected from the patient / subject's cancer or tumor. Tissue / cell samples may be obtained from solid tissue of fresh or frozen / preserved organs of the patient / subject, biopsy sections, blood, blood components, plasma, amniotic fluid, cerebrospinal fluid, interstitial fluid, peritoneal fluid, or cells. Tissue / cell samples may include primary or cultured cells. Tissue samples may contain additional, non-natural components, including antibiotics, anticoagulants, buffers, fixatives, nutrients, preservatives, etc.

[0038] In some embodiments, the sample is obtained from a patient's tissue sample or tumor tissue sample (e.g., a biopsy). In some embodiments, the tissue sample is obtained from any of the following tissues / cells: bladder tissue, breast tissue, or colorectal tissue, esophageal tissue, stomach tissue, head and neck tissue, lung tissue, mesothelial tissue, osteosarcoma tissue, ovarian tissue, pancreatic tissue, prostate tissue, kidney tissue, skin tissue, thyroid tissue, urothelial tissue, blood cells, bone, bone marrow, liver tissue, lymph nodes, etc. In some embodiments, the sample is a lung tissue sample.

[0039] In this article, “response” (or variations thereof such as “responsive” and “responsiveness”) refers to a patient response assessed through any endpoint that shows or suggests benefit to the patient. These include, but are not limited to, inhibiting cancer / tumor progression, such as completely stopping or slowing it; reducing cancer / tumor size; inhibiting, reducing, completely stopping, or slowing invasion into surrounding organs / tissues; inhibiting, reducing, completely stopping, or slowing metastasis; alleviating cancer / tumor-related symptoms; increasing survival time (e.g., overall survival and disease-free survival); and reducing mortality at some point after cancer treatment.

[0040] When assessing the response or responsiveness of a tumor / cancer to treatment, the Best Overall Response (BOR) is defined as the best response recorded from the start of treatment until cancer progression / recurrence. The following criteria can be used for response: Complete Response (CR); Partial Response (PR); Stable Disease (SD); and Progressive Disease (PD). These definitions are well known to those skilled in the art.

[0041] In this document, a patient’s “responsiveness” to treatment with a drug (e.g., an anti-PD-L1 antibody) (or a grammatical variation thereof, such as “responsive to…”) refers to a clinical or therapeutic benefit for a patient who has or is suspected of having a disease (such as cancer or a tumor). Such benefits include, but are not limited to, the following: (i) extended or prolonged survival (e.g., overall survival (OS) and progression-free survival (PFS)); (ii) a response of interest (e.g., complete remission (CR), partial remission (PR), no change (SD), disease control rate (DCR; CR+PR+SD)); or (iii) improvement of cancer / tumor signs or reduction of cancer / tumor symptoms. The presence or elevation of a marker, relative to patients without a marker or without elevated marker performance, can be used to identify patients who are more likely to respond to treatment. The presence or elevation of a marker, relative to patients without a marker or without elevated marker performance, can be used to predict or determine an increased likelihood that a patient can / will benefit from treatment.

[0042] In this article, “treatment” (e.g., “anti-cancer / tumor treatment”) refers to medical interventions that can be used to treat a disease (e.g., cancer / tumor). Drugs or anti-cancer therapeutic agents can be used in treatment. These include, but are not limited to, inhibitors (such as PD-1 / PD-L1 inhibitors, including PD-1 inhibitors and PD-L1 inhibitors that inhibit the binding between PD-1 and PD-L1), antibody pharmaceuticals (such as anti-PD-1 antibodies and anti-PD-L1 antibodies), agents for radiotherapy, anti-angiogenic agents, anti-tubulin agents, apoptosis agents, chemotherapy agents, cytotoxic agents, growth inhibitors, and any other agents or pharmaceuticals used to treat cancer / tumor, platelet-derived growth factor inhibitors, COX-2 inhibitors, interferons, cytokines, antagonists / agonists that bind to cancer-related molecules, etc.

[0043] Chemokines are known to participate in the maintenance of lymphoid tissues and control inflammation through cell migration, differentiation, and activation. They have also been reported to play a key role in recruiting immune cells from tumor tissues and lymph nodes. Chemokines are proteins with approximately 70 to 100 amino acid residues, and are classified into four subfamilies based on their amino acid sequence motifs containing cysteine ​​residues: CC, CXC, CX3C, and C. Mouse XCL1 and human XCL1 and XCL2 are known to belong to the C subfamily of chemokines. XCR1 (also known as GPR5) is the receptor for XCL1 and XCL2; that is, XCL1 and XCL2 act as agonists of XCR1 (the dendritic cell marker described herein). Mouse XCR1 is primarily expressed on CD8+ / CD103+ dendritic cells (DCs) in lymphoid tissues and peripheral tissues. Human XCR1 is expressed on CD141+ dendritic cells (DCs), similar to mouse dendritic cells (DCs).

[0044] Mouse XCR1+ / CD8+ / CD103+ dendritic cells and human XCR1+ / CD141+ dendritic cells exhibit strong cross-presentation capabilities. In "normal" antigen presentation, only proteins synthesized by the cell itself are degraded by the proteasome and loaded onto the major histocompatibility complex (MHC) and presented to CD8+ T cells. Products taken up from the extracellular environment via phagocytosis and degraded by endosomes and lysosomes are loaded onto the MHC class II and presented to CD4+ T cells. Conversely, in cross-presentation, products degraded by endosomes and lysosomes are loaded onto the MHC class I and presented to CD8+ T cells to induce the differentiation and proliferation of cytotoxic T cells. Cross-presentation is considered important for cytotoxic activity against tumors. In this article, "cross-presentation capability" refers to the ability of dendritic cells to present products to T cells. Dendritic cells with this capability are referred to as "cross-presenting dendritic cells." If the cells are CD8 positive T cells, this ability is called "cross-presentation ability to CD8 positive T cells".

[0045] An important function of chemokines is to accumulate effector T cells in tumors. Examples of chemokines include CXCL9 (also known as MIG; UniProtKB: Q07325 (human); e.g., the nucleotide and amino acid sequences shown in SEQ ID NO: 2 and 10, respectively), CXCL10 (also known as IP-10; UniProtKB: P02778 (human); e.g., the nucleotide and amino acid sequences shown in SEQ ID NO: 3 and 11, respectively), and CXCL11 (also known as I-TAC; UniProtKB: O14625 (human); e.g., the nucleotide and amino acid sequences shown in SEQ ID NO: 4 and 12, respectively). In summary, CXCL9, 10, and 11 belong to the CXC chemokine family and are ligands of CXCR3. They are produced by cells stimulated by inflammatory cytokines, particularly interferon-γ, such as macrophages, dendritic cells (DCs), and fibrocytes. CXCR3 is a chemokine receptor highly expressed on effector T cells and plays a crucial role in T cell transport. CXCR3 expression is induced by activation of naive T cells. Specifically, CXCL9 interacts with CD8+ T cells to play an important role in lymphocyte transport. CXCL10 is secreted by fibroblasts and macrophages stimulated by inflammatory cytokines and exhibits chemotactic activity towards monocytes, macrophages, T cells, and natural killer (NK) cells. CXCL11 is a low-molecular-weight chemokine that attracts activated T cells, monocytes, B cells, Th1 lymphocytes, and NK cells.

[0046] Dendritic cell markers can be used in this invention. The amount / quantity / number of dendritic cells (e.g., tumor-infiltrating dendritic cells or functional dendritic cells with cross-presentation capability) in tumor tissue samples obtained from cancer patients can show a response to PD-1 / PD-L1 inhibitors (such as anti-PD-1 antibodies and anti-PD-L1 antibodies). Therefore, in some embodiments, the markers of this invention can be markers used to estimate the amount of dendritic cells in a tumor. The amount of dendritic cells in a tumor can be estimated or determined by detecting the performance level of markers associated with the activation, development, and / or maturation of dendritic cells with cross-presentation capability. The markers include, but are not limited to, XCR1, Clec9, Irf8, and Batf3. The markers can be used individually or in combination as a cumulative performance of the markers, such as a cumulative DC gene score (DC score). The performance of multiple markers can be combined using any suitable mathematical method known in the art to obtain a DC score. The DC score can be obtained based on the marker performance levels described herein.

[0047] In some embodiments, the present invention provides: a method for identifying a patient with or suspected of having cancer, said cancer responding to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (which may be a PD-1 inhibitor or PD-L1 inhibitor that inhibits the binding between PD-1 and PD-L1, such as an anti-PD-1 antibody or an anti-PD-L1 antibody; this also applies to other embodiments of the present invention), said method comprising: detecting in a sample from the patient the following (i) and (ii): (i) at least one marker, which is an antigen-presenting cell marker or an antigen presentation marker; and (ii) at least one chemokine or chemoattractant.

[0048] In some embodiments, the present invention provides: a method for identifying a patient with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor, said method comprising: detecting in a sample from the patient the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) capable of cross-presenting CD8-positive T cells within the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor.

[0049] Throughout the specification / patent application, “method of identifying patients” can be rewritten as “method of selecting patients”, “method of screening patients”, “method for screening patients”, etc.

[0050] In some embodiments, the antigen-presenting cell marker (or antigen-presenting label) is a dendritic cell marker expressed on or in dendritic cells.

[0051] In some embodiments, the chemokine or chemokine is a T cell chemokine or T cell chemokine that attracts T cells by being recognized or bound by T cell chemokine receptors on the surface of T cells.

[0052] In some embodiments, the present invention provides: a method for identifying a patient with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody), said method comprising: detecting in a sample from the patient the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells within the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor.

[0053] In some embodiments, the present invention provides a method for detecting the following (i) and (ii) in a sample from a human individual: (i) at least one marker for estimating the number of dendritic cells (DCs) capable of cross-presenting CD8-positive T cells; and (ii) at least one chemokine that accumulates on effector T cells.

[0054] In some embodiments, the present invention provides a method for predicting the therapeutic effect (or efficacy) of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody) on a cancer patient, wherein the method comprises: detecting the following (i) and (ii) in a sample from the patient: (i) at least one marker for estimating the number of dendritic cells (DCs) with cross-presentation capability to CD8 positive T cells in the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor.

[0055] In some embodiments, the treatment comprises administering an effective amount of a PD-1 / PD-L1 inhibitor. In some embodiments, the PD-1 / PD-L1 inhibitor is an anti-PD-1 / PD-L1 antibody. In some embodiments, the anti-PD-1 / PD-L1 antibody is a humanized anti-PD-1 / PD-L1 antibody. In some embodiments, the humanized anti-PD-1 / PD-L1 antibody is atezolizumab. Preferably, the treatment is administered to a patient who has or is suspected of having cancer that has responded to the treatment.

[0056] The terms “cancer” and “cancerous” refer to or describe a physiological condition in mammals that is typically characterized by uncontrolled cell growth / proliferation. Examples of cancer include, but are not limited to: carcinoma, lymphoma (e.g., Hodgkin's and non-Hodgkin lymphoma), blastoma, sarcoma, melanoma, and leukemia such as acute lymphoblastic leukemia. More specific examples of these cancers include squamous cell carcinoma, lung cancer, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), lung adenocarcinoma, squamous cell carcinoma of the lung, peritoneal cancer, hepatocellular carcinoma, stomach cancer, gastrointestinal cancer, pancreatic cancer, glioma, cervical cancer, ovarian cancer, liver cancer, bladder cancer, urothelial carcinoma, hepatoma, breast cancer, colorectal cancer, endometrial or uterine cancer, salivary gland cancer, kidney cancer, prostate cancer, vulvar cancer, thyroid cancer, hepatic carcinoma, leukemia and other lymphoproliferative disorders, and various types of head and neck cancers. In some embodiments, the cancers are those to which anti-PD-1 or anti-PD-L1 antibodies are applicable. In some embodiments, the cancers are those to which atezolizumab is applicable. Given drug approvals obtained from entities such as the U.S. Food and Drug Administration (FDA) or prior art, those skilled in the art or medical practitioners can appropriately understand whether such approvals are applicable to cancer (or whether they can be used to treat cancer). In some embodiments, the cancer is selected from the group consisting of: breast cancer, non-small cell lung cancer, small cell lung cancer, bladder cancer such as urothelial carcinoma, and alveolar soft tissue sarcoma. In some embodiments, the cancer is non-small cell lung cancer.

[0057] The term “tumor” refers to the growth and proliferation of all neoplastic cells, whether malignant or benign, as well as all precancerous and cancerous cells and tissues. The terms “cancer,” “cancerous,” and “tumor” are not mutually exclusive in this document.

[0058] In this article, a “suspected cancer patient” refers to a patient who, considering subjective symptoms, objective symptoms, and the results of a predictive cancer diagnosis, is likely or probably has cancer, for example, through image analysis such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT); analysis of bodily fluids such as blood and urine; analysis of nucleic acids derived from the patient, such as DNA and RNA; and any predictive analysis used to diagnose cancer.

[0059] In some embodiments, the marker is a non-T-cell activation marker, that is, the marker is not a T-cell activation marker. If such a T-cell activation marker is used as a predictive marker, there is a concern that potential patients expected to respond to PD-1 / PD-L1 inhibitors may not be identified, where PD-1 or PD-L1 expression levels are low or nonexistent, the IFN-γ pathway is not activated, or there is little activated T-cell infiltration into the tumor, but activation has occurred in draining lymph nodes. Additionally, there is a concern that by including all patients with persistent PD-L1 expression in their tumors, patients without cancer antigens and unresponsive to PD-1 / PD-L1 inhibitors may be selected. Therefore, preferably, the present invention excludes the use of such T-cell activation markers. T-cell activation markers are known in the art and include, but are not limited to: CD69, CD25, CD28, CD38, CD40L, IFN-γ, PD-1, CD8, granzymes, and perforin.

[0060] In some embodiments, the marker is an antigen-presenting cell (APC) marker or an antigen presentation marker. In some embodiments, the marker is an antigen-presenting dendritic cell marker. In some embodiments, the marker is a cross-presenting dendritic cell marker. In some embodiments, the marker is selected from one or more markers of the group consisting of: XCR1, Clec9, Irf8, Batf3, CD205, CD103, and CD141, which are specific examples of dendritic cell markers, particularly cross-presenting dendritic cell markers. In some embodiments, the marker is selected from one or more markers of the group consisting of: XCR1, Clec9, Irf8, and Batf3. In some embodiments, the marker is one, two, three, or all of XCR1, Clec9, Irf8, and Batf3. In some embodiments, the marker is XCR1 alone.

[0061] In some embodiments, the chemokine is a T-cell chemokine. In some embodiments, the chemokine is a chemokine that accumulates effector T cells in a tumor. In some embodiments, the chemokine is a CXCR3 ligand. In some embodiments, two, three, or more CXCR3 ligands are used in combination as the chemokine. In some embodiments, the chemokine is one, two, or all of CXCL9, CXCL10, and CXCL11. In some embodiments, the chemokine is all of CXCL9, CXCL10, and CXCL11.

[0062] In this document, "patient cohort" refers to a population of patients who have or are suspected of having the same type of disease and (will) receive the same type of medical treatment. In some embodiments, patients in this invention belong to a patient cohort. Such a patient cohort may be suitably determined and may be of any size. In some embodiments, the patient cohort consists of a population of patients who have or are suspected of having cancer. In some embodiments, the patient cohort consists of a population of patients with various levels of intratumoral PD-L1 expression, which may be low or high. In some embodiments, patients belong to a patient cohort that includes patients with low (lower) intratumoral PD-L1 expression and patients with high (higher) intratumoral PD-L1 expression. In addition to patients who are expected to respond to treatment and have relatively high PD-L1 expression, this invention is able to identify potential patients who are expected to respond to treatment and have low or no PD-L1 expression. This invention can detect the entire effective patient cohort for PD-1 / PD-L1 inhibitors (e.g., anti-PD-1 antibodies or anti-PD-L1 antibodies), including patients with relatively low or no PD-L1 expression in their tumors. The thresholds for defining “high / low” performance are discussed elsewhere in this article.

[0063] In some embodiments, the method of the present invention detects: (i) at least one marker; and (ii) at least one chemokine. In some embodiments, the method of the present invention detects: (i) at least one marker; and (ii) one, two, three, or more chemokines. In some embodiments, the detection of (i) is measuring the mRNA expression level of the marker, and the detection of (ii) is measuring the mRNA expression level of one, two, three, or more chemokines. In some embodiments, the detections of (i) and (ii) are measuring the average (“AP / T score”) of the mRNA expression levels of the marker and one, two, three, or more chemokines. In the present invention, chemokines can be used in combination as biomarkers, including chemokines of accumulating effector T cells, such as CXCL9, CXCL10, and CXCL11. In some embodiments, the marker is XCR1, and the chemokine is one, two, or all of CXCL9, CXCL10, and CXCL11. Compared to using a single marker, the combination of biomarkers is expected to improve the accuracy of predictive analysis.

[0064] In some embodiments, the method further includes determining whether the marker and chemokine are detected. In some embodiments, the method further includes determining whether the mRNA expression level (or average expression level; "AP / T score") of the marker and chemokine is equal to or greater than a threshold.

[0065] In some embodiments, the method further includes identifying a patient as a recipient of the treatment if the mRNA expression level (or mean expression level; "AP / T score") of the labeled and / or chemokine is equal to or greater than a threshold. In some embodiments, the method further includes determining that the patient / subject has been treated if the mRNA expression level (or mean expression level; "AP / T score") of the labeled and / or chemokine is equal to or greater than a threshold. In some embodiments, the method further includes treating the (identified) patient / subject. In some embodiments, the method further includes administering an effective amount of a PD-1 / PD-L1 inhibitor, such as an anti-PD-1 antibody or an anti-PD-L1 antibody, to the patient / subject.

[0066] In some embodiments, in the method of the present invention, the detection (e.g., the detections mentioned herein in (i) and (ii)) is to determine an average (“AP / T score”) of the following (a) and (b): (a) the mRNA expression level of the label; and (b) the mRNA expression level of the chemokine. In some embodiments, the detection determines an average (“AP / T score”) of the following (a) and (b): (a) the mRNA expression level of the label; and (b) the mRNA expression levels of one, two, three, or more chemokines. In some embodiments, the label is XCR1, and the chemokine is selected from CXCL9, CXCL10, and CXCL11. In some embodiments, the label is XCR1, and the chemokine is all of CXCL9, CXCL10, and CXCL11. In some embodiments, the method further includes determining whether the average (“AP / T score”) is equal to or greater than a threshold.

[0067] In some embodiments, the method further includes identifying a patient as a patient / subject to receive the treatment if the average (“AP / T score”) is equal to or greater than a threshold. In some embodiments, the method further includes determining that a patient / subject has been treated if the average (“AP / T score”) is equal to or greater than a threshold. In some embodiments, the method further includes treating (identified) patients / subjects whose average (“AP / T score”) is equal to or greater than a threshold. In some embodiments, the method further includes administering an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody) to patients / subjects whose total amount is equal to or greater than a threshold.

[0068] In some embodiments, the method further includes displaying or predicting a high (or relatively high) therapeutic effect (or efficacy) of the PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody) on the patient if the mean (“AP / T score”) is equal to or greater than a threshold (compared to when the mean (“AP / T score”) is less than a threshold). In some embodiments, the degree (high / low) of the therapeutic effect (or efficacy) of the inhibitor is assessed using therapeutic indicators known in the art, such as: overall survival (OS), progression-free survival (PFS), complete response (CR), partial response (PR), no change (SD), disease control rate (DCR; CR+PR+SD), etc. In some embodiments, “high” therapeutic effect (or efficacy) means that the patient’s cancer responds to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody).

[0069] In some embodiments, the present invention provides a method of treating cancer in a patient who responds to treatment, the treatment comprising administering an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody), wherein the method comprises: obtaining a tissue sample from a human who has or is suspected of having cancer; detecting from the sample from the patient the following (i) and (ii): (i) at least one marker for estimating the number of dendritic cells (DCs) capable of cross-presenting CD8-positive T cells within the tumor; and (ii) at least one chemokine that accumulates effector T cells in the tumor; identifying a patient who has or is suspected of having cancer that responds to the treatment; determining that the (identified) patient has been treated; and treating the (identified) patient, or administering an effective amount of an inhibitor to the patient. In this context, “treatment” means surgical and / or medical treatment.

[0070] The accuracy of predicting the efficacy or effect of the method of the present invention can be assessed using the Receiver Operating Characteristic (ROC) curve, which is typically evaluated using a predictive algorithm. The ROC curve is a graph showing the diagnostic capability of a binary classification system with different discrimination thresholds. When generating the ROC curve, the area under the ROC curve (AUC) is calculated. AUC varies between 0 and 1. An AUC of 0.5 means "accidental," with no predictability. Generally, the following classifications are made: AUC 0.5 to 0.7, "low" accuracy; AUC 0.7 to 0.9, "moderate" accuracy; AUC 0.9 to 1.0, "high" accuracy. An AUC of 1 means perfect performance, i.e., 100% sensitivity and 100% specificity. In the context of the present invention, for example, AUC = 1 means that 100% of mice predicted to respond to treatment actually did respond, and 100% of mice predicted not to respond to treatment actually did not respond. This also applies to human models. However, in human clinical trials for cancer, a negative control could be a group receiving a conventional treatment (such as docetaxel) instead of a placebo. In this case, the ability to predict efficacy could be the increased predictability compared to docetaxel.

[0071] In some embodiments, the method of the present invention is a method for predicting a patient's response to a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody). In some embodiments, the method of the present invention is a method for predicting the therapeutic effect (or efficacy) of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody) on a patient. In some embodiments, the patient is a cancer patient.

[0072] A “threshold” (also called a “critical value” or “critical point”) can be suitably determined for distinguishing or predicting responsiveness and non-responsiveness to treatment. In some embodiments, the threshold is a threshold determined based on the levels of biomarkers (such as cellular markers and chemokines) in a patient group / population. For example, for a given entire patient group, the performance level of a patient’s biomarker (e.g., individual performance level, overall performance level, or average performance level (“AP / T score”), or any combination thereof) is measured and the patient is divided into “high performance” and “low performance” groups based on a given threshold for the performance level of the biomarker. In some embodiments, the threshold is determined such that a certain percentage of the total patients in the patient group (e.g., 30%, 50%, 70%, etc.) have a performance level equal to or greater than the threshold. In some embodiments, the threshold is determined such that a certain percentage of the total patients (e.g., 30%, 50%, 70%, etc.) are included in the “high performance” group with a performance level equal to or greater than the threshold, and the remainder of the total patients (e.g., 30%, 50%, 70%, etc.) are included in the “low performance” group with a performance level less than the threshold. If the threshold is increased, for example, by decreasing the percentage of the "high-performance" group, patients expected to be more responsive to treatment can be selected; however, sensitivity may decrease, and patients expected to be less responsive may be excluded. Therefore, the threshold can be appropriately determined based on the desired responsiveness to treatment and the required sensitivity for potential patients. In some embodiments, the threshold can be varied such that 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, or 70% of the total patients are included in the "high-performance" group. In the "high performance" group, that is, 70%, 69%, 68%, 67%, 66%, 65%, 64%, 63%, 62%, 61%, 60%, 59%, 58%, 57%, 56%, 55%, 54%, 53%, 52%, 51%, 50%, 49%, 48%, 47%, 46%, 45%, 44%, 43%, 42%, 41%, 40%, 39%, 38%, 37%, 36%, 35%, 34%, 33%, 32%, 31%, or 30% of the total patients are included in the "low performance" group. In some embodiments, a threshold is determined such that X% of the total patients in the patient group have a performance level equal to or greater than the threshold, where X = 30 to 70, for example, X equals any of the percentages mentioned above. In some embodiments, the percentage of the total patients is 30%, 50%, or 70%.To specify a threshold or cutoff value, the term "percentile" can be used. For example, "xth percentile" refers to the value (or fraction) below x% of the observations, that is, the data representing x% of the total patients, where x represents any of the above percentages, such as 30, 50, 70, etc.

[0073] In some embodiments, the present invention provides a method for selecting patients who have or are suspected of having cancer, the cancer being responsive to treatment, the treatment comprising administering an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody), wherein the method comprises: determining a patient cohort consisting of patients who have or are suspected of having cancer; measuring, from samples of each (and every) patient in the patient cohort, the mean (“AP / T score”) of the following (i) and (ii): (i) the mRNA expression level of a marker used to estimate the number of intratumoral dendritic cells (DCs) capable of cross-presenting CD8-positive T cells; and (ii) the mRNA expression level of one or more chemokines accumulating effector T cells in the tumor; determining a threshold such that the mean (“AP / T score”) of a certain percentage of the total patients in the patient cohort is equal to or greater than the threshold; and selecting a patient whose mean (“AP / T score”) is equal to or greater than the threshold.

[0074] In some embodiments, the present invention provides a method for predicting the therapeutic effect (or efficacy) of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody) on cancer patients in a patient cohort, wherein the method comprises: determining a patient cohort consisting of patients who have or are suspected of having cancer; measuring the mean (“AP / T score”) of the following (i) and (ii) in a sample from each patient in the patient cohort: (i) the mRNA expression level of at least one marker used to estimate the amount of dendritic cells (DCs) with cross-presentation capacity for CD8-positive T cells in the tumor; and (ii) the mRNA expression level of one or more chemokines that accumulate effector T cells in the tumor; determining a threshold such that the mean (“AP / T score”) of a certain percentage of the total patients in the patient cohort is equal to or greater than the threshold; and showing (or predicting) that the inhibitor has a high therapeutic effect (or efficacy) on patients with a mean (“AP / T score”) equal to or greater than the threshold.

[0075] In some embodiments, the present invention provides a kit (article) comprising one or more reagents for determining the presence or quantity of at least one marker and / or chemokine in a sample from a patient with cancer / tumor.

[0076] In some embodiments, the present invention provides a kit (or article of manufacture) comprising: one or more reagents for determining the presence or quantity of at least one marker and / or chemokine in a sample from a patient with cancer / tumor; and a package insert indicating that the one or more reagents are used to identify or select patients with or suspected of having cancer based on the presence or quantity of the marker / chemokine, said cancer responding to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody). In some embodiments, the present invention provides a method of manufacturing a kit (or article of manufacture) comprising, in a package, combining: one or more reagents for determining the presence or quantity of at least one marker and / or chemokine in a sample from a patient with cancer / tumor; and a package insert indicating that the one or more reagents are used to identify or select patients with or suspected of having cancer based on the presence or quantity of the marker / chemokine, said cancer responding to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody).

[0077] In some embodiments, the kit (or article) includes a container and a pharmaceutical leaflet or label (as referred to herein) on or attached to the container. The pharmaceutical leaflet or label may be in any form, such as paper, electronic media such as magnetic recording media, CDs, DVDs, etc. The container may include bottles, vials, syringes, etc. The container may be formed of materials such as glass or plastic. The kit (or article) may also contain other reaction materials, such as buffer solutions, diluents, filters, etc.

[0078] In some embodiments, the present invention provides the use of one or more reagents for manufacturing a kit (or product) for determining the presence or quantity of at least one marker and / or chemokine in a sample from a patient with cancer / tumor, the kit (or product) for identifying or selecting patients with or suspected of having cancer based on the presence or quantity of this marker / chemokine, the cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or an anti-PD-L1 antibody).

[0079] The reagent may be used for any of the following detection / quantification methods: RNA-Seq, Northern blotting, polymerase chain reaction (PCR) such as qRT-PCR, and other methods such as branched DNA, sequence-based amplification (NASBA), transcription-mediated amplification (TMA), fluorescence in situ hybridization (FISH), microarray analysis, gene expression profiling, gene expression sequence analysis (SAGE), immunohistochemistry (IHC), Western ink dot assay, immunoprecipitation, enzyme-linked immunosorbent assay (ELISA), enzyme-linked immunofiltration assay (ELIFA), flow cytometry (FCM) (also known as fluorescence activated cell sorting (FACS)), MassARRAY, proteomics, quantitative blood analysis (such as serum ELISA), in situ hybridization, and any other analysis performed on RNA, proteins, genes, and any tissue array method. In some embodiments, the reagent is a reagent used in RNA-Seq, which detects the mRNA levels of one or more labeled and / or chemokines.

[0080] In some embodiments, the present invention provides a kit (or article) for identifying or selecting patients with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody), comprising (i) a reagent for detecting at least one labeled substance; and (ii) a reagent for detecting at least one chemokine. In some embodiments, the present invention provides the use of (i) the reagent for detecting at least one labeled substance; and (ii) the reagent for detecting at least one chemokine, in the manufacture of a kit (or article) for identifying or selecting patients with or suspected of having cancer, said cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor (such as an anti-PD-1 antibody or anti-PD-L1 antibody). In some embodiments, the chemokine is one, two, three, or more chemokines. In some embodiments, detection of the reagent through (i) measures the mRNA expression level of the label, and detection of the reagent through (ii) measures the mRNA expression level of one, two, three, or more chemokines. In some embodiments, the kit (or product) is used to measure the average (“AP / T score”) of the mRNA expression level of the label and the mRNA expression levels of one, two, three, or more chemokines. In some embodiments, the chemokines are selected from the group consisting of CXCL9, CXCL10, and CXCL11. In some embodiments, the label is XCR1, and the chemokines are all of CXCL9, CXCL10, and CXCL11. In some embodiments, the label is XCR1, and the chemokines are CXCL9 and CXCL10. In some embodiments, the label is XCR1, and the chemokines are CXCL10 and CXCL11. In some embodiments, the label is XCR1, and the chemokines are CXCL9 and CXCL11. In some embodiments, the label is XCR1, and the chemokines are CXCL9. In some embodiments, the marker is XCR1, and the chemokine is CXCL10. In some embodiments, the marker is XCR1, and the chemokine is CXCL11. In some embodiments, the kit (or product) is used to determine whether the average of the mRNA expression levels of the marker and the mRNA expression levels of the chemokine (“AP / T score”) is equal to or greater than a threshold. The threshold may be determined based on the disclosure herein.

[0081] For clarity of understanding, although the invention has been or will be described in more detail herein through description and examples, such description and examples should not be construed as limiting the scope of the invention. All disclosures of patents and scientific literature cited herein are expressly incorporated herein by reference in their entirety. [Examples]

[0082] The following are examples of the methods and compositions of the present invention. It should be understood that various other embodiments can be implemented in view of the general description provided above.

[0083] Experimental Design Overview: The inventors tested the antitumor effect of an in vivo anti-mouse PD-L1 monoclonal antibody (mAb) in a mouse model. Flow cytometry, tumor-stimulated IFNγ release analysis, repertoire analysis, RNA sequencing, protein immunoassays, and immunohistochemistry were performed on isolated tumors or tumor-draining lymph nodes (dLNs). The accuracy of the predictive markers was evaluated in 17 tumor models through receiver operating characteristic (ROC) curve analysis.

[0084] Materials and Methods: Cell lines: Seventeen different cell lines were used. All cells were properly maintained and transfected.

[0085] Tumor Model: Cancer cells were subcutaneously implanted into the right flank of mice. When the tumor volume reached approximately 50-200 mm3 (day 1), anti-PD-L1 antibody or control IgG was administered. Anti-mouse PD-L1 mAb or rat IgG was administered intraperitoneally three times a week at a dose of 10 mg / kg. Anti-mouse CXCR3 mAb or hamster IgG was administered intraperitoneally twice a week at a dose of 50 μg / head. Tumor volume (V) was estimated using the equation V = L × W² × 0.5 (L = length; W = width). The percentage of tumor growth inhibition (TGI%) was calculated as follows: TGI% = [1 - (tumor volume of the treatment group on the last assessment day - tumor volume of the treatment group on day 1) / (tumor volume of the control group on the last assessment day - tumor volume of the control group on day 1)] x 100.

[0086] Flow cytometry analysis: To analyze tumor-infiltrating lymphocytes, tumor tissue was excised from control-treated mice and mice treated with anticancer drugs. Single-cell suspensions were obtained by dissecting the tumor and homogenizing it using a gentle MACS Dissociator. Cells were analyzed using an LSR Tortessa X-20 cell analyzer (BD Biosciences).

[0087] RNA Sequencing (RNA-seq): All RNA was isolated from tumor tissue. Sequencing was performed using the Illumina HiSeq 2500 sequencing system (100 bp paired-end sequencing). To assess gene expression, RNA log performance (R) was estimated using the following formula: R = log(Fragment per thousand bases per million reads of target mRNA (FPKM) value) - log(FPKM value of housekeeping genes)). The AP / T score (i.e., the average) was calculated as follows: AP / T score = {R(XCR1) + R(CXCL9) + R(CXCL10) + R(CXCL11)} / 4.

[0088] Immunohistochemistry: The location of CD8α+ T cells in tumor tissue was assessed by immunohistochemical staining of CD8α. The expression of PD-L1 in tumor tissue was assessed by immunohistochemical staining of PD-L1.

[0089] Clinical Study Design and Assessments: The study design for OAK has been previously reported (Rittmeyer A, Barlesi F, Waterkamp D, Park K, Ciardiello F, von Pawel J, et al., Lancet (London, England) 2017; 389 (10066): 255-65). All patients provided signed informed consent, and the study was conducted entirely in accordance with the Good Clinical Practice Guidelines for Pharmaceuticals and the Declaration of Helsinki. TruSeq RNA Access technology (Illumina (registered trademark)) was used for transcriptional profiling of tumors via RNA sequencing. RNA sequencing data were primarily derived from archival tissue baselines. To analyze the relationship between tumor gene expression and clinical outcomes, as one of the simplest methods, in this embodiment, the mean mRNA levels of XCR1, CXCL9, CXCL10, and CXCL11 were referred to as the "AP / T score," and ORR and overall survival were selected, respectively.

[0090] Statistical Analysis: To assess statistical significance in mouse model experiments, the Wilcoxon test was used to analyze the data. For two groups, P < 0.05 indicated a significant difference. For multiple groups, P values ​​were adjusted using the Holm-Bonferroni method. Receiver operating characteristic (ROC) curves were constructed, and the area under the ROC curve (AUC) was calculated to assess diagnostic accuracy, and the AUCs of all test parameters were compared separately. To analyze clinical data from the OAK study, OS was compared between treatment groups using a univariate Cox proportional hazards model, where BEPs and their subgroups were not stratified. No multiple correction was performed on P values ​​or 95% CI. All P values ​​were two-sided. P < 0.05 indicated a significant difference. The Kaplan-Meier method was used to estimate median OS and construct survival curves. Gene expression levels between the CR / PR, SD, and PD groups were compared using the Kruskal-Wallis test. [Example 1]

[0091] Antitumor activity of PD-L1 mAb by expressing the PD-L1 gene in tumor tissue: The antitumor activity of PD-L1 mAb was examined in 17 murine tumor models. PD-L1 mAb showed significant antitumor activity in 6 tumor models, which were classified as sensitive tumors. In the remaining 11 tumor models, PD-L1 mAb did not show significant antitumor activity and were therefore classified as insensitive tumors (Figure 1A). To examine the ability of PD-L1 to classify tumors as sensitive or insensitive to PD-L1 mAb, the expression of PD-L1 mRNA in tumor samples was measured by RNA sequencing and ROC curves were analyzed. In sensitive models, the range of PD-L1 mRNA expression levels was wide and overlapped with the range in insensitive tumor models. The area under the ROC curve (AUC) was 0.848. The optimal cutoff points for specificity and sensitivity, as shown by Youden's index, were 0.818 and 0.833, respectively (Figure 1B). [Example 2]

[0092] Anti-PD-L1 mAb Exerts Antitumor Activity in PD-L1-Negative and Immunodesert-like Tumor Models: To examine why intratumoral PD-L1 mRNA expression cannot fully predict the antitumor activity of PD-L1 mAb in mouse models, the mechanism of action of PD-L1 mAb in low-PD-L1 tumor models was analyzed. The FM3A model was selected as a low-PD-L1 tumor model, which showed the lowest intratumoral PD-L1 mRNA expression among models classified as PD-L1 mAb-sensitive (Figure 1B). First, histochemical characterization of FM3A tumors was performed. Under conditions where another sensitive tumor, Colon 38, showed partial positive staining, PD-L1 immunohistochemical staining showed that almost all cells in the tumor tissue were negative (Figure 2A). CD8α immunohistochemical staining showed CD8α+ T cell infiltration in Colon 38 tumors, but very few CD8α+ T cells in FM3A tumors (Figure 2B). Next, flow cytometry analysis revealed that F4 / 80+ cells in FM3A tumors expressed PD-L1, but only in small quantities were found in the tumor tissue (Figures 2C and 2D). Tumor cells that showed almost no PD-L1 expression (CD45- cells) constituted the majority of the tumor tissue (Figures 2C and 2D). These results indicate that FM3A tumors have a PD-L1 negative and immune desert-like phenotype. [Example 3]

[0093] Anti-PD-L1 mAb enhanced T cell initiation already occurring in lymph nodes: Next, we investigated whether the antitumor activity of PD-L1 mAb in the FM3A tumor model was T cell-dependent. CD8α or CD4 depletion eliminated the antitumor activity of PD-L1 mAb (Fig. 3A). PD-L1 mAb significantly increased the T cell population in tumors, including CD8α+ cells, Foxp3-CD4+ cells, and Foxp3+CD4+ cells (Figs. 3B and 3C). To examine the level of T cell diversity in tumors treated with PD-L1 mAb, the diversity of the TCR repertoire was assessed using the Simpson diversity index. In tumors treated with PD-L1 mAb, the variation in TCRα was less than in control tumors, while specific elements of the TCRα repertoire were increased in tumors treated with PD-L1 mAb (Fig. 3D). It was found that the Simpson diversity index in the PD-L1 mAb treatment group was significantly lower than that in the control group (Fig. 3D). These results suggest that treatment with PD-L1 mAb can enrich tumor-reactive T cells. Therefore, the focus is on the role of tumor-draining lymph nodes and PD-L1 in T cell initiation. First, the expression of PD-L1 on antigen-presenting dendritic cells (DCs) in lymph nodes was investigated. CD103+CD11c+ cells expressed PD-L1 in lymph nodes (Fig. 4A, left). Next, the expression of PD-L1 receptors (PD-1 and B7-1) on CD8+ T cells in lymph nodes was analyzed. Most CD8α+ T cells were PD-1 and B7-1 negative CD44-CD62L+ naïve T cells, but some CD44+CD62L-CD8α+ effector T cells were PD-1 and / or B7-1 positive cells (Fig. 4A, right). PD-L1 mAb increased the number of B7-1+CD8α+ T cells, PD-1+CD8α+ T cells, and B7-1+PD-1+CD8α+ T cells, and increased the CD69+ ratio of B7-1+CD8α+ T cells, PD-1+CD8α+ T cells, and B7-1-PD-1-CD8α+ T cells (Fig. 4B). Due to the low cell count, the CD69+ ratio of B7-1+PD-1+CD8α+ T cells in the control group could not be detected (Fig. 4B). Next, the tumor-specific T cell response during PD-L1 mAb treatment was investigated. Using lymphocytes from tumor-draining lymph nodes, IFNγ production was significantly increased in the control group stimulated with FM3A cells compared to stimulation with MBT2 cells (MHC-matched negative control cells), and this increase was more significant in the PD-L1 mAb group compared to the control group (Fig. 4C).These results suggest that prior to PD-L1 mAb treatment in the FM3A model, tumor antigen presentation and T cell initiation had already occurred in the lymph nodes at baseline, but PD-L1 on the antigen-presenting cells prevented T cell initiation, while PD-L1 mAb unleashed T cells (Fig. 6D). [Example 4].

[0094] Anti-PD-L1 mAb increases CXCR3+ activated T cells in lymph nodes, thereby transporting T cells to the tumor through a response to CXCR3 ligands already expressed in the tumor: Next, the time course of CD8+ T cell activation in lymph nodes and tumors treated with PD-L1 mAb was analyzed in the FM3A model. On day 8, PD-L1 mAb treatment increased the number of CD69+CD8α+ T cells in lymph nodes and increased the percentage of these cells in the tumor (Fig. 5A). Importantly, on day 4, PD-L1 mAb treatment increased these cells in lymph nodes but not in the tumor (Fig. 5A). In addition, PD-L1 mAb treatment increased the number of CXCR3+CD69+CD8α+, CXCR3+granzyme B (GzmB)+CD8α+, and CXCR3+Ki67+CD8α+ T cells in lymph nodes (Fig. 5B). FM3A tumors exhibit CXCR3 ligands, particularly CXCL9, regardless of PD-L1 mAb treatment (Fig. 5C). Due to PD-L1 mAb treatment, CXCR3 mAb significantly inhibited the increase of activated CD8α+ T cells in the tumor, but not in the lymph nodes (Fig. 5D), and significantly attenuated the inhibitory effect of PD-L1 mAb on tumor growth (Fig. 5E). Conversely, in the PD-L1 mAb-insensitive OV2944-HM-1 model, the expression of CXCR3 ligands in the tumor was lower than in the FM3A model, confirming that PD-L1 mAb treatment increased the number of CD69+CD8α+ T cells in the lymph nodes, but not in the tumor (Fig. 5F). These results suggest that the time difference between the PD-L1 mAb-induced increase in activated CD8+ T cells in the lymph nodes and the increase in activated CD8+ T cells in the tumor is due to the transport of T cells from the lymph nodes to tumors exhibiting CXCR3 ligands. [Example 5]

[0095] Predicting the antitumor activity of anti-PD-L1 mAb through gene expression associated with cross-presenting DCs and the expression of CXCR3 ligand in tumor tissue: Two biological characteristics of the FM3A model explain the antitumor activity of PD-L1 mAb therapy by enhancing T cell initiation in lymph nodes and accelerating T cell transport to the tumor: (i) presentation of tumor antigens to T cells in draining lymph nodes, and (ii) expression of CXCR3 ligand in the tumor. To present tumor antigens to T cells in draining lymph nodes, a series of stepwise events must be initiated (Chen DS, Mellman I., Immunity 2013; 39(1): 1-10). The first step is to capture tumor antigens in the tumor for processing via antigen cross-presenting cells (APCs). XCR1 (Yamazaki C, et al., Journal of Immunology (Baltimore, Md: 1950) 2013; 190(12); 6071-82; UniProtKB: P46094 (human); e.g., nucleotide and amino acid sequences shown in SEQ ID NO: 5 and 13 respectively), Clec9a (Piva L, et al., Journal of Immunology (Baltimore, Md: 1950) 2012; 189(3): 1128-32; UniProtKB: Q6UXN8 (human)); e.g., nucleotide and amino acid sequences shown in SEQ ID NO: 6 and 14 respectively), Irf8 (Tailor P, et al., Blood 2008; 111(4): 1942-5; UniProtKB: Q02556 ... Clec9a (Piva L, et al., Journal of Immunology (Baltimore, Md: 1950) 2013; 190(12); 6071-82; UniProtKB: P46094 (human) respectively), Irf8 (Tailor P, et al., Blood 2008; 111(4): 1942-5; UniProtKB: Q02556 (human) respectively), Irf8 (Tailor P, et al., Blood 2008; 111(4): 1942-5; UniProtKB: The nucleotide and amino acid sequences in SEQ ID NO: 7 and 15, and Batf3 (Hildner K, et al., Science (New York, NY) 2008; 322(5904): 1097-100; UniProtKB: Q9NR55 (human)); for example, the nucleotide and amino acid sequences shown in SEQ ID NO: 8 and 16, respectively) are referred to as APC markers. To examine the ability of these APC markers to classify tumors as PD-L1 mAb sensitive or insensitive, their mRNA in tumors was measured and analyzed by ROC curves. The AUC values ​​of XCR1, Clec9a, Irf8, and Batf3 were 0.894, 0.621, 0.742, and 0.515, respectively (Figure 6A).Their specificities / sensitivities were 0.818 / 0.833, 0.727 / 0.667, 0.818 / 0.667, and 0.818 / 0.333, respectively. Next, to examine the relationship between the antitumor activity of PD-L1 mAb and CXCR3 ligand expression, the mRNA expression of CXCL9, CXCL10, and CXCL11 was measured, and ROC curves were analyzed. The AUC values ​​of the three CXCR3 ligands as a single factor were 0.939, 0.879, and 0.833, respectively, and the AUC value obtained by averaging these three values ​​was 0.970 (Figure 6B). The specificities / sensitivities of the three CXCR3 ligands were 1.000 / 0.833, 0.818 / 0.833, and 0.909 / 0.833, respectively, and the specificity / sensitivity obtained by averaging these three values ​​was 0.909 / 1.000. Therefore, the AUC, sensitivity, and specificity of any single factor are still not perfect. Sensitive tumors are considered to have two characteristics: (i) tumor antigen presentation in draining lymph nodes and (ii) CXCR3 ligand expression in the tumor at baseline. Therefore, the inventors created a combined biomarker: a combined biomarker of antigen expression-related gene expression and T cell attraction-related gene expression (AP / T score), defined as the average expression of XCR1 and CXCR3 ligands. The AUC, sensitivity, and specificity of the AP / T score all reached 1.000 (Figure 6C). [Example 6].

[0096] Data from the OAK Phase 3 clinical trial were used to retrospectively assess the predictability of AP / T scores, specifically the combined gene expression levels of the XCR1 and CXCR ligands as defined above: After confirming the association between the combined XCR1 and CXCR3 ligand expression and efficacy in preclinical models, AP / T scores, mean expression of XCR1, CXCL9, CXCL10, and CXCL11 were tested by applying them to patient tissue gene expression data obtained in the OAK study (a Phase 3 clinical trial). Higher AP / T scores were observed only in patients treated with atezolizumab who achieved CP / PR (Figure 7A), while this trend was not observed in the dodocetaxel group. More importantly, improved OS benefits were observed at all three score cutoffs (greater than or equal to 30, greater than or equal to 50, and greater than or equal to 70 percentiles) relative to the biomarker-evaluable population (BEP) observed in the OAK study (Figure 7B). In the subgroup with AP / T scores greater than or equal to the 50th percentile, the OS hazard ratio (HR) was 0.76 ((95% CI: 0.59–0.97); P = 0.031), numerically lower than that of BEP, and the median OS in the atezolizumab or docetaxel treatment groups was 15.0 and 11.1 months, respectively. Patients with high AP / T scores (greater than or equal to the 50th percentile) derive a significant OS benefit from atezolizumab compared to docetaxel, but no significant difference is observed in patients with low AP / T scores (< the 50th percentile). The estimated median OS in the atezolizumab group for the high and low AP / T subgroups (divided at the 50th percentile) was 15.0 and 11.8, respectively, while the estimated median OS in the docetaxel group was 11.1 and 9.8, respectively (Figures 7C and 7D). [Industry Applicability]

[0097] The results showed that anti-PD-L1 mAbs exert their anti-tumor activity by blocking dLN and PD-L1 in the tumor site, providing a theoretical basis for the efficacy of PD-L1 antibodies in patients with low PD-L1 expression. Furthermore, novel biomarkers combining tumor antigen presentation-related gene expression and activated T cell delivery-related gene expression have been demonstrated to predict responses to atezolizumab. These data suggest that this new approach, focusing on dLN activity, will provide better predictive biomarkers for anti-PD-1 antibodies or anti-PD-L1 antibodies (such as atezolizumab) compared to traditional biomarkers that only focus on tumor site activity, or may be further extended to immune checkpoint inhibitors. [Simplified Explanation of the Diagram]

[0099] [Figure 1] Showing the relationship between the antitumor activity of anti-PD-L1 monoclonal antibody (mAb) and PD-L1 expression (Examples 1 and 2). (A) Representative tumor growth curves: Mice with tumors were randomly assigned to groups. Solid line, control; dashed line, PD-L1 mAb 10 mg / kg. Data are shown as mean + SD (n = 5-15 / group). Statistical analysis was performed using the Wilcoxon rank sum test; *, P < 0.05; NS, not significant. (B) PD-L1 mRNA expression in tissues insensitive or sensitive to PD-L1 mAb (left) and ROC curve analysis (right). Shaded circles indicate results from the FM3A model. [Figure 2] Showing PD-L1 expression and CD8α+ T cell infiltration in the FM3A tumor model (Example 2). (A) PD-L1 immunostaining baseline values ​​in tumor tissues of the Colon 38 model (positive control) and the FM3A model. (B) Baseline values ​​of CD8α immunostaining in tumor tissue. (C) Tumor-infiltrating immune cells and PD-L1 expression on tumor cells in FM3A tumors. (D) Cell distribution in FM3A tumors. Cells were identified by flow cytometry (C, D). [Figure 3] Shows that anti-PD-L1 mAb increases specific T cells in tumors and leads to T cell-dependent antitumor activity in PD-L1-negative tumor models (Example 3). (A) Tumor volume in mice treated with PD-L1 mAb and CD8α mAb or CD4 mAb in an FM3A tumor model (n=7 / group, day 19). Data are shown as mean + SD. Statistical analysis was performed using the Wilcarson rank and Holm-Bonferroni method. *, P < 0.05. (B) Infiltration of CD8α+ T cells into the tumor by CD8α immunostaining in tumor tissue after treatment with PD-L1 mAb (day 19). (C) Percentage of each T cell type in the tumor after PD-L1 mAb treatment (day 19) (n=14 / group). Cells were identified by flow cytometry. Statistical analysis was performed using the Wilcoxon rank and test; *, P<0.05. (D) Percentage of T cell receptor α (TCRα) sequences in the tumor after PD-L1 mAb treatment (day 19). Next-generation sequencing was performed using unbiased TCR repertoire analysis. Diversity was examined based on the clonal dominance of each TCR clonoid using the reciprocal of Simpson's diversity index (n=3–5 / group). Data are presented as mean + SD. [Figure 4] shows the role of PD-L1 in T cell initiation in lymph nodes (Example 3).(A) Baseline values ​​of PD-L1 expression or PD-L1 receptor (PD-1 and B7-1) expression on dendritic cells (DCs) or CD8α+ T cells in lymph nodes. (B) Number of PD-L1 receptor (PD-1 and B7-1)+CD8α+ T cells in lymph nodes and frequency of CD69+ cells in each PD-L1 receptor+CD8α+ T cell after treatment with PD-L1 mAb (day 4) (n=12 / group). Statistical analysis was performed using Wilcarson rank and test; *, P < 0.05; NS, not significant. (C) IFNγ secretion after specific stimulation of lymphocytes by co-culture with tumor cells (n=3 / group). IFNγ was quantified by ELISA. Statistical analysis was performed using Student's t-test and Holm-Bonferroni method. *, P < 0.05. Data are presented as mean + SD. [Figure 5] Shows that the time difference between the increase in activated CD8α+ T cells in lymph nodes and the increase in tumors is caused by T cell delivery to TCO / ICO tumors (Example 4). (A) Time course of CD8α+ T cell activation in tumor draining lymph nodes and tumors after treatment with PD-L1 mAb (days 4 and 8) (n=12 / group). (B) Number of CXCR3+ activated CD8α+ T cells in lymph nodes after treatment with PD-L1 mAb (n=12 / group). (C) Performance of CXCR3 ligand in tumors (n=6 / group). (D) Number of activated CD8α+ T cells in lymph nodes and tumors after treatment with PD-L1 mAb (day 8) (n=6 / group). (E) Tumor volume in mice treated with PD-L1 mAb and anti-CXCR3 mAb in the FM3A tumor model (day 18) (n=6 / group). (F) Performance of CXCR3 ligand in FM3A and OV2944-HM-1 tumors (left). Number of activated CD8α+ T cells in lymph nodes (middle) and tumors (right) after PD-L1 mAb treatment (day 8) (n=8 / group). Data are shown as mean + SD. Statistical analysis was performed using Wilcarson rank and test and Holm-Bonferroni method. *, P < 0.05; NS, not significant. [Fig. 6A] (Figs. 6A to 6D) show the relationship between anti-PD-L1 mAb antitumor activity and antigen-presented DC-related gene expression and / or CXCR3 ligand gene expression in murine tumor models (Examples 3 and 5). Fig. 6A shows ROC curve analysis through antigen-presented DC-related gene expression. [Fig. 6B] ROC curve analysis through CXCR3 ligand expression. [Figure 6C] Shows the combined RNA performance and ROC curve analysis of the three CXCR3 ligands of XCR1 (“AP / T fraction”) in tumor tissues that are insensitive or sensitive to PD-L1 mAb.[ Figure 6D ] Hypothesis of the mechanism of action of anti-PD-L1 Ab based on cancer-immune cycle revealed in PD-L1-negative and immune-like desert tumor models. [ Figure 7A ] shows the correlation of clinical results and combined mRNA expression levels (“AP / T scores”) of XCR1, CXCL9, CXCL10, and CXCL11 in tumor tissues from the Phase III OAK trial (Example 6). Figure 7A shows the relationship between ORR and AP / T scores. [ Figure 7B ] shows the forest plot of HEs of OS in the BEP population, as well as AP / T scores above the 30th, 50th, and 70th percentile cutpoints. [Figure 7C] Figures 7C and 7D show Kaplan-Meier estimates of high and low AP / T score subgroups (divided at the 50th percentile) in the atezolizumab and docetaxel treatment groups and HRs forest plots of OS. [Figure 7D] Figures 7C and 7D show the Kaplan-Meier estimates and HRs forest plots of OS for the subgroups of high and low AP / T scores (with the 50th percentile as a division) in the atezizumab and docetaxel-treated groups.

Sequence List

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Claims

1. A method for predicting the efficacy of a PD-1 / PD-L1 inhibitor in a patient with or suspected of having cancer, the cancer being responsive to treatment including administration of an effective amount of a PD-1 / PD-L1 inhibitor, wherein the method comprises: A patient group is determined to consist of patients who have or are suspected of having cancer. The AP / T score was measured as the mean of the following mRNA log expression levels from tumor tissue samples from patients: (i) XCR1 as a non-T cell activity marker to estimate the number of dendritic cells (DCs) in the tumor capable of cross-presenting CD8-positive T cells; and (ii) one or more chemokines selected from the group consisting of CXCL9, CXCL10, and CXCL11 that accumulate effector T cells in the tumor; and the PD-1 / PD-L1 inhibitor was shown to be highly effective in patients whose mean was equal to or greater than the threshold.

2. The method as described in claim 1, wherein the treatment comprises administering an effective amount of an anti-PD-L1 antibody.

3. The method as described in claim 1 or 2, wherein the treatment comprises administering an effective amount of atezolizumab.

4. The method as described in claim 1 or 2, wherein the cancer is non-small cell lung cancer.

5. The method as described in claim 1 or 2, wherein the chemokine is all of CXCL9, CXCL10, and CXCL11.

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