Pharmaceutical composition for preventing or treating cancer

Abstract

The present invention relates to a pharmaceutical composition for preventing or treating cancer, the pharmaceutical composition containing CD4+ CTL as an active ingredient. The CD4+ CTL according to the present invention performs a cytotoxic function of directly attacking and killing myeloma cells, thereby extending the progression-free survival of transplant-ineligible myeloma patients, and thus can contribute to increasing the survival rate of the patients. In addition, by using NKG2D+ CD4+ CTL as a biomarker for predicting the prognosis of myeloma patients, it is possible to analyze the CD4+ CTL status of individual patients and thereby establish customized treatment strategies. In addition, by increasing the cytotoxicity of NKG2D+ CD4+ CTL through a specific cytokine treatment, it is possible to more effectively prevent or treat cancer.

Description

Pharmaceutical composition for the prevention or treatment of cancer

[0001] The present invention relates to a composition for predicting cancer prognosis comprising, as an active ingredient, a preparation for measuring CD4+ CTLs upregulated by the NKG2D protein biomarker. Furthermore, the invention relates to a pharmaceutical composition for the prevention or treatment of cancer comprising CD4+ CTLs as an active ingredient.

[0002] Multiple myeloma (MM) is a malignant tumor of plasma cells within the bone marrow that is known to interact closely with the immune system. Immunological dysfunction can be observed during the progression of the disease, and recent single-cell RNA and T-cell receptor sequencing (scRNA-seq, scTCR-seq) has enabled more detailed research into these immune dysfunctions.

[0003] Immunotherapy, particularly T-cell manipulation using chimeric antigen receptors (CARs) or bispecific antibodies, is considered to have brought innovation to the treatment of multiple myeloma. However, despite high initial responsiveness, these therapies have drawbacks, such as the fact that the response is not sustained in all patients and, above all, relapses are common. This signifies the limitations of existing immunotherapy and suggests the need for further research into the functional characteristics of effector T cells.

[0004] Despite advancements in immunotherapy, most therapeutic strategies have focused primarily on CD8+ cytotoxic T lymphocytes (CTLs). Accordingly, the inventors have completed the present invention by confirming that certain subtypes of CD4+ T cells, traditionally known to mediate help or regulation, possess cytotoxicity and express cytotoxicity particularly in hematological cancers.

[0005] The object of the present invention is to provide a pharmaceutical composition for the prevention or treatment of cancer comprising CD4+ CTL as an active ingredient.

[0006] Another objective of the present invention is to provide a pharmaceutical composition for the prevention or treatment of cancer comprising CD4+ CTLs, in which cytotoxicity is activated via cytokines, as an active ingredient.

[0007] Another objective of the present invention is to provide a method for providing information for predicting cancer prognosis, comprising the step of measuring the ratio of NKG2D+ CD4+ CTLs to provide information regarding the likelihood of continued progression-free survival (PFS).

[0008] Another objective of the present invention is to provide a composition for predicting cancer prognosis comprising a preparation for measuring NKG2D+CD4+ CTLs.

[0009] However, the technical problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by those skilled in the art from the description below.

[0010] Various embodiments of the present invention are described with reference to the drawings. In the following description, for a complete understanding of the present invention, various specific details, such as specific forms, compositions, and processes, are described. However, specific embodiments may be practiced without one or more of these specific details, or in combination with other known methods and forms. In other examples, known processes and manufacturing techniques are not described as specific details so as not to make the present invention unnecessary or obscure. Reference throughout this specification to one embodiment implies that the particular features, forms, compositions, or characteristics described in association with the embodiment are included in one or more embodiments of the present invention. Accordingly, the circumstances of the embodiments expressed at various locations throughout this specification do not necessarily represent the same embodiment of the present invention. Additionally, particular features, forms, compositions, or characteristics may be combined in any suitable way in one or more embodiments. Unless otherwise defined in the specification, all scientific and technical terms used in this specification have the same meaning as commonly understood by those skilled in the art to which the present invention pertains.

[0011] In this invention, the term "T cell" refers to a type of lymphocyte that matures in the thymus and regulates or directly attacks immune responses in response to specific antigens. Possessing highly specialized cell surface antigen receptors, it plays an important role in the immune system.

[0012] In this invention, the term "CD4" is used as a marker to distinguish T cell subtypes, and CD4+ T cells primarily play a role in assisting the immune response.

[0013] In this invention, the term "CD8" is used as a marker to distinguish T cell subtypes, and CD8+ T cells primarily function to destroy infected cells or cancer cells.

[0014] In this invention, the term "CD4+ CTL (Cytotoxic T Lymphocyte)" refers to a CD4+ T cell having cytotoxic function; while typical CD4+ T cells perform helper and regulatory functions, this refers to a cell that possesses cytotoxic function under specific conditions. CD4+ CTLs can directly kill target cells.

[0015] In the present invention, the term "NKG2D" refers to an important immune receptor expressed in natural killer (NK) cells and some T cells, which promotes an immune response by recognizing proteins expressed by cells under stress.

[0016] In the present invention, the term "NKG2D+ CD4+ CTL" refers to a CD4+ CTL possessing an NKG2D receptor, which can mediate a high cytotoxic response and plays a role in effectively recognizing and eliminating abnormal cells, particularly cancer cells.

[0017] In the present invention, the term "immature or naive T cell" refers to an immature T cell that has not yet received antigen stimulation.

[0018] In the present invention, the term "memory T cell" refers to a T cell that has previously been exposed to an antigen and retains memory of it, which reacts rapidly upon reinfection to trigger an immune response.

[0019] In the present invention, the term "Tfh cells (T follicular helper cells)" refers to T helper cells that interact with B cells to induce antibody production. They are antigen-experienced CD4+ T cells found within the follicular periphery of B cells in secondary lymphoid organs such as lymph nodes, the spleen, and Peyer's patches. They are identified by the constitutive expression of CXCR5, a B cell follicular homing receptor.

[0020] In this invention, the term "Th2 cell" refers to T helper cells involved in allergic reactions. They produce IL-4, IL-5, IL-9, IL-13, etc., and play a defensive role against parasitic infections and are involved in the mechanism of allergic inflammatory responses.

[0021] In this invention, the term "Th17 cells" refers to T helper cells associated with chronic inflammatory responses. It refers to a population of pro-inflammatory helper T cells that produces IL-17, and is associated with signals that inhibit the differentiation of actual regulatory T cells by differentiating Th17s. Th17 cells play a crucial role in maintaining the mucosal barrier and contribute to the elimination of pathogens from the mucosal surface. Furthermore, these cells are associated with autoimmune diseases and inflammatory diseases. A decrease in Th17 cells on the mucosal surface is associated with chronic inflammation and the spread of microorganisms.

[0022] In the present invention, the term "Treg cell" refers to a regulatory T cell that suppresses an immune response. In particular, it plays a role in regulating the immune response by inhibiting the function of CD4+ CTLs.

[0023] Subtypes of CD4+ T cells include, but are not limited to, naive cells (CCR7+TCF7+FAS-HNRNPLL-), early activated cells (early activated, early.act, CCR7+TCF7+FAS-NR4A1+), central memory cells (CM, CCR7+FAS+), follicular helper T cells (Tfh, CXCR5+BCL6+), Th2 (GATA3+CCR4+), Th17 (RORC+CCR6+), Th1 (TBX21+CXCR3+IFNG+), two subtypes of regulatory T cells (Treg, FOXP3+CTLA4+): resting regulatory T cells (rTreg, CCR7+) and activated regulatory T cells (aTreg, HLA-DRA+TNFRSF9+), and interferon-stimulated gene-high-expression cells (IFN-stimulated It may include genes-enriched (ISGshi, OAS3+IRF7+) and activated and proliferating cells (activated and proliferating, act.proli, MKI67+CD38+).

[0024] The various subtypes of the aforementioned CD4+ T cells play a crucial role in attacking myeloma cells and suppressing disease progression; in particular, as the disease progresses, changes in the composition ratio of CD4+ T cell subtypes and the expansion of specific clones are observed.

[0025] CD4+ CTL subtypes may include, but are not limited to, TE.CTL, Th1.CTL, and Th17.CTL.

[0026] In the present invention, the term "TE.CTL" refers to a subset of cytotoxic T cells characterized by high expression of GZMB, PRF1, GNLY, NKG7, etc., and is a cluster representing a terminally differentiated effector CTL (Terminal Effector CTL) subtype.

[0027] TE.CTL refers to terminally differentiated cytotoxic CD4+ T cell subtypes and includes TE.CTL1 and TE.CTL2. They highly express representative cytotoxic molecules such as granzyme B (GZMB), granzyme A (GZMA), NKG7, granulacin (GNLY), and perforin (PRF1), have a phenotype that is positive for B3GAT1 (CD57) and KLRG1 and negative for CD27, and consistently express the transcription factor RUNX3.

[0028] TE.CTL1 is a subtype belonging to the TE.CTL cluster, referring to a cell subtype that shares the characteristics of overall cytotoxic CD4+ T cells but exhibits relatively intermediate levels of cytotoxicity compared to TE.CTL2 (see Fig. 3c). Specifically, expression of cytotoxicity-related molecules such as granzyme B (GZMB), granzyme A (GZMA), NKG7, granulacin (GNLY), and perforin (PRF1) is observed in TE.CTL1, but the expression levels are lower or intermediate compared to TE.CTL2, and the expression of surface markers such as CX3CR1, KLRK1 (NKG2D), SLAMF7 (CD319), ITGB1 (CD29), and ADGRG1 (GPR56) also tends to be lower compared to TE.CTL.

[0029] TE.CTL2 is a subtype of TE.CTL, a CD4+ CTL cluster, which is more differentiated than TE.CTL1 and possesses the highest cytotoxicity score. In particular, TE.CTL2 is a cluster that is significantly increased in the bone marrow of multiple myeloma (MM) patients, and it increased to a statistically significant level only in MM patients compared to other disease stages such as healthy individuals (HD), MGUS, and SMM. This TE.CTL2 is characterized by high expression of the transcription factor TBX21 (T-bet) and significantly increased expression of the NKG2D (KLRK1) receptor in MM patients. Furthermore, potent cytotoxic gene markers such as granzyme B (GZMB), granzyme A (GZMA), NKG7, granulacin (GNLY), and perforin (PRF1), as well as natural killer (NK) cell-related markers, are abundantly expressed. In addition, unlike TE.CTL1, CX3CR1 and B3GAT1 (CD57) are distinctly expressed in TE.CTL2 (see Figure 3c). TE.CTL2 shows a distinctly increasing frequency of upstream TCR clones, suggesting that TE.CTL2 is a subtype closely involved in the progression and immunological evolution of multiple myeloma.

[0030] In addition, trajectory analysis confirmed that TE.CTL corresponds to the final stage of the linear differentiation pathway leading from Th1 → Th1.CTL → TE.CTL, and that clonal-specific concentration was particularly high with the progression of multiple myeloma (MM).

[0031] In the present invention, the term "CX3CR1hi" refers to the characteristics of a subtype of CD4+ CTL that highly expresses the CX3CR1 receptor, exhibiting more potent cytotoxic activity compared to other CD4+ CTL subtypes and showing a tendency for the clone to expand rapidly as the disease progresses. In the present invention, a cluster composed of cells that highly express CX3CR1 among TE.CTL clusters is referred to as TE.CTL2. Furthermore, in addition to CX3CR1, these cells express various cytotoxic markers such as KLRK1 (NKG2D), SLAMF7 (CD319), and ADGRG1GPR56. In particular, they play an important role in specifically recognizing and killing myeloma cells.

[0032] In the present invention, the term "Th1.CTL" refers to a subset of CD4+ T cells expressing granzyme K (GZMK), which can be further subdivided into the IFNG high-expression (IFNGhi) subtype and the Th1.cyto subtype. It is also a CD4+ T cell subtype that highly expresses Th1 signature genes (IFNG, CCL4, CCL5, TOX, etc.) and possesses cytotoxicity. Th1.CTL can function as an intermediate cell state corresponding to the pre-differentiation stage to TE.CTL.

[0033] In the present invention, the term "Th17.CTL" refers to a CD4+ T cell subtype that expresses Granzyme K (GZMK) and highly expresses the Th17 signature gene, and possesses the characteristic of also having cytotoxicity. Th17.CTL can be subdivided into CCR6 and Th17.cyto subtypes, which can contribute to different inflammatory responses or tissue-specific immune responses.

[0034] In this specification, the term "tumor antigen specificity" refers to the selective ability of T cells or antibodies to recognize and respond to antigens that are specifically expressed in tumor cells or significantly overexpressed compared to normal tissues, and this can be functionally confirmed by whether cytokine production or cytotoxic response is induced upon stimulation with a peptide containing the said antigen. This specificity can be functionally evaluated by stimulating T cells ex vivo using overlapping peptides (OLPs) or epitope peptides containing the said tumor-associated antigen, and then determining whether cytokine production, such as interferon gamma (IFN-γ) or tumor necrosis factor alpha (TNF-α), or cytotoxic response is induced.

[0035] For example, in the present invention, when CD4+ CTLs were stimulated using BCMA or NY-ESO-1 derived overlapping peptides, IFN-γ and TNF-α production was induced in some patients, which demonstrates that the T cells have tumor specificity for BCMA or NY-ESO-1 antigens.

[0036] The above tumor-associated antigens (TAAs) are not limited to but may include BCMA, NY-ESO-1, MAGE-A3, MAGE-A6, MART-1, CEA, PRAME, and WT1, and may be associated with HLA class II restricted epitope stimulation.

[0037] In the present invention, the term "cancer" refers to or denotes a physiological condition characterized by typically uncontrolled cell growth in mammals. In the present invention, the cancers subject to prevention, diagnosis, treatment, or prognosis prediction are specifically breast cancer, ovarian cancer, colorectal cancer, gastric cancer, liver cancer, pancreatic cancer, cervical cancer, thyroid cancer, parathyroid cancer, lung cancer, non-small cell lung cancer, prostate cancer, gallbladder cancer, biliary tract cancer, non-Hodgkin lymphoma, Hodgkin lymphoma, blood cancer, bladder cancer, kidney cancer, melanoma, colon cancer, bone cancer, skin cancer, head cancer, uterine cancer, rectal cancer, brain tumor, prostatic cancer, fallopian tube carcinoma, endometrial carcinoma, vaginal cancer, vulvar carcinoma, esophageal cancer, small intestine cancer, endocrine gland cancer, adrenal cancer, soft tissue sarcoma, urethral cancer, penile cancer, ureteral cancer, renal cell carcinoma, renopelvic carcinoma, central nervous system (CNS) tumor, primary CNS lymphoma, spinal cord tumor, brainstem glioma or pituitary adenoma, myeloma, multiple myeloma, blood cancer, and It may be hematopoietic stem cell carcinoma, and more specifically, it may be myeloma, multiple myeloma, blood cancer, and hematopoietic stem cell carcinoma.

[0038] In the present invention, "non-solid cancer" refers to cancer that does not occur in solid organ tissues but occurs mainly in the circulatory or hematopoietic system, such as the blood, bone marrow, or lymphatic system. Such cancer is distinguished from solid tumors in that it does not form a tissue mass and exists in the form of abnormal cell proliferation in the blood or bone marrow.

[0039] The above non-solid cancers may include blood cancers, multiple myeloma, leukemia, lymphoma, and malignant diseases of hematopoietic stem cell origin, but are not limited thereto.

[0040] In the present invention, the term "blood cancer" refers to a malignant tumor that develops in cells (white blood cells, red blood cells, platelets, etc.) or tissues (bone marrow, lymph nodes, etc.) that constitute or regulate blood. Leukemia, lymphoma, myeloma, and multiple myeloma are included, but are not limited thereto. These mainly occur in the bone marrow and affect various blood cells.

[0041] In the present invention, the term "myeloma" or "multiple myeloma (MM)" refers to a malignant tumor that occurs in the bone marrow and is characterized by the abnormal proliferation of plasma cells. This disease is a cancer of plasma cells that primarily produce blood cells in the bone marrow.

[0042] In this invention, the term "Smoldering Multiple Myeloma" refers to a precancerous blood and bone marrow condition that occurs when myeloma cell levels are low, signifying an asymptomatic early-stage blood cancer. There is a possibility of progression to multiple myeloma.

[0043] In the present invention, the term "Newly Diagnosed Multiple Myeloma (NDMM)" refers to a patient who has recently been diagnosed with multiple myeloma and has not yet received any treatment. For patients with newly diagnosed multiple myeloma, standard treatments such as induction therapy may be attempted, and if the patient is eligible, autologous stem cell transplantation (ASCT) may also be attempted.

[0044] In the present invention, the term "cancer expressing an NKG2D ligand" refers to a case where an NKG2D ligand is expressed in cancer cells or in a tumor-associated immune environment. Such ligands exist in forms such as, for example, MICA, MICB, ULBP1-6, and can induce the activation of immune cells (e.g., CD8+ T cells, NK cells, CD4+ CTLs, etc.) that express NKG2D receptors. Furthermore, NKG2D ligands (MICA, MICB, ULBP1-6, etc.) are known to be induced by stress responses, DNA damage, inflammation, etc., in various solid tumors and hematological cancers, and they have the characteristic of being rarely expressed in normal tissues but selectively highly expressed in tumor tissues. For example, expression of NKG2D ligands has been reported in various solid cancers such as ovarian cancer, cervical cancer, breast cancer, colorectal cancer, lung cancer, and pancreatic cancer, as well as in hematological cancers such as acute myeloid leukemia (AML) and non-Hodgkin lymphoma (Dhar, P., & Wu, JD (2018). NKG2D and its ligands in cancer. Current Opinion in Immunology, 51, 55-61.). Specifically, in the present invention, it acts as a pathological feature that serves as a target for NKG2D+ CD4+ CTL-based therapeutic strategies, and the NKG2D+ CX3CR1hi CD4+ T cells according to the present invention can be effectively applied not only to multiple myeloma but also to various cancers expressing NKG2D ligands.

[0045] In the present invention, the term "BCMA (B-cell maturation antigen)" refers to a B-cell maturation antigen and is a target antigen of multiple myeloma. BCMA is selectively induced during plasma cell differentiation and is rarely present in naive and memory B cells. It is used as a target for antibody therapies and CAR-T cell therapies used in the treatment of multiple myeloma.

[0046] In the present invention, the term "bone marrow (BM)" refers to a hematopoietic organ that produces blood cells such as red blood cells, white blood cells, and platelets. Bone marrow is commonly used to diagnose blood diseases or malignant tumors.

[0047] In the present invention, the term "Bone Marrow Mononuclear Cells (BMMC)" mainly includes lymphocytes, monocytes, and stem cells. BMMCs play an important role in clinical research and various therapeutic approaches, and the isolation of BMMCs is performed by removing other cell types, such as red blood cells, from bone marrow samples.

[0048] In the present invention, the term "peripheral blood (PB)" refers to blood circulating in the body. Peripheral blood includes blood cells, plasma, and other components within the blood and is collected for various tests and analyses in medical and research fields.

[0049] In the present invention, the term "hematopoietic stem cell cancer" refers to cancer originating from hematopoietic stem cells, and primarily refers to a condition in which progenitor cells that should differentiate into normal blood cells within the bone marrow undergo malignant mutation and proliferate abnormally.

[0050] In the present invention, the term "NKG2D ligand" refers to a protein capable of inducing or regulating the activity of an immune cell by binding to NKG2D (Natural Killer Group 2, member D), a receptor expressed on the surface of immune cells, and is generally expressed when the cell is in a state such as stress, DNA damage, infection, or tumorigenesis. Although not limited thereto, the NKG2D ligand may include MICA (MHC class I-related chain A), MICB (MHC class I-related chain B), ULBP1-6 (UL16-binding proteins), and ULBP5 (UL16 binding protein 5). These are expressed on the surface of the cell membrane and induce the activation of immune cells (CD8+ T cells, NK cells, γδT cells, CD4+ CTLs, etc.) that possess the NKG2D receptor, thereby inducing an immune response. Although NKG2D ligands are rarely expressed in normal tissues, they tend to be selectively overexpressed in pathological environments including tumor tissues. Expression of NKG2D ligands has been reported in various solid tumors (e.g., breast cancer, colorectal cancer, lung cancer, etc.) and hematological cancers (e.g., multiple myeloma, AML, etc.), and they are known to be involved in immune evasion mechanisms in the tumor microenvironment.

[0051] In the present invention, the term "cytotoxicity" refers to the function of T cells that primarily have the ability to kill cells, and includes the process of targeting infected cells or cancer cells to eliminate them.

[0052] In this invention, the term "cytokine" refers to a small molecule protein that serves to transmit information between cells during an immune response. These proteins play an important role in activating or inhibiting various parts of the immune system.

[0053] The above cytokines may include, but are not limited to, IL-2, IL-6, IL-10, and IL-15.

[0054] In the present invention, the term "IL-2 (Interleukin-2)" refers to a cytokine signaling molecule that plays an important role in the immune system and triggers the body's response to microbial infection by regulating the activity of white blood cells responsible for immunity. It promotes the proliferation and survival of T cells, activates NK cells, suppresses immunity by activating regulatory T cells (TreG), and activates immunity by activating CD8+ T cells and NK cells. In the present invention, it was confirmed that in CD4+ CTLs with high NKG2D expression, NKG2D expression increases due to IL-2.

[0055] In the present invention, the term "IL-15 (Interlukin-15)" refers to a protein essential to the human immune system and is a type of inflammatory cytokine. IL-15 plays a role in regulating inflammatory and protective responses against viral infections or parasites. It is structurally similar to IL-2 and promotes the proliferation of activated T cells, NK cells, and B cells. In the present invention, it was confirmed that NKG2D expression increased by IL-15 in both CD4+ CTLs with high NKG2D expression and CD4+ CTLs with low NKG2D expression.

[0056] In the present invention, the term "antibody" refers to a substance that specifically binds to an antigen and causes an antigen-antibody reaction. For the purposes of the present invention, an antibody means an antibody that specifically binds to a regulatory T cell-specific protein or its extracellular domain. The antibodies of the present invention include polyclonal antibodies, monoclonal antibodies, and recombinant antibodies. The antibodies can be easily manufactured using techniques widely known in the art. For example, polyclonal antibodies can be produced by a method widely known in the art comprising the process of injecting an antigen of the biomarker protein into an animal and collecting blood from the animal to obtain serum containing the antibody. Such polyclonal antibodies can be produced from any animal, such as goats, rabbits, sheep, monkeys, horses, pigs, cattle, and dogs. In addition, monoclonal antibodies may be prepared using the hybridoma method (see Kohler and Milstein (1976) European Journal of Immunology 6:511-519), which is widely known in the art, or phage antibody library technology (see Clackson et al, Nature, 352:624-628, 1991; Marks et al, J. Mol. Biol., 222:58, 1-597, 1991). Antibodies prepared by the above methods may be separated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, and affinity chromatography. Furthermore, the antibodies of the present invention comprise not only a complete form having two full-length light chains and two full-length heavy chains, but also functional fragments of the antibody molecule. A functional fragment of an antibody molecule refers to a fragment that possesses at least an antigen-binding function, and includes Fab, F(ab'), F(ab')2, and Fv.

[0057] In this invention, the term "Daratumumab" refers to a human monoclonal antibody targeting the CD38 antigen, which can be used for the treatment of multiple myeloma. CD38 is a molecule expressed not only in plasma cells but also in some activated immune cells (such as CD4+ and CD8+ T cells). Daratumumab can eliminate tumor cells and specific immune cell subtypes by binding to CD38hi cells and inducing antibody-dependent cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent phagocytosis (ADCP).

[0058] In the present invention, "antibody that upregulates NKG2D" refers to an antibody that directly increases the expression or functional activity of the NKG2D receptor, or indirectly activates the NKG2D pathway by blocking the pathway that inhibits NKG2D activity. Such an antibody can play a role in enhancing the cytotoxic function (e.g., killing tumor cells) of NKG2D immune cells.

[0059] In the present invention, "cytotoxicity-activated CD4+ CTL" refers to a CD4+ CTL in which the expression of cytotoxic molecules such as perforin and granzyme B is increased within the cell by treatment with antibodies and / or co-stimulatory antibodies or combined stimulation by cytokines, and simultaneously the production of cytokines such as IFN-γ and TNF-α and the killing ability against tumor cells or target cells are enhanced.

[0060] In the present invention, "antibody activating cytotoxicity" refers to an antibody used for the purpose of increasing the expression of cytotoxic molecules or cytokine production of CD4+ CTLs, or the ability to directly kill cells against target cells, and specifically, may include an agonistic antibody comprising one or more of anti-CD3, anti-CD28, anti-4-1BB, anti-OX40, and anti-CD27 antibodies.

[0061] In the present invention, "anti-CD3 antibody" refers to an anti-CD3 monoclonal antibody that binds to CD3 on the surface of T cells. T cells can be activated by stimulating CD3 through the anti-CD3 antibody, and in particular, CD3 stimulation can significantly upregulate NKG2D in CD4+ CTLs (see Figures 6A and 6B).

[0062] The above anti-CD3 antibodies may include, but are not limited to, muromonab-CD3, otelixizumab, teplizumab, and visilizumab.

[0063] In the present invention, "anti-CD28 antibody" refers to an antibody that induces auxiliary stimulating signals necessary for T cell activation, proliferation, and survival by specifically recognizing and binding to the CD28 molecule, which is a co-stimulatory receptor of T cells.

[0064] In the present invention, "anti-4-1BB antibody" (or "anti-CD137 antibody") refers to an antibody that targets 4-1BB (CD137), a co-stimulatory receptor expressed on the surface of T cells and NK cells, and enhances the survival, proliferation, and cytotoxic functions of these cells.

[0065] In the present invention, "anti-OX40 antibody" (or "anti-CD134 antibody") refers to an antibody that targets OX40 (CD134), a co-stimulatory receptor expressed on activated T cells, and promotes the survival, memory formation, and cytokine secretion of T cells.

[0066] In the present invention, "anti-CD27 antibody" refers to an antibody that specifically binds to a CD27 molecule belonging to the TNF receptor family and contributes to the co-stimulation of T cells and the formation of memory T cells.

[0067] In the present invention, "agonist antibody" refers to an antibody that induces biological action occurring in a cell by transmitting a signal within the cell through binding to a specific molecule on the cell surface or a specific molecule within the cell, and is an agonist antibody that plays a role in promoting or activating the action induced by an antigen-antibody reaction.

[0068] In the present invention, "antagonist antibody" refers to an antibody that inhibits the action of a receptor, and plays a role in inhibiting the activation of the receptor by binding to the ligand binding site of the receptor.

[0069] In the present invention, the term "measuring agent" refers to an experimental reagent or tool used to detect, analyze, and confirm the presence, activity, or function of a substance or component to be measured, and various substances known to those skilled in the art may be included therein. Specifically, the CD4+ CTLs to be measured in the present invention include subtypes (NKG2D+ CX3CR1hi CD4+ CTLs) that highly express NKG2D and CX3CR1, and the agents for measuring their ratio or activity may include the following.

[0070] Antibodies for detecting cell surface markers or cytokines may include, but are not limited to, CD4 antibodies for CD4+ T cell identification, as well as antibodies against cytotoxic markers such as GrB, GrK, CD57, NKG2D(KLRK1), CX3CR1, GPR56, CD29, SLAMF7, T-BET, EOMES, CD107a, Perforin, CD28, KLRG1, PD-1, TIGIT, etc. These antibodies may be used alone or in combination to elucidate the cellular phenotype and functional characteristics of CD4 CTLs. Fluorescent labeling agents for flow cytometry may include, but are not limited to, fluorescent dyes conjugated to antibodies (FITC, PE, BV421, etc.), 7-AAD for cell viability analysis, TO-PRO-3 for detecting apoptotic cells, PKH-26 for target cell labeling, etc. Preparations for cytotoxicity evaluation and functional analysis may include, but are not limited to, samples used in cytotoxicity experiments using myeloma cell lines (U266B1, RPMI8226) or autologous myeloma cells, anti-CD3 antibodies that induce CD4+ T cell activation and promote NKG2D expression, cytokines such as IL-12, IL-2, and IL-15, and NKG2D blocking antibodies (including IgG isotypes) to verify NKG2D-dependent cytotoxicity. In addition, preparations for molecular biological analysis may include, but are not limited to, high-dimensional analysis technologies including single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (scTCR-seq), through which gene expression levels and TCR diversity of GZMB, KLRK1 (NKG2D), CX3CR1, etc., can be analyzed.

[0071] In the present invention, the term "control group" refers to a group used as a comparison standard to evaluate the clinical significance or disease association of a specific biomarker, and specifically, it may be a group including healthy donors (HD) and patients with MGUS (monoclonal gammopathy) and SMM (latent multiple myeloma) who are in the absence of disease or in the early pre-disease stage, or a group including patients with non-Hodgkin lymphoma without bone marrow involvement among blood cancer patients who are not multiple myeloma (MM) based on the same age group and gender.

[0072] This control group is defined in advance to ensure the reliability of statistical analysis and clinical judgment, and may include, for example, healthy donors (HD), a group of patients with MGUS (monoclonal gammopathy) or SMM (latent multiple myeloma) corresponding to the disease's prodromal stage, or patients with non-Hodgkin lymphoma without bone marrow involvement among other blood cancer patient groups that have the same age and gender conditions but are not multiple myeloma (MM). The predefined control group functions as a representative group of normal or non-progressive states in the diagnostic algorithm or prognostic judgment criteria of the present invention, and is utilized as a reference point to determine the presence of abnormalities in biomarkers or prognostic significance through relative comparison with the patient group under analysis.

[0073] In the present invention, the term "reference value" refers to the median of the ratio of NKG2D+ CD4+ CTLs within a specific group of cancer patients (e.g., a group of multiple myeloma patients) or a predefined cut-off criterion based on clinical judgment when it is statistically significant. For example, if the median ratio of NKG2D+ CD4+ CTLs analyzed after CD3 stimulation of bone marrow-derived mononuclear cells (BMMCs) of newly diagnosed multiple myeloma (NDMM) patients at the time of diagnosis is confirmed to be 2.9%, this can be used as a criterion to classify patients into a 'High group' and a 'Low group' based on whether the ratio exceeds 2.9%, and to evaluate the correlation with progression-free survival.

[0074] In the present invention, the terms "progression-free survival" or "progression-free survival (PFS)" refer to the period during which a patient suffering from a disease, such as cancer, survives without the disease worsening during or after treatment. Disease progression refers to a state of deterioration from one stage to the next, and includes, for example, cases where one or more of the following clinical symptoms (CRAB symptoms) are observed: a significant increase in M-protein levels in serum or urine, an increase in the proportion of malignant plasma cells in the bone marrow, the appearance of new bone lesions or the worsening of existing lesions, hypercalcemia, renal failure, anemia, or bone lesions. The criteria for disease progression in multiple myeloma can be referenced from the definition of the IMWG (International Myeloma Working Group). Therefore, PFS refers to the period from the start of treatment until disease progression or death occurs; it is the period during which the state of disease progression being suppressed due to the administration of a drug or pharmaceutical composition is maintained, and the period during which the patient maintains a stable state of disease without death is used as a measurement indicator. In the present invention, a statistically significant correlation was observed between the frequency of NKG2D+ CD4+ cytotoxic T cells (CTLs) and the progression-free survival (PFS) of patients. Specifically, the group in which the proportion of NKG2D+ CD4+ CTLs analyzed after applying anti-CD3 stimulation to bone marrow-derived mononuclear cells extracted from multiple myeloma patients (BMMCs) at the time of diagnosis was higher than the median of the entire patient group (e.g., 2.9%) showed a longer progression-free survival (PFS) than the group in which it was lower (low group). This suggests that NKG2D+ CD4+ CTLs are a cell group that contributes to the immune regulation and tumor control of the disease, and supports the potential use of the immune cell-based composition of the present invention as a prognostic prediction marker.

[0075] In this invention, the term "high proportion" may include the meaning of "high frequency" and has the following two meanings depending on the context. In relation to the comparison of disease progression stages, it means that a specific CD4+ CTL subtype is present at a statistically significantly higher frequency in the bone marrow of multiple myeloma (MM) patients compared to the control group. In other words, it signifies a pattern in which the proportion of the corresponding cell subtype in the bone marrow gradually increases as the disease progresses.

[0076] In relation to the progression-free survival (PFS) analysis, within the same MM patient cohort, the high group of patients with a higher proportion of a specific cell subtype (NKG2D+ CD4+ CTL) than the median of the entire patient group (e.g., 2.9%, see Fig. 6) has a statistically significantly higher progression-free survival (PFS) rate than the low group of patients.

[0077] In the present invention, the term "prevention" means suppressing the occurrence of a disease or illness in a subject who has not been diagnosed with having such a disease or illness but is likely to develop such a disease or illness. Any act of blocking disease symptoms or suppressing or delaying disease symptoms using the pharmaceutical composition of the present invention may be included without limitation.

[0078] In the present invention, the terms "treatment" and "improvement" may include, without limitation, any act of improving or benefiting from disease symptoms by treating the pharmaceutical composition of the present invention, and mean (a) inhibition of the progression of the disease, illness, or symptoms; (b) alleviation of the disease, illness, or symptoms; or (c) elimination of the disease, illness, or symptoms.

[0079] Specifically, in the present invention, the terms "treatment" and "improvement" refer to inhibiting or delaying the progression of a disease in cancer patients, including those with multiple myeloma (MM), and improving or alleviating pathological conditions caused by the disease, and may include any medical act that extends progression-free survival (PFS). Furthermore, in the present invention, "treatment" includes inducing or increasing cytotoxic activity against cancer cells (e.g., myeloma cells expressing MICA) using a composition containing NKG2D+ CD4+ CTLs as active ingredients. Experimentally, potent cytotoxic activity was induced in CD4+ CTLs with significantly increased NKG2D expression through IL-2 and / or IL-15 stimulation and anti-CD3 co-stimulation, and NKG2D-dependent apoptosis induction was confirmed, particularly in NKG2D ligand-expressing cells.

[0080] The term "method of treatment" as used in the present invention refers to any medical act that improves or benefits a target disease or symptom by administering or applying the pharmaceutical composition or cell therapy agent of the present invention to a patient. Specifically, it may refer to the inhibition or delay of disease progression, the alleviation or relief of symptoms, or the elimination or fundamental treatment of the disease. In particular, the method of treatment of the present invention targets cancer patients, including those with multiple myeloma (MM), and includes any medical act that extends progression-free survival (PFS). Furthermore, the method of treatment of the present invention includes inducing or increasing cytotoxic activity against cancer cells, such as myeloma cells expressing MICA, by using a composition containing NKG2D+ CD4+ CTL as an active ingredient. Experimentally, potent cytotoxic activity was induced in CD4+ CTLs with significantly increased NKG2D expression through IL-2 and / or IL-15 stimulation and anti-CD3 co-stimulation, and NKG2D-dependent apoptosis was confirmed, particularly in NKG2D ligand-expressing cells.

[0081] In this invention, the term "diagnosis" encompasses not only the act of identifying or determining the presence of a disease, but also a more comprehensive meaning that includes the stage of disease progression, prognosis, and prediction of treatment response. For example, by measuring the ratio of NKG2D+ CD4+ CTLs in patients with multiple myeloma, it is possible to evaluate not only the presence of the disease but also survival prognoses, such as the degree of disease progression or the potential for future progression-free survival (PFS). Furthermore, these indicators can be utilized to predict the course of the disease after treatment by comprehensively considering the patient's physiological state and immunological response. Therefore, "diagnosis" in this invention is understood as an integrated concept encompassing prognosis and prediction, serving as a process that provides useful information for establishing future treatment strategies and making personalized medical decisions for patients, in addition to identifying the disease.

[0082] In the present invention, the term "prognosis" refers to a medical judgment regarding the future clinical course of a specific disease when a patient is suffering from such a disease, particularly a chronic or progressive disease such as cancer. Specifically, it includes the patient's long-term health outcomes, such as the likelihood of disease progression, metastasis, risk of recurrence, survival time, and duration of treatment response, and is determined at the time of diagnosis or during the early stages of treatment. For example, in the present invention, survival prognosis can be evaluated by measuring the frequency of NKG2D+ CD4+ CTLs in the bone marrow of multiple myeloma patients and analyzing the correlation with progression-free survival (PFS). The frequency of these immune cells reflects the immune status that contributes to disease suppression and can function as a significant biomarker for determining the prognosis.

[0083] In this invention, the term "prediction" refers to a preliminary determination of how a specific patient will respond to a specific therapeutic agent or treatment strategy in the future. This is a process of individually estimating the course of the disease, treatment responsiveness, likelihood of side effects, and survival rate based on objective data such as the patient's genetic characteristics, immunological status, and biomarker levels. More specifically, prognosis prediction can be interpreted as any act of predicting the course of the disease after treatment by comprehensively considering the patient's physiological or environmental state, as the course of the disease after treatment may vary depending on the patient's physiological or environmental condition.

[0084] In the present invention, the term "cytotoxic activation" refers to a process in which immune cells, such as T cells or natural killer cells, are induced to a state capable of recognizing and killing target cells, and encompasses molecular, phenotypic, and functional changes necessary for CD4+ CTLs to perform the function of recognizing and eliminating cancer cells. Specifically, it may mean a significant increase in the expression of NKG2D, etc., in CD4+ CTLs, and cytotoxically activated CD4+ CTLs exhibit increased expression of cytotoxic effector molecules such as GZMB (Granzyme B), GZMA (Granzyme A), PRF1 (Perforin), NKG7, and GNLY (Granulysin); in particular, subclusters such as TE.CTL2 exhibit more highly differentiated cytotoxic characteristics due to the high expression of these molecules. This cytotoxic activation can be induced by TCR stimulation (e.g., anti-CD3 antibodies), and cytokines such as IL-2 and IL-15 act as important regulators that enhance cytotoxic function by inducing or increasing NKG2D expression.

[0085] In the present invention, the term "measuring agent" refers to a composition for analyzing the presence, expression level, or frequency of NKG2D+ CD4+ cytotoxic T cells (CTLs), and may include antibodies that specifically bind to surface or intracellular markers of cells to be analyzed, fluorescent labels, analysis probes, cell separation reagents, or analysis kit components containing reference value information. For example, the "measuring agent" of the present invention may include fluorescently labeled antibodies that specifically bind to NKG2D and CD4, a composition for separating mononuclear cells (PBMC or BM-MNC) from bone marrow or peripheral blood, cell fixation and permeation reagents, detection probes for analysis instruments (FACS), etc.

[0086] In the present invention, the term "tumor" refers to all newly formed cell growths and proliferations, regardless of whether they are malignant or benign, as well as all precancerous states and cancerous cells and tissues.

[0087] In the present invention, the term "pharmaceutical composition" is not limited to these but may be formulated and used in the form of oral formulations such as powders, granules, capsules, tablets, and aqueous suspensions, as well as topical preparations, suppositories, and sterile injectable solutions, according to conventional methods. The pharmaceutical composition of the present invention may include a pharmaceutically acceptable carrier. For oral administration, the pharmaceutically acceptable carrier may include binders, lubricants, disintegrants, excipients, solubilizers, dispersants, stabilizers, suspending agents, colorants, flavorings, etc. For injectable preparations, it may include buffers, preservatives, analgesics, solubilizers, isotonic agents, stabilizers, etc., in combination; and for topical administration, a base, excipients, lubricants, preservatives, etc. may be used. The formulations of the pharmaceutical composition of the present invention may be prepared in various ways by mixing with the pharmaceutically acceptable carriers described above. For example, for oral administration, it can be manufactured in the form of tablets, troches, capsules, elixirs, suspensions, syrups, wafers, etc., and for injectables, it can be manufactured in the form of unit dosing ampoules or multiple dosing ampoules. In addition, it can be formulated as a solution, suspension, tablet, capsule, sustained-release formulation, etc. Meanwhile, examples of carriers, excipients, and diluents suitable for formulation include lactose, dextrose, sucrose, sorbitol, mannitol, xylitol, erythritol, maltitol, starch, acacia gum, alginate, gelatin, calcium phosphate, calcium silicate, cellulose, methyl cellulose, microcrystalline cellulose, polyvinylpyrrolidone, water, methylhydroxybenzoate, propylhydroxybenzoate, talc, magnesium stearate, or mineral oil. In addition, it may additionally include fillers, anticoagulants, lubricants, wetting agents, fragrances, emulsifiers, preservatives, etc.

[0088] In the present invention, "routes of administration" for a pharmaceutical composition include, but are not limited to, oral, intravenous, intramuscular, intra-arterial, intramedullary, intradural, intracardiac, transdermal, subcutaneous, intraperitoneal, intranasal, intestinal, topical, sublingual, or rectal. Oral or parenteral administration is preferred.

[0089] In the present invention, the term "parenteral" includes subcutaneous, intradermal, intravenous, intramuscular, intra-articular, intrasynovial, intrasternal, intradural, intralesional, and intracranial injection or infusion techniques. The pharmaceutical composition of the present invention may also be administered in the form of a suppository for rectal administration.

[0090] In the present invention, the "use and dosage" of the composition may vary depending on various factors including the activity of the specific compound used, age, body weight, general health, gender, diet, time of administration, route of administration, elimination rate, drug combination, and the severity of the specific disease to be prevented or treated. The dosage of the pharmaceutical composition may be appropriately selected by a person skilled in the art, depending on the patient's condition, body weight, degree of disease, form of medication, route of administration, and duration, and may be administered at a dose of 0.0001 to 50 mg / kg or 0.001 to 50 mg / kg per day. Administration may be administered once a day or divided into several doses. The above dosage does not limit the scope of the present invention in any way. The pharmaceutical composition according to the present invention may be formulated as a pill, coated tablet, capsule, liquid, gel, syrup, slurry, or suspension.

[0091] In the present invention, the term "diagnostic device" refers to equipment capable of diagnosing a disease or predicting its prognosis in vitro based on human-derived biological samples such as blood, saliva, and urine. The term "diagnosis" herein is not limited to the simple determination of the presence or absence of a disease, but refers to a comprehensive concept that includes the evaluation of the degree of disease progression, prognosis, and responsiveness to treatment.

[0092] The above diagnostic device may, for example, include (a) a measurement unit that detects the presence and characteristics of cells or molecules to be analyzed from a biological sample, (b) a calculation unit that interprets the measurement value and calculates the correlation with the disease state or prognosis, and (c) an output unit that provides the analysis results to a user, and these components may be implemented in the form of physical equipment, software modules, or a combination thereof. The cancer prognosis diagnostic device according to the present invention includes equipment that can be utilized for various clinical decision-making, such as not only predicting the cancer prognosis of a subject but also determining whether to apply chemotherapy, predicting responsiveness to anticancer drugs, and further evaluating the prognosis after treatment. The information analyzed by the diagnostic device may include the phenotype, activity, or expression level of specific markers of cells, and based on such information, clinical indicators such as progression-free survival (PFS) of cancer can be estimated.

[0093] The term "measuring unit" included in the diagnostic device of the present invention refers to a component for quantitatively measuring the ratio and / or activity level of CD4+ CTLs or cell subtypes expressing NKG2D and CX3CR1, i.e., NKG2D+ CX3CR1hi CD4+ CTLs, in a CD4+ T cell population within a biological sample (e.g., peripheral blood, bone marrow, etc.) obtained from a subject (e.g., a patient). The measuring unit of the diagnostic device of the present invention may include the "measuring agent" described in the specification, and may perform multiple quantitative analysis based on a flow cytometer by labeling markers such as CD4, NKG2D (KLRK1), CX3CR1, GrB, CD57, CD107a, Perforin, etc. with fluorescent antibodies (FITC, PE, BV421, etc.), and may include a viability / death determination dye such as 7-AAD, TO-PRO-3. In addition, it may additionally include a functional-based evaluation module that evaluates cytotoxicity function by measuring the expression of CD107a, Perforin, IFN-γ, and TNF-α through stimulation with anti-CD3 antibodies and IL-2, IL-15, etc., and a scRNA-seq, RT-PCR, and Western blot-based molecular biological analysis unit that analyzes gene or protein expression such as GZMB, CX3CR1, and KLRK1(NKG2D).

[0094] The term "computation unit" included in the diagnostic device of the present invention refers to a component that interprets the immune cell characteristics of a subject, CD4+ CTLs, particularly the ratio or activity level of NKG2D+ CX3CR1hi CD4+ CTLs, based on analysis data obtained from the measurement unit, and determines the correlation with the prognosis of cancer by comparing this with a predefined control group or reference value. Specifically, the computation unit may determine that there is a high probability of prolonged progression-free survival (PFS) or conclude that the prognosis is favorable when the ratio of NKG2D+ CD4+ CTLs is above a specific threshold. Furthermore, it is designed to support clinical judgments, such as predicting responsiveness to chemotherapy, determining treatment strategies, or classifying risk groups, by analyzing changes in immune cells before and after anticancer treatment. The computation unit of the present invention may be implemented as a hardware-based processing device (e.g., central processing unit, memory, etc.) or a software algorithm that executes it (e.g., comparative analysis algorithm, machine learning model, etc.), and may additionally include functions for updating user-defined reference values ​​or linking with an external database.

[0095] The term "output unit" included in the diagnostic device of the present invention refers to a component that performs the function of delivering, storing, or transmitting information related to the cancer prognosis of a subject (e.g., a patient) to a user based on the analysis results derived by the computation unit. Specifically, the output unit includes a function that intuitively conveys to medical staff, researchers, or system users whether the prognosis of the subject patient is favorable or whether treatment responsiveness is predicted, based on the correlation analysis results between the ratio or activity level of NKG2D+ CX3CR1hi CD4+ CTL calculated by the computation unit and the progression-free survival (PFS). The output means may be implemented as a display device (e.g., monitor, touchscreen, etc.), a printer, a report generation module, a computerized record linkage system via a network, etc., and, if necessary, the analysis results may be automatically transmitted to an electronic health record (EHR) system or linked with a clinical decision support system (CDSS) to be utilized for establishing a treatment plan. Additionally, the output may be provided in a manner that includes a warning notification or a message recommending additional examination when immune cell activity falls below a certain standard or a high-risk prognosis is determined.

[0096] In one embodiment of the present invention, a composition for predicting cancer prognosis is provided, comprising as an active ingredient a preparation for measuring CD4+ CTLs in which the NKG2D protein biomarker is upregulated.

[0097] In the above specific example, a composition for predicting cancer prognosis is provided in which the CD4+ CTL upregulated by the NKG2D protein biomarker is CX3CR1hi, the composition for predicting cancer prognosis is provided in which the cancer is a non-solid tumor, the composition for predicting cancer prognosis is provided in which the non-solid tumor is any one selected from the group consisting of myeloma, multiple myeloma, hematological cancer, and hematopoietic stem cell carcinoma, and the composition for predicting cancer prognosis is provided in which the cancer has cancer cells expressing an NKG2D ligand.

[0098] In this specification, "CD4+ CTL with upregulated NKG2D protein biomarker" may be used interchangeably with "CD4+ CTL with upregulated NKG2D".

[0099] In one embodiment of the present invention, a method for providing information for predicting cancer prognosis is provided, comprising the step of measuring the ratio of NKG2D+ CD4+ CTLs to provide information regarding the likelihood of continued progression-free survival (PFS).

[0100] In the above embodiment, a method for providing information for predicting cancer prognosis is provided, further comprising the step of determining that progression-free survival (PFS) is more likely to continue when the ratio of NKG2D+ CD4+ CTLs is higher than a predefined control group or reference value, and further comprising the step of providing information that the prognosis is better in cancer patients expressing an NKG2D ligand when the ratio of NKG2D+ CD4+ CTLs is higher than a predefined control group or reference value.

[0101] In one embodiment of the present invention, a pharmaceutical composition for the prevention or treatment of cancer is provided, comprising a CD4+ CTL in which NKG2D is upregulated as an active ingredient, wherein the upregulation of NKG2D is by a cytokine, and the cytokine is one or more selected from the group consisting of IL-2, IL-6, IL-10, and IL-15.

[0102] In the above specific example, the pharmaceutical composition for preventing or treating cancer is provided, wherein the CD4+ CTL in which NKG2D is upregulated is CX3CR1hi, the pharmaceutical composition for preventing or treating cancer is provided, wherein the upregulation of NKG2D is by one or more antibodies selected from the group consisting of anti-CD3, anti-CD28, anti-4-1BB, anti-OX40, and anti-CD27, the pharmaceutical composition for preventing or treating cancer is provided, wherein the cytokine is by IL-2 and IL-15, the pharmaceutical composition for preventing or treating cancer is provided, wherein the cancer is a non-solid tumor, the pharmaceutical composition for preventing or treating cancer is provided, wherein the non-solid tumor is any one selected from the group consisting of myeloma, multiple myeloma, hematological cancer, and hematopoietic stem cell carcinoma, and wherein the cancer has cancer cells expressing an NKG2D ligand.

[0103] In one embodiment of the present invention, a diagnostic device for predicting cancer prognosis comprises: (a) a measuring unit for measuring the ratio of NKG2D+ CD4+ CTLs in a biological sample obtained from a target individual; (b) a calculation unit that determines that there is a higher probability of progression-free survival (PFS) continuing when the ratio of NKG2D+ CD4+ CTLs measured by the measuring unit is higher than a predefined control group or reference value; and (c) an output unit that outputs prognostic information of a cancer patient based on the result of the calculation unit's determination.

[0104] In the above embodiment, the diagnostic device is characterized in that the computing unit additionally determines information that the prognosis is better when the ratio of the NKG2D+ CD4+ CTL is higher than a predefined control group or reference value, and the cancer has cancer cells expressing an NKG2D ligand.

[0105] In one embodiment of the present invention, the use of a formulation for measuring CD4+ CTLs upregulated by the NKG2D protein biomarker is provided for cancer prognosis prediction.

[0106] In the above specific example, the use of a preparation for measuring CD4+ CTLs is provided in which the CD4+ CTL upregulated by the NKG2D protein biomarker is CX3CR1hi, the use of a preparation for measuring CD4+ CTLs is provided in which the cancer is a non-solid tumor, and the use of a preparation for measuring CD4+ CTLs is provided in which the non-solid tumor is any one selected from the group consisting of myeloma, multiple myeloma, hematological cancer, and hematopoietic stem cell carcinoma.

[0107] In one embodiment of the present invention, a CD4+ CTL with an upregulated NKG2D protein biomarker is provided for use in cancer prevention or treatment.

[0108] In the above specific example, the CD4+ CTL in which the NKG2D protein biomarker is upregulated is CX3CR1hi, the cancer prevention or treatment use is provided, the upregulation of NKG2D is by a cytokine, and the cytokine is one or more selected from the group consisting of IL-2, IL-6, IL-10 and IL-15, the cancer prevention or treatment use is provided, the cancer has cancer cells expressing an NKG2D ligand.

[0109] In one embodiment of the present invention, a method for preventing or treating cancer is provided, comprising the step of administering an NKG2D upregulated CD4+ CTL as an active ingredient.

[0110] In the above specific example, the method for preventing or treating cancer is provided in which the CD4+ CTL in which the NKG2D is upregulated is CX3CR1hi, the method for preventing or treating cancer is provided in which the upregulation of the NKG2D is by one or more antibodies selected from the group consisting of anti-CD3, anti-CD28, anti-4-1BB, anti-OX40, and anti-CD27, the method for preventing or treating cancer is provided in which the cancer is a non-solid tumor, and the non-solid tumor is any one selected from the group consisting of myeloma, multiple myeloma, hematological cancer, and hematopoietic stem cell carcinoma.

[0111] The CD4+ CTL of the present invention performs a cytotoxic function that directly attacks and kills myeloma cells, thereby contributing to increasing the survival rate of patients by extending the progression-free survival period, particularly in patients with myeloma who are ineligible for transplantation.

[0112] This invention was completed by discovering a correlation between the ratio of NKG2D+ CD4+ CTLs and the survival rate of multiple myeloma patients, and NKG2D+ CD4+ CTLs can be used as a biomarker for predicting the prognosis of multiple myeloma patients. Through this, personalized treatment strategies can be established by analyzing the individual patient's CD4+ CTL status.

[0113] Furthermore, the effects of the present invention are not limited to the effects described above, and should be understood to include all effects that can be inferred from the configuration of the invention described in the detailed description or claims of the present invention.

[0114] Figure 1A illustrates an overview of the study design. The researchers obtained bone marrow aspirates at diagnosis from healthy donors (HD, n=10), patients with monoclonal gammopathy (MGUS, n=10), asymptomatic multiple myeloma (SMM, n=11), and multiple myeloma (MM, n=19). After isolating the mononuclear cells, CD4+ T cells were sorted, GEMs were generated, and barcodes were assigned. Subsequently, a library was constructed and sequencing was performed to obtain expression profiles and T cell receptor (TCR) repertoires. Figure 1B visualizes a total of 160,956 CD4+ T cells color-coded according to cluster identity using UMAP. The included clusters are naive, early activation (early.act), central memory (CM), follicular helper T cells (Tfh), Th2, Th17, Th17.CTL, Th1, Th1.CTL, terminal differentiation CTL (TE.CTL), active proliferation (act.proli), IFN-stimulated gene-high expression cells (ISGshi), resting regulatory T cells (rTreg), and active regulatory T cells (aTreg). Figure 1C shows the relative expression levels by cluster by projecting the expression of key marker genes onto UMAP. Figure 1D is a dot graph showing the average expression and expression ratio of marker genes in each CD4+ T cell cluster. The size of the dot indicates the proportion of cells expressing the corresponding gene, and the color intensity indicates the average expression level. Figure 1E presents a heatmap showing the expression of 14 carefully selected gene signatures in CD4+ T cell clusters. It was generated based on module scores scaled in Seurat. Figure 1F is a pseudotime analysis of all BM CD4+ T cells, in which cells are color-coded according to their pseudotime values. Figure 1G is a box plot showing the pseudotime values ​​of each CD4+ T cell cluster.Figure 1H presents the UMAP projections of CD4+ T cells obtained from HD and each patient group (MGUS, SMM, MM), showing the distribution and abundance of various clusters. Figure 1I is a stacked bar graph showing the proportion of CD4+ T cell clusters in each patient group. Figure 1J presents the frequency of TE.CTL clusters among the total CD4+ T cells by patient group. Each point represents an individual patient, and the bar height indicates the interquartile range (IQR) and distribution range. P-values ​​were calculated using the Mann-Whitney U test relative to HD. (CM: central memory; rTreg: resting Treg; Tfh: T-follicular helper).

[0115] Figure 2A is a UMAP visualization of 101,286 CD4+ T cells obtained from bone marrow (BM). The top 10 extended clones are distinguished by color, and clonal T cells were further classified into n=1–3 and n>3 based on cell count. Figure 2B is a UMAP projection showing the distribution of top clones by myeloma progression stage. Figure 2C is a stacked bar graph showing the proportion of top clones in each individual's TCR repertoire space. Figure 2D is a box plot showing the proportion of n>1 clones and the top 10 clones among all TCR clones. Figure 2E is a UMAP projection of CD4+ T cells with n>1 clones and a stacked bar graph showing the proportion of CD4+ T cell clusters within these clones. Figure 2F is a box plot showing the frequency of TE.CTL clusters in n>1 clones at different disease stages. Figure 2G is a box plot showing the proportion of the top 10 clones among TE.CTL cells at different disease stages and the inverse Simpson index of total TCR repertoire diversity. Figure 2H is a heatmap showing the ratio of clonal overlap between CD4+ T cell clusters at different stages of multiple myeloma progression. Figure 2I presents the UMAP projection of clusters with overlapping TCR clones (Th1, Th17.CTL, Th1.CTL, TE.CTL, act.proli) and differentiation trajectories expressed in pseudotime values. (CM: central memory; rTreg: resting Treg; Tfh: T-follicular helper)

[0116] Figure 3A is a figure showing shared TCR clones by visualizing subclusters within CTL-related clusters (Th1, Th17.CTL, Th1.CTL, TE.CTL, act.proli) using UMAP. Figure 3B is a UMAP figure showing the expression of key genes related to cytotoxicity and differentiation in CD4+ T cells. Figure 3C is a dot plot presenting the average expression levels and the proportion of expressing cells of specific genes across the identified subclusters. The size of the dots represents the proportion of cells expressing the corresponding gene, and the intensity of the color represents the average expression level. Figure 3D is a stacked bar graph showing the proportion of each subcluster within CTL-related clusters at different disease stages, and a box plot presenting the proportion of the TE.CTL2 subcluster within CTL-related clusters. Figures 3E and 3F are figures showing the module scores of cytotoxicity-related gene expression in the TE.CTL1 and TE.CTL2 subclusters. Figure 3E presents the results at different disease stages, while Figure 3F presents the results within MM patients. Figure 3G is a volcano plot comparing the TE.CTL2 subclusters and precursor stages of MM patients, highlighting the top 10 genes upregulated in MM. Figure 3H presents the top 6 most significant results from a CellMarker 2024 analysis of the top 30 genes showing statistically significant differences in TE.CTL2 of MM patients. Figure 3I is a UMAP plot showing the distribution of the top 10 TCR clones. Figure 3J is a heatmap showing the frequency of the top 10 TCR clones within each subcluster of the disease stage. Color intensity indicates the degree of clonal expansion. P-values ​​were calculated using the Mann-Whitney U test or the Wilcoxon rank sum test.

[0117] Figure 4A is a representative flow cytometry plot and bar graph showing the expression of GrB and GrK on CD4+ T cells obtained from PBMC and BMMC of a control group (CT; PBMC n=14, BMMC n=29) and NDMM patients (n=43). Figure 4B shows the results of comparing the ratios of CD4+ CTLs in peripheral blood (PB) and bone marrow (BM) of CT (n=14) and NDMM patients (n=43). Figures 4C and 4D are flow cytometry histograms (C) and bar graphs (D) showing the expression of specific markers on CD4+GrB+ T cells (green) and CD4+ CTLs (orange) in the bone marrow of NDMM patients (n=31: CD57, CD28, KLRG1, CD29; n=20: CX3CR1, GPR56, T-BET, EOMES). Figures 4E and 4F are flow cytometry plots and bar graphs showing T-BET and RORγt expression, and IFN-γ and IL-17A production in total CD4+ T cells (E) and CD4+GrB+ T cells or CD4+ CTLs (F) of NDMM patients (n=20). Cells were cultured for 6 hours with or without phorbol 12-myristate 13-acetate (PMA) / ionomycin stimulation. Figures 4G and 4H are flow cytometry plots (G) and bar graphs (H) showing the pluripotency of CD4+GrB+ T cells and CD4+ CTLs after 6 hours of stimulation with PMA / ionomycin. Pultipotency was evaluated by the simultaneous production of IL-17A, TNF-α, and IFN-γ. The pie chart represents the proportion of cells producing different combinations of cytokines, with the number of functions distinguished by dark orange shades. Each point represents an individual patient, and the height of the bar indicates the mean and standard deviation. P-values ​​were calculated using the Mann-Whitney U test or the Wilcoxon rank sum test.(CT: control; FITC: fluorescein isothiocyanate; GrK: granzyme K; PE-Cy: phycoerythrin-cyanine; unsti: unstimulation.).

[0118] Figure 5A is a representative flow cytometry graph showing the expression of GrB, CD107a, and Perforin after isolating total CD4+ T cells from bone marrow mononuclear cells (BMMC) of a control group (CT, n=9) and NDMM patients (n=10), followed by ex vivo culture for 24 hours and anti-CD3 antibody stimulation. Figure 5B shows the proportion of GrB+, CD107a+, and Perforin+ cells among total CD4+ T cells after anti-CD3 stimulation. Figure 5C is a representative flow cytometry graph showing the expression of Perforin and CD107a by gating the CD4+ CTLs from the data in Figure 5A. Figure 5D presents the proportion of CD107a+, Perforin+, and CD107a+Perforin+ cells within CD4+ CTLs after anti-CD3 stimulation. Figures 5E and 5F are representative histograms and summary data analyzing cytotoxicity after pre-treating CD4+ T cells obtained from BMMC of MM patients (n=6) with an anti-CD3 antibody for 24 hours, followed by co-culture with U266B1 cells (E) or RPMI 8226 cells (F) at an effector:target (ET) ratio of 10:1 for 3 hours. Cytotoxicity is expressed as the net percentage of TO-PRO-3+ cells after co-culture. Figure 5G is a figure showing the correlation between activation-dependent lysis and the ratio of CTLs to total CD4+ T cells. Figures 5H and 5I are representative histograms and summary data analyzing cytotoxicity by stimulating isolated CD4+ CTLs with an anti-CD3 antibody for 18 hours and then co-culturing them with U266B1 cells (H, n=7) or RPMI 8226 cells (I, n=9) at a 10:1 ET ratio for 6 hours. Cytotoxicity is expressed as the pure ratio of TO-PRO-3+ cells. Figure 5J is a representative histogram and summary data analyzing the cytotoxicity of CD4+ CTLs against autologous (myeloma) myeloma cells isolated from fresh BMMCs of NDMM patients (n=12).Each point represents an individual patient, and the height of the bar represents the mean. The correlation coefficient (R) and P-value were calculated using the Pearson correlation test or the Wilcoxon rank sum test.

[0119] Figure 6A is a representative flow cytometry plot (n=22) showing NKG2D expression in CD4+GrB- T cells and CD4+ CTLs after anti-CD3 stimulation. Figure 6B is a bar graph showing the proportion of NKG2D expression under the same conditions. Figure 6C shows the change in the proportion of NKG2D+ cells among CD4+ CTLs after anti-CD3 stimulation in bone marrow mononuclear cells (BMMC) of NDMM patients. The analysis was divided into a low group (≤2.9%, n=11) and a high group (>2.9%, n=11) based on the median frequency of NKG2D+ cells after thawing (2.9%). Figure 6D is a schematic diagram of the cytotoxicity analysis. CD4+CD57- cells and CD4+CD57+ T cells were isolated from BMMCs of NDMM patients and co-cultured with myeloma cells for 6 or 10 hours in the presence of IgG (10 μg / mL) or NKG2D blocking antibody (10 μg / mL). Figures 6E and 6F are representative histograms and bar graphs showing the proportion of TO-PRO-3+ cells in U266B1 cells (n=13) and RPMI 8226 cells (n=14) after co-culture with CD4+CD57- or CD4+CD57+ T cells (6 hours, various ET ratio conditions). Figure 6G is a representative histogram and bar graph showing the effect of NKG2D blocking on the cytotoxicity of CD4+CD57- or CD4+CD57+ T cells against RPMI 8226 cells (n=16). Figure 6H shows the Kaplan-Meier survival curves comparing progression-free survival (PFS) between the entire patient group (n=65) and the transplant-ineligible patient group (n=48) according to the proportion of NKG2D+ cells among CD4+ CTLs in BMMC. Each point represents an individual patient, and the height of the bars indicates the mean and standard deviation. P-values ​​were calculated using the Mann-Whitney U test, the Wilcoxon rank sum test, or the log-rank test.

[0120] Figure 7A illustrates a flow cytometry gating strategy for identifying CD4+ T cells, CD8+ T cells, and CD4+FOXP3+ Treg in bone marrow mononuclear cells (BMMC) of NDMM patients. Figure 7B shows Kaplan-Meier curves comparing progression-free survival (PFS) for all patients (n=70, left), transplant-ineligible patients (n=46, middle), and autologous hematopoietic stem cell transplant (ASCT) patients (n=24, right) when the frequency of CD4+ T cells among total T cells is below or above the median (52.6%). Figure 7C shows the results of comparing PFS in the same patient group when the CD4 / CD8 ratio is below or above the median (1.3). Figure 7D shows the results of comparing PFS for all patients (n=30, left), transplant-ineligible patients (n=23, middle), and ASCT patients (n=7, right) when the frequency of FOXP3+ Treg among total CD4+ T cells was below / above the median (6.4%). Figure 7E is a Kaplan-Meier curve comparing PFS in the same patient group when the CD8+ T cell / CD4+FOXP3+ Treg ratio was below / above the median (14.3).

[0121] Figure 8 is a heatmap showing the top 30 differentially expressed genes selected based on expression rate (pct.1 > 0.2) and mean log2 fold change (avg_log2 fold change > 0.6) in a total of 50 CD4+ T cell clusters, including healthy individuals (HD), MGUS, SMM, and MM. The color bars at the top of the heatmap indicate each CD4+ T cell subgroup, and a list of the top 30 genes is listed on the right. Genes marked in red represent the major marker genes identified in each cluster.

[0122] Figure 9 shows the changes in the frequency of BM CD4+ T cell subtypes during the progression of myeloma. Figure 9A visualizes the distribution of bone marrow CD4+ T cell subtypes in individual patients at each disease stage through a stacked bar graph, where each color represents a different CD4+ T cell subtype. Figure 9B compares the frequency of CD4+ T cell subtypes by disease stage, excluding the TE.CTL cluster shown in Figure 1J. Each point represents a single patient, the height of the box indicates the interquartile range (IQR), and the vertical line represents the total range. P-values ​​were calculated using the Mann-Whitney U test in comparison to healthy donors (HD).

[0123] Figure 10A is a UMAP plot classifying a total of 589,403 cells into major hematopoietic and immune cell populations from healthy individuals (HD, n=33) and multiple myeloma patients, including MGUS (n=4), SMM (n=6), and MM (n=87; primary, relapsed, remission). Data were aggregated from GSE120221, PRJNA765009, GSE189460, GSE271107, and GSE223060, and Seurat's Harmony method was used. Figure 10B is a feature plot showing the expression of major marker genes and mitochondrial genes (percent.mt), illustrating T cell identification and quality control. Figure 10C is a UMAP plot of the cell population distribution observed in each dataset. Figures 10D and 10E show the subclustering of total T cells and feature plots representing representative marker expression. Figure 10F is a UMAP plot of the bone marrow CD4+ T cell subpopulation. Figure 10G is a dot plot summarizing representative gene expression across the CD4+ T cell subpopulation. The size of the dots represents the proportion of cells expressing the corresponding gene, and the color intensity indicates the average expression level. Figure 10H is a feature plot showing cytotoxicity-related gene expression in the CD4+ T cell subpopulation. Figure 10I is a stacked bar graph showing the proportion of each CD4+ T cell cluster by patient group. Figure 10J is a box plot comparing the frequency of TE.CTL among total CD4+ T cells at each disease stage. Figure 10K is a box plot comparing the frequencies of naive, TE.CTL, ISGshi, and aTreg clusters that showed significant differences between HD and MM in individuals with a total CD4+ T cell count of 100 or more. Each dot represents an individual patient, and the height of the box indicates the interquartile range (IQR) and the distribution range. The P-value was calculated using the Mann-Whitney U test by comparing with HD.

[0124] Figure 11A is a UMAP figure showing the distribution of the top 10 clones and T cell clones with cell counts of 1–3 and >3 by disease stage. Figure 11B is a heatmap showing the frequency of the top 10 clones in the CD4+ T cell subgroups of each individual at each disease stage. Figure 11C is a heatmap showing the clone overlap ratio within each CD4+ T cell subgroup at each disease stage. Overlap was determined by the frequency of shared TCR clones among all TCR clones within a row cluster. The color intensity of the heatmap indicates the overlap ratio of the top 10 clones within each cluster.

[0125] Figure 12 illustrates the analysis of bone marrow-derived Treg subcluster characteristics in multiple myeloma. Figure 12A is a UMAP of Treg clustered by integrating rTreg and aTreg. Figure 12B is a heatmap showing the expression of Treg signature genes and marker genes related to naive, memory, and activation states by Treg subgroup. Figure 12C is a UMAP showing the relative expression levels of key genes among Treg subtypes. Figure 12D is a dot graph showing the expression of key genes used for cluster identification, where the dot size represents the proportion of cells expressing the corresponding gene and the color intensity represents the average expression level. Figure 12E is a heatmap showing gene expression patterns related to the 'Treg signature and immunosuppressive molecules' and 'Migration' pathways. Figure 12F is a heatmap showing the module scores of metabolic pathways, such as the tricarboxylic acid cycle (TCA) and fatty acid oxidation (FAO), by Treg subtype. Figure 12G is a contour UMAP plot visualizing the distribution of Treg subtypes by disease stage. Figure 12H is a stacked bar graph representing the proportion of Treg clusters within each patient group. Figure 12I is a box plot comparing the frequencies of Treg subtypes by disease stage, where each point represents an individual patient, the height of the box represents the interquartile range (IQR), and the vertical line represents the total range. P-values ​​were calculated using the Mann-Whitney U test.

[0126] Figure 13 shows the frequency of CD4+ CTLs and CD8+GrB+ T cells in patients with multiple myeloma. Figure 13A is a scatter plot showing the correlation between the ratio of GrB+ cells (i.e., CD4+ CTLs) among CD4+ T cells in peripheral blood (PB) and bone marrow (BM) of control groups (CT, n=14) and MM patients (n=43), with a significant positive correlation observed in MM (R=0.831, P<0.001). Figure 13B is a box plot comparing the ratio of GrB+ cells (CTLs) among CD4+ T cells in BMMC of control groups (CT, n=29), MGUS patients (n=15), SMM patients (n=15), and MM patients (n=48), showing that the frequency of CD4+ CTLs increases as the disease stage progresses. Figure 13C shows the results of analyzing GrB and GrK expression in CD8+ T cells in PBMC and BMMC of the control group (CT) and MM patients (n=43). The left side shows representative flow cytometry viscosities, and the right side is a bar graph summarizing the distribution of CD8+ T cells by GrB / GrK combinations in PB and BM. The proportion of GrB+ cells in the BM of MM patients was significantly increased (P=0.022). Figure 13D presents the results of comparing the proportion of GrB+ cells among CD8+ T cells in PB and BM of the control group and MM patients, presenting the differences between groups as a bar graph. Figure 13E is a scatter plot showing the correlation between the proportion of GrB+ cells among CD8+ T cells in PB and BM of the control group and MM patients, confirming a significant positive correlation in MM patients (R=0.604, P<0.001).

[0127] Figure 14 is a graph analyzing the immunophenotype characteristics of CD4+ cytotoxic T cells (CTLs). Figure 14A is a representative flow cytometry plot showing CCR7 and CD45RA expression in CD4+ (left) and CD8+ (right) T cells obtained from PBMCs and BMMCs of healthy control groups (CT, n=10) and newly diagnosed multiple myeloma patients (NDMM, n=24), with cells classified according to Granzyme B (GrB) expression. Figure 14B compares the proportions of naive cells (N, CCR7+CD45RA+), central memory (CM, CCR7+CD45RA-), effector memory (EM, CCR7-CD45RA-), and effector memory RA type (EMRA, CCR7-CD45RA+) within CD4+ CTLs and CD8+GrB+ T cells in CT and NDMM patients. Figure 14C is a representative flow cytometry plot showing the expression of CD57, CD28, and KLRG1 in CD4+ CTLs and CD4+GrB+ T cells in PBMCs and BMMCs of CT and NDMM patients. Figure 14D compares the proportion of CD57+CD28-KLRG1+ cells within CD4+ CTLs in CT (n=14) and NDMM (n=30) patients. Figures 14E and 14F are a histogram and bar graph showing the expression ratios of PD-1 and TIGIT in CD4+ CTLs in PBMCs and BMMCs of CT and NDMM patients. Figures 14G and 14H are representative plots showing the co-expression of CX3CR1, CD57, and GrB in bone marrow-derived CD4+ T cells of MM patients. Figures 14I and 14J analyze the correlation between the following ratios in bone marrow-derived T cells of MM patients (n=20), where the red circles in Figure 14I represent GrB+CD4+ / CX3CR1+CD4+ T cells and the orange squares represent CD57+CD4+ T cells, and Figure 14J represents CD57+ / CD4+ and CX3CR1+ / CD4+ T cells.In addition, each point represents an individual patient, the box height represents the mean ± standard deviation, and the correlation coefficient (R) and P-value were calculated using Pearson correlation analysis or Wilcoxon rank sum test.

[0128] Figure 15 illustrates changes in CD4+ CTL frequency and CD38 expression in patients with multiple myeloma (MM) at diagnosis, relapse, and after daratumumab treatment. Figure 15A compares the frequency of CD4+ CTLs among total CD4+ T cells in paired samples of patients with NDMM and relapsed / refractory MM (RRMM) (n=6). Figures 15B and 15C show representative plots (B) and summary data (C) regarding CD38 expression of CD4+ CTLs and CD4+GrB+ T cells in peripheral blood (PB) and bone marrow (BM) of NDMM patients (n=32). Figures 15D and 15E are representative plots (D) and graphs (E) showing the change in the proportion of CD38+ cells in CD4+ CTLs before and after daratumumab treatment in RRMM patients (n=4), where each point represents an individual patient and the box heights represent the mean and standard deviation (sd). P-values ​​were calculated using the Wilcoxon rank sum test.

[0129] Figure 16 shows NKG2D expression in CD4+ cytotoxic T cells (CTLs) after cytokine stimulation. Figure 16A is a flow cytometry plot and summary graph showing MHC II expression in myeloma cells of NDMM patients. Figure 16B is a representative histogram showing HLA-DR / DP / DQ and MICA expression in U266B1 and RPMI 8226 cells. Figure 16C is a representative flow cytometry plot and bar graph showing NKG2D expression in CD4+ CTLs of NDMM patients (n=65), divided into a low expression group (≤2.9%) and a high expression group (>2.9%). Figure 16D is a bar graph comparing the frequency of CD4+ CTLs among total CD4+ T cells in MM patients, divided into a group with low NKG2D expression frequency (≤2.9%, n=33) and a group with high NKG2D expression frequency (>2.9%, n=32). Figure 16E compares the change in the proportion of NKG2D+ cells among CD4+ CTLs after anti-CD3 stimulation in BMMCs of NDMM patients between the low (n=11) and high (n=11) groups. Figures 16F and 16G are representative plots and graphs showing the change in NKG2D expression in CD4+GrB+ T cells and CD4+ CTLs after treating BMMCs of NDMM patients (n=14) with IL-2 (50 ng / mL), IL-12 (10 ng / mL), and IL-15 (50 ng / mL) for 24 hours. Figure 16H compares the proportion of NKG2D+ cells in CD4+ CTLs after cytokine treatment, divided into low (≤2.9%, n=7) and high (>2.9%, n=7) groups. Figure 16I is a flow cytometry plot showing the changes in cytotoxic effects following NKG2D blockade after co-culturing CD4+CD57+ or CD4+CD57- T cells from NDMM patients with RPMI 8226 cells; each point represents an individual patient, and the box height indicates the mean ± standard deviation (sd). P-values ​​were calculated using the Mann-Whitney U test or the Wilcoxon rank sum test, and nsThis means that it is not statistically significant.

[0130] Figure 17 illustrates the gating strategy for myeloma cells and the isolation strategy for CD4+CD57+ / - cells. Figure 17A shows the gating strategy for myeloma cells in bone marrow mononuclear cells (BMMC) of NDMM patients. Figure 17B shows the isolation strategy for CD4+CD57- or CD4+CD57+ cells in BMMC of MM patients. Figure 17C is a representative plot of CD138+ myeloma cells isolated from BMMC of MM patients using autologous cell isolation. Figure 17D shows the strategy for isolating live myeloma cells from concentrated CD138+ myeloma cells.

[0131] Figure 18 shows cytokine production by CD4+ cytotoxic T cells (CTLs) following BCMA OLP and TAA stimulation. Figure 18A is a representative flow cytometry plot analyzing IFN-γ and TNF-α production after stimulating CD4+ CTLs obtained from bone marrow mononuclear cells (BMMCs) of NDMM patients with BCMA overlapping peptide (OLP), tumor-associated antigens (TAA, e.g., NY-ESO-1), or PMA / ionomycin as a positive control. Figure 18B is a bar graph showing the frequency of CD4+ CTL response to each peptide pool across multiple myeloma patients.

[0132] Figure 19 summarizes a graphic highlighting the importance of CD4+ CTLs in multiple myeloma (MM). Increased frequency and clonal activity of CD4+ cytotoxic T lymphocytes (CTLs) were observed in MM, which was confirmed through scRNA-seq and scTCR-seq analyses of bone marrow mononuclear cells (BMMCs) from patients with HD, MGUS, SMM, and MM. CD4+ CTLs exhibit an effector memory phenotype and express markers associated with cytotoxicity. They mediate potent effector functions and direct cytotoxicity against myeloma cells through TCRs and NKG2D. In particular, a high frequency of NKG2D+ CD4+ CTLs is associated with better survival in MM patients.

[0133] Figure 20 illustrates the synergistic effect of cytotoxicity on CD4+ CTLs by combined stimulation with anti-CD3 and IL-2 / IL-15 in NDMM patients. CD4+CD57- and CD4+CD57+ T cells were separated by FACS from bone marrow mononuclear cells (BMMC) of NDMM patients (n=14) that had been frozen and thawed, and then cultured for 18 hours in 96-well round-bottom plates coated with or uncoated with anti-CD3 antibodies. After stimulation, IL-2 and IL-15 were added, and the cells were co-cultured with RPMI 8226 myeloma cells for 5 hours at an effector-to-target ratio of 10:1. Cytotoxicity was evaluated by measuring target cell lysis using TO-PRO-3 uptake. Figure 20A is a summary of target cell lysis under each treatment condition, and Figure 20B is a graph of net lysis calculated by subtracting background lysis from the non-stimulated condition (no anti-CD3) under the anti-CD3 stimulated condition. Each point represents an individual patient sample, and the P-value was calculated using the Wilcoxon signed-rank test.

[0134] Figure 21 shows the results of comparing the log1p(FPKM) expression levels of ULBP5, an NKG2D ligand, across various cancer types. High expression was observed in hematological cancers such as MMRF-COMPASS, TARGET-ALL-P2, NCICCR-DLBCL, and TCGA-LAML, while conversely, it was relatively low in TCGA-KIRC (renal clear cell carcinoma) and TCGA-SKCM (melanoma). MMRF-COMPASS is Multiple Myeloma, TARGET-ALL-P2 is Acute Lymphoblastic Leukemia (Phase II), NCICCR-DLBCL is Diffuse Large B-Cell Lymphoma, TCGA-LAML is Acute Myeloid Leukemia, TCGA-SKCM is Skin Cutaneous Melanoma, TCGA-OV is Ovarian Serous Cystadenocarcinoma, TCGA-KIRC is Kidney Renal Clear Cell Carcinoma, TCGA-LUAD is Lung Adenocarcinoma, TCGA-COAD is Colon Adenocarcinoma, TCGA-PAAD is Pancreatic Adenocarcinoma, and TCGA-BRCA is It refers to breast invasive carcinoma.

[0135] The present invention will be described in more detail below through examples. These examples are intended solely to explain the present invention more specifically, and it will be obvious to those skilled in the art that the scope of the present invention is not limited by these examples according to the gist of the invention.

[0136] Experimental method

[0137] Patient sample preparation

[0138] The present invention was approved by the Institutional Review Board of Severance Hospital, Yonsei University College of Medicine (Seoul, Korea; IRB 4-2024-0326). Compliance with the Declaration of Helsinki was ensured, and written informed consent was obtained from all participants. Paired samples of peripheral blood mononuclear cells (PBMC) and BM mononuclear cells (BMMC) were collected from patients who had no prior treatment experience at the time of diagnosis.

[0139] scRNA-seq and scTCR-seq

[0140] scRNA-seq and scTCR-seq libraries were prepared using the Chromium Next GEM Single Cell 5' HT v2 reagent via multiplexing with classified CD4+ T cells. scRNA-seq data were analyzed using the Seurat and Demuxlet packages. For scTCR-seq, cells with CDR3 sequences that matched TCRA and TCRB one-to-one were selected. For public data analysis, scRNA-seq datasets for BM cells from GSE120221, PRJNA765009, GSE189460, GSE271107, and GSE22306036-40 were aggregated using the Seurat package, and batch correction was performed using the Harmony technique. TCR-seq analysis included TCR sequence evaluation using public TCR databases (McPAS-TCR and VDJdb).

[0141] Multicolor flow cytometry

[0142] Flow cytometry analysis was performed using FACSLyric (BD Biosciences), and the data were analyzed using FlowJo (Treestar).

[0143] Stimulation of patient samples

[0144] Cryopreserved PBMCs or BMMCs were thawed and resuspended in RPMI-1640 medium (Cytiva) supplemented with 10% FBS (Corning). Cells were stimulated with phorbol myristate acetate (PMA, Sigma-Aldrich, 50 ng / mL) and ionomycin (Sigma-Aldrich, 1 μg / mL) or anti-CD3 antibody (1 μg / mL, Invitrogen). To evaluate antigen-specific cytokine production by CD4+ T cells, BCMA overlapping peptides (OLP) across the entire amino acid sequence and HLA class II restriction epitope peptides of tumor-associated antigens (purity >70%, GenScript) were used. Cells were stimulated with BCMA OLP pool or tumor antigen peptide pool (2 μg / mL each) for 6 hours, and Brefeldin A and monensin were added 1 hour after stimulation.

[0145] Cytotoxicity Analysis

[0146] Target myeloma cells stained with PKH-26 dye (Sigma-Aldrich) were co-cultured with CD4+ T cells enriched at various effector-to-target (ET) ratios for 3–6 hours after prestimulation, regardless of the presence or absence of anti-CD3 antibodies. Selected CD4+CD57- or CD4+CD57+ T cells were stimulated for 18 hours, regardless of the presence or absence of anti-CD3 antibodies, and then co-cultured with target myeloma cells for 6 hours. To evaluate the autologous tumor cell apoptosis ability of CD4+ CTLs, selected autologous myeloma cells were co-cultured with CD4CD57 T cells paired at a 5:1 ET ratio for 16 hours in the presence of IL-2 (50 ng / mL, PeproTech) without anti-CD3 stimulation. Block assays were performed using anti-NKG2D antibody (10 μg / mL, BD Biosciences) or IgG isomorphic control (10 μg / mL, BD Biosciences). Net lysis was calculated by subtracting the ratio of apoptotic target cells cultured only under conditions where the target cells were cultured from the ratio of apoptotic target cells cultured together under conditions where the effector and target cells were cultured together. The dead target cells were stained with TO-PRO-3 (Thermo Fisher).

[0147] Statistical analysis

[0148] Statistical analysis was performed using GraphPad Prism 9.2 (GraphPad Software) and the R package.

[0149] Experimental results

[0150] The abundance of CD4+ T cells in the bone marrow is associated with improved survival in patients with multiple myeloma.

[0151] To evaluate the clinical significance of CD4+ and CD8+ T cells in multiple myeloma (MM), the frequency of these cells among total CD3+ T cells was measured in bone marrow aspirates from newly diagnosed MM (NDMM) patients (Fig. 7A). As autologous hematopoietic stem cell transplantation (ASCT) following high-dose chemotherapy is considered the standard treatment for extending progression-free survival (PFS) in transplant-eligible patients, the patient group was classified according to transplant status.

[0152] The abundance of CD4+ T cells among total T cells showed a significant correlation with improved PFS, particularly in the group of patients ineligible for transplantation (Fig. 7B). In these patients, a higher CD4 / CD8 ratio was associated with significantly longer PFS, and these results were observed in a situation where baseline clinical indicators and treatment profiles were evenly distributed (see Baseline Clinical Characteristics of NDMM Patients, Tables 1 to 4).

[0153]

[0154]

[0155]

[0156]

[0157] ECOG: Eastern Cooperative Oncology Group, PS: Performance Status, BM: Bone Marrow, FLC: Free Light Chain, R-ISS: Revised International Staging System, N / A: Not Available, V: Bortezomib, T: Thalidomide, D: Dexamethasone, M: Melphalan, P: Prednisolone, R: Lenalidomide

[0158] On the other hand, no such survival benefit was observed in patients who underwent ASCT, and only slight differences in survival were observed depending on the frequency of FOXP3+ regulatory T cells (Tregs) among total CD4+ cells and the CD8 / Treg ratio (Figs. 7B to 7E).

[0159] GZMB-expressing CD4+ CTLs are significantly increased in patients with myeloma.

[0160] To more precisely identify CD4+ T cell subtypes associated with clinically significant prognosis in multiple myeloma (MM), CD4+ T cells were isolated using FACS from bone marrow mononuclear cells (BMMC) of healthy donors (HD, n=10), monoclonal gammopathy (MGUS, n=10), asymptomatic myeloma (SMM, n=11), and multiple myeloma patients (MM, n=19) (Fig. 1A). The functional status of BM CD4+ T cells was inferred by performing droplet-based scRNA-seq and paired scTCR-seq, and a total of 160,956 CD4+ T cell datasets were obtained from 50 subjects (basic information and cell counts after processing of samples subjected to scRNA-seq; see Table 5).

[0161]

[0162] A total of 14 different BM CD4+ T cell subtypes were identified through unsupervised clustering based on differentially expressed genes. The above CD4+ T cell subtypes include naive cells (CCR7+TCF7+FAS-HNRNPLL-), early activated cells (early activated, early.act, CCR7+TCF7+FAS-NR4A1+), central memory cells (central memory, CM, CCR7+FAS+), follicular helper T cells (follicular helper T, Tfh, CXCR5+BCL6+), Th2 (GATA3+CCR4+), Th17 (RORC+CCR6+), Th1 (TBX21+CXCR3+IFNG+), and two subtypes of regulatory T cells (Treg, FOXP3+CTLA4+): resting regulatory T cells (resting Treg, rTreg, CCR7+) and activated regulatory T cells (activated Treg, aTreg, HLA-DRA+TNFRSF9+), and IFN-stimulated gene-enriched cells (IFN-stimulated genes-enriched, ISGshi). There are OAS3+IRF7+) and activated and proliferating cells (activated and proliferating, act.proli, MKI67+ CD38+) (see FIGS. 1B to 1D and FIG. 8A, and Tables 6 to 8 showing the top 50 differentially expressed genes in CD4+ T cell clusters).

[0163]

[0164]

[0165]

[0166] Notably, two distinct states were identified among bone marrow CD4+ T cell subtypes that highly express cytotoxic effector molecules. One was a subtype expressing GZMB, and the other was a subtype expressing GZMK (Figs. 1B to 1D). The GZMB-expressing subtype expressed cytotoxic molecules such as GZMA, NKG7, GNLY, and PRF1 at high levels, and also expressed markers related to terminal differentiation such as B3GAT1, KLRG1, and CD27. Accordingly, this population was named terminal effector cytotoxic T cells (TE.CTL) (Figs. 1B-D). On the other hand, the GZMK-expressing subtype had low expression levels of cytotoxic molecules but expressed Th1 or Th17 signature genes more highly (Figs. 1B to 1D). Accordingly, these subtypes were named Th1.CTL and Th17.CTL, respectively (Figs. 1B to 1D).

[0167] Analysis of module scores for a set of signature genes related to CD4+ T cell function revealed that three CTL clusters—Th1.CTL, Th17.CTL, and TE.CTL—and the Th1 subtype exhibited strong activation, effector function, and TCR signaling profiles (see Fig. 1E and Tables 9 to 11 showing selected gene signatures). Among these, TE.CTL was found to have the highest expression of genes related to cytokines and receptors, migration, adhesion, and cytotoxicity (Fig. 1E).

[0168]

[0169]

[0170]

[0171] Through cell trajectory analysis, the possibility was suggested that a differentiation pathway exists from Th1 to TE.CTL via Th1.CTL (Figs. 1F to 1G), which implies that CD4+ CTLs can originate from Th1 cells.

[0172] As a result of investigating changes in the frequency of BM CD4+ T cell subtypes, the terminal effector cytotoxic T cell (TE.CTL) population was found to be significantly increased in multiple myeloma (MM) patients compared to healthy donors (HD) (P=0.003) (Figs. 1H-J). In addition, an increase in the ISGshi subtype and a decrease in the act.proli subtype were also observed in multiple myeloma patients (Figs. 9A and 9B).

[0173] To validate these results, publicly available bone marrow single-cell RNA sequencing datasets were integrated to analyze data consisting of a total of 589,403 cells (of which 94,401 were CD4+ T cells). The data originated from HD (n=33), MGUS (n=4), SMM (n=6), and MM (n=87) (Figs. 10A to 10E). CD4+ T cells were clustered based on subtype-specific marker gene expression, including the TE.CTL cluster (Figs. 10F to 10H).

[0174] As a result, the frequency of TE.CTLs was consistently significantly higher in multiple myeloma patients (MM) than in healthy donors (HD) (P=0.037), accompanied by a decrease in naive CD4+ T cells and an increase in ISGshi and activated regulatory T cells (aTregs) (Figs. 10I to 10K).

[0175] Significant clonal expansion of BM CD4+ terminal effector cytotoxic T cell (TE.CTL) clusters in multiple myeloma patients

[0176] To evaluate whether the increased frequency of TE.CTLs in multiple myeloma is associated with clonal expansion, scTCR-seq data of BM CD4+ T cells were analyzed. In a combined dataset containing a total of 101,286 cells, expanded T cell clones (n>1) and the top 10 clones (greater than 0.1% of total CD4+ T cells, n>3) were found to be primarily located within the TE.CTL community (see Figure 2A, Tables 12 and 13 showing the cell numbers and frequencies of the top 10 clones analyzed by scTCR-seq, and Tables 14 to 16 showing the CDR3 amino acid sequences of the TCRα and TCRβ chains of the top 10 clones). Notably, the proportion of expanded clones and the top 10 clones increased with disease progression and was significantly more abundant in multiple myeloma patients (MM) compared to healthy donors (HD) (Figures 2B-D, Figures 11A and 11B). Importantly, the frequency of TE.CTLs among expanded CD4+ T cell clones was significantly higher in MM than in HD (Figs. 2E-F), and the proportion of the top 10 clones within the TE.CTL cluster was also significantly higher in MM, along with a significant decrease in TCR diversity of CD4+ T cells (Fig. 2G).

[0177]

[0178]

[0179]

[0180]

[0181]

[0182] To analyze the clonal dynamics of CD4+ T cells in greater depth, clonal duplication between subtypes was investigated.

[0183] As a result, it was confirmed that duplicate T cell clones existed among the TE.CTL, Th1, Th1.CTL, Th17.CTL, and act.proli colonies at all disease stages (Fig. 2H, Fig. 11C).

[0184] In the asymptomatic myeloma (SMM) stage, shared clones between TE.CTL and other subtypes increased, while in the multiple myeloma (MM) stage, they were concentrated in Th1.CTL and act.proli (Fig. 2H). Cell trajectory analysis revealed that TE.CTL follows a pathway originating from Th1, passing through Th1.CTL, and transitioning to a more differentiated state (Fig. 2I).

[0185] In summary, these results suggest the possibility that TE.CTL emerges in the progenitor stage and undergoes clonal expansion in multiple myeloma (MM) due to continuous antigenic stimulation.

[0186] The TE.CTL2 subtype within TE.CTL increased and was accompanied by clonal expansion.

[0187] By precisely analyzing cytotoxic T cell (CTL) clusters (Th1.CTL, Th17.CTL, TE.CTL) and corresponding subtypes (Th1, act.proli) that share TCR clonotypes with them, a total of nine detailed subtypes were identified (see Fig. 3A and Tables 17 and 18 showing the top 50 differentially expressed genes in CTL-related clusters). Focusing on TE.CTL, it was confirmed that two subclusters, TE.CTL1 and TE.CTL2, exist (Fig. 3A).

[0188]

[0189]

[0190] TE.CTL2 showed high expression levels of GZMB, NKG7, PRF1, and GNLY, as well as elevated expression of CX3CR1, KLRK1 (NKG2D), SLAMF7 (CD319), ITGB1 (CD29), and ADGRG1 (GPR56), exhibiting characteristics of being more differentiated and having higher cytotoxicity than TE.CTL1. In contrast, the expression of cytotoxicity markers in TE.CTL1 was at an intermediate level (Fig. 3B-C).

[0191] Th17.CTLs were classified into Th17.cyto and CCR6 subtypes, and Th1.CTLs were classified into Th1.cyto and IFNGhi (high expression of IFNG and TNF) subtypes.

[0192] Act.proli was divided into act (highly expressing CD38) and proli (highly expressing MKI67) (Fig. 3A-C).

[0193] As the role of RUNX3, a transcription factor that induces cytotoxic molecule expression in CD4+ T cells, is already known, we analyzed RUNX3 expression and confirmed that RUNX3 is stably expressed across all CTL clusters and corresponding subtypes that share clonal types (Fig. 3C). On the other hand, TBX21 and PRDM1, which regulate cytotoxic gene expression in Th1 cells, exhibited different expression patterns. TBX21 was predominantly expressed in TE.CTLs, particularly TE.CTL2, while PRDM1 was highly expressed in the IFNGhi and act subtypes (Fig. 3C).

[0194] Subsequently, focusing on CTL-related clusters, TE.CTL2 was the only subtype that was significantly increased in multiple myeloma (MM) patients compared to healthy donors (HD), monoclonal gammopathy (MGUS), and asymptomatic myeloma (SMM) (Fig. 3D).

[0195] Both TE.CTL1 and TE.CTL2 showed higher cytotoxicity scores in multiple myeloma (MM) than in healthy donors (HD), and TE.CTL2 showed the highest score in multiple myeloma (MM) (Figs. 3E and 3F).

[0196] Differential expression gene analysis revealed that KLRK1 expression in TE.CTL2 in multiple myeloma (MM) was significantly increased compared to non-MM, and cytotoxic and natural killer (NK) cell-specific gene markers were concentrated according to CellMarker 2024 (Figs. 3G-H). Importantly, the proportion of the top 1 clone within TE.CTL increased with disease progression, and it was confirmed that TE.CTL2 is a subtype in which the top 10 clones are particularly concentrated (Figs. 3I and 3J).

[0197] As multiple myeloma progresses, regulatory T cells (Treg) exhibit a more immunosuppressive phenotype.

[0198] Considering the inhibitory function of regulatory T cells (Treg) on ​​cytotoxic T cells (CTL), resting regulatory T cells (rTreg) and activated regulatory T cells (aTreg) were analyzed, and a total of five subtypes were identified (see Fig. 12A and Table 19, which shows the top 50 differentially expressed genes in the Treg subcluster). The CCR7hi and NR4A2hi Treg subtypes exhibited a naive state, characterized by low expression of both regulatory T cell signature genes and activation marker genes (Figs. 12A to 12C). In contrast, the HLA-DRAhi, FOXP3hi, and IL2RAhi Treg subtypes showed high expression of regulatory T cell signature genes and appeared in a memory and activated state (Figs. 12A to 12C). Among them, the FOXP3hi and IL2RAhi Treg subtypes showed increased expression of IKZF2, ICOS, IL10RA, and TGFB1, while the HLA-DRAhi and FOXP3hi Treg subtypes showed increased expression of genes related to glycolysis and the citric acid cycle (TCA cycle) (see Figures 12D and 12F, and Table 20, which shows the set of genes associated with the metabolism of regulatory T cells (Treg)). In particular, the FOXP3hi Treg subtype was significantly increased in MM patients compared to HD and MGUS, and the CCR7hi Treg subtype was found to be decreased in MM compared to HD (Figures 12G and 12I).

[0199]

[0200]

[0201] CD4+ CTLs are significantly increased in NDMM patients.

[0202] To characterize CD4+ CTLs more precisely through flow cytometry, Grzyme B (GrB) and Grzyme K (GrK), based on high GZMB and low GZMK expression in clonal expanded TE.CTLs, were used as markers (Fig. 1C). CD4+GrB+GrK- T cells were defined as CD4+ CTLs in the peripheral blood (PB) and bone marrow (BM) of multiple myeloma patients (Fig. 4A). Therefore, CD4+GrB+ T cells were used as markers for CD4+ CTLs in subsequent analyses. Subsequently, the frequency of CD4+ CTLs among total CD4+ T cells was measured in multiple myeloma patients and compared with non-Hodgkin lymphoma (NHL) patients without bone marrow involvement as a control group. As a result, the frequency of CD4+ CTLs in the bone marrow of MM patients (n=47) was significantly higher compared to the age- and sex-matched control group (n=14); even within the same patient group, levels were higher in the bone marrow than in peripheral blood, and a strong correlation between the two sites was confirmed (Figs. 4A-B and Fig. 13A). Additionally, CD4+ CTLs were significantly increased in the bone marrow of MGUS (n=15) and SMM (n=15) patients compared to the control group (Fig. 13B). On the other hand, while the frequency of CD8+GrB+ T cells did not show a significant difference between the groups, the levels between PB and BM within MM patients showed a correlation (Figs. 13C to 13E).

[0203] CD4+ CTLs exhibit a unique cytotoxic immune phenotype.

[0204] To analyze the memory cell phenotype of CD4+ CTLs, the expression of CCR7 and CD45RA, as well as the differentiation markers CD57, CD28, and KLRG1, were evaluated. As a result, CD4+ CTLs from multiple myeloma patients mostly exhibited an effector memory cell (EM) phenotype, and CD8+GrB+ T cells primarily displayed an effector memory cell phenotype expressing CD45RA (Figs. 14A and 14B). CD4+ CTLs from multiple myeloma (MM) patients exhibited a characteristic immunophenotype of CD57+CD28-KLRG1+, which was distinct from CD4+GrB- T cells (Figs. 4C-D, 14C-D). Notably, PD-1 expression was significantly higher in CD4+ CTLs than in CD4+GrB- T cells in both PB and BM of MM patients, and TIGIT expression was specifically increased in bone marrow CD4+ CTLs of MM patients (Figs. 14E-F). Consistent with the transcriptome analysis results, the expression of CX3CR1, GPR56, and CD29 was significantly higher in CD4+ CTLs than in CD4+GrB- T cells (Figs. 4C-D). CX3CR1 and CD57 were predominantly expressed in CD4+ CTLs and were rarely observed in CD4+GrB- T cells (Figs. 14G-H). Furthermore, the frequencies of CX3CR1+CD4+ T cells and CD57+CD4+ T cells showed strong correlations with each other and with the frequency of CD4+ CTLs, which supported the scRNA-seq results (Figs. 14I-J, Fig. 3C). Supporting that CD4+ CTLs are effectors and cytotoxic subtypes, the expression of T-BET and EOMES was significantly higher in CD4+ CTLs compared to CD4+GrB- T cells (Figs. 4C-D). However, CD4+ CTLs did not express RORγt and produced almost no IL-17A, but instead produced large amounts of IFN-γ in response to PMA / ionomycin stimulation (Figs. 4E-F).In particular, they exhibited high polyfunctionality, such as the simultaneous production of IFN-γ and TNF-α upon stimulation, which was a distinguishing feature from Th2 or Th17 cells (Figs. 4G-H). Additionally, analysis of paired samples from patients with relapsed or refractory MM revealed that the frequency of myeloid CD4+ CTLs among total CD4+ T cells decreased at the time of relapse compared to the time of diagnosis (Fig. 15A; refer to Table 21, which shows baseline clinical characteristics at diagnosis for patients with relapsed / refractory multiple myeloma (RRMM) and patients treated with daratumumab). Furthermore, CD4+ CTLs had a lower proportion of CD38+ cells than CD4+GrB- T cells (Figs. 15B-C), and both subtypes showed a similar decrease in CD38+ cells after daratumumab treatment (Figs. 15D-E).

[0205]

[0206] BM CD4+ CTLs in multiple myeloma patients exhibit strong effector function and reactivity to myeloma antigens.

[0207] The functional capacity of BM CD4+ CTLs was evaluated. When bone marrow mononuclear cells (BMMCs) were stimulated ex vivo with an anti-CD3 antibody, the proportion of GrB+ cells among total CD4+ T cells significantly increased, and the expression of CD107a and perforin also increased (Figs. 5A-B). In both the control group and MM patients, CD107a+ and CD107a+Perforin+ CD4+ CTLs were strongly increased by anti-CD3 stimulation, and no significant difference was observed between the two groups (Figs. 5C-D). Subsequently, CD4+ T cells were isolated from BMMCs pre-activated with CD3 from NDMM patients and co-cultured with myeloma cells (Figs. 5E-F). Myeloma cells obtained from patients exhibited diverse MHC II expression patterns (Fig. 16A), and since it was difficult to obtain fresh bone marrow aspirates and culture primary myeloma cells without cytokines, myeloma cell lines were used. Specifically, U266B1 and RPMI 8226 cell lines were used, distinguished by the presence of HLA-DR / DP / DQ expression (Fig. 16B). As a result, bone marrow CD4+ T cells from MM patients clearly exhibited cytotoxic activity against myeloma cells upon anti-CD3 stimulation (Figs. 5E-F). In addition, a positive correlation trend was observed between CD4+ CTL frequency and anti-CD3 stimulation-dependent cell lysis rate (Fig. 5G).

[0208] CD4+ CTLs were isolated from BMMCs of NDMM patients using CD57 as a surrogate marker, as CD57 is specifically expressed in CD4+ CTLs but not in CD4+GrB- cells (Figs. 4D, 17B). When the isolated cells were stimulated with anti-CD3, CD4+ CTLs exhibited significantly higher cytotoxicity against myeloma cells compared to CD4+CD57- cells (Figs. 5H-I). However, unstimulated CD4+ T cells also showed basal cytotoxicity of up to approximately 10%, suggesting the existence of additional cytotoxic mechanisms. In particular, CD4+ CTLs demonstrated cytotoxicity against the patient's own myeloma cells even without anti-CD3 stimulation and exhibited the ability to recognize and target autologous tumor cells (Figs. 5J, 17C-D).

[0209] Next, we investigated whether highly expanded CD4+ CTLs in MM have the potential to specifically recognize tumor-associated antigens. The TCR sequences of the top 10 clones predominantly observed in CD4+ CTLs were compared with tumor-specific TCR sequences listed in public databases (McPAS-TCR and VDJdb). As a result, among 40 carriers of multiple myeloma or precursor disease (MGUS, SMM), none of the top 10 clones matched known tumor-specific TCRs. However, one clone each from the top 3rd position in MGUS_1 patient and the top 7th position in MM_3 patient matched CMV-specific TCRβ sequences, but most expanded clones did not correspond to known virus-specific TCRs.

[0210] In addition, to evaluate the antigen specificity of bone marrow CD4+ CTLs, BMMCs from MM patients were stimulated with BCMA overlapping peptide (OLP) and HLA class II restriction epitope peptides derived from tumor-associated antigens such as NY-ESO-1. As a result, CD4+ CTLs in 26.8% (11 / 41) of the total patients responded to OLP to produce IFN-γ and TNF-α (see Figure 18A-B and Table 22 showing the amino acid sequences of BCMA OLP and tumor-associated antigen-derived epitope peptides), confirming that BM CD4+ CTLs can recognize and respond to myeloma antigens.

[0211]

[0212] CD4+ CTLs kill MM cells in an NKG2D-dependent manner.

[0213] The researchers recently reported that NKG2D ligand expression in myeloma cells is associated with prognosis. Based on the fact that the TE.CTL2 subtype is specifically abundant in MM patients and highly expresses KLRK1 (NKG2D) (Fig. 3G), NKG2D expression in BM CD4+ CTLs was evaluated. As a result, NKG2D expression was not observed in CD4+GrB- cells; NKG2D was specifically expressed only in CD4+ CTLs, and there were differences in expression levels among patients (Fig. 16C). Furthermore, anti-CD3 stimulation significantly increased NKG2D+ expression in CD4+ CTLs (Figs. 6A-B). Patients with a higher proportion of NKG2D cells among CD4+ CTLs tended to show a greater likelihood of NKG2D induction in response to anti-CD3 stimulation (Figs. 6C, Figs. 16D-E). These results suggest that TCR stimulation induces NKG2D expression in CD4+ CTLs, and that this expression is particularly stronger in cells with high basal NKG2D levels.

[0214] In addition, when BMMCs were treated with IL-2 and IL-15 ex vivo, NKG2D expression in CD4+ CTLs significantly increased, unlike with IL-12 (Figs. 16F-H). CD4+ CTLs with high basal NKG2D expression responded to both IL-2 and IL-15 stimulation, resulting in a significant increase in the proportion of NKG2D+ cells, whereas the group with low basal expression responded only to IL-15 (Figs. 16F-H).

[0215] Additionally, to confirm the synergistic effect of cytotoxicity on CD4+ CTLs by combined stimulation with anti-CD3 and IL-2 / IL-15 in NDMM patients, CD4+CD57- and CD4+CD57+ T cells were isolated by FACS from bone marrow mononuclear cells (BMMC) of NDMM patients (n=14) that had been frozen and thawed, and then cultured for 18 hours in 96-well round-bottom plates coated with or uncoated with anti-CD3 antibodies. After stimulation, IL-2 and IL-15 were added, and the cells were co-cultured with RPMI 8226 myeloma cells for 5 hours at an effector-to-target ratio of 10:1, and cytotoxicity was evaluated by measuring target cell lysis using TO-PRO-3 uptake. As a result, CD4+CD57+ T cells exhibited overall higher cytotoxic activity compared to CD57- cells, and while cytotoxicity increased with stimulation by IL-2, IL-15, or anti-CD3 alone, the highest cytotoxic activity was induced with combined stimulation by anti-CD3 and IL-2 / 15 (P<0.001, see Fig. 20). In particular, in the net lysis analysis, a distinct increase in cytotoxicity was observed in multiple patient samples under combined stimulation conditions, along with the production of IFN-γ and TNF-α, suggesting that the functional activation of CD4+ CTLs can be synergistically induced by cytokine and TCR co-stimulation.

[0216] Finally, we evaluated whether NKG2D+CD4+ CTLs from multiple myeloma (MM) patients could exhibit NKG2D-dependent cytotoxic activity. MM CD4+ CTLs were sorted and co-cultured with myeloma cells expressing the NKG2D ligand (MICA) in the presence of IL-2 and IL-15 (Figs. 6D, 16B). As a result, CD4+ CTLs exhibited strong cytotoxic activity against myeloma cells even without anti-CD3 stimulation (Figs. 6E-F). Notably, this cytotoxicity was significantly reduced by blocking NKG2D, a phenomenon not observed in CD4+CD57- T cells (Figs. 6G, 16I).

[0217] Notably, transplant-incompatible MM patients with a high frequency of NKG2D+CD4+ CTLs in their bone marrow at diagnosis had a significantly longer progression-free survival (PFS) compared to the entire patient group (including ASCT recipients) (Fig. 6H). On the other hand, there was no significant difference in the overall frequency of CD4+ CTLs between the high-expression and low-expression NKG2D groups, and baseline clinical indicators were similar (Fig. 16D; see Tables 23 and 24 showing baseline clinical characteristics of newly diagnosed multiple myeloma (NDMM) patients). For reference, Table 25 shows the baseline clinical characteristics of the control group, and Table 26 summarizes the major resources used.

[0218]

[0219]

[0220]

[0221] MALT: Mucosa-associated lymphoid tissue, DLBCL: Diffuse large B-cell lymphoma, CNS: Central nervous system, No: Number.

[0222]

[0223] Foregoing, specific parts of the present invention have been described in detail. It is evident to those skilled in the art that such specific descriptions are merely preferred embodiments and do not limit the scope of the invention. Accordingly, the actual scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A composition for predicting cancer prognosis comprising, as an active ingredient, a preparation for measuring CD4+ CTLs upregulated by the NKG2D protein biomarker.

2. In Paragraph 1, A composition for predicting cancer prognosis, wherein the CD4+ CTL with the NKG2D protein biomarker upregulated is CX3CR1hi.

3. In Paragraph 1, A composition for predicting cancer prognosis, wherein the above cancer is a non-solid cancer.

4. In Paragraph 3, A composition for predicting cancer prognosis, wherein the above-mentioned non-solid cancer is any one selected from the group consisting of myeloma, multiple myeloma, blood cancer, and hematopoietic stem cell carcinoma.

5. In Paragraph 1, A composition for predicting cancer prognosis, wherein the above cancer is a cancer cell expressing an NKG2D ligand.

6. A method for providing information for predicting cancer prognosis, comprising the step of measuring the ratio of NKG2D+ CD4+ CTLs to provide information regarding the likelihood of continued progression-free survival (PFS).

7. In Paragraph 6, A method for providing information for cancer prognosis prediction, further comprising a step of determining that progression-free survival (PFS) is more likely to continue when the ratio of the above NKG2D+ CD4+ CTLs is higher than a predefined control group or reference value.

8. In Paragraph 6, A method for providing information, further comprising the step of providing information that the prognosis is better in cancer patients expressing an NKG2D ligand when the ratio of the above NKG2D+ CD4+ CTLs is higher than a predefined control group or reference value.

9. A pharmaceutical composition for the prevention or treatment of cancer comprising an active ingredient CD4+ CTL in which NKG2D is upregulated, wherein the upregulation of NKG2D is by a cytokine, and the cytokine is one or more selected from the group consisting of IL-2, IL-6, IL-10, and IL-15.

10. In Paragraph 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the CD4+ CTL in which the above NKG2D is upregulated is CX3CR1hi.

11. In Paragraph 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the upregulation of the above NKG2D is by one or more antibodies selected from the group consisting of anti-CD3, anti-CD28, anti-4-1BB, anti-OX40, and anti-CD27.

12. In Paragraph 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the above cytokines are IL-2 and IL-15.

13. In Paragraph 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the above cancer is a non-solid cancer.

14. In Paragraph 13, A pharmaceutical composition for the prevention or treatment of cancer, wherein the above-mentioned non-solid cancer is any one selected from the group consisting of myeloma, multiple myeloma, blood cancer, and hematopoietic stem cell carcinoma.

15. In Paragraph 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the cancer has cancer cells expressing an NKG2D ligand.

16. As a diagnostic device for predicting cancer prognosis, (a) A measuring unit for measuring the ratio of NKG2D+ CD4+ CTLs to a biological sample obtained from a target individual; (b) a calculation unit that determines that there is a higher likelihood of progression-free survival (PFS) continuing when the ratio of NKG2D+ CD4+ CTLs measured by the above measurement unit is higher than a predefined control group or reference value; and (c) An output unit that outputs prognostic information of a cancer patient based on the judgment result of the above-mentioned operation unit; a diagnostic device comprising 17. In Paragraph 16, A diagnostic device characterized by the above-described operation unit additionally determining information that the prognosis is better when the ratio of the NKG2D+ CD4+ CTL is higher than a predefined control group or reference value.

18. In Paragraph 16, A diagnostic device in which the above cancer is a cancer cell expressing NKG2D ligand.

19. Use of a preparation that measures CD4+ CTLs upregulated by the NKG2D protein biomarker in cancer prognosis prediction.

20. In Paragraph 19, Use of a preparation for measuring CD4+ CTLs, wherein the CD4+ CTL upregulated by the above NKG2D protein biomarker is CX3CR1hi.

21. In Paragraph 19, The above cancer is a non-solid cancer, and the use of a preparation for measuring CD4+ CTLs.

22. In Paragraph 21, The above-mentioned non-solid tumor is any one selected from the group consisting of myeloma, multiple myeloma, hematological cancer, and hematopoietic stem cell carcinoma, and the use of a preparation for measuring CD4+ CTLs.

23. Use of CD4+ CTLs upregulated by the NKG2D protein biomarker for cancer prevention or treatment.

24. In Paragraph 24, CD4+ CTLs with the above-mentioned NKG2D protein biomarker upregulated as CX3CR1hi are for use in cancer prevention or treatment.

25. In Paragraph 24, The upregulation of the above NKG2D is by a cytokine, and the cytokine is one or more selected from the group consisting of IL-2, IL-6, IL-10 and IL-15, for use in cancer prevention or treatment.

26. In Paragraph 24, The above cancer is a cancer cell having an NKG2D ligand, for use in cancer prevention or treatment.

27. A method for preventing or treating cancer comprising the step of administering CD4+ CTLs with upregulated NKG2D as an active ingredient.

28. In Paragraph 27, A method for preventing or treating cancer, wherein the CD4+ CTL in which the above NKG2D is upregulated is CX3CR1hi.

29. In Paragraph 27, A method for preventing or treating cancer, wherein the upregulation of the above NKG2D is by any one or more antibodies selected from the group consisting of anti-CD3, anti-CD28, anti-4-1BB, anti-OX40 and anti-CD27.

30. In Paragraph 27, The above cancer is a non-solid cancer, a method for preventing or treating cancer.

31. In Paragraph 30, A method for preventing or treating cancer, wherein the above-mentioned non-solid cancer is any one selected from the group consisting of myeloma, multiple myeloma, blood cancer, and hematopoietic stem cell cancer.

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