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KR-20260064501-A - Pharmaceutical composition for preventing or treating cancer

KR20260064501AKR 20260064501 AKR20260064501 AKR 20260064501AKR-20260064501-A

Abstract

The present invention relates to a pharmaceutical composition for the prevention or treatment of cancer comprising CD4 + CTLs as an active ingredient. The CD4 + CTLs of the present invention perform a cytotoxic function by directly attacking and killing myeloma cells, thereby contributing to increasing the survival rate of patients, particularly in myeloma patients who are ineligible for transplantation, by extending the progression-free survival period. Furthermore, by using NKG2D + CD4 + CTLs as a biomarker for predicting the prognosis of myeloma patients, it is possible to establish personalized treatment strategies by analyzing the individual patient's CD4 + CTL status. Additionally, the prevention or treatment of cancer can be achieved more effectively by increasing the cytotoxicity of NKG2D + CD4 + CTLs through treatment with specific cytokines.

Inventors

  • 조현수
  • 김소정
  • 곽정은

Assignees

  • 연세대학교 산학협력단

Dates

Publication Date
20260507
Application Date
20250905
Priority Date
20241031

Claims (18)

  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 Article 1, A composition for predicting cancer prognosis, wherein the CD4 + CTL in which the above NKG2D protein biomarker is upregulated is CX3CR1 hi .
  3. In Article 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 Article 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 cancer prognosis prediction, comprising the step of measuring the ratio of NKG2D + CD4 + CTL to provide information regarding the likelihood of continued progression-free survival (PFS).
  7. In Article 6, A method for providing information for predicting cancer prognosis, further comprising a step of determining that progression-free survival (PFS) is more likely to continue when the ratio of NKG2D + CD4 + CTL is higher than a predefined control group or reference value.
  8. In Article 6, A method for providing information, further comprising the step of providing information that the prognosis is better in cancer patients expressing the NKG2D ligand when the ratio of NKG2D + CD4 + CTL 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 Article 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the CD4 + CTL in which the above NKG2D is upregulated is CX3CR1 hi .
  11. In Article 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 Article 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the above cytokines are IL-2 and IL-15.
  13. In Article 9, A pharmaceutical composition for the prevention or treatment of cancer, wherein the above cancer is a non-solid cancer.
  14. In Article 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 Article 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 + CTL in 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 if the ratio of NKG2D + CD4 + CTL 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 Article 16, A diagnostic device characterized by the above-described operation unit additionally determining information that the prognosis is better when the ratio of NKG2D + CD4 + CTL is higher than a predefined control group or reference value.
  18. In Article 16, A diagnostic device in which the above cancer is a cancer cell expressing NKG2D ligand.

Description

Pharmaceutical composition for preventing or treating cancer 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. 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. 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. 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. 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 presents the pseudotime analysis of total BM CD4 + T cells, color-coding the cells 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), illustrating 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 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) 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 are 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 each disease stage. Figure 2G is a box plot showing the proportion of the top 10 clones among