TOPK inhibitors and immune checkpoint inhibitors for treatment of gastric cancer

Abstract

The invention provides a medicine for treating gastric cancer and a use scheme thereof. Specifically, the invention provides application of the TOPK inhibitor in treatment of the gastric cancer, and the TOPK is found to be a potential drug target for treatment of the gastric cancer and shows huge potential in the aspect of enhancing immunotherapy. Results of the application show that when the TOPK inhibitor and the immune checkpoint blocker are combined for use, the treatment effect can be remarkably improved, a new treatment strategy is provided for combined use of targeted therapy and immunotherapy of TOPK positive gastric cancer patients, and meanwhile, a solid foundation is also laid for further research and development in related fields.

Description

Technical Field

[0001] This application belongs to the field of pharmaceutical technology. Specifically, it relates to a drug for treating gastric cancer and its usage regimen. Background Art

[0002] Gastric cancer (GC) is a highly malignant gastric tumor. In recent years, targeted therapy, immunotherapy, and combination therapies have gradually become new directions for GC treatment. Two major molecular biomarkers, HER2 and PD-L1, have been used for the precision treatment of GC. Although new targets such as FGFR2, Claudin-18.2, and VEGFR2 are constantly emerging, their coverage is limited (for example, HER2-positive patients only account for 12% - 23% of GC patients), and the efficacy of related treatment regimens still needs to be improved. PD-L1 is a recognized key molecule for immunotherapy in GC. However, the efficacy of immunotherapy or chemotherapy alone for GC patients is still not ideal. GC cells usually have the ability to proliferate rapidly and can effectively evade the attack of cytotoxic immune cells, resulting in resistance to immunotherapy and accelerating disease progression. For this reason, combination therapy, such as combining anti-PD-1 antibody with HER2 targeted therapy or multi-kinase inhibitors, has brought new hope to some GC patients. However, in order to enhance the effectiveness of immunotherapy, inhibit the rapid proliferation and immune escape ability of GC, it is still necessary to develop key bifunctional targets that can simultaneously promote proliferation and mediate immune resistance.

[0003] T-lymphokine-activated killer cell-originated protein kinase (TOPK), also known as PDZ-binding kinase (PBK), is a serine / threonine protein kinase that participates in cell cycle regulation and anti-apoptosis. Multiple cancers, including GC, show high expression of TOPK, and this high expression promotes the proliferation, invasion, metastasis, and survival of cancer cells. Therefore, TOPK is considered a very promising therapeutic target. Currently, some small molecule drugs such as OTS964 and OTS514 have been proven to specifically antagonize TOPK and have a significant inhibitory effect on tumor growth. More importantly, TOPK is related to the infiltration of immune cells in the tumor microenvironment, although its mechanism and therapeutic value are still unclear. JAK2 is a key mediator in the upstream pathway of IFN-γ and can phosphorylate and activate TOPK, thus promoting the development of Burkitt Lymphoma, which indicates that there may be a potential connection between TOPK and IFN-γ stimulation.

[0004] IFN-γ is a key cytokine secreted by cytotoxic immune cells in the tumor microenvironment and plays an important role in eliminating cancer cells in various cancers. IFN-γ plays a dual role in GC, which can both inhibit and enhance tumor cells. Under the stimulation of IFN-γ, GC cells may acquire adaptive immune resistance, inhibit the cytotoxicity of immune cells, and promote their own proliferation and metastasis. In addition, the mechanism of IFN-γ-induced immune checkpoints (including PD-L1) is crucial in immune surveillance escape. The translation efficiency (TE) of STAT1 mediated by eIF4F can increase the surface level of PD-L1 under the stimulation of IFN-γ, and this process is blocked by the intervention of eIF4A1. Generally, the components of the eIF4F complex are activated under IFN-γ conditions and play a key role in tumor immune escape by controlling the translation of immune checkpoints. Summary of the Invention

[0005] Aiming at the problems existing in the prior art, the present application aims to determine a key bifunctional target that can both inhibit proliferation and inhibit the immune escape mediated by PD-L1 and IDO1.

[0006] Specifically, the present application relates to the following aspects:

[0007] 1. Use of a TOPK inhibitor in the treatment of gastric cancer.

[0008] 2. Use of a TOPK inhibitor in the preparation of a drug for the treatment of gastric cancer.

[0009] 3. Use of a TOPK inhibitor in enhancing the therapeutic effect of an immune checkpoint inhibitor on gastric cancer.

[0010] 4. Use of a TOPK inhibitor in the preparation of an enhancer for enhancing the therapeutic effect of an immune checkpoint inhibitor on gastric cancer.

[0011] 5. Use of an immune checkpoint inhibitor in enhancing the therapeutic effect of a TOPK inhibitor on gastric cancer.

[0012] 6. Use of an immune checkpoint inhibitor in the preparation of an enhancer for enhancing the therapeutic effect of a TOPK inhibitor on gastric cancer.

[0013] 7. Use of a TOPK inhibitor and an immune checkpoint inhibitor in the treatment of gastric cancer.

[0014] 8. Use of a TOPK inhibitor and an immune checkpoint inhibitor in the preparation of a drug for the treatment of gastric cancer.

[0015] 9. The use according to any one of items 1 to 8, wherein the TOPK inhibitor is selected from compounds, antisense molecules, ribozymes, RNAi molecules, or low molecular weight organic molecules, preferably selected from OTS964 or OTS514.

[0016] 10. Use according to any one of items 3-9, wherein the immune checkpoint inhibitor target includes at least one of PD-L1, PD-1, and CTLA-4 involved in immunosuppressive signals.

[0017] 11. Use according to item 10, wherein the immune checkpoint inhibitor is selected from compounds, antibodies, antibody fragments or fusion polypeptides (such as Fc fusions, such as CTLA4-Fc), antisense molecules, ribozymes or RNAi molecules, or low molecular weight organic molecules.

[0018] 12. A kit, which comprises a TOPK inhibitor and an immune checkpoint inhibitor.

[0019] 13. The kit according to item 12, wherein the TOPK inhibitor is selected from compounds, antisense molecules, ribozymes, RNAi molecules, or low molecular weight organic molecules, preferably selected from OTS964 or OTS514.

[0020] 14. The kit according to item 12 or 13, wherein the immune checkpoint inhibitor target includes at least one of PD-L1, PD-1, and CTLA-4 involved in immunosuppressive signals.

[0021] 15. The kit according to any one of items 12-14, wherein the immune checkpoint inhibitor is selected from compounds, antibodies, antibody fragments or fusion polypeptides (such as Fc fusions, such as CTLA4-Fc), antisense molecules, ribozymes, RNAi molecules, or low molecular weight organic molecules.

[0022] Beneficial effects:

[0023] Through genome-wide CRISPR-Cas9 screening, this application for the first time discovers that TOPK is a key regulator of PD-L1 in GC under IFN-γ stimulation. TOPK has potential value in enhancing immunotherapy by regulating the eIF4A1-STAT1-PD-L1 / IDO1 signaling axis and is a potentially druggable target for treating GC.

[0024] This application discovers that TOPK has dual functions: regulating the cell cycle in the nucleus and regulating protein translation in the cytoplasm. TOPK inhibitors can block the adaptive expression of IFN-γ-induced PD-L1 and IDO1 by inhibiting the phosphorylation of components of the eIF4F complex (including eIF4A1), thereby enhancing the cytotoxicity of immune cells and weakening the immune escape ability of GC cells.

[0025] This application discovers that the combined use of TOPK inhibitors and immune checkpoint blockers can significantly enhance the sensitivity of GC cells to treatment, providing a new treatment strategy for the combined use of targeted therapy and immunotherapy for TOPK-positive GC patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 shows the results of identifying inhibitors that block IFN-γ-induced PD-L1 by combining CRISPR and compound screening. Figure 1a Shows a CRISPR / Cas9 genome-wide screen for targets that mediate IFN-γ-induced overexpression of PD-L1 (CD274) in gastric cancer cells (NCI-N87) based on the MAGeCK-VISPR algorithm. Figure 1b Shows the GO pathway annotation of potential mediators of the IFN-γ-induced PD-L1 pathway in gastric cancer cells (NCI-N87). Figure 1c Shows the sgRNA scores and rankings of targets that mediate IFN-γ-induced PD-L1 expression. Fifty known kinase inhibitors of the top 50 kinases that may mediate the IFN-γ / PD-L1 pathway in gastric cancer cells are annotated in the human protein kinase dendrogram. Figure 1d Shows the inhibitory effects of the top 50 kinase inhibitors (100 nM) on gastric cancer cells (NCI-N87) for 48 hours. In this application, inhibitors with an inhibition rate > 25% were selected. Figure 1e Shows the results of enhanced cytotoxicity of PBMC-T cells against gastric cancer cells in an in vitro real-time monitoring model of double-labeled live cells, that is, co-culture of PBMC-T cells with gastric cancer cells (NCI-N87). Figure 1f Shows the percentage of inhibition of PBMC-T cell cytotoxicity by co-culturing kinase inhibitors (100 nM) with gastric cancer cells (NCI-N87) for 48 hours. In this application, inhibitors with cytotoxicity > 90% were selected. Figure 1g Shows a Venn diagram of the intersection (OTS964, OTS514) of the screening results of kinase inhibitors (100 nM). Figure 1h Shows that OTS964 (50 nM) reduced the membrane PD-L1 protein level in IFN-γ-induced gastric cancer cells (NUGC3, SNU1, MKN28, MGC803, MKN45). Figure 1i Shows that TOPK knockdown (TOPK-KD) inhibited the overexpression of membrane PD-L1 induced by IFN-γ. The dotted line represents the mean fluorescence intensity (MFI) of the negative control (NC) of the IFN-γ group. Figure 1j Shows that TOPK overexpression promoted the overexpression of membrane PD-L1 induced by IFN-γ. In Figures 1a - 1c , Figures 1h - 1j , gastric cancer cells were treated with 10 ng / ml IFN-γ for 48 hours to simulate IFN-γ-induced conditions.

[0027] Figure 2 shows the results of effective inhibition of gastric cancer proliferation by protein kinase TOPK inhibitors. Figure 2a Shows the growth inhibition curves of gastric cancer cells treated with OTS964 in a dose- and time-dependent manner, where the time-dependent inhibitory effect was detected at OTS964 (50 nM). Figure 2b Shows the growth inhibition curves of gastric cancer cells treated with OTS514 in a dose- and time-dependent manner, where the time-dependent inhibitory effect was detected at OTS514 (50 nM). Figure 2c and Figure 2d Shows that in the CFU experiment, OTS964 effectively inhibited the colony formation of gastric cancer cells, where Figure 2c are the detection results for 48 hours. Figure 2e Shows that in the CFU experiment, it was detected at 48 hours that OTS964 effectively induced apoptosis of gastric cancer cells. Figure 2f Shows that OTS964 induced cell cycle arrest of gastric cancer cells at the G2 / M phase. Figure 2g Shows that OTS964 disrupted the mitochondrial membrane potential. Gastric cancer cells were treated with 10 ng / ml IFN-γ for 48 hours to simulate IFN-γ induction conditions, and OTS964 was treated with 50 nM for 48 hours. Figure 2h Shows that OTS964 and OTS514 reduced the size of tumor spheroids and their 3D viability. OTS964 and OTS514 were treated with 50 nM for 48 hours. Figure 2i Shows that OTS964 effectively inhibited tumor growth in BALB / c nude mice. *P < 0.05, **P < 0.01, ***P < 0.001.

[0028] Figure 3 shows the results of protein kinase TOPK promoting the proliferation, invasion, and metastasis of gastric cancer. Figure 3a Shows that in the real-time monitoring model, TOPK expression affects the proliferation of gastric cancer cells. Figure 3b and Figure 3c Shows that TOPK expression affects the formation and 3D viability of tumor spheroids of gastric cancer cells (SGC7901, BGC823, NCI-N87, and MFC) at 72 hours. Figure 3d Shows the results of Edu staining and TUNEL experiments on the proliferation of gastric cancer cells at 48 hours under conditions of regulating TOPK expression. Figure 3e Shows that it was detected at 48 hours that TOPK expression affects the colony formation of gastric cancer cells. Figure 3f and Figure 3g Shows that TOPK expression affects the scratch healing, migration, and invasion of gastric cancer cells. Figure 3h Shows that TOPK expression affects the growth of subcutaneous cell xenograft tumors in BALB / c nude mice (n = 5). Figure 3iIt is shown that TOPK expression affects the lung metastasis and growth of gastric cancer cells (SGC7901) in BALB / c nude mice (n = 6). *P < 0.05, **P < 0.01, ***P < 0.001.

[0029] Figure 4 shows the results of TOPK-mediated IFN-γ-induced PD-L1 and IDO1 expression. Figure 4a It is shown that in the ERP107734 database, patients with better efficacy of immune checkpoint therapy have higher TOPK expression. The combined group of TOPK and PD-1 expression (TOPK + PD-1) shows an increased area under the curve (AUC) for predicting the efficacy of anti-PD-1 therapy. Figure 4b It is shown that IFN-γ treatment for 48 hours induces the overexpression of STAT1, PD-L1, IDO1, and phosphorylated proteins p-TOPK-Tyr-74 and p-STAT1-Tyr-74. Figure 4c It is shown that dose-gradient IFN-γ induces the overexpression of membrane PD-L1 within 48 hours. The dotted line represents the MFI of the control group. Figure 4d It is shown that TOPK knockdown inhibits the overexpression of total STAT1, PD-L1, and IDO1 proteins under the induction of 10 ng / ml IFN-γ. Figure 4e It is shown that TOPK knockdown inhibits the overexpression of membrane PD-L1 and cytoplasmic IDO1 in gastric cancer cells under the induction of 10 ng / ml IFN-γ. Figure 4f It is shown that TOPK knockdown inhibits the expression of L-kynurenine under the conditions of IFN-γ (10 ng / ml) and L-tryptophan (100 uM). Figure 4g It is shown that after TOPK knockdown, the cytotoxicity of PBMC-T cells against gastric cancer cells is significantly enhanced within 48 hours. Figure 4h It is shown that after TOPK overexpression, the cytotoxicity of PBMC-T cells against gastric cancer cells is reduced within 48 hours. Figure 4i It is shown that under the induction of 10 ng / ml IFN-γ, TOPK expression in gastric cancer cells (green) affects the phagocytosis of tumor spheroids by macrophages (orange) within 48 hours. Figure 4j It is shown that under the induction of 10 ng / ml IFN-γ, TOPK expression in gastric cancer cells (blue) affects the killing activity of NK cells (purple) against tumor spheroids within 48 hours. Figure 4k It is shown that TOPK knockdown inhibits the growth of MFC derived from 615 mice in vivo. In Figures 4d - 4f 、 Figures 4i - 4j Gastric cancer cells are treated with 10 ng / ml IFN-γ for 48 hours to simulate the IFN-γ induction condition. *P < 0.05, **P < 0.01, ***P < 0.001.

[0030] Figure 5 shows that TOPK enhances the translation of STAT1 mRNA by phosphorylating components of the eIF4F complex. Figure 5a Show the results of differential domain analysis of proteins affected by TOPK phosphorylation. Figure 5b Show the co-localization results of TOPK and eIF4A1 in gastric cancer cells. Figure 5c Show the molecular docking model diagram of TOPK and eIF4A1. Figure 5d Show the immunoprecipitation results of TOPK and pan-phosphorylated serine / threonine proteins. Knockdown of TOPK inhibited the phosphorylation level of eIF4A1. Figure 5e Show the TOPK phosphorylation site scores and rankings of eIF4A and components of the eIF4F complex predicted based on the substrate specificity map of the human kinome. Figure 5f Show the predicted phosphorylation interaction network of TOPK and components of the eIF4F complex. Figure 5g Show that inhibiting the function of eIF4A1 with silvestrol can block the overexpression of membrane PD-L1 induced by IFN-γ in gastric cancer cells. The dotted line represents the MFI of the DMSO (added IFN-γ) group. Figure 5h Show that inhibiting the function of eIF4A1 with silvestrol can block the overexpression of total STAT1, PD-L1, and IDO1 induced by IFN-γ in gastric cancer cells. Figure 5i Show the nine-quadrant diagram of differential RPFs obtained by Ribo-seq and mRNA expression obtained by RNA-seq in TOPK-knockdown SGC7901 cells (n = 3) compared with negative control (NC) cells (n = 4).

[0031] Figure 5j Show that knockdown of TOPK reduces the TE of STAT1 in SGC7901 and BGC823 as confirmed by Western blot and qPCR. Figure 5k Show that under IFN-γ induction conditions, ribosome profiling found that knockdown of TOPK promoted the reduction of STAT1 mRNA in polysomes in SGC7901 cells (TOPK-KD1), and the mRNA levels of IDO1 and PD-L1 were only partially affected, while the TOPK mRNA level was not affected. In Figure 5d 、 Figures 5g - 5k Gastric cancer cells were treated with 10 ng / ml IFN-γ for 48 hours to simulate IFN-γ induction conditions. *P < 0.05, **P < 0.01, ***P < 0.001.

[0032] Figure 6 shows the results of the TOPK inhibitor OTS964 blocking IFN-γ-induced PD-L1 and IDO1 expression. Figure 6aIt was shown that OTS964 reduced the overexpression of total STAT1, PD-L1 and IDO1 proteins induced by IFN-γ. The protein expression levels of TOPK and eIF4A1 were not affected. Figure 6b It was shown that OTS964 (50 nM) reduced the phosphorylation levels of proteins including p-eIF4B (Ser422), p-eIF4E (Ser209), p-4EBP1 (Thr37 / 46), p-STAT1 (Tyr701) in gastric cancer cells. Figure 6c It was shown that OTS964 inhibited the expression of L-kynurenine under the conditions of IFN-γ (10 ng / ml) and L-tryptophan (100 μM). Figure 6d It was shown the results of PLA analysis of the spatial proximity interaction between TOPK and eIF4A1 in gastric cancer cells. Under the condition of IFN-γ induction, positive interactions (red) between TOPK and eIF4A1 were observed in SGC7901 and BGC823 cells. Figure 6e It was shown that under the condition of IFN-γ induction, OTS964 inhibited the enrichment of STAT1 mRNA in polysomes by ribosome analysis, while had no effect on TOPK and GAPDH mRNAs. Figure 6f It was shown that at different effector cell to target cell ratios (PBMC-T:SGC7901), the cell index of RTCA changed with the time gradient. Figure 6g It was shown the RTCA cell index. OTS964 synergistically promoted the cytotoxicity of PBMC-T against gastric cancer cells (PBMC-T:SGC7901 = 5:1). Figure 6h It was shown that OTS964 enhanced the cytotoxicity of PBMC-T cells against BGC823 and NCI-N87 (N87-Flag) with overexpressed TOPK in vitro within 48 hours. Figure 6i It was shown that OTS964 inhibited the growth of subcutaneous cell allografts in 615 mice (n = 6). Figure 6j It was shown the analysis results of metabolites of the tryptophan metabolic pathway in vivo treated with OTS964. OTS964 increased the level of L-tryptophan and decreased the level of L-kynurenine in gastric cancer tumors (n = 4). Figure 6k It was shown the OPLS-DA plot, the x-axis represents the covariance between the principal component and the metabolite, and the y-axis represents the correlation coefficient between the principal component and the metabolite. Metabolites close to the upper right and lower left corners indicate more significant differences. Red dots represent metabolites with variable importance in projection (VIP) values greater than 1, while green dots represent metabolites with VIP values less than or equal to 1. In Figures 6a - 6e , gastric cancer cells were treated with 10 ng / ml IFN-γ for 48 hours to simulate the IFN-γ induction condition; in Figures 6b - 6e , Figures 6g - 6kIn this case, OTS964 was treated at 50 nM for 48 hours. *P < 0.05.

[0033] Figure 7 shows the results of the combined use of TOPK inhibitor and immune checkpoint inhibitor for the treatment of gastric cancer. Figure 7a It shows that in the real-time monitoring model, when PBMC-T cells were co-cultured with BGC823 cells or NCI-N87 (N87-Flag) cells overexpressing TOPK, the combined use of OTS964 (50 nM) and anti-CTLA-4 antibody showed a synergistic effect in enhancing PBMC-T cell cytotoxicity and inhibiting cell growth. Anti-CTLA-4 antibody or isotype control antibody: 100 nM. Figure 7b It shows that in the real-time monitoring model, when PBMC-T cells were co-cultured with BGC823 cells or NCI-N87 (N87-Flag) cells overexpressing TOPK, the combined use of OTS964 (50 nM) and anti-PD-1 antibody showed a synergistic effect in enhancing PBMC-T cell cytotoxicity and inhibiting cell growth. Anti-PD-1 antibody or isotype control antibody: 20 nM. Figure 7c It shows that in the real-time monitoring model, when PBMC-T cells were co-cultured with BGC823 cells or NCI-N87 (N87-Flag) cells overexpressing TOPK, the combined use of OTS964 (50 nM) and anti-CTLA-4 and anti-PD-1 antibodies showed a synergistic effect in enhancing PBMC-T cell cytotoxicity and inhibiting cell growth. Anti-CTLA-4 antibody or isotype control: 100 nM; anti-PD-1 antibody or isotype control: 20 nM. Figure 7d It shows that in the real-time monitoring model, when PBMC-T cells were co-cultured with BGC823 cells or NCI-N87 (N87-Flag) cells overexpressing TOPK, the combined use of OTS964 (50 nM) and bispecific anti-PD-1 / CTLA-4 antibody (cadonilimab) showed a synergistic effect in increasing PBMC-T cell cytotoxicity and inhibiting cell growth. Bispecific anti-PD-1 / CTLA-4 antibody or isotype control: 50 nM. Figure 7e It shows that in the co-culture model, OTS964 (50 nM) alone or in combination with an antibody significantly increased the secretion of GZMB or perforin by PBMC-T cells. Figure 7f It shows that in the co-culture model, OTS964 (50 nM) alone or in combination with an antibody significantly increased the secretion of TNF-β. Figure 7g It shows that OTS964 alone or in combination with anti-CTLA-4 antibody or anti-PD-1 antibody synergistically inhibited tumor growth in 615 mice. Figure 7hIt was shown that immunohistochemical staining revealed that the combination of OTS964 with anti-CTLA-4 antibody or anti-PD-1 antibody decreased the production of L-kynurenine. Figure 7i It was shown that multi-color flow cytometry assays revealed that OTS964 alone or in combination with anti-CTLA-4 or anti-PD-1 antibody increased the infiltration of immune cells including NK cells, NKT cells, CD4 + or CD8 + T cells, and conventional dendritic cells (cDC), increased the allograft M1 / M2 macrophage ratio, and decreased the numbers of CD25 + regulatory T cells (Treg) or myeloid-derived suppressor cells (MDSC). *P<0.05, **P<0.01, ***P<0.001. Detailed implementation manners

[0034] The present application will be further described below in conjunction with embodiments. It should be understood that the embodiments are only used to further illustrate and explain the present application and are not used to limit the present application.

[0035] Unless otherwise defined, the technical and scientific terms in this specification have the same meanings as those commonly understood by those skilled in the art. Although methods and materials similar or equivalent to those described herein can be used in experiments or practical applications, the materials and methods are described below. In case of conflict, the present specification, including its definitions, shall prevail. Additionally, the materials, methods, and examples are for illustrative purposes only and are not restrictive. The present application will be further described below in conjunction with specific embodiments, but not to limit the scope of the present application.

[0036] Definition

[0037] As used herein, the term "immune checkpoint inhibitor" refers to an antagonist of an inhibitory or co-inhibitory immune checkpoint. The terms "immune checkpoint inhibitor", "checkpoint inhibitor", and "CPI" are used interchangeably herein. Immune checkpoint inhibitors can antagonize inhibitory or co-inhibitory immune checkpoints by interfering with receptor-ligand binding and / or altering receptor signaling. Examples of immune checkpoints (ligands and receptors) that can be antagonized, some of which are selectively upregulated in various types of cancer cells, include: PD-1 (programmed cell death protein 1); PD-L1 (PD-1 ligand); BTLA (B and T lymphocyte attenuator); CTLA-4 (cytotoxic T lymphocyte-associated antigen 4); TIM-3 (T cell immunoglobulin and mucin domain-containing protein 3); LAG-3 (lymphocyte activation gene 3); TIGIT (T cell immunoreceptor with Ig and ITIM domains); CD276 (B7-H3), PD-L2, galectin-9, CEACAM-1, BTLA, CD69, galectin-1, CD113, GPR56, VISTA, 2B4, CD48, GARP, PD1H, LAIR1, TIM-1, and TIM-4, as well as killer inhibitory receptors, which can be divided into two classes based on their structural characteristics: i) killer cell immunoglobulin-like receptors (KIR), and ii) C-type lectin receptors (members of the type II transmembrane receptor family). Immune checkpoint inhibitors encompass compounds that inhibit the activity or control the mechanisms of the immune system.

[0038] The "Programmed Death-1 (PD-1)" receptor refers to an immunosuppressive receptor belonging to the CD28 family. PD-1 is mainly expressed on previously activated T cells in the body and binds to two ligands, PD-L1 (also known as B7-H1 or CD274) and PD-L2 (also known as B7-DC or CD273). The term "PD-1" as used herein includes human PD-1 (hPD-1), variants, isotypes, and species homologs of hPD-1, as well as analogs having at least one common epitope with hPD-1. "Programmed Death Ligand-1 (PD-L1)" is one of the two cell surface glycoprotein ligands of PD-1 (the other being PD-L2), which downregulates T cell activation and cytokine secretion after binding to PD-1. The term "PD-L1" as used herein includes human PD-L1 (hPD-L1), variants, isotypes, and species homologs of hPD-L1, as well as analogs having at least one common epitope with hPD-L1. The term "PD-L2" as used herein includes human PD-L2 (hPD-L2), variants, isotypes, and species homologs of hPD-L2, as well as analogs having at least one common epitope with hPD-L2. The ligands of PD-1 (PD-L1 and PD-L2) are expressed on the surfaces of antigen-presenting cells (such as dendritic cells or macrophages) and other immune cells. The binding of PD-1 to PD-L1 or PD-L2 results in the downregulation of T cell activation. Cancer cells expressing PD-L1 and / or PD-L2 can turn off T cells expressing PD-1, which leads to the inhibition of the anti-cancer immune response. The interaction between PD-1 and its ligands results in a reduction in tumor-infiltrating lymphocytes, a decrease in T cell receptor-mediated proliferation, and immune evasion of cancer cells. Immunosuppression can be reversed by inhibiting the local interaction between PD-1 and PD-L1, and this effect is additive when the interaction between PD-1 and PD-L2 is also blocked.

[0039] "Cytotoxic T Lymphocyte Associated Antigen-4 (CTLA-4)" (also known as CD152) is a T cell surface molecule and a member of the immunoglobulin superfamily. This protein downregulates the immune system by binding to CD80 (B7-1) and CD86 (B7-2). As used herein, the term "CTLA-4" includes human CTLA-4 (hCTLA-4), variants, isotypes, and species homologs of hCTLA-4, and analogs having at least one common epitope with hCTLA-4. CTLA-4 is a homolog of the stimulatory checkpoint protein CD28 and has a much higher binding affinity for CD80 and CD86. CTLA4 is expressed on the surface of activated T cells, and its ligands are expressed on the surface of professional antigen-presenting cells. The binding of CTLA4 to its ligands blocks the co-stimulatory signal of CD28 and generates an inhibitory signal. Thus, CTLA-4 downregulates T cell activation.

[0040] As used herein, the term "antibody" is used in the broadest sense and encompasses a variety of antibody structures, including not only intact (i.e., full-length) antibodies, but also antigen-binding fragments thereof (e.g., Fab, Fab’, F(ab’)2, Fv), variants thereof, fusion proteins containing antibody portions, humanized antibodies, chimeric antibodies, diabodies, linear antibodies, single-chain antibodies (scFV), VHH antibodies, multispecific antibodies (e.g., bispecific antibodies), multispecific single-chain antibodies, and any other modified configuration of an immunoglobulin molecule containing an antigen recognition site of the desired specificity, including glycosylation variants of the antibody, amino acid sequence variants of the antibody, and covalently modified antibodies.

[0041] Typically, an intact or full-length antibody comprises two heavy chains and two light chains. Each heavy chain contains a heavy chain variable region (VH) and first, second, and third constant regions (CH1, CH2, CH3). Each light chain contains a light chain variable region (VL) and a constant region (CL), and the light chain constant region includes kappa (κ) or lambda (λ). The full-length antibody can be any type of antibody, such as IgD, IgE, IgG, IgA, or IgM (or subclasses thereof), but the antibody does not need to belong to any particular class. Immunoglobulins can be designated as different classes based on the amino acid sequence of the constant region of the heavy chain. Generally, there are five main classes of immunoglobulins: IgA, IgD, IgE, IgG, and IgM, and several of these classes can be further differentiated into subclasses (isotypes), such as IgG1, IgG2, IgG3, IgG4, IgA1, and IgA2. The heavy chain constant regions corresponding to the different immunoglobulin classes are designated α, δ, ε, γ, and μ, respectively. The subunit structures and three-dimensional structures of different classes of immunoglobulins are well known.

[0042] As used herein, the term "antisense molecule" refers to a DNA or RNA molecule that contains a nucleic acid sequence complementary to the sequence of certain mRNA or a fragment or derivative thereof, which binds or hybridizes to the complementary sequence in the mRNA and inhibits the translation of the mRNA into protein.

[0043] As used herein, the term "ribozyme" refers to an RNA molecule that functions as an enzyme or a molecule composed of a protein containing such an RNA molecule, also referred to as ribonucleic acid enzyme or catalytic RNA. It utilizes an RNA molecule with a defined tertiary structure to carry out chemical reactions and has catalytic or autocatalytic properties. As is well known, some ribozymes can cleave themselves or other RNA molecules to inhibit their activity, and other ribozymes can catalyze the aminotransferase activity of ribosomes. Such ribozymes include hammerhead ribozymes, VS ribozymes, and hairpin ribozymes, etc.

[0044] As used herein, the term "RNAi molecule" refers to an RNA or its analog that has sufficient sequence complementarity to a target RNA to direct RNA interference. In some embodiments, it also includes DNA that can be used to generate RNA. RNA interference (RNAi) refers to a sequence-specific or selective process by which the target molecule (e.g., target gene, protein, or RNA) is downregulated. In some embodiments, the RNAi molecule is a small interfering RNA (siRNA), a short hairpin RNA (shRNA), or a microRNA (miRNA).

[0045] As used herein, the term "siRNA (small interfering RNA)" refers to a short double-stranded RNA that can induce RNAi by cleaving certain mRNA. The siRNA includes a sense RNA strand having a sequence homologous to the mRNA of the target gene and an antisense RNA strand having a sequence complementary to it. The siRNA can inhibit the expression of the target gene and thus can be used for gene knockdown, gene therapy, etc.

[0046] As used herein, the term "shRNA (short hairpin RNA)" is a single-stranded RNA that includes a stem portion and a loop portion that form a double-stranded part through hydrogen bonding. It is processed and transformed into siRNA by proteins such as Dicer and performs the same function as siRNA.

[0047] As used herein, the term "miRNA (microRNA)" refers to 21 to 23 non-coding RNAs that regulate gene expression post-transcriptionally by promoting the degradation of the target RNA or by inhibiting its translation.

[0048] As used herein, the terms "fusion polypeptide" or "fusion protein" generally refer to a polypeptide comprising at least two domains. Generally, a polypeptide containing at least two such domains is considered a fusion polypeptide when the two domains are: (1) not contained in the same peptide in nature, and / or (2) not previously linked or connected to each other in a single polypeptide, and / or (3) have been linked or connected to each other by artificial manipulation. In some embodiments, the fusion polypeptide is an Fc fusion polypeptide, such as a CTLA4-Fc fusion polypeptide.

[0049] As used herein, the term "cancer" (also known as carcinoma) generally refers to any type of malignant neoplasm, i.e., any morphological and / or physiological alteration (based on genetic re-programming) of target cells that shows or has a tendency to develop cancer characteristics compared to unaffected (healthy) wild-type control cells. Examples of such alterations can involve cell size and shape (becoming larger or smaller), cell proliferation (increase in cell number), cell differentiation (change in physiological state), apoptosis (programmed cell death), or cell survival. Thus, the term "gastric cancer" refers to a cancerous growth in the gastric parenchyma. In this document, the terms "gastric cancer" and "GC" can be used interchangeably.

[0050] As used herein, the term "T-LAK cell-originated proteinkinase (TOPK)" (also known as PBK) is an important serine / threonine protein kinase that plays important roles in cell cycle regulation, tumor growth, and immune escape. The abnormal activation of TOPK is closely related to the occurrence and development of various cancers.

[0051] The term "comprising" or "including" should be understood in an open, non-exclusive sense, i.e., "including but not limited to".

[0052] TOPK inhibitor

[0053] This application provides the use of TOPK inhibitors for the treatment of gastric cancer.

[0054] This application provides the use of TOPK inhibitors for the preparation of a medicament for the treatment of gastric cancer.

[0055] The TOPK inhibitors of this application provide a new medicament for the treatment of TOPK-positive GC patients.

[0056] Currently, the actual or potential treatment methods for GC are still limited. According to existing statistical data, HER2 accounts for 12%–23%, CLDN18.2 accounts for 17%–18%, and FGFR1-4 gene abnormalities account for 12%. In this application, the inventors determined TOPK to be a potential therapeutic target for GC through a comprehensive approach of high-throughput CRISPR-Cas9 and compound screening. Through analysis, the inventors found that TOPK was highly expressed in 32.26% (120 out of 372 cases) of GC patients and was significantly expressed in 58.06% of advanced stage IV patients. This result suggests that targeted therapy against TOPK may cover a larger proportion of GC patients and significantly inhibit the malignant progression of tumors.

[0057] Existing studies have shown that there is a lack of systematic research on druggable oncogenic kinases with dual roles in GC. Based on this, in this application, the inventors determined that TOPK has dual roles: regulating the cell cycle in the nucleus and regulating protein translation in the cytoplasm. The inventors found through research that the interaction and phosphorylation of eIF4A1 mediated by TOPK and other components of the eIF4F complex will increase the TE of STAT1 in GC, induce the adaptive overexpression of PD-L1 and IDO1, and lead to immunosuppressive metabolism through PD-L1-mediated immune checkpoint inhibition, IDO1-induced tryptophan depletion, and kynurenine production. This result suggests that TOPK has potential value in enhancing immunotherapy by regulating the eIF4A1-STAT1-PD-L1 / IDO1 signaling axis, indicating that TOPK may be a potential druggable target for the combination of targeted therapy and immunotherapy in the treatment of advanced GC. Further, in this application, the inventors found that TOPK inhibitors can effectively antagonize this process, reshape the tumor immune metabolic microenvironment, and trigger anti-tumor immunity in GC.

[0058] In this application, the TOPK inhibitor refers to a substance that can specifically bind to TOPK, preferably human TOPK, or bind to a polynucleotide or its fragment that binds to TOPK, and inhibit the activity and / or expression of TOPK protein or polynucleotide. The TOPK inhibitor can include, but is not limited to, any compound, protein, fusion protein, antibody, amino acid, peptide, virus, carbohydrate, lipid, nucleic acid, extract, or fraction, as long as it inhibits the activity or expression of TOPK.

[0059] In some embodiments, compared with GC cells not treated with a TOPK inhibitor, the TOPK inhibitor is an inhibitor that reduces the expression of TOPK in GC cells. Reducing the expression of TOPK may refer to a decrease in the mRNA and / or protein produced by the TOPK gene, or the TOPK gene not producing mRNA and / or protein. Inhibitors of TOPK may include, but are not limited to, antisense molecules, RNAi molecules, ribozymes, etc. that bind to the DNA or mRNA of the TOPK gene in a complementary manner.

[0060] In some embodiments, the TOPK inhibitor is an antisense molecule. The antisense molecule can be, for example, an antisense oligonucleotide. The term "antisense oligonucleotide" refers to DNA or RNA or a derivative thereof that contains a nucleic acid sequence complementary to a specific mRNA sequence. In this case, the antisense oligonucleotide can bind to the complementary sequence in the mRNA, thereby inhibiting the translation of the mRNA into protein.

[0061] In some embodiments, the TOPK inhibitor is an RNAi molecule. The RNAi molecule can be selected from, for example, siRNA, shRNA, or miRNA.

[0062] Antisense molecules, RNAi molecules, ribozymes, etc. that bind complementarily to the DNA or mRNA of the TOPK gene can inhibit the translation of the TOPK mRNA, inhibit the transport, maturation of TOPK into the cytoplasm, or inhibit any other activity crucial for the biological function of TOPK.

[0063] In some embodiments, compared with GC cells not treated with a TOPK inhibitor, the TOPK inhibitor is an inhibitor that inactivates the function of TOPK or reduces its activity in GC cells. The TOPK inhibitor may include, but is not limited to, compounds that specifically bind to TOPK, low molecular weight organic molecules, peptides, peptidomimetics, fusion proteins, antibodies, aptamers, etc.

[0064] Wherein, the term "peptidomimetic" means a peptide-like molecule having the activity of the peptide on which its structure is based. Such peptidomimetics include chemically modified peptides, peptide-like molecules containing non-naturally occurring amino acids, and peptoids, and have activities such as those of the peptidomimetics derived therefrom (for example, see Goodman and Ro, Peptidomimetics for Drug Design, "Burger's Medicinal Chemistry and Drug Discovery" Vol. 1 (ed. M.E. Wolff; John Wiley & Sons 1995), pp. 803-861).

[0065] As used herein, the term "aptamer" refers to single-stranded nucleic acids (DNA, RNA, or modified nucleic acids) that have a stable tertiary structure and are capable of binding to a target molecule with high affinity and specificity.

[0066] As used herein, the term "low molecular weight organic molecule" generally refers to organic compounds with a low molecular weight (<1000 daltons).

[0067] In some embodiments, the TOPK inhibitor is OTS964 or OTS514.

[0068] In the present application, the TOPK inhibitor can be used in any manner and by any means known in the art. The manner and means of use will depend on the type of immune checkpoint inhibitor to be used.

[0069] TOPK inhibitor and immune checkpoint inhibitor

[0070] In the present application, the applicant has found that the combination of a TOPK inhibitor and an immune checkpoint inhibitor can produce a synergistic effect in killing GC cells. On the one hand, the TOPK inhibitor weakens the intrinsic viability of cancer cells; on the other hand, the immune checkpoint inhibitor enhances the ability of immune cells to recognize and kill cancer cells. This dual mechanism of action significantly improves the therapeutic effect and overcomes the problem of drug resistance in single therapy, providing a new treatment strategy for the combined use of targeted therapy and immunotherapy for TOPK-positive GC patients.

[0071] The present application provides the use of the above TOPK inhibitor for enhancing the therapeutic effect of an immune checkpoint inhibitor in the treatment of gastric cancer.

[0072] The present application provides the use of the above TOPK inhibitor for preparing an enhancer for enhancing the therapeutic effect of an immune checkpoint inhibitor in the treatment of gastric cancer.

[0073] The present application provides the use of an immune checkpoint inhibitor for enhancing the therapeutic effect of the above TOPK inhibitor in the treatment of gastric cancer.

[0074] The present application provides the use of an immune checkpoint inhibitor for preparing an enhancer for enhancing the therapeutic effect of a TOPK inhibitor in the treatment of gastric cancer.

[0075] The present application provides the use of the above TOPK inhibitor and an immune checkpoint inhibitor for the treatment of gastric cancer.

[0076] The present application provides the use of the above TOPK inhibitor and an immune checkpoint inhibitor for preparing a medicament for the treatment of gastric cancer.

[0077] Among them, the immune checkpoint inhibitor can be used in any manner and through any route known in the art. The manner and route of use will depend on the type of immune checkpoint inhibitor to be used.

[0078] In some embodiments, the immune checkpoint inhibitor targets include at least one of PD-L1, PD-1, and CTLA-4 involved in immunosuppressive signals. For example, one, two, or all three of PD-L1, PD-1, and CTLA-4 are involved. In some embodiments, the immune checkpoint inhibitor target is PD-1. In some embodiments, the immune checkpoint inhibitor target is CTLA-4. In some embodiments, the immune checkpoint inhibitor target is PD-1 and CTLA-4.

[0079] This application is not intended to limit the immune checkpoint inhibitor targets. Those skilled in the art can understand that other targets can also be targeted by immune checkpoint inhibitors, provided that such targeting results in the stimulation of an immune response, such as an anti-tumor immune response, as reflected in an increase in T cell proliferation, enhanced T cell activation, etc.

[0080] In some embodiments, the immune checkpoint inhibitor is selected from compounds, antibodies, antibody fragments or fusion polypeptides, antisense molecules, ribozymes, RNAi molecules, or low molecular weight organic molecules.

[0081] Among them, the fusion polypeptide can be, for example, an Fc fusion polypeptide, such as CTLA-4-Fc.

[0082] Among them, the antisense molecule can be, for example, an antisense oligonucleotide.

[0083] Among them, the RNAi molecule can be selected from, for example, siRNA, shRNA, or miRNA.

[0084] In some embodiments, the immune checkpoint inhibitor blocks inhibitory signals related to immune checkpoints. In some embodiments, the immune checkpoint inhibitor is an antibody or a fragment thereof that disrupts the inhibitory signal transduction related to immune checkpoints. In some embodiments, the immune checkpoint inhibitor is a compound or a low molecular weight organic molecule that disrupts the inhibitory signal transduction. In some embodiments, the immune checkpoint inhibitor is a peptide-based inhibitor that disrupts the inhibitory signal transduction. In some embodiments, the immune checkpoint inhibitor is an antisense oligonucleotide, siRNA, shRNA, or miRNA that disrupts the inhibitory signal transduction.

[0085] In some embodiments, the immune checkpoint inhibitor is an antibody, a fragment thereof, or an antibody mimetic that blocks the interaction between checkpoint inhibitor proteins, such as an antibody or a fragment thereof that blocks the interaction between PD-1 and PD-L1 or PD-L2. In some embodiments, the immune checkpoint inhibitor is an antibody or a fragment thereof that blocks the interaction between CTLA-4 and CD80 or CD86.

[0086] As described herein, inhibiting or blocking inhibitory immune checkpoint signaling prevents or reverses immunosuppression and establishes or enhances cellular immunity. In some embodiments, inhibition of immune checkpoint signal transduction reduces or inhibits immune system dysfunction. In some embodiments, inhibition of immune checkpoint signaling reduces the degree of immune cell dysfunction.

[0087] Wherein the term "dysfunction" refers to immune cells that are in a state of reduced immune responsiveness to antigen stimulation. Dysfunction includes unresponsiveness to antigen recognition and impaired ability to convert antigen recognition into downstream T cell effector functions, such as proliferation, cytokine production (e.g., IL-2), and / or target cell killing.

[0088] In some embodiments, the immune checkpoint inhibitor target is PD-1, and the immune checkpoint inhibitor is an anti-PD-1 antibody. Non-limiting examples of the anti-PD-1 antibody include: Nivolumab, Pembrolizumab, MEDI-0680, PDR001 (Spartalizumab), REGN2810 (Cemiplimab), BGB-108, Iparomlimab, Camrelizumab, Sintilimab, Tislelizumab, Toripalimab, Dostarlimab, Retifanlimab, Sasanlimab, Penpulimab, CS1003, HLX10, SCT-I10A, Cindilimab, Balstilimab, Genolimzumab, BI 754091, YBL-006, BAT1306, HX008, Cemiplimab, Budigalimab, AMG 404, CX-188, JTX-4014, 609A, Sym021, LZM009, F520, SG001, AM0001, ENUM 244C8. In some embodiments, the immune checkpoint inhibitor is Pembrolizumab.

[0089] In some embodiments, the immune checkpoint inhibitor target is CTLA-4, and the immune checkpoint inhibitor is an anti-CTLA-4 antibody. Non-limiting examples of the anti-CTLA-4 antibody include: Ipilimumab, L3D10, Tremelimumab, Zalifrelimab, IBI310. In some embodiments, the immune checkpoint inhibitor is Ipilimumab. In some embodiments, the immune checkpoint inhibitor is Tremelimumab.

[0090] In some embodiments, the immune checkpoint inhibitor targets are PD-1 and CTLA-4, and the immune checkpoint inhibitors are anti-PD-1 antibodies and anti-CTLA-4 antibodies. In some embodiments, the immune checkpoint inhibitors are Nivolumab and Ipilimumab, Pembrolizumab and Ipilimumab, Spartalizumab and Tremelimumab, Tislelizumab and Ipilimumab, Sintilimab and Ipilimumab, Toripalimab and Ipilimumab, or Camrelizumab and Ipilimumab.

[0091] In some embodiments, the immune checkpoint inhibitor targets are PD-1 and CTLA-4, and the immune checkpoint inhibitor is a bispecific PD-1 / CTLA-4 antibody. Non-limiting examples of bispecific PD-1 / CTLA-4 antibodies include: Lorigerlimab, MEDI5752, vudalimab, cadonilimab. In some embodiments, the immune checkpoint inhibitor is cadonilimab.

[0092] Pharmaceutical composition, kit

[0093] The present application provides a pharmaceutical composition, which comprises the above-mentioned TOPK inhibitor and the above-mentioned immune checkpoint inhibitor.

[0094] In some embodiments, the TOPK inhibitor is OST964.

[0095] In some embodiments, the immune checkpoint inhibitor target is PD-1, and the immune checkpoint inhibitor is an anti-PD-1 antibody. In some embodiments, the immune checkpoint inhibitor is Pembrolizumab.

[0096] In some embodiments, the immune checkpoint inhibitor target is CTLA-4, and the immune checkpoint inhibitor is Ipilimumab.

[0097] In some embodiments, the immune checkpoint inhibitor targets are PD-1 and CTLA-4, and the immune checkpoint inhibitors are anti-PD-1 antibodies and anti-CTLA-4 antibodies. In some embodiments, the immune checkpoint inhibitors are Nivolumab and Ipilimumab, Pembrolizumab and Ipilimumab, Spartalizumab and Tremelimumab, Tislelizumab and Ipilimumab, Sintilimab and Ipilimumab, Toripalimab and Ipilimumab, or Camrelizumab and Ipilimumab.

[0098] In some embodiments, the immune checkpoint inhibitor targets are PD-1 and CTLA-4, and the immune checkpoint inhibitor is a bispecific PD-1 / CTLA-4 antibody. In some embodiments, the immune checkpoint inhibitor is cadonilimab.

[0099] In some embodiments, the pharmaceutical composition further comprises a pharmaceutically acceptable carrier.

[0100] As used herein, the term "pharmaceutically acceptable carrier" is intended to include any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic agents, and absorption delaying agents, etc. that are compatible with the administration of the drug. The use of such media and agents for pharmaceutically active substances is well known in the art. Unless in any case where any conventional medium or agent is incompatible with the active compound, their use in these compositions is encompassed. Pharmaceutically acceptable carriers include diluents, fillers, salts, buffers, stabilizers, solubilizers, protectants, osmotic pressure regulators, and other materials well known in the art. Exemplary pharmaceutically acceptable carriers are described in U.S. Patent No. 5,211,657, and other carriers are known to those skilled in the art. Such formulations generally may contain salts, buffers, preservatives, compatible carriers, and optionally other therapeutic agents. When used in medicine, the salt should be pharmaceutically acceptable, but non-pharmaceutically acceptable salts can be conveniently used to prepare their pharmaceutically acceptable salts, without excluding them from the scope of the present invention. Such pharmacologically and pharmaceutically acceptable salts include, but are not limited to, salts prepared from the following acids: hydrochloric acid, hydrobromic acid, sulfuric acid, nitric acid, phosphoric acid, maleic acid, salicylic acid, citric acid, formic acid, malonic acid, succinic acid, etc. In addition, pharmaceutically acceptable salts can be prepared as alkali metal salts or alkaline earth metal salts, such as sodium salts, potassium salts, or calcium salts.

[0101] The present application provides a kit, which comprises the above-mentioned TOPK inhibitor and the above-mentioned immune checkpoint inhibitor.

[0102] Among them, the TOPK inhibitor and the immune checkpoint inhibitor can be present in the container of the kit in a mixture or in a separate form. In some embodiments, the kit includes: (1) a first container containing the TOPK inhibitor; (2) a second container containing the immune checkpoint inhibitor.

[0103] In some embodiments, the TOPK inhibitor is OST964.

[0104] In some embodiments, the target of the immune checkpoint inhibitor is PD-1, and the immune checkpoint inhibitor is an anti-PD-1 antibody. In some embodiments, the immune checkpoint inhibitor is Pembrolizumab.

[0105] In some embodiments, the target of the immune checkpoint inhibitor is CTLA-4, and the immune checkpoint inhibitor is Ipilimumab.

[0106] In some embodiments, the targets of the immune checkpoint inhibitor are PD-1 and CTLA-4, and the immune checkpoint inhibitor is an anti-PD-1 antibody and an anti-CTLA-4 antibody. In some embodiments, the immune checkpoint inhibitor is Nivolumab and Ipilimumab, Pembrolizumab and Ipilimumab, Spartalizumab and Tremelimumab, Tislelizumab and Ipilimumab, Sintilimab and Ipilimumab, Toripalimab and Ipilimumab, or Camrelizumab and Ipilimumab.

[0107] In some embodiments, the targets of the immune checkpoint inhibitor are PD-1 and CTLA-4, and the immune checkpoint inhibitor is a bispecific PD-IPD-1 / CTLA-4 antibody. In some embodiments, the immune checkpoint inhibitor is cadonilimab.

[0108] In some embodiments, the kit further includes an instruction manual that describes a method for combining the TOPK inhibitor and the immune checkpoint inhibitor for treating GC.

[0109] The present application also provides the use of the above-mentioned pharmaceutical composition and the above-mentioned kit in the treatment of gastric cancer.

[0110] Examples

[0111] The following will illustrate the content of this application in combination with specific embodiments, but the scope of this application is not limited thereto. Unless otherwise specified, the reagents and instruments used in the following embodiments are all conventional reagents and instruments in the art and can be obtained through commercial purchase. The methods used are all conventional experimental methods, and those skilled in the art can undoubtedly implement the described solutions and obtain corresponding results according to the content of the embodiments. All experiments were independently repeated at least three times in vitro and at least five times in vivo.

[0112] The nucleotides involved in the embodiments are as follows:

[0113] Table 1 Nucleotide sequences involved in this application

[0114]

[0115]

[0116] Sources of key vectors involved in the embodiments:

[0117] Table 2 Vectors involved in this application

[0118]

[0119]

[0120] Sources of key antibodies involved in the embodiments:

[0121] Table 3 Antibodies involved in this application

[0122]

[0123]

[0124]

[0125] The key reagents involved in the embodiments are as follows:

[0126] Table 4 Reagents involved in this application

[0127]

[0128]

[0129]

[0130]

[0131] The specific steps of some experimental operations involved in the embodiments are as follows:

[0132] Cell line selection, cell culture, transfection, and gene editing

[0133] The following cell lines were used in this application: SGC7901, SNU1, NUGC3, MKN28, MFC, MGC803, BGC823, MKN45, NCI-N87, and CT26. Among them, the SNU1, SNU16, MFC, NCI-N87, and CT26 cell lines (derived from the Shanghai Institute of Cell Biology, Chinese Academy of Sciences); the NUGC3, MKN28, and MKN45 cell lines (derived from the Japanese Collection of Research Bioresources); the SGC7901, BGC823, and MGC803 cell lines (derived from the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital); the NK-92MI cells (derived from iCell); the THP-1 cells were derived from Abm.

[0134] The cancer cell lines were cultured in DMEM medium (containing 10% FBS and 1% penicillin-streptomycin). The NK-92MI cells were cultured in a specific medium (iCell-h331-001b). The THP-1 cells were cultured in RPMI-1640 medium, and the THP-1 cells were stimulated with 100 ng / ml of PMA to differentiate into macrophages for further research. The NK-92MI cells were cultured in a specific medium (iCell-h331-001b, including MEMα medium, FBS, horse serum, inositol, β-mercaptoethanol, folic acid, penicillin-streptomycin).

[0135] In cell transfection and gene editing experiments, siRNAs (as shown in Table 1) or plasmids (as shown in Table 2) targeting TOPK or negative controls were transfected into cells according to Lipofectamine 2000 (Thermo Fisher Scientific) to construct cells overexpressing TOPK (Flag-TOPK) and corresponding negative control cells (EV), or to construct cells with knockdown of TOPK (TOPK-KD) and corresponding negative control cells (NC).

[0136] CRISPR-Cas9 genome-wide screening

[0137] Experiments combining CRISPR-Cas9 screening and compound screening were performed on gastric cancer cells (NCI-N87) to explore potential mediators in the IFN-γ / PD-L1 pathway. The experimental procedure was as described by Ma, X, Jia, S, Wang, G, Liang, M, Guo, T, Du, H, Li, S, Li, X, Huangfu, L, Guo, J, Xing, X, Ji, J (2023) TRIM28 promotes the escape of gastric cancer cells from immune surveillance by increasing PD-L1 abundance. Signal Transduct Target Ther 8, 246. At the same time, the MAGeCK software package was used to perform quantitative and statistical evaluations of sgRNA and gene enrichment.

[0138] Bioinformatics and public data sources

[0139] The ClusterProfiler package (version 3.18.0) was used for Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment; the ggplot2 package (R V^4.3.1) was used to visualize the results of the enrichment analysis; based on the MsigDB database, the GSVA package was used to perform single-sample gene set enrichment analysis (ssGSEA); in addition, the Spearman correlation coefficient in R was used to evaluate the association between gene expression and pathway scores, with P < 0.05.

[0140] Isolation and culture of PBMC-T cells

[0141] Peripheral blood samples from human donors were collected, and peripheral blood mononuclear cells (PBMCs) were isolated. These were cultured in RPMI-1640 medium (containing 10% FBS, 1% penicillin-streptomycin, 10 ng / ml IL-2, and 25 μl / ml CD3 / CD28) for at least three days to finally obtain PBMC-T cells.

[0142] Live cell real-time monitoring model

[0143] The Incucyte ZOOM live cell analysis system (Sartorius) was used to evaluate cell proliferation, migration, and toxicity. In bright field, the Incucyte was used to monitor unlabeled 2D monolayer culture models, and in dark field, it was used to monitor labeled 2D co-culture models. Cancer cells were labeled green (Cytolight Green Fast Dye, Sartorius), and PBMC-T cells were labeled red (Cytolight Red Fast Dye, Sartorius). 3×10 3 cancer cells were added to each well (96-well plate) at a cancer cell to PBMC-T cell ratio of 1:10. The real-time results of cell confluence were analyzed using Incucyte ZOOM software. When evaluating the effects of TOPK inhibitors and immune checkpoint inhibitors on enhancing PBMC-T cell cytotoxicity and inhibiting cell growth, the TOPK inhibitors and immune checkpoint inhibitors were added at the initial stage of co-culture of PBMC-T cells and cancer cells.

[0144] The xCELLigence RTCA real-time cell analysis system (Agilent) was used to detect cell adhesion, proliferation, and toxicity. 50 μl of DMEM medium containing cancer cells was added to each well, and 50 μl of DMEM medium containing OTS964 or PBMC-T cells (PBMC-T:DC = 5:1) or a combination of both was added 24 hours later. The cell index was recorded for 72 hours, and the continuous real-time results were analyzed using xCELLigence RTCA software 2.0.

[0145] Flow cytometry

[0146] An Accuri C6 flow cytometer (BD Biosciences) was used to detect cell cycle, apoptosis, and the expression of membrane proteins. In cell cycle detection, the harvested cells were washed, fixed with 70% ethanol at 4 °C overnight, washed with PBS, and incubated with PI staining buffer containing RNase in the dark at room temperature for 30 minutes. Flow cytometry was used to analyze cell DNA content and cell cycle distribution.

[0147] In apoptosis detection, the procedure was performed according to the FITC Apoptosis Detection Kit (Annexin V). The harvested cells were washed with pre-cooled PBS and resuspended in binding buffer. Annexin V-FITC and PI were added, and the cells were incubated in the dark at room temperature for 15 minutes. Flow cytometry was used to analyze cell apoptosis.

[0148] In the detection of membrane protein expression, the harvested cells were washed and then added with fluorescein-conjugated antibodies (as shown in Table 3), incubated on ice in the dark for 15 minutes, washed with PBS, resuspended, and the expression levels were detected by flow cytometry.

[0149] The cellular composition and surface protein expression in the immune microenvironment of mouse tumor tissues were analyzed by multi-color flow cytometry. Tumor tissues were extracted from mice and stored in MACS Tissue Storage Solution (Miltenyi Biotech), cut into small pieces and digested. The digested tissues were filtered through a 70-μm cell strainer to obtain single-cell suspensions. After washing with PBS, fluorescently conjugated antibodies (as shown in Table 3) were added for staining, and flow cytometry was used to analyze each cell subset. In this application, four panels and gating strategies focused on macrophages, MDSCs, DCs, and lymphocytes. Data were analyzed using FlowJo software (BD Biosciences) to determine the phenotypes and frequencies of various immune cell subsets in the tumor microenvironment. The gating strategy was referenced from Faget, J, Groeneveld, S, Boivin, G, Sankar, M, Zangger, N, Garcia, M, Guex, N, Zlobec, I, Steiner, L, Piersigilli, A, Xenarios, I, Meylan, E (2017) Neutrophils and Snail Orchestrate the Establishment of a Pro-tumor Microenvironment in Lung Cancer. Cell Rep 21, 3190-3204..

[0150] Colony-forming unit (CFU) assay

[0151] As previously described (Huangfu, L, Wang, X, Tian, S, Chen, J, Wang, X, Fan, B, Yao, Q, Wang, G, Chen, C, Han, J, Xing, X, Ji, J (2023) Piceatannol enhances Beclin-1 activity to suppress tumor progression and its combination therapy strategy with everolimus in gastric cancer. Sci China Life Sci 66, 298-312.), the CFU assay was performed to evaluate the ability of single cancer cells to form colonies.

[0152] Briefly, 5×10 2 cancer cells were seeded into 6-well plates (with three replicates per group) and incubated for 10-14 days to allow colony formation.

[0153] Confocal experiments, immunofluorescence staining (IF), EdU / TUNEL, and JC1

[0154] Confocal experiments and immunofluorescence staining were performed as previously described (Huangfu, L, Wang, X, Tian, S, Chen, J, Wang, X, Fan, B, Yao, Q, Wang, G, Chen, C, Han, J, Xing, X, Ji, J (2023) Piceatannol enhances Beclin-1 activity to suppress tumor progression and its combination therapy strategy with everolimus in gastric cancer. Sci China Life Sci 66, 298-312.). Among them, incubation was carried out with primary antibodies (as shown in Table 3), and different secondary antibodies were added for re-incubation: Alexa Fluor 488 (green fluorescence), Alexa Fluor 594 (red fluorescence). The cell nuclei were counterstained with Hoechst-33342 for 5 minutes.

[0155] EdU / TUNEL assay or JC1 assay was performed according to the TUNEL Cell Apoptosis Detection Kit (Guangzhou Ribobio Co., Ltd.) and the Enhanced Mitochondrial Membrane Potential Detection Kit (Nanjing Beyotime Biotechnology Co., Ltd.).

[0156] High-content imaging (HCI) of 3D tumor spheroids

[0157] A 3D tumor spheroid model was constructed using a spheroid microplate (Corning, 4520) according to the spheroid-forming protocol to stimulate and evaluate the proliferation of cancer cells at the 3D level. Real-time monitoring was performed using the Cellvoyager CV8000 system (Yokogawa), and analysis was performed using the CellPathfinder software.

[0158] Briefly, in bright-field monolayer culture, 100 μl of cell suspension (5×10 5 cells / ml, prepared using DMEM and 10% FBS) was added. The size of the tumor spheroids was measured at 24, 48, and 72 hours, respectively. For dark-field co-culture, first, 50 μl of cancer cells were added at 0 hour at 1×10 5Cells were seeded into a 96-well plate at a density of cells / ml and co-cultured with THP-1-derived macrophages or MK-92MI cells 6 - 12 hours later. 3D cell viability was evaluated using the CellTiter-Glo 3D Cell Viability Assay Kit (Promega), and luminescence signals were measured using a microplate reader (BioTek Synergy H1, Agilent) after 72 hours of monolayer or co-culture.

[0159] Immunohistochemical staining (IHC) and multiplex immunohistochemical staining (mIHC)

[0160] The excised tumor tissues were fixed with 10% formalin, embedded in paraffin (FFPE), and subjected to histological analysis after HE staining. Multiplex immunohistochemical staining was performed on FFPE sections using the AlphaXTSA Multiplex Immunohistochemistry Kit (Alphaxbio Biotechnology Co., Ltd.). Among them, incubation was carried out with primary antibodies (as shown in Table 3), nuclei were stained with DAPI, imaged under a fluorescence microscope, and data analysis was performed using HALO software.

[0161] Migration and invasion Transwell assay

[0162] The Transwell assay was performed according to the previously described experimental protocol (Han, J, Nie, M, Chen, C, Cheng, X, Guo, T, Huangfu, L, Li, X, Du, H, Xing, X, Ji, J (2022) SDCBP-AS1 destabilizes beta-catenin by regulating ubiquitination and SUMOylation of hnRNP K to suppress gastric tumorigenicity and metastasis. Cancer Commun (Lond) 42, 1141 - 1161.) to evaluate the migration and invasion abilities of cancer cells.

[0163] Briefly, 5×10 4 cells were suspended in 200 μl of serum-free DMEM and seeded onto a polycarbonate filter membrane. For the invasion assay, the filter membrane was pre-coated with 100 μl of Matrigel matrix; for the migration assay, the filter membrane remained uncoated. 400 μl of DMEM containing 10% FBS was added to the lower chamber. Continuous real-time results were analyzed using Incucyte ZOOM software (Sartorius).

[0164] Wound healing assay

[0165] The scratch wound healing assay was performed according to the previously described experimental protocol (Han, J, Nie, M, Chen, C, Cheng, X, Guo, T, Huangfu, L, Li, X, Du, H, Xing, X, Ji, J (2022) SDCBP-AS1 destabilizes beta-catenin by regulating ubiquitination and SUMOylation of hnRNP K to suppress gastric tumorigenicity and metastasis. Cancer Commun (Lond) 42, 1141-1161.) to evaluate cell migration ability.

[0166] Briefly, a 96-well scratch tool (Sartorius) was used to create a scratch on the confluent monolayer cells to induce a wound. Subsequently, the medium was replaced with serum-free medium. Real-time monitoring and analysis were performed using the Incucyte system.

[0167] qRT-PCR

[0168] In qRT-PCR, the gene-specific primers used are shown in the following table (Table 1), and GADPH was used as an internal reference control.

[0169] Protein immunoblotting (Western blot)

[0170] Membrane and cytoplasmic proteins were separated using a membrane and cytoplasmic protein extraction kit (Beyotime). Protein samples were first extracted or separated using RIPA lysis buffer (Solarbio). Proteins were separated by 12.5% SDS-PAGE and transferred to a nitrocellulose membrane (NC membrane). The membrane was blocked with TBST buffer containing 5% skim milk at room temperature for 1 hour, and then incubated with the primary antibody (shown in Table 3) overnight at 4°C. After washing, the membrane was incubated with a fluorescently labeled secondary antibody (680RD goat anti-mouse IgG secondary antibody for mouse primary antibody, 800CW goat anti-rabbit IgG secondary antibody for rabbit primary antibody, LI-COR Biosciences) at room temperature for 1 hour.

[0171] ELISA and CCK-8 assays

[0172] The cytokines secreted in the cell supernatant were measured using ELISA kits, including human perforin ELISA kit (Wuhan Abbkine Scientific Co., Ltd., RK00135), human granzyme B (GZMB) ELISA kit (KE00121), human IFN-γ ELISA kit (Suzhou EKSELL BIO TECHNOLOGY Co., Ltd., EH008), human TNF-α ELISA kit (Suzhou EKSELL BIO TECHNOLOGY Co., Ltd., EH009), and human TNF-β ELISA kit (Solarbio, SEKH-0048).

[0173] The Cell Counting Kit-8 (Dojindo) was used to evaluate the cancer cell proliferation ability. Briefly, the cell suspension (100 μl / well) was added to a 96-well plate, and then 10 μl of CCK-8 solution was added to each well. After incubation for 1 hour, the absorbance was measured at 450 nm using a microplate reader (BioTek Synergy H1, Agilent).

[0174] Co-Immunoprecipitation (co-IP) and mass spectrometry analysis

[0175] The co-IP experiment was performed according to the previously described experimental protocol (Huangfu, L, Wang, X, Tian, S, Chen, J, Wang, X, Fan, B, Yao, Q, Wang, G, Chen, C, Han, J, Xing, X, Ji, J (2023) Piceatannol enhances Beclin-1 activity to suppress tumor progression and its combination therapy strategy with everolimus in gastric cancer. Sci China Life Sci 66, 298-312.) to explore potential interacting proteins.

[0176] Briefly, whole cell lysates were prepared using IP buffer (consisting of 20 mM Tris-HCl (pH = 7.5), 150 mM NaCl, 10% glycerol, 1 mM EDTA, 1% Triton X, 1 mM PMSF, and 1 mM DTT), incubated with the target antibody (shown in Table 3) at 4°C for 2 hours, added with protein A / G agarose beads (Merck) equilibrated and incubated with rotation at 4°C overnight. The next day, the agarose beads were washed, the immunoprecipitated proteins were eluted, and Western blot detection or mass spectrometry analysis was performed.

[0177] Ribosome sequencing (Ribo-seq) and ribosome distribution analysis

[0178] The cells to be detected were incubated in DMEM medium containing 0.1 mg / ml cycloheximide (CHX) for 1 minute, washed with PBS (containing 0.1 mg / ml CHX), the cell suspension was collected using a cell scraper, and ribosome-protected fragments (RPFs) were isolated according to the previously described experimental protocol (Ingolia, NT, Brar, GA, Rouskin, S, McGeachy, AM, Weissman, JS (2012) The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat Protoc 7, 1534-1550.). While preparing the ribosome sequencing library, transcriptome sequencing was performed, the results of translatome and transcriptome analysis were visualized using a nine-quadrant plot, and the enriched RPFs were visualized using a proteomic map.

[0179] Ribosome distribution analysis was performed according to the previously described experimental protocol (Yuan, M, Tu, B, Li, H, Pang, H, Zhang, N, Fan, M, Bai, J, Wang, W, Shu, Z, DuFort, CC, Huo, S, Zhai, J, Yao, K, Wang, L, Ying, H, Zhu, WG, Fu, D, Hu, Z, Zhao, Y (2022) Cancer-associated fibroblasts employ NUFIP1-dependent autophagy to secrete nucleosides and support pancreatic tumor growth. Nat Cancer 3, 945-960.) to verify the mRNA distribution characteristics in polysome fractionation.

[0180] Proteome and phosphoproteome determination

[0181] The cell samples to be detected were lysed in lysis buffer containing 1% protease inhibitor mixture, sonicated three times on ice using a high-intensity ultrasonic processor, the supernatant was collected, and the protein concentration in the supernatant was determined using the Pierce TM BCA Protein Assay Kit (Thermo Fisher Scientific).

[0182] The extracted protein samples were digested into peptides with trypsin, phosphopeptides were affinity enriched, and the peptides were measured using 4D liquid chromatography-tandem mass spectrometry (LC-MS / MS). The data was processed using MaxQuant software (v.1.6.15.0). The analysis used the “Homo_sapiens_9606_SP_20230103.fasta” database, which contains 20,389 protein sequences. Trypsin / P was designated as the digestion specificity, allowing a maximum of two uncut sites. The identification accuracy of spectra, peptides, and proteins was set at a false discovery rate (FDR) of 1%. The relative quantification values of the ratio of phosphorylated proteins to total proteins were used for subsequent differential expression analysis of post-translational modifications. When P < 0.05, the significance threshold for differential expression was set at an absolute fold change exceeding 1.5.

[0183] GO analysis was performed on the differentially expressed proteins to determine their enriched pathways. MoMo was used to analyze the motif characteristics of the modification sites, and based on the results of the MoMo analysis, the degree of change in the amino acid frequencies near the modification sites was scored and presented in the form of a heatmap. According to the fold change of the phosphorylated proteins, they were further divided into four parts (Q1-Q4). Protein domain enrichment analysis was performed using the Pfam database (https: / / pfam.xfam.org / ). Fisher's exact test was used to evaluate the significance of enrichment in the differentially expressed proteins. Statistical significance was defined as P < 0.05.

[0184] Metabolomics

[0185] After thawing, rinsing, and grinding the samples, they were mixed with 70% methanol, vortexed, and centrifuged, and the supernatant was harvested for metabolomics analysis. Using ExionLC TM AD high-performance liquid chromatography and Determination of the content of tryptophan and its metabolites by 6500+LC-MS / MS (SCIEX); 31 metabolites in the tryptophan-kynurenine pathway were detected (refer to the Metware database), and the raw data were collected and processed using Analyst 1.6.3 software and MultiQuant 3.0.3 software (SCIEX). The following calculation formula was used for quantification: (content of amino acids in solid samples, ng / g) = (concentration value obtained by substituting the sample peak area into the standard curve, ng / ml) × (volume of the extraction solution used in the extraction process, μl) / (sample mass, g) / 1000; after the data were log2-transformed and mean-centered, the OPLS-DA analysis was performed using the OPLSR.Anal function of the MetaboAnalystR package (V1.0.1) in R software. The variable importance in projection (VIP) analysis value and the absolute Log2FC value were used to determine the metabolites significantly regulated between groups.

[0186] Molecular docking

[0187] The inventors performed protein docking of TOPK and eIF4A1. The three-dimensional structures of the proteins were derived from the AlphaFold Protein Structure Database (https: / / alphafold.ebi.ac= / ). Rigid docking simulations were performed using the Global Range Molecular Matching (GRAMM) docking software (http: / / vakser.compbio.ku.edu / resources / gramm / ) to predict the interactions between the proteins predicted by AlphaFold. The visualization of the docking was achieved through PyMol software (Version 2.1, https: / / pymol.org / ).

[0188] Proximity ligation assay (PLA)

[0189] According to The PLA experiment was performed using the in situ detection reagent FarRed (Sigma-Aldrich) to analyze the spatial proximity and direct interaction of intracellular molecules. In addition, the TOPK protein and the PBK polyclonal antibody conjugated with Plus488 (Proteintech) were jointly used to evaluate the spatial sublocalization of the TOPK protein in cells.

[0190] CDX, CDA mouse models and treatment

[0191] To establish CDX and CDA mouse models, male mice aged 4 - 6 weeks (including immunodeficient BALB / c nude mice and immunocompetent 615 mice, purchased from the Institute of Hematology, Chinese Academy of Medical Sciences) were selected. A 100 μL single-cell suspension of PBS containing 1×10 5 cancer cells or only PBS was subcutaneously injected into the lateral abdomen of the mice, and the tumor growth was regularly monitored. The weight was measured and the volume was calculated (volume calculation formula V = length × width × width) / 2).

[0192] A lung metastasis model was established in the CDX mouse model by using luciferase-transfected cells and an in vivo imaging system. After the mice were anesthetized by inhalation, the collected cells were injected into the tail vein. The painful symptoms, weight loss, and overall health status of the mice were regularly monitored, and tumor metastasis was evaluated by bioluminescence imaging.

[0193] The treatment of 6 - 8-week-old mice included targeted therapy or combined immunotherapy. The mice were randomly divided into a treatment group and a control group. OTS964 (Selleck, S7648) was diluted with DMSO and intraperitoneally injected at a dose of 1 mg / time. The control group used the same dilution ratio and volume of DMSO. InVivoMAb anti-mouse PD-1 (BioXCell, BE0146) or isotype control antibody (BioXCell, BE0089) was diluted with InVivoPure pH 7.0 dilution buffer (BioXCell, IP0070) and intraperitoneally injected at a dose of 250 μg / time. InVivoMAb anti-mouse CTLA-4 (BioXCell, BE0131) or isotype control (BioXCell, BE0087) was also diluted with the buffer and intraperitoneally injected at a dose of 250 μg / time. For combination therapy, the two dilutions were mixed and administered by intraperitoneal injection. In the CDA mouse model, starting from the 5th day after transplantation, the drug was administered every 4 days for 3 weeks, and the mice were sacrificed for detection on the 35th day after transplantation. When the mice showed skin necrosis or the tumor volume was close to 2000 mm 3 they were sacrificed for detection.

[0194] Example 1 Identification of inhibitors that block IFN-γ-induced PD-L1 by combining CRISPR and compound screening

[0195] IFN-γ promotes cancer cell immune escape. To identify potential targets mediating IFN-γ-induced PD-L1 overexpression in GC cells, this application performed CRISPR / Cas9-based genome-wide editing and compound screening in IFN-γ-stimulated GC cells. The results showed that in NCI-N87 cells, STAT1 was significant in IFN-γ-induced PD-L1 expression ( Figure 1a)。In addition, GO and KEGG pathway annotations were performed on the most potential genes regulating IFN-γ-induced PD-L1 expression, and several important signaling pathways were found, including "regulation of protein serine / threonine kinase activity", "protein targeting to endoplasmic reticulum", and "JAK-STAT signaling pathway" were enriched( Figure 1b )。Given the key role and targeting potential of kinases in proliferation and metastasis, this application focused on identifying and targeting key kinases that affect PD-L1 expression under IFN-γ stimulation. This application identified the top 5 proteins kinases that significantly affect PD-L1 expression differences in GC cells, and at the same time listed 50 known kinase inhibitors targeting them( Figure 1c )。

[0196] These kinase inhibitors were used to treat GC cells, and their effects were evaluated using a real-time monitoring model. The results showed that the PLK1 inhibitors BI2536 and Volasertib, and the TOPK inhibitors OTS964 and OTS514 all achieved significant inhibitory effects( Figure 1d )。In the real-time monitoring model of in vitro double-labeled live cells, OTS964 and OTS514 significantly enhanced the cytotoxicity of PBMC-T to GC cells( Figure 1e and 1f )。Both OTS964 and OTS514 showed significant inhibitory effects on GC cells, increased the level of GZMB in the supernatant, and enhanced the cytotoxicity of PBMC-T( Figure 1g )。Furthermore, flow cytometry was used to verify that OTS964 could block the upregulation of membrane PD-L1 in IFN-γ-induced GC cells (NUGC3, SNU1, MKN28, MGC803, MKN45)( Figure 1h )。

[0197] Based on different TOPK expression levels, the inventors of this application constructed cells with stable overexpression of TOPK (Flag-TOPK) or knockdown of TOPK (TOPK-KD). When the knockdown amount of TOPK decreased, its expression amount increased( Figure 1i and Figure 1j )。

[0198] To study the potential effects of TOPK inhibitors (OTS964 and OTS514) on GC cells, a real-time monitoring model experiment was conducted, and the results showed that these inhibitors significantly inhibited the proliferation of GC cells in a dose- and time-dependent manner( Figure 2a and Figure 2b )。In the CFU experiment, OTS964 inhibited the proliferation of GC cells (SGC7901, BGC823, and NCI-N87)( Figure 2c and Figure 2d), and is accompanied by an increase in apoptosis ( Figure 2e ). Notably, OTS964 can arrest GC cells at the G2 / M phase ( Figure 2f ), and the disruption of mitochondrial membrane potential was detected by JC-1 staining ( Figure 2g ). In addition, OTS964 and OTS514 reduced the size of tumor spheres and their 3D viability ( Figure 2h ). Finally, in BALB / c nude mice, OTS964 significantly inhibited the growth of BGC823-derived subcutaneous tumors without causing weight loss ( Figure 2i ).

[0199] From the above results, it can be seen that OTS964 is superior to OTS514 in inhibiting GC cell proliferation, anti-tumor formation, and immunomodulatory effects, and OTS964 has lower toxicity and side effects compared to OTS514. Therefore, this application selects OTS964 for subsequent experiments.

[0200] Example 2 Protein kinase TOPK promotes the proliferation, invasion, and metastasis of GC

[0201] TOPK expression regulates the proliferation of GC cells in a real-time monitoring model (Incucyte) ( Figure 3a ). These findings were verified in an HCI monitoring model of 3D tumor spheres ( Figure 3b and Figure 3c ). Similar results were also observed by EdU staining, while opposite results were observed in the TUNEL assay ( Figure 3d ). By CFU assay, TOPK knockdown reduced the colony formation of GC cells, while its overexpression enhanced the colony formation of GC cells ( Figure 3e ). The positive regulatory effect of TOPK on the migration and invasion of GC cells was detected by in vitro scratch wound healing and Transwell assays ( Figure 3f -g). In an in vivo CDX mouse model, TOPK knockdown inhibited the growth of subcutaneous tumors, while TOPK overexpression promoted tumor growth ( Figure 3h ); further, in a mouse lung metastasis model, TOPK knockdown inhibited metastasis and tumor growth ( Figure 3i ).

[0202] Example 3 TOPK mediates IFN-γ-induced PD-L1 and IDO1 expression

[0203] The proliferation and invasion of TOPK explain the phenomenon that the TOPK inhibitor OTS964 inhibits GC. However, the mechanism by which OTS964 regulates the adaptive expression of IFN-γ-induced PD-L1 and enhances immune cytotoxicity remains unclear. This example explored and analyzed the potential role of TOPK in the GC immune metabolic microenvironment. In a cohort of GC patients (ERP107734) receiving immunotherapy, the expression of TOPK in the responder group was higher than that in the non-responder group. The area under the curve (AUC) for predicting immunotherapy response using the combination of PD-L1 and TOPK expression was 0.876( Figure 4a ).

[0204] Since it has been reported that JAK2 (a downstream kinase of the IFN-γ pathway) can phosphorylate and stabilize TOPK, the inventors observed that upon IFN-γ stimulation, the phosphorylation of TOPK at Tyr-74 and STAT1 at Tyr-701 increased, accompanied by an increase in the protein levels of PD-L1 and IDO1( Figure 4b ), as well as the membrane translocation of PD-L1( Figure 4c ). TOPK knockdown reduced the protein levels of STAT1, IDO1, and membrane PD-L1( Figure 4d and Figure 4e ). IDO1 is responsible for consuming tryptophan (a nutrient for cytotoxic cells) and generating L-kynurenine. In vitro, by IF assay, TOPK knockdown led to a decrease in L-kynurenine production( Figure 4f ). In the 2D Incucyte monitoring model, the results showed that TOPK knockdown in GC cells significantly enhanced PBMC-T cell cytotoxicity( Figure 4g ), while TOPK overexpression attenuated this cytotoxicity( Figure 4h ).

[0205] In addition, in the 3D model, macrophages (THP-1 stimulated with PMA)( Figure 4i ) and NK-92MI( Figure 4j ) showed significantly enhanced cytotoxicity against TOPK-knockdown GC cells, while showing attenuated cytotoxicity against GC cells overexpressing TOPK. Consistent with these findings, TOPK knockdown in MFC significantly inhibited the xenograft growth of subcutaneous cells in CDA mice( Figure 4k ).

[0206] Example 4 TOPK Enhances the Translation of STAT1 mRNA by Phosphorylating Components of the eIF4F Complex

[0207] eIF4A1 is a key component of the eIF4F complex in eukaryotic ribosomes and participates in RNA unwinding and translation processes through its DEAD domain. In this application, the DEAD domain was identified as the key region interacting with TOPK phosphorylation ( Figure 5a ), and the co-localization of TOPK and eIF4A1 was characterized in GC cells ( Figure 5b ). Through molecular docking analysis, it was found that eIF4A1 could bind to the active pocket of TOPK, providing a structural condition for phosphorylation ( Figure 5c ). When TOPK was knocked down, the phosphorylation level of eIF4A1 decreased ( Figure 5d ).

[0208] The inventors of this application analyzed the phosphorylation sites, scores, and rankings of 303 serine / threonine kinases in the eIF4F complex using the human serine / threonine kinase substrate map. Kinase profiling analysis showed that multiple phosphorylation sites on eIF4A1 (including S78, T158, T393, and S56) were strongly phosphorylated by TOPK and ranked among the top in the analyzed kinases. Notably, many key components of the eIF4F complex may be potential substrates with high phosphorylation scores and rankings, and their predicted phosphorylation sites can promote translation, such as eIF4B-S422 and eIF4E-S209 ( Figure 5e ). Therefore, the binding of TOPK to eIF4A1 may bring TOPK closer to other components of the eIF4F complex, thus creating conditions for further phosphorylation, and TOPK is involved in the extensive phosphorylation process of the eIF4F complex ( Figure 5f ).

[0209] Furthermore, the inventors of this application explored whether eIF4A1 plays a central role in mediating the function of TOPK in IFN-γ stimulation. The results preliminarily showed that the eIF4A1 inhibitor silvestrol reduced the expression of membrane PD-L1 and the total protein expression of STAT1, PD-L1, and IDO1 under IFN-γ stimulation ( Figure 5g and Figure 5h ). The analysis combining Ribo-seq and transcriptome data showed that TOPK knockdown significantly reduced the TE (the ratio of RPFs to mRNA) of PD-L1, STAT1, and IDO1 ( Figure 5i ).

[0210] In addition, the inventors of this application calculated the mRNA and protein levels of STAT1 and TE (the ratio of protein to mRNA), and confirmed that after TOPK knockdown, the mRNA level of STAT1 was not regulated, but the protein level and TE decreased ( Figure 5j) Ribosome profiling showed that the RPFs of STAT1, IDO1, and PD-L1 were reduced in the high molecular weight (HMW) polysome fraction ( Figure 5k ).

[0211] Example 5 TOPK inhibitor OTS964 blocks IFN-γ-induced PD-L1 and IDO1 expression

[0212] The inventors of the present application observed that upon IFN-γ stimulation, after administration of OTS964, the expression of proteins such as STAT1, PD-L1, and IDO1 was reduced, while the expression of TOPK and eIF4A1 was not affected ( Figure 6a ). In addition, OTS964 inhibited the IFN-γ-induced increase in membrane PD-L1 ( Figure 1h ), while reducing the phosphorylation levels of p-eIF4B (Ser422), p-eIF4E (Ser209), p-4EBP1 (Thr37 / 46), and p-STAT1 (Tyr701) ( Figure 6b ), as well as the production of L-kynurenine ( Figure 6c ). The PLA experiment showed that OTS964 disrupted the binding between TOPK and eIF4A1 ( Figure 6d ). Consistent with this finding, OTS964 inhibited the IFN-γ-induced enrichment of STAT1 mRNA RPFs in HMW polysomes, while having no effect on the mRNA RPF enrichment of TOPK and GAPDH ( Figure 6e ).

[0213] The inventors of the present application evaluated the regulatory effect of OTS964 on PBMC-T cell cytotoxicity using a real-time cell monitoring model. Based on the non-labeled real-time cell analysis (RTCA) model, the optimal effector cell to target cell ratio was determined to be 5:1 (i.e., PBMC-T:SGC7901) ( Figure 6f ). OTS964 significantly enhanced the synergistic cytotoxic effect of PBMC-T on SGC7901, exceeding the effects of OTS964 or PBMC-T cells alone ( Figure 6g ). OTS964 also significantly enhanced the cytotoxicity of PBMC-T (red) against BGC823 (green) and TOPK-overexpressing NCI-N86 (green) ( Figure 6h ). Consistent with these findings, OTS964 inhibited tumor growth of MFC in immunocompetent mice ( Figure 6i ). In addition, mass spectrometry analysis of metabolites showed that OTS964 increased the production of L-tryptophan and decreased the production of L-kynurenine, blocking the L-TRP metabolic pathway ( Figure 6j and Figure 6k ).

[0214] These findings together indicate that the TOPK inhibitor OTS964 blocks the IFN-γ-induced expression of PD-L1 and IDO1 in GC, thereby reducing the immunosuppressive effects of these immune checkpoints and enhancing the cytotoxicity of immune T cells in the immunometabolic microenvironment.

[0215] Example 6 Synergistic use of TOPK inhibitor and immune checkpoint inhibitor for GC treatment

[0216] In this example, the effects of TOPK-targeted therapy combined with immune checkpoint inhibitors (including anti-PD-1 (Pembrolizumab), anti-CTLA-4 (Ipilimumab), and dual anti-PD-1 / CTLA-4 antibody) on GC were evaluated. OTS964 enhanced the cytotoxicity of PBMC-T against BGC823 or TOPK-overexpressing NCI-N87, and this cytotoxicity was further enhanced when combined with anti-CTLA-4 antibody ( Figure 7a ), anti-PD-1 antibody ( Figure 7b ), or both ( Figure 7c ). Previously, the inventor's clinical trial using the dual anti-PD-1 / CTLA-4 antibody (cadonilimab) showed an encouraging response rate, and the combination with the TOPK inhibitor also showed significant synergistic effects ( Figure 7d ).

[0217] Meanwhile, when OTS964 was used alone or in combination with immune checkpoint inhibitors, the secretion of GZMB, perforin, and TNF-β could be significantly increased, but there was no effect on the secretion of TNF-α ( Figure 7e and 7f ), indicating the potential role of OTS964 in enhancing PBMC-T cell cytotoxicity.

[0218] Furthermore, the inventor of the present application evaluated the synergistic effects of the combination of OTS964 and immunotherapy in vivo and observed that OTS964 inhibited the growth of subcutaneously transplanted GC tumors and further showed synergistic effects with anti-CTLA-,-4 antibody or anti-PD-1 antibody ( Figure 7g ), accompanied by a decrease in L-kynurenine ( Figure 7h ). The study showed that OTS964 treatment enhanced the infiltration of cytotoxic immune cells, especially when combined with anti-PD-1 antibody or anti-CTLA-4 antibody ( Figure 7i ).

[0219] The above are only the preferred embodiments of the present application, and are not intended to limit the present application in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present application without departing from the technical solution content of the present application still fall within the protection scope of the technical solution of the present application.

Claims

1. Use of a TOPK inhibitor in the treatment of gastric cancer.

2. Use of a TOPK inhibitor in the preparation of a medicament for the treatment of gastric cancer.

3. Use of a TOPK inhibitor in enhancing the therapeutic effect of an immune checkpoint inhibitor on gastric cancer.

4. Use of a TOPK inhibitor in the preparation of an enhancer for enhancing the therapeutic effect of an immune checkpoint inhibitor on gastric cancer.

5. Use of an immune checkpoint inhibitor in enhancing the therapeutic effect of a TOPK inhibitor on gastric cancer.

6. Use of an immune checkpoint inhibitor in the preparation of an enhancer for enhancing the therapeutic effect of a TOPK inhibitor on gastric cancer.

7. Use of a TOPK inhibitor and an immune checkpoint inhibitor in the treatment of gastric cancer.

8. Use of a TOPK inhibitor and an immune checkpoint inhibitor in the preparation of a medicament for the treatment of gastric cancer.

9. Use according to any one of claims 1 to 8, wherein The TOPK inhibitor is selected from a compound, an antisense molecule, a ribozyme, an RNAi molecule, or a low molecular weight organic molecule, preferably selected from OTS964 or OTS514.

10. Use according to any one of claims 3 to 9, wherein, The immune checkpoint inhibitor targets include at least one of PD-L1, PD-1, and CTLA-4 involved in immunosuppressive signals; Preferably, the immune checkpoint inhibitor is selected from a compound, an antibody, an antibody fragment, or a fusion polypeptide (such as an Fc fusion, such as CTLA4-Fc), an antisense molecule, a ribozyme, an RNAi molecule, or a low molecular weight organic molecule.

11. A kit comprising a TOPK inhibitor and an immune checkpoint inhibitor.

12. The medicine box according to claim 11, wherein, The TOPK inhibitor is selected from a compound, an antisense molecule, a ribozyme, an RNAi molecule, or a low molecular weight organic molecule, preferably selected from OTS964 or OTS514.

13. The medicine box according to claim 11 or 12, wherein, The immune checkpoint inhibitor targets include at least one of PD-L1, PD-1, and CTLA-4 involved in immunosuppressive signals; Preferably, the immune checkpoint inhibitor is selected from a compound, an antibody, an antibody fragment, or a fusion polypeptide (such as an Fc fusion, such as CTLA4-Fc), an antisense molecule, a ribozyme, or an RNAi molecule, or a low molecular weight organic molecule.

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