Application of STX10 in treatment and prognosis evaluation of kidney cancer

Abstract

The invention relates to application of STX10 in treatment and prognosis evaluation of kidney cancer. The key effect of the STX10 in the renal clear cell carcinoma is emphasized, and the fact that the expression of the STX10 in ccRCC is remarkably up-regulated is revealed. Overexpression of the STX10 promotes proliferation and migration of ccRCC cells, is an independent risk factor of poor OS, PFI and DSS of the ccRCC and is closely related to poor immunotherapy response, it is clear that the STX10 can serve as a prognosis biomarker and a treatment target of the ccRCC, and development of kidney cancer can be obviously inhibited, the survival rate of patients can be prolonged and prognosis can be improved by inhibiting the STX10 or reducing the biological activity of the STX10. Related molecular mechanisms in the occurrence and development process of the kidney cancer are enriched, sufficient scientific basis and theoretical basis are provided for exploring new kidney cancer diagnosis, prognosis judgment and treatment molecular targets and developing new targeted drugs, accurate treatment can be better achieved, and important social value and scientific significance are achieved.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine and relates to the application of STX10 in the treatment and prognostic assessment of renal cell carcinoma. Background Technology

[0002] Renal cell carcinoma (RCC) is one of the most common malignant tumors of the urinary system, with an estimated 400,000 new cases worldwide each year, and its global incidence is on the rise. High-risk factors for RCC include smoking, high body mass index (BMI), and occupational exposure to trichloroethylene. Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of RCC, accounting for approximately three-quarters of all RCC cases. Surgical resection is the most important and effective treatment for early-stage localized ccRCC, but about 30% of patients with localized RCC experience tumor recurrence or metastasis after surgery, progressing to advanced renal cell carcinoma and leading to a poor prognosis. Therefore, effective adjuvant therapy is urgently needed for ccRCC patients to reduce the risk of recurrence and death from metastatic disease. Currently, first-line treatment for metastatic ccRCC mainly includes combination therapy based on immune checkpoint inhibitors (ICIs) and anti-angiogenic drugs. The advent of immunotherapy has been proven to significantly improve the prognosis of patients with metastatic ccRCC. Due to the significant heterogeneity of ccRCC, some patients develop acquired resistance to ICIs, leading to large differences in overall treatment response. This poses a significant challenge to the clinical treatment of ccRCC. Traditional clinical parameters (such as TNM staging) cannot accurately predict the risk of recurrence and metastasis or the sensitivity to treatment in localized ccRCC. While MSKCC and IMDC risk models, which combine clinical factors such as performance status, are used to assess the prognosis of metastatic ccRCC patients, they also struggle to identify the responsiveness of metastatic ccRCC to immune checkpoint inhibitor therapy. Therefore, there is an urgent need to identify more reliable biomarkers that can predict the prognosis of ccRCC patients and guide individualized treatment.

[0003] STX family proteins belong to a specific subclass of soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) and are involved in vesicle transport and cellular secretion. Studies have shown that certain genes in the STX family are closely related to tumor progression; for example, STX4 has been found to promote tumor progression in ccRCC by activating the AKT pathway, and high expression of STX3 in esophageal squamous cell carcinoma (ESCC) is associated with poor prognosis. Simultaneously, some members of this family are also involved in cell cycle regulation, especially STX6, which accelerates the G1 / S phase transition by upregulating key cell cycle regulatory proteins such as CDK4, CDK6, and cyclin D3, leading to abnormal cell proliferation in tumors. These findings provide insights into the development of the STX protein family as tumor biomarkers.

[0004] Synaptokinin 10 (STX10) is a protein-coding gene in the STX family. The protein encoded by STX10 is typically involved in docking and fusion of the Golgi apparatus. In studies related to osteosarcoma prognosis, silencing STX10 has been found to limit the migration, invasion, and proliferation of osteosarcoma cells, suggesting it could serve as a novel target gene for predicting the prognosis of osteosarcoma patients. This hints at the potential significance of STX10 in cancer biology, but its expression pattern, clinical prognosis, and biological function in the context of ccRCC (collateral chronic renal cell carcinoma) remain unverified. Therefore, to better understand the role of STX10 in ccRCC, this invention focuses on STX10 and, through bioinformatics analysis and in vitro experiments, aims to elucidate its potential significance as a prognostic biomarker for ccRCC and for assessing immunotherapy response. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the treatment of renal cell carcinoma in the prior art by revealing that STX10 expression is significantly upregulated in ccRCC. Overexpression of STX10 promotes the proliferation and invasion of ccRCC cells, is an independent risk factor for poor overall survival (OS), progression-free survival (PFI), and recurrent spontaneous aspiration (DSS) in ccRCC, and is closely associated with poor immunotherapy response. STX10 can serve as a potential novel biomarker for predicting the prognosis and efficacy of immunotherapy in ccRCC, aiming to provide new directions and evidence for risk stratification and targeted therapy strategies for this refractory malignancy.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution.

[0007] The first aspect of this invention provides the use of STX10 inhibitors in the preparation of medicaments for the prevention and / or treatment of renal cell carcinoma.

[0008] Preferably, the STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

[0009] Preferably, the STX10 inhibitor is selected from siRNA designed based on the STX10 gene, and the siRNA is selected from one or more of siSTX10-1 and siSTX10-2. The siSTX10-1 sequence is shown in SEQ ID NO: 1 (5'-GTCCAGGAAATGAAGGACCAT-3'), and the siSTX10-2 sequence is shown in SEQ ID NO: 2 (5'-AGCCCAACAGCCGTAGCATTT-3').

[0010] Preferably, the renal cell carcinoma is clear cell renal cell carcinoma.

[0011] A second aspect of the present invention provides the use of a reagent for detecting STX10 expression levels in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of renal cell carcinoma.

[0012] Preferably, the reagent for detecting STX10 expression level includes primers for detecting STX10 gene expression level and / or reagents for detecting STX10 protein content.

[0013] Preferably, the primers for detecting STX10 gene expression levels are selected from one or more of the following primer pairs:

[0014] Primer pair 1: The upstream sequence is shown in SEQ ID NO: 3 (5'-GAGACCATCGGTATAGTGGAAGC-3'), and the downstream sequence is shown in SEQ ID NO: 4 (5'-CAAAAATGCTACGGCTGTTGG-3');

[0015] Primer pair 2: The upstream sequence is shown in SEQ ID NO: 5 (5'-ACAGCCGTAGCATTTTTGGAG-3'), and the downstream sequence is shown in SEQ ID NO: 6 (5'-TCCTCGATGTAGCGAGATGTG-3').

[0016] Preferably, the reagent for detecting STX10 protein content is selected from YT6910 (Immunoway).

[0017] Preferably, the renal cell carcinoma is clear cell renal cell carcinoma.

[0018] A third aspect of the present invention provides a kit for the auxiliary diagnosis and / or prognostic assessment of renal cell carcinoma, including reagents for detecting STX10 expression levels.

[0019] Preferably, the reagent for detecting STX10 expression level includes primers for detecting STX10 gene expression level and / or reagents for detecting STX10 protein content.

[0020] Preferably, the primers for detecting the STX10 gene expression level are selected from the following primer pairs:

[0021] Primer pair 1: The upstream sequence is shown in SEQ ID NO: 3, and the downstream sequence is shown in SEQ ID NO: 4;

[0022] Primer pair 2: The upstream sequence is shown in SEQ ID NO: 5, and the downstream sequence is shown in SEQ ID NO: 6.

[0023] Preferably, the reagent for detecting STX10 protein content is selected from anti-STX10 Antibody.

[0024] Preferably, the kit further includes one or more of PCR enzyme, PCR buffer, dNTPs, and fluorescent substrate.

[0025] Preferably, the fluorescent substrate is selected from Syber Green or fluorescently labeled probes.

[0026] Preferably, the renal cell carcinoma is clear cell renal cell carcinoma.

[0027] The fourth aspect of this invention provides the use of STX10 inhibitors in the preparation of drugs that enhance the sensitivity of anti-PD-1 antibodies to renal cell carcinoma treatment.

[0028] Preferably, the STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

[0029] Preferably, the STX10 inhibitor is selected from siRNA designed based on the STX10 gene, and the siRNA is selected from one or more of siSTX10-1 and siSTX10-2, wherein the siSTX10-1 sequence is shown in SEQ ID NO: 1 and the siSTX10-2 sequence is shown in SEQ ID NO: 2.

[0030] Preferably, the renal cell carcinoma is clear cell renal cell carcinoma.

[0031] The fifth aspect of the present invention provides a pharmaceutical composition for the prevention and / or treatment of renal cell carcinoma, comprising an STX10 inhibitor, an anti-PD-1 antibody, and pharmaceutically acceptable excipients.

[0032] Preferably, the STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

[0033] Preferably, the STX10 inhibitor is selected from siRNA designed based on the STX10 gene, and the siRNA is selected from one or more of siSTX10-1 and siSTX10-2, wherein the siSTX10-1 sequence is shown in SEQ ID NO: 1 and the siSTX10-2 sequence is shown in SEQ ID NO: 2.

[0034] Preferably, the renal cell carcinoma is clear cell renal cell carcinoma.

[0035] Preferably, the pharmaceutically acceptable pharmaceutical excipient is selected from one or more of fillers, disintegrants, binders, lubricants, flavoring agents, preservatives, antioxidants, and colorants.

[0036] It should be understood that, unless otherwise specified, in the context of this invention, STX10 includes STX10 nucleotides and the STX10 protein encoded by those nucleotides. The STX10 inhibitor refers to a substance capable of specifically downregulating the expression level of STX10 and / or the transcriptional level of its mature mRNA and / or the expression level or activity of the STX10 protein. For example, methods such as antisense oligonucleotides, siRNA, shRNA, sgRNA, antagomiRs, miRNA sponges, miRNA erasers, target masking, and / or multi-target methods can be used to downregulate the expression level and / or activity of STX10; any method that can reduce the level and / or activity of STX10 is acceptable. The primers and / or primer pairs refer to PCR primers used to synthesize the STX10 gene cDNA strand in PCR, thereby detecting the expression level of the STX10 gene mRNA. In addition to the primers and / or primers listed in this invention, those skilled in the art are fully capable of designing corresponding primers and / or primer pairs based on the STX10 gene sequence using conventional methods and techniques in the art, including but not limited to molecular biology, and screening the designed primers and / or primer pairs using conventional experimental methods, as long as they can specifically detect the STX10 expression level; alternatively, conventional reagents and methods in the art can be used to detect the STX10 protein expression level; the same applies to other genes / proteins.

[0037] As a major pathological subtype of renal cell carcinoma, ccRCC (collapsed renal cell carcinoma) is primarily characterized by metastasis and recurrence, which are major causes of its poor prognosis. ccRCC is highly invasive and heterogeneous, making the exploration and development of reliable novel prognostic biomarkers essential for individualized stratified treatment and follow-up of ccRCC patients. This invention integrates multiple transcriptome datasets to evaluate the relationship between STX10 expression levels and survival outcomes (including OS, PFS, and DSS) in ccRCC patients from a clinical prognostic perspective. The results show that STX10 is a promising biomarker in ccRCC, and subsequent analyses demonstrated its predictive value for immunotherapy response.

[0038] Soluble N-ethylmaleimide-sensitive attachment protein receptors (SNAREs) are key proteins mediating the fusion of intracellular vesicles with target membranes, located in the plasma membrane, endoplasmic reticulum, and Golgi apparatus. Since cancer cells can utilize invasive pseudopodia to promote invasion of the extracellular matrix (ECM) for tumor metastasis, and SNAREs possess transmembrane domains and participate in vesicle transport, they are believed to significantly influence this process. The STX family, as a specific subclass of SNAREs, participates in vesicle transport and secretion, and can influence tumor development through similar mechanisms. Related studies have shown that STX family proteins can serve as potential biomarkers for tumor prognosis in various cancers, exhibiting a significant association with tumor development. STX10 belongs to the STX family. To further demonstrate that STX10 may also have some impact on tumors, pan-cancer analysis was performed using pan-cancer data from the UCSC dataset, obtaining comprehensive information on cancerous and normal tissues from numerous cancer patients and conducting preliminary analysis. The results showed that STX10 expression was significantly upregulated in tumor tissues of various cancers compared to normal tissues, highlighting the potential value of STX10 as a prognostic biomarker in multiple tumors. Currently, the relationship between STX10 and ccRCC has not been reported; therefore, a series of comprehensive bioinformatics analyses were conducted. These analyses revealed that high STX10 expression was closely associated with poor overall survival (OS), disseminated intravascular coagulation (DSS), and prognostic feasibility (PFI) in ccRCC. Furthermore, TMAIHC analysis confirmed the upregulation of STX10 expression in ccRCC tissues. In vitro experiments further validated the overexpression of STX10 in renal cell carcinoma tissues. The fusion of bioinformatics analysis and in vitro experimental results confirms that STX10 can serve as a key biomarker for the treatment and prognosis of ccRCC.

[0039] This invention determined the predictive function of STX10 for the prognosis of clear cell renal cell carcinoma (ccRCC) patients using univariate and multivariate Cox regression analysis and survival analysis. Simultaneously, GSEA functional enrichment analysis and multi-omics analysis were used to explore the potential mechanisms of STX10 in ccRCC, and an immunotherapy cohort validated the conclusion that ccRCC patients with high STX10 expression had a poorer response to immunotherapy (anti-PD-1). In summary, these results establish the value of STX10 as a biomarker for the treatment and prognosis of ccRCC, which has profound implications for the prognostic risk assessment of ccRCC patients and provides important information for the development of immunotherapy strategies for ccRCC. Overall, this invention highlights the crucial role of STX10 in clear cell renal cell carcinoma and reveals the significant upregulation of STX10 expression in ccRCC. Overexpression of STX10 promotes the proliferation and migration of ccRCC cells and is an independent risk factor for poor overall survival (OS), progression-free survival (PFI), and disseminated intraepithelial neoplasia (DSS) in ccRCC. It is also closely associated with poor immunotherapy response. This study clarifies that STX10 can serve as a prognostic biomarker and therapeutic target for ccRCC. Inhibiting STX10 or reducing its biological activity can significantly inhibit the development of renal cell carcinoma, prolong patient survival, and improve prognosis. This invention enriches the understanding of the relevant molecular mechanisms in the development and progression of renal cell carcinoma, providing sufficient scientific evidence and theoretical basis for exploring new molecular targets for the diagnosis, prognosis, and treatment of renal cell carcinoma, and developing new targeted drugs. It contributes to achieving better precision treatment and has significant social and scientific value. Attached Figure Description

[0040] Figure 1 This is a schematic diagram showing the mRNA expression levels of STX10 in tumor and normal tissues.

[0041] Figure 2 This is a schematic diagram showing the mRNA expression levels of STX10 in paired tumor and normal tissues.

[0042] Figure 3 This is a schematic diagram showing the results of univariate Cox regression analysis of STX10 in different tumor types when OS is used as the observation endpoint.

[0043] Figure 4 This is a schematic diagram of the univariate Cox regression analysis results of STX10 in different tumor types when PFI is used as the observation endpoint.

[0044] Figure 5 This is a schematic diagram of the Kaplan-Meier survival analysis results between high and low STX10 expression groups in the TCGA-PFI, TCGA-OS, TCGA-DSS, ICGC-OS, and EMTAB1980-OS cohorts.

[0045] Figure 6This is a schematic diagram of the results of multivariate Cox regression analysis of the TCGA and ICGC cohorts.

[0046] Figure 7 This is a schematic diagram showing the cellular localization analysis results of the STX10 protein in the Human Protein Atlas (HPA).

[0047] Figure 8 This is a schematic diagram of the results of HPA-based immunofluorescence image analysis of STX10 protein.

[0048] Figure 9 This is a schematic diagram of the STX10 immunohistochemical staining results of 75 ccRCC clinical samples.

[0049] Figure 10 This is a schematic diagram of typical STX10 immunohistochemical images of ccRCC cancer tissue and adjacent normal tissue.

[0050] Figure 11 This is a schematic diagram showing the statistical analysis results of STX10 H score between tumor tissue and adjacent normal tissue.

[0051] Figure 12 This is a schematic diagram of the Kaplan-Meier analysis results for overall survival in patients with ccRCC.

[0052] Figure 13 This is a schematic diagram illustrating the validation results of STX10 knockdown efficiency q-PCR.

[0053] Figure 14 This is a schematic diagram of the experimental results for 5-ethynyl-2-deoxyuridine.

[0054] Figure 15 This is a schematic diagram of the Transwell invasion experiment results.

[0055] Figure 16 This is a schematic diagram of the results for the top 10 significantly activated KEGG pathways.

[0056] Figure 17 This is a schematic diagram showing the results of the top 10 significantly suppressed KEGG pathways.

[0057] Figure 18 This is a schematic diagram showing the mutation landscape and copy number variation landscape between the STX10 high expression group and the low expression group.

[0058] Figure 19 This is a schematic diagram illustrating the results of the analysis of mutational differences in 20 frequently mutated genes and the mutational differences in the first 10 amplified and deleted chromosomal segments between the STX10 high expression group and the low expression group.

[0059] Figure 20A schematic diagram illustrating the results of identifying mutations associated with STX10 expression.

[0060] Figure 21 A schematic diagram showing the results of identifying CNV chromosome fragments associated with STX10 expression.

[0061] Figure 22 This diagram illustrates the results of arm gain, arm loss, local gain, and local loss between the high-expression and low-expression groups of STX10.

[0062] Figure 23 This is a schematic diagram showing the results of mutation landscape and copy number variation landscape analysis between the STX10 high expression group and the low expression group.

[0063] Figure 24 This is a schematic diagram showing the identification results of mutations related to STX10 expression.

[0064] Figure 25 Kaplan-Meier survival analysis and scatter plot for the STX10 high expression group and low expression group in the RCC 2020 cohort.

[0065] Figure 26 Kaplan-Meier survival analysis and scatter plot for the STX10 high expression group and low expression group in the Melan GSE91061 cohort.

[0066] Figure 27 Kaplan-Meier survival analysis and scatter plot were performed to compare the high and low expression groups of STX10 in the Melan GSE78220 cohort.

[0067] Figure 28 Kaplan-Meier survival analysis and scatter plot were performed to compare the high and low expression groups of STX10 in the GBM PRJNA482620 cohort. Detailed Implementation

[0068] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention.

[0069] Unless otherwise specified, the cell lines listed in this invention, including Caki-1 and 786-O, were purchased from the OriCell cell bank and cultured according to existing techniques. All cell lines were identified by short tandem repeat analysis at the China Center for Type Culture Collection (Wuhan), and the presence of mycoplasma contamination was verified using a PCR detection kit (Shanghai Biothrive Sci). All cell lines were cryopreserved in liquid nitrogen for subsequent experiments. All reagents used in this invention were commercially available.

[0070] In this invention, informed consent was obtained from all patients using clinical samples, and the relevant procedures and methods were approved by the ethics committee, complying with medical ethics requirements and the Good Clinical Practice (GCP) guidelines for drug clinical trials. All experimental procedures adhered to the Declaration of Helsinki. The experimental methods used in this invention, such as bioinformatics analysis, molecular biology experiments, cell biology experiments, and immunohistochemistry, are all conventional methods and techniques in the field. Bioinformatics analysis was performed using R software version 4.3, with the "limma" package used for differential analysis and the "survival" and "survminer" packages used for KM survival curve plotting. Representative results from biological experimental replicates are presented in the contextual figures, and data are displayed as mean ± SD and mean ± SEM as specified in the figures. All in vitro experiments were repeated at least three times, and animal experiments were repeated twice. Data were analyzed using GraphPad Prism 8.0 software. Conventional medical statistical methods such as t-tests, chi-square tests, and analysis of variance were used to compare the differences in means between two or more groups. *p < 0.05 was considered a significant difference.

[0071] Example 1

[0072] To investigate the expression and prognosis of STX10 in human cancer, RNA-seq data of 33 pan-cancer tissues from the TCGA database were obtained using the "TCGA plot R" package. The expression levels of STX10 mRNA in each sample were then obtained. Clinical data were integrated from the UCSC Xena platform, and samples were divided into normal and tumor groups for differential STX10 expression analysis. A p-value less than 0.05 was considered statistically significant. After data processing, STX10 expression data for 15 paired cancer types (normal paired samples with more than 20 tumor and normal samples each) were obtained and then divided into normal and tumor groups for differential expression analysis. Differential expression analysis showed that STX10 expression was significantly upregulated in various cancer tissues compared with normal tissues. It was higher than normal in bladder cancer (BLCA), breast cancer (BRCA), cholangiocarcinoma (CHOL), colon cancer (COAD), glioblastoma (GBM), esophageal cancer (ESCA), head and neck squamous cell carcinoma (HNSC), clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (KIRP), hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), prostate cancer (PRAD), rectal cancer (READ), pulmonary sarcomatoid carcinoma (SARC), gastric adenocarcinoma (STAD), and endometrial cancer (UCEC). However, it showed lower expression than normal in renal chromophobe carcinoma (KICH), while no significant difference was observed in other cancer types (see [link to relevant documentation]). Figure 1 For paired samples, consistent observations were made in BLCA, BRCA, COAD, ESCA, HNSC, ccRCC, KIRP, LIHC, STAD, and UCEC that STX10 expression was significantly upregulated in cancer tissues compared to paired normal tissues, while in KICH, it was downregulated in cancer tissues compared to paired normal tissues. No significant differences were observed in the remaining cancers (see [link to relevant documentation]). Figure 2 This suggests that the upregulation of STX10 expression may be associated with the occurrence of various cancers and has the potential to serve as a cancer biomarker for research.

[0073] Subsequently, univariate Cox regression analysis was performed on the processed TCGA pan-cancer cohort's TPM RNA-seq data, with overall survival (OS) and progression-free survival (PFI) as prognostic endpoints, to investigate the prognostic role of STX10 expression in pan-cancer. Specifically, transcriptome and survival data for 32 different cancer types were obtained and analyzed from the UCSC database, with prognostic endpoints including overall survival (OS) and progression-free survival (PFI). Univariate Cox regression analysis of the survival data for these cancer types showed that STX10 has different prognostic values ​​in different types of cancer. Upregulation of STX10 expression was associated with a higher risk ratio (HR) for OS or PFI in some cancers, including OS in adrenocortical carcinoma (ACC), KICH, KIRC, and LIHC, and PFI in ACC, KIRC, glioblastoma (LGG), and PRAD (see [link to relevant documentation]). Figure 3-4 In contrast, upregulation of STX10 expression was associated with lower hazard ratios (HRs) for overall survival (OS) in STAD and for prognostic precipitates (PFI) in BLCA, GBM, LUAD, and LUSC. For other cancers, no significant prognostic value was observed for STX10. These findings indicate that STX10 expression is closely associated with the prognosis of various cancers, particularly ACC and ccRCC. Upregulation of STX10 expression was associated with higher HRs for OS or PFI in both, further suggesting that STX10 has the potential to serve as a biomarker for ccRCC. Combined with the aforementioned results, STX10 expression in ccRCC was higher in cancerous tissue than in normal tissue (including paired samples, p < 0.05), while no significant statistical difference was observed in ACC. Therefore, STX10 may be considered an independent risk factor affecting various prognostic endpoints.

[0074] To validate the prognostic value of STX10 in ccRCC, transcriptomic data and clinical information from the TCGA-KIRC, ICGC-RECA-EU, and E-MTAB-1980 datasets were obtained. Samples meeting the following criteria were excluded: (1) overall survival (OS), progression-free interval (PFI), or disease-free survival (DSS) less than 30 days in the cohort; (2) PFI or DSS less than OS; and (3) formalin-fixed paraffin-embedded (FFPE) tissue samples. Finally, only tumor samples containing both RNA-Seq expression data and survival information were retained; if a patient had multiple sequencing samples, one sample was randomly retained. Analysis revealed significantly higher STX10 expression in the high-TNM stage groups of the TCGA database (TNM staging, pathological staging, Fuhrman classification, and E-MTAB-1980 dataset) (p < 0.05). While no significant difference was observed in the ICGC-RECA dataset, the trend of higher STX10 expression in the high-TNM stage group was consistent with the other two groups. The optimal cutoff value for STX10 in the five cohorts was then calculated using the "survminer" software package (0.4.9). Based on the optimal cutoff value (minprop = 0.3), samples were divided into high and low expression groups. Kaplan-Meier survival analysis was performed using the "survival" software package (3.6.4), and the log-rank test was used to compare survival differences between groups to assess the impact of STX10 gene expression on ccRCC prognosis. The results showed that the high STX10 expression group had worse OS, PFI, and DSS (see [link to relevant documentation]). Figure 5 (p < 0.05). To further evaluate the prognostic potential of STX10, univariate and multivariate Cox regression analyses were performed on the treated cohort. Univariate Cox regression analysis showed that STX10 was significant in predicting OS, PFI, and DSS (p < 0.05). Multivariate Cox regression analysis, including clinicopathological factors with p < 0.05, showed that STX10 could serve as an independent prognostic factor for ccRCC patients with OS, PFS, and DSS as endpoints (see [link to relevant documentation]). Figure 6 The above results indicate that STX10 is an independent prognostic factor for OS, PFI, and DSS in ccRCC, and the higher its expression level, the worse the patient's prognosis. In conclusion, based on the above results, STX10 can be identified as an independent prognostic risk factor for OS, PFI, and DSS in ccRCC.

[0075] Human Protein Atlas (HPA) data show that STX10 is primarily located in the Golgi apparatus and vesicles in cells (see [link to HPA data]). Figure 7 Immunofluorescence staining images provided evidence for the cellular sublocalization of STX10 (see [link]). Figure 8 To clarify the expression of STX10 in ccRCC tissues, immunohistochemical analysis was performed on tissue samples (obtained from Zhongshan People's Hospital) from 75 clear cell renal cell carcinoma samples and 75 paired adjacent normal tissue samples (cortical nephrons). The specific steps are as follows:

[0076] (1) Use a pathological tissue sectioning machine to cut the tissue into sections to a thickness of 4μm, spread them on a non-slip glass slide, and dry them at 65℃ for 2 hours for later use.

[0077] (2) Dewaxing: Immerse the glass slide in xylene I for 5 min → xylene II for 5 min → xylene III for 5 min → anhydrous ethanol I for 5 min → anhydrous ethanol II for 5 min → 95% ethanol for 5 min → 85% ethanol for 5 min → 75% ethanol for 5 min → ddH2O I for 3 min → ddH2O II for 3 min.

[0078] (3) Blocking peroxidase: Soak in 3% hydrogen peroxide for 10 min, then wash with PBS for 5 min.

[0079] (4) High-pressure antigen retrieval: Prepare EDTA retrieval solution and add it to the pressure cooker. Place the glass slide in the cooker, heat at 800W for 20 minutes, and then let it cool naturally.

[0080] (5) Wash the slide twice with PBS for 3 minutes each time. Use a small piece of paper to absorb the moisture around the tissue. Use a biochemical pen to draw circles 0.5 cm away from the tissue boundary.

[0081] (6) Oily tissue surface: Immerse the glass slide in 0.1% PBST, lift it up and down and soak for 3 minutes.

[0082] (7) Primary antibody incubation: Dilute the antibody with antibody (STX10) diluent according to the instructions, incubate at 4°C overnight with 50uL, wash with PBS for 3min, and then wash with PBST for 3min.

[0083] (8) Secondary antibody incubation: 1 drop of DAKO secondary antibody per tissue, covering the tissue surface, incubated at 37°C for 1 hour, washed with PBS for 3 minutes, and then washed with PBST for 3 minutes.

[0084] (9) Prepare DAB chromogenic solution: Prepare the chromogenic solution according to the ratio. After shaking off the liquid on the slide, add freshly prepared DAB chromogenic solution to the circle. Control the chromogenic time under the microscope. The positive result is brownish-yellow. Soak the slide in PBS to stop the chromogenic process.

[0085] (10) Counterstaining cell nuclei: After terminating DAB staining, slides were counterstained with hematoxylin for about 3 minutes, rinsed with running water, mounted with 20 μL of mounting medium, and observed under a microscope. The immunohistochemical staining intensity was analyzed using the "IHC Profiler" plugin in ImageJ software, and the expression level of STX10 in the samples was assessed using the H score method. According to the percentage of STX10 staining intensity in the sample tissue, several intensities were identified: Negative, Low Positive, Positive, and High Positive. The H score for each part was calculated as: percentage of strong staining * 3 + percentage of moderate staining * 2 + percentage of weak staining * 1.

[0086] Experimental results are as follows Figure 9-11 As shown in the figure. The results showed that, consistent with mRNA expression, STX10 protein expression was significantly higher in ccRCC samples than in adjacent normal tissues. The samples were divided into high and low groups using the optimal cutoff value of the H score (minprop=0.3), and KM survival analysis was performed with overall survival (OS) as the prognostic endpoint. The results showed that patients with high STX10 expression had a worse prognosis (see...). Figure 12 The above results further validate the potential of STX10 as a prognostic biomarker for ccRCC.

[0087] Example 2

[0088] To more precisely elucidate the role of STX10 in the biological behavior of NMIBCs, a series of in vitro functional experiments were conducted. First, two specific siRNAs targeting STX10 were designed (siSTX10-1, sequence shown in SEQ ID NO: 1 (5'-GTCCAGGAAATGAAGGACCAT-3'); siSTX10-2, sequence shown in SEQ ID NO: 2 (5'-AGCCCAACAGCCGTAGCATTT-3')) and transfected into Caki-1 and 786-O cells. The knockdown efficiency was verified by qPCR (upstream primer sequence shown in SEQ ID NO: 3, downstream primer sequence shown in SEQ ID NO: 4). The results are shown below. Figure 13As shown in the figure. The results showed that, compared with the blank vector si-NC group, the expression of STX10 in cells transfected with siSTX10-1 and siSTX10-2 was significantly inhibited (the above qPCR experiment was repeated using primer pair 2 (upstream sequence as shown in SEQ ID NO: 5, downstream sequence as shown in SEQ ID NO: 6), and the results were similar, so they will not be repeated here). Subsequently, 5-ethynyl-2-deoxyuridine assay and Transwell invasion assay were carried out using the cells with the above STX10 knockdown. The specific steps of the 5-ethynyl-2-deoxyuridine assay are as follows:

[0089] (1) Culture the cells in the logarithmic growth phase to an appropriate density in a culture plate. Replace with fresh medium containing 20 μM EdU and incubate in a CO2 incubator at 37°C for 2 hours.

[0090] (2) Remove the culture medium and wash the cells twice with PBS. Add 4% paraformaldehyde and fix at room temperature for 15-30 minutes. After washing with PBS, add 0.5% Triton X-100 and permeate at room temperature for 10-20 minutes. Wash thoroughly with PBS again.

[0091] (3) Mix the click chemistry reaction solution (containing buffer, CuSO4, fluorescent dye-azide, reducing agent, etc.) according to the proportions specified in the BeyoClick™ EdU-488 Cell Proliferation Detection Kit instructions. Add the reaction solution to the cell sample and incubate at room temperature in the dark for 30 minutes.

[0092] (4) After the reaction is complete, wash with PBS several times in the dark to remove unbound dye, and observe and record under a fluorescence microscope.

[0093] Experimental results are as follows Figure 14 As shown in the figure. The results showed that, compared with the blank vector si-NC group, the ability of bladder cancer cells to form colonies was significantly reduced after silencing the UBR5 gene with siRNA, and the colony formation of bladder cancer cells was significantly inhibited. The difference was statistically significant (*p<0.05, **p<0.01, ***p<0.001).

[0094] The specific steps of the Transwell invasion experiment are as follows:

[0095] (1) One day before the experiment, put a tube of Matrigel matrix gel that had been dispensed from -20°C into a 4°C refrigerator overnight to melt it from a solid state to a liquid state.

[0096] (2) Prepare 10% Matrigel matrix gel on ice, take 50 μL to coat the upper chamber surface of the bottom membrane of the Transwell chamber, place it at 37°C, and wait for the matrix gel to solidify for 30 min.

[0097] (3) After trypsin digestion of cells in the logarithmic growth phase, the cells are resuspended in basal culture medium to form a cell suspension, counted, and the cell density is adjusted to 1×10⁻⁶. 5 per mL.

[0098] (4) Remove and discard the basal culture medium from the small chamber and the 24-well plate. Add 200 μL of cell suspension to the upper chamber of the Transwell chamber and 600 μL of complete culture medium (basal culture medium + 10% fetal bovine serum) to the lower chamber of the 24-well plate.

[0099] (5) The culture plate was placed in a CO2 incubator at 37°C and cultured for another 48 hours.

[0100] (6) Remove the chamber, rinse twice with PBS, fix with 4% paraformaldehyde in a 24-well plate for 20 min, and stain with crystal violet solution for 15 min.

[0101] (7) Carefully wipe away the cells and matrix gel in the upper layer of the microporous membrane of the chamber with a cotton swab, and take a picture under an inverted microscope.

[0102] Experimental results are as follows Figure 15 As shown in the figure. The results showed that the number of cells migrating across the basement membrane was significantly reduced in the Transwell assay. These experiments collectively demonstrate that inhibiting STX10 expression can effectively suppress the progression of ccRCC.

[0103] Example 3

[0104] To explore the potential molecular function and biological processes involved by STX10, GSEA enrichment analysis was performed using the ClusterProfiler R package based on the correlation between STX10 and mRNA in the TCGA-KIRC dataset. Figure 16-17 Showing the top 10 activations by absolute value of normalized enrichment score (NES) in KEGG (see [link]). Figure 16 ) and inhibition (see Figure 17The study investigated the STX10 pathway, revealing that STX10-related biological processes are primarily positively regulated by pathways related to tumor development, such as ribosomes, oxidative phosphorylation, and base excision repair. It also included metabolic processes such as activation of pyrimidine metabolism, inhibition of propionic acid metabolism, fatty acid metabolism, and phosphatidylinositol metabolism. Previous research has shown that activation of the ribosome pathway leads to ribosome formation, a process also known as ribosome biosynthesis (RiBi). In tumor cells, alterations in RiBi activate nucleolar stress response-related pathways (such as mTOR and PI3K / AKT), significantly enhancing rRNA transcription and ribosome assembly efficiency to support the protein synthesis needs during cancer cell biosynthesis and metabolic activities, leading to rapid tumor proliferation. Furthermore, some studies suggest that ribosome synthesis is abnormally increased in almost all cancers; cancer may stimulate cell proliferation by enhancing ribosome biosynthesis, indicating a close relationship between ribosome pathway activation and tumorigenesis. Simultaneously, activation of the oxidative phosphorylation pathway may lead to abnormal energy metabolism, thereby promoting tumor development. Furthermore, studies across multiple cancer cohorts have revealed that overexpression of base excision repair genes is significantly associated with poor prognosis in patients with various cancers, including ccRCC. Although not directly related to renal cell carcinoma, this still suggests that abnormal BER may indirectly lead to tumor progression by affecting the tumor microenvironment or treatment resistance. Based on these results, it can be concluded that STX10 may be involved in promoting the activation of tumor cell proliferation-related pathways, thereby contributing to the development of ccRCC.

[0105] Studies have shown that high levels of somatic mutations and CNVs are associated with poorer patient survival. To clarify the molecular mechanism of STX10 in ccRCC, a mutational genomics analysis was performed on the TCGA-KIRC cohort. Specifically, in the TCGA-KIRC cohort, GISTIC2.0 (www.genepattern.org) was used to identify regions of the genome that were significantly amplified or deleted in a set of samples. The “maftools” and “ComplexHeatmap” R packages were used to visualize the top 20 most frequently mutated genes and the top 10 chromosomal segments with the highest amplification and deletion frequencies, respectively, to explore genomic differences between high and low STX10 expression groups. Furthermore, copy number variation load was reflected by the total number of copy number deletions and increases at the focal and arm levels. For the CheckMate data from the immunotherapy cohort, the same method was used to visualize the top 20 most frequently mutated genes and the top 10 chromosomal segments with the highest amplification and deletion frequencies, respectively, to explore the significance of genomic differences between high and low STX10 expression groups in immunotherapy. Fisher's exact test was used to assess the frequency differences of mutations and copy number variations between the two expression groups. The changes in STX10 expression levels between the wild-type and mutant subtypes were compared using the Wilcoxon rank-sum test.

[0106] Experimental results are as follows Figure 18-22 As shown, the results indicate that, through somatic mutation and copy number variation analysis of the TCGA-KIRC cohort, comparing the top 20 most frequently mutated genes (FMGs) between the STX10 high and low expression groups, it was found that the STX10 high expression group generally had a higher gene mutation frequency, especially the mutations in PBRM1 and SYNE1, which showed significant differences between groups, with significantly higher mutation rates in the STX10 high expression group (see [link to relevant documentation]). Figure 18-19 (p < 0.05). Furthermore, there were significant differences in the expression of PBRM1, SETD2, ATM, and SYNE1 between the mutant and wild-type groups (see [link to relevant documentation]). Figure 20 (p < 0.05). Among the top 10 amplified and top 10 deleted CNVs at the arm level, significant differences were observed in the amplification of 7q21.12 and the deletions of 3p25.3, 3p21.1, and 14q31.1 between the high and low STX10 groups (see [link to article]). Figure 19 (p < 0.05), and the expression level of STX10 also showed statistically significant differences between the mutated and non-mutated subgroups of these chromosomal segments (see [link to relevant documentation]). Figure 21 (p < 0.05). Furthermore, significant amplification and deletion were observed in both local lesions and at the arm level in the high STX10 expression group, indicating higher chromosomal instability in the STX10 high expression group (see [link to relevant documentation]). Figure 22 (p < 0.05).

[0107] The PBRM1 gene, located on the short arm of chromosome 3, is involved in cell differentiation, proliferation, and DNA repair. In clear cell renal cell carcinoma (ccRCC), the PBRM1 mutation rate is approximately 40%, and it is considered the second most common mutation gene after VHL. As a prevalent mutation in ccRCC, PBRM1 has a tumor-suppressive effect; its mutation may lead to ccRCC metastasis, and studies have directly shown that low PBRM1 expression is associated with poor prognosis. While SYNE1 is not considered a prevalent mutation gene in ccRCC, its tumor-suppressive function has been confirmed in various cancers, including ccRCC. Furthermore, SYNE1 gene silencing enhances tumor cell proliferation and migration, directly confirming its tumor-suppressive function. Based on these findings, it is speculated that high STX10 expression may increase the mutation frequency of PBRM1 and SYNE1, leading to weakened tumor-suppressive effects and thus promoting the development of ccRCC. Furthermore, significant amplification and deletion were observed in both local lesions and at the arm level in the STX10 high-expression group, indicating higher chromosomal instability (CIN). It is suggested that there is a complex association between CIN and immune escape, and tumors with high CIN may be a driver of cancer progression. In summary, patients with high STX10 expression have significant genomic alterations, representing higher genomic instability, while patients with low STX10 expression are considered to have a stable genomic subtype. In ccRCC, patients with high STX10 expression are more likely to experience immune escape, thus responding poorly to ICIs, and are associated with a more unfavorable mutational landscape.

[0108] To further investigate the association between STX10 mutation genomics and immunotherapy response, CheckMate data from the post-immunotherapy cohort were used for somatic mutation and copy number variation analysis. The results showed that in ccRCC, Von Hippel-Lindau (VHL) and BAP1 exhibited higher mutation frequencies in the STX10 high-expression group, at 66% and 18%, respectively, with significant differences between groups (see [link to study]). Figure 23 (p < 0.05). In particular, BAP1 expression was significantly higher in the mutant group than STX10 (see [reference]). Figure 24 (p < 0.05). Among the first 10 amplified and first 10 deleted CNVs at the arm level, significant differences were observed between the high and low STX10 groups in the amplification of 1q32.1 and the deletion of 14q32.33, 9q34.3, and 9p21.1, and the expression level of STX10 also showed statistically significant differences between the mutated and non-mutated subgroups of these chromosomal segments.

[0109] VHL, the tumor suppressor gene with the highest mutation frequency in ccRCC, is a major genetic event in most ccRCC cases due to its inactivation. Studies have shown that VHL mutations lead to abnormal accumulation of HIF-α (especially HIF-2α), activating downstream target genes such as VEGFA and PDGF, thereby promoting angiogenesis, cell proliferation, and metabolic reprogramming, ultimately driving ccRCC. Although VHL is the most frequently mutated gene in ccRCC, a single mutation is insufficient to cause ccRCC; it requires mutations in other genes to induce tumor development. This includes another significantly different mutated gene in this cohort, BAP1. BAP1 is also a common mutated gene in ccRCC, with a mutation frequency of approximately 10-15%. As a tumor suppressor gene, BAP1 is typically associated with higher tumor grade, risk of distant metastasis, and shorter overall survival; simultaneously, BAP1-deficient tumors are more likely to exhibit immune exhaustion and immune evasion. Therefore, BAP1 mutations usually indicate a poor prognosis for ccRCC. The above results reveal the potential molecular switch that leads to immune escape in ccRCC and explain, from a molecular perspective, the potential mechanism by which high expression of STX10 may affect the immunotherapy response and thus lead to poor prognosis in ccRCC patients, revealing potential molecular targets related to the immunotherapy response in ccRCC.

[0110] In recent years, immunotherapy has emerged as a novel treatment approach, offering new treatment options for patients with various solid tumors. This is due to the role of ccRCCs in the CD8+ pathway within the tumor microenvironment (TME). + and CD4 +The high frequency of T cell occurrence makes it a promising candidate for immune checkpoint blockade therapy (ICB). However, current ICBs are not effective for all individuals with ccRCC; more than half of the patients do not respond to immunotherapy (primary resistance) or experience disease progression after treatment (secondary resistance), and these patients often have a poor prognosis. Therefore, it is crucial to find a new indicator to determine which patients are more likely to respond to immunotherapy. The aforementioned functional enrichment analysis of STX10-related genes revealed the enrichment of the key OXPHOS pathway. Existing research suggests that activation of the OXPHOS pathway may increase tumor cell resistance to immune checkpoint inhibitors (ICIs) by regulating the tumor microenvironment or energy supply. Mutation analysis based on the TCGA-KIRC and CheckMate cohorts showed that STX10 leads to increased mutation frequencies in PBRM1, VHL, and BAP1, with statistically significant differences (p < 0.05). Furthermore, multi-omics mutation analysis showed that the high STX10 expression group had a higher copy number load, which can promote immune escape and thus lead to poor immunotherapy efficacy. These studies suggest that STX10 may also serve as a biomarker in the immunotherapy process for ccRCC. Further investigation is planned to explore whether STX10 affects immunotherapy for ccRCC.

[0111] Specifically, the RCC-Braun-anti-PD1 (renal cell carcinoma dataset), GSE91061-anti-PD1 (melanoma dataset), GSE78220-anti-PD1 (melanoma dataset), and PRJNA482620-anti-PD1 (glioblastoma dataset) datasets were obtained from the Tumor Immunotherapy Gene Expression Resource (TIGER) database to explore the predictive ability of STX10 expression on immunotherapy response in ccRCC patients. The above four datasets were processed to exclude samples that met the following conditions: (1) samples with no survival information or OS < 3 days were excluded; (2) samples with combination therapy were excluded from the cohort, and only single-drug therapy samples were retained; (3) samples before treatment (POST), after treatment (EDT), and during treatment (ON) were excluded, and only pre-treatment samples were retained; (4) samples with treatment response of Not Evaluated / NE / UNK were removed. The four processed external datasets were used to predict the response to immunotherapy. The expression level of STX10 mRNA in each sample was obtained. The optimal cutoff value of STX10 expression (minprop=0.3) was calculated using the "survminer" software package. Patients were divided into high and low groups, and Kaplan-Meier survival analysis was performed using the "survival" software package.

[0112] In the RCC-Braun-anti-PD1 dataset, Kaplan-Meier analysis showed that patients with low STX10 expression responded better to anti-PD-1 antibody therapy, while patients with high STX10 expression exhibited a statistically significant trend toward poorer prognosis; furthermore, based on STX10 expression grouping, the high STX10 expression group had a higher number of individuals with death outcomes (see [link to relevant documentation]). Figure 25 (p < 0.05). Results from the other three cohorts also showed that, even without significant differences, patients with low STX10 expression were consistent with the trend of benefiting more from anti-PD-1 therapy (see [link to study]). Figure 26-28It is noteworthy that studies have shown that tumor tissues with low PBRM1 expression are often accompanied by a reduction in CD4 cells. Combined with the aforementioned finding that PBRM1 exhibits significantly higher mutation rates in the STX10 high-expression group, this may, to some extent, explain the impaired efficacy of anti-PD-1 immunotherapy in ccRCC patients with high STX10 expression. These results indicate that high STX10 expression is associated with poor immunotherapy (anti-PD-1) outcomes, suggesting that STX10 has the potential to become a sensitive biomarker for predicting immunotherapy (anti-PD-1) response in ccRCC patients. From a practical perspective, this provides a more precise intervention target for overcoming drug resistance and a basis for exploring personalized immunotherapy strategies for ccRCC, contributing to optimized patient prognosis.

[0113] Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of the urinary tract, and some patients have metastases at the time of initial diagnosis. In recent years, immune checkpoint inhibitor therapy has shown promising results in some metastatic ccRCC patients; however, due to tumor heterogeneity and immune escape during treatment, the individual variability in immunotherapy efficacy is significant, posing a major challenge to assessing the prognosis of ccRCC. Therefore, there is an urgent need to identify more precise biomarkers for early detection, intervention, and personalized treatment of ccRCC. STX10, a member of the STX family, is associated with key processes in tumor progression, but its role in ccRCC has not been fully investigated. This invention uses bioinformatics analysis techniques and a series of in vitro experiments to elucidate the expression of STX10 in ccRCC and its potential as a biomarker for the prognosis and treatment of ccRCC.

[0114] This invention first uses pan-cancer analysis to explore the expression and prognosis of STX10 in various human malignant tumors, finding that STX10 expression is significantly upregulated in various malignant tumors, including ccRCC, compared to normal tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to verify the prognostic value of STX10 in five ccRCC cohorts. Kaplan-Meier survival analysis showed that ccRCC patients with high STX10 expression had worse OS, PFS, and DSS, while Cox regression analysis confirmed that STX10 is an independent risk factor for poor OS, PFI, and DSS in ccRCC. Subsequently, immunohistochemistry was used to verify the relationship between STX10 expression and prognosis in ccRCC tissue microarrays, and cell experiments were used to verify the role of STX10 in ccRCC proliferation and invasion. Immunohistochemical results showed that STX10 overexpression in ccRCC tumor tissue was associated with poor overall survival, while cell experiments showed that inhibiting STX10 expression effectively inhibited ccRCC proliferation and invasion. Furthermore, functional enrichment analysis, somatic mutation analysis, and copy number variation analysis were conducted to elucidate the biological functions related to STX10. GSEA enrichment analysis revealed that STX10 expression is enriched in key pathways related to tumor development, such as ribosome activation, oxidative phosphorylation, and base excision repair. Multi-omics somatic mutation and copy number variation analysis based on the TCGA-KIRC and CheckMate cohorts revealed significant differences in genomic alterations among STX10 expression subgroups, providing a multi-omics perspective for exploring the molecular mechanisms of STX10 in ccRCC. In addition, Kaplan-Meier survival analysis was performed using four external datasets to investigate the predictive ability of STX10 on immunotherapy (anti-PD-1 / PDL-1) response. The results showed that the low STX10 expression group responded well to immune checkpoint inhibitor therapy.

[0115] In summary, this invention emphasizes the crucial role of STX10 in clear cell renal cell carcinoma (ccRCC), revealing its significant upregulation. STX10 overexpression promotes ccRCC cell proliferation and migration, is an independent risk factor for poor overall survival (OS), progression-free survival (PFI), and disseminated intravascular coagulation (DSS) in ccRCC, and is closely associated with poor immunotherapy response. This invention clarifies that STX10 can serve as a prognostic biomarker and therapeutic target for ccRCC. Inhibiting STX10 or reducing its biological activity can significantly suppress renal cell carcinoma development, prolong patient survival, and improve prognosis. This invention enriches our understanding of the relevant molecular mechanisms in the development and progression of renal cell carcinoma, providing ample scientific evidence and theoretical foundation for exploring new molecular targets for renal cell carcinoma diagnosis, prognosis, and treatment, and developing new targeted drugs. It contributes to achieving better precision medicine and has significant social and scientific value.

[0116] The above detailed embodiments provide a specific description of the analytical methods involved in this invention. It should be noted that the above description is only intended to help those skilled in the art better understand the methods and ideas of this invention, and is not intended to limit the scope of the invention. Without departing from the principles of this invention, those skilled in the art can make appropriate adjustments or modifications to this invention, and such adjustments and modifications should also fall within the protection scope of this invention.

Claims

1. Application of STX10 inhibitors in the preparation of drugs for the prevention and / or treatment of renal cell carcinoma.

2. The application according to claim 1, characterized in that, The STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

3. Application of reagents for detecting STX10 expression levels in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of renal cell carcinoma.

4. The application according to claim 3, characterized in that, The reagents for detecting STX10 expression levels include primers for detecting STX10 gene expression levels and / or reagents for detecting STX10 protein content.

5. The application according to claim 4, characterized in that, The primers used to detect the STX10 gene expression level were selected from the following primer pairs: Primer pair 1: The upstream sequence is shown in SEQ ID NO: 3, and the downstream sequence is shown in SEQ ID NO: 4; Primer pair 2: The upstream sequence is shown in SEQ ID NO: 5, and the downstream sequence is shown in SEQ ID NO:

6.

6. The application according to claim 4, characterized in that, The reagent used to detect the STX10 protein content was selected from anti-STX10 Antibody.

7. Application of STX10 inhibitors in the preparation of drugs that enhance the sensitivity of anti-PD-1 antibodies to renal cell carcinoma treatment.

8. The application according to claim 7, characterized in that, The STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

9. A pharmaceutical composition for the prevention and / or treatment of renal cell carcinoma, characterized in that, This includes STX10 inhibitors, anti-PD-1 antibodies, and pharmaceutically acceptable excipients.

10. The pharmaceutical composition according to claim 9, characterized in that, The STX10 inhibitor is selected from one or more of siRNA, shRNA, and sgRNA designed based on the STX10 gene.

Images