Identification of T cell exhaustion-related genes in clear cell renal cell carcinoma and construction of a prognostic model

Background: T cell exhaustion (TEX) is associated with tumor progression and the efficacy of immunotherapy. The aim of this study is to investigate TEX-related genes in clear cell renal cell carcinoma(ccRCC), identify their key genes, and construct a prognostic model based on TEX-related genes. Method: Tumor and normal samples of ccRCC were obtained from TCGA. WGCNA was employed to screen TEX-related genes, while MCODE was used to filter hub genes. Analysis of hub gene differential expression between tumor and normal tissues was conducted alongside immune cell correlation assessments. Renal cancer patients were stratified into two subgroups via clustering analysis, enabling comparison of TEX-related gene expression and immune cell infiltration between these groups. Subsequently, a prognostic model was constructed using lasso regression analysis, evaluating the correlation between risk scores, clinical features, immunotherapeutic efficacy, and IC50 of chemotherapy drugs. External validation of the model was performed using ICGC datasets. Results: ： In our study, we identified 5 hub genes among 185 TEX-related genes in ccRCC, all of which exhibited a positive correlation with T cell infiltration. The high expression subgroup of TEX- related genes displayed lower survival rates compared to the low-expression subgroup. Our developed prognostic model effectively predicts overall patient survival, demonstrating high accuracy via ROC curve analysis. Additionally, increased risk scores were associated with poorer clinical features, diminished immunotherapeutic efficacy, and higher IC50 values for chemotherapy drugs. Conclusion: The TEX-related genes we identified may potentially serve as novel targets for the treatment of advanced-stage renal cancer. Moreover, the TEX-related prognostic model could serve as an effective tool for predicting outcomes in renal cancer patients.