T-Cell Exhaustion-Related Gene Signatures Predict Clinical Outcomes and Immunotherapy Response in Kidney Renal Clear Cell Carcinoma

T-cell exhaustion (TEX) is a crucial immune escape mechanism and a pathway of resistance in cellular immunotherapy, yet its prognostic role in kidney renal clear cell carcinoma (KIRC) remains unclear. This study analyzed 518 KIRC patients from the TCGA dataset, identifying TEX-related genes through Gene Set Variation Analysis (GSVA) and Weighted Gene Co-Expression Network Analysis (WGCNA). Using survival random forest and LASSO-Cox analyses, eight differentially expressed genes (RUFY4, NOD2, IL15RA, CXCL13, GBP5, DERL3, SPIB, and SLCO5A1) were selected to construct a TEX risk model. Functional analyses, including GO, KEGG, GSEA, CIBERSORT, and ssGSEA, explored the relationship between TEX risk scores and signaling pathways and immune cell infiltration. The IMvigor210 dataset evaluated the correlation between TEX risk scores and immunotherapy response, while single-cell data analysis and qRT-PCR validated the expression of a key TEX gene. The TEX risk model demonstrated accurate prognostic prediction for KIRC patients, serving as a new independent prognostic factor. GSEA results highlighted the enrichment of tumor proliferation, migration, and immunity functions within the model. TEX features were associated with immune cell infiltration and specific immune checkpoints, effectively predicting clinical responses to immunotherapy. Thus, TEX signatures are pivotal in clinical decision-making for KIRC, helping to distinguish patients and guide treatment strategies for maximum benefit.