Construction of Cuproptosis-Related Gene Prognostic Model and Immune Infiltration Analysis in Chromophobe Renal Cell Carcinoma

Objective To investigate the expression characteristics of cuproptosis-related genes in chromophobe renal cell carcinoma (ChRCC) and their potential value in prognostic assessment and immune regulation, to construct a cuproptosis-related risk score model based on the single TCGA-KICH cohort, and to preliminarily explore its reference value in prognostic stratification.

Methods Transcriptomic data and clinical information of ChRCC patients in the TCGA-KICH cohort were analyzed to screen cuproptosis-related differentially expressed genes, and pathway enrichment analysis was performed to clarify their potential biological functions. Random forest and multivariate Cox regression analyses were used to identify key genes, construct a prognostic risk score model, and develop a nomogram. CIBERSORT was used to evaluate differences in immune cell infiltration between different risk groups, and correlations between key cuproptosis-related genes and immune checkpoint expression were analyzed.

Results Cuproptosis-related genes, including SLC31A1, DLAT, PDHA1, DLD, ATP7A, CDKN2A, GLS, and LIPT1, were identified and were mainly enriched in pathways such as the tricarboxylic acid (TCA) cycle and fatty acid metabolism. A prognostic risk score model was constructed based on the three core genes ATP7A, GLS, and LIPT1, and the model showed a certain discriminatory ability in the internal cohort. Immune analysis showed that the proportions of some immune cell infiltrates differed between risk groups, and the expression of key genes was negatively correlated with the immune checkpoint programmed death-ligand 1 (PD-L1), indicating that the cuproptosis pathway may be potentially associated with changes in the tumor immune microenvironment.

Conclusion Key cuproptosis-related genes showed characteristic differential expression patterns in ChRCC, with ATP7A significantly upregulated and GLS and LIPT1 significantly downregulated. The risk score model constructed based on these genes showed a certain potential for prognostic assessment in this cohort and may provide preliminary reference for risk stratification research in ChRCC patients, but its accuracy still requires further validation in future large-scale cohorts.