Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Abstract

AbstractClear cell renal cell carcinoma (ccRCC) is an immunogenic tumor and investigating the immunorelated genes is of great significance. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, a immunoprognosis model was constructed to identify 4 hub genes with moderate predictive values for the prognosis of ccRCC patients. Interestingly, these 4 genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltrate and could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of 3 hub genes were associated with tumor progression (P<0.1). In conclusion, 4 genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.