Despite the increasing importance and status of immune checkpoint blockade (ICB), little is known about the underlying molecular mechanisms determining the target clear cell renal cell carcinoma (ccRCC) population. In this study, we screened out 6 immune cells strongly correlated with expression levels of PD-L1 and IFN-γ based on the ccRCC samples extracted from GSE and TCGA data sets. By performing unsupervised clustering and lasso regression analysis, we grouped the ccRCC into 4 clusters and selected the two most distinct sub-clusters for further investigation-cluster A1 and B1. Next, we compared the two clusters in terms of mRNA, somatic mutations, copy number variations, DNA methylation, miRNA, lncRNA and constructed the differentially expressed genes (DEGs) hub by combing together the previous results at levels of DNA methylation, miRNA, and lncRNA. PTPRG and CHL1 were identified as key nodes in the regulation hub of immunophenotypes in ccRCC patients. Finally, we established the prognosis model by using Lasso-Cox regression and Kaplan-Meier analysis, recognizing WNT2, C17orf66, and PAEP as independent significant risk factors while IRF4 as an independent protective factor.
Keywords: bioinformatics; ccRCC kidney cancer; immunophenotype; multi-omics study; prognosis model.
Copyright © 2022 Zeng, Li, Hu and Peng.