Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma whose pathogenesis is not well understood. We aimed at identifying novel immune-related biomarkers that could be valuable in the diagnosis and prognosis of ccRCC.
The Robust Rank Aggregation (RRA) method was used to integrate differently expressed genes (DEGs) of 7 Gene Expression Omnibus (GEO) datasets and obtain robust DEGs. Weighted gene co-expression network analyses (WGCNA) were performed to identify hub genes associated with clinical traits in The Cancer Genome Atlas (TCGA) database. Comprehensive bioinformatic analyses were used to explore the role of hub genes in ccRCC.
Four hub genes IFI16, LMNB1, RHBDF2 and TACC3 were screened by the RRA method and WGCNA. These genes were found to be up-regulated in ccRCC, an upregulation that could be due to their associations with late TNM stages and tumor grades. The Receiver Operating Characteristic (ROC) curve and Kaplan-Meier survival analysis showed that the four hub genes had great diagnostic and prognostic values for ccRCC, while Gene Set Enrichment Analysis (GSEA) showed that they were involved in immune signaling pathways. They were also found to be closely associated with multiple tumor-infiltrating lymphocytes and critical immune checkpoint expressions. The results of Quantitative Real-time PCR (qRT-PCR) and immunohistochemical staining (IHC) analysis were consistent with bioinformatics analysis results.
The four hub genes were shown to have great diagnostic and prognostic values and played key roles in the tumor microenvironment of ccRCC.