Identification of potential crucial genes associated with carcinogenesis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common genitourinary malignancy with high mortality. However, the molecular pathogenesis of ccRCC remains unclear and effective biomarkers for daily practice are still limited. Thus, we aimed to identify the potential crucial genes and pathways associated with carcinogenesis of ccRCC and further analyze the molecular mechanisms implicated in tumorigenesis. In the present study, expression profiles GSE 66270, GSE 53757, GSE 36895, and GSE 76351 were downloaded from GEO database, including 244 matched primary and adjacent normal tissues, furthermore, the level 3 RNAseq dataset (RNAseqV2 RSEM) of KIRC was also downloaded from The Cancer Genome Atlas (TCGA), which consist of 529 ccRCC tumors and 72 normal tissues. Then, differentially expressed genes (DEGs) and pathway enrichment were analyzed by using R software. A total of 129 up‐ and 123 down‐regulated genes were identified, which were aberrantly expressed both in GEO and TCGA data. Second, Gene ontology (GO) analyses revealed that most of the DEGs were significantly enriched in integral component of membrane, extracellular exosome, plasma membrane, cell adhesion, and receptor binding. Signaling pathway analyses indicated that DEGs had common pathways in signal transduction, metabolism, and immune system. Third, hub genes were identified with protein‐protein interaction (PPI) network, including PTPRC, TGFB1, EGF, MYC, ITGB2, CTSS, FN1, CCL5, KNG1, and CD86. Additionally, sub‐networks analyse was also performed by using MCODE plugin. In conclusion, the novel DEGs and pathways in ccRCC identified in this study may provide new insight into the underlying molecular mechanisms that facilitates RCC carcinogenesis. In the present study, RNAseq dataset from TCGA and 4 microarray data from GEO were integrated and deeply analyzed by using bioinformatic approach. A total of 252 differentially expressed genes and 10 hub genes were identified in ccRCC, ontology, and signaling pathway analyses were also performed. The results may provide new insight into the underlying molecular mechanisms that facilitates RCC carcinogenesis.