Abstract: Objective To screen the potential key candidate genes in clear cell renal cell carcinoma (ccRCC) by bioinformatical analysis and to confirm its expression level between ccRCC tissue and normal renal tissue. Methods Differentially expressed genes (DEGs) were identified, functional and pathway enrichment analysis were performed and DEGs-associated protein–protein interaction network (PPI) was constructed. Real-Time PCR, Western blot and Immunohistochemistry analysis were used to detect the expression level of one of the DEGs in ccRCC tissue and normal renal tissue. The results were validated from transcription level and survival analysis by TCGA database. Results GATA3 was screened by bioinformatical analysis. The results showed that GATA3 was downregulated in ccRCC tissue samples(P<0.01). The TCGA database data showed that the expression level of GATA3 in ccRCC samples was significantly lower than the normal samples(P<0.01) and the survival outcome of low expression GATA3 patients is significantly lower than the high expression patients(P<0.05). Conclusion Bioinformatical analysis could improve our understanding of the cause and underlying molecular events, the candidate gene GATA3 could be used for new therapeutic targets and diagnostic targets of ccRCC.

Key words: cell renal cell carcinoma, bioinformatical analysis, differentially expressed genes, GATA3, gene expression