Identification of potential biomarkers and candidate therapeutic drugs for clear cell renal cell carcinoma by bioinformatic analysis and reverse network pharmacology.

This study aims to analyze the potential biomarkers using bioinformatics technology, explore the pathogenesis, and investigate potential Chinese herbal ingredients for the Clear cell renal cell carcinoma (ccRCC), which could provide theoretical basis for early diagnosis and effective treatment of ccRCC. The gene expression datasets GSE6344 and GSE53757 were obtained from the Gene Expression Omnibus database to screen differentially expressed genes (DEGs) involved in ccRCC carcinogenesis and disease progression. Enrichment analyses, protein-protein interaction networks construction, survival analysis and herbal medicines screening were performed with related software and online analysis platforms. Moreover, network pharmacology analysis has also been performed to screen potential target drugs of ccRCC and molecular docking analysis has been used to validate their effects. Total 274 common DEGs were extracted through above process, including 194 up-regulated genes and 80 down-regulated genes. The enrichment analysis revealed that DEGs were significantly focused on multiple amino acid metabolism and HIF signaling pathway. Ten hub genes, including FLT1, BDNF, LCP2, AGXT2, PLG, SLC13A3, SLC47A2, SLC22A8, SLC22A7, and SLC13A3, were screened. Survival analysis showed that FLT1, BDNF, AGXT2, PLG, SLC47A2, SLC22A8, and SLC12A3 were closely correlated with the overall survival of ccRCC, and AGXT2, SLC47A2, SLC22A8, and SLC22A7 were closely associated with DFS. The potential therapeutic herbs that have been screened were Danshen, Baiguo, Yinxing, Huangqin and Chuanshanlong. The active compounds which may be effective in ccRCC treatment were kaempferol, Scillaren A and (-)-epigallocatechin-3-gallate.