Abstract
The aim of the present study was to investigate the pathogenesis of metastatic prostate carcinoma, to find the metabolic pathways changed in the disease and to screen out the potential therapeutic drugs. GSE38241 was downloaded from Gene Expression Omnibus; the Geoquery package was applied to preprocessed expression profiling, and the differentially-expressed genes (DEGs) were selected with limma (linear regression model packages). Next, WikiPathways cluster analysis was performed for DEGs on a Gene Set Analysis Toolkit V2 platform, and DEGs with hypergeometric algorithms were calculated through gene set enrichment analysis. A total of 1,126 DEGs were identified between the normal prostate and metastatic prostate carcinoma. In addition, KPNA4, SYT1, PLCB1, SPRED1, MBNL2, RNF165, MEF2C, MBNL1, ZFP36L1 and CELF2, were found to be likely to play significant roles in the process of metastatic prostate carcinoma. The small molecules STOCK1N-35874 and 5182598 could simulate the state of normal cells well, while the small molecules MS-275 and quinostatin could simulate the state of metastatic prostate carcinoma cells. In conclusions, the small molecules STOCK1N-35874 and 5182598 were identified to be good potential therapeutic drugs for the treatment of metastatic prostate carcinoma, while the two small molecules MS-275 and quinostatin could cause metastatic prostate carcinoma.
Keywords:
differentially expressed genes; metastatic prostate carcinoma; microRNA; small molecules.