Identification of key molecules for castration resistance prostate cancer by bioinformatic analysis

Background: Castration resistance prostate cancer (CRPC) is a complex tumor associated with high mortality. To discover key molecules in CRPC, we dissected the data of CRPC based on arrays by bioinformatic analysis. Methods: The gene expression profiling datasets of prostate cancer were analyzed online. The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david.ncifcrf.gov/) was used to perform Gene Ontology (GO) functional and KEGG pathway enrichment analyses. Molecular Complex Detection (MCODE) in Cytoscape software (Cytoscape_v3.6.1) was applied to screen hub genes. Gene expression data were obtained from the ONCOMINE website (https://www.oncomine.org/). The gene expression and survival data were downloaded and analyzed. Results: 4 datasets (GSE104935, GSE120005, GSE78201, and GSE21887) were included for analysis. The 15 overlap up-regulated genes and 27 overlap down-regulated genes were identified and analyzed by DAVID. 11 proteins corresponding to genes (ELOVL6, ABCA1, FOXO3, and TNRC6B; ALDH1A3, OSBPL8, ACSL3, SLC45A3, KLK2, FKBP5, and PMEPA1) were identified to be key genes. Gene expression suggested OSBPL8, PMEPA1, and SLC45A3 were different expressed in CRPC patients, these genes were also associated with survival. Conclusions: OSBPL8, PMEPA1, and SLC45A3 were involved with CRPC. These candidate genes were rarely researched, their functions needed experiments in vivo and in vitro to verify.