Integrative Bioinformatics Analysis for Investigating Potential Genes of Prostate Cancer

Globally, prostate cancer (PCa) is among the most malignant diseases for men. This study aims to find out putative genes for PCa. To find differentially expressed genes (DEGs), we examined three microarray datasets that are freely accessible. We found 458 common DEGs (cDEGs) by LIMMA, an R package. To create the protein–protein interaction (PPI) network, we mapped these genes to STRING database and from the constructed PPI network we extracted the top 15 hub genes (HubGs), namely, TOP2A, RRM2, NCAPG, BUB1B, CENPU, CENPF, AURKA, TPX2, MKI67, BIRC5, CDCA5, NUSAP1, EZH2, ECT2, and TK1. These 15 hub genes were used to perform gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies which revealed strong associations with key functions and signaling pathways in patients with PCa. Patients with lower expressions of the five hub genes BIRC5, CDCA5, CENPF, NUSAP1, and TK1 had higher survival rates. These genes may serve as potential biomarkers for PCa prognosis.