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To screen for marker genes associated with to the metastasis of prostate cancer (PCa), in silico analysis of the Gene Expression Omnibus dataset GSE27616, which included 4 metastatic and 5 localized PCa tissue samples, was performed. Differentially expressed genes (DEGs) were identified. Their potential functions were identified by Gene Ontology and Kyoto Encyclopedia of Gene Genomes pathway enrichment analyses. Furthermore, protein-protein interaction (PPI) networks for DEGs were constructed using Cytoscape. Module analysis of the PPI networks was performed with Cluster ONE. A total of 561 DEGs were screened, including 208 upregulated and 353 downregulated genes. Proliferating cell nuclear antigen ( PCNA ) and cluster of differentiation 4 ( CD4 ) exhibited the highest degrees of connectivity in the PPI networks for up- and down-regulated DEGs, respectively. The DEGs in module A, including CD58 , 2 , 4 and major histocompatibility complex, class II DP-β1 were enriched in 'cell adhesion molecules'. Anaphase promoting complex subunit 4, cell division cycle 20 and cell division cycle 16 in module B were primarily enriched in 'cell cycle'. The DEGs, including CD4, PCNA and baculoviral IAP repeat containing 5, may have critical roles in PCa metastasis and could thus be used as novel biomarker candidates for metastatic PCa. However, further studies are required to verify these results.

Identification of candidate genes that may contribute to the metastasis of prostate cancer by bioinformatics analysis