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The present study aimed to screen potential genes associated with metastatic prostate cancer (PCa), in order to improve the understanding of the mechanisms underlying PCa metastasis. The GSE3325 microarray dataset, which was downloaded from the Gene Expression Omnibus database, consists of seven clinically localized PCa samples, six hormone-refractory metastatic PCa samples and six benign prostate tissue samples. The Linear Models for Microarray Data package was used to identify differentially-expressed genes (DEGs) and a hierarchical cluster analysis for DEGs was performed with the pheatmap package. Furthermore, potential functions for the DEGs were predicted by a functional enrichment analysis. Subsequently, microRNAs (miRNAs) potentially involved in the regulation of PCa metastasis were identified by WebGestalt software, and the miRNA-DEG regulatory network was visualized using Cytoscape. In addition, a pathway enrichment analysis for DEGs in the regulatory network was performed. A total of 306 and 2,073 genes were differentially expressed in the clinically localized PCa and the metastatic PCa groups, respectively, as compared with the benign prostate group, of which 174 were differentially expressed in both groups. A number of the DEGs, including CAMK2D and SH3BP4 , were significantly enriched in the cell cycle, and others, such as MAF , were associated with the regulation of cell proliferation. Furthermore, some DEGs ( CAMK2D and PCDH17 ) were observed to be regulated by miR-30, whereas others ( ADCY2 , MAF , SH3BP4 and PCDH17 ) were modulated by miR-182. Additionally, ADCY2 and CAMK2D were distinctly enriched in the calcium signaling pathway. The present study identified novel DEGs, including ADCY2 , CAMK2D , MAF , SH3BP4 and PCDH17 , that may be involved in the metastasis of PCa.

Investigation of the molecular mechanisms underlying metastasis in prostate cancer by gene expression profiling