Microarray analysis of copy-number variations and gene expression profiles in prostate cancer

BACKGROUND: This study aimed to identify potential prostate cancer (PC)-related variations in gene expression profiles. METHODS: Microarray data from the GSE21032 dataset that contained the whole-transcript and exon-level expression profile (GSE21034) and Agilent 244K array-comparative genomic hybridization data (GSE21035) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and copy-number variations (CNVs) were identified between PC and normal tissue samples. Coexpression interactions of DEGs that contained CNVs (CNV–DEGs) were analyzed. Pathway enrichment analysis of CNV–DEGs was performed. Drugs targeting CNV–DEGs were searched using the Drug–Gene Interaction database. RESULTS: In total, 679 DEGs were obtained, including 182 upregulated genes and 497 downregulated genes. A total of 48 amplified CNV regions and 45 deleted regions were determined. The number of CNVs at 8q and 8p was relatively higher in PC tissue. Only 16 DEGs, including 4 upregulated and 12 downregulated genes, showed a positive correlation with CNVs. In the coexpression network, 3 downregulated CNV–DEGs, including FAT4 (FAT atypical cadherin 4), PDE5A (phosphodiesterase 5A, cGMP-specific), and PCP4 (Purkinje cell protein 4), had a higher degree, and were enriched in specific pathways such as the calmodulin signaling pathway. Five of the 16 CNV–DEGs (e.g., PDE5A) were identified as drug targets. CONCLUSION: The identified CNV–DEGs could be implicated in the progression of human PC. The findings could lead to a better understanding of PC pathogenesis.