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.