Bioinformatics and system biology approaches for identifying potential therapeutic targets for prostate cancer

Abstract

Prostate cancer (PCa) is the primary cause of cancer-related deaths among men, and its incidence increases with age. Despite the availability of treatments, the high costs and complications associated with current cancer therapies pose challenges. Therefore, there is an urgent need to explore globally accessible and effective alternative medications to support prostate cancer treatment. Bioinformatics and system biology approaches were utilized to investigate repurposed medicines for prostate cancer treatment guided by host genomic biomarkers. The investigation identified 120 common differentially expressed genes (DEGs) and 24 hub genes (HubGs) as potential therapeutic targets by analyzing gene expression patterns and protein-protein interaction (PPI) networks. The top 10 hub genes CDK1, CCNA2, RRM2, ASPM, MELK, HJURP, DLGAP5, NCAPG, TTK, and HMMR are associated with the development and progression of prostate cancer. The DEGs enrichment analysis revealed significant axon guidance, cell-cell adhesion, extracellular space, and calcium signaling pathways associated with prostate cancer. Gene regulatory network analysis revealed transcription factors (FOXC1, GATA2 and E2F1 etc.) and micro-RNAs (hsa-mir-16–5p, hsa-mir-24–3p and hsa-mir-34a-5p etc.) as regulators of hub genes. The potential drug candidates, includingindirubin-3′-Monoxime (−7.7 kcal/mol), benzene sulfonamide (−8.8 kcal/mol), and cladribine (−6.6 kcal/mol) have been identified as the top 3 candidate drugs against CDK1, CCNA2 and RRM2, respectively. Besides, these drugs exhibit strong binding affinity with the target proteins and suggest their potential for repurposing in the treatment of prostate cancer. Collectively, the findings present valuable insights for advancing prostate cancer research, potentially leading to a deeper understanding and novel treatment strategies for relevant diseases.