Integrative genomic and bioinformatic prioritization of drug repurposing candidates for prostate cancer

Abstract

Abstract Objective Prostate cancer remains a prevalent global health challenge, with limited treatment options for advanced stages. There is a critical need to identify effective therapies through systematic integration of genomic and biological data. Methods We analyzed 10,911 single nucleotide polymorphisms (SNPs) in 554 genes from genome- and phenome-wide association studies to identify biological risk genes for prostate cancer. Bioinformatic analysis was used to map these genes to key pathways and potential drug targets. Drug repurposing opportunities were assessed through Connectivity Map (CMap) transcriptomic signature analysis in the PC3 prostate cancer cell line, with additional molecular docking studies to evaluate drug-target interactions. Results We identified 77 prostate cancer-associated genes. Drug repurposing analysis revealed 59 drugs targeting 13 genes, including 11 approved for prostate cancer and 22 in clinical or preclinical development. Notably, 26 candidate drugs had not been previously linked to prostate cancer. CMap analysis prioritized five candidates: estradiol-benzoate and estradiol-cypionate (targeting ESR2), which showed the highest CMap scores, danazol and oxymetholone (targeting AR), and selumetinib (targeting MAP2K1/MEK), each demonstrating potential to modulate key pathways in prostate cancer. Molecular docking analysis further supported these findings, revealing that estradiol-benzoate and estradiol-cypionate have strong predicted binding affinities for ESR2, while selumetinib robustly interacts with MAP2K1. Conversely, danazol and oxymetholone displayed weaker predicted binding, suggesting a more limited capacity for direct protein engagement. Conclusions Integrating genomics, bioinformatics, and molecular docking provides an effective strategy for identifying and prioritizing drug repurposing candidates in prostate cancer. Estradiol-benzoate, estradiol-cypionate, and selumetinib emerge as promising candidates, meriting further preclinical and clinical evaluation for advanced prostate cancer therapy.

Keywords

• Prostate cancer
• Germline variants
• Drug repurposing
• Drug target genes
• Bioinformatics
• ESR2 and MAP2K1