PURPOSE: This study aimed to identify genetic targets linked to prostate cancer risk using advanced genetic analysis techniques. OBJECTIVE: The goal was to conduct a comprehensive analysis using Mendelian Randomization (MR), colocalization, and single-cell RNA sequencing to identify druggable genes as potential therapeutic targets or diagnostic markers. METHODS: The study involved selecting 2608 druggable genes by intersecting expression Quantitative Trait Loci (eQTLs) with druggable genome databases. MR analysis using prostate cancer GWAS data identified genes with causal associations to prostate cancer risk. Colocalization analysis confirmed shared genetic variants influencing both the exposure and outcome. Single-cell RNA sequencing assessed gene expression in prostate tumor cell types, while a phenome-wide association study (PheWAS) evaluated potential side effects. RESULTS: MR analysis identified 58 genes associated with prostate cancer risk, with 12 validated by colocalization analysis. Five genes (BAK1, ATP1B2, PEMT, TPM3, ZDHHC7) demonstrated strong colocalization, indicating potential as drug targets. Single-cell RNA sequencing revealed their enrichment in prostate tumor T cells and macrophages. PheWAS suggested minimal side effects for most, except BAK1, which was linked to increased platelet counts. CONCLUSION: This study identified several genetic targets associated with prostate cancer risk, highlighting the potential for targeted therapy. By integrating Mendelian randomization analysis, colocalization analysis, and single-cell RNA sequencing, the accuracy of target validation was improved, which may provide new directions for targeted therapy in prostate cancer.