Identification of potential bladder cancer drug targets through Mendelian randomization and molecular docking.

Bladder cancer is a common and lethal malignancy with high treatment costs due to frequent recurrence and prolonged therapy. Despite therapeutic advances, many patients develop drug-resistant metastatic disease, underscoring the need for new treatments. Using the STROBE-MR guidelines, we performed Mendelian randomization with cis- expression quantitative trait loci (eQTLs) from the eQTLGen Consortium (n = 31,684) as exposures. Two independent cohorts served as discovery and replication sets for target identification. Drug prediction and molecular docking were applied to validate the targets. Twelve significant drug targets were identified. Phenome-wide association study revealed additional associations of NDST1 and HMGCR with proteomic traits and health service use, respectively. Molecular docking confirmed strong binding for available protein structures. Our study identified 12 promising drug targets for bladder cancer and suggests that MR-based prioritization may improve clinical trial success and reduce development costs.