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.

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Publication Details

Journal
Discover Oncology
Published
2025-11-26
DOI
https://doi.org/10.1007/s12672-025-03929-7
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Yapeng Xing, Bing Tian Zhao, Yunchao Huang, Kai Li et al.
Discover Oncology
Genetic Associations and Epidemiology
article

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

Yapeng Xing, Bing Tian Zhao, Yunchao Huang, Kai Li, Libo Yang, Chengwei Bi, Yuanpeng Duan, Wei Luo, Guoying Zhang, Yong Yang, Liang Yu, Yuanlong Shi
article en

Abstract

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.

Discover OncologyVol. 16(1)
Peking University (CN), Kunming Medical University (CN), First Affiliated Hospital of Kunming Medical University (CN)
National Natural Science Foundation of China, Kunming Medical University, Yunnan Provincial Science and Technology Department
Openalex Percentile: Top 61%
Genetic Associations and Epidemiology
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