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Unveiling the association between HMG-CoA reductase inhibitors and bladder cancer: a comprehensive analysis using Mendelian randomization, animal models, and transcriptomics

The Pharmacogenomics Journal volume 24, Article number: 24 (2024) Cite this article

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Abstract

This study utilized Mendelian randomization (MR) analysis and genome-wide association study (GWAS) data to investigate the association between commonly prescribed drugs and bladder cancer (BLCA) risk. Our results revealed that HMG CoA reductase (HMGCR) inhibitors, specifically simvastatin, are significantly associated with reduced BLCA risk. We further showed that simvastatin could significantly inhibit BLCA proliferation and epithelial-mesenchymal transition in animal models, with transcriptomic data identifying several pathways associated with these processes. Higher expression of HMGCR were linked with BLCA development and progression, and certain blood lipids, such as lipoprotein particles and very low density lipoprotein (VLDL) cholesterol, might influence BLCA risk. These findings suggested that HMGCR inhibitors, particularly simvastatin, could be potential treatment options or adjuvant therapies for BLCA.

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Fig. 1: Associations between 23 types of drugs and BLCA risk.
Fig. 2: Associations between different types of statins and BLCA risk.
Fig. 3: Simvastatin inhibited BLCA growth in vivo.
Fig. 4: Mechanisms of the effect of simvastatin on BLCA analyzed by transcriptomic analyses.
Fig. 5: The HMGCR mRNA level was correlated with the malignancy and prognosis of patients with BLCA.
Fig. 6: Associations between blood lipids and BLCA risk.
Fig. 7: Schematic illustration of the study.

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Data availability

The transcriptomic data have been uploaded in the GEO database under the accession number GSE270394. The GSE215949, GSE149566, and GSE13507 datasets were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/gds). The remaining data can be accessed in the article or Supplementary information.

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Acknowledgements

We thank Wu et al., Kettunen et al., Global Lipid Genetics Consortium, UK Biobank, FinnGen consortium for providing GWAS data. The excellent technical assistance of Shenjuan Li, Zilin Xu and Yuanyuan Xing at Zhongnan Hospital of Wuhan University is gratefully acknowledged. We also gratefully thank the exceptional assistance in editing diagram by Dr. Yuruo Chen. This study was supported by the grants from the National Natural Science Foundation of China (81902603), the Fundamental Research Funds for the Central Universities (4206-413100049, 2042022dx0003), and the Research Fund of Zhongnan Hospital of Wuhan University (YYXKNLJS2024001, PTPP2024001, RLYC2024001001).

Author information

Author notes

  1. These authors contributed equally: Houyi Wei, Zhilong Li.

Authors and Affiliations

  1. Department of Urology, Hubei Key Laboratory of Urological Diseases, Zhongnan Hospital of Wuhan University, Wuhan, China

    Houyi Wei, Zhilong Li, Gang Wang & Xinghuan Wang

  2. Department of Biological Repositories, Human Genetic Resource Preservation Center of Hubei Province, Zhongnan Hospital of Wuhan University, Wuhan, China

    Kaiyu Qian, Lingao Ju, Danni Shan, Mengxue Yu, Yayun Fang, Yu Xiao & Gang Wang

  3. Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China

    Wenzhi Du

  4. Euler Technology, ZGC Life Sciences Park, Beijing, China

    Yi Zhang

  5. Center for Quantitative Biology, School of Life Sciences, Peking University, Beijing, China

    Yi Zhang

  6. Medical Research Institute, Frontier Science Center of Immunology and Metabolism, Wuhan University, Wuhan, China

    Xinghuan Wang

Authors
  1. Houyi Wei
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  2. Zhilong Li
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  3. Kaiyu Qian
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  4. Wenzhi Du
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  5. Lingao Ju
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  6. Danni Shan
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  7. Mengxue Yu
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  8. Yayun Fang
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  9. Yi Zhang
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  10. Yu Xiao
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  11. Gang Wang
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  12. Xinghuan Wang
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Contributions

H.W., G.W., Z.L., W.D., Y.X. and X.W. designed the study and wrote the manuscript. H.W., G.W., Z.L., L.J., D.S., M.Y., Y.F., and Y.Z. collected the data and performed the experiments. H.W., G.W., Z.L., W.D., K.Q., and Y.Z. performed the data analysis and interpretation. All authors have read and approved the manuscript.

Corresponding authors

Correspondence to Yu Xiao, Gang Wang or Xinghuan Wang.

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Wei, H., Li, Z., Qian, K. et al. Unveiling the association between HMG-CoA reductase inhibitors and bladder cancer: a comprehensive analysis using Mendelian randomization, animal models, and transcriptomics. Pharmacogenomics J 24, 24 (2024). https://doi.org/10.1038/s41397-024-00346-x

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