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Computational pharmacogenomic screen identifies drugs that potentiate the anti-breast cancer activity of statins

Author

Listed:
  • Jenna E. Leeuwen

    (University of Toronto
    University Health Network)

  • Wail Ba-Alawi

    (University of Toronto
    University Health Network)

  • Emily Branchard

    (University Health Network)

  • Jennifer Cruickshank

    (University Health Network)

  • Wiebke Schormann

    (University of Toronto)

  • Joseph Longo

    (University of Toronto
    University Health Network)

  • Jennifer Silvester

    (University Health Network)

  • Peter L. Gross

    (Department of Medicine, McMaster University)

  • David W. Andrews

    (University of Toronto
    University of Toronto)

  • David W. Cescon

    (University Health Network
    University of Toronto)

  • Benjamin Haibe-Kains

    (University of Toronto
    University Health Network
    University of Toronto
    Ontario Institute of Cancer Research)

  • Linda Z. Penn

    (University of Toronto
    University Health Network)

  • Deena M. A. Gendoo

    (University of Birmingham, Birmingham
    University of Birmingham, Birmingham)

Abstract

Statins, a family of FDA-approved cholesterol-lowering drugs that inhibit the rate-limiting enzyme of the mevalonate metabolic pathway, have demonstrated anticancer activity. Evidence shows that dipyridamole potentiates statin-induced cancer cell death by blocking a restorative feedback loop triggered by statin treatment. Leveraging this knowledge, we develop an integrative pharmacogenomics pipeline to identify compounds similar to dipyridamole at the level of drug structure, cell sensitivity and molecular perturbation. To overcome the complex polypharmacology of dipyridamole, we focus our pharmacogenomics pipeline on mevalonate pathway genes, which we name mevalonate drug-network fusion (MVA-DNF). We validate top-ranked compounds, nelfinavir and honokiol, and identify that low expression of the canonical epithelial cell marker, E-cadherin, is associated with statin-compound synergy. Analysis of remaining prioritized hits led to the validation of additional compounds, clotrimazole and vemurafenib. Thus, our computational pharmacogenomic approach identifies actionable compounds with pathway-specific activities.

Suggested Citation

  • Jenna E. Leeuwen & Wail Ba-Alawi & Emily Branchard & Jennifer Cruickshank & Wiebke Schormann & Joseph Longo & Jennifer Silvester & Peter L. Gross & David W. Andrews & David W. Cescon & Benjamin Haibe-, 2022. "Computational pharmacogenomic screen identifies drugs that potentiate the anti-breast cancer activity of statins," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33144-9
    DOI: 10.1038/s41467-022-33144-9
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    References listed on IDEAS

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    1. Vasanthi S. Viswanathan & Matthew J. Ryan & Harshil D. Dhruv & Shubhroz Gill & Ossia M. Eichhoff & Brinton Seashore-Ludlow & Samuel D. Kaffenberger & John K. Eaton & Kenichi Shimada & Andrew J. Aguirr, 2017. "Dependency of a therapy-resistant state of cancer cells on a lipid peroxidase pathway," Nature, Nature, vol. 547(7664), pages 453-457, July.
    2. Guha, Rajarshi, 2007. "Chemical Informatics Functionality in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 18(i05).
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