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

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-Kains (), Linda Z. Penn () and Deena M. A. Gendoo ()
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Jenna E. Leeuwen: University of Toronto
Wail Ba-Alawi: University of Toronto
Emily Branchard: University Health Network
Jennifer Cruickshank: University Health Network
Wiebke Schormann: University of Toronto
Joseph Longo: University of Toronto
Jennifer Silvester: University Health Network
Peter L. Gross: Department of Medicine, McMaster University
David W. Andrews: University of Toronto
David W. Cescon: University Health Network
Benjamin Haibe-Kains: University of Toronto
Linda Z. Penn: University of Toronto
Deena M. A. Gendoo: University of Birmingham, Birmingham

Nature Communications, 2022, vol. 13, issue 1, 1-17

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-33144-9

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