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Computational pharmacogenomic screen identifies drugs that potentiate the anti-breast cancer activity of statins
Jenna E van Leeuwen1,2, Wail Ba-Alawi1,2, Emily Branchard2
1Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, M5G 1L7, Canada.
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.
Insights
This study introduces a computational method to find new cancer drugs that work with statins. It identifies compounds like nelfinavir, honokiol, clotrimazole, and vemurafenib that enhance statin
Area of Science:
- Pharmacogenomics
- Cancer Biology
- Drug Discovery
Background:
- Statins, FDA-approved cholesterol-lowering drugs, exhibit anticancer properties by inhibiting the mevalonate pathway.
- Dipyridamole enhances statin-induced cancer cell death by disrupting a feedback loop.
Purpose of the Study:
- To develop an integrative pharmacogenomics pipeline (MVA-DNF) to identify novel compounds synergistic with statins.
- To identify compounds with similar structural, cellular, and molecular profiles to dipyridamole.
Main Methods:
- Development of a pharmacogenomics pipeline focusing on mevalonate pathway genes.
- Identification and validation of top-ranked compounds based on drug-network fusion analysis.
- Correlation analysis between compound synergy and expression of epithelial cell markers like E-cadherin.
Main Results:
- Validated nelfinavir and honokiol as compounds synergistic with statins.
- Identified low E-cadherin expression as a predictive marker for statin-compound synergy.
- Validated additional compounds, clotrimazole and vemurafenib, through the MVA-DNF pipeline.
Conclusions:
- The MVA-DNF computational approach effectively identifies actionable compounds with pathway-specific anticancer activities.
- This strategy offers a novel method for discovering combination cancer therapies involving statins.
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