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Grant Abstract: Women's Health Study: Infrastructure support for cohort follow-up

Grant Number: 5U01CA182913-07
PI Name: Buring
Project Title: Women's Health Study: Infrastructure support for cohort follow-up

Abstract: Despite popular use of vitamin supplements to prevent chronic disease among half of US adults, their benefits remain controversial and little is known about pharmacogenomic effects on efficacy and safety. Vitamin E (alpha-tocopherol or AT), the main lipid-soluble antioxidant in cell membranes, prevents cellular damage from free radical propagation. Based on promising observational studies, AT supplementation was thought to reduce cancer risk. However, randomized clinical trials (RCTs) failed to demonstrate consistent benefit. Pharmacogenomics, the study of how genomic variation modifies pharmacological activity, has the potential to guide targeting of subpopulations for maximum benefit. However, few AT RCTs have enough genome-wide association study (GWAS) data to power pharmacogenomic discovery. Candidate gene analysis and machine learning are two approaches that obviate the need for high statistical power. Using candidate gene analysis in two RCTs (WHS and ATBC) we demonstrated genetic variation in catechol-O-methyltransferase (COMT) modified cancer rates with randomized AT compared to placebo. COMT is a Phase 2 enzyme that metabolizes endogenous catechol containing compounds (i.e. catechol estrogens), preventing their auto-oxidation and subsequent DNA, lipid and protein damaging potential. While individuals homozygous for low-activity COMT (met/met) had significantly reduced rates of overall cancer with randomized AT, the inverse was found for individuals homozygous for high-activity COMT (val/val). We hypothesize that low COMT activity, can synergize with AT to inhibit pathways used by cancerous cells to transform, proliferate or metastasize. In in-vitro pilot studies, maximum inhibition of cell proliferation and induction of apoptosis was observed when COMT was both silenced (silencing RNAs) and inhibited with Tolcapone in the presence of AT. The translational research objectives of this proposal seek to expand these published and pilot studies. In Specific Aim 1, we examine synergistic effects of in-vitro COMT-AT perturbation on other cancer phenotypes (reactive oxygen species, ATP metabolism, and clonogenicity). In Specific Aim 2, we determine pathways and mechanism of action underlying COMT-AT interactions by mining gene expression data from cells treated with AT and COMT inhibitors. In Specific Aim 3, we use machine learning and GWAS data from WHS to identify novel pharmacogenomic loci that modify AT efficacy. While interest in supplements and precision prevention is increasing, their optimal use is under debate. This proposal leverages the WHS to understand the COMT-AT axis and translate its potential to development of cancer preventive or even chemotherapeutic interventions. Further, we propose building a machine learning platform for discovery of other novel AT cancer prevention pharmacogenomic loci. Given widespread use of AT, in over-the-counter supplements and multivitamins, identifying pharmacogenomic loci and elucidating their underlying mechanism of action is critical to maximize benefits and minimize harms of this important vitamin supplement.

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