Abstract 07: The effect of genetic variants on the relationship between statins and breast cancer in the Women's Health Initiative Observational Study.

Background: Statins are the most widely prescribed and most effective cholesterol-lowering drugs used in the United States. Statins are a logical candidate for cancer chemoprevention in that they have multiple cellular effects other than lowering cholesterol, including: inhibition of rho GTPases, induction of apoptosis, and decreasing markers of chronic inflammation. A chemopreventive effect of statins on breast cancer has been suggested, however there is significant variation in inter-individual response to statins, and underlying genetic differences may modify the effect of statins on cancer risk. The purpose of this analysis was to evaluate whether there is an interaction between genes modifying statin metabolism and statin use in relationship with breast cancer risk in a case-control study nested within the Women's Health Initiative (WHI) Observational Study (OS). Methods: Genome Wide Association Study (GWAS) data on 30,380 SNPS were available for 1,683 breast cancer cases and 1,683 one-to-one matched controls from the WHI and were included in Cancer Genetic Markers of Susceptibility (CGEMS). Matching criteria were: age at screening, enrollment date, race/ethnicity (all were White), hysterectomy status at baseline and history of breast cancer at baseline. Statin use, sociodemographic information and potentially confounding variables were evaluated at baseline and breast cancer diagnoses were centrally adjudicated. We examined interactions between baseline statin use (yes or no) and 22 SNPs in or near 9 candidate lipid metabolism genes using a conditional logistic model adjusted for features at baseline associated with case/control status. We also examined interactions between statin use and all available SNPs from the GWAS after adjustment for significant features. Results: There were two SNPs out of the 22 SNPs in or near the lipid genes of interest that were nominally significant; rs1529711 in the CARM1 gene [near candidate gene SMARC4 , minor allele frequency (MAF) 15%], Pint=0.04, and rs9282564 in the ABCB1 gene (MAF 10%), Pint=0.01. When all GWAS SNPs were examined for interactions with statin use, 34 SNPs achieved statistical significance using a 5% false discovery rate. The GWAS SNP with the greatest evidence for interaction with statin use on breast cancer risk was rs2875218 (Pint=0.0000076). Conclusion: Two SNPs (rs1529711 and rs9282564) near candidate genes ( SMARC4 and ABCB1 , respectively) showed trends as effect modifiers of statins on breast cancer risk. SMARC4 is a SWI/SNF related, matrix associated, actin dependent regulator of chromatin, and was identified as a candidate effect modifier in a genome-wide study of statin induced myopathy (Link et al., NEJM , 2008). ABCB1 encodes a large transmembrane protein integral to the blood-brain barrier and functions as a drug-transport pump between brain and blood which attenuated LDL-C reduction in a study by Newman and Hulley ( JAMA 1996). From the genome-wide analyses, a SNP (rs2875218) located between PRDX3P3 and FREM2 on chromosome 13 was strongly implicated as interacting with statin use on breast cancer risk. Future analyses will examine tagSNPs covering genomic regions of interest including candidate genes and loci identified through this genome-wide examination of SNP x Statin interactions. We will also explore the associations by statin subtype (lipophilic, hydrophilic). Genetic associations such as these, if confirmed, may have implications in terms of personalized medicine, given that statin efficacy in relation to breast cancer risk may be increased or decreased in individuals dependent on inherited genetic polymorphisms. Citation Format: Allison M. Jay, Cathryn H. Bock, Gregory Dyson, Jennifer L. Beebe-Dimmer, Lifang Hou, Barbara V. Howard, Ross Prentice, Michael S. Simon. The effect of genetic variants on the relationship between statins and breast cancer in the Women's Health Initiative Observational Study. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 07.