Abstract P1-08-11: Association of variants in candidate genes on lipid profiles in women with early breast cancer on adjuvant aromatase inhibitor therapy

Abstract

Abstract Background Aromatase inhibitors (AI) can exert unfavorable effects on lipid profiles, but previous studies have reported inconsistent results. Given the intricate biological relationship between estrogen and lipid profiles, these mixed results may be explained in part by variation in genes encoding proteins involved in the drug's target and in estrogen metabolism and signaling. The purpose of this study was to investigate associations of single-nucleotide polymorphisms (SNP) in candidate genes with AI-mediated changes in lipid profiles. Methods We completed a prospective multicenter randomized observational open-label study to test the association of SNPs in candidate genes on biomarkers of estrogenic and anti-estrogenic activity in post-menopausal women with early breast cancer who were recommended adjuvant AI therapy. Eligible women were randomly assigned to exemestane or letrozole, and were followed for 2 years. We genotyped 137 SNPs from germ line DNA in the following candidate genes: ARVCF, COMT, CYP19A1, ESR1, ESR2, PGR, EP300, EZH2, NCOA1-3, NCOR1-2, NRIP, and PELP1. Lipid profiles including total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG) were measured at baseline and 3 months after initiating AI. We conducted genetic association data analysis and multivariate linear regressions to analyze the genetic effects using dominant, recessive, and additive models. Multivariate analysis included age, body mass index, prior hormone replacement therapy, and prior tamoxifen. To adjust for multiple comparisons, only SNPs with a p<0.0003 were considered significant. Results We enrolled 502 women in to the study, but for this analysis we excluded women who did not have genetic data (n = 33), had incomplete data (n = 23), discontinued or crossed over AI therapy (n = 48), women not fasting at both time points (n = 89), or those on lipid-lowering medications (n = 162). A total of 200 women were evaluable (letrozole 107, exemestane 93). Lipid profiles in all patients (n = 200) at baseline and 3 months after initiating AI, respectively, were as follows: TC 204.9 and 203.3 (unchanged, p = 0.43); HDL 61.3 and 56.8 (decreased, p = 6.3E-10); LDL 122.2 and 124.6 (unchanged, p = 0.22); and TG 107.1 and 103.6 (unchanged, p = 0.26). Genetic association and multivariate analysis revealed that SNPs in ESR1 and NCOR1 are significantly associated with additional changes in lipid parameters as summarized in Table 1. Table 1.Significant findings of multivariate linear regressions analyzing genetic associations between candidate gene SNPs and lipid profiles of AI-treated women.CohortNumberSNP (gene)Minor Allele FrequencyLipid ParameterModel UsedMean Absolute Change (mg/dL)P-valueAll patients184rs9340958 (ESR1)0.07TCRecessive-2.250.0003Letrozole96rs9340958 (ESR1)0.07TCRecessive5.280.00009 101rs3020368 (ESR1)0.09TCRecessive6.350.00007Exemestane93rs3798758 (ESR1)0.03HDLDominant, additive-7.970.00001 88rs926848 (ESR1)0.03HDLDominant, additive-7.970.00002 93rs61753150 (NCOR1)0.01TGDominant, additive-11.630.00003 Conclusions Variants in genes involved in estrogen metabolism and signaling are associated with changes in lipid profiles in AI-treated women and should be validated in other studies. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-08-11.