Abstract A2: Genetic variation in estrogen receptor genes and mammographic breast density

Abstract

Abstract Mammographic density is one of the strongest, independent risk factors in the development of breast cancer. Women with mammographically dense breasts, those with greater than or equal to 75% dense tissue, are at a four to six-fold greater risk of developing breast cancer when compared to those with “no measurable dense tissue,” in which the breasts are composed entirely of fat. Many of the established risk factors for breast cancer have been shown to be associated with variations in breast density (i.e., age, menopausal status, parity, BMI, and postmenopausal hormone use). Additionally, twin studies have also shown that heritability accounts for approximately 60% of the variance in mammographic density. Given the established role of estrogens in the development and progression of breast cancer, we have evaluated the role of 17 single-nucleotide polymorphisms (SNPs) in the estrogen receptor 1 and 2 genes (ESR1 and ESR2), and the recently identified G-Protein Coupled Estrogen Receptor 1 (GPER) gene, which has been demonstrated to regulate physiologic responses to estrogens independent of the traditional estrogen receptors. This study population consisted of 370 cancer-free (excluding cancers of the skin) Caucasian, postmenopausal women enrolled in the Mammograms and Masses Study (MAMS). Three different measures of mammographic density were computed: dense breast area, total breast area, and percent breast density, using the classification system developed by Wolfe in 1976, and a compensating polar planimeter, wax pencil, and transparent overlay. Breast density was calculated as the proportion of visibly dense breast to total breast area, expressed as a percentage. DNA was extracted from buffy coat samples, and genotyping was done using the Sequenom iPLEX Gold Assay. Heterozygote and homozygous variant genotypes were collapsed and compared to the common allele genotype for all statistical analyses. General linear models and χ2 analyses were conducted. We arranged our percent density variable into tertiles for further analysis. We observed that three SNPs in ESR2 (rs12435857, rs1256044, and rs1256031) were significantly associated with percent mammographic density. For ESR2 rs1256044 and rs1256031, mean percent mammographic density was significantly higher among women with at least one rare allele compared to women homozygous for the common allele (respectively, P=0.02 and P=0.03). Conversely, mean percent mammographic density was significantly higher among women with ESR2 rs12435857 GG genotype compared to those with GA/AA genotypes, 29.0 and 23.7, respectively (P=0.03). Our results suggest that common genetic variation in ESR2 is associated with percent mammographic density. Since estrogen receptor genes are highly expressed in breast tissue, functional SNPs in these genes may alter breast cancer risk, by altering mammographic density. Citation Information: Cancer Prev Res 2010;3(1 Suppl):A2.