Table S1: DNA methylation in rFNA samples Table S2: Association between methylation and menopause as measured by LH and FSH- Univariate analysis Table S3: Association between Methylation and Menstrual Cycle as Measured by Estradiol and Progesterone - Univariate Analysis Table S4: Association between DNA methylation and lifetime Gail risk score - multivariate analysis Table S5: Association between DNA Methylation and percent breast density Table S6: Association between DNA Methylation and Masood cytology score Table S7: Gene methylation versus standard cytology Table S8: Spearman correlation: relationship between biomarkers within the panel Table S9: Agreement between baseline and 6 month methylation levels in rFNA among individuals (n=15).
ARTICLE ABSTRACT
Methods to determine individualized breast cancer risk lack sufficient sensitivity to select women most likely to benefit from preventive strategies. Alterations in DNA methylation occur early in breast cancer. We hypothesized that cancer-specific methylation markers could enhance breast cancer risk assessment. We evaluated 380 women without a history of breast cancer. We determined their menopausal status or menstrual cycle phase, risk of developing breast cancer (Gail model), and breast density and obtained random fine-needle aspiration (rFNA) samples for assessment of cytopathology and cumulative methylation index (CMI). Eight methylated gene markers were identified through whole-genome methylation analysis and included novel and previously established breast cancer detection genes. We performed correlative and multivariate linear regression analyses to evaluate DNA methylation of a gene panel as a function of clinical factors associated with breast cancer risk. CMI and individual gene methylation were independent of age, menopausal status or menstrual phase, lifetime Gail risk score, and breast density. CMI and individual gene methylation for the eight genes increased significantly (P < 0.001) with increasing cytological atypia. The findings were verified with multivariate analyses correcting for age, log (Gail), log (percent density), rFNA cell number, and body mass index. Our results demonstrate a significant association between cytological atypia and high CMI, which does not vary with menstrual phase or menopause and is independent of Gail risk and mammographic density. Thus, CMI is an excellent candidate breast cancer risk biomarker, warranting larger prospective studies to establish its utility for cancer risk assessment. Cancer Prev Res; 9(8); 673–82. ©2016 AACR.
