Gene methylation and cytological atypia in random fine needle aspirates for assessment of breast cancer risk: 10-year follow up in average risk women.

Abstract

10520 Background: Alterations in DNA methylation occur early in tumorigenesis, and are a potential breast cancer risk biomarker. We previously reported a study where healthy volunteers underwent random fine needle aspiration (rFNA) of the breasts; cumulative methylation index of eight preselected tumor suppressor genes (CMI) was associated with the presence of cytological atypia in rFNA samples. We now report 10-year follow-up of this population, to evaluate whether increased CMI is associated with subsequent breast cancer development. Methods: 380 women, unselected by breast cancer risk, were enrolled. Demographics, breast cancer risk factors, lifetime Gail model risk estimates (Gail-LR), and %breast density were obtained at baseline. rFNA samples were assessed for cytopathology (Masood Score, MS) and CMI. Patients were contacted annually for 10 years to ascertain development of invasive or non-invasive breast cancer. In univariate analysis, log-rank test was used to compare breast cancer incidence rates between individuals with high and low baseline measures (separated by median). Area under the ROC curve was used to evaluate the cancer prediction accuracy. In multivariate analysis, the effect of CMI (after log-transformation to reduce skewness) was further studied using Cox regression model adjusting for confounding baseline variables. Results: 362 women participated in follow up. At a median follow up time of 9.5 years after rFNA sampling, 16 women developed invasive or non-invasive breast cancer. There were no significant differences between women who developed cancer and those that did not in regard to demographic factors, %breast density, MS, or Gail-LR. On univariate analysis, Gail-LR was higher in women who developed cancer (13.0 vs. 16.5, p=0.08). The largest hazard ratios were observed from high breast density (2.30, 95% CI 0.8, 6.6) and high CMI (2.26, 95% CI 0.8, 6.6, p=0.07). In breast cancer prediction, the AUC for CMI was 0.64 (95% CI 0.51, 0.77). In separate bivariable models that adjusted for age, Gail-LR, MS, and %breast density, the HR for log CMI was consistently above unity, with a p value consistently below 0.1, except for the model that included MS (see Table). Conclusions: Elevated CMI has potential as a robust predictor of future breast cancer occurrence in average risk women, even when adjusted for breast density or cytologic atypia. Our prior analysis established that CMI is not susceptible to variation with menstrual cycle phase and menopausal status. These features support its further evaluation in larger trials. Clinical trial information: NCT00896636 .[Table: see text]