Gene methylation and cytological atypia in random fine-needle aspirates for assessment of breast cancer risk

Vered Stearns, Mary Jo Fackler, Sidra Hafeez, Zoila Lopez Bujanda, Robert T. Chatterton, Lisa K. Jacobs, Nagi F. Khouri, David Ivancic, Kara Kenney, Christina Shehata, Stacie C. Jeter, Judith A. Wolfman, Carola M. Zalles, Peng Huang, Seema A. Khan, Saraswati Sukumar

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Methods to determine individualized breast cancer risk lack sufficient sensitivity to select womenmost 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.

Original languageEnglish (US)
Pages (from-to)673-682
Number of pages10
JournalCancer Prevention Research
Issue number8
StatePublished - Aug 2016

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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