Abstract 2623: Common genetic variants associated with breast cancer risk used in the Athena study to enhance models identifying women for breast cancer chemoprevention
Authors: Sarah Theiner, Sarah D. Sawyer, Paige Kendall, Alexandra S. Perry, Denise Wolf, Scott Huntsman, Bo Pan, Jeffery A. Tice, David A. Pearce, Thomas Cink, Laura Esserman, Elad Ziv, Laura van ‘t Veer
Journal: Cancer Research (2016)

Abstract Background: The U.S. Preventive Services Task Force recommends that women with a &amp;gt;3% five-year risk of developing breast cancer consider taking selective estrogen receptor modifiers (SERMs) or aromatase inhibitors (AIs) to reduce their risk. Polygenic risk score (PRS), calculated by adding the individual breast cancer risk association for each common genetic variant (SNP), has been found to predict women at low- to high-risk of breast cancer. We analyze associations between SNP risk alleles and known breast cancer risk factors (ethnicity, family history of breast cancer and number of biopsies); furthermore, we quantify the likely impact on chemoprevention recommendations by adding the PRS to known risk models in a subset of women participating in the University of California 100,000 women Athena Breast Health Network. Methods: Our research cohort included 838 women with no previous diagnosis of breast cancer from the University of California, San Francisco, and was enriched for women determined to be at elevated risk for developing breast cancer by the Gail model. A panel of 75 breast cancer risk SNPs were evaluated on saliva and blood samples (Akesogen Inc; COGS oncochip array). The PRS for each patient was calculated by converting the odds ratio for each SNP into a likelihood ratio (LR) and combining LR's across SNPs. Breast Cancer Surveillance Consortium (BCSC), Gail, BCSC-PRS and Gail-PRS scores (risk models incorporating PRS within a Bayesian framework), were evaluated for each patient. Associations between variables were assessed using t-test or ANOVA. A threshold of p&amp;lt;0.05 was used to assess significance. Results: Women in this study carry an average of 65 risk allele SNPs (of 150, 2 per locus). By ANOVA, there is a statistically significant association between the SNPs risk allele count and ethnicity (p = 0.014), with a trend towards association with a family history of a first-degree relative with breast cancer (p = 0.053). PRS is significantly associated with a family history breast cancer (p = 0.031); neither SNP allele count nor PRS associates with previous biopsy status. We found by adding PRS that 12% (86/707) and 13% (104/776) of patients with a prior BCSC or Gail score &amp;lt;3% five-year risk, respectively, changed classifications and would be eligible for chemoprevention. Conversely, 37% (36/98) and 36% (22/62) of patients with a BCSC or Gail score of &amp;gt;3% five-year risk, respectively, changed classifications by adding PRS and would no longer be eligible for chemoprevention. Conclusion: The addition of SNP based PRS to BCSC and Gail models significantly changes how women are classified and as a result changes whether risk reducing agents are recommended. PRS will be combined with BCSC and genetic test results for 9 breast cancer genes to calculate a women's breast cancer risk in the PCORI-funded Athena WISDOM study of 100,000 women, comparing risk-based vs. annual mammography screening. Citation Format: Sarah Theiner, Sarah D. Sawyer, Paige Kendall, Alexandra S. Perry, Denise Wolf, Scott Huntsman, Bo Pan, Jeffery A. Tice, David A. Pearce, Thomas Cink, Laura Esserman, Elad Ziv, Laura van ‘t Veer. Common genetic variants associated with breast cancer risk used in the Athena study to enhance models identifying women for breast cancer chemoprevention. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2623.