Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival

A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS₃₁₃) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS₃₁₃ with clinicopathologic characteristics of, and survival following, breast cancer.

Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS₃₁₃ and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS₃₁₃ (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.

The PRS₃₁₃ was associated with more favorable tumor characteristics. In BCAC, increasing PRS₃₁₃ was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS₃₁₃ was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS₃₁₃ was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.

An increased PRS₃₁₃ is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS₃₁₃ has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS₃₁₃ as increasing PRS₃₁₃ is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.