Abstract PR008: Development and testing of a polygenic risk score for breast cancer. Aggressiveness
Authors: Shieh Yiwey , Roger Jacquelyn , Yau Christina , Wolf Denise , Hirst Gillian , Swigart Lamorna , Huntsman Scott , Hu Donglei , Nierenberg Jovia , Middha Pooja , Heise Rachel , Kachuri Linda , Zhu Qianqian , Yao Song , Ambrosone Christine , Kwan Marilyn , Caan Bette , Witte John , Kushi Lawrence , Veer Laura van ’T. , Esserman Laura , Ziv Elad 
Published: January 2023

Background: Aggressive breast cancers have increased proliferation or metastatic potential and portend a poor prognosis. The ability to identify women at elevated risk of aggressive cancers could have major implications for screening and prevention, yet there are no available tools for predicting aggressive cancer risk. We sought to construct a polygenic risk score (PRS) for aggressive breast cancers by leveraging the associations of single nucleotide polymorphisms (SNPs) with tumor gene expression. We used as our measure of aggressiveness the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. We hypothesized that known breast cancer susceptibility SNPs would have differential associations with ROR-P, which could then be used to construct a PRS for ROR-P. Methods: We developed our PRS in a case-only analysis of 3 studies containing SNP genotypes and tumor gene expression: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 TRIAL (total n=2,363). We used linear regression models to evaluate individual SNP associations with ROR-P, adjusted for genetic ancestry and study. We then constructed PRS using varying p-value thresholds and used cross-validation to identify the PRS with highest model r2. To assess whether the ROR-P PRS was associated with poor prognosis, we performed survival analysis in two longitudinal cohorts of breast cancer patients: the UK Biobank (women with incident invasive cancers only) and the Pathways Study. These studies included 10,196 total cases with 785 deaths. We built Cox proportional hazards models to evaluate the association between the ROR-P PRS (adjusted for genetic ancestry) and breast cancer-specific survival (BCSS) in both studies. We then performed meta-analysis of the Cox model results. We also constructed joint models containing the ROR-P PRS and a PRS representing the case-case risk of ER-negative vs. ER-positive cancer, PRSER-/ER+. Results: We tested the associations between 226 breast cancer susceptibility SNPs and ROR-P. The best-performing PRS contained 76 SNPs and had a cross-validated r2 of 0.051. In the UK Biobank and Pathways Study, higher ROR-P PRS was associated with worse BCSS, with nearly identical effects observed in each study, HR per standard deviation of 1.13 (95% CI 1.05-1.21, p=9.0x10-4) in meta-analysis. The ROR-P PRS’s effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS was providing additional prognostic information beyond ER status. Conclusions: We used breast cancer susceptibility SNPs to construct a PRS for ROR-P, a prognostic signature recapitulating aggressiveness, and found the ROR-P PRS to be associated with worse BCSS. Our findings represent an improvement on current PRS for overall breast cancer risk, which preferentially predict cancers with favorable prognosis. Given that aggressive cancers are more likely to present as advanced cancers even among women undergoing routine screening, our findings could potentially identify women who may benefit from more intensive screening.

Citation Format: Yiwey Shieh, Jacquelyn Roger, Christina Yau, Denise Wolf, Gillian Hirst, Lamorna Swigart, Scott Huntsman, Donglei Hu, Jovia Nierenberg, Pooja Middha, Rachel Heise, Linda Kachuri, Qianqian Zhu, Song Yao, Christine Ambrosone, Marilyn Kwan, Bette Caan, John Witte, Lawrence Kushi, Laura van ’T. Veer, Laura Esserman, Elad Ziv. Development and testing of a polygenic risk score for breast cancer. Aggressiveness. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr PR008.