Abstract 769: Incorporating a cross-ancestry polygenic risk score into a clinical model improved breast cancer risk prediction in women with pathogenic variants

Abstract Introduction. We previously developed and validated a cross-ancestry polygenic risk score (caPRS) to predict risk of developing breast cancer (BC) in women who do not carry pathogenic variants (PVs) in BC susceptibility genes. Here we aimed to expand upon that study by integrating the caPRS with the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model to combine the effects of genetic and clinical factors in carriers of PVs in BRCA1, BRCA2, PALB2, CHEK2 and ATM. Methods. We explored the association of caPRS among 12, 525 women from the UK Biobank and the Consortium of Investigators of Modifiers of BRCA1/2. The effect size of the caPRS was evaluated separately for individuals carrying PVs in BRCA1, BRCA2, CHEK2, ATM and PALB2. We used a logistic regression model adjusted for age, first-degree BC family history (FHx) and cohort for BRCA1 and BRCA2 to examine the association of the caPRS with BC. The effect sizes were expressed as standardized odds ratios (ORs) with 95% confidence intervals (CIs). The estimated absolute risks to age 80 of developing BC were calculated for unaffected women by combining the caPRS-based risk with gene-specific clinical risk estimates from the BOADICEA model based on U. S. incidences. Results. The caPRS was significantly associated with BC risk across all PV carrier groups. Using BOADICEA alone, the estimated absolute BC risk by age 80 for an average unaffected 20-year-old female in the U. S. with an unknown FHx ranged from 23. 8% for CHEK2 carriers to 79. 4% for BRCA2 carriers. Integration of caPRS into BOADICEA, yielded the distribution of risk for each gene. (Table) Gene N OR per SD (95% CI) Absolute risk by BOADICEA Median absolute risk by BOADICEA + caPRS (Range) ATM 2, 037 1. 46 (1. 25 - 1. 71) 24. 9% 27. 1% (0. 1 - 70. 5) BRCA1 5, 794 1. 24 (1. 18 - 1. 31) 76. 1% 75. 6% (55. 6 - 87. 7) BRCA2 4, 018 1. 40 (1. 31 - 1. 49) 79. 4% 78. 7% (45. 2 - 92. 1) CHEK2 372 1. 88 (1. 41 - 2. 55) 23. 8% 28. 2% (0. 0 - 78. 4) PALB2 304 1. 81 (1. 37 - 2. 43) 53. 9% 56. 3% (2. 9 - 90. 9) Conclusions. The caPRS significantly modified BC risk for carriers of PVs and could help tailor guidelines for women with PVs, particularly in moderate penetrance genes. More data is needed to increase the precision and reach of risk assessment in diverse populations. Citation Format: Placede Tshiaba, Monika Sun, Dariusz Ratman, Jeffrey N. Weitzel, Premal Shah, Matthew Rabinowitz, Akash Kumar, Kate Im. Incorporating a cross-ancestry polygenic risk score into a clinical model improved breast cancer risk prediction in women with pathogenic variants abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 769.