Abstract
Abstract Approximately 15% of genetic screens for mutations in BRCA1 and BRCA2 identify Variants of Uncertain Significance (VUS). Primarily missense mutations, VUS are often difficult to interpret, leading to either uncertainty in how to properly counsel a patient or an unnecessary prophylactic surgery. Given the paucity of data for which missenses are classified as truly pathogenic, computational deleterious missense prediction (DMP) algorithms are used to predict whether a mutation is likely deleterious or neutral. Accuracy of DMPs can vary considerably and have only been calibrated on a relatively small number of missense mutations of demonstrable effect on protein function. In this study, the performance of 41 different DMPs was compared to functional data from 455 functionally characterized missense variants in BRCA1 and BRCA2. New optimized thresholds for classifying missense mutations as deleterious are presented for several existing models as well as a newly derived naïve voting method (NVM). The areas under the curve estimates for the NVM approach are between 0.889-0.922, much higher than previous methods. We estimate that the overall pathogenic potential of missense variants to be 6.8% for BRCA1 and 3.2% of BRCA2, but can be as high as 50% depending on protein location. Overall these results provide key insights into how to predict deleterious missense mutations in BRCA1 and BRCA2. Citation Format: Hart SN, Hoskin T, Shimelis H, Feng B, Lindor NM, Monteiro A, Iversen E, Goldgar DE, Suman V, Couch FJ. Optimized prediction of deleterious missense mutations in BRCA1 and BRCA2 genes [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-02-03.
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