Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-ML

Steven N Hart; Eric C Polley; Hermella Shimelis; Siddhartha Yadav; Fergus J Couch

doi:10.1038/s41523-020-0159-x

Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-ML

NPJ Breast Cancer. 2020 Apr 29:6:13. doi: 10.1038/s41523-020-0159-x. eCollection 2020.

Authors

Steven N Hart¹, Eric C Polley¹, Hermella Shimelis², Siddhartha Yadav³, Fergus J Couch^{1

2}

Affiliations

¹ 1Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA.
² 2Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA.
³ 3Department of Oncology, Mayo Clinic, Rochester, MN USA.

Abstract

In silico predictions of missense variants is an important consideration when interpreting variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes. We trained and evaluated hundreds of machine learning algorithms based on results from validated functional assays to better predict missense variants in these genes as damaging or neutral. This new optimal "BRCA-ML" model yielded a substantially more accurate method than current algorithms for interpreting the functional impact of variants in these genes, making BRCA-ML a valuable addition to data sources for VUS classification.

Keywords: Cancer genetics; Medical genetics; Mutation.

Abstract

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