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Am J Hum Genet. 2018 Feb 1;102(2):233-248. doi: 10.1016/j.ajhg.2017.12.013. Epub 2018 Jan 25.

Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches.

Author information

1
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
2
Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
3
Division of Nephrology, University of New Mexico, Albuquerque, NM 87131, USA.
4
Department of Statistical Science, Duke University, Durham, NC 27708, USA.
5
Department of Structural Biology, University of California, San Diego, San Diego, CA 92093, USA.
6
Cancer Epidemiology Program, H. Lee Moffitt Cancer Center, Tampa, FL 33612, USA.
7
Department of Health Sciences Research, Mayo Clinic, Scottsdale, AZ 85259, USA.
8
Huntsman Cancer Institute and Department of Dermatology, University of Utah, Salt Lake City, UT 84132, USA.
9
Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA.
10
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: couch.fergus@mayo.edu.

Abstract

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

KEYWORDS:

BRCA2; VUS; cancer predisposition; functional assay

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