An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance

Edwin S. Iversen, Gary Lipton, Steven Hart, Kun Y. Lee, Chunling Hu, Eric C. Polley, Tina Pesaran, Amal Yussuf, Holly LaDuca, Elizabeth Chao, Rachid Karam, David E. Goldgar, Fergus J. Couch, Alvaro N.A. Monteiro

Research output: Contribution to journalArticlepeer-review

Abstract

Loss-of-function variants in the BRCA1 and BRCA2 susceptibility genes predispose carriers to breast and/or ovarian cancer. The use of germline testing panels containing these genes has grown dramatically, but the interpretation of the results has been complicated by the identification of many sequence variants of undefined cancer relevance, termed “Variants of Uncertain Significance (VUS).” We have developed functional assays and a statistical model called VarCall for classifying BRCA1 and BRCA2 VUS. Here we describe a multifactorial extension of VarCall, called VarCall XT, that allows for co–analysis of multiple forms of genetic evidence. We evaluated the accuracy of models defined by the combinations of functional, in silico protein predictors, and family data for VUS classification. VarCall XT classified variants of known pathogenicity status with high sensitivity and specificity, with the functional assays contributing the greatest predictive power. This approach could be used to identify more patients that would benefit from personalized cancer risk assessment and management.

Original languageEnglish (US)
Article number35
Journalnpj Genomic Medicine
Volume7
Issue number1
DOIs
StatePublished - Dec 2022

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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