Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort

Abstract

Purpose: Genetic testing of individuals often results in identification of genomic variants of unknown significance (VUS). Multiple lines of evidence are used to help determine the clinical significance of these variants. Methods: We analyzed~138,000 individuals tested by multigene panel testing (MGPT). We used logistic regression to predict carrier status based on personal and family history of cancer. This was applied to 4644 tested individuals carrying 2383 BRCA1/2 variants to calculate likelihood ratios informing pathogenicity for each. Heterogeneity tests were performed for specific classes of variants defined by in silico predictions. Results: Twenty-two variants labeled as VUS had odds of >10:1 in favor of pathogenicity. The heterogeneity analysis found that among variants in functional domains that were predicted to be benign by in silico tools, a significantly higher proportion of variants were estimated to be pathogenic than previously indicated; that missense variants outside of functional domains should be considered benign; and that variants predicted to create de novo donor sites were also largely benign. Conclusion: The evidence presented here supports the use of personal and family history from MGPT in the classification of VUS and will be integrated into ongoing efforts to provide largescale multifactorial classification.

BRCA1/2 Mutation Detection in the Tumor Tissue from Selected Polish Patients with Breast Cancer Using Next Generation Sequencing

“…Interestingly, in six samples, we detected VUSs. Previous studies have shown that co-segregation analysis and family history in a large cohort [ 44 ], as well as protein structure [ 45 ], in addition to the increasing number of functional studies, the development of computational prediction algorithms and database enlargement, allow VUSs to be reclassified as well [ 46 , 47 ].…”

A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays

“…Classification of VUS based on posterior probabilities from a Bayesian “system”, which by construction, requires specification of prior probabilities has been suggested by Plon et al 29 previously. Some recent BRCA VUS classification models have used the Align GVGD sequence conservation model to specify these prior probabilities 33 , 47 , 48 . In contrast, in the VarCall models we describe here, we specified a non-informative prior distribution on each variant’s function status.…”

ESMO recommendations on predictive biomarker testing for homologous recombination deficiency and PARP inhibitor benefit in ovarian cancer

“…A major challenge for BRCA and wider HRR gene testing is determining the clinical relevance of variants of uncertain significance (VUS) that are typically rarer missense mutations and also include intronic or exonic mutations that may alter RNA splicing. [43][44][45] The biological relevance of variants that lead to partial or 'leaky' splicing defects, particularly in BRCA2, that reduce full length transcript production are particularly hard to interpret. 46 The problem of VUS is even more pronounced for wider gene panel tests where the functional and clinical consequences of most individual genomic loci are not well characterised and individual mutations are not highly recurrent.…”