Optimizing the identification of risk-relevant mutations by multigene panel testing in selected hereditary breast/ovarian cancer families

Abstract

The introduction of multigene panel testing for hereditary breast/ovarian cancer screening has greatly improved efficiency, speed, and costs. However, its clinical utility is still debated, mostly due to the lack of conclusive evidences on the impact of newly discovered genetic variants on cancer risk and lack of evidence-based guidelines for the clinical management of their carriers. In this pilot study, we aimed to test whether a systematic and multiparametric characterization of newly discovered mutations could enhance the clinical utility of multigene panel sequencing. Out of a pool of 367 breast/ovarian cancer families Sanger-sequenced for BRCA1 and BRCA2 gene mutations, we selected a cohort of 20 BRCA1/2-negative families to be subjected to the BROCA-Cancer Risk Panel massive parallel sequencing. As a strategy for the systematic characterization of newly discovered genetic variants, we collected blood and cancer tissue samples and established lymphoblastoid cell lines from all available individuals in these families, to perform segregation analysis, loss-of-heterozygosity and further molecular studies. We identified loss-of-function mutations in 6 out 20 high-risk families, 5 of which occurred on BRCA1, CHEK2 and ATM and are esteemed to be risk-relevant. In contrast, a novel RAD50 truncating mutation is most likely unrelated to breast cancer. Our data suggest that integrating multigene panel testing with a pre-organized, multiparametric characterization of newly discovered genetic variants improves the identification of risk-relevant alleles impacting on the clinical management of their carriers.

Multigene panel sequencing for the diagnosis of hereditary breast/ovarian cancer syndromes is raising concerns due to the absence of univocal interpretation of the cancer risk conferred by non-BRCA1/2 mutations. Integrating these technologies with a systematic and multiparametric characterization of newly discovered genetic variants improves the identification of risk-relevant alleles enhancing their clinical utility.

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