| Literature DB >> 27633797 |
Christophe Béroud1,2, Stanley I Letovsky3, Corey D Braastad4, Sandrine M Caputo5, Olivia Beaudoux6, Yves Jean Bignon7, Brigitte Bressac-De Paillerets8, Myriam Bronner9, Crystal M Buell4, Gwenaëlle Collod-Béroud1, Florence Coulet10, Nicolas Derive5, Christina Divincenzo4, Christopher D Elzinga4, Céline Garrec11, Claude Houdayer5,12, Izabela Karbassi4, Sarab Lizard13, Angela Love4, Danièle Muller14, Narasimhan Nagan3, Camille R Nery15, Ghadi Rai1, Françoise Revillion16, David Salgado1, Nicolas Sévenet17, Olga Sinilnikova18, Hagay Sobol19, Dominique Stoppa-Lyonnet5,12, Christine Toulas20, Edwin Trautman3, Dominique Vaur21, Paul Vilquin22, Katelyn S Weymouth3, Alecia Willis23, Marcia Eisenberg23, Charles M Strom15.
Abstract
As next-generation sequencing increases access to human genetic variation, the challenge of determining clinical significance of variants becomes ever more acute. Germline variants in the BRCA1 and BRCA2 genes can confer substantial lifetime risk of breast and ovarian cancer. Assessment of variant pathogenicity is a vital part of clinical genetic testing for these genes. A database of clinical observations of BRCA variants is a critical resource in that process. This article describes BRCA Share™, a database created by a unique international alliance of academic centers and commercial testing laboratories. By integrating the content of the Universal Mutation Database generated by the French Unicancer Genetic Group with the testing results of two large commercial laboratories, Quest Diagnostics and Laboratory Corporation of America (LabCorp), BRCA Share™ has assembled one of the largest publicly accessible collections of BRCA variants currently available. Although access is available to academic researchers without charge, commercial participants in the project are required to pay a support fee and contribute their data. The fees fund the ongoing curation effort, as well as planned experiments to functionally characterize variants of uncertain significance. BRCA Share™ databases can therefore be considered as models of successful data sharing between private companies and the academic world.Entities:
Keywords: BRCA1; BRCA2; NGS; breast cancer; genetic databases; ovarian cancer; variant classification
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Year: 2016 PMID: 27633797 DOI: 10.1002/humu.23113
Source DB: PubMed Journal: Hum Mutat ISSN: 1059-7794 Impact factor: 4.878