BRCA Share: A Collection of Clinical BRCA Gene Variants.

Beroud C1,2, Letovsky SI3, Braastad CD4, Caputo SM5, Beaudoux O6, Bignon YJ7, De Paillerets BB8, Bronner M9, Buell CM4, Collod-Béroud G1, Coulet F10, Derive N5, Divincenzo C4, Elzinga CD4, Garrec C11, Houdayer C5,12, Karbassi I4, Lizard S13, Love A4, Muller D14, Nagan N3, Nery CR15, Rai G1,Revillion F16, Salgado D1, Sévenet N17, Sinilnikova O18, Sobol H19, Stoppa-Lyonnet D5,12, Toulas C20, Trautman E3, Vaur D21, Vilquin P22, Weymouth KS3, Willis A23; Laboratory Corporation of America Variant Classification Group; Quest Diagnostics Variant Classification Group; UNICANCER Genetic Group BRCA Laboratory Network, Eisenberg M23, Strom CM24.

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Abstract

As next generation sequencing (NGS) 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 critical part of clinical genetic testing for these genes. A database of clinical observations of BRCA variants is a critical resource in that process. This paper 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 (UMD) generated by the French Unicancer Genetic Group (UGG) 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. This article is protected by copyright. All rights reserved.