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1. Classification of 101 BRCA1 and BRCA2 variants of uncertain significance by cosegregation study: A powerful approach.

Author

Caputo SM, Golmard L, Léone M, Damiola F, Guillaud-Bataille M, Revillion F, Rouleau E, Derive N, Buisson A, Basset N, Schwartz M, Vilquin P, Garrec C, Privat M, Gay-Bellile M, Abadie C, Abidallah K, Airaud F, Allary AS, Barouk-Simonet E, Belotti M, Benigni C, Benusiglio PR, Berthemin C, Berthet P, Bertrand O, Bézieau S, Bidart M, Bignon YJ, Birot AM, Blanluet M, Bloucard A, Bombled J, Bonadona V, Bonnet F, Bonnet-Dupeyron MN, Boulaire M, Boulouard F, Bouras A, Bourdon V, Brahimi A, Brayotel F, Bressac de Paillerets B, Bronnec N, Bubien V, Buecher B, Cabaret O, Carriere J, Chiesa J, Chieze-Valéro S, Cohen C, Cohen-Haguenauer O, Colas C, Collonge-Rame MA, Conoy AL, Coulet F, Coupier I, Crivelli L, Cusin V, De Pauw A, Dehainault C, Delhomelle H, Delnatte C, Demontety S, Denizeau P, Devulder P, Dreyfus H, d'Enghein CD, Dupré A, Durlach A, Dussart S, Fajac A, Fekairi S, Fert-Ferrer S, Fiévet A, Fouillet R, Mouret-Fourme E, Gauthier-Villars M, Gesta P, Giraud S, Gladieff L, Goldbarg V, Goussot V, Guibert V, Guillerm E, Guy C, Hardouin A, Heude C, Houdayer C, Ingster O, Jacquot-Sawka C, Jones N, Krieger S, Lacoste S, Lallaoui H, Larbre H, Laugé A, Le Guyadec G, Le Mentec M, Lecerf C, Le Gall J, Legendre B, Legrand C, Legros A, Lejeune S, Lidereau R, Lignon N, Limacher JM, Doriane Livon, Lizard S, Longy M, Lortholary A, Macquere P, Mailliez A, Malsa S, Margot H, Mari V, Maugard C, Meira C, Menjard J, Molière D, Moncoutier V, Moretta-Serra J, Muller E, Nevière Z, Nguyen Minh Tuan TV, Noguchi T, Noguès C, Oca F, Popovici C, Prieur F, Raad S, Rey JM, Ricou A, Salle L, Saule C, Sevenet N, Simaga F, Sobol H, Suybeng V, Tennevet I, Tenreiro H, Tinat J, Toulas C, Turbiez I, Uhrhammer N, Vande Perre P, Vaur D, Venat L, Viellard N, Villy MC, Warcoin M, Yvard A, Zattara H, Caron O, Lasset C, Remenieras A, Boutry-Kryza N, Castéra L, and Stoppa-Lyonnet D

Subjects
Breast Neoplasms classification, Breast Neoplasms genetics, Female, Genetic Testing, Genotype, Humans, Ovarian Neoplasms classification, Ovarian Neoplasms genetics, BRCA1 Protein genetics, BRCA2 Protein genetics, Breast Neoplasms pathology, Genetic Predisposition to Disease, Genetic Variation, Ovarian Neoplasms pathology
Abstract

Up to 80% of BRCA1 and BRCA2 genetic variants remain of uncertain clinical significance (VUSs). Only variants classified as pathogenic or likely pathogenic can guide breast and ovarian cancer prevention measures and treatment by PARP inhibitors. We report the first results of the ongoing French national COVAR (cosegregation variant) study, the aim of which is to classify BRCA1/2 VUSs. The classification method was a multifactorial model combining different associations between VUSs and cancer, including cosegregation data. At this time, among the 653 variants selected, 101 (15%) distinct variants shared by 1,624 families were classified as pathogenic/likely pathogenic or benign/likely benign by the COVAR study. Sixty-six of the 101 (65%) variants classified by COVAR would have remained VUSs without cosegregation data. Of note, among the 34 variants classified as pathogenic by COVAR, 16 remained VUSs or likely pathogenic when following the ACMG/AMP variant classification guidelines. Although the initiation and organization of cosegregation analyses require a considerable effort, the growing number of available genetic tests results in an increasing number of families sharing a particular variant, and thereby increases the power of such analyses. Here we demonstrate that variant cosegregation analyses are a powerful tool for the classification of variants in the BRCA1/2 breast-ovarian cancer predisposition genes., Competing Interests: Declaration of interests D.S.-L. and the Institut Curie have received honoraria for her participation in education meetings organized by AstraZeneca or Tesaro. The remaining authors declare no conflict of interest., (Copyright © 2021 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2021
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2. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification.

Author

Parsons MT, Tudini E, Li H, Hahnen E, Wappenschmidt B, Feliubadaló L, Aalfs CM, Agata S, Aittomäki K, Alducci E, Alonso-Cerezo MC, Arnold N, Auber B, Austin R, Azzollini J, Balmaña J, Barbieri E, Bartram CR, Blanco A, Blümcke B, Bonache S, Bonanni B, Borg Å, Bortesi B, Brunet J, Bruzzone C, Bucksch K, Cagnoli G, Caldés T, Caliebe A, Caligo MA, Calvello M, Capone GL, Caputo SM, Carnevali I, Carrasco E, Caux-Moncoutier V, Cavalli P, Cini G, Clarke EM, Concolino P, Cops EJ, Cortesi L, Couch FJ, Darder E, de la Hoya M, Dean M, Debatin I, Del Valle J, Delnatte C, Derive N, Diez O, Ditsch N, Domchek SM, Dutrannoy V, Eccles DM, Ehrencrona H, Enders U, Evans DG, Farra C, Faust U, Felbor U, Feroce I, Fine M, Foulkes WD, Galvao HCR, Gambino G, Gehrig A, Gensini F, Gerdes AM, Germani A, Giesecke J, Gismondi V, Gómez C, Gómez Garcia EB, González S, Grau E, Grill S, Gross E, Guerrieri-Gonzaga A, Guillaud-Bataille M, Gutiérrez-Enríquez S, Haaf T, Hackmann K, Hansen TVO, Harris M, Hauke J, Heinrich T, Hellebrand H, Herold KN, Honisch E, Horvath J, Houdayer C, Hübbel V, Iglesias S, Izquierdo A, James PA, Janssen LAM, Jeschke U, Kaulfuß S, Keupp K, Kiechle M, Kölbl A, Krieger S, Kruse TA, Kvist A, Lalloo F, Larsen M, Lattimore VL, Lautrup C, Ledig S, Leinert E, Lewis AL, Lim J, Loeffler M, López-Fernández A, Lucci-Cordisco E, Maass N, Manoukian S, Marabelli M, Matricardi L, Meindl A, Michelli RD, Moghadasi S, Moles-Fernández A, Montagna M, Montalban G, Monteiro AN, Montes E, Mori L, Moserle L, Müller CR, Mundhenke C, Naldi N, Nathanson KL, Navarro M, Nevanlinna H, Nichols CB, Niederacher D, Nielsen HR, Ong KR, Pachter N, Palmero EI, Papi L, Pedersen IS, Peissel B, Perez-Segura P, Pfeifer K, Pineda M, Pohl-Rescigno E, Poplawski NK, Porfirio B, Quante AS, Ramser J, Reis RM, Revillion F, Rhiem K, Riboli B, Ritter J, Rivera D, Rofes P, Rump A, Salinas M, Sánchez de Abajo AM, Schmidt G, Schoenwiese U, Seggewiß J, Solanes A, Steinemann D, Stiller M, Stoppa-Lyonnet D, Sullivan KJ, Susman R, Sutter C, Tavtigian SV, Teo SH, Teulé A, Thomassen M, Tibiletti MG, Tischkowitz M, Tognazzo S, Toland AE, Tornero E, Törngren T, Torres-Esquius S, Toss A, Trainer AH, Tucker KM, van Asperen CJ, van Mackelenbergh MT, Varesco L, Vargas-Parra G, Varon R, Vega A, Velasco Á, Vesper AS, Viel A, Vreeswijk MPG, Wagner SA, Waha A, Walker LC, Walters RJ, Wang-Gohrke S, Weber BHF, Weichert W, Wieland K, Wiesmüller L, Witzel I, Wöckel A, Woodward ER, Zachariae S, Zampiga V, Zeder-Göß C, Lázaro C, De Nicolo A, Radice P, Engel C, Schmutzler RK, Goldgar DE, and Spurdle AB

Subjects
Alternative Splicing, Early Detection of Cancer, Female, Genetic Predisposition to Disease, Humans, Likelihood Functions, Male, Multifactorial Inheritance, Neoplasms genetics, BRCA1 Protein genetics, BRCA2 Protein genetics, Computational Biology methods, Mutation, Missense, Neoplasms diagnosis
Abstract

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification., (© 2019 Wiley Periodicals, Inc.)

Published
2019
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3. BRCA Share: A Collection of Clinical BRCA Gene Variants.

Author

Béroud C, Letovsky SI, Braastad CD, Caputo SM, Beaudoux O, Bignon YJ, Bressac-De Paillerets B, Bronner M, Buell CM, Collod-Béroud G, Coulet F, Derive N, Divincenzo C, Elzinga CD, Garrec C, Houdayer C, Karbassi I, Lizard S, Love A, Muller D, Nagan N, Nery CR, Rai G, Revillion F, Salgado D, Sévenet N, Sinilnikova O, Sobol H, Stoppa-Lyonnet D, Toulas C, Trautman E, Vaur D, Vilquin P, Weymouth KS, Willis A, Eisenberg M, and Strom CM

Subjects
Data Curation, Female, Genetic Predisposition to Disease, Humans, Mutation, BRCA1 Protein genetics, BRCA2 Protein genetics, Breast Neoplasms genetics, Databases, Factual economics, Ovarian Neoplasms genetics
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., (© 2016 WILEY PERIODICALS, INC.)

Published
2016
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