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. 2021 Oct 7;108(10):1907-1923.
doi: 10.1016/j.ajhg.2021.09.003. Epub 2021 Sep 30.

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

Sandrine M Caputo  1 , Lisa Golmard  2 , Mélanie Léone  3 , Francesca Damiola  4 , Marine Guillaud-Bataille  5 , Françoise Revillion  6 , Etienne Rouleau  5 , Nicolas Derive  2 , Adrien Buisson  3 , Noémie Basset  7 , Mathias Schwartz  2 , Paul Vilquin  8 , Celine Garrec  9 , Maud Privat  10 , Mathilde Gay-Bellile  11 , Caroline Abadie  12 , Khadija Abidallah  2 , Fabrice Airaud  9 , Anne-Sophie Allary  13 , Emmanuelle Barouk-Simonet  14 , Muriel Belotti  15 , Charlotte Benigni  16 , Patrick R Benusiglio  17 , Christelle Berthemin  2 , Pascaline Berthet  18 , Ophelie Bertrand  19 , Stéphane Bézieau  9 , Marie Bidart  20 , Yves-Jean Bignon  21 , Anne-Marie Birot  22 , Maud Blanluet  2 , Amelie Bloucard  2 , Johny Bombled  5 , Valerie Bonadona  23 , Françoise Bonnet  14 , Marie-Noëlle Bonnet-Dupeyron  24 , Manon Boulaire  6 , Flavie Boulouard  25 , Ahmed Bouras  3 , Violaine Bourdon  13 , Afane Brahimi  26 , Fanny Brayotel  27 , Brigitte Bressac de Paillerets  5 , Noémie Bronnec  28 , Virginie Bubien  14 , Bruno Buecher  29 , Odile Cabaret  5 , Jennifer Carriere  2 , Jean Chiesa  30 , Stephanie Chieze-Valéro  31 , Camille Cohen  32 , Odile Cohen-Haguenauer  32 , Chrystelle Colas  2 , Marie-Agnès Collonge-Rame  33 , Anne-Laure Conoy  6 , Florence Coulet  7 , Isabelle Coupier  8 , Louise Crivelli  34 , Véronica Cusin  7 , Antoine De Pauw  2 , Catherine Dehainault  2 , Hélène Delhomelle  19 , Capucine Delnatte  35 , Sophie Demontety  29 , Philippe Denizeau  36 , Pierre Devulder  18 , Helene Dreyfus  37 , Catherine Dubois d'Enghein  2 , Anaïs Dupré  14 , Anne Durlach  38 , Sophie Dussart  23 , Anne Fajac  39 , Samira Fekairi  13 , Sandra Fert-Ferrer  40 , Alice Fiévet  5 , Robin Fouillet  25 , Emmanuelle Mouret-Fourme  19 , Marion Gauthier-Villars  29 , Paul Gesta  31 , Sophie Giraud  41 , Laurence Gladieff  42 , Veronica Goldbarg  43 , Vincent Goussot  44 , Virginie Guibert  9 , Erell Guillerm  7 , Christophe Guy  29 , Agnès Hardouin  25 , Céline Heude  18 , Claude Houdayer  2 , Olivier Ingster  45 , Caroline Jacquot-Sawka  46 , Natalie Jones  14 , Sophie Krieger  47 , Sofiane Lacoste  29 , Hakima Lallaoui  48 , Helene Larbre  27 , Anthony Laugé  29 , Gabrielle Le Guyadec  49 , Marine Le Mentec  29 , Caroline Lecerf  29 , Jessica Le Gall  2 , Bérengère Legendre  6 , Clémentine Legrand  50 , Angélina Legros  25 , Sophie Lejeune  26 , Rosette Lidereau  29 , Norbert Lignon  42 , Jean-Marc Limacher  51 , Doriane Livon  52 , Sarab Lizard  53 , Michel Longy  14 , Alain Lortholary  54 , Pierre Macquere  14 , Audrey Mailliez  6 , Sarah Malsa  55 , Henri Margot  14 , Véronique Mari  56 , Christine Maugard  57 , Cindy Meira  6 , Julie Menjard  58 , Diane Molière  22 , Virginie Moncoutier  2 , Jessica Moretta-Serra  52 , Etienne Muller  47 , Zoe Nevière  18 , Thien-Vu Nguyen Minh Tuan  2 , Tetsuro Noguchi  13 , Catherine Noguès  52 , Florine Oca  6 , Cornel Popovici  13 , Fabienne Prieur  59 , Sabine Raad  14 , Jean-Marc Rey  8 , Agathe Ricou  47 , Lucie Salle  31 , Claire Saule  19 , Nicolas Sevenet  14 , Fatoumata Simaga  29 , Hagay Sobol  13 , Voreak Suybeng  29 , Isabelle Tennevet  60 , Henrique Tenreiro  29 , Julie Tinat  28 , Christine Toulas  61 , Isabelle Turbiez  62 , Nancy Uhrhammer  11 , Pierre Vande Perre  61 , Dominique Vaur  47 , Laurence Venat  63 , Nicolas Viellard  29 , Marie-Charlotte Villy  29 , Mathilde Warcoin  29 , Alice Yvard  54 , Helene Zattara  6 , Olivier Caron  43 , Christine Lasset  23 , Audrey Remenieras  13 , Nadia Boutry-Kryza  3 , Laurent Castéra  47 , Dominique Stoppa-Lyonnet  64
Affiliations

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

Sandrine M Caputo et al. Am J Hum Genet. .

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.

Keywords: BRCA1; BRCA2; classification; clinical; cosegregation data; multifactorial model; variant of uncertain significance.

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Conflict of interest statement

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.

Figures

Figure 1
Figure 1
Variant classification criteria in the framework of the 5 classes of likelihood of pathogenicity and COVAR study variant selection criteria The variant classification or selection for COVAR study relies on the presence of at least one of the listed criteria. (1) For large duplications, tandem status disrupting the gene must be demonstrated by mRNA analysis or breakpoint sequencing, otherwise this variant should be considered to be a VUS. (2) Multifactorial likelihood model proposed by Goldgar et al. (3) This classification criterion has been used since January 2019. Before 2019, these splice variants were classified in class 5 and were confirmed by mRNA analysis. (4) Total gnomAD cohort or subpopulations except for Finnish, Ashkenazi Jewish, and “Other” groups due to the possibility of a founder effect and/or the small number of subjects. gnomAD started to be used as the control database for classification criteria in July 2017. Between December 2014 and June 2017, allele frequency was determined from the ExAC database, with the same thresholds and population groups for classification. Between 2012 and November 2014, allele frequency was determined from the 1000 Genomes Project and Exome Sequencing Project databases, with only one threshold, allele frequency > 1% for classification in class 1 variant, and only the total cohort of both projects. (5) With no clinical or biological signs of Fanconi anemia. (6) Align-GVGD prediction algorithm classifies variants from C0 to C65 classes; C0 corresponds to the least likely functional variants and C65 corresponds to the most likely functional variants. The last species of IARC alignment, purple sea urchin, is removed for Align-GVGD prediction when it is the only species with an amino acid change; in this case, the inclusion criterion corresponds to Align-GVGD class C35 to C65 AND deleterious prediction by SIFT algorithm. IARC, International Agency for Research on Cancer.
Figure 2
Figure 2
Increase of the number of BRCA1 and BRCA2 variants in the FrOG database since 2012, not including the result of the COVAR study classification
Figure 3
Figure 3
Patients and variants in the COVAR study from December 2011 to November 2019 (A) Number of affected individuals and variants included and number of variants classified. (B) Number of families participating in the COVAR study according to the number of relatives included.
Figure 4
Figure 4
Classified variants type and in silico prediction (A) Classified variants according to the type of variation. (B) Classified variants according to the in silico predicted protein effect: Align-GVGD, SIFT, or PolyPhen-2.
See this image and copyright information in PMC

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