HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures

Helen Davies 1 Dominik Glodzik 1 Sandro Morganella 1 Lucy R Yates 1, 2 Johan Staaf 3 Xueqing Zou 1 Manasa Ramakrishna 4, 1 Sancha Martin 1 Sandrine Boyault 5 Anieta M Sieuwerts 6 Peter T Simpson 7 Tari A King 8 Keiran Raine 1 Jorunn E Eyfjord 9 Gu Kong 10 Åke Borg 3 Ewan Birney 1 Hendrik G Stunnenberg 11 Marc J Van de Vijver 12 Anne Børresen-Dale 13, 14 John W M Martens 6 Paul N Span 15 Sunil R Lakhani 16 Anne Vincent-Salomon 10, 17 Christos Sotiriou 18 Andrew Tutt 19 Alastair M Thompson 20 Steven Van Laere 21 Andrea L Richardson 22, 23 Alain Viari 24, 25 Peter J Campbell 1 Michael R Stratton 1 Serena Nik-Zainal 26, 1
Abstract : Approximately 1–5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (~1–5%) who could have selective therapeutic sensitivity to PARP inhibition.
Type de document :
Article dans une revue
Nature Medicine, Nature Publishing Group, 2017, 23 (4), pp.517 - 525. 〈10.1038/nm.4292〉
Liste complète des métadonnées

Littérature citée [52 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01525050
Contributeur : Marie-France Sagot <>
Soumis le : mercredi 12 juillet 2017 - 11:20:59
Dernière modification le : jeudi 28 juin 2018 - 14:35:37
Document(s) archivé(s) le : mercredi 24 janvier 2018 - 23:00:43

Fichier

davies2017.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Helen Davies, Dominik Glodzik, Sandro Morganella, Lucy R Yates, Johan Staaf, et al.. HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures. Nature Medicine, Nature Publishing Group, 2017, 23 (4), pp.517 - 525. 〈10.1038/nm.4292〉. 〈hal-01525050〉

Partager

Métriques

Consultations de la notice

384

Téléchargements de fichiers

93