| Literature DB >> 31294896 |
Melissa S Cline1, Giulia Babbi2, Sandra Bonache3, Yue Cao4, Rita Casadio2, Xavier de la Cruz5,6, Orland Díez3,5, Sara Gutiérrez-Enríquez3, Panagiotis Katsonis7, Carmen Lai8, Olivier Lichtarge7,9,10,11, Pier L Martelli2, Gilad Mishne8, Alejandro Moles-Fernández5, Gemma Montalban5, Sean D Mooney12, Robert O'Conner13, Lars Ootes5, Selen Özkan5, Natalia Padilla5, Kymberleigh A Pagel14, Vikas Pejaver12, Predrag Radivojac14,15, Casandra Riera5, Castrense Savojardo2, Yang Shen4, Yuanfei Sun4, Scott Topper8, Michael T Parsons16, Amanda B Spurdle16, David E Goldgar17.
Abstract
Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.Entities:
Keywords: BRCA; BRCA1; BRCA2; CAGI; CAGI5; variant interpretation
Mesh:
Substances:
Year: 2019 PMID: 31294896 PMCID: PMC6744348 DOI: 10.1002/humu.23861
Source DB: PubMed Journal: Hum Mutat ISSN: 1059-7794 Impact factor: 4.878