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Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants
Author(s) -
Cline Melissa S.,
Babbi Giulia,
Bonache Sandra,
Cao Yue,
Casadio Rita,
Cruz Xavier,
Díez Orland,
GutiérrezEnríquez Sara,
Katsonis Panagiotis,
Lai Carmen,
Lichtarge Olivier,
Martelli Pier L.,
Mishne Gilad,
MolesFernández Alejandro,
Montalban Gemma,
Mooney Sean D.,
O'Conner Robert,
Ootes Lars,
Özkan Selen,
Padilla Natalia,
Pagel Kymberleigh A.,
Pejaver Vikas,
Radivojac Predrag,
Riera Casandra,
Savojardo Castrense,
Shen Yang,
Sun Yuanfei,
Topper Scott,
Parsons Michael T.,
Spurdle Amanda B.,
Goldgar David E.
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23861
Subject(s) - biology , interpretation (philosophy) , breast cancer , clinical practice , variation (astronomy) , clinical significance , computational biology , bioinformatics , genetics , cancer , medicine , computer science , family medicine , physics , astrophysics , programming language
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.