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Hum Mutat. 2019 Sep;40(9):1546-1556. doi: 10.1002/humu.23861. Epub 2019 Aug 23.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants.

Author information

1
Genomics Institute, UC Santa Cruz, Santa Cruz, California.
2
FaBiT Department, Biocomputing Group, University of Bologna, Bologna, Italy.
3
Oncogenetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.
4
Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas.
5
Clinical and Translational Bioinformatics Research Unit, Vall d'Hebron Institute of Research (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
6
Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
7
Department of Medical and Human Genetics, Baylor College of Medicine, Houston, Texas.
8
Color Genomics, Burlingame, California.
9
Department of Biochemistry & Molecular Biology, Baylor College of Medicine, Houston, Texas.
10
Department of Pharmacology, Baylor College of Medicine, Houston, Texas.
11
Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, Texas.
12
Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington.
13
Sage Bionetworks, Seattle, Washington.
14
Computer Science and Informatics, Indiana University, Bloomington, Indiana.
15
Khoury College of Computer Science, Northeastern University, Boston, Massachusetts.
16
Molecular Cancer Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
17
Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah.

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.

KEYWORDS:

BRCA; BRCA1; BRCA2; CAGI; CAGI5; variant interpretation

PMID:
31294896
PMCID:
PMC6744348
[Available on 2020-09-01]
DOI:
10.1002/humu.23861

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