Skip to main content

A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays.

Publication ,  Journal Article
Biswas, K; Lipton, GB; Stauffer, S; Sullivan, T; Cleveland, L; Southon, E; Reid, S; Magidson, V; Iversen, ES; Sharan, SK
Published in: NPJ genomic medicine
December 2020

Sequencing-based genetic tests to identify individuals at increased risk of hereditary breast and ovarian cancers have resulted in the identification of more than 40,000 sequence variants of BRCA1 and BRCA2. A majority of these variants are considered to be variants of uncertain significance (VUS) because their impact on disease risk remains unknown, largely due to lack of sufficient familial linkage and epidemiological data. Several assays have been developed to examine the effect of VUS on protein function, which can be used to assess their impact on cancer susceptibility. In this study, we report the functional characterization of 88 BRCA2 variants, including several previously uncharacterized variants, using a well-established mouse embryonic stem cell (mESC)-based assay. We have examined their ability to rescue the lethality of Brca2 null mESC as well as sensitivity to six DNA damaging agents including ionizing radiation and a PARP inhibitor. We have also examined the impact of BRCA2 variants on splicing. In addition, we have developed a computational model to determine the probability of impact on function of the variants that can be used for risk assessment. In contrast to the previous VarCall models that are based on a single functional assay, we have developed a new platform to analyze the data from multiple functional assays separately and in combination. We have validated our VarCall models using 12 known pathogenic and 10 neutral variants and demonstrated their usefulness in determining the pathogenicity of BRCA2 variants that are listed as VUS or as variants with conflicting functional interpretation.

Duke Scholars

Published In

NPJ genomic medicine

DOI

EISSN

2056-7944

ISSN

2056-7944

Publication Date

December 2020

Volume

5

Issue

1

Start / End Page

52

Related Subject Headings

  • 3206 Medical biotechnology
  • 3105 Genetics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Biswas, K., Lipton, G. B., Stauffer, S., Sullivan, T., Cleveland, L., Southon, E., … Sharan, S. K. (2020). A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays. NPJ Genomic Medicine, 5(1), 52. https://doi.org/10.1038/s41525-020-00158-5
Biswas, Kajal, Gary B. Lipton, Stacey Stauffer, Teresa Sullivan, Linda Cleveland, Eileen Southon, Susan Reid, Valentin Magidson, Edwin S. Iversen, and Shyam K. Sharan. “A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays.NPJ Genomic Medicine 5, no. 1 (December 2020): 52. https://doi.org/10.1038/s41525-020-00158-5.
Biswas K, Lipton GB, Stauffer S, Sullivan T, Cleveland L, Southon E, et al. A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays. NPJ genomic medicine. 2020 Dec;5(1):52.
Biswas, Kajal, et al. “A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays.NPJ Genomic Medicine, vol. 5, no. 1, Dec. 2020, p. 52. Epmc, doi:10.1038/s41525-020-00158-5.
Biswas K, Lipton GB, Stauffer S, Sullivan T, Cleveland L, Southon E, Reid S, Magidson V, Iversen ES, Sharan SK. A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays. NPJ genomic medicine. 2020 Dec;5(1):52.

Published In

NPJ genomic medicine

DOI

EISSN

2056-7944

ISSN

2056-7944

Publication Date

December 2020

Volume

5

Issue

1

Start / End Page

52

Related Subject Headings

  • 3206 Medical biotechnology
  • 3105 Genetics