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

Abstract 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 significanc...

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Autores principales:	Kajal Biswas, Gary B. Lipton, Stacey Stauffer, Teresa Sullivan, Linda Cleveland, Eileen Southon, Susan Reid, Valentin Magidson, Edwin S. Iversen, Shyam K. Sharan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Genetics QH426-470
Acceso en línea:	https://doaj.org/article/040ac1e333f54a36a947eae448e108dd
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spelling	oai:doaj.org-article:040ac1e333f54a36a947eae448e108dd2021-12-02T12:33:16ZA computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays10.1038/s41525-020-00158-52056-7944https://doaj.org/article/040ac1e333f54a36a947eae448e108dd2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41525-020-00158-5https://doaj.org/toc/2056-7944Abstract 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.Kajal BiswasGary B. LiptonStacey StaufferTeresa SullivanLinda ClevelandEileen SouthonSusan ReidValentin MagidsonEdwin S. IversenShyam K. SharanNature PortfolioarticleMedicineRGeneticsQH426-470ENnpj Genomic Medicine, Vol 5, Iss 1, Pp 1-16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Genetics QH426-470
spellingShingle	Medicine R Genetics QH426-470 Kajal Biswas Gary B. Lipton Stacey Stauffer Teresa Sullivan Linda Cleveland Eileen Southon Susan Reid Valentin Magidson Edwin S. Iversen Shyam K. Sharan A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
description	Abstract 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.
format	article
author	Kajal Biswas Gary B. Lipton Stacey Stauffer Teresa Sullivan Linda Cleveland Eileen Southon Susan Reid Valentin Magidson Edwin S. Iversen Shyam K. Sharan
author_facet	Kajal Biswas Gary B. Lipton Stacey Stauffer Teresa Sullivan Linda Cleveland Eileen Southon Susan Reid Valentin Magidson Edwin S. Iversen Shyam K. Sharan
author_sort	Kajal Biswas
title	A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
title_short	A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
title_full	A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
title_fullStr	A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
title_full_unstemmed	A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays
title_sort	computational model for classification of brca2 variants using mouse embryonic stem cell-based functional assays
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/040ac1e333f54a36a947eae448e108dd
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A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays

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