Cargando…

Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome

PURPOSE: Variants in the DNA mismatch repair (MMR) gene MSH6, identified in individuals suspected of Lynch syndrome, are difficult to classify owing to the low cancer penetrance of defects in that gene. This not only obfuscates personalized health care but also the development of a rapid and reliabl...

Descripción completa

Detalles Bibliográficos
Autores principales: Drost, Mark, Tiersma, Yvonne, Glubb, Dylan, Kathe, Scott, van Hees, Sandrine, Calléja, Fabienne, Zonneveld, José B. M., Boucher, Kenneth M., Ramlal, Renuka P. E., Thompson, Bryony A., Rasmussen, Lene Juel, Greenblatt, Marc S., Lee, Andrea, Spurdle, Amanda B., Tavtigian, Sean V., de Wind, Niels
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200593/
https://www.ncbi.nlm.nih.gov/pubmed/31965077
http://dx.doi.org/10.1038/s41436-019-0736-2
_version_ 1783529366440902656
author Drost, Mark
Tiersma, Yvonne
Glubb, Dylan
Kathe, Scott
van Hees, Sandrine
Calléja, Fabienne
Zonneveld, José B. M.
Boucher, Kenneth M.
Ramlal, Renuka P. E.
Thompson, Bryony A.
Rasmussen, Lene Juel
Greenblatt, Marc S.
Lee, Andrea
Spurdle, Amanda B.
Tavtigian, Sean V.
de Wind, Niels
author_facet Drost, Mark
Tiersma, Yvonne
Glubb, Dylan
Kathe, Scott
van Hees, Sandrine
Calléja, Fabienne
Zonneveld, José B. M.
Boucher, Kenneth M.
Ramlal, Renuka P. E.
Thompson, Bryony A.
Rasmussen, Lene Juel
Greenblatt, Marc S.
Lee, Andrea
Spurdle, Amanda B.
Tavtigian, Sean V.
de Wind, Niels
author_sort Drost, Mark
collection PubMed
description PURPOSE: Variants in the DNA mismatch repair (MMR) gene MSH6, identified in individuals suspected of Lynch syndrome, are difficult to classify owing to the low cancer penetrance of defects in that gene. This not only obfuscates personalized health care but also the development of a rapid and reliable classification procedure that does not require clinical data. METHODS: The complete in vitro MMR activity (CIMRA) assay was calibrated against clinically classified MSH6 variants and, employing Bayes’ rule, integrated with computational predictions of pathogenicity. To enable the validation of this two-component classification procedure we have employed a genetic screen to generate a large set of inactivating Msh6 variants, as proxies for pathogenic variants. RESULTS: The genetic screen-derived variants established that the two-component classification procedure displays high sensitivities and specificities. Moreover, these inactivating variants enabled the direct reclassification of human variants of uncertain significance (VUS) as (likely) pathogenic. CONCLUSION: The two-component classification procedure and the genetic screens provide complementary approaches to rapidly and cost-effectively classify the large majority of human MSH6 variants. The approach followed here provides a template for the classification of variants in other disease-predisposing genes, facilitating the translation of personalized genomics into personalized health care.
format Online
Article
Text
id pubmed-7200593
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group US
record_format MEDLINE/PubMed
spelling pubmed-72005932020-05-07 Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome Drost, Mark Tiersma, Yvonne Glubb, Dylan Kathe, Scott van Hees, Sandrine Calléja, Fabienne Zonneveld, José B. M. Boucher, Kenneth M. Ramlal, Renuka P. E. Thompson, Bryony A. Rasmussen, Lene Juel Greenblatt, Marc S. Lee, Andrea Spurdle, Amanda B. Tavtigian, Sean V. de Wind, Niels Genet Med Article PURPOSE: Variants in the DNA mismatch repair (MMR) gene MSH6, identified in individuals suspected of Lynch syndrome, are difficult to classify owing to the low cancer penetrance of defects in that gene. This not only obfuscates personalized health care but also the development of a rapid and reliable classification procedure that does not require clinical data. METHODS: The complete in vitro MMR activity (CIMRA) assay was calibrated against clinically classified MSH6 variants and, employing Bayes’ rule, integrated with computational predictions of pathogenicity. To enable the validation of this two-component classification procedure we have employed a genetic screen to generate a large set of inactivating Msh6 variants, as proxies for pathogenic variants. RESULTS: The genetic screen-derived variants established that the two-component classification procedure displays high sensitivities and specificities. Moreover, these inactivating variants enabled the direct reclassification of human variants of uncertain significance (VUS) as (likely) pathogenic. CONCLUSION: The two-component classification procedure and the genetic screens provide complementary approaches to rapidly and cost-effectively classify the large majority of human MSH6 variants. The approach followed here provides a template for the classification of variants in other disease-predisposing genes, facilitating the translation of personalized genomics into personalized health care. Nature Publishing Group US 2020-01-22 2020 /pmc/articles/PMC7200593/ /pubmed/31965077 http://dx.doi.org/10.1038/s41436-019-0736-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have permission under this license to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Article
Drost, Mark
Tiersma, Yvonne
Glubb, Dylan
Kathe, Scott
van Hees, Sandrine
Calléja, Fabienne
Zonneveld, José B. M.
Boucher, Kenneth M.
Ramlal, Renuka P. E.
Thompson, Bryony A.
Rasmussen, Lene Juel
Greenblatt, Marc S.
Lee, Andrea
Spurdle, Amanda B.
Tavtigian, Sean V.
de Wind, Niels
Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title_full Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title_fullStr Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title_full_unstemmed Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title_short Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
title_sort two integrated and highly predictive functional analysis-based procedures for the classification of msh6 variants in lynch syndrome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200593/
https://www.ncbi.nlm.nih.gov/pubmed/31965077
http://dx.doi.org/10.1038/s41436-019-0736-2
work_keys_str_mv AT drostmark twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT tiersmayvonne twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT glubbdylan twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT kathescott twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT vanheessandrine twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT callejafabienne twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT zonneveldjosebm twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT boucherkennethm twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT ramlalrenukape twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT thompsonbryonya twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT rasmussenlenejuel twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT greenblattmarcs twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT leeandrea twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT spurdleamandab twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT tavtigianseanv twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome
AT dewindniels twointegratedandhighlypredictivefunctionalanalysisbasedproceduresfortheclassificationofmsh6variantsinlynchsyndrome