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Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm

BACKGROUND: Lynch syndrome is a hereditary cancer syndrome associated with high risks of colorectal and endometrial cancer that is caused by pathogenic variants in the mismatch repair genes (MLH1, MSH2, MSH6, PMS2, EPCAM). Accurate classification of variants identified in these genes as pathogenic o...

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Autores principales: Morris, Brian, Hughes, Elisha, Rosenthal, Eric, Gutin, Alexander, Bowles, Karla R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4929734/
https://www.ncbi.nlm.nih.gov/pubmed/27363726
http://dx.doi.org/10.1186/s12863-016-0407-0
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author Morris, Brian
Hughes, Elisha
Rosenthal, Eric
Gutin, Alexander
Bowles, Karla R.
author_facet Morris, Brian
Hughes, Elisha
Rosenthal, Eric
Gutin, Alexander
Bowles, Karla R.
author_sort Morris, Brian
collection PubMed
description BACKGROUND: Lynch syndrome is a hereditary cancer syndrome associated with high risks of colorectal and endometrial cancer that is caused by pathogenic variants in the mismatch repair genes (MLH1, MSH2, MSH6, PMS2, EPCAM). Accurate classification of variants identified in these genes as pathogenic or benign enables informed medical management decisions. Previously, we developed a clinical History Weighting Algorithm (HWA) for the classification of variants of uncertain significance (VUSs) in BRCA1 and BRCA2. The BRCA1/2 HWA is based on the premise that pathogenic variants in these genes will be identified more often in individuals with strong personal and/or family histories of breast and/or ovarian cancer, while the identification of benign variants should be independent of cancer history. Here we report the development of a similar HWA to allow for classification of VUSs in genes associated with Lynch syndrome using data collected through both syndrome-specific and pan-cancer panel testing. METHODS: Upon completion of algorithm development, the HWA was tested using simulated variants constructed from 79,214 probands, as well as 379 true variants. Positive (PPV) and negative predictive values (NPV) were calculated on a per gene basis. RESULTS: 25,500 pathogenic and 50,500 benign simulated variants were analyzed using the HWA and the PPVs and NPVs for each gene were greater than 0.997 and 0.999, respectively. The HWA was also evaluated using 100 trials for each of the 379 true variants. PPVs of >0.998 and NPVs of >0.999 were obtained for all genes. CONCLUSIONS: We have developed and implemented a HWA to aid in the classification of VUSs in genes associated with Lynch syndrome. The work presented here demonstrates that this HWA is able to classify MLH1, MSH2, and MSH6 VUSs as either benign or pathogenic with high accuracy.
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spelling pubmed-49297342016-07-02 Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm Morris, Brian Hughes, Elisha Rosenthal, Eric Gutin, Alexander Bowles, Karla R. BMC Genet Research Article BACKGROUND: Lynch syndrome is a hereditary cancer syndrome associated with high risks of colorectal and endometrial cancer that is caused by pathogenic variants in the mismatch repair genes (MLH1, MSH2, MSH6, PMS2, EPCAM). Accurate classification of variants identified in these genes as pathogenic or benign enables informed medical management decisions. Previously, we developed a clinical History Weighting Algorithm (HWA) for the classification of variants of uncertain significance (VUSs) in BRCA1 and BRCA2. The BRCA1/2 HWA is based on the premise that pathogenic variants in these genes will be identified more often in individuals with strong personal and/or family histories of breast and/or ovarian cancer, while the identification of benign variants should be independent of cancer history. Here we report the development of a similar HWA to allow for classification of VUSs in genes associated with Lynch syndrome using data collected through both syndrome-specific and pan-cancer panel testing. METHODS: Upon completion of algorithm development, the HWA was tested using simulated variants constructed from 79,214 probands, as well as 379 true variants. Positive (PPV) and negative predictive values (NPV) were calculated on a per gene basis. RESULTS: 25,500 pathogenic and 50,500 benign simulated variants were analyzed using the HWA and the PPVs and NPVs for each gene were greater than 0.997 and 0.999, respectively. The HWA was also evaluated using 100 trials for each of the 379 true variants. PPVs of >0.998 and NPVs of >0.999 were obtained for all genes. CONCLUSIONS: We have developed and implemented a HWA to aid in the classification of VUSs in genes associated with Lynch syndrome. The work presented here demonstrates that this HWA is able to classify MLH1, MSH2, and MSH6 VUSs as either benign or pathogenic with high accuracy. BioMed Central 2016-07-01 /pmc/articles/PMC4929734/ /pubmed/27363726 http://dx.doi.org/10.1186/s12863-016-0407-0 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Morris, Brian
Hughes, Elisha
Rosenthal, Eric
Gutin, Alexander
Bowles, Karla R.
Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title_full Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title_fullStr Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title_full_unstemmed Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title_short Classification of genetic variants in genes associated with Lynch syndrome using a clinical history weighting algorithm
title_sort classification of genetic variants in genes associated with lynch syndrome using a clinical history weighting algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4929734/
https://www.ncbi.nlm.nih.gov/pubmed/27363726
http://dx.doi.org/10.1186/s12863-016-0407-0
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