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Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO

Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many sy...

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Autores principales: Lee, Gavin, Liang, Jane W, Zhang, Qing, Huang, Theodore, Choirat, Christine, Parmigiani, Giovanni, Braun, Danielle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478415/
https://www.ncbi.nlm.nih.gov/pubmed/34406119
http://dx.doi.org/10.7554/eLife.68699
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author Lee, Gavin
Liang, Jane W
Zhang, Qing
Huang, Theodore
Choirat, Christine
Parmigiani, Giovanni
Braun, Danielle
author_facet Lee, Gavin
Liang, Jane W
Zhang, Qing
Huang, Theodore
Choirat, Christine
Parmigiani, Giovanni
Braun, Danielle
author_sort Lee, Gavin
collection PubMed
description Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes. We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro.
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spelling pubmed-84784152021-09-30 Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO Lee, Gavin Liang, Jane W Zhang, Qing Huang, Theodore Choirat, Christine Parmigiani, Giovanni Braun, Danielle eLife Cancer Biology Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes. We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro. eLife Sciences Publications, Ltd 2021-08-18 /pmc/articles/PMC8478415/ /pubmed/34406119 http://dx.doi.org/10.7554/eLife.68699 Text en © 2021, Lee et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cancer Biology
Lee, Gavin
Liang, Jane W
Zhang, Qing
Huang, Theodore
Choirat, Christine
Parmigiani, Giovanni
Braun, Danielle
Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title_full Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title_fullStr Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title_full_unstemmed Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title_short Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
title_sort multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel r package panelpro
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478415/
https://www.ncbi.nlm.nih.gov/pubmed/34406119
http://dx.doi.org/10.7554/eLife.68699
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