Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
- ETH Zürich and EPFL, Switzerland
- Harvard T.H. Chan School of Public Health, United States
- Broad Institute of MIT and Harvard, United States
Abstract
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.
Data availability
This manuscript introduces PanelPRO, an innovative multi-gene multi-cancer Mendelian model. Software for this model, including the model parameter database, is available to download for research use; https://projects.iq.harvard.edu/bayesmendel/panelpro
Article and author information
Author details
Funding
National Institutes of Health (5T32CA009337)
- Jane W Liang
- Theodore Huang
National Institutes of Health (2T32CA009001)
- Theodore Huang
National Institutes of Health (4P30CA006516)
- Giovanni Parmigani
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Lee et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
eLife 10:e68699.
https://doi.org/10.7554/eLife.68699
