学术文献库

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 to identify these individuals focus on specific syndromes by including family and personal history for a small number of cancers. Recent evidence from multi-gene panel testing has shown that many syndromes once thought to be distinct are overlapping, motivating the development of models that incorporate family history information on several cancers and predict mutations for more comprehensive panels of genes. Once such class of models are Mendelian risk prediction models, which use family history information and Mendelian laws of inheritance to estimate the probability of carrying genetic mutations, as well as future risk of developing associated cancers. To flexibly model the complexity of many cancer-mutation associations, we present a new software tool called PanelPRO, a R package that extends the previously developed BayesMendel R package to user-selected lists of susceptibility genes and associated cancers. The model identifies individuals at an increased risk of carrying cancer susceptibility gene mutations and predicts future risk of developing hereditary cancers associated with those genes. Additional functionalities adjust for prophylactic interventions, known genetic testing results, and risk modifiers such as race and ancestry. The package comes with a customizable database with default parameter values estimated from published studies. The PanelPRO package is open-source and provides a fast and flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. The software enables the identification of high-risk individuals, which will have an impact on personalized prevention strategies for cancer and individualized decision making about genetic testing.