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Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53

TP53种系突变家族癌症风险预测的统计方法和工具

基本信息

批准号：
10370406
负责人：
Wenyi Wang
金额：
$ 35.15万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10370406
关键词：
Accounting Affect Assessment tool BRCA mutations Bioinformatics Cancer Center Cancer Etiology Clinic Clinical Clinical Management Computer software Counseling Country Data Data Set Decision Making Disease Early Diagnosis Education Epidemiologist Epithelial Evaluation Extended Family Family Family history of Family member Frequencies Future Genetic Genetic Counseling Germ-Line Mutation Hereditary Breast and Ovarian Cancer Syndrome High-Risk Cancer Human Individual Inherited International Li-Fraumeni Syndrome Life Malignant Neoplasms Medical Modeling Mutation National Cancer Institute Oncogenes Organ Outcome Outcomes Research Pattern Pediatrics Penetrance Physicians Population Probability Public Health Recording of previous events Research Risk Risk Assessment Screening for cancer Site Software Tools Statistical Methods Syndrome TP53 gene Testing Tissues Tumor Suppressor Genes University of Texas M D Anderson Cancer Center cancer diagnosis cancer genetics cancer risk cancer site cancer type clinical practice early onset genetic counselor improved indexing large datasets lifetime risk malignant breast neoplasm mathematical model member mortality mutation carrier open source programs receptor risk prediction risk prediction model screening screening program software development tool

项目摘要

Project Summary Sophisticated risk prediction modeling has greatly improved screening and testing for inheritable cancer syndromes such as BRCA1/2 mutations in breast cancer. Such a quantitative risk prediction model is urgently needed for the early detection of the Li-Fraumeni syndrome (LFS) following the demonstration of reduced mortality with surveillance testing for that syndrome. LFS primarily arises from germline mutations in the TP53 tumor suppressor gene and is characterized by cancer occurring relatively early in life, often repeatedly over a lifetime, and affecting multiple sites that overlap with those of other cancer syndromes, in particular the hereditary breast and ovarian cancer syndrome. Our objective is to improve the clinical management of individuals with a family history of early-onset cancers by developing mathematical models to assess 1) germline mutation carrier probability prior to TP53 testing and 2) the absolute lifetime risk of developing cancers in individuals with TP53 mutations. Our rationale is that our advanced models will enable the systematic and comprehensive risk evaluation of families with inherited TP53 mutations so that genetic counselors and physicians can provide more effective counseling and screening of individuals who carry TP53 germline mutations, given the high frequency and varied cancer-type outcomes in these individuals. We will accomplish our research objective through the following Specific Aims. 1) Characterize the onset of specific cancer types for individuals at risk of LFS: a) Estimate the penetrance of TP53 mutation-associated cancers by cancer type, using extended-family data from MD Anderson Cancer Center (MDACC) and from external clinics; b) Develop LFSPROCS to incorporate cancer-type-specific penetrances, and validate these models in predicting future risk; c) Enrich LFSPRO with additional modifiers of cancer risk, such as HER2 status for breast cancer; 2) Characterize the number of primary cancers for individuals at risk of LFS: a) estimate the penetrance for the number of primary cancers using extended-family data; c) Develop LFSPROMP and LFSPROMP+CS to incorporate new penetrances and validate these models; and 3) Develop software and disseminate it among cancer genetic clinics. Our significant contribution will be to develop an advanced quantitative risk assessment tool that will provide more accurate risk quantification, and to provide a general statistical framework for including additional cancer sites and cancer genes for risk assessment in the future. The associated software suite LFSPRO will be quickly disseminated into the MDACC Li-Fraumeni Education and Early Detection (LEAD) screening program, as well as other screening studies in the nation. LFSPRO is already integrated in BayesMendel and CancerGene packages, which are widely used for risk assessment and counseling at high-risk cancer clinics, in particular breast cancer clinics. With the addition of our advanced models, these software tools will continue to bring LFS counseling to new populations under clinical settings and reach more families that are affected by TP53 mutations.

项目总结