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

• 批准号: 9902384
• 负责人: Wenyi Wang
• 金额: $ 42.02万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9902384
• 关键词: Accounting; Affect; Assessment tool; BRCA1 gene; Bioinformatics; Cancer Center; Cancer Etiology; Clinic; Clinical; Clinical Management; Computer software; Counseling; Country; Data; Data Set; Decision Making; Disease; Early Diagnosis; Education; Epidemiologist; Epithelial; Epithelium; 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 model; screening; screening program; software development; tool

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.

项目概要 复杂的风险预测模型极大地改善了遗传性癌症的筛查和检测 乳腺癌中的 BRCA1/2 突变等综合征。这样的定量风险预测模型亟待建立 在证明了李法美尼综合症（LFS）减少后，需要早期发现 对该综合征进行监测测试的死亡率。 LFS 主要由 TP53 种系突变引起 肿瘤抑制基因，其特点是癌症发生在生命相对较早的时期，通常在一段时间内反复发生 终生，并影响与其他癌症综合征重叠的多个部位，特别是 遗传性乳腺癌和卵巢癌综合征。我们的目标是改善临床管理 通过建立数学模型来评估有早发癌症家族史的个体1) TP53 测试之前的种系突变携带者概率和 2) 发生的绝对终生风险 TP53 突变个体的癌症。我们的理由是我们的先进模型将使 对具有遗传性TP53突变的家庭进行系统、全面的风险评估，以便遗传 咨询师和医生可以为 TP53 携带者提供更有效的咨询和筛查 考虑到这些个体中癌症类型结果的高频率和多样化，种系突变。我们将 通过以下具体目标来实现我们的研究目标。 1) 描述特定症状的发作 有 LFS 风险的个体的癌症类型： a) 通过以下方式估计 TP53 突变相关癌症的外显率： 癌症类型，使用 MD 安德森癌症中心 (MDACC) 和外部诊所的大家庭数据； b) 开发 LFSPROCS 以纳入癌症类型特异性外显率，并在 预测未来风险； c) 用额外的癌症风险修饰因子丰富 LFSPRO，例如 HER2 状态 乳腺癌; 2) 描述有 LFS 风险的个体的原发癌症数量： a) 估计 使用大家庭数据计算原发癌症数量的外显率； c) 开发 LFSPROMP 和 LFSPROMP+CS 纳入新的渗透率并验证这些模型； 3) 开发软件和 在癌症遗传诊所中传播它。我们的重大贡献将是开发先进的 定量风险评估工具，将提供更准确的风险量化，并提供通用的风险评估工具 统计框架，包括额外的癌症部位和癌症基因，用于未来的风险评估。 相关软件套件 LFSPRO 将快速传播到 MDACC Li-Fraumeni Education 和早期检测 (LEAD) 筛查计划，以及全国的其他筛查研究。 LFSPRO 是 已经集成到 BayesMendel 和 CancerGene 软件包中，广泛用于风险评估和 在高风险癌症诊所，特别是乳腺癌诊所提供咨询。加上我们先进的 模型，这些软件工具将继续为临床环境下的新人群提供 LFS 咨询 并惠及更多受 TP53 突变影响的家庭。