Statistical Methods for Cancer Genes

描述（由申请人提供）：识别由于遗传易感性而处于癌症高风险的个体是复杂的，并且越来越重要。概率预测算法利用孟德尔遗传和易感基因的其他生物学特征的领域知识，成功地促进了改进的筛查，预防和基因检测，以及癌症研究的设计和分析。研究人员开发、验证、应用和传播了广泛使用的孟德尔模型BRCAPRO。根据他们的经验，他们已经确定了在癌症遗传学中需要新一代孟德尔预测模型。 第一个目标是开发统计方法，推广目前在临床遗传咨询实践中使用的孟德尔模型。创新将集中在五个领域：A）解释报告的谱系中的错误; B）解释多个癌症部位的时间-事件分布的依赖性; C）解释由共享环境因素或其他来源引起的家族相关性; D）解释多等位基因综合征;以及E）合并关于协变量和与基因活性相关的生物标志物的信息。第二个目标将引入一类新的多综合征模型，以同时识别癌症综合征和预测突变携带者状态。这些将使临床医生和研究人员能够解决癌症易感基因表型重叠以及具有多个位点的散发性家族的高频率所带来的新挑战。第三个目标是开发灵活的用户友好的软件，用于研究和临床环境中的方法的应用。该提案的目的将克服目前临床遗传咨询中使用的工具的紧迫的实际局限性，从而有助于改善基因检测的筛查，预防和决策。

DESCRIPTION (provided by applicant): Identifying individuals at high risk of cancer because of inherited genetic susceptibility is complex and increasingly important. Probabilistic prediction algorithms that exploit domain knowledge of Mendelian inheritance and other biological characteristics of susceptibility genes successfully contribute to improved screening, prevention, and genetic testing, and to the design and analysis of cancer studies. The investigators have developed, validated, applied and disseminated the widely used Mendelian model BRCAPRO. Based on their experience they have identified the need for a new generation of Mendelian prediction models in cancer genetics. The first aim will develop statistical approaches that generalize Mendelian models currently used in clinical genetic counseling practice. Innovation will focus on five areas: A) accounting for errors in reported pedigrees; B) accounting for dependencies in time-to-event distributions for multiple cancer sites; C) accounting for familial correlations arising from shared environmental factors or other sources; D) accounting for multiallelic syndromes; and E) incorporating information on covariates and on biomarkers related to the genes' activity. The second aim will introduce a novel class of multi-syndrome models to simultaneously identify cancer syndromes and predict mutation carrier status. These will enable clinicians and researchers to address the emerging challenges posed by the overlap in phenotype for cancer susceptibility genes, and by the high frequency of sporadic families with multiple sites. The third aim will develop flexible user-friendly software for the application of the methods in both research and clinical settings. The aims of this proposal will overcome pressing practical limitations of tools currently used in clinical genetic counseling, and thus contribute to improved screening, prevention and decision making about genetic testing.