Genetic Epidemiology of Breast Cancer: Risk, Instability, and Statistical Methods

描述（由申请人提供）：乳腺癌是发病率和死亡率的主要来源，并且仍然是美国女性中最常见的癌症，2008年新发病例超过183，000例（Ries et al. 2008）。本申请涉及乳腺癌发展的两个方面：生殖系突变，如两个肿瘤抑制基因BRCA 1/2，以及以拷贝数变化和等位基因丢失为特征的体细胞突变。本申请的第一个目的是在没有外部疾病发病率数据的情况下，从基于人群的病例对照研究中估计候选基因（如BRCA 1/2）的年龄依赖性突变功能。从数据和建模框架中获得的估计值将用于估计突变携带者概率并预测女性的乳腺癌风险。一个共享的脆弱性模型将被用来解释广泛观察到的家庭之间的重大风险异质性。该模型将扩展到一个通用的多变量脆弱性模型，以允许不同类型的关系和多个候选基因相关表型的相关程度不同。尽管最近成功地鉴定了乳腺癌的新候选基因座，但约四分之三的乳腺癌病例在家庭中没有聚集性。据信，癌症的发展是由于染色体位置上遗传畸变的积累，这些染色体位置对维持正常细胞功能至关重要。来自特定染色体位置的遗传信息的丢失和获得被认为是肿瘤抑制基因或癌基因参与肿瘤发生的指示。使用基因组不稳定性数据，本申请的第二个目的是鉴定参与乳腺癌肿瘤发展的新型致癌网络。图形模型为基础的方法将开发使用新的稀疏回归和多重测试技术。随着高通量基因分型技术的广泛应用，研究人员能够进行大规模的全基因组关联和基因组不稳定性研究。这使我们能够确定新的候选基因座，可能只有适度的影响乳腺癌的风险或发现致癌网络在这样一个细节，这是以前不可行的。有一个很大的需要，这些新的基因的特征，并提供这些网络的推理。这里提出的方法是朝着这个方向的努力。公共卫生相关性：该项目旨在描述与人群中基因相关的乳腺癌风险，估计突变携带者概率，并预测健康个体在这些基因突变状态下患乳腺癌的风险。它还旨在了解基因组不稳定性在乳腺肿瘤发生和发展中的作用。最终目标是为设计有效的个体定制预防策略以降低乳腺癌风险提供见解。

DESCRIPTION (provided by applicant): Breast cancer is a major source of morbidity and mortality, and remains the most common cancer occurring in U.S. women, with over 183,000 new cases for 2008 (Ries et al. 2008). This application addresses two aspects of breast cancer development: germline mutations, as in two tumor suppressor genes BRCA1/2, and somatic mutations characterized by copy number changes and allelic loss. The first aim of this application is on the estimation of the age-dependent penetrance function of candidate genes like BRCA1/2 from population-based case-control studies without external disease incidence data. The estimates obtained from the data and the modeling framework will be used to estimate the mutational carrier probability and predict the breast cancer risk of a woman. A shared frailty model will be used to account for the widely observed substantial risk heterogeneity among families. The model will be extended to a general multivariate frailty model to allow for varying degrees of the correlation for different types of relations and multiple candidate gene-related phenotypes. Despite recent successes in identifying novel candidate loci for breast cancer, about three- quarter of breast cancer cases having no clustering in families. It is believed that cancer develops as a result of an accumulation of genetic aberrations at chromosomal locations that are critical in maintaining normal cell functions. The loss and gain of genetic information from specific chromosomal locations are considered an indication for the involvement of tumor suppressor or oncogenes in the tumorigenesis. Using genomic instability data, the second aim of this application is on identifying novel oncogenic networks involved in breast cancer tumor development. Graphical model-based methods will be developed by using novel sparse regression and multiple testing techniques. As the high throughput genotyping technologies become widely available, researchers are able to conduct large scale genome-wide association and genomic instability studies. This allows us to identify novel candidate loci that may have only moderate effect on breast cancer risk or discover oncogenic networks at such a detail that is not previously feasible. There is a great need to characterize these novel genes and provide inference for these networks. The methods proposed here are efforts towards this direction. PUBLIC HEALTH RELEVANCE: This project aims to characterize the breast cancer risk in relation to genes in the population, estimate the mutation carrier probabilities, and predict a healthy individual's risk for developing breast cancer given the mutational status in these genes. It also aims to gain knowledge on the role of genomic instabilities in breast tumor initiation and progression. The ultimate goal is to provide insight in devising effective individual-tailored prevention strategies for reducing breast cancer risk.