BRCA1 and BRCA2 missense mutations and breast cancer risk

描述（由申请人提供）：BRCA1和BRCA2基因种系失活突变的女性患乳腺癌和卵巢癌的风险显著升高。这些基因突变的临床基因检测已成为临床实践的重要组成部分，因为与癌症易感突变存在的知识相关的手术预防和靶向治疗益处。然而，这一过程往往因不确定意义变异（VUS）的检测而变得复杂，VUS主要是错义突变，对蛋白质功能的影响未知，与癌症风险的关联未知。缺乏关于这些VUS的信息意味着携带这些变异的个体不能从加强的风险评估中获益，也不能在手术预防或定制治疗选择（如铂和PARP抑制剂治疗）方面做出明智的决定。在这里，我们建议通过开发一个综合模型，结合新的VUS分类的遗传和功能方法，来确定在BRCA1和BRCA2基因中发现的VUS与癌症的相关性。然而，由于BRCA1和BRCA2是大蛋白，具有几种已确定的不同功能，这些功能可能在癌症发展中起作用，也可能不起作用，因此在将检测应用于VUS分类之前，必须确定不同功能对肿瘤抑制和癌症风险的贡献。因此，在Aim1中，我们将对BRCA1变异进行全面的功能分析，以确定哪些分子功能有助于抑制肿瘤，在Aim 2中，我们将对BRCA2变异进行全面的功能分析，以确定哪些分子功能影响癌症的风险。具体而言，我们将评估已知致病性和非致病性变异对BRCA1和BRCA2定义功能的影响，然后使用发现与癌症风险相关的检测将我们的分析扩展到VUS。在Aim 3中，我们提出扩展BRCA1和BRCA2 VUS分类的多因子模型。在这里，我们将开发新的方法，允许将VUS先证者的个人和家族史纳入已建立的预测模型。我们将把该模型应用于候选中度风险VUS的分类，最重要的是，我们将开发一个贝叶斯混合模型，该模型将定量功能分析数据与遗传数据集成在一起，用于VUS分类。

DESCRIPTION (provided by applicant): Women with germline inactivating mutations in the BRCA1 and BRCA2 genes are at significantly elevated risk of breast and ovarian cancer. Clinical genetic testing for mutations in these genes has become an important part of clinical practice because of the surgical prevention and targeted treatment benefits associated with knowledge of the presence of a cancer predisposing mutation. However, this process is often complicated by the detection of Variants of Uncertain Significance (VUS), which are predominantly missense mutations with an unknown influence on protein function and unknown association with cancer risk. The lack of information about these VUS means that individuals found to carry these variants cannot benefit from enhanced risk assessment or make informed decisions about surgical prevention or tailored treatment options such as platinum and PARP inhibitor therapy. Here we propose to determine the cancer relevance of VUS found throughout the BRCA1 and BRCA2 genes by developing a comprehensive model incorporating new genetic and functional approaches for VUS classification. However, because BRCA1 and BRCA2 are large proteins, with several established distinct functions that may or may not have a role in cancer development, the contribution of the different functions to tumor suppression and cancer risk must be determined before assays can be applied to VUS classification. Thus, in Aim1 we will perform a comprehensive functional analysis of BRCA1 variants to determine which molecular functions contribute to tumor suppression and in Aim 2 we will perform a comprehensive functional analysis of BRCA2 variants to determine which molecular functions influence the risk of cancer. Specifically, we will evaluate the influence of known pathogenic and non- pathogenic variants on defined functions of BRCA1 and BRCA2 and then extend our analyses to VUS using the assays found to be associated with cancer risk. In Aim 3 we propose to extend the multifactorial model for classification of BRCA1 and BRCA2 VUS. Here we will develop new methods allowing incorporation of personal and family histories of VUS probands into an established predictive model. We will apply the model to classification of candidate moderate risk VUS, and most importantly, we will develop a Bayesian mixture model that integrates quantitative functional assay data with genetic data for the purposes of VUS classification.