BRCA1 and BRCA2 missense mutations and breast cancer risk

描述(由申请人提供)：具有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增加。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，因为手术预防和靶向治疗受益于了解癌症易感突变的存在。然而，这一过程往往因为检测到不确定意义的变异(VUS)而变得复杂，这些变异主要是错义突变，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VU的信息意味着，被发现携带这些变异的个人无法从增强的风险评估中受益，也无法在手术预防或定制治疗方案(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的模型来确定在BRCA1和BRCA2基因中发现的VUS的癌症相关性，该模型结合了用于VUS分类的新的遗传和功能方法。然而，由于BRCA1和BRCA2是大蛋白，有几个已建立的不同功能，可能在癌症发生中起作用，也可能不起作用，因此在检测方法应用于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变体进行全面的功能分析，以确定哪些分子功能有助于肿瘤抑制；在目标2中，我们将对BRCA2变体进行全面的功能分析，以确定哪些分子功能影响癌症风险。具体地说，我们将评估已知的致病和非致病变异对BRCA1和BRCA2定义功能的影响，然后使用与癌症风险相关的分析将我们的分析扩展到VUS。在目标3中，我们建议扩展多因素模型用于BRCA1和BRCA2 VU的分类。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历史纳入到已建立的预测模型中。我们将把该模型应用于中等风险候选VU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相结合，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.