COMPLETE VARIANT PROFILING OF ALL KNOWN BREAST CANCER GENES

描述（由申请人提供）：该项目的目标是识别和表征所有已知乳腺癌基因中临床可操作的突变，以便将其纳入临床护理。将对来自3000例病例和2000例祖先匹配对照的DNA样本进行测序，以确定所有已知的乳腺癌基因。生殖系突变将在功能和乳腺癌的相对风险方面进行评估。乳腺癌基因中临床可操作变异的发现和表征涉及三个目标。在AIM 1中，我们将对来自3000名乳腺癌女性和2000名祖先匹配对照的DNA样本中的所有18个已知乳腺癌基因进行测序。与此同时，我们将同样评估从我们独立的家族研究中出现的6个新的遗传性乳腺癌候选基因。对于所有特征，我们将使用我们最近开发的方法同时捕获和多重测序，以bb100 - 300倍的中位覆盖率，外显子，内含子，调控和两侧乳腺癌基因间区域。在AIM 2中，我们将识别所有被预测会导致基因功能丧失的变异，包括截断突变（无论是无义突变、帧移、破坏CNV等）、完全基因组缺失和假定的破坏性错义突变。我们将使用生物信息学工具评估所有变异对基因功能的影响。具有可能剪接效应的变异将通过患者RNA和离体小基因的RT-PCR进行评估。最有希望的错义等位基因将在实验中进行DNA损伤反应、酶活性丧失和其他适当的功能分析。在AIM 3中，我们将根据病例与对照组中明确功能丧失突变的组合频率，测试乳腺癌与24个基因中每一个基因的关联强度。将估算每个基因的相对风险。目前，将基因组学整合到临床护理中的挑战对于乳腺癌的遗传易感性来说是及时的，因为多种致病基因是已知的，专门的乳房筛查方式是可用的，降低风险的手术是有效的，乳腺癌的治疗受患者基因型的影响。这个项目的目标是为翻译提供必要的信息和技术。

DESCRIPTION (provided by applicant): The goal of this project is to identify and characterize clinically actionable mutations in all known breast cancer genes so that they can be incorporated into clinical care. DNA samples from 3000 cases and 2000 ancestry matched controls will be sequenced for all known breast cancer genes. Germline mutations will be evaluated with respect to function and relative risk of breast cancer. The discovery and characterization of clinically actionable variants in breast cancer genes involves three aims. In AIM 1, we will sequence all 18 known breast cancer genes in DNA samples from 3000 women with breast cancer and 2000 ancestry-matched controls. In parallel, we will similarly evaluate 6 new candidate genes for inherited breast cancer that have emerged from our independent family studies. For all characterizations, we will use our recently developed approach for simultaneous capture and multiplexed sequencing, to >300-fold median coverage, of exons, introns, regulatory, and flanking intergenic regions of breast cancer genes. In AIM 2, we will identify all variants predicted to lead to loss of gene function, including truncating mutations (whether nonsense, frameshifts, disrupting CNV and so on), complete genomic deletions, and putatively damaging missense mutations. We will assess all variants for effect on gene function using bioinformatics tools. Variants with possible splice effects will be evaluated by RT-PCR of patient RNA and ex vivo minigenes. The most promising missense alleles will be tested experimentally for DNA damage response, loss of enzyme activity and other functional assays as appropriate. In AIM 3, we will test the strength of association of breast cancer with each of the 24 genes, based on the combined frequency of unambiguous loss-of-function mutations in cases vs controls. Relative risks will be estimated for each gene. The challenge of integrating genomics into clinical care is timely now for inherited predisposition to breast cancer, because multiple causal genes are known, specialized breast screening modalities are available, risk- reducing surgery is effective, and treatment of breast cancer is influenced by the patient's genotype. The goal of this project is to provide the information and technology necessary for this translation.