Impact of germline variants on racial and ethnic differences in somatic mutation frequency

摘要 肿瘤测序数据显示，种族和种族之间的突变频率存在显著差异。 种族群体。其中一些差异可以归因于环境暴露，如吸烟 但即使在根据已知因素进行调整后，差距仍然存在。描述良好的例子包括 与亚裔和非裔美国人相比，非裔美国人乳腺癌中TP53突变的发生率更高 非西班牙裔白人女性和KRAS突变在结直肠癌中的高发生率 相对于其他种族群体的非裔美国人。因为癌症的侵袭性和存活率取决于 在肿瘤中，通路受到干扰，即癌症驱动因素突变在人群中发生的频率 应该会影响到一些已观察到的种族结果差异。来自我们实验室和其他机构的新兴数据 表明生殖系遗传变异影响肿瘤中的躯体事件。我们发现了两者之间的联系 来自癌症基因组图谱的头颈部鳞状细胞癌中的AURKA变异体和TP53。我们 发现至少有一个AURKA等位基因的个体以前与癌症风险相关，更有可能 相对于非风险相关等位基因纯合子的个体，具有功能获得型TP53突变。 这些研究和其他研究表明，生殖系遗传变异和体细胞突变之间存在关联 (GxM)在肿瘤发生中的作用。本研究将寻找与TP53、PIK3CA、 和KRAS突变，以解释肿瘤生物学中的种族差异。在这项研究中，我们将测试 创新的假说认为，不同种族之间频率不同的生殖系遗传变异推动了 观察到体细胞突变频率的种族差异。我们的目标是了解该协会 在种族差异中体细胞突变、生殖系基因变异和肿瘤发生之间的关系，并确定 使用体外模型研究GxM关联对癌症表型的生物学影响。利用现有的基因 和突变数据，这些目标将在两个目标上实现：1.识别和表征GxM 乳腺癌中TP53和PIK3CA突变的相关性以了解胚系变异如何 导致体细胞突变频率的种族差异。在3700个GxM关联研究中发现的变体 乳腺癌患者将在来自多个种族和地区的4000例额外乳腺癌病例中进行评估 种族群体。将使用CRISPR/Cas9对顶级GxM交互进行功能评估，以创建敲打和 基因敲除突变和等位基因。2.鉴定和表征与KRAS突变相关的GxM。 在目标1中使用类似的方法治疗结直肠癌(CRC)。这些研究将应用一个新的概念来 发现通过突变频率衡量癌症结局中种族差异的新的生物学驱动因素。 这项研究的结果有可能为机械学研究提供信息，这反过来将导致新的 癌症的治疗策略在突变频率和结果上表现出种族差异。

Summary Tumor sequencing data have revealed significant differences in mutation frequencies between racial and ethnic groups. Some of these differences can be attributed to environmental exposure, such as smoking frequency, but disparities persist even after adjustment for known factors. Well-described examples include TP53 mutations that are seen at elevated rates in breast cancers in African-Americans compared to Asian and non-Hispanic White women and KRAS mutations that are observed in higher rates in colorectal cancers from African-Americans relative to other racial groups. As cancer aggressiveness and survival can depend on what pathways are perturbed in a tumor, the frequency at which a cancer driver mutation occurs in a population should influence some of the observed racial disparities in outcomes. Emerging data from our lab and others suggest that germline genetic variants impact somatic events in tumors. We identified associations between AURKA variants and TP53 in head and neck squamous cell carcinomas from The Cancer Genome Atlas. We found that individuals with at least one AURKA allele previously associated with cancer risk were more likely to have gain-of-function TP53 mutations relative to individuals homozygous for the non-risk associated allele. These and other studies suggest an association between germline Genetic variants and somatic Mutations (GxM) in tumor development. This study will search for novel Genetic variants associated with TP53, PIK3CA, and KRAS Mutations in order to explain racial differences in tumor biology. In this study, we will test the innovative hypothesis that germline genetic variants that differ in frequency between racial groups drive the observed racial differences in frequency of somatic mutations. Our goals are to understand the association between somatic mutations, germline genetic variants and tumorigenesis in racial disparities, and to determine the biological impact of GxM associations on cancer phenotypes using in vitro models. Using existing genotype and mutation data, these goals will be accomplished in two aims: 1. To identify and characterize GxM associations for TP53 and PIK3CA mutations in breast cancer in order to understand how germline variants drive racial differences in somatic mutation frequency. Variants found in GxM association studies from 3700 individuals with breast cancer will be evaluated in 4000 additional breast cancer cases from multiple racial and ethnic groups. Top GxM interactions will be assessed functionally using CRISPR/Cas9 to create knock-in and knock-out mutations and alleles. 2. To identify and characterize GxM associations for KRAS mutations in colorectal cancer (CRC) using a similar approach in Aim 1. These studies will apply a novel concept to discover new biological drivers for racial disparities in cancer outcomes, as measured by mutation frequencies. Results from this study have the potential to inform mechanistic studies which, in turn, will lead to new therapeutic strategies for cancers showing racial differences in mutation frequency and outcome.