Discovery of Risk Loci and Genomics of Pancreatic Cancer through Exome Sequencing

描述（由申请人提供）：胰腺腺癌（PaCa）是美国第四大癌症死亡原因，全球第八大癌症死亡原因。然而，如果在早期发现，有有效的手术治疗。这方面的一个主要困难是缺乏既定的预防和筛查策略。在这里，我们建议发现重要的遗传风险因素来帮助实现这一策略，使用4400例胰腺病例和4400例匹配的欧洲血统对照的外显子组和靶向测序。为了控制如此大量基因组测序的成本，我们采用了以下两阶段的研究设计，包括我们的前两个目标：(1)在整个外显子组中进行深度发现，然后(2)在第一阶段对被认为最有希望的基因进行靶向测序。基于乳腺癌真实研究中发现的变异模式，该设计保留了高功率（>90%）来识别具有中度PaCa风险变异的基因。在我们的第三个目标(3)中，我们建议利用现有的肿瘤组织，量化从PaCa基因组的大型研究中鉴定出的基因的体细胞突变负荷。这种体细胞变异将在Aim 1中与全外显子组测序配对，以阐明宿主-肿瘤基因组相互作用。我们提出的工作利用了MD安德森癌症中心强大的样本资源环境和一个由流行病学、基因组学、病理学、外科和计算人类遗传学等领域的不同专业知识组成的良好团队。我们提出的分析方法将由统计遗传学的主要专家进行，他们对这些技术的发展做出了重大贡献。基于先前对PaCa家族聚集性的研究，以及迄今为止全基因组关联研究的相对缺乏发现，我们预计会有许多具有罕见变异的PaCa中至高风险基因。鉴于流行病学和人口统计学数据，我们的两阶段研究设计和大量患者资源，我们的研究为成功鉴定这些基因提供了很好的动力。这些结果将为这种可怕的致命疾病的病因学提供新的见解。

DESCRIPTION (provided by applicant): Pancreatic adenocarcinoma (PaCa) is the 4th leading cause of cancer death in the United States and 8th leading cause worldwide. However, if caught at an early stage, there exist effective surgical treatments. A major difficulty with this is the lck established prevention and screening strategies. Here we propose to discover important genetic risk factors to aid in such a strategy, using exome and targeted sequencing of 4,400 pancreatic cases and 4,400 matched controls of European descent. To manage the cost of sequencing such large portions of the genome, we employ the following 2-stage study design, encompassing our first two aims: (1) deep discovery across whole exomes, followed by (2) targeted sequencing of genes deemed most promising in the first stage. This design retains high power (>90%) to identify genes with moderate risk variation for PaCa, based on the patterns of variation discovered in real studies of breast cancer. In our third aim (3) we propose to quantify somatic mutational load in genes identified from large studies of PaCa genomes, using existing tumor tissue. This somatic variation will be paired to whole-exomes sequenced in Aim 1 to elucidate host-tumor genomic interactions. Our proposed work leverages a strong environment of sample resources at MD Anderson Cancer Center and a well-constructed team of diverse expertise spanning fields of Epidemiology, Genomics, Pathology, Surgery and Computational Human Genetics. The analytical methods we propose will be conducted by leading experts in statistical genetics, who have made major contributions to the development of these techniques. Based on previous studies of familial aggregation of PaCa, and the relative paucity of findings to date from genome-wide association studies, we expect there to be numerous genes with rare variation of intermediate to high risk for PaCa. Given the epidemiological and demographic data, our 2-stage study design and large patient resource, our study is well powered for successful identification of these genes. These results will offer new insights in the etiology of this dreaded and deadly disease.