Multifactor risk scores with susceptibility gene mutations to enhance risk assessment of pancreatic cancer

项目总结/摘要 我们建议改善胰腺导管腺癌（PDAC）的风险评估，PDAC是一种主要的致死性癌症 没有早期检测策略。我们假设一种新的增强的多因素风险评分 （eMRS）将通过纳入携带者， 遗传性癌症综合征致病性变异的状态。我们将使用大马约开发一种新的eMRS 自2002年以来招募的PDAC病例的临床数据集和马约诊所生物库中的初级保健对照， Regeneron Genetics Center（RGC）最近完成了全外显子组测序（WES），以首次评估 有限的现有模型。然后，我们将使用这些数据构建eMRS，并执行 使用英国生物库进行独立验证。我们将首先在风险数据集中测试模型的价值- 马约诊所PDAC患者的一级亲属（FDR）。我们新的PDAC eMRS将首次 全面适应遗传性癌症综合征致病变异，以分层PDAC的风险， 相同处理的测序和信息学工作流程。该研究小组包括基因的领导者 PDAC的识别和遗传流行病学，已经领导了GWAS，确定了将被 包括在风险模型测试和开发中。通过利用现有的三个主要基因组数据集， 一个家庭数据集与伴随的流行病学和疾病的协变量，我们的具体目标是：（1）使用 关于马约诊所PDAC病例和马约生物样本库对照的唯一协调数据集，以验证已发表的 多基因风险评分（PRS）和MRS模型。我们将前瞻性地收集和分析马约诊所的4,552例 招募病例和53，229名对照来评估迄今为止未经验证的模型。(2)要构建和验证 用于PDAC的新型增强eMRS，其包含癌症生殖系致病性变体。(2a)我们将使用 为目标1中的病例和对照建立的数据集，包括其他流行病学风险因素和生殖系 遗传性癌症基因的致病性变异状态，以前没有公开提供 数据集。(2b)我们将使用独立的基因型和风险因素数据集来验证我们的新eMRS 从2，371例PDAC病例和其余497，629例非PDAC英国生物库参与者中提取， 生殖系DNA也将由RGC测序。(3)确定PRS、MRS或eMRS 可以进一步细化PDAC病例一级亲属中的PDAC风险。我们将比较标准化发病率 从马约诊所PDAC收集的23，739名亲属的个人癌症史数据集中的SIR 病例的家族史问卷，以量化和评估影响。该项目将产生几个有用的 遗传风险分层模型，为PDAC提供更精确的风险评估。结果 预计对PDAC的风险评估、遗传咨询和早期发现具有转化影响 通过更好地，潜在的有针对性的，识别个人的风险增加，谁在未来可能 提供微创监测或其他早期检测和预防的选择。

PROJECT SUMMARY / ABSTRACT We propose to improve risk assessment of pancreatic ductal adenocarcinoma (PDAC), a major lethal cancer for which no early detection strategy exists. We hypothesize that a novel enhanced multifactor risk score (eMRS) will improve risk stratification for moderate to high genetic risk strata for PDAC, by incorporating carrier status of hereditary cancer syndrome pathogenic variants. We will develop a new eMRS using large Mayo Clinic datasets of PDAC cases recruited since 2002 and primary care controls in the Mayo Clinic Biobank with recently completed whole exome sequencing (WES) by Regeneron Genetics Center (RGC) to first assess the limited number of existing published models. We will then construct our eMRS with these data and perform independent validation using the UK Biobank. We will test the value of the model in a dataset of at-risk first- degree relatives (FDRs) of Mayo Clinic PDAC patients. Our new eMRS for PDAC will for the first time comprehensively accommodate inherited cancer syndrome pathogenic variants to stratify risk of PDAC in identically processed sequencing and informatics workflows. The study team includes leaders in gene identification and genetic epidemiology of PDAC, having led the GWAS that identified the risk SNPs that will be included in risk model testing and development. By leveraging the three existing major genomic datasets and one family dataset with accompanying epidemiologic and disease covariates, our specific aims are: (1) To use uniquely coordinated datasets on Mayo Clinic PDAC cases and Mayo Biobank controls to validate published polygenic risk score (PRS) and MRS models. We will assemble and analyze Mayo Clinic’s 4,552 prospectively recruited cases and 53,229 controls to evaluate the heretofore unvalidated models. (2) To build and validate a novel, enhanced eMRS for PDAC that incorporates cancer germline pathogenic variants. (2a) We will use the datasets built for cases and controls in Aim 1 and include additional epidemiologic risk factors and germline pathogenic variant status for hereditary cancer genes, which have not been previously available in public datasets. (2b) We will validate our new eMRS with an independent dataset of genotype and risk factor data extracted from 2,371 PDAC cases and the remaining 497,629 non-PDAC UK Biobank participants whose germline DNA will have also been sequenced by RGC. (3) To determine the extent that PRS, MRS or eMRS can further refine PDAC risk in first degree relatives of PDAC cases. We will compare standardized incidence ratios (SIRs) in a dataset of personal cancer histories of 23,739 relatives assembled from Mayo Clinic PDAC cases’ family history questionnaires to quantify and assess impact. This project will result in several useful genetic risk stratification models to provide more precise risk assessment for PDAC. The results are anticipated to have a translational impact on risk assessment, genetic counseling, and early detection of PDAC through better, potentially targeted, identification of individuals at increased risk who in the future could be offered minimally invasive surveillance or other options for early-stage detection and prevention.