Building Data Science Tools for Genetic Models of Colorectal Cancer Progression and Risk

结直肠癌(CRC)是美国癌症死亡的第二大原因。筛选 结肠镜检查可降低结直肠癌的发病率和死亡率。退伍军人事务部合作研究计划#380 “无症状受试者结肠腺瘤(1 Cm)危险因素的前瞻性评估” 是首批证明筛查结肠镜检查安全性的研究之一，并强调了 切除癌前病变息肉对预防结直肠癌的益处。 然而，结直肠癌的个体风险有相当大的差异，这可能会影响开始时的年龄。 关于结直肠癌筛查、筛查方式和随访频率。然而，指导方针并不承认 这种可变性，在低风险个体中进行过多的结肠镜筛查和监测 以及没有对高危人群提供足够或及时的筛查和监测。遗传和 基因组数据为改进结直肠癌风险预测和更好地针对结直肠癌提供了一种有希望的策略 筛选资源。然而，在这些基因组风险计算中，缺少的是对 临床上有意义的结直肠癌先兆某些基因变化和这些变化的时间 预测未来CRC时间的时间进程。结直肠癌先兆和结直肠癌的纵向研究 进展，确定进展的遗传风险因素，并纳入个性化 风险模型只能通过开发集成的数据资源和 应用新的统计模型。我们已经开始开发资源，让大型- 开发全面的临床和遗传风险模型所需的规模分析。这项建议是 建立在我们的工作CSP#380的基础上，该工作结合了3121名退伍军人的纵向研究计划 1994年至1997年接受了结肠镜筛查，并已随访20年。我们 已使用CSP#380研究数据库将新兴统计模型应用于纵向 结合了每次结肠镜检查的临床信息的队列，允许估计 提供信息的随访时间，同时考虑到随着时间的推移死亡的相互竞争的风险。我们 我还扩展了CSP#380的生物信息库，以包括在 结肠镜检查提供了纵向组织资源。这项提议的目标是延长 CSP#380中开发的退伍军人结肠镜检查队列(VACC)的方法和模型，包括 所有退伍军人都在退伍军人医院接受过结肠镜检查。我们将在CSP#380中执行广泛的测试 以提供数据质量的估计。这个更大的VA数据集将允许更彻底的发现 以及对CRC风险模型中的遗传因素进行测试。这一雄心勃勃的项目将把发展 从退伍军人病历中产生的组织病理学结果的精选表型文库 适用于CSP#380的关节纵向模型。我们将开始探索如何将基因 通过CSP#380中的试点研究将信息纳入这些模型，并制定未来应用这些模型的计划 模型到其他VA数据集。

Colorectal cancer (CRC) is the 2nd leading cause of cancer death in the United States. Screening for CRC with colonoscopy reduces incidence and mortality. The VA Cooperative Studies Program #380 “Prospective Evaluation of Risk Factors for Colonic Adenomas (>1cm) in Asymptomatic Subjects” was one of the first studies to demonstrate the safety of screening colonoscopy and highlight the magnitude of benefit through the removal of precancerous polyps for the prevention of CRC. However, there is considerable variability in individual risk of CRC that could impact age at initiation of CRC screening, screening modality and frequency of follow-up. Yet, guidelines do not recognize this variability, performing too much colonoscopy screening and surveillance in low risk individuals and not providing enough or timely screening and surveillance in high-risk individuals. Genetic and genomic data offer a promising strategy to improve CRC risk prediction and better target CRC screening resources. However, what is missing in these genomic risk calculations is recognition of the timing of certain genetic changes and of those changes in CRC precursors in a clinically meaningful time course to predict the timing of future CRC. Longitudinal studies of CRC precursors and progression, identification of genetic risk factors for progression, and incorporation into personalized risk models can only be accomplished through development of an integrated data resource and application of new statistical models. We have begun to develop the resources to allow the large- scale analyses needed to develop comprehensive clinical and genetic risk models. This proposal is built on our work CSP#380 which incorporates a longitudinal research program of 3121 Veterans who underwent screening colonoscopy between 1994 and 1997 and have been followed for 20 years. We have used the CSP#380 research database to apply emerging statistical models for longitudinal cohorts that incorporate the clinical information from each colonoscopy, allowing estimates of informative follow-up times while taking the competing risk of mortality over time into account. We have also extended the biorepository for CSP#380 to include pathology specimens obtained at colonoscopy to provide a longitudinal tissue resource. The goal of this proposal is to extend the approach and models developed in CSP#380 to the VA Colonoscopy Cohort (VACC), which includes all Veterans with exposure to colonoscopy in the VA. We will perform extensive testing in CSP#380 to provide estimates of data quality. This much larger VA data set will allow more thorough discovery and testing of genetic factors in CRC risk models. This ambitious project will combine development of a curated phenotype library with histopathology results generated from VA medical records with the joint longitudinal models applied to CSP#380. We will begin to explore how to incorporate genetic information into these models through pilot studies in CSP#380 with the future plan of applying these models to additional VA datasets.