Modeling Neoplastic Progression in Barrett's Esophagus

描述（由申请人提供）：我们的长期目标是了解肿瘤进展的进化动力学，并开发可以预防或延迟癌症的有效干预措施。肿瘤通过克隆进化过程发展为恶性肿瘤。然而，人们对这一演变的动力知之甚少。我们建议开发一个基于代理的计算模型的肿瘤进展的Barrett食管作为一种工具，研究肿瘤进展的动力学，并整合遗传，病理，临床和流行病学数据对这种疾病。我们将巴雷特上皮细胞代表为模型的代理人，以便我们可以捕获驱动肿瘤进展的遗传多样性和进化动态。巴雷特食管是一种人类癌前病变，其中食管的鳞状衬里被隐窝结构的肠化生所取代。巴雷特食管是唯一已知的食管腺癌的前体，其发病率在西方世界比任何其他癌症都增长得快。然而，大多数巴雷特食管患者从未患上癌症，因此迫切需要预测进展风险并干预高危患者的方法。我们将对我们的模型进行敏感性分析，以确定可能成为癌症风险预测和癌症预防干预目标的最佳生物标志物的模型参数。Barrett食管肿瘤进展的关键方面是未知的，必须进行测量以开发该疾病的综合预测模型。我们先前已经表明，在单个时间点，巴雷特上皮内细胞克隆的遗传多样性可预测未来的癌症进展。这要么是因为遗传多样性在进展过程中增加，要么是因为高风险患者与低风险患者相比具有高水平的遗传多样性。我们已经证明，我们可以使用基于检测单细胞中244个高度可变微卫星的突变的细胞谱系测定来测量Barrett食管细胞之间的遗传多样性。我们将确定遗传多样性如何随着时间的推移而变化，在60个特征良好的巴雷特食管患者中，并使用近似贝叶斯计算将模型的参数与这些结果拟合。我们将测试非甾体抗炎药（NSAID）的使用是否与巴雷特食管癌症风险的显著降低有关，是否与细胞间遗传多样性的减少有关。我们还将在两个时间点测量243名Barrett食管患者队列中的隐窝密度，以1）确定模型中应模拟的隐窝数量以代表组织，2）确定隐窝密度是否随时间变化，3）测试隐窝的数量或密度是否预测癌症的进展和4）测试NSAID使用和隐窝密度之间的关联。该项目将提高对Barrett食管肿瘤进展的理解，并建立一个模型，该模型可以作为预测工具，用于确定有希望的干预和生物标志物开发靶点。公共卫生相关性：一旦肿瘤侵入其他器官，就很难治愈。因此，我们现在的重点是在癌症变得无法治愈之前预防癌症。特别是，我们研究巴雷特食管，一种癌前病变，可发展成食管癌。这是一种重要的疾病，因为食管癌的发病率在美国比任何其他癌症都增长得快。然而，大多数巴雷特食管患者永远不会患上癌症，因此有必要了解巴雷特细胞演变成恶性肿瘤的过程，并识别高风险患者，以便我们将医疗资源和任何干预措施的固有风险集中在他们身上。我们建议开发计算模型的恶性肿瘤的演变在巴雷特食管和测量动态活检从巴雷特食管患者的过程。这些模型将有助于确定用于测量Barrett食管患者癌症风险的良好生物标志物以及癌症预防的目标。我们的方法应该推广到其他癌前病变。

DESCRIPTION (provided by applicant): Our long-term goals are to understand the evolutionary dynamics of neoplastic progression and to develop effective interventions that can prevent or delay cancer. Neoplasms progress to malignancy through a process of clonal evolution. However, the dynamics of that evolution are poorly understood. We propose to develop an agent-based computational model of neoplastic progression in Barrett's esophagus as a tool to study the dynamics of neoplastic progression and to integrate the genetic, pathological, clinical, and epidemiological data on this disease. We will represent the cells of the Barrett's epithelium as the agents of the model so that we can capture the genetic diversity and evolutionary dynamics that drive neoplastic progression. Barrett's esophagus is a human, pre-malignant condition in which the squamous lining of the esophagus is replaced by a crypt structured intestinal metaplasia. Barrett's esophagus is the only known precursor to esophageal adenocarcinoma, the incidence of which is increasing faster than any other cancer in the Western world. However, most people with Barrett's esophagus never develop cancer, so there is an urgent need for methods to predict risk of progression and intervene in patients at high risk. We will carry out a sensitivity analysis of our model to identify the model parameters that are likely to make the best biomarkers for cancer risk prediction and targets for cancer prevention interventions. Key aspects of neoplastic progression in Barrett's esophagus are unknown and will have to be measured to develop a comprehensive, predictive model of the disease. We have previously shown that the genetic diversity of clones of cells, at a single time point, within Barrett's epithelium is predictive of future progression to cancer. This is either because genetic diversity increases during progression or because high-risk patients have high, constant levels of genetic diversity compared to low-risk patients. We have shown that we can use a cell lineage assay based on detecting mutations in a panel of 244 highly mutable microsatellites in single cells, to measure genetic diversity among cells in Barrett's esophagus. We will determine how genetic diversity changes over time, in 60 well-characterized patients with Barrett's esophagus, and fit the parameters of the model to those results using approximate Bayesian computation. We will test whether or not non-steroidal anti-inflammatory drug (NSAID) use, which is associated with a dramatic reduction in cancer risk in Barrett's esophagus, is associated with a decrease in genetic diversity among cells. We will also measure the density of crypts in a cohort of 243 patients with Barrett's esophagus at two time points to 1) determine the number of crypts that should be simulated in the model in order to represent the tissue, 2) determine if crypt density changes over time, 3) test if the number or density of crypts predicts progression to cancer and 4) test for an association between NSAID use and crypt density. This project will result in an improved understanding of neoplastic progression in Barrett's esophagus and a model that can act as a predictive tool for identifying promising targets for intervention and biomarker development. PUBLIC HEALTH RELEVANCE: Once a tumor has invaded other organs, it is very difficult to cure. Thus, we are now focusing on preventing cancer before it becomes incurable. In particular, we study Barrett's esophagus, a pre-malignant condition that can develop into esophageal cancer. This is an important disease because the incidence of esophageal cancer is increasing faster than any other cancer in the United States. However, most patients with Barrett's esophagus will never develop cancer, so there is a need to understand the process by which Barrett's cells evolve malignancy and identify patients at high risk, so that we can focus our medical resources, and the inherent risks of any interventions, on them. We are proposing to develop computational models of the evolution of malignancy in Barrett's esophagus and to measure the dynamics of that process in biopsies from patients with Barrett's esophagus. These models will help to identify good biomarkers for measuring cancer risk in patients with Barrett's esophagus as well as targets for cancer prevention. Our methods should be generalizable to other pre-malignant conditions.