Multiscale modeling of spatiotemporal evolution in Barrett's esophagus

巴雷特食管时空演化的多尺度建模

• 批准号: 10659649
• 负责人: Kathleen M. Curtius
• 金额: $ 61.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10659649
• 关键词: Acceleration; Address; Adenocarcinoma In Situ; Age; Aging; Automobile Driving; Barrett Esophagus; Biological; Biological Assay; Biological Markers; Calibration; Case/Control Studies; Cells; Clinical; Clonal Evolution; Clonal Expansion; Computer Models; DNA methylation profiling; DNA sequencing; Data; Development; Diagnosis; Early Diagnosis; Epigenetic Process; Esophageal Adenocarcinoma; Esophageal Tissue; Esophagus; Evolution; Future; Genetic; Genetic Markers; Genome; Genomics; Gland; Goals; Growth; Individual; Intervention; Lesion; Life; Malignant Neoplasms; Maps; Matched Group; Mathematics; Measurement; Measures; Methylation; Microdissection; Modeling; Molecular; Molecular Profiling; Mutation; Natural History; Outcome; Patient-Focused Outcomes; Patients; Performance; Persons; Phylogenetic Analysis; Population; Probability; Procedures; Prognostic Marker; Public Health; Recording of previous events; Research; Resolution; Risk; Sampling; Screening for cancer; Somatic Mutation; TP53 gene; Targeted Resequencing; Testing; Time; Tissue Sample; Tissues; Translating; Update; Work; cancer risk; carcinogenesis; clinical care; cohort; colonic crypt; cost; data-driven model; design; experimental study; follow-up; genomic data; high risk; human tissue; improved; innovation; insight; mathematical model; models and simulation; molecular marker; multi-scale modeling; multiple omics; neoplastic; outcome forecast; patient population; predictive modeling; premalignant; progression risk; prospective; reconstruction; screening; spatiotemporal; stem cell replacement; stem cells; surveillance strategy; tissue mapping; tumor progression

PROJECT SUMMARY The practical goal of this project is to obtain high-resolution genetic and epigenetic maps that reveal the evolutionary relationships and dynamics over space and time in Barrett’s esophagus (BE). Barrett’s is the precursor to esophageal adenocarcinoma (EAC) therefore patients undergo surveillance exams to detect early cancers. Our study will provide an unprecedented level of molecular detail that has not been achieved in any previous study of pre-cancer evolution in BE. Importantly, the proposed experiments and analyses will define a BE patient’s “tissue phylogeography”, including significant features of clonal expansions that are predictive of BE progressing to future EAC. To this end, we will leverage a rich set of serially collected tissue samples and genomic data from patients in the Seattle BE natural history cohort that includes cancer outcome patients and an age-matched group of patients with non-cancer outcomes, sampled at multiple time points. The unique design of this case-control study enables us to identify (epi)genetic markers prognostic of progression using data from advanced multi-omic platforms. Computational modeling and phylogenetics will be used to extract the elusive but essential information on when BE arises in a patient, how fast particular clones spread in BE, and how dispersive these clones are within the tissue. Ultimately, we will use these evolutionary quantities to forecast outcomes of cancer versus non-cancer in a well-documented prospective patient population. The long-term goal of the project is to assess the feasibility and performance of data-driven predictive models that can be translated to improved clinical care. Notably, this project will quantify the utility of robust molecular markers for EAC risk to improve the current practice of relying solely on histopathologic features that are difficult to assess and interpret. To facilitate this goal, we will parameterize the inferred space-time dynamics in phylogeographic reconstructions of this pre-cancer, and embed these measurements in a multiscale model framework for progression from BE to EAC in a population. This multiscale approach explicitly models the stochastic clonal expansions at the cellular level over a patient’s lifetime, within the spatial constraints of the esophagus. The three specific aims for our project are: 1) Measure how new clones arise and spread within Barrett’s glands; 2) Measure how glands move and grow through the Barrett’s lesion by quantifying epigenetic drift to estimate Barrett’s tissue age and constructing phylogeographies to infer how Barrett’s clones spatially evolve; and 3) Integrate spatiotemporal measurements from multi-region Barrett’s samples into a multiscale model of EAC development. The proposed project is innovative because we will infer evolutionary parameters, such as rates of stem cell replacement and TP53 two-hit inactivation in BE, from (epi)genomic data for the first time. This research is significant because it is expected to provide predictive models that incorporate dynamic biomarkers of EAC progression in BE patients to potentially offer new strategies of risk-based surveillance.

项目摘要 该项目的实际目标是获得高分辨率的遗传和表观遗传图，以揭示 巴雷特食管（BE）中的时间和时间的进化关系和动态。巴雷特是 食管腺癌（EAC）的前体患者接受监视检查以早期检测 癌症。我们的研究将提供前所未有的分子细节水平 先前研究BE的前癌前进化。重要的是，提出的实验和分析将定义 成为患者的“组织植物地理学”，包括克隆扩张的重要特征，这些特征可预测 发展到未来的EAC。为此，我们将利用一组丰富的连续收集的组织样品和 来自西雅图患者的基因组数据是包括癌症结果患者的自然史队列和 一组非癌症结果的患者组成的患者，在多个时间点进行了采样。独特 该病例对照研究的设计使我们能够使用（EPI）遗传标志物使用 来自高级多摩变平台的数据。计算建模和系统发育学将用于提取 关于患者何时出现何时出现的难以捉摸但基本的信息，特定克隆在BE中散布的速度， 以及这些克隆在组织内的分散方式。最终，我们将使用这些进化量 在有据可查的预期患者人群中，癌症与非癌症的预测结果。 该项目的长期目标是评估数据驱动的预测模型的可行性和性能 可以将其转化为改善临床护理。值得注意的是，该项目将量化鲁棒分子的效用 EAC风险的标记，以改善仅依靠组织病理学特征的当前做法 难以评估和解释。为了促进这一目标，我们将参数化推断的时空动态 该前癌者的植物地理重建，并将这些测量嵌入到多尺度模型中 在人群中从BE到EAC的发展框架。这种多尺度方法明确对 在患者一生中，在细胞水平的随机克隆扩张，在空间约束中 食管。我们项目的三个具体目标是：1）衡量新克隆如何在其中出现和传播 巴雷特的腺体； 2）测量地面如何通过量化表观遗传学来通过巴雷特的病变移动和生长 漂移估计Barrett的组织时代并构建植物地理学，以推断Barrett的克隆如何空间 进化; 3）将多区巴雷特样品的时空测量集成到多尺度 EAC开发的模型。拟议的项目具有创新性，因为我们将推断进化参数， 例如，（EPI）基因组数据中的干细胞置换率和TP53两次失活的率 时间。这项研究很重要，因为有望提供结合动态的预测模型 BE患者的EAC进展生物标志物可能会提供新的基于风险的监视策略。