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.

项目概要 该项目的实际目标是获得高分辨率遗传和表观遗传图谱，揭示 巴雷特食管（BE）在空间和时间上的进化关系和动态是。 食管腺癌（EAC）的先兆，因此患者接受监测检查以早期发现 我们的研究将提供前所未有的分子细节水平，这是任何研究都未达到的。 重要的是，所提出的实验和分析将定义一个BE的癌前进化。 BE 患者的“组织系统发育地理学”，包括可预测的克隆扩增的显着特征 为了实现这一目标，我们将利用一系列丰富的连续收集的组织样本和数据。 来自西雅图 BE 自然历史队列患者的基因组数据，其中包括癌症结果患者和 一组具有非癌症结果的年龄匹配的患者，在多个时间点进行采样。 这项病例对照研究的设计使我们能够使用以下方法识别进展预后的（表观）遗传标记： 来自先进的多组学平台的数据将用于提取。 关于患者何时出现 BE、特定克隆在 BE 中传播的速度等难以捉摸但重要的信息， 最终，我们将利用这些进化量来确定这些克隆在组织内的分散程度。 在有据可查的前瞻性患者群体中预测癌症与非癌症的结果。 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 值得注意的是，该项目将量化强大分子的效用。 EAC 风险标志物可改善目前仅依赖组织病理学特征的做法 为了实现这一目标，我们将参数化推断的时空动力学。 对这种癌前病变进行系统发育地理学重建，并将这些测量结果嵌入到多尺度模型中 这种多尺度方法明确模拟了人群中从 BE 到 EAC 的进展框架。 在患者一生的空间限制内，细胞水平上的随机克隆扩张 我们项目的三个具体目标是：1）测量新克隆如何在食道内产生和传播。 2) 通过量化表观遗传来测量腺体如何在巴雷特病变中移动和生长 漂移来估计巴雷特的组织年龄并构建系统发育地理学来推断巴雷特的克隆如何在空间上进行 演化；3) 将多区域 Barrett 样本的时空测量结果整合到多尺度中 EAC 开发模型是创新的，因为我们将推断进化参数， 例如 BE 中的干细胞替代率和 TP53 两次打击失活，来自第一个的（表观）基因组数据 这项研究意义重大，因为它有望提供包含动态的预测模型。 BE 患者 EAC 进展的生物标志物有可能提供基于风险的监测的新策略。