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谱，以揭示 Barrett食管（BE）在空间和时间上的进化关系和动态。巴雷特是 食管腺癌（EAC）的前体，因此患者接受监测检查，以早期发现 癌的我们的研究将提供前所未有的分子细节水平，这在任何 先前对BE癌前演变的研究。重要的是，拟议的实验和分析将定义一个 BE患者的“组织扩张地理学”，包括预测BE的克隆扩增的显著特征。 向未来的EAC迈进。为此，我们将利用一组丰富的连续收集的组织样本， 来自西雅图BE自然史队列中的患者的基因组数据，包括癌症结果患者和 一组年龄匹配的非癌症患者，在多个时间点取样。独特的 本病例对照研究的设计使我们能够使用以下方法鉴定（EPI）预后进展的遗传标记： 来自先进的多组学平台的数据。计算建模和遗传学将用于提取 关于BE何时在患者中出现，特定克隆在BE中传播的速度， 以及这些克隆在组织中的分散程度。最终，我们将用这些进化量来 在有充分证据的前瞻性患者人群中预测癌症与非癌症的结局。 该项目的长期目标是评估数据驱动预测模型的可行性和性能 可以转化为更好的临床护理。值得注意的是，该项目将量化稳健分子的效用， EAC风险的标志物，以改善目前仅依赖组织病理学特征的做法， 难以评估和解释。为了实现这一目标，我们将参数化推断时空动力学， 对这一癌前病变进行地理重建，并将这些测量结果嵌入到多尺度模型中 在人群中从BE进展到EAC的框架。这种多尺度方法明确地模拟了 在患者的一生中，在细胞水平上的随机克隆扩增， 食道我们项目的三个具体目标是：1）测量新克隆如何产生和传播 巴雷特腺; 2）通过定量表观遗传学来测量腺体如何通过巴雷特病损移动和生长。 漂移来估计巴雷特的组织年龄，并构建空间地理学来推断巴雷特的克隆如何在空间上 3）将来自多区域巴雷特样本的时空测量整合到多尺度模型中。 EAC发展模式。该项目是创新的，因为我们将推断进化参数， 例如BE中干细胞置换率和TP 53两次击中失活率，来自第一次（epi）基因组数据， 时间这项研究是重要的，因为它有望提供预测模型， 在BE患者中评估EAC进展的生物标志物，以潜在地提供基于风险的监测的新策略。