Modeling Neoplastic Progression in Barrett's Esophagus - Renewal -2

巴雷特食管肿瘤进展建模 - 更新 -2

• 批准号: 10594704
• 负责人: Carlo Maley
• 金额: $ 49.89万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-07 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594704
• 关键词: Barrett Esophagus; Bayesian Analysis; Benign; Biological Markers; Biopsy; Cancer Patient; Cell model; Cells; Cessation of life; Classification; Clinic; Clinical; Clonal Expansion; Collection; Consensus; Data; Decision Trees; Detection; Development; Diagnosis; Disease; Early Intervention; Epigenetic Process; Equilibrium; Esophageal Adenocarcinoma; Esophageal Tissue; Esophagectomy; Evolution; Future; Generations; Genes; Genetic; Genetic Models; Genomics; Heritability; Individual; Intervention; Length; Life; Malignant Neoplasms; Malignant neoplasm of esophagus; Measures; Methylation; Modeling; Morbidity - disease rate; Mutation; Neoplasms; Outcome; Parameter Estimation; Pathway interactions; Patients; Persons; Phenotype; Phylogenetic Analysis; Phylogeny; Physicians; Population Genetics; Population Sizes; Precancerous Conditions; Process; Prospective cohort; Resources; Risk; Risk Assessment; Selection for Treatments; Signal Transduction; Single Nucleotide Polymorphism; Stress; Surface; System; Testing; Time; Tissues; Trees; cancer risk; cohort; cost; genome sequencing; genome wide methylation; high risk; indexing; mortality risk; overtreatment; patient subsets; predictive modeling; premalignant; prevent; random forest; risk stratification; standard of care; stem cell population; stem cells; tool; treatment response; tumor; tumor progression; whole genome

Patients with Barrett's Esophagus are at increased risk of developing esophageal adenocarcinoma, but there is currently no reliable way to determine who is at high versus low risk. We propose to quantify the evolutionary dynamics in Barrett's and determine if those measures predict cancer risk. Neoplastic progression is fundamentally a stochastic evolutionary process at the cell level. However, there are often many different genetic and epigenetic alterations that can contribute to the development of a cancer, and the ones that evolve in any given cancer are random. This makes it difficult to assess the risk that a pre-cancerous tissue will evolve into cancer based simply on what mutations have occurred previously. We propose a different approach: Measure the dynamics of cell level evolution rather than the products of that evolution. We hypothesize that the rate of cellular evolution in a tissue should predict how likely and how quickly that tissue will evolve into a cancer. We will test this hypothesis in Barrett’s esophagus. We propose to fit both population genetic and phylogenetic models to data from Barrett’s esophagus biopsies spread over space and time in order to estimate parameters of the rate of cellular evolution and test if they are predictive of progression to esophageal adenocarcinoma. Five parameters determine the rate of evolution: 1) stem cell population size, 2) stem cell generation time, 3) mutation rate, 4) the strength of selection, and 5) heritability of the alterations. We have recently shown that we can measure all those parameters in clinical biopsies. We will measure all five parameters in Barrett’s esophagus based on CpG methylation and copy number alterations using methylation arrays, as well as single nucleotide variants identified in whole genome sequencing, in a prospective cohort of Barrett’s patients having either stable, benign disease or validated cancer outcomes. We will use those measures of the rate of evolution in Barrett’s esophagus to derive multivariable risk models of progression to esophageal adenocarcinoma as well as a classification system for the types of evolution present, that are clinically useful for the management of Barrett’s esophagus. If we are successful, we will reduce morbidity in patients likely to progress through earlier intervention, reduce suffering and stress in low-risk patients, and focus resources and interventions on those high-risk patients who will benefit from them. Our proof of principle would also justify using our tools to measure evolution in other pre-cancers to predict progression. In full-blown cancers, our measures may also predict their response to therapy and to select therapies that are matched to the evolutionary dynamics of a patient’s cancer.

Barrett食管患者发生食管腺癌的风险增加，但 目前没有可靠的方法来确定谁是高风险还是低风险。我们建议量化进化 巴雷特的动态，并确定这些措施是否预测癌症风险。肿瘤进展是 基本上是细胞水平上的随机进化过程。然而，往往有许多不同的 遗传和表观遗传改变，可以有助于癌症的发展，以及那些演变 都是随机的这使得评估癌前组织演变的风险变得困难 仅仅根据之前发生的突变就能转化为癌症。我们提出了一个不同的方法： 测量细胞水平进化的动态，而不是进化的产物。我们假设 组织中细胞进化的速度应该预测该组织进化成一种细胞的可能性和速度。 癌我们将在巴雷特食管中检验这一假设。我们建议，以适应人口遗传和 系统发育模型的数据从巴雷特食管活检分布在空间和时间， 估计细胞进化速率的参数，并测试它们是否可预测食管癌的进展。 腺癌五个参数决定了进化的速度：1）干细胞群体的大小，2）干细胞 世代时间，3）突变率，4）选择强度，和5）改变的遗传力。我们有 最近表明我们可以在临床活检中测量所有这些参数。我们将测量所有五个 基于CpG甲基化和使用甲基化的拷贝数改变的Barrett食管参数 阵列，以及在全基因组测序中鉴定的单核苷酸变异，在一个前瞻性队列中， Barrett患者具有稳定的良性疾病或经验证的癌症结果。我们将利用这些 Barrett食管进展速率的测量，以推导出进展至 食管腺癌以及目前的演变类型的分类系统，即 临床上可用于治疗巴雷特食管。如果我们取得成功，我们将减少 患者可能通过早期干预而进展，减少低风险患者的痛苦和压力，以及 将资源和干预措施集中在那些将从中受益的高危患者身上。我们的原则证明 这也将证明使用我们的工具来测量其他癌前病变的演变以预测进展是合理的。全面发展 癌症，我们的措施也可以预测他们对治疗的反应，并选择与之匹配的治疗方法。 病人癌症的进化动力学