Computational Models of the Human Cell Cycle to Reveal Disease Mechanism and Inform Treatment

人类细胞周期的计算模型揭示疾病机制并为治疗提供信息

• 批准号: 10033514
• 负责人: Jeremy Purvis
• 金额: $ 30.71万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-11 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10033514
• 关键词: Abnormal Cell; Activity Cycles; Behavior; CCNE1 gene; Cell Cycle; Cell Cycle Arrest; Cell Cycle Progression; Cell Cycle Regulation; Cell Differentiation process; Cell Proliferation; Cell division; Cell model; Cells; Chemicals; Chromatin; Clinical Treatment; Clinical Trials; Collaborations; Combined Modality Therapy; Computer Analysis; Computer Models; Coupling; Cues; Cyclin D1; Cyclin-Dependent Kinases; DNA; DNA Binding; DNA Damage; DNA Repair; DNA Repair Inhibition; DNA biosynthesis; Data; Disease; Down-Regulation; Embryonic Development; Endoderm; Epithelial Cells; Eye; Family; Future; G2 Phase; Generations; Genetic; Genetic Transcription; Geometry; Goals; Growth; Growth Factor Receptors; Human; Image; Image Analysis; Immunofluorescence Immunologic; In Vitro; Inherited; Joints; KRAS2 gene; Knowledge; Learning; Link; Malignant Neoplasms; Malignant neoplasm of pancreas; Measures; Mediating; Messenger RNA; Mitosis; Mitotic; Modeling; Modernization; Molecular; Mothers; Mutate; Mutation; Network-based; Oncogenes; Oncogenic; Organ; PI3K/AKT; Pancreas; Pathway interactions; Pharmaceutical Preparations; Pharmacology; Physicians; Pluripotent Stem Cells; Process; Proliferating; Protein p53; Protocols documentation; Publications; RAS Family Gene; RAS genes; Radiation; Radiation Induced DNA Damage; Radiation Oncology; Radiation therapy; Recording of previous events; Refractory; Research; Resolution; Retina; S Phase; Scheme; Scientist; Signal Transduction; Stress; Testing; Therapeutic; Time; Tissues; cancer therapy; cell type; cellular imaging; chemotherapy; chromatin immunoprecipitation; clinically relevant; convolutional neural network; daughter cell; design; epithelium regeneration; expectation; extracellular; gene product; genetic manipulation; human disease; human embryonic stem cell; human model; human stem cells; human tissue; individualized medicine; induced pluripotent stem cell; insight; paracrine; pluripotency; predicting response; predictive modeling; response; small molecule; small molecule inhibitor; stem cells; targeted treatment; therapeutic DNA; transmission process; treatment response

PROJECT SUMMARY / ABSTRACT The overall goal of this project is to develop computational models that predict how the human cell cycle responds to clinically-relevant perturbations such as radiotherapy, targeted therapy, oncogenic mutation, and directed differentiation. These models will fill a significant void in our understanding of the mechanisms underlying the initiation, progression, and treatment of diseases that involve abnormal cell proliferation. Our approach is to use quantitative single-cell imaging to measure the molecular states of proliferating cells and to integrate these data into predictive modeling frameworks. We have assembled a cross-institutional team comprising a computational biologist, two cell biologists, and a physician scientist with specialization in radiation oncology. The team has a strong and productive history of collaboration with six joint publications to date. Aim 1 investigates the mechanism by which retinal epithelial cells respond to radiation-induced DNA damage during S phase to execute G2 arrest. Time-lapse imaging and deterministic modeling will predict: how the response to DNA damage is delayed until the S/G2 transition; how a small-molecule inhibitor of DNA repair—currently involved in clinical trial—intensifies the arrest response; and how loss of the tumor suppressor p53 renders cells refractory to combination therapy. Aim 2 asks how pancreatic epithelial cells with mutations in KRAS escape permanent cell cycle arrest. We will use high-content imaging to profile multiple signaling activities in single cells expressing oncogenic KRAS. These data will be used to construct a manifold representation of cell cycle progression that spans a two-week time course of oncogenic KRAS-mediated transformation. Computational analysis of the manifold’s geometry will identify molecular branching points in G1 that govern the proliferation/arrest decision in pancreatic cells, and we will validate these predictions through small molecules and genetic manipulation. Aim 3 tests the hypothesis that human embryonic stem cells inherit cell-cycle-specific gene products (specifically, G1 regulators) from the previous G2 phase to promote pluripotency in daughter cells. We will combine mitosis-specific chromatin profiling with convolutional neural network-based image analysis to identify the mechanisms by which stem cells sustain rapid proliferation and pluripotency over multiple cell-cycle generations. Each aim yields both basic and applied knowledge, providing fundamental insights into cell cycle progression under perturbation and generating specific, molecular predictions to inform new treatment schemes. With an eye toward the future, predictive models of the human cell cycle will enable patient-specific treatments for diseases that are driven by abnormal cell proliferation.

项目概要/摘要 该项目的总体目标是开发预测人类细胞周期的计算模型 对临床相关的干扰做出反应，例如放射治疗、靶向治疗、致癌突变和 定向分化。这些模型将填补我们对机制理解的重大空白 涉及异常细胞增殖的疾病的发生、进展和治疗的基础。我们的 方法是使用定量单细胞成像来测量增殖细胞的分子状态并 将这些数据集成到预测建模框架中。我们组建了一支跨机构团队 由一名计算生物学家、两名细胞生物学家和一名专门从事医学研究的科学家组成 放射肿瘤学。该团队与六家联合出版物有着悠久而富有成效的合作历史， 日期。目标 1 研究视网膜上皮细胞对辐射诱导的 DNA 做出反应的机制 S阶段损坏执行G2逮捕。延时成像和确定性建模将预测：如何 对 DNA 损伤的反应被延迟到 S/G2 转变； DNA小分子抑制剂如何 修复（目前正在进行临床试验）可增强逮捕反应；以及肿瘤如何消失 p53 抑制因子使细胞对联合治疗产生耐药性。目标 2 询问胰腺上皮细胞如何 KRAS 突变逃脱了永久性细胞周期停滞。我们将使用高内涵成像来分析多个 表达致癌 KRAS 的单细胞中的信号传导活动。这些数据将用于构建流形 细胞周期进展的表示，跨越致癌 KRAS 介导的两周时间过程 转变。流形几何形状的计算分析将识别分子分支点 G1 控制胰腺细胞的增殖/停滞决策，我们将验证这些预测 通过小分子和基因操纵。目标 3 检验人类胚胎干的假设 细胞从之前的 G2 期继承细胞周期特异性基因产物（特别是 G1 调节因子） 促进子细胞的多能性。我们将结合有丝分裂特异性染色质分析与卷积 基于神经网络的图像分析，以确定干细胞维持快速增殖的机制 以及多个细胞周期世代的多能性。每个目标都会产生基础知识和应用知识， 提供对扰动下细胞周期进展的基本见解并生成特定的、 分子预测为新的治疗方案提供信息。着眼于未来，预测模型 人类细胞周期将使针对异常细胞驱动的疾病的患者特异性治疗成为可能 增殖。