Steady states and cellular transitions associated with carcinogenesis and tumor progression

与癌发生和肿瘤进展相关的稳态和细胞转变

• 批准号: 9355497
• 负责人: James R. Heath
• 金额: $ 10.07万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-08 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9355497
• 关键词: Antineoplastic Agents; BRAF gene; Biological; Biological Assay; Breast; Cancer Model; Cancerous; Cell Cycle Kinetics; Cell Line; Cell model; Cells; Chemicals; Combined Modality Therapy; Complement; Computer Simulation; Coupled; Data; Dose; Drug resistance; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Exposure to; Freedom; Genes; Genotype; Glioblastoma; Goals; Growth; Human; Immunotherapy; Ising model; Joints; Kinetics; Knowledge; Laws; Maintenance; Malignant Neoplasms; Malignant neoplasm of brain; Measurement; Measures; Melanoma Cell; Metabolic; Metabolism; Metastatic Melanoma; Modeling; Modification; Nature; Neural Crest; Outcome; Output; Patients; Pharmaceutical Preparations; Phase Transition; Phenotype; Phosphoproteins; Physics; Process; Proteins; Proteomics; Regimen; Research; Resistance; Resistance development; Science; Signal Transduction; Site; System; Temperature; Testing; Theoretical Studies; Theoretical model; Work; base; cancer cell; carcinogenesis; chemical carcinogen; cigarette smoking; cytokine; design; drug development; exome sequencing; experimental study; genetic regulatory protein; improved; in vivo; inhibitor/antagonist; killings; mTOR Inhibitor; melanocyte; melanoma; mutant; physical model; programs; protein metabolite; response; targeted treatment; theories; therapy design; transcriptome sequencing; tumor; tumor growth; tumor progression

Project Summary/Abstract Cellular transitions are fundamental to many steps of carcinogenesis and tumor progression. Such transitions are broadly studied, but general models have been historically limited to qualitative descriptions. This contrasts with phase transitions in physical systems, which are well characterized within the context of the physico- chemical laws, and can be partially understood, in a predictive capacity, using simple, precise models such as the Ising model. Such models are based upon a system of interacting lattice sites. A parameter (e.g. Temperature) is varied, and the fluctuations of the lattice sites are analyzed as the system approaches and passes through a critical point. All critical system-specific details are captured in the interactions between the lattice sites, and the models can yield specific, experimentally verifiable predictions. Ising-like in silico models have guided theoretical studies of transitions in various gene or protein regulatory networks, although resultant predictions can be challenging to experimentally test. We seek a general approach where the experimental input is a statistically large number of single cell measurements, with many protein and metabolite analytes quantitatively measured per cell. From this data we capture the fluctuations and thereby determine the analyte-analyte correlations. In an Ising model analogy, such measurements define the site interactions. These inputs permit straightforward theoretic models for resolving cellular steady states, transitions between steady states, and for making testable predictions. Studies of the chemically-induced-carcinogenesis transition provide preliminary data/proof of concept. For Aim 1 we develop a picture of cancer cell steady states using integrated metabolic and proteomic single cell assays on cancer models of Glioblastoma Multiforme and Melanoma. In Aims 2 and 3 we expand this approach to two apparent cellular transitions associated with resistance against targeted therapies: the adaptation of heterogeneous brain cancers to certain targeted inhibitors, and a drug-induced cellular de-differentiation observed in melanomas and other tumors in response to immunotherapy and targeted inhibitors. All aims are joint experiment/theory aims. Aims 2-3 involve in vivo testing of predictions, as well as exome sequencing and global RNA-seq kinetic studies to complement the single cell kinetic analyses. Anticipated outcomes of the work include a general, quantitative approach towards describing cellular transitions associated with cancer. Further, we propose to mine those descriptions of cellular transitions to identify therapy combinations that are designed to hit targets that drive tumor growth, as well as those that drive the transition (and thus promote resistance) Preliminary data to support of this goal is provided. Additionally, guidance for non-continuous therapy dosing (e.g. metronomic or pulsatile regimens) that exploit knowledge of the kinetics, barriers, and reversibility of the transition to resistance is anticipated

项目摘要/摘要 细胞转化是肿瘤发生和发展的许多步骤的基础。这样的过渡 被广泛研究，但一般模型历史上一直局限于定性描述。这形成了鲜明的对比 对于物理系统中的相变，它在物理的上下文中被很好地描述-- 化学定律，并可以部分地理解，在预测能力，使用简单，精确的模型，如 伊辛模型。这样的模型是基于相互作用的晶格点系统。参数(例如 温度)是变化的，并分析了随着系统的接近和 经过一个临界点。所有关键系统特定的详细信息都会在 晶格位置，这些模型可以产生特定的、可通过实验验证的预测。硅胶模型中的Ising-like 指导了各种基因或蛋白质调控网络中的转变的理论研究，尽管结果是 预测可能很难在实验中得到验证。 我们寻求一种一般的方法，其中实验输入是统计上大量的单细胞 测量，与许多蛋白质和代谢物分析物定量测量每个细胞。根据这些数据，我们 捕捉波动，从而确定分析物-分析物的相关性。在伊辛模型的类比中， 这样的测量定义了站点交互作用。这些输入允许直接的理论模型 解析细胞稳定状态，稳定状态之间的转换，并做出可测试的预测。研究 对化学诱导致癌转变的研究提供初步数据/概念证明。对于目标1，我们 使用集成的代谢和蛋白质组学单细胞分析绘制癌细胞稳定状态的图像 多形性胶质母细胞瘤和黑色素瘤的肿瘤模型。在目标2和目标3中，我们将这种方法扩展到两个 与靶向治疗耐药相关的明显细胞转变：适应 异种脑癌对某些靶向抑制剂的作用，以及药物诱导的细胞去分化 在黑色素瘤和其他肿瘤中观察到对免疫治疗和靶向抑制剂的反应。所有目标都是 联合实验/理论目标。目标2-3涉及体内预测测试，以及外显子组测序和 全球rna-seq动力学研究，以补充单细胞动力学分析。 这项工作的预期结果包括描述细胞的一般的、定量的方法 与癌症相关的过渡。此外，我们建议挖掘这些对细胞转变的描述以 确定旨在达到推动肿瘤生长的目标的治疗组合，以及那些 提供了支持这一目标的初步数据，以推动过渡(并因此促进阻力)。 此外，对非连续治疗剂量的指导(例如，节律或脉搏疗法)利用 预期会有向抗性转变的动力学、障碍和可逆性方面的知识。