Steady states and cellular transitions associated with carcinogenesis and tumorprogression

与癌发生和肿瘤进展相关的稳态和细胞转变

• 批准号: 9618374
• 负责人: James R. Heath
• 金额: $ 54.35万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 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 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9618374
• 关键词: Steady; states; cellular; transitions; associated

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 细胞转变是致癌和肿瘤进展的许多步骤的基础。这样的过渡 广泛研究了，但是一般模型在历史上一直限于定性描述。这对比了 物理系统中的相变，在物理学的背景下得到很好的特征 化学定律，可以使用简单，精确的模型（例如 ISING模型。这样的模型基于相互作用的晶格位点的系统。参数（例如 温度）是多种多样的，随着系统接近，分析了晶格位点的波动，并且 通过一个关键点。所有关键系统特定的细节均在 晶格位点，模型可以产生特定的实验可验证的预测。在计算机模型中类似 尽管导致了各种基因或蛋白质调节网络中过渡的理论研究 预测在实验测试中可能具有挑战性。 我们寻求一种一般方法，其中实验输入是统计上大量的单个单元 测量值，许多蛋白质和代谢物分析物进行了定量测量每个细胞。从这个数据我们 捕获波动，从而确定分析物 - 分析物相关性。在一个类比中， 这样的测量定义了站点相互作用。这些输入允许直接的理论模型 解决细胞稳态，稳态之间的过渡以及进行可测试的预测。研究 化学诱导的 - 癌变过渡提供了初步数据/概念证明。对于目标1我们 使用综合代谢和蛋白质组学单细胞测定法开发癌细胞稳态的图片 胶质母细胞瘤多形和黑色素瘤的癌症模型。在目标2和3中，我们将这种方法扩展到两种 与靶向疗法的抗性相关的明显细胞转变：适应 异质的脑癌对某些靶向抑制剂和药物诱导的细胞脱不同 在黑色素瘤和其他肿瘤中观察到，响应免疫疗法和靶向抑制剂。所有目标都是 联合实验/理论的目的。目标2-3涉及预测的体内测试以及外显子组测序和 全局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一种描述细胞的一般定量方法 与癌症相关的过渡。此外，我们建议挖掘细胞过渡到 确定旨在击中促进肿瘤生长的靶标的疗法组合以及 推动过渡（从而促进阻力）初步数据来支持此目标。 此外，非连续治疗剂量的指导（例如计量或脉动方案） 预计将了解过渡到抵抗的动力学，障碍和可逆性