Multi-scale Complex Systems Transdisciplinary Analysis of Response to Therapy (MC

治疗反应的多尺度复杂系统跨学科分析（MC

• 批准号: 8328164
• 负责人: William Daniel Hillis
• 金额: $ 304.93万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-28 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8328164
• 关键词: Acute Myelocytic Leukemia; Alternative Therapies; Behavior; Belief; Biological Models; Cancer Model; Cell model; Clinical; Commit; Complex; Cytotoxic Chemotherapy; Data Set; Development; Environment; Genotype; Growth; Heterogeneity; Immune; Individual; Instruction; Malignant Neoplasms; Measurement; Metabolic; Modeling; Molecular; Non-Hodgkin' s Lymphoma; Outcome; Patients; Physiological; Property; Relative (related person); Research Personnel; Sampling; Scientist; Simulate; System; Techniques; Testing; Therapeutic; Vision; cancer cell; cancer therapy; clinically relevant; molecular scale; neoplastic cell; novel; physical science; response; tool; tumor; tumor growth; virtual

We are convinced that the diverse perspectives and techniques developed by physical and quantitative scientists can make a significant impact on cancer management and treatment in potentially revolutionary ways. This proposal is centered on our strong belief that diverse physical measurements at multiple scales from molecular to organismic need to be integrated with sophisticated and diverse modeling approaches to generate a model of cancer that can be used predict the behavior of cancers during emergence and in response to perturbation. Our primary hypothesis is that multi-scale measurement and modeling will allow specific cases of cancer to be modeled with sufficient fidelity to estimate'the relative probable efficacy of alternative therapies (rationally integrating genotype, tumor environment and treatment parameters to predict outcome). Our strategy presupposes that analyses of specific properties at the molecular-cell, tumor and host levels when integrated in an appropriate modeling framework can inform therapeutic response. The consortium that has committed to this project is a group of investigators with widely diverse expertise and a common vision to develop and to apply physical sciences approaches to the study of cancer. This proposal describes the development of an integrated virtual cancer model that Incorporates a molecular-cellular model (RP1), a cancer cell evolutionary model of tumor heterogeneity (RP2), a whole tumor model with physically relevant spatial parameters to model tumor micro-environment and interaction with vasculature (RP3), and, lastly, a host model that aims to model physiological, immune and metabolic responses to tumor growth (RP4). These models will be built upon a unique synchronized dataset wherein a suite of novel measurement platforms are applied to a common set of samples from clinically relevant model systems testing therapeutic response of acute myelogenous leukemia (AML) and non-Hodgkins lymphoma (NHL) to standard cytotoxic therapy.

我们相信，物理和定量科学家开发的不同观点和技术可以以潜在的革命性方式对癌症管理和治疗产生重大影响。该提案的核心是我们坚信，从分子到有机体的多个尺度的不同物理测量需要与复杂且多样化的建模方法相结合，以生成癌症模型，该模型可用于预测癌症出现期间的行为以及对癌症的反应。扰动。我们的主要假设是，多尺度测量和建模将允许对特定癌症病例进行足够保真度的建模，以估计替代疗法的相对可能疗效（合理整合基因型、肿瘤环境和治疗参数以预测结果）。我们的策略预设，当整合到适当的模型框架中时，对分子细胞、肿瘤和宿主水平的特定特性进行分析可以为治疗反应提供信息。致力于该项目的联盟是一群具有广泛不同专业知识和共同愿景的研究人员，致力于开发和应用物理科学方法来研究癌症。该提案描述了集成虚拟癌症模型的开发，该模型结合了分子细胞模型（RP1）、肿瘤异质性的癌细胞进化模型（RP2）、具有物理相关空间参数来模拟肿瘤微环境的整个肿瘤模型以及与脉管系统的相互作用（RP3），最后是旨在模拟对肿瘤生长的生理、免疫和代谢反应的宿主模型（RP4）。这些模型将建立在独特的同步数据集的基础上，其中一套新颖的测量平台应用于来自临床相关模型系统的一组通用样本，测试急性髓性白血病（AML）和非霍奇金淋巴瘤（NHL）对标准的治疗反应细胞毒疗法。