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.

我们坚信，物理和定量科学家开发的各种观点和技术可以以潜在革命性的方式对癌症管理和治疗产生重大影响。该提案的重点是我们强烈的信念，即从分子到有机体的多种尺度上进行了多样化的物理测量，必须与复杂和多样化的建模方法融合在一起，以产生一种可以使用的癌症模型，该模型可以预测癌症在出现过程中的行为以及响应扰动。我们的主要假设是，多尺度的测量和建模将允许以足够的保真度对特定的癌症进行建模，以估算替代疗法的相对可能有效性（合理地整合基因型，肿瘤环境和治疗参数以预测结果）。我们的策略以分析分子细胞，肿瘤和宿主水平的特定特性的分析为前提，当将其集成到适当的建模框架中时可以为治疗反应提供信息。致力于该项目的财团是一群具有广泛专业知识的研究人员，并且是发展和应用物理科学方法的共同愿景，以进行癌症研究。 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肿瘤生长（RP4）。这些模型将建立在独特的同步数据集中，其中一套新的测量平台将应用于临床相关的模型系统测试急性粒细胞性白血病（AML）和非Hodgkins lymphkins Lymphoma（NHL）对标准细胞毒性治疗的常见样本。