Physical Dynamics of Cancer Response to Chemotherapy in 3D Microenvironments

3D 微环境中癌症对化疗反应的物理动力学

• 批准号: 9024313
• 负责人: LISA Joy MCCAWLEY
• 金额: $ 54.71万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-25 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9024313
• 关键词: Acidity; Address; Adverse effects; Affect; Apoptosis; Biomedical Engineering; Biopsy; Biopsy Specimen; Bioreactors; Breast; Breast Cancer cell line; Cell Culture Techniques; Cell Line; Cellular Spheroids; Chemicals; Clinical assessments; Complex; Computer Simulation; Coupled; Development; Disease; Dose; Engineering; Experimental Models; Extracellular Matrix; Feedback; Goals; Growth; Growth and Development function; Human; In Vitro; Intercellular Fluid; Malignant Neoplasms; Mammary Neoplasms; Measurement; Metabolic; Methodology; Methods; Microfluidics; Modeling; Monitor; Morphology; Necrosis; Normal tissue morphology; Nutrient; Organ; Organoids; Outcome; Outcome Study; Patients; Pattern; Pharmaceutical Preparations; Population; Primary Neoplasm; Property; Resolution; Running; System; Technology; Testing; Therapeutic; Thick; Tissues; Tracer; Tumor Tissue; Tumor-Derived; anticancer treatment; base; chemotherapy; design; drug efficacy; improved; in vitro Model; in vivo; in vivo Model; malignant breast neoplasm; mathematical model; micro-total analysis system; novel; personalized therapeutic; physical science; pre-clinical; pressure; public health relevance; reconstruction; response; senescence; simulation; therapeutic development; tumor; tumor growth; tumor microenvironment; tumorigenic

 DESCRIPTION (provided by applicant): These studies aim to develop a new computationally driven platform to examine complex physical and chemical microenvironments utilizing organ-on-chip microfluidic bioreactor technology coupled with a predictive mathematical model of tumor growth and therapeutic response. Malignant breast tumors are highly heterogeneous in terms of their cellular composition, varying levels of oxygenation, acidity, and nutrients, as well as local changes in the extracellular matrix. Furthermore, tumor tissue and tumor microenvironment properties can dynamically evolve not only during tumor growth but also when anticancer treatments are administered. Despite this, nearly all pre-clinical assessments of drug efficacy and optimal dosing are performed using homogeneous 2D cell cultures that do not resemble the cellular, metabolic, and physical features manifest in tumors in vivo. Such approach suffered from overly reductionist ex vivo / in vitro studies may not fully recapitulate th complexity of cancers especially the physical and chemical microenvironment. To address these issues we propose to develop an integrated quantitative platform that combines the power of organ-on-chip 3D tissue bioreactor, developed to include non-uniform fully controlled physical and chemical microenvironments, together with a 3DMultiCel math model that allows predictive testing of a broad range of microenvironmental combinations around the experimentally validated baseline. To achieve this goal in a quantitative way we have formed a transdisciplinary team consisting of cancer biologists, biomedical engineers and mathematicians, who will develop an experimental platform for individualized anticancer treatment based on physical science principles. Our long-term goal is to provide a computationally driven "lab-on-chip" platform for 3D organotypic cultures derived from patients' tumor biopsies that will be exposed to fully controlled but dynamically variable microenvironments that will be used to optimize personalized therapeutic treatments that effectively provoke breast tumor regression with minimized harmful side effects for surrounding normal tissue. Outcomes of this study will be: (i) an improved experimental platform that combines 3D culture of tumor organoids coupled with validated predictive mathematical models for the growth and response of human breast tumor organoids within realistic microenvironments; and (ii) quantitative methods that allow one to assess the dynamics of breast tumor organoid development and response to anti-tumor treatments, using mathematical modeling. Our aims are: 1. Develop a predictive methodology to assess effects of defined microenvironments on the dynamics of normal and tumorigenic breast organoids and their sensitivity to therapeutics; 2. Construct and validate in silico model-guided complex spatial and temporal microenvironmental gradients established within TTb-G reactor, and assess breast tumor organoids response to chemotherapeutics. 3. Apply our integrated computational/engineering approach to guide therapy and predict therapeutic response ex vivo and in vivo.

 描述（由申请人提供）：这些研究旨在开发一种新的计算驱动平台，利用片上器官微流体生物反应器技术以及肿瘤生长和治疗反应的预测数学模型来检查复杂的物理和化学微环境。恶性乳腺肿瘤在细胞组成、不同水平的氧合、酸度和营养方面具有高度异质性。 细胞外基质的局部变化。此外，肿瘤组织和肿瘤微环境特性不仅可以在肿瘤生长过程中动态变化，而且在进行抗癌治疗时也可以动态变化。尽管如此，几乎所有药物疗效和最佳剂量的临床前评估都是使用均质的二维细胞培养物进行的，这些细胞培养物与体内肿瘤中表现出的细胞、代谢和物理特征不同。这种方法遭受过度简化的离体/体外研究可能无法完全概括癌症的复杂性，尤其是物理和化学微环境。为了解决这些问题，我们建议开发一个集成的定量平台，该平台结合了片上器官 3D 组织生物反应器的强大功能，该反应器的开发包括非均匀完全控制的物理和化学微环境，以及 3DMultiCel 数学模型，该模型允许围绕实验验证的基线对各种微环境组合进行预测测试。为了定量地实现这一目标，我们组建了一个由癌症生物学家、生物医学工程师和数学家组成的跨学科团队，他们将开发基于物理科学原理的个体化抗癌治疗实验平台。我们的长期目标是为源自患者肿瘤活检的 3D 器官型培养物提供一个计算驱动的“芯片实验室”平台，这些培养物将暴露于完全受控但动态变化的微环境中，用于优化个性化治疗，有效促进乳腺肿瘤消退，同时最大限度地减少对周围正常组织的有害副作用。这项研究的成果将是：(i) 一个改进的实验平台，将肿瘤类器官的 3D 培养与经过验证的预测数学模型相结合，用于现实微环境中人类乳腺肿瘤类器官的生长和反应； (ii) 定量方法，允许人们使用数学模型评估乳腺肿瘤类器官发育的动态和对抗肿瘤治疗的反应。我们的目标是： 1. 开发一种预测方法来评估特定微环境对正常和致瘤性乳腺类器官动态及其对治疗敏感性的影响； 2. 构建并验证 TTb-G 反应器内建立的计算机模型引导的复杂空间和时间微环境梯度，并评估乳腺肿瘤类器官对化疗的反应。 3. 应用我们的集成计算/工程方法来指导治疗并预测体外和体内的治疗反应。