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: 9543230
• 负责人: LISA Joy MCCAWLEY
• 金额: $ 51.32万
• 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/9543230
• 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; Dimensions; Disease; Dose; Engineering; Experimental Models; Exposure to; Extracellular Matrix; Feedback; Goals; Growth; Growth and Development function; Human; In Vitro; Intercellular Fluid; Lab-On-A-Chips; Malignant Neoplasms; Mammary Neoplasms; Measurement; Metabolic; Methodology; Methods; Microfluidic Microchips; Modeling; Monitor; Morphology; Necrosis; Normal tissue morphology; Nutrient; Organoids; Outcome; Outcome Study; Patients; Pattern; Pharmaceutical Preparations; Pharmacotherapy; Prediction of Response to Therapy; Primary Neoplasm; Property; Resolution; Running; System; Technology; 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; novel; organ on a chip; personalized predictions; personalized therapeutic; physical science; pre-clinical; predictive test; pressure; public health relevance; reconstruction; response; senescence; simulation; therapeutic development; three dimensional cell culture; treatment response; 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（由应用程序提供）：这些研究旨在开发一个新的计算驱动平台，以检查使用器官芯片微流体生物反应器技术的复杂物理和化学微环境，并结合了肿瘤生长和治疗反应的预测数学模型。恶性乳腺肿瘤在其细胞组成，氧合水平，酸度和营养水平的程度上是高度异质的 随着细胞外基质的局部变化。此外，肿瘤组织和肿瘤微环境的特性不仅可以在肿瘤生长过程中动态发展，而且还可以在施用抗癌治疗时进化。尽管如此，几乎所有对药物效率和最佳剂量的临床前评估都是使用与细胞，代谢和物理特征相似的均质2D细胞培养物进行的。这种方法受到过度还原主义的离体 /体外研究的影响，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的复杂性。为了解决这些问题，我们建议开发一个集成的定量平台，该平台结合了芯片3D组织生物反应器的功能，开发的是包括非均匀控制的物理和化学微环境，以及3DMulticel数学模型，允许对围绕实验平面进行广泛的微环境组合的预测测试。为了以定量的方式实现这一目标，我们组成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，他们将基于物理科学原理开发一个实验平台，以用于个性化的抗癌治疗。我们的长期目标是为3D有机培养物提供一个计算驱动的“实验室芯片”平台，该平台从患者的肿瘤活检中得出，该平台将暴露于完全控制但动态可变的微环境中，这些微环境将用于优化个性化的治疗治疗，可有效地促进乳腺肿瘤回归的乳房肿瘤，并为周围的正常造成正常的副作用而产生最小化的伤害副作用。这项研究的结果将是：（i）一个改进的实验平台，结合了肿瘤类器官的3D培养物，并结合了经过验证的预测性数学模型，以实现逼真的微环境中人类乳腺肿瘤器官的生长和反应； （ii）使用数学建模允许人们评估乳腺肿瘤器官发育和对抗肿瘤处理的反应的定量方法。我们的目的是：1。开发一种预测方法来评估定义的微环境对正常和肿瘤性乳腺癌动力学的影响及其对治疗的敏感性； 2。构建和验证在TTB-G反应器内建立的硅模型引导的复合空间和临时微环境梯度，并评估乳腺肿瘤类器官对化学治疗剂的反应。 3。应用我们的集成计算/工程方法指导治疗并预测体内和体内治疗反应。