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(PQB6)An Integrative Computational and Bioengineered Tissue Model of Metastasis

(PQB6)转移的综合计算和生物工程组织模型

基本信息

批准号：
8730584
负责人：
DAVID B AGUS
金额：
$ 55.77万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-05 至 2017-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8730584
关键词：
Affect Apoptosis Area Biochemical Biological Models Biology Biomechanics Biomedical Engineering Biophysics Blood Vessels Calibration California Cancer Model Cancer Patient Cell Culture Techniques Cells Cessation of life Clinical Colon Carcinoma Colonic Neoplasms Complex Computer Simulation Data Development Dimensions Disease Progression Disseminated Malignant Neoplasm Distant Dose Endothelial Cells Extracellular Matrix Frequencies Future Goals Growth Growth Factor Hepatic Hepatocyte Histology Histopathology Human Hypoxia Image Impairment In Situ In Vitro Individual Laboratories Life Liver Liver parenchyma Malignant Epithelial Cell Malignant Neoplasms Malignant neoplasm of liver Measurement Mechanics Metabolic Metastatic Neoplasm to the Liver Metastatic to Methods Modeling Molecular Morphology Necrosis Neoplasm Metastasis Organ Organoids Outcome Patients Pharmaceutical Preparations Prognostic Marker Psyche structure Regenerative Medicine Research Resolution Shapes Simulate Site Stem cells Structure System Techniques Testing Therapeutic Time Tissue Engineering Tissue Model Tissues Tumor Cell Invasion Universities Validation Variant biophysical properties cancer cell cancer therapy cell growth forest human data in vivo interdisciplinary approach mathematical model metastatic colorectal neoplastic cell neovascularization novel physical science public health relevance research study scaffold simulation spatiotemporal stem therapeutic target tissue support frame tumor tumor growth tumor microenvironment tumor progression virtual

项目摘要

DESCRIPTION (provided by applicant): Metastatic cancer growth is one of the most challenging areas in cancer treatment. However, metastasis is difficult to study systematically in the laboratory largely due to discrepancies between cell culture models and tumor growth in vivo. Much research has been devoted to defining molecular and biochemical changes during tumor progression, but a deeper understanding of the interaction between cancer cells and the organ microenvironment is crucial to future advances in cancer therapy. Our overall goal is to develop an integrated bioengineered/computational model of metastatic tumor growth to probe the relationships between growth dynamics, heterogeneous microenvironments, and the underlying biophysics. This proposal applies an interdisciplinary approach to cancer metastasis by directly merging the methods of the physical sciences, regenerative medicine, and tissue engineering. A University of Southern California-led multi-institutional team has developed mechanistic, multiscale computational models of vascularized tumor growth in complex virtual tissues. Wake Forest University has developed tissue bioengineering techniques to create functional liver organoids that can be injected with cancer cells and will be used to recapitulate the in vivo milieu of cancer metastasis. We propose to use bioengineering to create living liver tissues in situ with the native structure and function of human livers. The proposed integrated bioengineered/computational platform should give unprecedented spatiotemporal resolution and microenvironmental control of metastatic colon cancer growth. In Aim 1 of this proposal the computational model will be calibrated to data from bioengineered hepatic disc and in situ organoid experiments. Simulation predictions of colon cancer metastatic development will be compared to experiments to quantify accuracy and determine need for model refinements. In Aim 2, the calibrated model will be used to systematically investigate colon tumor growth dynamics under diverse microenvironmental conditions, in which we modulate biophysical parameters by applying mechanical forces, altering oxygenation, and administering therapeutics. We will validate the model's predictions against in situ organoid experiments under these same conditions. In Aim 3, we will calibrate the simulator to patient-derived metastatic colon tumor explants and determine if simulations of tumor growth correspond with imaging and outcome data from the same patients. This project will create a first-of-its-kind integrated computational/bioengineered liver metastasis model, providing a reproducible, controllable system for probing and manipulating the dynamics of metastasis, testing and refining hypotheses, and making predictions that can be extrapolated to human cancer. These integrative modeling efforts will give a new dimension to understanding tumor spread and yield important information about treating cancer metastases.

描述（由申请人提供）：转移性癌症生长是癌症治疗中最具挑战性的领域之一。然而，肿瘤的转移很难系统地研究