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.

Public Health Relevance

Most cancer-related deaths are the result of uncontrolled tumor invasion and growth of metastases throughout the body. This metastatic tumor spread depends crucially on the ability of cancer cells to thrive in the site of the metastases called the microenvironment. We will use bioengineered livers seeded with metastatic colon cancer to systematically investigate the microenvironmental factors contributing to metastatic progression in colon cancer patients and develop computational models to predict outcome and identify new targets for treatment.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Greenspan, Emily J
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Southern California
Internal Medicine/Medicine
Schools of Medicine
Los Angeles
United States
Zip Code
Ghaffarizadeh, Ahmadreza; Heiland, Randy; Friedman, Samuel H et al. (2018) PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems. PLoS Comput Biol 14:e1005991
Ng, Chin F; Frieboes, Hermann B (2018) Simulation of Multispecies Desmoplastic Cancer Growth via a Fully Adaptive Non-linear Full Multigrid Algorithm. Front Physiol 9:821
Vyas, Dipen; Baptista, Pedro M; Brovold, Matthew et al. (2017) Self-assembled liver organoids recapitulate hepatobiliary organogenesis in vitro. Hepatology :
Ng, Chin F; Frieboes, Hermann B (2017) Model of vascular desmoplastic multispecies tumor growth. J Theor Biol 430:245-282
Devarasetty, Mahesh; Skardal, Aleksander; Cowdrick, Kyle et al. (2017) Bioengineered Submucosal Organoids for In Vitro Modeling of Colorectal Cancer. Tissue Eng Part A 23:1026-1041
Garvey, Colleen M; Gerhart, Torin A; Mumenthaler, Shannon M (2017) Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques. J Vis Exp :
Baptista, Pedro M; Moran, Emma C; Vyas, Dipen et al. (2016) Fluid Flow Regulation of Revascularization and Cellular Organization in a Bioengineered Liver Platform. Tissue Eng Part C Methods 22:199-207
Juarez, Edwin F; Lau, Roy; Friedman, Samuel H et al. (2016) Quantifying differences in cell line population dynamics using CellPD. BMC Syst Biol 10:92
Ghaffarizadeh, Ahmadreza; Friedman, Samuel H; Macklin, Paul (2016) BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations. Bioinformatics 32:1256-8
Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko (2016) Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth. Methods Mol Biol 1516:335-346

Showing the most recent 10 out of 15 publications