DOI
https://doi.org/10.25772/4V8P-EQ38
Author ORCID Identifier
https://orcid.org/0000-0002-1846-5514
Defense Date
2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Biomedical Engineering
First Advisor
Christopher A. Lemmon, Ph.D.
Second Advisor
Seth H. Weinberg, Ph.D.
Abstract
Epithelial-mesenchymal transition (EMT) regulates the cellular processes of migration, growth, and proliferation - as well as the collective cellular process of tissue remodeling - in response to mechanical and chemical stimuli in the cellular microenvironment. Cells of the epithelium form cell-cell junctions with adjacent cells to function as a barrier between the body and its environment. By distributing localized stress throughout the tissue, this mechanical coupling between cells maintains tensional homeostasis in epithelial tissue structures and provides positional information for regulating cellular processes. Whereas in vitro and in vivo models fail to capture the complex interconnectedness of EMT-associated signaling networks, previous computational models have succinctly reproduced components of the EMT program. In this work, we have developed a computational framework to evaluate the mechanochemical signaling dynamics of EMT at the molecular, cellular, and tissue scale. First, we established a model of cell-matrix and cell-cell feedback for predicting mechanical force distributions within an epithelial monolayer. These findings suggest that tensional homeostasis is the result of cytoskeletal stress distribution across cell-cell junctions, which organizes otherwise migratory cells into a stable epithelial monolayer. However, differences in phenotype-specific cell characteristics led to discrepancies in the experimental and computational observations. To better understand the role of mechanical cell-cell feedback in regulating EMT-dependent cellular processes, we introduce an EMT gene regulatory network of key epithelial and mesenchymal markers, E-cadherin and N-cadherin, coupled to a mechanically-sensitive intracellular signaling cascade. Together these signaling networks integrate mechanical cell-cell feedback with EMT-associated gene regulation. Using this approach, we demonstrate that the phenotype-specific properties collectively account for discrepancies in the computational and experimental observations. Additionally, mechanical cell-cell feedback suppresses the EMT program, which is reflected in the gene expression of the heterogeneous cell population. Together, these findings advance our understanding of the complex interplay in cell-cell and cell-matrix feedback during EMT of both normal physiological processes as well as disease progression.
Rights
© Lewis E. Scott
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
8-9-2019
Included in
Biomechanics and Biotransport Commons, Computational Engineering Commons, Molecular, Cellular, and Tissue Engineering Commons