| A quantitative, comprehensive understanding of transforming growth factor beta (TGF-beta) signaling---which regulates a diverse array of key physiologic processes (e.g., cell proliferation, differentiation, apoptosis, motility, angiogenesis, and immune surveillance)---is critical for the development of targeted cancer therapy. However, two apparently opposite roles that TGF-beta exerts during cancer progression---as a tumor suppressor in normal to pre-malignant cells and as a tumor promoter in malignant cells---render it intractable. The goal of this dissertation is to improve our understanding of the complexity and dynamics of the TGF-beta signaling network, and in particular, mechanisms underlying the disparate, contradictory roles of TGF-beta signaling in tumorigenesis. To this aim, we focus on the development of multi-scale models of TGF-beta signaling from molecular level to cellular and tissue level, and a variety of model-based analysis and generation of testable hypotheses.;We begin by developing a mathematical model of the canonical TGF-beta signaling pathway mediated by Smad transcription factors. The developed mechanistic model, which describes mathematically how extracellular TGF-beta signal is sensed by its cognate receptors and transmitted into the nucleus through intracellular Smad proteins, is used to investigate the dynamics of nuclear accumulation of the ligand-induced Smads that ultimately control expression of TGF-beta-targeted genes, and how the nuclear retention of the Smads is regulated and modulated. The model also predicts possible dynamic behavior of the Smad-mediated pathway in abnormal, cancerous cells, and provides clues regarding possible mechanisms for explaining the seemingly contradictory roles of TGF-beta via the Smad pathway during cancer progression.;To understand the mysterious correlation between high levels of TGF-beta and poor prognosis, a macroscopic mechanistic model of TGF-beta-driven regulation of tissue homeostasis is developed from a control engineering perspective. The model---which deals, not with a single cell, but with the cell population as a systemic entity---represents a control system characterization of how two primary physiological processes governing homeostasis of a tissue, cell proliferation and cell death, are regulated by TGF-beta via the interactions between proliferating cells and their surroundings. The model allows predicting possible dynamic characteristics of the TGF-beta-mediated control system in cancer tissues, from which we are able to present an alternative perspective of the TGF-beta paradox in cancer. The results indicate that the correlation between increased levels of TGF-beta and poor prognosis may have been inadvertently misconstrued as causality, creating an apparent paradox.;To gain a quantitative understanding of how TGF-beta can exhibit its multi-functionality independent of Smad, two novel single-cell models of non-Smad pathways are presented for the first time. A mechanistic model of the TGF-beta-triggered ERK MAP kinase activation pathway and its crosstalk with the canonical Smad pathway is developed and employed to yield quantitative insight into how the crosstalk among the various TGF-beta branch pathways influences the system behavior. Model simulation and analysis reveals that the dynamics of Smad signaling at the cytoplasmic level may be significantly regulated by TGF-beta-triggered ERK signaling, and compartment-specific receptor endocytosis may play a critical role in regulating the TGF-beta-induced cellular outcomes. Furthermore, the model predictions of cancerous system behavior propose that multi-level genetic and/or epigenetic abnormalities of major components of TGF-beta signaling leads to changes in the intensity and duration of both Smad and ERK signaling during cancer progression, ultimately resulting in an imbalance between the Smad and ERK pathways in favor of tumor promotion.;Finally, we present a novel mathematical modeling framework for understanding the complex signaling behavior of TGF-beta-induced apoptosis. The model incorporates various TGF-beta branch pathways, including the TAK1-MKK3/6-p38, Smad-GADD45beta-MTK1, and putative ARTS pathways, which are coupled with downstream caspase activation cascades and the mitochondrial pathway. Model analysis reveals important regulatory mechanisms of TGF-beta-driven apoptosis, and identifies how all-or-none behavior of apoptosis can be elicited. Furthermore, in silico experiments of apoptotic signaling in cancer cells provide insight into how the tumor-suppressor role of TGF-beta as a pro-apoptotic signal can become attenuated so that cancer cells are able to avoid cell death, and allow us to propose a promising therapeutic strategy against cancer. |
