The application of signaling networks to cancer metastasis and cellular motility through the EGFR pathway

Abstract

This thesis explores the problem of cancer metastasis by analyzing the various downstream components of the epidermal growth factor receptor (EGFR) pathway. This work develops a mathematical model that consists of partial differential equations and signaling networks. Analysis techniques for these nonlinear reaction-diffusion equations included a study of the biological background and motivation, along with computational simulation of the various sets of models developed. The modeling effort combined biochemical reaction-diffusion equations for various species with mathematical descriptions of the mechanical machinery of the cell to characterize the foundations of cell movement in response to stimuli. By quantifying and qualifying the signaling networks and molecular pathways involved in cellular signaling and linking intracellular signaling to the mechanical machinery of the cell, it is possible to quickly check in silico the effects of changing various feedback parameters and signaling molecule concentrations. By creating a model of this process, it is possible to perform rapid tests of different pharmaceuticals on the biochemical and biomechanical pathways, in order to assess how they would affect cell motility and cancer metastasis on a large scale.