  Experimental evidence indicates that human brain cancer cells proliferate or
migrate, yet do not display both phenotypes at the same time. Here, we present
a novel computational model simulating this cellular decision-process leading
up to either phenotype based on a molecular interaction network of genes and
proteins. The model's regulatory network consists of the epidermal growth
factor receptor (EGFR), its ligand transforming growth factor-a (TGFa), the
downstream enzyme phospholipaseC-gamma (PLCg) and a mitosis-associated response
pathway. This network is activated by autocrine TGFa secretion, and the
EGFR-dependent downstream signaling this step triggers, as well as modulated by
an extrinsic nutritive glucose gradient. Employing a framework of mass action
kinetics within a multiscale agent-based environment, we analyze both the
emergent multicellular behavior of tumor growth and the single-cell molecular
profiles that change over time and space. Our results show that one can indeed
simulate the dichotomy between cell migration and proliferation based solely on
an EGFR decision network. It turns out that these behavioral decisions on the
single cell level impact the spatial dynamics of the entire cancerous system.
Furthermore, the simulation results yield intriguing experimentally testable
hypotheses also on the sub-cellular level such as spatial cytosolic
polarization of PLCg towards an extrinsic chemotactic gradient. Implications of
these results for future works, both on the modeling and experimental side are
discussed.
