Simulating the impact of a molecular 'decision-process' on cellular phenotype and multicellular patterns in brain tumors.

Complex Biosystems Modeling Laboratory, Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA.
Journal of Theoretical Biology (Impact Factor: 2.3). 05/2005; 233(4):469-81. DOI: 10.1016/j.jtbi.2004.10.019
Source: PubMed

ABSTRACT 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-alpha (TGF alpha), the downstream enzyme phospholipaseC-gamma (PLC gamma) and a mitosis-associated response pathway. This network is activated by autocrine TGF alpha 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 analyse 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 PLC gamma towards an extrinsic chemotactic gradient. Implications of these results for future works, both on the modeling and experimental side are discussed.


Available from: Chaitanya Athale, Jun 13, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Experimental evidence suggests that epidermal growth factor receptor (EGFR)-mediated activation of the signaling protein phospholipase Cgamma plays a critical role in a cancer cell's phenotypic decision to either proliferate or to migrate at a given point in time. Here, we present a novel three-dimensional multiscale agent-based model to simulate this cellular decision process in the context of a virtual brain tumor. Each tumor cell is equipped with an EGFR gene-protein interaction network module that also connects to a simplified cell cycle description. The simulation results show that over time proliferative and migratory cell populations not only oscillate but also directly impact the spatio-temporal expansion patterns of the entire cancer system. The percentage change in the concentration of the sub-cellular interaction network's molecular components fluctuates, and, for the 'proliferation-to-migration' switch we find that the phenotype triggering molecular profile to some degree varies as the tumor system grows and the microenvironment changes. We discuss potential implications of these findings for experimental and clinical cancer research.
    Journal of Theoretical Biology 02/2007; 244(1):96-107. DOI:10.1016/j.jtbi.2006.06.034 · 2.30 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Agent-based models (ABM) provide a flexible multi-layer platform to incorporate various modeling techniques into a single hybrid model for designing optimal biomaterial scaffolds for angiogenesis in tissue engineering applications. Scaffold geometrical variables are considered as design variables. The growth factor concentration profile is the only process variable considered in the study. The product variables used to illustrate the combined effects of scaffold design variables and process variables on the outcome of angiogenesis include the density and depth of capillary invasion within the scaffold. The scaffold design process and the ABM developed to simulate angiogenesis are described in this paper. The performance of the ABM and vascularization of polymer scaffolds are evaluated by simulation studies. The effects of pore size, pore size distribution, and interconnectivity on total blood vessel length, invasion depth, and the total number of sprouts formed during the vascularization process are reported. The integration of the simulation of angiogenesis with ABMs and scaffold design techniques provide an iterative process for designing optimal scaffold structures. This facilitates faster design of optimized scaffolds with significantly less cost and enables better understanding of the mechanisms of angiogenesis of polymer scaffolds for tissue engineering applications.
    Industrial & Engineering Chemistry Research 02/2015; DOI:10.1021/ie503133e · 2.24 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.
    Journal of Artificial Societies and Social Simulation, The 01/2009; 12. · 1.16 Impact Factor