A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture

Abstract

BackgroundGlioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists.ResultsHerein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students.ConclusionsIt is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.Electronic supplementary materialThe online version of this article (10.1186/s12918-017-0516-z) contains supplementary material, which is available to authorized users.

Integrating in vitro experiments with in silico approaches for Glioblastoma invasion: the role of cell-to-cell adhesion heterogeneity

“…CA models have been also extended to hybrid discrete-continuous (HDC) models in an attempt to additionally describe the interactions between cells and the microenvironment. These models integrate data from both experimental and/or clinical sources and have been widely used to describe critical aspects of tumour evolution and invasion, including genotype to phenotype relations 66 , inter- and intra-tumoral heterogeneity 19 , 67 , the effect of autocrine/paracrine signalling on cell proliferation and motility 66 , 68 , cell-to-cell and cell-to-matrix adhesion 33 , 51 , 67 , 69 , 70 , phenotypic plasticity 71 – 73 , the formation of invasive branches 74 , evolutionary dynamics 75 , 76 , the interplay with the brain anatomic features 77 , 78 and the microenvironmental factors 79 , as well as treatment outcomes 80 , 81 .…”

In silico tumor growth validation based on human brain cancer models

“…As mentioned before, CA models have been also extended to hybrid HDC models in an attempt to additionally designate the interactions between cells and the microenvironment. These models integrate data from both experimental and/or clinical sources and have been widely used to describe critical aspects of tumour evolution and invasion including genotype to phenotype relations [129], inter-and intra-tumoral heterogeneity [104,113], the effect of autocrine/paracrine signaling on cell proliferation and motility [129,130], cell-to-cell and cell-to-matrix adhesion [104,112,114,131,132], phenotypic plasticity [133][134][135], the formation of invasive branches [108], evolutionary dynamics [136,137], the interplay with the brain anatomic features [100,138] and the microenvironmental factors [139], as well as treatment outcomes [101,140].…”