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.

Authors

Justin Caccavale, University of Delaware
David Fiumara, University of Delaware
Michael Stapf, University of Delaware
Liedeke Sweitzer, University of Delaware
Hannah J. Anderson, University of Delaware
Jonathan Gorky, Thomas Jefferson UniversityFollow
Prasad Dhurjati, University of DelawareFollow
Deni S. Galileo, University of Delaware; Christiana Care Health SystemFollow

Document Type

Article

Publication Date

12-11-2017

Comments

This article has been peer reviewed. It is the author’s final published version in BMC Systems Biology

Volume 11, Issue 1, December 2017, Article number 124.

The published version is available at DOI: 10.1186/s12918-017-0516-z. Copyright © Caccavale et al.

Abstract

BACKGROUND: Glioblastoma 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.

RESULTS: Herein, 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.

CONCLUSIONS: It 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.

Recommended Citation

Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J.; Gorky, Jonathan; Dhurjati, Prasad; and Galileo, Deni S., "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." (2017). Department of Pathology, Anatomy, and Cell Biology Faculty Papers. Paper 229.
https://jdc.jefferson.edu/pacbfp/229

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

PubMed ID

29228953