In silico modeling for tumor growth visualization.

Fleur Jeanquartier,Andreas Holzinger,Claire Jean-Quartier,David Cemernek

doi:10.1186/s12918-016-0318-8

Fleur Jeanquartier, Andreas Holzinger + Show 2 more

Open Access

https://doi.org/10.1186/s12918-016-0318-8

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Abstract

BackgroundCancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research.ResultsWe aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscapeand http://styx.cgv.tugraz.at:8080/cpm-cytoscape/.ConclusionIn-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective.

Highlights

We present a new 2D visualization approach for a dynamic cellular model simulation that accounts for lattice size, cell size, environment parameters and interactions between cells
The Java packages consist of the implementation of the Cellular Potts model (CPM) itself, a graph converter to convert the CPM lattice into a graph structure, a more specific cytoscape converter to represent the graph enrichment needed for the visualization library as well as the servlet to provide the communication interface between backend and frontend via JSON
Recent advances in Computational Biology show high potential to deepen the understanding of origin and progression of cancer

Summary

Introduction

Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. Cancer depicts a group of diseases which refer to abnormal new growth of cells which can spread and invade different areal parts throughout the body [2]. A tumor is most commonly described as an abnormal growth of clustered cells which can be either benign (well-structured and non-harmful) or malignant (cancerous) [3].

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