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Cellular Automaton Modeling of Tumor Invasion

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Encyclopedia of Complexity and Systems Science

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Cancer cells acquire characteristic traits in a step-wise manner during carcinogenesis . Some of these traits are autonomous growth,induction of angiogenesis, invasion and metastasis. In this chapter, the focus is on one of the late stages of tumor progression: tumor invasion. Tumorinvasion has been recognized as a complex system, since its behavior emerges from the combined effect of tumor cell-cell andcell‐microenvironment interactions. Cellular automata (CA) provide simple models of self‐organizing complex systems in which collectivebehavior can emerge out of an ensemble of many interacting “simple” components. Recently, cellular automata have been used to gaina deeper insight in tumor invasion dynamics. In thischapter, we briefly introduce cellular automata as models oftumor invasion...

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Abbreviations

Cadherins:

Important class of transmembrane proteins. They play a significant role in cell-cell adhesion, ensuring that cells within tissues are bound together.

Chemotaxis:

Motion response to chemical concentration gradients of a diffusive chemical substance.

Extracellular matrix (ECM):

Components that are extracellular and composed of secreted fibrous proteins (e. g. collagen) and gel-like polysaccharides (e. g. glycosaminoglycans) binding cells and tissues together.

Fiber tracts:

Bundle of nerve fibers having a common origin, termination, and function and especially one within the spinal cord or brain.

Haptotaxis:

Directed motion of cells along adhesion gradients of fixed substrates in the ECM, such as integrins.

“Slime trail motion”:

Cells secrete a non‐diffusive substance; concentration gradients of the substance allow the cells to migrate towards already explored paths.

Somatic evolution:

Darwinian‐type evolution that occurs on soma (as opposed to germ) cells and characterizes cancer progression [1].

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Acknowledgments

We are grateful to D. Basanta, L. Brusch, A. Chauviere, E. Flach and F. Peruani for the comments and the fruitful discussions. Weacknowledge support from the systems biology network HepatoSys of the German Ministry for Education and Research through grant 0313082J. AndreasDeutsch is a member of the DFG Research Center for Regenerative Therapies Dresden – Cluster of Excellence – andgratefully acknowledges support by the Center. The research was supported in part by funds from the EU Marie Curie Network “Modeling,Mathematical Methods and Computer Simulation of Tumor Growth and Therapy” (EU-RTD IST-2001-38923). Finally, the authors would like tothank for the financial support of the Gottfried Daimler- and Karl Benz foundation through the project “Biologistics: From bio‐inspiredengineering of complex logistical systems until nanologistics” (25-02/07).

Author information

Authors and Affiliations

  1. Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany

    Haralambos Hatzikirou & Andreas Deutsch

  2. Institute of Pathology, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany

    Georg Breier

Authors
  1. Haralambos Hatzikirou
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  2. Georg Breier
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  3. Andreas Deutsch
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Editor information

Editors and Affiliations

  1. RAMTECH LIMITED, 122 Escalle Lane, Larkspur, CA, 94939, USA

    Robert A. Meyers Ph. D. (Editor-in-Chief) (Editor-in-Chief)

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© 2009 Springer-Verlag

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Hatzikirou, H., Breier, G., Deutsch, A. (2009). Cellular Automaton Modeling of Tumor Invasion . In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_60

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