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Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth

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Stem Cell Heterogeneity

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1516))

Abstract

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell–cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

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Acknowledgments

JP and HE were partially supported by the Personalized Medicine Award 09-33000-15-03 from the DeBartolo Family Personalized Medicine Institute Pilot Research Awards in Personalized Medicine (PRAPM). PM was supported by the Breast Cancer Research Foundation and the National Institutes of Health [1R01CA180149].

Author information

Authors and Affiliations

  1. Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33647, USA

    Jan Poleszczuk & Heiko Enderling

  2. Center for Applied Molecular Medicine, University of Southern California, Los Angeles, CA, 90033, USA

    Paul Macklin

Authors
  1. Jan Poleszczuk
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  2. Paul Macklin
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  3. Heiko Enderling
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Corresponding author

Correspondence to Heiko Enderling .

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Editors and Affiliations

  1. Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

    Kursad Turksen

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© 2016 Springer Science+Business Media New York

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Poleszczuk, J., Macklin, P., Enderling, H. (2016). Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth. In: Turksen, K. (eds) Stem Cell Heterogeneity. Methods in Molecular Biology, vol 1516. Humana Press, New York, NY. https://doi.org/10.1007/7651_2016_346

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  • DOI: https://doi.org/10.1007/7651_2016_346

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6549-6

  • Online ISBN: 978-1-4939-6550-2

  • eBook Packages: Springer Protocols

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