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A Survey of Models for Tumor-Immune System Dynamics pp 295–333Cite as

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Tumor Heterogeneity and Growth Control

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Abstract

Tumor growth control is described especially as it pertains to tumor heterogeneity. Four facets heterogeneity are reviewed; statistical or distributional heterogeneity, epigenetic or environmental heterogeneity, emergence of intrinsic or clonal heterogeneity, and the development of clonal subpopulations in a heterogeneous micro-environment. A model of tumor growth and its control is developed. Growth control is defined for a heterogeneous tumor composed of a cycling, proliferative compartment and a non-cycling, quiescent one. The paradigm for this form of heterogeneity is hypoxia in a solid tumor. It is used to establish a linkage between the carrying capacity of a tumor-bearing host for its tumor burden. The model is then applied to three disparate tumor growth phenomena. Each study is accompanied by an exploration of what we know (the experimental and clinical literature describing the phenomenon), what we think we know (a summary of the underlying growth processes we surmise accounts for the phenomenon), what we wish we know (areas which are still unexplored in the laboratory or clinic), and a description of the experiment and its analysis (a means of gathering and analyzing the missing information to complete a picture of the phenomenon in question).

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Author information

Authors and Affiliations

  1. Research Support and Information Services, Roche Bioscience, Palo Alto, CA, USA

    S. Michelson

  2. Radiation Biology Laboratories, Brown University, Providence, RI, USA

    J. T. Leith

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  1. S. Michelson
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Editors and Affiliations

  1. Department of Mathematics, Old Dominion University, Norfolk, Virginia, 23529-0077, USA

    John A. Adam

  2. Dipartimento di Matematica, Politecnico di Torino, 10129, Torino, Italy

    Nicola Bellomo

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Michelson, S., Leith, J.T. (1997). Tumor Heterogeneity and Growth Control. In: Adam, J.A., Bellomo, N. (eds) A Survey of Models for Tumor-Immune System Dynamics. Modeling and Simulation in Science, Engineering, & Technology. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8119-7_7

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  • DOI: https://doi.org/10.1007/978-0-8176-8119-7_7

  • Publisher Name: Birkhäuser, Boston, MA

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