Biomedical Engineering Reference
In-Depth Information
6.3
MODELING TUMORS AS COMPLEX
BIOSYSTEMS: AN AGENT-BASED
APPROACH
Yuri Mansury and Thomas S. Deisboeck
Complex Biosystems Modeling Laboratory, Harvard-MIT (HST)
Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown
We argue that tumors behave as
complex dynamic self-organizing
and
adaptive biosys-
tems
. In this chapter, we present a numerical
agent-based model
of malignant brain tumor
cells in which both time and space are discrete yet environmental variables are treated as
a continuum. Simulations of this
multiscale
algorithm allow us to investigate the molecu-
lar, microscopic, and multicellular patterns that
emerge
from various interactions among
cells and between the cells and their environments.
1.
INTRODUCTION
Studies of multicellular organisms recently experienced a paradigm shift
into a framework that views these biological life forms as
complex systems
. In
studies of malignant tumors, such a paradigm shift is accompanied by growing
evidence that these tumors behave as dynamic self-organizing and adaptive bio-
systems (see (1-3) and chapter 6.1 by Pienta (Part III, this volume)). The present
chapter reviews the applications of insights from complex system research in
studies of malignant brain tumor cells, such as glioblastoma multiforme (GBM).
Understanding the emerging behavior of malignant cancer cells with the use of
Address correspondence to: Thomas S. Deisboeck, Complex Biosystems Modeling Laboratory,
Harvard-MIT Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospi-
tal, East CNY-2301, 13th Street, Building 149, Charlestown, MA 02129 (deisboec@helix.mgh.
harvard.edu).
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