Agent-Based Models in Cancer Prevention Research (pp. 105-116)
Authors: (John W. Pepper, Nadarajen A. Vydelingum, Barbara K. Dunn, Richard M. Fagerstrom, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA)
Abstract: Agent-based models have proven very useful for studying complex dynamic
processes. As biomedical researchers have turned their attention to the most complex
diseases, they have made increasing use of agent-based models in various areas,
including cancer biology. Cancer is arguably the ultimate complex biological system. It
has recently become clear that much of its complexity arises through Darwinian
evolution, driven by uncontrolled natural selection among rapidly mutating somatic cells.
Here we review the application of agent-based models and simulations to five key
open questions in cancer prevention research. The five research questions we review as
case studies include: 1) What normally prevents somatic evolution from generating
cancer? 2) Why do benign growths often progress to malignant cancers? 3) What is the
chronological sequence of molecular events in cancer progression? 4) Are there reliable
molecular biomarkers for cancer?; and 5) Will evolved drug resistance stymie efforts at
long-term cancer chemoprevention?
We conclude that molecular analysis can be usefully augmented by using agentbased
models to generate plausible and productive hypotheses for empirical testing.
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