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Paradoxical Dependencies of Tumor Dormancy and Progression on Basic Cell Kinetics

¹ Center of Cancer Systems Biology, Caritas St. Elizabeth's Medical Center, Tufts University School of Medicine, Boston, Massachusetts; ² Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida; and ³ Division of Mathematics, University of Dundee, Dundee, United Kingdom

Requests for reprints: Philip Hahnfeldt, Center of Cancer Systems Biology, Caritas St. Elizabeth's Medical Center, Tufts University School of Medicine, 736 Cambridge Street, 02135 Boston, MA. Phone: 617-789-2998; Fax: 617-562-7142; E-mail: Philip.Hahnfeldt{at}tufts.edu.

Even after a tumor is established, it can early on enter a state of dormancy marked by balanced cell proliferation and cell death. Disturbances to this equilibrium may affect cancer risk, as they may cause the eventual lifetime clinical presentation of a tumor that might otherwise have remained asymptomatic. Previously, we showed that cell death, proliferation, and migration can play a role in shifting this dynamic, making the understanding of their combined influence on tumor development essential. We developed an individual cell-based computer model of the interaction of cancer stem cells and their nonstem progeny to study early tumor dynamics. Simulations of tumor growth show that three basic components of tumor growth—cell proliferation, migration, and death—combine in unexpected ways to control tumor progression and, thus, clinical cancer risk. We show that increased proliferation capacity in nonstem tumor cells and limited cell migration overall lead to space constraints that inhibit proliferation and tumor growth. By contrast, increasing the rate of cell death produces the expected tumor size reduction in the short term, but results ultimately in paradoxical accelerated long-term growth owing to the liberation of cancer stem cells and formation of self-metastases.[Cancer Res 2009;69(22):8814–21]

Key Words: Tumor dormancy • tumor progression • cancer stem cells • apoptosis • self-metastases • agent-based model