1. ¹Division of Hematology, Mayo Clinic Rochester, Rochester, MN, USA
2. ²Department of Molecular Medicine, Mayo Clinic Rochester, Rochester, MN, USA
3. ³Biomathematics Resource Core and Department of Biochemistry and Molecular Biology, Mayo Clinic Rochester, Rochester, MN, USA
4. ⁴Department of Mathematics, Southern Methodist University, Dallas, TX, USA
5. ⁵Department of Mathematics, University of Houston, Houston, TX, USA

Correspondence: Dr D Dingli, Department of Molecular Medicine, Mayo Clinic, 200 First St SW, Mayo W10, Rochester, MN 55905, USA. E-mail: dingli.david@mayo.edu

Received 19 January 2009; Revised 2 April 2009; Accepted 26 April 2009; Published online 5 June 2009.

Abstract

Replication-competent viruses are being tested as tumor therapy agents. The fundamental premise of this therapy is the selective infection of the tumor cell population with the amplification of the virus. Spread of the virus in the tumor ultimately should lead to eradication of the cancer. Tumor virotherapy is unlike any other form of cancer therapy as the outcome depends on the dynamics that emerge from the interaction between the virus and tumor cell populations both of which change in time. We explore these interactions using a model that captures the salient biological features of this system in combination with in vivo data. Our results show that various therapeutic outcomes are possible ranging from tumor eradication to oscillatory behavior. Data from in vivo studies support these conclusions and validate our modeling approach. Such realistic models can be used to understand experimental observations, explore alternative therapeutic scenarios and develop techniques to optimize therapy.