ON STABILITY OF A COMBINED GLEEVEC AND IMMUNE MODEL IN CHRONIC LEUKEMIA: EXPLOITING DELAY SYSTEM STRUCTURE

Abstract This paper focuses on the stability analysis of a delay-differential system encountered in modeling immune dynamics during Gleevec treatment for chronic myelogenous leukemia. A simple algorithm is proposed for the analysis of delay effects on the stability. The analysis shows that the model yields two fixed points, one stable and one unstable. The stable fixed point corresponds to some equilibrium solution in which the leukemia population is kept below the cytogenetic remission level. This result implies that, during Gleevec treatment, the resulting anti-leukemia immune response can serve to control the leukemia population. However, the rate of approach to the stable fixed point is very slow, indicating that the immune response is largely ineffective at driving the leukemia population towards the stable fixed point. Finally, a few remarks are made about possible treatment strategies that can be used to accelerate the approach of the leukemia and immune populations towards this stable equilibrium.

[1]  L. Saveanu,et al.  Ex Vivo Characterization of Multiepitopic Tumor-Specific CD8 T Cells in Patients with Chronic Myeloid Leukemia: Implications for Vaccine Development and Adoptive Cellular Immunotherapy1 , 2005, The Journal of Immunology.

[2]  Doron Levy,et al.  Post-transplantation dynamics of the immune response to chronic myelogenous leukemia. , 2005, Journal of theoretical biology.

[3]  Doron Levy,et al.  Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia , 2008, PLoS Comput. Biol..

[4]  S J Lee CHRONIC MYELOGENOUS LEUKAEMIA , 2000, British journal of haematology.

[5]  Carl T. Bergstrom,et al.  Models of CD8+ responses: 1. What is the antigen-independent proliferation program. , 2003, Journal of theoretical biology.

[6]  Daniel Isnardon,et al.  Imatinib and plasmacytoid dendritic cell function in patients with chronic myeloid leukemia. , 2004, Blood.

[7]  Tatsuo Furukawa,et al.  The effects of STI571 on antigen presentation of dendritic cells generated from patients with chronic myelogenous leukemia , 2003, Hematological oncology.

[8]  Brent Neiman,et al.  A Mathematical Model of Chronic Myelogenous Leukemia , 2000 .

[9]  Richard J. Jones,et al.  Treatment options for chronic myeloid leukemia: imatinib versus interferon versus allogeneic transplant , 2004, Current opinion in oncology.

[10]  P. Klenerman,et al.  Low level viral persistence after infection with LCMV: a quantitative insight through numerical bifurcation analysis. , 2001, Mathematical biosciences.

[11]  Martin A. Nowak,et al.  Dynamics of chronic myeloid leukaemia , 2005, Nature.

[12]  Susan O'Brien,et al.  Molecular Responses in Patients with Chronic Myelogenous Leukemia in Chronic Phase Treated with Imatinib Mesylate , 2005, Clinical Cancer Research.

[13]  Alan S. Perelson,et al.  Different Dynamics of CD4+ and CD8+ T Cell Responses During and After Acute Lymphocytic Choriomeningitis Virus Infection 1 , 2003, The Journal of Immunology.

[14]  Helen Moore,et al.  A mathematical model for chronic myelogenous leukemia (CML) and T cell interaction. , 2004, Journal of theoretical biology.