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Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia

Overview of attention for article published in PLoS Computational Biology, June 2008
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Title
Dynamics and Potential Impact of the Immune Response to Chronic Myelogenous Leukemia
Published in
PLoS Computational Biology, June 2008
DOI 10.1371/journal.pcbi.1000095
Pubmed ID
Authors

Peter S. Kim, Peter P. Lee, Doron Levy

Abstract

Recent mathematical models have been developed to study the dynamics of chronic myelogenous leukemia (CML) under imatinib treatment. None of these models incorporates the anti-leukemia immune response. Recent experimental data show that imatinib treatment may promote the development of anti-leukemia immune responses as patients enter remission. Using these experimental data we develop a mathematical model to gain insights into the dynamics and potential impact of the resulting anti-leukemia immune response on CML. We model the immune response using a system of delay differential equations, where the delay term accounts for the duration of cell division. The mathematical model suggests that anti-leukemia T cell responses may play a critical role in maintaining CML patients in remission under imatinib therapy. Furthermore, it proposes a novel concept of an "optimal load zone" for leukemic cells in which the anti-leukemia immune response is most effective. Imatinib therapy may drive leukemic cell populations to enter and fall below this optimal load zone too rapidly to sustain the anti-leukemia T cell response. As a potential therapeutic strategy, the model shows that vaccination approaches in combination with imatinib therapy may optimally sustain the anti-leukemia T cell response to potentially eradicate residual leukemic cells for a durable cure of CML. The approach presented in this paper accounts for the role of the anti-leukemia specific immune response in the dynamics of CML. By combining experimental data and mathematical models, we demonstrate that persistence of anti-leukemia T cells even at low levels seems to prevent the leukemia from relapsing (for at least 50 months). As a consequence, we hypothesize that anti-leukemia T cell responses may help maintain remission under imatinib therapy. The mathematical model together with the new experimental data imply that there may be a feasible, low-risk, clinical approach to enhancing the effects of imatinib treatment.

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Geographical breakdown

Country Count As %
United States 2 3%
Unknown 64 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 24%
Student > Ph. D. Student 13 20%
Student > Bachelor 8 12%
Professor > Associate Professor 7 11%
Professor 4 6%
Other 10 15%
Unknown 8 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 27%
Mathematics 12 18%
Medicine and Dentistry 7 11%
Computer Science 5 8%
Engineering 3 5%
Other 8 12%
Unknown 13 20%