Interaction between the immune system and acute myeloid leukemia: A model incorporating promotion of regulatory T cell expansion by leukemic cells

金沢大学国際基幹教育院高等教育開発・支援系Population dynamics of regulatory T cells (Treg) are crucial for the underlying interplay between leukemic and immune cells in progression of acute myeloid leukemia (AML). The goal of this work is to elucidate the dynamics of a model that includes Treg, which can be qualitatively assessed by accumulating clinical findings on the impact of activated immune cell infusion after selective Treg depletion. We constructed an ordinary differential equation model to describe the dynamics of three components in AML: leukemic blast cells, mature regulatory T cells (Treg), and mature effective T cells (Teff), including cytotoxic T lymphocytes. The model includes promotion of Treg expansion by leukemic blast cells, leukemic stem cell and progenitor cell targeting by Teff, and Treg-mediated Teff suppression, and exhibits two coexisting, stable steady states, corresponding to high leukemic cell load at diagnosis or relapse, and to long-term complete remission. Our model is capable of explaining the clinical findings that the survival of patients with AML after allogeneic stem cell transplantation is influenced by the duration of complete remission, and that cut-off minimal residual disease thresholds associated with a 100% relapse rate are identified in AML. © 2018 Elsevier B.V.Embargo Period 12 month

Mathematical models of Leukaemia and its treatment: A review

Leukaemia accounts for around 3% of all cancer types diagnosed in adults, and is the most common type of cancer in children of paediatric age. There is increasing interest in the use of mathematical models in oncology to draw inferences and make predictions, providing a complementary picture to experimental biomedical models. In this paper we recapitulate the state of the art of mathematical modelling of leukaemia growth dynamics, in time and response to treatment. We intend to describe the mathematical methodologies, the biological aspects taken into account in the modelling, and the conclusions of each study. This review is intended to provide researchers in the field with solid background material, in order to achieve further breakthroughs in the promising field of mathematical biology