Display Abstract

Title Clonal selection and therapy resistance in acute leukemias: Mathematical modelling explains different proliferation patterns at diagnosis and relapse

Name Anna Marciniak-Czochra
Country Germany
Email anna.marciniak@iwr.uni-heidelberg.de
Co-Author(s) Natalia Baran, Anthony D.Ho and Thomas Stiehl
Submit Time 2014-02-15 17:15:54
Session
Special Session 3: Mathematical models in the systems biology of cancer
Contents
Recent experimental evidence suggests that acute myeloid leukemias may originate from multiple clones of malignant cells. However, it is not known how the observed clones may differ with respect to cell properties such as proliferation and self-renewal. There are scarcely any data on how these cell properties change due to chemotherapy and relapse. We propose a new mathematical model to investigate the impact of cell properties on multi-clonal composition of leukemias. Model results imply that enhanced self-renewal may be a key mechanism in the clonal selection process. Simulations suggest that fast proliferating and highly self-renewing cells dominate at primary diagnosis while relapse following therapy-induced remission is triggered mostly by highly self-renewing but slowly proliferating cells. Comparison of simulation results to patient data demonstrates that the proposed model is consistent with clinically observed dynamics. To explain the underlying phenomenon, we investigate a structured population model with a continuum of different cell clones. We show mass concentration of the model solutions, which reflects the process of selection of clones with highest self-renewal potential.