Understanding Blood Cancer Dynamics-Insights from Mathematical Modeling


Thomas Stiehl, Institute of Applied Mathematics, Heidelberg University


2019.01.16 16:00-17:00


520 Pao Yue-Kong Library


Acute leukemias belong to the most aggressive types of blood cancers. A clinical hallmark of acute leukemias is a large inter-individual heterogeneity with respect to treatment response and disease progression speed. The disease originates from a small population of so called cancer stem cells that carry mutations and give rise to the malignant cell bulk. Upon expansion, the malignant cells out-compete healthy blood production (hematopoiesis) which results in severe symptoms.

To study the interaction of malignant and healthy cells, we propose mathematical models of hierarchical cell populations. Cell competition and selection are mediated by various biologically inspired feedback mechanisms. The models relate disease dynamics to basic cell properties, such as proliferation rate (number of cell divisions per unit of time) and self-renewal fraction (probability that a progeny of a stem cell is again a stem cell). Depending on the posed questions, we use different mathematical approaches, including nonlinear ordinary differential equations, integro-differential equations and stochastic simulations.

A combination of mathematical analysis, computer simulations and patient data analysis provides insights in the following questions: (1) Which mechanisms allow malignant cells to out-compete their benign counterparts? (2) How do cancer stem cell properties (proliferation rate and self-renewal fraction) affect the clinical course and patient prognosis? (3) What can we learn about cancer stem cell parameters using routine clinical data? (4) What is the impact of cancer stem cell heterogeneity on disease dynamics? Which cell properties confer selective advantages? (5) How do cancer cells respond to signals from their environment? Does this affect disease dynamics?

The talk is based on joint works with Anna Marciniak-Czochra (Institute of Applied Mathematics, Heidelberg University), Anthony D. Ho, Natalia Baran and Christoph Lutz (Heidelberg University Hospital).