Understanding Cancer Through Evolutionary Game Theory

Cancer, Stem Cells and Developmental Biology
Green and Blue Lecture Hall, UMCU
Dr. Kateřina Staňková

Dr. Kateřina Staňková, Department of Data Science and Knowledge Engineering, Maastricht University

Katerina Stankova

Titel: Understanding Cancer Through Evolutionary Game Theory


Cancer can be viewed as an evolutionary process and as such can be modeled and explained using evolutionary game theory. In the first part of the talk we will focus on hallmarks of cancer and various models of cancer as a game (e.g. non-spatial model based on differential equations, spatial model using diffusion equations, spatial in-silico models).
Subsequently, we will focus on the cancer treatment. The current standard of care for cancer therapy is to kill the largest possible number of tumor cells by applying the maximum tolerable dose.  While this approach is often initially successful at reducing tumor burden, it inevitably fails due to evolution and proliferation of resistant cancer phenotypes. Moreover, this highest tolerable dose regimen is typically very aggressive to the patient and very expensive. Shifting the goal of therapy from complete elimination of tumor burden to instead controlling the tumor burden (with much lower treatment doses) for a maximal period of time – the so-called adaptive therapy – can change the approach to therapy dramatically. We will show that Stackelberg game theory can be very helpful in designing such an adaptive treatment. 



Dr. Kateřina Staňková is an assistant professor in game theory, with additional expertise in optimization, optimal control, mathematical biology, and adaptive dynamics.  She specializes on modeling complex real-world systems and predicting their temporal and spatial behavior, using mathematical techniques.
Her PhD research (at Delft Institute of Applied Mathematics, TU Delft, 2005-2009) focused on Stackelberg and inverse Stackelberg games and on application of these games in traffic control and in energy markets. During her postdoctoral fellowships at INRIA Grenoble - Rhône-Alpes and Delft Center for Systems and Control, TU Delft (2010-2012) her attention was drawn to modeling complex biological systems, such as arthropod predator-prey systems or tri-trophic systems plant-herbivore-carnivore, in collaboration with colleagues from The Netherlands, France, and Brazil.  She continues working on these research areas in her current position at the Department of Data Science and Knowledge Engineering, Maastricht University (since 2012).  
Since 2015 she has been working on modeling cancer growth and treatment, using spatial evolutionary game theory, in collaboration with the Moffitt Cancer Center, Florida, US, and University of Illinois at Chicago, US. She is very much interested in understanding both spatial and temporal characteristics of cancer, using advanced analytical and computational tools to find optimal treatment, and validating the predicted behaviors via histological data.


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