How modelling and statistical physics can contribute to understand brain tumors?
Mathilde Badoual and Christophe Deroulers (IMNC)
Diffuse low-grade gliomas are slowly-growing tumors. After tens of years, they transform inexorably into more aggressive forms, jeopardizing the patient’s life.
In our team, we combine mathematical modelling, statistical physics and image analysis, in order to have a better understanding of the natural history of these tumors and their response to treatments.
We present here two projects:
We will start with the effect of radiotherapy on gliomas. We developed a mathematical model that describes the evolution of cell density in gliomas and their response to treatments such as radiotherapy. We will show how biological data and clinical data were used to design and validate the model, and we will discuss the results of the model.
The second part of the talk will be about the collective behaviour of precursor cells that are suspected to be at the origin of gliomas. In their « normal state », these cells proliferate and die in order to maintain a constant cell density all over the adult brain (homeostasis). We modelled these phenomena with a cellular automaton and we will show that in the cases of almost uniform conditions, we observe oscillations, but in the case of non-uniform conditions, we observe intriguing phenomena such as propagating waves, spiral waves, large transient oscillations, and even population extinction. We will also show how the appearance of an abnormal cell can lead to the appearance of a glioma.