17/10/2013
Seminar Friday, 18 October 2013
Time: 13:30
Where: Univ. of York, Ron Cooke Hub: RCH/204
http://www.nottingham.ac.uk/mathematics/people/grazziela.figueredo
Early-stage cancer and its interactions with the immune system are still not fully understood. In order to better understand these processes, researchers employ different methods. Simulation and in particular, agent-based simulation (ABS) have been found useful tools for understanding it.
In a previous study we have built an ABS model to study the interplay of immune cells and early-stage cancer. The model considers interactions between tumour cells and immune effector cells, as well as the immune-stimulatory and suppressive cytokines IL-2 and TGF-Beta. IL-2 molecules mediate the immune response towards tumour cells. They interfere on the proliferation of effector cells according to the number of tumour cells in the system. Conversely, TGF-Beta stimulates tumour growth and suppresses the immune responses by inhibiting the activation of effector cells and reducing tumour-antigen expression.
In order to validate our model, we used a well-established mathematical model found in the literature. While at average both models do not show a statistical significant difference, some additional trends in the results of the ABS model are observed. As ABS is a stochastic simulation method, it was run for multiple times. Instead of having one solution, as it is the case for a deterministic mathematical model, ABS produces a variety of outcomes. These solutions are usually very similar. In our cases study, however, we could observe some instances which could not have been observed by using analytical methods).
The use of ABS modelling has therefore led to the discovery of additional “rare” patterns, which we would have not been able to derive by using analytical methods. These “extreme cases” indicate that there might be circumstances where the tumour cells are completely eliminated by the immune system, without the need of any cancer therapies. We strongly believe that the observed emergent behaviour produced by stochastic simulation can make a useful contribution to assisting immunological research. With the additional information supplied from the ABS, immunologists can test new hypotheses and further investigate whether these extreme cases actually occur in reality and why.
