Modelling the immune response to antigens is a complex endeavour that no single mathematical approach has so far been able to capture. In order to build quantitative models of immunotherapies, sophisticated new data and multi scale computational methods are required. To investigate T cell signal integration, new experiments will be performed at P1 and interrogated. The main objective is to develop mathematical and computational methods to explore T cell immunotherapies and T cell immunogenicity.
Modelling the immune response to antigens is a complex endeavour that no single mathematical approach has so far been able to capture. In order to build quantitative models of immunotherapies, sophisticated new data and multiscale computational methods are required.
To investigate T cell signal integration (as proposed for ESR15), new experiments will be performed at P1 and interrogated. To represent in silico the processes relevant for the regulated killing of tumour cells by T cells, as well as the effect of checkpoint inhibitors on CD8+ T cells (ESR12), and for CD8+ T cell infiltration into tumour environments depending on the inflammatory profile of the tumour (ESR13), available knowledge, assumptions and additional data from published literature will be integrated into computational models (based on ODEs, as well as stochastic compartmental birth, death and migration processes).
Computational models will describe signal integration by T cells, combinations and redundancy, the spatial dynamics of T cells trafficking from lymph nodes to tumours and the infiltration of T cells into the tumour. Molecular mechanisms, receptors and cytokines, will also be integrated to represent possible drug targets (ESR12, ESR13 and ESR15). Within the tumour environment, tumour growth and the regulation of T cell activity, including the inactivation of T cells by cancer cells, will also be represented.
ODE based, Boolean and stochastic models, depending on the data type, will be developed by ESR12, ESR13 and ESR15. These models will be analysed to identify the most relevant factors and processes for the T cell appearance at the tumour and the effect of inhibitory co-receptors on CD8+ T cells and drug re-inforced killing of cancer cells.
ESR14 will make use of ODEs, as well as stochastic processes to develop a multiscale (molecular, cellular and whole body) computational model of T cell responses to anti-cancer therapies. ESR14 will also carry out model selection and parameter inference with Bayesian methods and published data.