Nonlinear dynamics of biochemical networks in pancreatic cancer: From experimental data to mathematical models (FORSYS)

Nonlinear dynamics of biochemical networks in pancreatic cancer: From experimental data to mathematical models (FORSYS)

This project combines theoretical and experimental systems biology to challenge pancreatic cancer (PC), a tumour disease with a very poor prognosis. It is focused on mathematical modelling of chemical kinetics and transport processes in biochemical reaction networks of PC cells. The model properties are analysed with methods of dynamical systems theory and methods of experimental design to understand, predict and improve the cellular response to chemotherapy. This effort is supported by quantitative cell biology, and the development of experimental techniques for systems biology.

The progression of pancreatic cancer is accelerated by an extended fibrosis which has been linked to the activation of pancreatic stellate cells. Therefore therapies will be particularly effective if they simultaneously hit carcinoma and stroma cells. Candidates include interferons and inhibitors of the Ras-Raf-ERK pathway whose effects on the molecular level are poorly understood so far.

The mathematical modelling of multiple signalling pathways in two interacting cell types allows a systematic investigation of their dynamics and of their effects on cellular properties. The modelling of signal transduction in PC is accomplished by the development of mathematical tools to efficiently analyze the established hierarchy of models: Moving from a single signalling pathway to interacting multiple signalling pathways and moving from a single cell type to two interacting cell types requires new mathematical approaches to analyze the increasing complexity. Special attention is paid to properties of transient signalling and quantitative methods to improve the experimental design.

Workpackages and workflow of the project


First results: IFNγ stimulated Stat1 signalling pathway