These authors contributed equally.
Predictive mathematical models of cancer signalling pathways
Article first published online: 17 JAN 2012
© 2011 The Association for the Publication of the Journal of Internal Medicine
Journal of Internal Medicine
Volume 271, Issue 2, pages 155–165, February 2012
How to Cite
Bachmann, J., Raue, A., Schilling, M., Becker, V., Timmer, J. and Klingmüller, U. (2012), Predictive mathematical models of cancer signalling pathways. Journal of Internal Medicine, 271: 155–165. doi: 10.1111/j.1365-2796.2011.02492.x
- Issue published online: 17 JAN 2012
- Article first published online: 17 JAN 2012
- Accepted manuscript online: 5 DEC 2011 11:54AM EST
- cell biology;
- lung cancer
Abstract. Bachmann J, Raue A, Schilling M, Becker V, Timmer J, Klingmüller U (German Cancer Research Center, Heidelberg; BIOSS Centre for Biological Signalling Studies, Freiburg; and University of Freiburg, Freiburg; Germany). Predictive mathematical models of cancer signalling pathways (Key Symposium). J Intern Med 2012; 271:155–165.
Complex intracellular signalling networks integrate extracellular signals and convert them into cellular responses. In cancer cells, the tightly regulated and fine-tuned dynamics of information processing in signalling networks is altered, leading to uncontrolled cell proliferation, survival and migration. Systems biology combines mathematical modelling with comprehensive, quantitative, time-resolved data and is most advanced in addressing dynamic properties of intracellular signalling networks. Here, we introduce different modelling approaches and their application to medical systems biology, focusing on the identifiability of parameters in ordinary differential equation models and their importance in network modelling to predict cellular decisions. Two related examples are given, which include processing of ligand-encoded information and dual feedback regulation in erythropoietin (Epo) receptor signalling. Finally, we review the current understanding of how systems biology could foster the development of new treatment strategies in the context of lung cancer and anaemia.