Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells
Date
2012-12
Journal Title
Journal ISSN
Volume Title
Publisher
Public Library of Science
Abstract
The present work exemplifies how parameter identifiability analysis can be used to gain insights into differences in
experimental systems and how uncertainty in parameter estimates can be handled. The case study, presented here,
investigates interferon-gamma (IFNc) induced STAT1 signalling in two cell types that play a key role in pancreatic cancer
development: pancreatic stellate and cancer cells. IFNc inhibits the growth for both types of cells and may be prototypic of
agents that simultaneously hit cancer and stroma cells. We combined time-course experiments with mathematical
modelling to focus on the common situation in which variations between profiles of experimental time series, from different
cell types, are observed. To understand how biochemical reactions are causing the observed variations, we performed a
parameter identifiability analysis. We successfully identified reactions that differ in pancreatic stellate cells and cancer cells,
by comparing confidence intervals of parameter value estimates and the variability of model trajectories. Our analysis shows
that useful information can also be obtained from nonidentifiable parameters. For the prediction of potential therapeutic
targets we studied the consequences of uncertainty in the values of identifiable and nonidentifiable parameters.
Interestingly, the sensitivity of model variables is robust against parameter variations and against differences between IFNc
induced STAT1 signalling in pancreatic stellate and cancer cells. This provides the basis for a prediction of therapeutic
targets that are valid for both cell types.
Description
CITATION: Rateitschak, K., et al. 2012. Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells. PLoS Computational Biology, 8(12): 1-14, doi: 10.1371/journal.pcbi.1002815.
The original publication is available at http://journals.plos.org/ploscompbiol
The original publication is available at http://journals.plos.org/ploscompbiol
Keywords
Interferon-gamma induced STAT1 signalling, Parameter estimation, Pancreas -- Cancer, Pancreatic stellate, Cancer cells
Citation
Rateitschak, K., et al. 2012. Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells. PLoS Computational Biology, 8(12): 1-14, doi: 10.1371/journal.pcbi.1002815