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Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells

dc.contributor.authorRateitschak, Katjaen_ZA
dc.contributor.authorWinter, Felixen_ZA
dc.contributor.authorLange, Falkoen_ZA
dc.contributor.authorJaster, Roberten_ZA
dc.contributor.authorWolkenhauer, Olafen_ZA
dc.date.accessioned2013-02-23T12:42:05Z
dc.date.available2013-02-23T12:42:05Z
dc.date.issued2012-12
dc.identifier.citationRateitschak, 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
dc.identifier.issn1553-7358 (online)
dc.identifier.issn1553-734X (print)
dc.identifier.otherdoi: 10.1371/journal.pcbi.1002815
dc.identifier.urihttp://hdl.handle.net/10019.1/79602
dc.descriptionCITATION: 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.
dc.descriptionThe original publication is available at http://journals.plos.org/ploscompbiol
dc.description.abstractThe 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.en_ZA
dc.description.sponsorshipFinancial support: Bundesministerium für Bildung und Forschung through the FORSYS partner program (grant number 0315255 to KR); Deutsche Forschunggemeinschaft (to RJ); Interdisciplinary Faculty of the University of Rostock: Grant to FW; Helmholtz Society: Support to OW.en_ZA
dc.format.extent14 pages
dc.language.isoen_ZAen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.subjectInterferon-gamma induced STAT1 signallingen_ZA
dc.subjectParameter estimationen_ZA
dc.subjectPancreas -- Canceren_ZA
dc.subjectPancreatic stellateen_ZA
dc.subjectCancer cellsen_ZA
dc.titleParameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cellsen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's versionen_ZA
dc.rights.holderAuthors retain copyrighten_ZA


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