Article (Scientific journals)
A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GIST.
Trairatphisan, Panuwat; Wiesinger, Monique; Bahlawane, Christelle et al.
2016In PLoS ONE, 11 (5), p. 0156223
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Abstract :
[en] BACKGROUND: Signal transduction networks are increasingly studied with mathematical modelling approaches while each of them is suited for a particular problem. For the contextualisation and analysis of signalling networks with steady-state protein data, we identified probabilistic Boolean network (PBN) as a promising framework which could capture quantitative changes of molecular changes at steady-state with a minimal parameterisation. RESULTS AND CONCLUSION: In our case study, we successfully applied the PBN approach to model and analyse the deregulated Platelet-Derived Growth Factor (PDGF) signalling pathway in Gastrointestinal Stromal Tumour (GIST). We experimentally determined a rich and accurate dataset of steady-state profiles of selected downstream kinases of PDGF-receptor-alpha mutants in combination with inhibitor treatments. Applying the tool optPBN, we fitted a literature-derived candidate network model to the training dataset consisting of single perturbation conditions. Model analysis suggested several important crosstalk interactions. The validity of these predictions was further investigated experimentally pointing to relevant ongoing crosstalk from PI3K to MAPK signalling in tumour cells. The refined model was evaluated with a validation dataset comprising multiple perturbation conditions. The model thereby showed excellent performance allowing to quantitatively predict the combinatorial responses from the individual treatment results in this cancer setting. The established optPBN pipeline is also widely applicable to gain a better understanding of other signalling networks at steady-state in a context-specific fashion.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Trairatphisan, Panuwat ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Wiesinger, Monique ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Bahlawane, Christelle ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Haan, Serge ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Sauter, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
External co-authors :
no
Language :
English
Title :
A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GIST.
Publication date :
2016
Journal title :
PLoS ONE
ISSN :
1932-6203
Publisher :
Public Library of Science, United States - California
Volume :
11
Issue :
5
Pages :
e0156223
Peer reviewed :
Peer Reviewed verified by ORBi
FnR Project :
FNR1233900 - A Systems Biology To Pdgf Signaling, 2011 (01/10/2011-30/09/2015) - Panuwat Trairatphisan
Name of the research project :
R-AGR-0085 - IRP11 - PDGFR-KIT (20110101-20141231) - HAAN Serge
Funders :
University of Luxembourg - UL
Available on ORBilu :
since 01 June 2016

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