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Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data.
- Source :
-
Nature communications [Nat Commun] 2015 Sep 10; Vol. 6, pp. 8033. Date of Electronic Publication: 2015 Sep 10. - Publication Year :
- 2015
-
Abstract
- Mass spectrometry is widely used to probe the proteome and its modifications in an untargeted manner, with unrivalled coverage. Applied to phosphoproteomics, it has tremendous potential to interrogate phospho-signalling and its therapeutic implications. However, this task is complicated by issues of undersampling of the phosphoproteome and challenges stemming from its high-content but low-sample-throughput nature. Hence, methods using such data to reconstruct signalling networks have been limited to restricted data sets and insights (for example, groups of kinases likely to be active in a sample). We propose a new method to handle high-content discovery phosphoproteomics data on perturbation by putting it in the context of kinase/phosphatase-substrate knowledge, from which we derive and train logic models. We show, on a data set obtained through perturbations of cancer cells with small-molecule inhibitors, that this method can study the targets and effects of kinase inhibitors, and reconcile insights obtained from multiple data sets, a common issue with these data.
- Subjects :
- Chromatography, Liquid
Data Interpretation, Statistical
Humans
MCF-7 Cells
Models, Biological
Phosphorylation
Tandem Mass Spectrometry
Models, Statistical
Phosphoproteins metabolism
Phosphotransferases antagonists & inhibitors
Protein Kinase Inhibitors pharmacology
Proteomics methods
Signal Transduction
Subjects
Details
- Language :
- English
- ISSN :
- 2041-1723
- Volume :
- 6
- Database :
- MEDLINE
- Journal :
- Nature communications
- Publication Type :
- Academic Journal
- Accession number :
- 26354681
- Full Text :
- https://doi.org/10.1038/ncomms9033