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dc.contributor.authorChoudhary, Kumari Sonal
dc.contributor.authorRohatgi, Neha
dc.contributor.authorHalldorsson, Skarphedinn
dc.contributor.authorBriem, Eirikur
dc.contributor.authorGudjonsson, Thorarinn
dc.contributor.authorGudmundsson, Steinn
dc.contributor.authorRolfsson, Ottar
dc.date.accessioned2016-08-15T15:50:54Z
dc.date.available2016-08-15T15:50:54Z
dc.date.issued2016-06
dc.date.submitted2016
dc.identifier.citationEGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT. 2016, 12 (6):e1004924 PLoS Comput. Biol.en
dc.identifier.issn1553-7358
dc.identifier.pmid27253373
dc.identifier.doi10.1371/journal.pcbi.1004924
dc.identifier.urihttp://hdl.handle.net/2336/618382
dc.descriptionTo access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.en
dc.description.abstractEpithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.
dc.description.sponsorshipIcelandic Research Fund (RANNIS) 130591-051 152358-051 152369-051en
dc.language.isoenen
dc.publisherPublic Library Scienceen
dc.relation.urlhttp://dx.doi.org/ 10.1371/journal.pcbi.1004924en
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4890760/en
dc.rightsArchived with thanks to PLoS computational biologyen
dc.subjectNAF12
dc.subject.meshEpithelial-Mesenchymal Transitionen
dc.subject.meshNeoplasm Metastasisen
dc.subject.meshReceptor, Epidermal Growth Factoren
dc.titleEGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.en
dc.typeArticleen
dc.contributor.department[ 1 ] Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland [ 2 ] Univ Iceland, Biomed Ctr, Reykjavik, Iceland [ 3 ] Univ Iceland, Sch Hlth Sci, Dept Anat, Stem Cell Res Unit, Reykjavik, Iceland [ 4 ] Landspitali Univ Hosp, Dept Lab Hematol, Reykjavik, Iceland,   Landspitali National University Hospitalen
dc.identifier.journalPLoS computational biologyen
dc.rights.accessOpen Accessen
refterms.dateFOA2018-09-12T16:07:29Z
html.description.abstractEpithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.


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