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      Constitutive activation of oncogenic PDGFRα-mutant proteins occurring in GIST patients induces receptor mislocalisation and alters PDGFRα signalling characteristics

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          Abstract

          Background

          Gastrointestinal stromal tumours (GIST) are mainly characterised by the presence of activating mutations in either of the two receptor tyrosine kinases c-KIT or platelet-derived growth factor receptor-α (PDGFRα). Most mechanistic studies dealing with GIST mutations have focused on c-KIT and far less is known about the signalling characteristics of the mutated PDGFRα proteins. Here, we study the signalling capacities and corresponding transcriptional responses of the different PDGFRα proteins under comparable genomic conditions.

          Results

          We demonstrate that the constitutive signalling via the oncogenic PDGFRα mutants favours a mislocalisation of the receptors and that this modifies the signalling characteristics of the mutated receptors. We show that signalling via the oncogenic PDGFRα mutants is not solely characterised by a constitutive activation of the conventional PDGFRα signalling pathways. In contrast to wild-type PDGFRα signal transduction, the activation of STAT factors (STAT1, STAT3 and STAT5) is an integral part of signalling mediated via mutated PDGF-receptors. Furthermore, this unconventional STAT activation by mutated PDGFRα is already initiated in the endoplasmic reticulum whereas the conventional signalling pathways rather require cell surface expression of the receptor. Finally, we demonstrate that the activation of STAT factors also translates into a biologic response as highlighted by the induction of STAT target genes.

          Conclusion

          We show that the overall oncogenic response is the result of different signatures emanating from different cellular compartments. Furthermore, STAT mediated responses are an integral part of mutated PDGFRα signalling.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12964-015-0096-8) contains supplementary material, which is available to authorized users.

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          Most cited references53

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            PDGFRA activating mutations in gastrointestinal stromal tumors.

            Most gastrointestinal stromal tumors (GISTs) have activating mutations in the KIT receptor tyrosine kinase, and most patients with GISTs respond well to Gleevec, which inhibits KIT kinase activity. Here we show that approximately 35% (14 of 40) of GISTs lacking KIT mutations have intragenic activation mutations in the related receptor tyrosine kinase, platelet-derived growth factor receptor alpha (PDGFRA). Tumors expressing KIT or PDGFRA oncoproteins were indistinguishable with respect to activation of downstream signaling intermediates and cytogenetic changes associated with tumor progression. Thus, KIT and PDGFRA mutations appear to be alternative and mutually exclusive oncogenic mechanisms in GISTs.
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              Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures

              Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We present a threshold-free algorithm called Rank–rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expression profiles. To demonstrate RRHO sensitivity and dynamic range, we identified shared expression networks in cancer microarray profiles driving tumor progression, stem cell properties and response to targeted kinase inhibition. We demonstrate how RRHO can be used to determine which model system or drug treatment best reflects a particular biological or disease response. The threshold-free and graphical aspects of RRHO complement other rank-based approaches such as Gene Set Enrichment Analysis (GSEA), for which RRHO is a 2D analog. Rank–rank overlap analysis is a sensitive, robust and web-accessible method for detecting and visualizing overlap trends between two complete, continuous gene-expression profiles. A web-based implementation of RRHO can be accessed at http://systems.crump.ucla.edu/rankrank/ .
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                Author and article information

                Contributors
                christelle.bahlawane@uni.lu
                r_eule@gmx.de
                monique.wiesinger@uni.lu
                jiali.wang@uni.lu
                Arnaud.Muller@lih.lu
                andreas.girod@uni.lu
                Petr.Nazarov@lih.lu
                Kathrin.Felsch@gmx.de
                Laurent.Vallar@lih.lu
                thomas.sauter@uni.lu
                venkata.satagopam@uni.lu
                serge.haan@uni.lu
                Journal
                Cell Commun Signal
                Cell Commun. Signal
                Cell Communication and Signaling : CCS
                BioMed Central (London )
                1478-811X
                31 March 2015
                31 March 2015
                2015
                : 13
                : 21
                Affiliations
                [ ]Molecular Disease Mechanisms Group, Life Sciences Research Unit, University of Luxembourg, 162A Avenue de la Faïencerie, L-1511 Luxembourg, Luxembourg
                [ ]Signal Transduction Group, Life Sciences Research Unit, University of Luxembourg, 162A Avenue de la Faïencerie, L-1511 Luxembourg, Luxembourg
                [ ]Systems Biology Group, Life Sciences Research Unit, University of Luxembourg, 162A Avenue de la Faïencerie, L-1511 Luxembourg, Luxembourg
                [ ]Genomics Research Unit, Luxembourg Institute of Health, 84 Val Fleuri, L-1526 Luxembourg, Luxembourg
                [ ]Light Microscopy Facility, Life Sciences Research Unit, University of Luxembourg, 162a Avenue de la Faïencerie, L-1511 Luxembourg, Luxembourg
                [ ]Deparment of Biochemistry, RWTH-Aachen University, Pauwelsstr. 30, D-52074 Aachen, Germany
                [ ]Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7 Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg
                Article
                96
                10.1186/s12964-015-0096-8
                4396151
                25880691
                3394e472-b4e7-4dbb-b972-14f125dcc220
                © Bahlawane et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 October 2014
                : 5 March 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Cell biology
                pdgfrα,gastrointestinal stromal tumour,gist,stat,akt,mapk
                Cell biology
                pdgfrα, gastrointestinal stromal tumour, gist, stat, akt, mapk

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