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Integration of proteomic and transcriptomic profiles identifies a novel PDGF-MYC network in human smooth muscle cells

Title
Integration of proteomic and transcriptomic profiles identifies a novel PDGF-MYC network in human smooth muscle cells
Authors
Yang, W[Yang, Wei]Ramachandran, A[Ramachandran, Aruna]You, S[You, Sungyong]Jeong, H[Jeong, HyoBin]Morley, S[Morley, Samantha]Mulone, MD[Mulone, Michelle D.]Logvinenko, T[Logvinenko, Tanya]Kim, J[Kim, Jayoung]Hwang, D[Hwang, Daehee]Freeman, MR[Freeman, Michael R.]Adam, RM[Adam, Rosalyn M.]
DGIST Authors
Hwang, D[Hwang, Daehee]
Issue Date
2014-08-01
Citation
Cell Communication and Signaling, 12
Type
Article
Article Type
Article
Keywords
Adaptor Proteins, Signal TransducingAnimal ExperimentAnimal ModelBladderBladder InjuryBladder MuscleCell CultureCell MigrationCell MotionCell MovementCell ProliferationCell SurvivalCells, CulturedCytologyDIAPH3DIAPH3 Protein, HumanDiaphanous Related Formin 3Drug EffectsEarly Growth Response Factor 1FemaleGene ExpressionGene Expression ProfilingGene TargetingGeneticsHumanHuman CellHumansIn Vitro StudyIn Vivo StudyLamellipodiumMessenger RNAMetabolismMouseMyc ProteinMyocytes, Smooth MuscleNetwork AnalysisNon-HumanPDGFPhysiologyPlatelet-Derived Growth FactorProtein C JunProtein DatabaseProtein ExpressionProtein Interaction MapsProtein MybProtein Protein InteractionProteomeXchange PXD000624ProteomicsProto-Oncogene Proteins C-JUNProto-Oncogene Proteins C-MYCRegulator ProteinSignal Transducing Adaptor ProteinSmooth Muscle FiberTranscription Factor AP-1Transcription Factor RUNX1TranscriptomicsUnclassified DrugUpregulationUrinary BladderVisceral Smooth Muscle
ISSN
1478-811X
Abstract
Background: Platelet-derived growth factor-BB (PDGF-BB) has been implicated in the proliferation, migration and synthetic activities of smooth muscle cells that characterize physiologic and pathologic tissue remodeling in hollow organs. However, neither the molecular basis of PDGFR-regulated signaling webs, nor the extent to which specific components within these networks could be exploited for therapeutic benefit has been fully elucidated. Results: Expression profiling and quantitative proteomics analysis of PDGF-treated primary human bladder smooth muscle cells identified 1,695 genes and 241 proteins as differentially expressed versus non-treated cells. Analysis of gene expression data revealed MYC, JUN, EGR1, MYB, RUNX1, as the transcription factors most significantly networked with up-regulated genes. Forty targets were significantly altered at both the mRNA and protein levels. Proliferation, migration and angiogenesis were the biological processes most significantly associated with this signature, and MYC was the most highly networked master regulator. Alterations in master regulators and gene targets were validated in PDGF-stimulated smooth muscle cells in vitro and in a model of bladder injury in vivo. Pharmacologic inhibition of MYC and JUN confirmed their role in SMC proliferation and migration. Network analysis identified the diaphanous-related formin 3 as a novel PDGF target regulated by MYC and JUN, which was necessary for PDGF-stimulated lamellipodium formation. Conclusions: These findings provide the first systems-level analysis of the PDGF-regulated transcriptome and proteome in normal smooth muscle cells. The analyses revealed an extensive cohort of PDGF-dependent biological processes and connected key transcriptional effectors to their regulation, significantly expanding current knowledge of PDGF-stimulated signaling cascades. These observations also implicate MYC as a novel target for pharmacological intervention in fibroproliferative expansion of smooth muscle, and potentially in cancers in which PDGFR-dependent signaling or MYC activation promote tumor progression. © 2014 Yang et al.; licensee BioMed Central Ltd.
URI
http://hdl.handle.net/20.500.11750/3058
DOI
10.1186/s12964-014-0044-z
Publisher
BioMed Central Ltd.
Related Researcher
  • Author Hwang, Dae Hee Systems Biology and Medicine Lab
  • Research Interests Multilayered spatiotemporal networks; Regulatory motifs or pathways; Metabolite-protein networks; Network stochasticity; Proteomics and informatics
Files:
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Collection:
New BiologyETC1. Journal Articles


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