TGF-beta stimulation in human and murine cells reveals commonly affected biological processes and pathways at transcription level

Khalid Abnaof*, Nikhil Mallela, Gudrun Walenda, Steffen K. Meurer, Kristin Sere, Qiong Lin, Hubertus Smeets, Kurt Hoffmann, Wolfgang Wagner, Martin Zenke, Ralf Weiskirchen, Holger Froehlich

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Background: The TGF-beta signaling pathway is a fundamental pathway in the living cell, which plays a key role in many central cellular processes. The complex and sometimes contradicting mechanisms by which TGF-beta yields phenotypic effects are not yet completely understood. In this study we investigated and compared the transcriptional response profile of TGF-beta 1 stimulation in different cell types. For this purpose, extensive experiments are performed and time-course microarray data are generated in human and mouse parenchymal liver cells, human mesenchymal stromal cells and mouse hematopoietic progenitor cells at different time points. We applied a panel of bioinformatics methods on our data to uncover common patterns in the dynamic gene expression response in respective cells. Results: Our analysis revealed a quite variable and multifaceted transcriptional response profile of TGF-beta 1 stimulation, which goes far beyond the well-characterized classical TGF-beta 1 signaling pathway. Nonetheless, we could identify several commonly affected processes and signaling pathways across cell types and species. In addition our analysis suggested an important role of the transcription factor EGR1, which appeared to have a conserved influence across cell-types and species. Validation via an independent dataset on A549 lung adenocarcinoma cells largely confirmed our findings. Network analysis suggested explanations, how TGF-beta 1 stimulation could lead to the observed effects. Conclusions: The analysis of dynamical transcriptional response to TGF-beta treatment experiments in different human and murine cell systems revealed commonly affected biological processes and pathways, which could be linked to TGF-beta 1 via network analysis. This helps to gain insights about TGF-beta pathway activities in these cell systems and its conserved interactions between the species and tissue types.
Original languageEnglish
Article number55
JournalBMC Systems Biology
Publication statusPublished - 15 May 2014


  • TGF-beta
  • Microarray
  • Time-course analysis
  • Gene set analysis
  • Clustering
  • Functional similarity


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