title: Surfing the data tsunami, a bioinformatic dissection of the proangiogenic monocyte.
abstract: In this review we compare expression studies on monocyte subsets as an example to show the integrated possibilities of molecular databases and bioinformatic analysis tools. Monocytes have been recognized as cells with great plasticity and differentiation potential that play a pivotal role in revascularization processes, i.e. angiogenesis and arteriogenesis. To gain more insight in the relevant developmental programs, we compared the full-genome mRNA expression profiles of several distinct human monocyte subpopulations previously identified based on surface marker expression. These included classical and non-classical, M1 and M2 macrophages, circulating angiogenic cells (CAC), and non-monocyte-derived endothelial colony-forming cells (ECFC). Their transcriptional profiles revealed distinct and overlapping gene expression signatures and pathways reminiscent of utilization of transcription factors driving polarization into the different monocytic phenotypes. Hierarchical cluster analysis revealed that CAC are most related to M2 macrophages and unstimulated macrophages, and to a lesser extent to classical monocytes, and are quite distinct from M1 macrophages and ECFC. Analysis of the promoter region of CAC-expressed genes suggests that in particular the ETS family of transcription factors is important in CAC development. These analyses show the power of combining multiple datasets with existing databases on biological knowledge, to interpret full genome expression data.
authors.affiliation: Department of Molecular Cell Biology and Immunology, VU University Medical Center, 1081BT Amsterdam, The Netherlands.
authors.forename: T C T M
authors.initials: TC
authors.lastname: van der Pouw Kraan
authors.forename: A M
authors.initials: AM
authors.lastname: van der Laan
authors.forename: J J
authors.initials: JJ
authors.lastname: Piek
authors.forename: A J G
authors.initials: AJ
authors.lastname: Horrevoets
mesh_terms: D002454:Cell Differentiation; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000502:physiology; D015894:Genome, Human; D006801:Humans; D008264:Macrophages / Q000378:metabolism; D009000:Monocytes / Q000378:metabolism*; D018919:Neovascularization, Physiologic / Q000502:physiology*