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Proteomics. 2004 Apr;4(4):1014-28.

A combination of proteomics, principal component analysis and transcriptomics is a powerful tool for the identification of biomarkers for macrophage maturation in the U937 cell line.

Author information

1
TNO Pharma, Zeist, The Netherlands. Verhoeckx@pharma.tno.nl

Abstract

The monocyte-like human histiocytic lymphoma cell line U937 can be induced by phorbol 12-myristate 13-acetate (PMA) to undergo differentiation into a macrophage-like phenotype. We have used two-dimensional gel electrophoresis (2-DE), oligonucleotide microarrays and principal component analysis (PCA) to characterize the U937 cell line as a model system for the differentiation of monocytes into macrophages. A total of 226 differentially expressed proteins were found, of which 41 were selected by PCA for identification using matrix-assisted laser desorption/ionization tandem mass spectrometry. Based on the PCA results, three marker proteins were selected for confirmation of differential expression using Western blot and quantitative real time-PCR. The selected marker proteins were: gamma interferon inducible lysosomal thiol reductase, cathepsin D and adipocyte-fatty acid binding protein. All three proved to be good differentiation markers for macrophage maturation of U937 cells as well as peripheral blood-derived macrophages. The transcriptomics data revealed a large number of additional putative differentiation markers in U937 macrophages, many of which are known to be expressed in peripheral blood-derived macrophages. These include osteospontin, matrix metalloproteinase 9, and HC-gp39. Our results show that the characteristics of U937 macrophages resemble those of inflammatory (exudate) macrophages, exemplified by the down-regulation of 5' nucleotidase and the up-regulation of leucine aminopeptidase mRNAs. In conclusion, using the powerful combination of transcriptomics, 2-DE and PCA, our results show that U937 cells differentiated by PMA treatment are an excellent model system for monocyte derived macrophage generation from blood.

PMID:
15048983
DOI:
10.1002/pmic.200300669
[Indexed for MEDLINE]

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