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. 2013;16(1):15-24.
doi: 10.3727/105221613x13776146743307.

Differential expression of distinct surface markers in early endothelial progenitor cells and monocyte-derived macrophages

Affiliations

Differential expression of distinct surface markers in early endothelial progenitor cells and monocyte-derived macrophages

Shu-Meng Cheng et al. Gene Expr. 2013.

Abstract

Bone marrow-derived endothelial progenitor cells (EPCs) play a fundamental role in postnatal angiogenesis. Currently, EPCs are defined as early and late EPCs based on their biological properties and their time of appearance during in vitro culture. Reports have shown that early EPCs share common properties and surface markers with adherent blood cells, especially CD14+ monocytes. Distinguishing early EPCs from circulating monocytes or monocyte-derived macrophages (MDMs) is therefore crucial to obtaining pure endothelial populations before they can be applied as part of clinical therapies. We compared the gene expression profiles of early EPCs, blood cells (including peripheral blood mononuclear cells, monocytes, and MDMs), and various endothelial lineage cells (including mature endothelial cells, late EPCs, and CD133+ stem cells). We found that early EPCs expressed an mRNA profile that showed the greatest similarity to MDMs than any other cell type tested. The functional significance of this molecular profiling data was explored by Gene Ontology database search. Novel plasma membrane genes that might potentially be novel isolation biomarkers were also pinpointed. Specifically, expression of CLEC5A was high in MDMs, whereas early EPCs expressed abundant SIGLEC8 and KCNE1. These detailed mRNA expression profiles and the identified functional modules will help to develop novel cell isolation approaches that will allow EPCs to be purified; these can then be used to target cardiovascular disease, tumor angiogenesis, and various ischemia-related diseases.

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Conflict of interest statement

The authors declare no conflicts of interests.

Figures

Figure 1
Figure 1
Cultivation and characterization of early and late EPCs. (A) Cord blood MNCs were isolated and plated on fibronectin-coated culture dishes for 4 days. Adherent eEPCs are shown in the left panel. Twenty-one days after plating, late EPCs with a cobblestone-like morphology were selected, reseeded, and grown to confluence (right). (B) Both early and late EPCs endocytose DiI-acLDL (acetylated low density lipoprotein; red) and bind fluorescein isothiocyanate UEA-1 (lectin) (green). Cells were counterstained with Hoechst 33258 to show the nucleus (blue). (C, D) Expression of indicated progenitor, endothelial, and hematopoietic markers in early (C) and late (D) EPCs by flow cytometric analysis.
Figure 2
Figure 2
Similar yet distinct gene expression patterns between eEPCs and MDMs. (A) A PCA plot using genes differentially expressed between CD133+ stem cells and mature endothelial cells (8,880 probe sets, q < 10−4). LEC, lymphatic endothelial cell; BEC, blood vessel endothelial cell; CD133, CD133+ stem cells; CD34, CD34+ progenitor cells. (B) Transcriptome distance analysis for eEPCs and various blood cell or endothelial cell types. Average linkage distances between transcriptomes were calculated as described using the aforementioned 8,880 probe sets. Mo, monocyte.
Figure 3
Figure 3
Genes unique in eEPCs and MDMs. (A) Heat map showing differentially expressed genes in eEPCs or MDMs. Columns represent human tissue and stem cell samples, and rows represent probe sets. Genes in red: increased expression; in blue: decreased expression. Genes picked for RT-qPCR in (B) (underlined) and Figure 4 (underlined and in bold) are also shown. (B) Validation of array data by RT-qPCR. Mean gene expression levels of eEPC proteins (compared to GAPDH control) are shown. Results are expressed as the mean ± SD.
Figure 4
Figure 4
Cell membrane proteins specifically expressed in eEPCs or MDMs. These four genes were selected according to the “Cellular Component” ontology in the GO database. Mean gene expression levels of eEPC proteins (compared to GAPDH control) by RT-qPCR are shown. Results are expressed as the mean ± SD.

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