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Quantification of circulating endothelial and progenitor cells: comparison of quantitative PCR and four-channel flow cytometry
© Steurer et al; licensee BioMed Central Ltd. 2008
Received: 09 May 2008
Accepted: 28 August 2008
Published: 28 August 2008
Circulating endothelial cells (CEC) and endothelial precursor cells (CEP) have been suggested as markers for angiogenesis in cancer. However, CEC/CEP represent a tiny and heterogeneous cell population, rendering a standardized monitoring in peripheral blood difficult. Thus, we investigated whether a PCR-based detection method of CEC/CEP might overcome the limitations of rare-event flow cytometry.
To test the sensitivity of both assays endothelial colony forming cell clones (ECFC) and cord blood derived CD45- CD34+ progenitor cells were spiked into peripheral blood mononuclear cells (PBMNC) of healthy volunteers. Samples were analyzed for the expression of CD45, CD31, CD34, KDR or CD133 by 4-color flow cytometry and for the expression of CD34, CD133, KDR and CD144 by qPCR. Applying flow cytometry, spiked ECFC and progenitor cells were detectable at frequencies ≥ 0.01%, whereas by qPCR a detection limit of 0.001% was achievable. Furthermore, PBMNC from healthy controls (n = 30), patients with locally advanced rectal cancer (n = 20) and metastatic non-small cell lung cancer (NSCLC, n = 25) were analyzed. No increase of CEC/CEP was detectable by flow cytometry. Furthermore, only CD34 and KDR gene expression was significantly elevated in patients with metastatic NSCLC. However, both markers are not specific for endothelial cells.
QPCR is more sensitive, but less specific than 4-channel flow cytometry for the detection of CEC/CEP cell types. However, both methods failed to reliably detect an increase of CEC/CEP in tumor patients. Thus, more specific CEC/CEP markers are needed to validate and improve the detection of these rare cell types by PCR-based assays.
CEC a heterogenous and rare cell type of the peripheral blood
In this study both methods, flow cytometry and qPCR, were evaluated to compare the ability to detect mature peripheral blood-derived endothelial colony forming cells (ECFC; CEC phenotype) and cord blood-derived progenitors (CEP phenotype) spiked into PBMNC of healthy volunteers.
Phenotype analysis of cord blood progenitor cells and ECFC by flow cytometry
Detection of progenitors spiked into peripheral blood samples
Quantification of both CD34 and CD133 gene transcripts proved to be a reliable approach for detecting spiked progenitor cells in PBMNC samples with 10-fold greater sensitivity than flow cytometry. At a frequency of only 0.001% progenitor cells were detectable by a 3.9-fold increased gene expression for CD133 (SD 2.2) and a 3.4-fold increase for CD34 (SD 2.3) in comparison to unspiked controls (p = 0.03; figure 3B). Although linear, the increase of CD34 and CD133 gene transcripts was not proportional to the number of cells spiked, possibly due to technical reasons (e.g., cell clumping) or cell death as progenitor cells are more fragile compared to mature cells. Due to their low expression on progenitors as described above, CD144 and KDR gene expression was not analyzed.
Detection of ECFC spiked into peripheral blood samples
QPCR was at least 10-fold more sensitive than flow cytometry for ECFC detection. Indeed, at a frequency of 0.001% relative gene expression of KDR was increased 48.3-fold (SD 52.1; p = 0.027) and that of CD144 40.8-fold (SD 58.5; p = 0.04) compared to unspiked controls (figure 4B). Due to their low expression level on ECFC as described above, CD34 and CD133 gene transcripts were not determined in this setting.
Detection of CEC/CEP in peripheral blood of cancer patients and healthy volunteers
Recently, CEC and CEP have been suggested as surrogate markers for angiogenesis and response to antiangiogenic therapy in cancer . Flow cytometric rare event analysis, currently the most commonly applied method for CEC/CEP assessment, is technically demanding due to a high level of "background noise", i.e. false positive events due to autofluorescence, cell clumps and non-specific staining of other cell types such as monocytes, lymphocytes, non-lysed erythrocytes, aggregated platelets , dead cells or endothelial microparticles. Furthermore, technical aspects such as inadequate cleaning of the cytometer, blocking, washing and lysing procedures may impact the flow-cytometric analysis. Even with freshly drawn blood and standardized technical workup non-specific binding of fluorochrome-matched isotype controls may be observed in up to 0.5% of cells analyzed markedly exceeding the anticipated number of CEC and CEP within the PBMNC fraction (0.01% to 0.0001%) . As a result, CEC/CEP measurements are virtually not comparable between different laboratories posing a major obstacle for the interpretation of the data published in the literature.
The detection limit of 0.001% CEC/CEP in PBMNC determined for qPCR in our spiking experiments is compatible with frequencies of CEC/CEP in humans reported in the literature  and well above the values determined by 4-color flow cytometry (i.e., 0.01%).
However, despite markedly improved sensitivity determined in our spiking experiments we found normal endothelial marker gene expression when we applied qPCR to samples from patients with newly diagnosed locally advanced rectal cancer. This may be due to the rather low tumor burden in this study cohort as overall angiogenic activity depends not only on the tumor type but also on tumor load. When we analysed blood samples from patients with a high tumor burden, i.e., metastatic NSCLC, we found significantly elevated gene expression levels of CD34 and KDR which may indicate an elevated number of CEC. Importantly, these markers are not specific for endothelial cells and might as well reflect circulating hematopoietic progenitors due to tumor-associated inflammatory stimuli, metastatic cells or platelet contamination. This represents the major limitation of the qPCR methodology as applied in our study: gene transcript quantification is carried out on total RNA derived from PBMNC. Thus and in contrast to flow cytometry, qPCR does not allow to identify distinct cell types through simultaneous assessment of multiple markers on one cell and the detection of CD34 and KDR gene expression alone in PBMNC is by no means proof for CEC/CEP. But currently there are no specific CEC/CEP markers available, crucial for a valid molecular detection assay. Enrichment procedures (e.g., immunomagnetic beads for CD146) are currently being studied to improve CEC detection limits achievable with flow cytometry. However, it remains to be determined whether these labor-intensive techniques can provide the purity and cell numbers required for proper flow cytometric CEC enumeration.
In conclusion qPCR is more sensitive, but less specific than 4-channel flow cytometry for the detection of CEC/CEP. Nevertheless, both methods failed to reliably detect an increase of CEC/CEP in tumor patients. However, despite significant improved detection limits by qPCR a single marker expressed specifically in CEP/CEC is hitherto missing. Such a marker would be crucial to achieve high specificity and to discriminate these rare cells from other cell populations of the peripheral blood. Thus, transcriptome analysis of sorted and functionally tested CEC/CEP might lead to the discovery of novel markers that can be used in real-time PCR-based assays.
Acquisition of blood samples
No. of patients
Rectal cancer patients
UICC stage I
UICC stage II
UICC stage III
median age (years)
UICC stage IV
median age (years)
Isolation of progenitor cells from cord blood
Human umbilical cord blood samples (n = 10) were obtained at birth from full-term newborns. Blood samples were collected in heparinized tubes and stored at 8°C no longer than 12 h before flow cytometric analysis and mRNA extraction, respectively. MNC were isolated by Ficoll density gradient centrifugation (Lymphoprep®, Nycomed, Norway). Progenitor cells were enriched by a two step immunomagnetic bead separation protocol by negative selection for CD45 and subsequent positive selection for CD34+ (CD34 isolation kit, CD45 microbeads, Miltenyi Biotec). Progenitor cells were spiked into PBMNC of healthy volunteers at frequencies ranging from 0.001 to 1%.
Generation of endothelial colony forming cells (ECFC) from peripheral blood
Autologous ECFC cultures were generated as described previously [7, 13]. Briefly, PBMNC from five healthy donors were isolated by Ficoll density gradient centrifugation, resuspended in EGM-2 medium (Cambrex) and placed into a six-well-plate coated with type I collagen (from kangaroo, Sigma-Aldrich). After 24 h, non-adherent cells were removed by changing the medium. Autologous ECFC were spiked into PBMNC of the corresponding donor at frequencies ranging from 0.001 to 1%.
Flow cytometric detection and enumeration of of CEC/CEP was carried out according to a recently published protocol . Except for the anti-CD34 antibody monoclonal antibodies were chosen exactly as suggested by the authors. In brief, after Fc-blocking (Fc-receptor blocking antibody, Miltenyi Biotec) PBMNC were incubated in triplicates with antibodies specific for CD31-FITC (BD Pharmingen), CD34-PC7 (Beckman Coulter), CD45 PerCP (BD Pharmingen), CD133-PE (Miltenyi Biotec) or VEGF-R2 (KDR)-PE (R&D Systems). Appropriate fluorochrome-conjugated isotype-matched murine IgG antibodies (BD Pharmingen) were used as controls for each staining procedure. After incubation for 30 min at 4°C, cells were washed, resuspended in 300 mL PBS and analyzed in a Cytomics-FC-500 cytometer using the Cytomics RXP-Software (Beckman Coulter; figure 2). CEC were defined as CD31+/CD34+/CD45-/CD133- and CEP were defined as CD31+/CD34+/CD133+/CD45-/low cells. All experiments were carried out in triplicates with analysis of at least 5 × 105 cells per run.
Genes and primer sequences used for qPCR
Assay range cycles
For absolute quantification CD34, CD133, KDR and CD144 cDNAs were subcloned by the use of the PCR-Script cloning kit (Stratagene). Plasmid copies were calculated as follows: amount (copies/μL) = 6 × 1023 (copies/mol) × concentration (g/μL)/MW (g/mol). Standard curves were generated by logarithmic dilutions of triplicates of the amplicon-containing plasmids in a complex matrix of COS-7 cDNA. These external standard curves were used to calculate copy numbers per μg total RNA in all PBMNC samples using the iCycler software (BioRad).
Statistical analysis was performed with the GraphPad Prism 5 software for Windows. All tests of statistical significance were two-sided. Student's t-test was used for the analysis of spiking experiments. Kruskal Wallis H test was applied to study differences between healthy controls, rectal cancer patients and NSCLC patients.
This work was supported by the Fellinger Krebsforschungsverein (MS) and the Austrian Science Fund NFN-92 (GU, EG). The funding bodies had no role in study design, collection, analysis and interpretation of data, writing and submission of the manuscript.
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