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Clinical Cancer Research 13, 76-80, January 1, 2007. doi: 10.1158/1078-0432.CCR-06-1324
© 2007 American Association for Cancer Research
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Human Cancer Biology

Determination of Microvessel Density by Quantitative Real-time PCR in Esophageal Cancer: Correlation with Histologic Methods, Angiogenic Growth Factor Expression, and Lymph Node Metastasis

Sonja Loges1, Henning Clausen1, Uta Reichelt2, Michael Bubenheim3, Andreas Erbersdobler2, Paulus Schurr4, Emre Yekebas4, Gunter Schuch4, Jakob Izbicki4, Klaus Pantel5, Carsten Bokemeyer1 and Walter Fiedler1

Authors' Affiliations: Departments of 1 Internal Medicine II, 2 Pathology, 3 Medical Informatics, and 4 General, Visceral, and Thoracic Surgery, and 5 Institute of Tumor Biology, University Hospital Hamburg-Eppendorf, Hamburg, Germany

Requests for reprints: Walter Fiedler, Department of Medicine II, University Hospital Hamburg-Eppendorf, 20246 Hamburg, Germany. Phone: 49-40-42803-3919; Fax: 49-40-42803-4600; E-mail: fiedler{at}uke.uni-hamburg.de.


   Abstract
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 Abstract
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Purpose: Angiogenesis and lymphangiogenesis are important steps in tumor growth and dissemination and are of prognostic importance in solid tumors. The determination of microvessel density (MVD) by immunohistology is subject to considerable variability between different laboratories and observers. We compared MVD determination by immunohistology and quantitative real-time PCR and correlated the results with clinical variables.

Experimental Design: The expression of endothelial antigens vascular endothelial cadherin (CD144), P1H12 (CD146), tie-2, and VEGFR-2, and lymphatic endothelial markers VEGFR-3, Prox, and LYVE was assessed by quantitative PCR (qPCR) in primary surgical samples. The expression of angiogenetic growth factors VEGF-A, VEGF-C, VEGF-D, angiopoietin-1, and angiopoietin-2 was quantified by PCR and correlated with MVD and clinical variables.

Results: The expression of endothelial antigens vascular endothelial cadherin (CD144), P1H12 (CD146), tie-2, and VEGFR-2 correlated with each other in 54 samples of primary esophageal cancer (P < 0.0001 for all comparisons). MVD determined immunohistologically by CD31 staining in a subgroup of 35 patients correlated significantly with the qPCR method. The expression of angiogenetic growth factors VEGF-A, VEGF-C, VEGF-D, angiopoietin-1, and angiopoietin-2 was significantly associated with MVD (P < 0.0001 for all comparisons). Analysis of the expression of lymphendothelial markers VEGFR-3, Prox, and LYVE revealed concordant results, indicating that quantification of lymphendothelial cells is possible by qPCR. The presence of lymph node metastasis on surgical specimens was significantly correlated with MVD (P < 0.003), VEGFR-2 (P < 0.048), and VEGF-C (P < 0.042) expression.

Conclusions: These results indicate that quantification of MVD by qPCR in surgical samples of esophageal carcinoma yields similar results with immunohistology. Interestingly, the extent of angiogenesis and lymphangiogenesis was not related in individual tumor samples. Lymph node metastases could be predicted by MVD and VEGF-C expression.

The formation of new blood vessels (angiogenesis) and lymph vessels (lymphangiogenesis) significantly contribute to malignant growth and metastasis of solid tumors (1–3).

Angiogenesis and lymphangiogenesis are mediated by distinct cytokines and their receptors. The best characterized and most specific cytokines are the vascular endothelial growth factors (VEGF-A, -B, -C, -D, and -E) and their receptors (VEGFR-1, -2, and -3; refs. 4, 5). Another major class of angiogenesis inducers is the angiopoietin cytokine and receptor family consisting of angiopoietin-1 (Ang1), angiopoietin-2 (Ang2), and their receptor Tie2 (6, 7).

VEGF-A binds to VEGFR-2 which is expressed on vascular endothelial cells and is believed to be the main inducer of angiogenesis (6, 7). VEGF-C and VEGF-D are ligands of VEGFR-2 and VEGFR-3. VEGF-C and VEGF-D play an essential role in lymphangiogenesis as VEGFR-3 is expressed mainly on lymphatic endothelial cells (8, 9).

Vascular endothelial cells are characterized by the expression of several cell surface markers such as adhesion molecule vascular endothelial cadherin (VE-cadherin, CD144) and by P1H12 (CD146; ref. 10). Lymphatic endothelial cells are distinct from vascular endothelial cells. Specific cell surface markers for lymphatic endothelial cells are VEGFR-3 and the hyaluronic acid receptor LYVE (11).

The assessment of angiogenesis and lymphangiogenesis has emerged as a potentially useful prognostic and predictive factor in human malignancies. Analysis of microvessel density (MVD) in solid tumors is done by staining for endothelial cell surface molecules such as CD31 using immunohistochemistry. This approach has revealed a relationship between MVD in the primary tumor specimen and the prognosis of different solid tumors including prostate, colon, esophagus, and breast cancers (12). Despite the fact that the majority of studies have identified MVD as an independent prognostic factor, other studies have questioned these findings. This discrepancy may be due to a lack of standardized immunohistochemical techniques, the wide range of antibodies employed, different antigen retrieval methods, nonstandardized cutoff points, and due to interobserver variability (13). Therefore, it is necessary to develop more robust, standardized techniques to measure angiogenesis in tumor samples.

To address this issue, we did quantitative PCR (qPCR) analyses of several angiogenic and lymphangiogenic markers (VEGFR-2, VEGFR-3, VE-cadherin, P1H12, Tie2, and LYVE) in primary esophageal carcinoma tissue from 54 patients undergoing operative resection. Furthermore, we quantified gene expression of angiogenic growth factors VEGF-A, VEGF-C, VEGF-D, Ang1, and Ang2. Additionally, we quantified MVD immunohistochemically with CD31 staining. We correlated qPCR data with immunohistochemistry and clinical variables.


   Materials and Methods
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 Abstract
 Materials and Methods
Results
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Isolation of RNA and synthesis of cDNA. Total cellular RNA was isolated from cryosections of tumor tissue that was shock-frozen and stored in liquid nitrogen immediately after resection. Cryosections corresponding to ~0.5 mg of tissue were stored in RNAlater (Qiagen, Hilden, Germany) prior to RNA isolation. Before RNA isolation, the percentage of tumor infiltration was determined on parallel cryosections by a pathologist. Tumor tissue was homogenized using Qiashredder columns (Qiagen) according to the manufacturer's instructions. Total cellular RNA was isolated with RNeasy (Qiagen) as described by the manufacturer. For cDNA synthesis, 3 µg of RNA was immediately used with the You Prime cDNA synthesis kit (Pharmacia, Uppsala, Sweden) and random primers (Invitrogen, Carlsbad, CA). CDNA was stored at –20°C.

Primers for qPCR. All primers were designed with the Primer3 software (14). The PCR product of the glycerinaldehyde-3-phosphate dehydrogenase (GAPDH) spanned intron H of the GAPDH gene; thus, the larger genomic fragment could be detected by melting curve analysis. Contamination with genomic DNA was not detected in any of the analyzed samples.

Quantitative real-time PCR. Real time-PCR was carried out on LightCycler (Roche, Basel, Switzerland) using the FAST Start DNAMaster SYBR Green kit (Roche). The relative amount of expressed cDNA was calculated from a relative standard curve obtained by using log dilutions of plasmids containing the gene of interest. Plasmids were constructed by cloning the amplification products into the pCRII Vector using the TA-Cloning kit (Invitrogen). All recombinant DNA work was done in a S1 facility after approval according to German law.

The results of two independent analyses for each gene and sample or plasmid dilution were averaged. The calculated amount of the target genes was normalized to the endogenous reference control gene GAPDH. All data are presented as the ratio of the target gene/GAPDH. Primer sequences are provided in Table 1 . PCR conditions are available upon request.


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  		Table 1. Primer sequences

 
Dilution of endothelial cells in peripheral blood mononuclear cells to validate qPCR. Peripheral blood mononuclear cells from healthy donors were isolated using Ficoll-Hypaque (Pharmacia) density gradient centrifugation. Human umbilical vein endothelial cells were cultured in EGM-2 medium as described by the manufacturer (Cambrex, Walkersville, MD). Human umbilical vein endothelial cells were diluted 1:10,000, 1:1,000, 1:100, and 1:10 in peripheral blood mononuclear cells. Pure peripheral blood mononuclear cells were used as negative controls. RNA isolation and cDNA synthesis were done as described above. cDNA was stored at –20°C.

Assessment of MVD. Immunohistochemistry was done on representative paraffin sections using the alkaline phosphatase anti–alkaline phosphatase technique with the primary antibody anti-CD31 (clone JC/70A; BioGenex, San Ramon, CA) at a dilution of 1:15. The immunohistochemical protocol had been established in previous experiments and included pretreatment of sections in a microwave oven at 750 W for 10 min, immersed in 10 mmol/L of citric acid monohydrate (pH 6).

MVD was scored by a single investigator blinded for the results of the other experiments. Microvessels marked with anti-CD31 were counted in four adjacent high-power fields (Axioskop, Zeiss, Jena, Germany) within highly vascular tumor areas ("hot-spots") according to a modified method described by Weidner et al. (15). MVD was then calculated per square millimeter of tumor tissue. Larger vessels served as positive internal immunohistochemical controls.

Statistics. In order to measure the degree of association between the expression of two different gene markers, measured both times on a continuous scale, we used {tau}b, i.e., Kendall's {tau} corrected for ties because this coefficient does not assume a linear relationship between the expression of both markers. In order to test the hypothesis of independence between two continuous variables, we therefore used the test of independence based on Kendall's {tau}. If only one variable was continuous, Wilcoxon's test was used. When categories were used for both variables, the P value is the one corresponding to the so-called Fisher's exact test. All calculations were performed using version 13 of SPSS. As this study is explorative, no adjustment for multiple testing was carried out, and every time the P values were <0.05, differences were called significant.


   Results
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Discussion
 References
 
Patients. We analyzed samples obtained from primary tumor sections from 54 patients with newly diagnosed esophageal carcinoma. All patients had tumor resections at the Surgical Center of the University Hospital Hamburg-Eppendorf (Hamburg, Germany). All patients gave informed consent that their tumor tissue could be used for research purposes. The study was approved by the local ethics committee. For patient characteristics, see Table 2 .


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  		Table 2. Patient's characteristics

 
MVD. Because the determination of MVD by immunohistologic examination is time- and labor-intensive, one major goal of the study was to investigate whether MVD could be quantified in primary tumors by qPCR.

First, we did logarithmic dilutions of human umbilical vein endothelial cells in peripheral blood mononuclear cells from healthy volunteers. qPCR for VE-cadherin (CD144) and P1H12 (CD146) were carried out. A linear correlation between the absolute human umbilical vein endothelial cell number and the qPCR results was found (Pearson's correlation coefficients CD144 = 0.99; CD146 = 0.96). Then we analyzed the endothelial cell content in samples from 54 patients with primary resection of esophageal cancer by qPCR. Eighty-seven percent of samples contained at least 60% of tumor tissue as determined by histology of adjacent sections. Total cellular RNA was extracted from snap-frozen tumor sections. For qPCR, the following endothelial antigens were chosen: CD144, CD146, VEGFR-2, and Tie2. Endothelial cell–specific mRNA was detected in all samples. Expression of all marker genes was highly associated with each other, e.g., CD144 with CD146 ({tau}b = 0.45), CD144 with VEGFR-2 ({tau}b = 0.744), and CD144 with tie-2 ({tau}b = 0.684; P for all comparisons <0.0001; correlation graphs available as Supplementary Online Data, graphs 1-3). The close association between the expression of independent markers of endothelial cells indicates that the qPCR results of MVD are robust and reliable.

Second, qPCR results were compared with immunohistology of adjacent sections. MVD was determined after staining for CD31 by a blinded pathologist. The highest association was found for CD144 ({tau}b = 0.258, P = 0.038) and VEGFR-2 ({tau}b = 0.222, P = 0.074; Supplementary graphs 4-5). These results show that MVD quantified by immunohistology and qPCR yield comparable results. As expected, MVD was higher in adenocarcinoma than in squamous cell carcinoma (P < 0.0001).

Association between the expression of angiogenic factors and MVD. To investigate whether MVD depends on the expression of angiogenic factors, we measured the expression of VEGF-A, VEGF-C, VEGF-D, Ang1, and Ang2. Ninety-four percent of tumor specimens expressed Ang1, the other angiogenic cytokines were detected by qPCR in all samples analyzed.

Because CD144 mRNA expression was the factor with the highest concordance with histologically determined MVD, we compared the gene expression of angiogenic factors with CD144. Coefficients between CD144 and the respective factor were: VEGF-A ({tau}b = 0.427), VEGF-C ({tau}b = 0.402), VEGF-D ({tau}b = 0.518), Ang1 ({tau}b = 0.626), and Ang2 ({tau}b = 0.498). All correlations were statistically significant (P < 0.0001) implying a close association between angiogenic factor expression and MVD (Supplementary graphs 6-10).

Lymphendothelial cells. We also analyzed the expression of lymphendothelial cell antigens Prox, LYVE, and VEGFR-3 for possible quantification of lymphatic vessels. A statistically significant relationship between the expression of lymphendothelial markers was detected: LYVE with Prox ({tau}b = 0.334, P = 0.002), LYVE with VEGFR-3 ({tau}b = 0.450, P = 0.015), and VEGFR-3 with Prox ({tau}b = 0.317, P = 0.087) indicating that qPCR results were concordant (Supplementary graphs 11-13).

Lymph node metastases. Angiogenic variables were correlated with lymph node metastases detected on surgical specimens. A significant association was found between immunohistologically determined MVD and the occurrence of N+ status (P = 0.003). Among the endothelial antigens analyzed by qPCR, the biggest difference between lymph node–positive and lymph node–negative patients was seen for VEGFR-2 expression (P = 0.048; Fig. 1 ). When the relationship between lymph node metastases and the expression of angiogenic growth factors VEGF-A, VEGF-C, VEGF-D, Ang-1, and Ang-2 were examined, only VEGF-C showed a significant difference (P = 0.04; Fig. 2 ).


Figure 1
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  		Fig. 1. VEGFR-2 expression in relation to the presence of lymph node metastases (P = 0.048).

 

Figure 2
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  		Fig. 2. VEGF-C expression in relation to the presence of lymph node metastases (P = 0.04).

 

   Discussion
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 Abstract
 Materials and Methods
 Results
 Discussion
References
 
Angiogenesis and lymphangiogenesis play important roles in tumor growth and metastasis. Recent evidence suggests an association between angiogenesis in the primary tumor and patient outcome in different malignancies (15–17).

Microscopic determination of MVD is widely used to quantify angiogenesis in different tumors. There is strong variation in patient selection criteria, interobserver variation, number of hotspots counted, markers employed, and methods used leading to confounding reports in the literature (18). Considering the emerging effect of angiogenesis in clinical oncology, a more objective and less labor-intensive standardized method is needed to quantify angiogenesis.

We therefore developed qPCR assays to measure mRNA expression of different endothelial antigens such as CD144, CD146, VEGFR-2, and Tie2. The expression of all independent endothelial surface molecules showed significant correlations with each other. In our analyses, expression of the endothelial cell–specific adhesion molecule VE-cadherin was significantly correlated both with endothelial cell count in log dilutions of human umbilical vein endothelial cells and with MVD counted by an independent blinded pathologist. VEGFR-2 mRNA expression was also correlated with MVD. Consequently, quantification of VE-cadherin and VEGFR-2 mRNA represents a novel robust and objective tool to measure angiogenesis in esophageal carcinoma and probably other primary tumors.

There have been no reports on VE-cadherin expression in esophageal carcinoma published to date. Other investigators quantified VE-cadherin gene expression in breast carcinoma showing significant correlations with tumor vasculature supporting our data (19).

In our study, we additionally investigated the expression of angiogenic growth factors VEGF-A, VEGF-C, VEGF-D, Ang1, and Ang2. We could show a close relationship between the expression of angiogenic growth factor and VE-cadherin, suggesting concerted expression of these cytokines; thus, providing a strong signal for induction of neoangiogenesis.

Shih et al. used qPCR to quantify the expression of the same endothelial cell surface markers and cytokines in a murine transgenic model of prostate adenocarcinoma. The authors showed strong associations between all analyzed factors concordant with our results (20).

Most published reports on human primary tumors focus on single cytokines implicated in angiogenesis and use semiquantitative immunohistochemistry or conventional PCR for quantification of gene expression. Because of significant differences in angiogenetic gene expression during various phases of tumor development, a panel of markers may more accurately predict the level of angiogenesis than single markers.

Therefore, there is considerable variation in correlating the expression of angiogenic growth factors with MVD in the literature. For example, 6 out of 12 studies showed significant correlations of VEGF-A protein expression determined by semiquantitative immunohistochemistry or PCR and MVD in squamous cell carcinoma of the esophagus (21). Analysis of gene expression by quantitative methods may yield more uniform results.

We also quantified lymphendothelial markers (LYVE, Prox, and VEGFR-3) and showed significant correlations between these molecules. The expression of these markers was unrelated to MVD determined by CD31 immunohistology, indicating the distinct nature of lymphangiogenesis and angiogenesis. Interestingly, no correlation between the density of lymphendothelial cells and lymph node metastases was identified.

We then correlated all markers with the nodal status of the patients. A clear association between MVD determined by immunohistology or qPCR and lymph node involvement was detected. Interestingly, no association between the density of lymphatic endothelial cells and nodal status could be identified. When analyzing the expression of angiogenetic growth factors, the only significant relationship was found between lymph node metastases and VEGF-C. One possible explanation for this finding may be that VEGF-C acts on lymphatic endothelial cells in draining lymph nodes, rendering them more vulnerable to implantation of tumor cells, but further research is needed to support this hypothesis. Similar to our results, an association between VEGF-C expression and lymph node metastases has already been shown in esophageal carcinoma by others (22).

In summary, qPCR represents a fast and reliable technique to study MVD in tumor samples. qPCR of VE-cadherin (CD144) and VEGFR-2 are proposed as the most reliable markers which should be employed for the quantification of MVD. Larger studies should be done to determine the prognostic significance of these findings and to relate MVD to responses to innovative targeted therapies.


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

Received 5/31/06; revised 10/ 9/06; accepted 10/17/06.


   References
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 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

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HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online