Flow cytometric analysis of circulating endothelial cells and endothelial progenitors for clinical purposes in oncology: A critical evaluation (Review)

  • Authors:
    • Marco Danova
    • Giuditta Comolli
    • Mariangela Manzoni
    • Martina Torchio
    • Giuliano Mazzini
  • View Affiliations

  • Published online on: March 18, 2016     https://doi.org/10.3892/mco.2016.823
  • Pages: 909-917
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Malignant tumors are characterized by uncontrolled cell growth and metastatic spread, with a pivotal importance of the phenomenon of angiogenesis. For this reason, research has focused on the development of agents targeting the vascular component of the tumor microenvironment and regulating the angiogenic switch. As a result, the therapeutic inhibition of angiogenesis has become an important component of anticancer treatment, however, its utility is partly limited by the lack of an established methodology to assess its efficacy in vivo. Circulating endothelial cells (CECs), which are rare in healthy subjects and significantly increased in different tumor types, represent a promising tool for monitoring the tumor clinical outcome and the treatment response. A cell population circulating into the blood also able to form endothelial colonies in vitro and to promote vasculogenesis is represented by endothelial progenitor cells (EPCs). The number of both of these cell types is extremely low and they cannot be identified using a single marker, therefore, in absence of a definite consensus on their phenotype, require discrimination using combinations of antigens. Multiparameter flow cytometry (FCM) is ideal for rapid processing of high numbers of cells per second and is commonly utilized to quantify CECs and EPCs, however, remains technically challenging since there is as yet no standardized protocol for the identification and enumeration of these rare events. Methodology in studies on CECs and/or EPCs as clinical biomarkers in oncology is heterogeneous and data have been obtained from different studies leading to conflicting conclusions. The present review presented a critical review of the issues that limit the comparability of results of the most significant studies employing FCM for CEC and/or EPC detection in patients with cancer.

Introduction

Circulating endothelial cells (CECs) and endothelial progenitor cells (EPCs) have been proposed as non-invasive surrogate biomarkers of angiogenesis in cancer and other diseases (15). Their baseline number and kinetics in cancer patients has been widely investigated and several previous studies have demonstrated that they can be altered by disease status and treatments, including biological anti-angiogenic drugs and chemotherapy (CT) (1,2). However, CECs and EPCs are small, heterogeneous cell populations for which, despite extensive research, debate remains about the phenotypic definition and this makes reproducible identification and counting technically challenging (68).

Multicolor flow cytometry (FCM) is becoming an increasingly important technology for studies on clinical biomarkers and it is the most widely utilized method for the analysis of rare events, including CECs and EPCs, since it is a rapid, quantitative technique that has also the advantage of simultaneous determination of multiple markers (912). To date, several FCM-based methods to detect CECs and EPCs in patients with solid tumors have been developed. The majority of these are based on different combinations of surface markers, sample-handling and staining protocols, gating strategies and data analysis programs.

The present review analyzed some of the main published FCM analyses of CECs and EPCs in order to identify the methodological aspects most responsible for the discordant results observed. The aim was to establish the pre-analytical and analytical factors that must be carefully taken into consideration when CECs and EPCs are quantified for clinical purposes in oncology.

Flow cytometric analysis of circulating endothelial cells in patients with cancer

Despite the lack of universal consensus on phenotypic identification, CECs are accepted as cells, which circulate into the blood and express endothelial markers in the absence of progenitor and hematopoietic markers (13,14). Elevated CEC levels have been described in a range of tumor types and several studies have suggested that their number, viability and kinetics would be useful as a prognostic/predictive tool in patients with cancer (2,10,13,15).

Since CECs are rare events, their precise quantification in peripheral blood (PB) samples requires a technically rigorous analytical approach, which should take many factors into consideration (8). Several pre-analytical and analytical steps significantly affect not only the quantification of CECs, but can also result in a change in the definition of these cells, leading to problems in the interpretation of the results (Table I) and in their potential association with clinical endpoints (Table II) (1634).

Table I.

Selected outcomes and characteristics of eligible studies assessing CEC levels by flow cytometry in patients with cancer.

Table I.

Selected outcomes and characteristics of eligible studies assessing CEC levels by flow cytometry in patients with cancer.

First authorTumor typeCEC phenotypeCEC u.m.PatientsControlsP-valueRefs.
GoodaleBreastCD45-, CD146+/600 events6154<0.05(16)
GoonBreastCD45-, CD146+, CD3+/ml9.0 (5.0–12.7)7.7 (6–10)0.05(17)
KuoBreastCD45-, CD146+, CD31+, CD133+, Syto16+ cells/µla−0.609n.a. (18)
VrolingNSCLCCD45-, CD3bright, VEGFR2+/ml41n.a. (19)
YuanNSCLCCD45-, CD31+, CD146+/105 cells299±221117±33<0.001(20)
RonzonimCRCCD45-, CD146+, CD133-, CD34+/WBC30200.09(21)
ManzonimCRCCD45-, CD146+, CD133-, CD34+/WBC35180.01(22)
RamcharanmCRCCD45-, CD146+, CD34+/ml208<0.05(23)
LinRectalCD45-, CD31bright, CD133-, VEGFR2+/105 events1,000473<0.01(24)
StarlingerPancreasCD45-, CD146+, CD31+/5×105 events4.520.46(25)
YuGynecologicalCD45-, CD146+, CD31+, CD105+% WBC1.360.18>0.0001(26)
FaraceRCCCD45-, CD146+, CD31+, 7ADD-/ml13n.a. (27)
BhattRCCCD45-, CD31+, CD146+, CD133-/µl0.93 (0.19–11.75)0.33 (0.12–0.99)0.05(28)
BlannProstateCD45-, CD146+, CD34+, CD309-/ml25280.004(29)
FuerederProstateCD45-, CD146+, CD133-, CD31+, Syto16+% WBC0.22092n.a. (30)
DuBoisOsteosarcomaCD45-, CD146+, CD133-, CD31+/ml6451,6700.12(31)
CuppiniMalignant gliomaCD45-, CD146+, CD133-, CD31+,/ml101260.01(32)
BrunnerHead and neckCD5-, CD146+, CD31+/5×105 events2017<0.01(33)
MancusoVariousCD45-, CD146+, CD133-, CD31+, Syto16+/ml951140<0.0001(34)

a cells/ml, adjusted regression coefficient. CEC, circulating endothelial cell; WBC, white blood cell; CD, cluster differentiation; Syto16, cell-permeant green fluorescence nucleic acid stain; RCC, renal cell carcinoma; NSCLC, non-small cell lung cancer; mCRC, metastatic colorectal cancer; VEGF, vascular endothelial growth factor; n.a., not available; u.m., units of measurement.

Table II.

Correlation between CECs and clinical endpoints defined in the studies analyzed.

Table II.

Correlation between CECs and clinical endpoints defined in the studies analyzed.

First authorTumor typeClinical correlationsRefs.
GoodaleBreastCECs correlate with disease stage(16)
GoonBreastCECs positively correlate with Nottingham Prognostic Index, tumor size and invasiveness(17)
Kuo CECs are not surrogate biomarker of angiogenesis in patients receiving chemotherapy plus antiangiogenic agents(18)
VrolingNSCLCCECs correlate with response to tyrosine kinase inhibitors(19)
YuanNSCLCCECs may potentially become biomarkers for diagnosis(20)
RonzonimCRCCECs correlate with progression-free survival(21)
ManzonimCRCCECs are predictive biomarkers of response to chemotherapy and correlate with progression-free survival(22)
RamcharanmCRCCECs are not able to better predict the 2 year outcome in comparison with Dukes and AJCC stage(23)
LinRectalCECs may be prognosis and morbidity biomarkers(24)
StarlingerPancreasCECs may potentially become prognostic and/or predictive biomarkers(25)
YuGynecologicalNot found(26)
FaraceRCCCECs don't correlate with either progression-free survival and overall survival(27)
BhattRCCNot found(28)
BlannProstateNot found(29)
FuerederProstateNot found(30)
DuBoisOsteosarcomaNot found(31)
CuppiniMalignant gliomaNot found(32)
BrunnerHead and neckNot assessed(33)
MancusoVariousNot assessed(34)

[i] CEC, circulating endothelial cell; NSCLC, non-small cell lung cancer; RCC, renal cell carcinoma; mCRC, metastatic colorectal cancer.

Circulating endothelial cells cannot be identified by any single surface marker and combinations of fluorochrome-conjugated monoclonal antibodies (MoAbs), which vary profoundly between studies, are utilized in the attempt to improve the analytical capability of FCM. The lack of a unified strategy is due to the extreme variety of phenotypic definitions of CECs, even between studies on the identical tumor type (13).

In many previous studies, CECs are identified as those positive for a nuclear binding fluorochrome, negative for the leukocyte marker, cluster of differentiation (CD)45, and positive for CD31 and CD146 (25,28,3034). Previously, the expression of CD109, a cell surface glycoprotein which has been shown to be overexpressed in tumor endothelial cells, has been utilized to identify a specific subpopulation of CECs potentially useful as a prognostic marker in specific tumor types (35). Another complicating factor, reported only in certain studies, is the choice of the marker for the definition of CECs with apoptotic features (17,36). The different marker utilized can cause a significant change in the baseline count of this CEC subset, making it difficult to explore its clinical relevance (Table I) (17).

In other previous studies, the CEC phenotype is defined by similar combinations of markers, however, with different degrees of expression. This amplifies the range of combinations of MoAbs utilized and, particularly for panels made up of a large number of reagents, gives rise to an additional source of possible criticism (interferences between the various probes).

Since in the analysis of rare events, precision increases with the number of cells collected, CEC identification must be performed with a large number of acquired events, meaning an adequate sample of PB must be collected. When the steps in the pre-analytical phase of FCM protocols were compared, information on the modality of sample collection and of sample storage, and on the protocols for erythrocyte-depletion, were either lacking or significant differences emerged between the various studies, as shown in Table I.

A lack of uniformity was also revealed regarding the characteristics of patients and samples: Type of cancer treatment used, PB sample size, the presence or absence of a healthy control group, and tumor histology/subtype and disease stage (early or metastatic).

The numerous differences in FCM and experimental procedure make the clinical interpretation of the CEC numbers obtained highly difficult and affects the validity of the differences recorded between patients and controls, therefore, greatly limiting comparability of studies (Table II).

Flow cytometric analysis of endothelial progenitor cells in patients with cancer

Several assessment techniques have been proposed for EPCs, since they were first described by Asahara et al (37) with FCM being one of the most widely utilized.

Endothelial progenitor cells include numerous subtypes, which serve a variety of roles in promoting vascular growth (38) and, as yet, no universal consensus is available on the markers that require identification (7,39). Furthermore, the range of cellular markers that can be used to identify EPCs is even wider compared with that for CECs. As a consequence, wide variation, in terms of choice of MoAbs and extreme heterogeneity in their combinations, emerged across the previous studies. The focus of numerous previous studies in humans has been on the simultaneous expression of stem cell markers, including CD34 or CD133, and endothelial antigens, including CD31, type 2 vascular endothelial growth factor receptor (VEGFR-2 or kinase-insert domain, KDR) and VEGFR-1 (Table III) (9,17,18,21,23,24,2734,4054).

Table III.

Selected outcomes and characteristics of eligible studies assessing EPC levels by flow cytometry in cancer patients.

Table III.

Selected outcomes and characteristics of eligible studies assessing EPC levels by flow cytometry in cancer patients.

First authorTumor typeEPC phe.o9notypeEPC u.m.PatientsControlsP-valueRefs.
NaikBreastCD14+, CD133+, VEGFR2+/5×105 events165n.a. (40)
GoonBreastCD34+, CD133+, CD45-/ml121 (81–186)169 (106–241)<0.05(17)
KuoBreastCD45-, CD31+, CD146+, CD133+/105 eventsxWBC0.295n.a. (18)
JainBreastCD45dim, CD133+, VEGFR2+/ml21.3n.a. (41)
BogosSCLCCD34+, VEGFR3+/ml1.625 (600–2.750)455 (370–530)<0.01(42)
NowakNSCLCCD34+, CD133+, VEGFR2+%11±0.0070.025±0.018<0.001(43)
MoritaNSCLCCD45-, CD34+, CD31+, CD133+/µl3711<0.05(44)
SakamoriNSCLCCD31+, CD34+, CD133+, CD45-/µl404<0.001(45)
PirroNSCLCCD34+, VEGFR2+/ml2.3±0.322.3±0.26>0.05(46)
RonzonimCRCCD45-, CD34+, CD133+, CD146+xWBC/1000.20.1>0.05(21)
RamcharanmCRCCD34+, CD45-, VEGFR2+7ml21 (10–44)7 (0–14)<0.001(23)
LinRectalCD31+, VEGFR2+, CD45dim, CD133+/105 events3034<0.01(24)
SuOvarianCD34+, VEGFR2+/ml1.260368<0.01(47)
QiuOvarianCD34+, VEGFR3+%0.98 (0.55–1.94)0.15 (0.10–0.23)<0.01(48)
KimGynecologicalCD45-, CD31+, CD133+, VEGFR2+%0.032±0.0140.002±0.002<0.01(49)
YangRCCCD45-, CD34+, VEGFR2+%0.280.08<0.01(50)
FaraceRCCCD45dim, CD34+, VEGFR2+, 7ADD-% CD34 cells0.50n.a. (27)
BhattRCCCD34+, CD133+, CD146+, CD45-/µl0.97 (0.39–5.88)0.19 (0.08–0.47)<0.01(28)
BlannProstateCD34+, CD309+, CD45-, CD146-/ml38 (15–74)32 (18–82)>0.01(29)
FuerederProstateCD45-, CD31+, CD146+, CD133+, 7ADD-, Syto16+bright% WBC0.29233n.a. (30)
DuBoisOsteosarcomaCD45-, CD31+, CD146+, CD133+/ml1262600.69(31)
RafatGlioblastomaCD34+, VEGFR2+1.23±1.090.08±0.04<0.05 (51)
CorsiniGliomaCD45dim, CD34+, CD133+/µl3.8±5.33.6±2.8>0.05(52)
BrunnerHead & neckCD133+, VEGFR2+/105 events4.5 (1–41)2 (0–7)<0.001(33)
HaGastricCD34+, CD133+/ml20±13.94±2.6<0.05(53)
SieghartHCCCD34+, Cd133+, VEGFR2+%0.14±0.090.06±0.04<0.01(54)
MancusoVariousCD45-, CD31+, CD146+, CD133+, 7ADD-, Syto16+bright/ml4291810.00019(34)
MasoulehVariousCD45-, CD31+, CD133+% MNCs0.1–3.10.17–1.9<0.01   (9)

[i] EPC, circulating endothelial cell; WBC, white blood cell; MNCs, mononuclear cells; CD, cluster differentiation; VEGFR, vascular endothelial growth factor receptor; 7ADD, 7-amino-actynomicin D; Syto-16, cell-permaneant green fluorescence nucleic acid stain; RCC, renal cell carcinoma; u.m., units of measurement; HCC, hepatocellular carcinoma.

With regards to reported EPC numbers, another source of disparity between studies is that EPC count data are presented in two different forms: Number of EPCs in the PB sample volume and frequencies for a defined number of mononuclear cells (MNCs). In addition, the numerical values of EPCs are often reported with an error-approximation, which may affect the significance of the differences between patients and controls. The units of measurement and the algorithms utilized to obtain the absolute number of EPCs were also extremely heterogeneous. Finally, the cell populations to whom EPCs are associated often include not only WBCs and MNCs, but also cell subtypes, including CD34+ and VEGFR3+cells.

Another consideration to be made is that an ideal clinical biomarker must be highly biologically informative, and also easy and rapid to obtain and show a strong statistical association with the clinical course of the disease. While complex antigen phenotypes may be more specific, they are difficult to reproduce and the complexity of antigenic combination does not necessarily improve the performance of EPCs as clinical biomarkers. Hence, instead of widening the antigenic profile of EPCs to increase specificity, research should be aimed at making their identification and quantification more simple, reproducible and easy to obtain in clinical practice.

In addition to the impact of biological and procedural issues, from a technical point of view, the use of FCM has to deal with problems associated with background noise, which may lead to false positive results. Consequently, signal enhancement and noise reduction are crucial. In their review, Van Craenenbroeck et al (55) also listed the various steps that should be taken into consideration for this type of analysis. Pre-analytical factors included the choice of the sample material, modality of blood collection, handling temperature and certain subject-associated confounding factors. Numerous other problems associated with data acquisition, mentioned by Van Craenenbroeck et al (55), were the protocols for erythrocyte-depletion, the wash/no wash approaches. The authors suggested steps that must be followed to reduce the sources of error in FCM results. The importance of standardizing an appropriate gating strategy and multiple data analysis methods are highlighted in detail in one previous study (56).

To summarize, the rapidity of the expansion of this field is partly inhibited by an incomplete understanding of the biology, and the consequent lack of a universal definition of EPCs, as well as the lack of a standardized FCM assay procedure for their identification and characterization. Overcoming these particular obstacles can provide further insights into their possible clinical implications in oncology (Table IV).

Table IV.

Correlation between EPCs and clinical endpoints defined in the studies analyzed.

Table IV.

Correlation between EPCs and clinical endpoints defined in the studies analyzed.

First authorTumor typeClinical correlationsRefs.
NaikBreastEPCs correlate with disease stage and with response to chemotherapy(40)
GoonBreastEPCs do not correlate with Nottingham Prognostic Index, tumor size, invasiveness(17)
KuoBreastEPCs change dinamicly during antiangiogenic chemotherapy, they are candidate markers of angiogenesis(18)
JainBreastEPCs correlate with risk of relapse and disease progression(41)
BogosSCLCEPCs are significantly increased and correlate with lymphatic involvement and prognosis(42)
NowakNSCLCEPCs correlate with disease stage and with risk of disease progression(43)
MoritaNSCLCEPCs correlate with clinical response not with progression-free survival(44)
SakamoriNSCLCEPCs correlate with response to chemotherapy and with risk of disease progression(45)
PirroNSCLCEPCs correlate with risk of disease recurrence(46)
RonzonimCRCNot assessed(21)
RamcharanmCRCEPCs do not predict 2 year outcome in CRC in comparison with Dukes' and AJCC stage(23)
LinRectalNot assessed(24)
SuOvarianEPCs correlate with response to chemotherapy and with risk of disease progression(47)
QiuOvarianEPCs correlate with lymph node metastasis(48)
KimGynecologicalEPCs may be useful surrogate marker to monitor treatment response(49)
YangRCCNot assessed(50)
FaraceRCCEPCs correlate with progression-free survival and overall survival(27)
BhattRCCNot found(28)
BlannProstateNot found(29)
FuerederProstateNot found(30)
DuBoisOsteosarcomaNot found(31)
RafatGlioblastomaNot found(51)
CorsiniGliomaNot found(52)
BrunnerHead & neckEPCs surrogate marker of response to chemotherapy(33)
HaGastricEPCs correlate with lymph node metastasis and histological differentiation(53)
SieghartHCCNot assessed(54)
MancusoVariousNot assessed(34)
MasoulehVariousNot found(9)

[i] EPC, endothelial progenitor cell; NSCLC, non-small cell lung cancer; SCLC, small cell lung cancer; RCC, renal cell carcinoma; mCRC, metastatic colorectal cancer; HCC, hepatocellular carcinoma; AJCC, American Joint Committee on Cancer.

Discussion

The role of angiogenesis in tumor growth is well-established and it is clear that this phenomenon is essential for the dissemination of metastases, as well as for the aggressive recurrence and refractoriness of the tumor (5760). Several effective anti-angiogenic drugs are now available and several are under development and, in order to improve the individualization of cancer treatment, blood-based biomarkers that accurately reflect their effects are urgently required (6163). Numerous reports suggest that serial counting of CECs and/or EPCs can be successfully used to this end, however, this interesting prospect needs to be fully corroborated in the clinical setting, first of all by overcoming the areas of controversy that persist in the study of CEC and EPC biology.

Elevated CEC counts are associated with certain malignancies, however, conflicting results concerning their actual prognostic or predictive value during chemotherapy with or without anti-angiogenic therapy have been reported. The clinical utility of CEC counts can be limited, in part, by the lack of specificity for tumor vasculature and the possible variety of non-malignant causes, which can impact their number. In this regard, it has recently been hypothesized that specific antigens, tumor endothelial markers (TEM), enriched in tumor, vs. non-malignant endothelia, may be detectable on CEC surface and that these circulating TEM+ endothelial cells may constitute more specific blood-based biomarkers (64).

For EPCs, it must be also emphasized that it is now clear that the EPC phenotype is dynamic and a definite EPC identity may become elusive. Indeed, the endothelial differentiation potential can vary according to local environmental conditions and change over time. For these reasons, as long as clinical applications are concerned, a detailed functional characterization of these cells may be even more relevant compared with their antigenic phenotype (6567).

On the other hand, all studies on clinical biomarkers would be required to be performed utilizing an highly efficient, specific and reproducible assay (68). Multi-color flow cytometric techniques are widely utilized in clinical studies to detect and quantify CECs and EPCs in whole blood, however, they remain technically challenging. The number of these cells is extremely low and they cannot be identified by a single marker, but only by a combination of antigens. As for other types of flow cytometric analysis of rare events, frequent sources of error include the contamination of cell populations with false positive events and the fluorescence associated with non-specific events. Such limitations can only be overcome through the optimization of MoAb panels, proper compensation for the staining with each individual fluorescently conjugated MoAb to maximize signal to noise ratio, appropriate selection of the regions of interest on the graphic display, the utilization of the linear scale for the low intensity staining regions (reserving the log scale for brightly staining markers), the utilization of hardware that allows high data rate collection and the utilization of dedicated data analysis programs. The majority of published protocols fail to properly address the majority of these issues.

In conclusion, the lack of a consensus on a consistent CEC and EPC phenotypic definition and the multitude of flow cytometric methods applied, which are not always sufficiently detailed, has resulted in a great heterogeneity in the reported blood levels of CECs and EPCs. These aspects, together with the heterogeneity of the patients series in the various studies, limit their potential to guide therapeutic strategies in clinical practice (69). In spite of these shortfalls, steps forward in the definition of the potential utility of CECs and EPCs for clinical purposes have been achieved, although reliable quantification of these cells is a work in progress and the interpretation of results must be made cautiously (35,10,70,71). In order to validate future reports that indicate, within well-designed trials, a true clinical value for both CECs and EPCs, unambiguous phenotypic definition of these cells together with careful inter-laboratory standardization of the quantitative techniques of analysis, including FCM, are mandatory.

Acknowledgements

The authors would like to thank Ms. Claire Archibald for English revision. The present study was partly supported by the IRCCS San Matteo Foundation (no. 80425 to Dr Giuditta Comolli).

References

1 

Goon PK, Lip GY, Boos CJ, Stonelake PS and Blann D: Circulating endothelial cells, endothelial progenitor cells and endothelial microparticles in cancer. Neoplasia. 8:79–88. 2006. View Article : Google Scholar : PubMed/NCBI

2 

Kraan J, Sleijfer S, Foekens JA and Gratama JW: Clinical value of circulating endothelial cell detection in oncology. Drug Discov Today. 17:710–717. 2012. View Article : Google Scholar : PubMed/NCBI

3 

Koutrompi M, Dimopoulos S, Psarra K, Kypirianou T and Nanas S: Circulating endothelial and progenitor cells: Evidence from acute and long-term exercise effects. World J Cardiol. 4:312–326. 2012. View Article : Google Scholar : PubMed/NCBI

4 

Costiniuk CT, Hibert BM, Simard T, Ghazawi FM, Angel JB and O'Brien ER: Circulating endothelial progenitor cells in HIV infection: A systematic review. Trends Cardiovasc Med. 23:192–200. 2013. View Article : Google Scholar : PubMed/NCBI

5 

King TF and McDermott JH: Endothelial progenitor cells and cardiovascular disease. J Stem Cells. 9:93–106. 2014.PubMed/NCBI

6 

Strijbos MH, Gratama JW, Kraan J, Lamers CH, den Bakker MA and Sleijfer S: Circulating endothelial cells in oncology: Pitfalls and promises. Br J Cancer. 98:1731–1735. 2008. View Article : Google Scholar : PubMed/NCBI

7 

Timmermans F, Plum J, Yöder MC, Ingram DA, Vandekerckhove B and Case J: Endothelial progenitor cells: Identity defined? J Cell Mol Med. 13:87–102. 2009. View Article : Google Scholar : PubMed/NCBI

8 

Hedley BD and Keeney M: Technical issues: Flow cytometry and rare event analysis. Int J Lab Hematol. 35:344–350. 2013. View Article : Google Scholar : PubMed/NCBI

9 

Masouleh BK, Baraniskin A, Schmiegel W and Schroers R: Quantification of circulating endothelial progenitor cells in human peripheral blood: Establishing a reliable flow cytometric protocol. J Immunol Methods. 357:38–42. 2010. View Article : Google Scholar : PubMed/NCBI

10 

Mund JA, Estes ML, Yoder MC, Ingram DA Jr and Case J: Flow cytometric identification and functional characterization of immature and mature circulating endothelial cells. Arterioscler Thromb Vasc Biol. 32:1045–1053. 2012. View Article : Google Scholar : PubMed/NCBI

11 

Nielsen MH, Beck-Nielsen H, Andersen MN and Handberg A: A flow cytometric method for characterization of circulating cell-derived microparticles in plasma. J Extracell Vescicles. 3:10.3402/jev.v3.2079532014.

12 

Kraan J, Strijbos MH, Sieuwerts AM, Foekens JA, den Bakker MA, Verhoef C, Sleijfer S and Gratama JW: A new approach for rapid and reliable enumeration of circulating endothelial cells in patients. J Thromb Haemost. 10:931–939. 2012. View Article : Google Scholar : PubMed/NCBI

13 

Bertolini F, Shaked Y, Mancuso P and Kerbel RS: The multifaced circulating endothelial cell in cancer: Towards marker and target identification. Nat Rev Cancer. 6:835–845. 2006. View Article : Google Scholar : PubMed/NCBI

14 

Sutherland DR, Anderson L, Keeney M, Nayar R and Chin-Yee I: The ISHAGE guidelines for CD34+cell determination by flow cytometry. International society of haematotherapy and graft Engineering. J Haematother. 5:213–226. 1996. View Article : Google Scholar

15 

Mancuso P and Bertolini F: Circulating endothelial cells as biomarkers in clinical oncology. Microvasc Res. 79:224–228. 2010. View Article : Google Scholar : PubMed/NCBI

16 

Goodale D, Phay C, Brown W, Gray-Statchuk L, Furlong P, Lock M, Chin-Yee I, Keeney M and Allan AL: Flow cytometric assessment of monocyte activation markers and circulating endothelial cells in patients with localized or metastatic breast cancer. Cytometry B Clin Cytom. 76:107–117. 2009. View Article : Google Scholar : PubMed/NCBI

17 

Goon PK, Lip GY, Stonelake S and Blann AD: Circulating endothelial cells and circulating progenitor cells in breast cancer: Relationship to endothelial damage/dysfunction/apoptosis, clinicopathologic factors and the Nottingham prognostic index. Neoplasia. 11:771–779. 2009. View Article : Google Scholar : PubMed/NCBI

18 

Kuo YH, Lin CH, Shau WY, Chen TJ, Yang SH, Huang SM, Hsu C, Lu YS and Cheng AL: Dynamics of circulating endothelial cells and endothelial progenitor cells in breast cancer patients receiving cytotoxic chemotherapy. BMC Cancer. 12:6202012. View Article : Google Scholar : PubMed/NCBI

19 

Vroling L, Lind JS, de Haas RR, Verheul HM, van Hinsbergh VW, Broxterman HJ and Smith EF: CD133+ circulating hematopoietic progenitor cells predict for response to sorafenib plus erlotinib in non-small cell lung cancer patients. Br J Cancer. 102:268–275. 2010. View Article : Google Scholar : PubMed/NCBI

20 

Yuan DM, Zhang Q, Lu YL, Ma XQ, Zhan Y, Liu HB and Song Y: Predictive and prognostic significance of circulating endothelial cells in advanced non-small cell lung cancer patients. Tumor Biol. 36:9031–9037. 2015. View Article : Google Scholar

21 

Ronzoni M, Manzoni M, Mariucci S, Loupakis F, Brugnatelli S, Bencardino K, Rovati B, Tinelli C, Falcone A, Villa E and Danova M: Circulating endothelial cells and endothelial progenitor as predictive markers of clinical response to bevacizumab-based first-line treatment in advanced colorectal cancer patients. Ann Oncol. 21:2382–2389. 2010. View Article : Google Scholar : PubMed/NCBI

22 

Manzoni M, Mariucci S, Delfanti S, Rovati B, Ronzoni M, Loupakis F, Brugnatelli S, Tinelli C, Villa E, Falcone A and Danova M: Circulating endothelial cells and apoptotic fraction are mutually independent predictive biomarkers in bevacizumab-based treatment for advanced colorectal cancer. J Cancer Res Clin oncol. 138:1187–1196. 2012. View Article : Google Scholar : PubMed/NCBI

23 

Ramcharan KS, Lip GY, Stonelake S and Blann AD: Increased pre-surgical numer of endothelial progenitor cells and circulating endothelial cells in coorectal cancer fail to predict outcome. Int J Colorectal Dis. 30:315–321. 2015. View Article : Google Scholar : PubMed/NCBI

24 

Lin CC, Liu CY, Chen MJ, Wang TE, Chu CH, Wang HY, Shih SC, Hsu ML, Hsu TC and Chen YJ: Profiles of circulating endothelial cells and serum cytokines during adjuvant chemoradiation in rectal cancer patients. Clin Transl Oncol. 15:855–860. 2013. View Article : Google Scholar : PubMed/NCBI

25 

Starlinger P, Brugger P, Reiter C, Schauer D, Sommerfeldt S, Tamndl D, Kuerher I, Schoppmann SF, Gnant M and Brostjan C: Discrimination between circulating endothelial cells and blood cell populations with overlapping phenotype reveals distinct regulation and predictive potential in cancer therapy. Neoplasia. 13:980–990. 2011. View Article : Google Scholar : PubMed/NCBI

26 

Yu HK, Lee HJ, Choi HN, Ahn JH, Choi JY, Song HS, Lee KH, Yoon Y, Yi LS, Kim JS, et al: Characterization of CD5-/CD31+/CD105+ circulating cells in the peripheral blood of patients with gynecologic malignancies. Clin Cancer Res. 19:5340–5350. 2013. View Article : Google Scholar : PubMed/NCBI

27 

Farace F, Gross-Groupil M, Tournay E, Taylor M, Vimond N, Jacques N, Billiot F, Mauguen A, Hill C and Escudier B: Levels of circulating CD45(dim)CD34(+)VEGFR2(+)progenitor cells correlate with outcome in metastatic renal cell carcinoma patients treated with tyrosine kinase inhibitors. Br J Cancer. 104:1144–1150. 2011. View Article : Google Scholar : PubMed/NCBI

28 

Bhatt RS, Zurita AJ, O'Neill A, Norden-Zfoni A, Zhan L, Wu HK, Wen PY, George D, Sukhatme VP, Atkins MB and Heymach JV: Increased mobilization of circulating endothelial progenitors in von Hippel-Lindau disease and renal cell carcinoma. Br J Cancer. 105:112–117. 2011. View Article : Google Scholar : PubMed/NCBI

29 

Blann AD, Balakrishnan B, Shantsila E, Ryan P and Lip GY: Endothelial progenitor cells and circulating endothelial cells in early prostate cancer: A comparison with plasma vascular markers. Prostate. 71:1047–1053. 2011. View Article : Google Scholar : PubMed/NCBI

30 

Fuereder T, Wacheck V, Strommer S, Horak P, Gerschpacher M, Lamm W, Kivaranovic D and Krainer M: Circulating endothelial progenitor cells in castration resistant prostate cancer: A randomized, controlled, biomarker study. PLoS One. 9:e953102014. View Article : Google Scholar : PubMed/NCBI

31 

DuBois SG, Stempak D, Wu B, Mokthari RB, Nayar R, Janeway KA, Goldsby R, Grier HE and Baruchel S: Circulating endothelial cells and circulating endothelial precursor cells in patients with osteosarcoma. Pediatr Blood Cancer. 58:181–184. 2012. View Article : Google Scholar : PubMed/NCBI

32 

Cuppini L, Calleri A, Bruzzone MG, Prodi E, Anghileri E, Pellegatta S, Mancuso P, Porrati P, Di Stefano AL, Cerroni M, et al: Prognostic value of CD109+ circulating endothelial cells in recurrent glioblastoma treated with bevacizumab and irinotecan. PLoS One. 8:e743452013. View Article : Google Scholar : PubMed/NCBI

33 

Brunner M, Thurnher D, Heiduscha G, Grasl MCh, Brostjain C and Erovic BM: Elevated levels of circulating endothelial progenitor cells in head and neck cancer patients. J Surg Oncol. 98:545–550. 2008. View Article : Google Scholar : PubMed/NCBI

34 

Mancuso P, Antoniotti P, Quarna J, Calleri A, Rabascio C, Tacchetti C, Braidotti P, Wu HK, Zurita AJ, Saronni L, et al: Validation of a standardized method for enumerating circulating endothelial cells and progenitors: Flow cytometry and molecular and ultrastructural analyses. Clin Cancer Res. 15:267–273. 2009. View Article : Google Scholar : PubMed/NCBI

35 

Mancuso P, Calleri A, Gregato G, Labanca V, Quarna J, Antoniotti P, Cuppini L, Finocchiaro G, Eoli M, Rosti V and Bertolini F: A subpopulation of circulating endothelial cells express CD109 and is enriched in the blood of cancer patients. PLoS One. 9:e1147132014. View Article : Google Scholar : PubMed/NCBI

36 

Wlodkowic D, Telford W, Skommer J and Darzynkiewicz Z: Apoptosis and beyond: Cytometry in studies of programmed cell death. Methods Cell Biol. 103:55–98. 2011. View Article : Google Scholar : PubMed/NCBI

37 

Asahara T, Murohara T, Sullivan A, Silver M, van der Zee R, Li T, Witzenbichler B, Schatteman G and Isner JM: Isolation of putative progenitor endothelial cells for angiogenesis. Science. 275:964–967. 1997. View Article : Google Scholar : PubMed/NCBI

38 

Pelosi E, Castelli G and Testa U: Endothelial progenitors. Blood Cells Mol Dis. 52:186–194. 2014. View Article : Google Scholar : PubMed/NCBI

39 

Fadini GP, Losordo D and Dimmeler S: Critical reevaluation of endothelial progenitor cell phenotypes for therapeutic and diagnostic use. Curr Res. 17:624–637. 2012.

40 

Naik RP, Jin D, Chuang E, Gold EG, Tousimis EA, Moore AL, Christos PJ, de Dalmas T, Donovan D, Rafii S and Vahdat LT: Circulating endothelial progenitor cells correlate to stage in patients with invasive breast cancer. Breast Cancer Res Treat. 107:133–138. 2008. View Article : Google Scholar : PubMed/NCBI

41 

Jain S, Ward MM, O'Loughlin J, Boeck M, Wiener N, Chuang E, Cigler T, Moore A, Donovan D, Lam C, et al: Incremental increase in VEGFR2+hematopoietic progenitor cells and VEGFR2+ endothelial progenitor cells predicts relapse and lack of tumor response in breast cancer patients. Breast Cancer Res Treat. 132:235–242. 2012. View Article : Google Scholar : PubMed/NCBI

42 

Bogos K, Renyi-Vamos F, Dobos J, Kenessey I, Tovari J, Timar J, Strausz J, Ostoros G, Klepetko W, Ankersmit HJ, et al: High VEGFR-3-positive circulating lymphatic/vascular endothelial progenitor cell level is associated with poor prognosis in human small cell lung cancer. Clin Cancer Res. 15:1741–1746. 2009. View Article : Google Scholar : PubMed/NCBI

43 

Nowak K, Rafat N, Belle S, Weiss C, Hanusch C, Hohenberger P and Beck GCh: Circulating endothelial progenitor cells are increased in human lung cancer and correlate with stage of disease. Eur J Cardiothorac Surg. 37:758–763. 2010. View Article : Google Scholar : PubMed/NCBI

44 

Morita R, Sato K, Nakano M, Miura H, Odaka H, Nobori K, Kosaka T, Sano M, Watanabe H, Shioya T and Ito H: Endothelial progenitor cells are associated with response to chemotherapy in human non-small-cell lung cancer. J Cancer Res Clin Oncol. 137:1849–1857. 2011. View Article : Google Scholar : PubMed/NCBI

45 

Sakamori Y, Masago K, Ohmori K, Togashi Y, Nagai H, Okuda C, Kim YH, Ichiyama S and Mishima M: Increase in circulating endothelial progenitor cells predicts response in patients with advanced non-small cell lung cancer. Cancer Sci. 103:1065–1070. 2012. View Article : Google Scholar : PubMed/NCBI

46 

Pirro M, Cagini L, Paciullo F, Pecoriello R, Mannarino MR, Bagaglia F, Capozzi R, Puma F and Mannarino E: Baseline and post-surgery endothelial progenitor cell levels in patients with early-stage non-small cell lung carcinoma: Impact on cancer recurrences and survival. Eur J Cardiothorac. 44:e245–252. 2013. View Article : Google Scholar

47 

Su Y, Zheng L, Wang Q, Li W, Cai Z, Xiong S and Bao J: Quantity and clinical relevance of circulating endothelial progenitor cells in human ovarian cancer. J Exp Clin Cancer Res. 29:272010. View Article : Google Scholar : PubMed/NCBI

48 

Qiu H, Cao L, Wang D, Xu H and Laing Z: High levels of circulating CD34+/VEGFR3+ lymphatic/vascular endothelial progenitor cells is correlated with lymph node metastasis in patients with epithelial ovarian cancer. J Obstetr Gynaecol Res. 39:1268–1275. 2013. View Article : Google Scholar

49 

Kim YB, Chung YW, Bae HS, Lee JK, Lee NW, Lee KW and Song JY: Circulating endothelial progenitor cells in gynaecological cancer. J Int Med Res. 41:293–299. 2013. View Article : Google Scholar : PubMed/NCBI

50 

Yang B, Gu W, Peng B, Xu Y, Liu M, Che J, Geng J and Zheng J: High level of circulating endothelial progenitor cells positively correlates with serum vascular endothelial growth factor in patients with renal cell carcinoma. J Urol. 188:2055–2061. 2012. View Article : Google Scholar : PubMed/NCBI

51 

Rafat N, Beck GCh, Schulte J, Tuettenberg J and Vajkoczy P: Circulating endothelial progenitor cells in malignant gliomas. J Neurosurg. 112:43–49. 2010. View Article : Google Scholar : PubMed/NCBI

52 

Corsini E, Ciusani E, Gaviani P, Silvani A, Canazza A, Bernardi G, Calatozzolo C, DiMeco F and Salmaggi A: Decrease in circulating endothelial progenitor cells in treated glioma patients. J Neuroncol. 108:123–129. 2012. View Article : Google Scholar

53 

Ha X, Zhao M, Zhao H, Peng J, Deng Z, Dong J, Yang X, Zhao Y and Ju J: Identification and clinical significance of circulating endothelial progenitor cells in gastric cancer. Biomarkers. 18:487–492. 2013. View Article : Google Scholar : PubMed/NCBI

54 

Sieghart W, Fellner S, Reiberger T, Ulbrich G, Ferlitsch A, Wacheck V and Peck-Radosavljevic M: Differential role of circulating endothelial progenitor cells in cirrhotic patients with or without hepatocellular carcinoma. Dig Liver Dis. 41:902–906. 2009. View Article : Google Scholar : PubMed/NCBI

55 

Van Craenenbroeck EM, Van Craenenbroeck AH, van Ierssel S, Bruydonckx L, Hoymans VY, Vrints CJ and Conraads VM: Quantification of circulating CD3+/KDR+/CD45dim endothelial progenitor cells: Analytical considerations. Int J Cardiol. 167:1688–1695. 2013. View Article : Google Scholar : PubMed/NCBI

56 

Verschoor CP, Lelic A, Bramson JL and Bowdish DM: An introduction to automated flow cytometry gating tools and their implementation. Front Immunol. 6:3802015. View Article : Google Scholar : PubMed/NCBI

57 

De Palma M and Nucera S: Circulating endothelial progenitors and tumor resistance to vascular-targeting therapies. Cancer Discov. 2:395–397. 2012. View Article : Google Scholar : PubMed/NCBI

58 

Bielenberg DR and Zetter BR: The contribution of angiogenesis in the process of metastasis. Cancer J. 21:267–273. 2015. View Article : Google Scholar : PubMed/NCBI

59 

Gacche RN: Compensatory angiogenesis and tumor refractoriness. Oncogenesis. 4:e1532015. View Article : Google Scholar : PubMed/NCBI

60 

Moccia F, Zuccolo E, Poleto V, Cinelli M, Bonetti E, Guerra G and Rosti V: Endothelial progenitor cells support tumour growth and metastatisation: Implications for the resistance to anti-angiogenic therapy. Tumour Biol. 36:6603–6614. 2015. View Article : Google Scholar : PubMed/NCBI

61 

Wilson PM, LaBonte MJ and Lenz HJ: Assessing the in vivo efficacy of biologic antianiogenic therapies. Cancer Chemother Pharmacol. 71:1–12. 2013. View Article : Google Scholar : PubMed/NCBI

62 

Yadav L, Puri N, Rastogi V, Satpute P and Sharma V: Tumour angiogenesis and angiogenic inhibitors: A review. J Clin Diagn Res. 9:XE01–XE05. 2015.PubMed/NCBI

63 

Hatch AJ, Clarke JM, Nixon AB and Hurwitz HI: Identifying blood-based protein biomarkers for antiangiogenic agents in the clinic. Cancer J. 21:322–326. 2015. View Article : Google Scholar : PubMed/NCBI

64 

Mehran R, Nilsson M, Khajavi M, Du Z, Cascone T, Wu HK, Cortes A, Xu L, Zurita A, Schier R, et al: Tumor endothelial markers define novel subsets of cancer-specific circulating endothelial cells associated with antitumor efficacy. Cancer Res. 74:2731–2741. 2014. View Article : Google Scholar : PubMed/NCBI

65 

Moschetta M, Mishima Y, Sahin I, Manier S, Glavey S, Vacca A, Roccaro AM and Ghobrial IM: Role of endothelial progenitor cells in cancer progression. Biochim Biophys Acta. 1846:26–39. 2014.PubMed/NCBI

66 

Marcola M and Rodrigues CE: Endothelia progenitor cells in tumor angiogenesis: Another brick in the wall. Stem Cells Int. 2015:8326492015. View Article : Google Scholar : PubMed/NCBI

67 

Ye L and Poh KK: Enhancing endothelial progenitor cell for clinical use. World J Stem Cells. 7:894–898. 2015. View Article : Google Scholar : PubMed/NCBI

68 

Cappelletti V, Appierto V, Tiberio P, Fina E, Callari M and Daidone MG: Circulating biomarkers for prediction of treatment response. J Natl Cancer Inst Monogr. 2015:60–63. 2015. View Article : Google Scholar : PubMed/NCBI

69 

Pober JS: Just the FACS or stalking the elusive circulating endothelial progenitor cell. Arterioscler Thromb Vasc Biol. 32:837–838. 2012. View Article : Google Scholar : PubMed/NCBI

70 

Manzoni M, Comolli G, Torchio M, Mazzini G and Danova M: Circulating endothelial cells and their subpopulations: Role as predictive biomarkers in antiangiogenic therapy for colorectal cancer. Clin Colorectal Cancer. 14:11–17. 2015. View Article : Google Scholar : PubMed/NCBI

71 

Ge YZ, Wu R, Lu TZ, Xin H, Yu P, Zhao Y, Liu H, Xu Z, Xu LW, Shen JW, et al: Circulating endothelial progenitor cell: A promising biomarker in clinical oncology. Med Oncol. 32:3322015. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

June 2016
Volume 4 Issue 6

Print ISSN: 2049-9450
Online ISSN:2049-9469

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
APA
Danova, M., Comolli, G., Manzoni, M., Torchio, M., & Mazzini, G. (2016). Flow cytometric analysis of circulating endothelial cells and endothelial progenitors for clinical purposes in oncology: A critical evaluation (Review). Molecular and Clinical Oncology, 4, 909-917. https://doi.org/10.3892/mco.2016.823
MLA
Danova, M., Comolli, G., Manzoni, M., Torchio, M., Mazzini, G."Flow cytometric analysis of circulating endothelial cells and endothelial progenitors for clinical purposes in oncology: A critical evaluation (Review)". Molecular and Clinical Oncology 4.6 (2016): 909-917.
Chicago
Danova, M., Comolli, G., Manzoni, M., Torchio, M., Mazzini, G."Flow cytometric analysis of circulating endothelial cells and endothelial progenitors for clinical purposes in oncology: A critical evaluation (Review)". Molecular and Clinical Oncology 4, no. 6 (2016): 909-917. https://doi.org/10.3892/mco.2016.823