• circulating tumor cells (CTCs);
  • circulating tumor stem cells (CTSCs);
  • breast cancer;
  • multiparameter flow cytometry;
  • sensitivity;
  • specificity;
  • overall survival (OS)


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited

We wanted to demonstrate the value of multiparameter flow cytometry in detecting human tumor cells of breast cancer (BC) (SKBR-3) in normal peripheral blood. In addition, we investigated a cluster of patients to compare the overall survival (OS) between advanced BC patients [circulating tumor cells (CTCs) ≥5 group] and limited BC patients (CTCs <5 group). SKBR-3 human BC cells were serially diluted in normal whole blood to demonstrate the sensitivity of multiparameter flow cytometry for detecting CTCs, and we also compared the specificity with reverse transcriptase polymerase chain reaction (RT-PCR) method. On the other hand, we detected CTCs among 45 patients by multiparameter flow cytometry. OS was calculated by the Kaplan-Meier product limit method, and compared it between CTCs <5 and CTCs ≥5 groups with the log-rank test. Cox regression models were fitted to determine the associated factors on survival. Human BC cells (SKBR-3) could be differentiated from normal blood based on the multiple light scatter and cell surface marker expression by multiparameter flow cytometry. The method was found to have a sensitivity limit of 10−5 and was effective for detecting human BC cells in vivo. It also found that this method had a higher specificity compared with RT-PCR. For the retrospective study, the median OS was 95 weeks and 65.5 weeks (P < 0.05, 2-tailed) for patients with CTCs <5 and CTCs ≥5, respectively. Kaplan-Meier was used to analyze the patients' survival with Log Rank P = 0.004 and Breslow P = 0.003, which showed that these two groups had statistically significant difference. Cox regression analysis was performed, and we found CTCslevels, metastasis and age (P < 0.05) were three relative factors for patients' survival. Multiparameter flow cytometry can detect CTCs effectively and has the potential to be a valuable tool for prognosis assessment among BC patients in clinical situations in China. © 2010 International Society for Advancement of Cytometry

Breast Cancer (BC) is the most common cancer in women in developed countries. In developing countries, such as China, the incidence of BC is currently increasing, particularly in the larger cities (1). In many patients with solid tumors of epithelial origin, circulating cells with the characteristics of tumor cells can be identified in the peripheral blood that is known as circulating tumor cells (CTCs). These cells are present not only in patients with metastatic disease but also in those whose tumors are apparently localized (2). There may be intermittent shedding of tumor cells into the circulation corresponding with micro-invasive events within the tumor. The first phase of the metastatic cascade consists of loss of tumor cell adhesion, induction of cell motility, and local tumor cell invasion (3). These steps are followed by either dissemination to regional lymph nodes or circulation through the blood, and homing to secondary organs, where the tumor cells may reside as viable cells in a “dormant” state (4). Some of these cells eventually become precursors of metastases that can arise many years after curative resection of the primary tumor (5). Although apoptosis contributed to a high rate of circulating cells, only a small part of the cells can adhere in organs through blood vessels that were named as circulating tumor stem cells (CTSCs) (6).

CTCs cells can be selected with the fluorescent antibody that linked to a monoclonal antibody directed against CD45 for negative selection of leukocytes (7–9). From these cluster cells, Ep-CAM (epithelial-cell adhesion molecule) and Cytokeratin 8,18,19 (Cytokeratin 8,18,19-phycoerythrin staining) positive cells are the target cells as these two monoclonal antibodies can be adhered in epithelial cells. Given the multistep nature of the metastatic cascade, there should be several opportunities for early identification and therapeutic targeting of metastatic cells.

In the past, various immunologic procedures, including immunocytology- and immunohistochemistry-based methods, and reverse transcriptase polymerase chain reaction (RT-PCR), have been used to detect systemic tumor cell contamination (10–14). Most current methods do not seem to be sensitive or specific enough to detect circulating cells in significant numbers of patients with carcinomas (15–17). Recently, a major advance in this area occurred with the advent of flow cytometry, which makes possible the detection of CTCs in a good balance of sensitivity and specificity. In addition, the simple procedure and lower cost have made it possible to apply in clinical situations.

The aim of this study was twofold. First, we wish to evaluate our new multiparameter flow cytometric methodology and compare it with conventional RT-PCR. Second, we wish to further evaluate the overall survival (OS) between advanced breast cancer (ABC) patients, who had CTCs ≥5, and limited breast cancer (LBC) patients, which was CTCs <5 in Chinese patients with multiparameter flow cytometry.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited


A prospective study was conducted to evaluate the clinical utility of CTCs levels in patients who were being treated in the Union Hospital in Wuhan. Forty-five patients with BC and three other healthy people were enrolled between September 2006 and June 2008. Additional criteria for inclusion was informed consent. Twenty patients had no sign of overt metastasis at the time of primary diagnosis and have been evaluated for further clinical follow-up. Twenty-five patients had overt metastases at diagnosis and have been considered as a positive reference group which was also follow-up group. The follow-up groups were characterized as follows: mean age at diagnosis was 50 years (range, 32–74 years). None of the patients had a history of previous cancer. Details on clinicopathologic data (e.g., histopathology of carcinoma, tumor stage, lymph node status, and grading) are shown in Table 1. All of these patients had systemic therapy including 12 patients adopting cytokine-induced killer cells therapy (CIK). Before the initiation of therapy in our hospital, patients had imaging evaluation (including computed tomography scans of chest and abdomen) of their tumor size and sites. We also took a baseline blood draw for enumeration of CTCs.

Table 1. Patient characteristics
 AllCTC <5(n=27)CTC ≥5(n=18) 
  1. ALND, axillary lymph node dissection.

  2. a

    The P-value of TNM Stage and Metastasis groups are < 0.05. There are obvious statistically significant differences in different TNM Stages, and between Metastasis and non-metastasis.

Age, years
TNM Stage
Primary tumor sites
 Left breast2453.31458.31041.70.807
 Right breast2146.71361.9838.1 
Clinical pathology
 Infiltrating ducta2862.21760.71139.30.921
 Mucous cancer12.21100.000.0 
Diameter of tumor
 ≤2.0 cm1328.9961.5430.70.522
 2.0–5.0 cm2760.01659.31140.7 
 >5.0 cm511.1240.0360.0 

Cell Line

Carcinoma cell lines SKBR-3 (breast) maintained in RPMI 1640 plus 10% fetal calf serum were used to evaluate the sensitivity and specificity of the method and as positive control cells.


Antibodies that recognize white bloods cells used for multiparameter flow cytometry were as follows: anti-CD45-PerCP, Ep-CAM, and Cytokeratin 8,18,19 (Cytokeratin 8,18,19-phycoerythrin staining) from Becton Dickinson, USA.

Preparation of Blood and Samples

Approximately 20-mL EDTA-blood was drawn by vein puncture from 45 patients with BC treated in our hospital and three healthy volunteers. The blood of the healthy volunteers were used to evaluate the sensitivity and specificity and as negative control cells. To avoid contamination with skin cells, 5 mL blood was discarded before the study samples were taken. Blood samples were prepared as previously described (18). Briefly, the mononucleocytes were separated from the blood over Ficoll-Paque (Haoyang biological production, Tianjin, China) for 20 min with 1800g at 4°C. The interface cells were then removed and washed, and the RBCs were removed using a lysis buffer followed by a repeated wash. The mononuclear cells were then counted and aliquot for RT-PCR and multiparameter flow cytometry on the basis of at least 2–3 × 106 cells for each methodology. The cell pellet was resuspended in phosphate-buffered saline for multiparameter flow cytometry and in Trizol reagent (Invitrogen, UK), which was kept at −70°C until RNA extraction for RT-PCR.

Flow Cytometry

After separated from the blood over Ficoll-Paque, mononucleocytes were washed twice with sterile PBS. The isolated cells were then labeled monoclonal antibodies that target epithelial cell antigens (CD45−, Ep-CAM+, Cytokeratin 8,18,19+), maintained in dark at 4°C for 30 min. We added monoclonal antibodies anti-CD45-PerCP 20 μL, Ep-CAM-PE 20 μL, and Cytokeratin 8,18,19-FITC 20 μL per 7.5 mL whole blood. Cell pellets were resuspended in 250 μL PBS and then enumerated by FACS Caliber™ (Becton Dickison, USA).

To evaluate the sensitivity and specificity of the method (tumor cells recovery), SKBR-3 BC cells were used. Cells were counted after trypsinization and using a Neubauer chamber, and then 1, 10, 50, and 500 cells were spiked, respectively, into 7.5 mL of blood from a healthy person. Blood was processed as described for samples. To accurately estimate the number of cells spiked into the blood, we controlled the volume of the cell suspension liquid to be the same for every specimen. The average number of Ep-CAM and cytokeratin 8,18,19 positive cells on FACS Caliber™ was used to calculate the cell recovery.


RNA was extracted from 1 mL Trizol which had been kept at −70°C. After thawing, add 0.2 mL chloroform to the tube after centrifugation at 12,000g for 15 min at 4°C; the supernatants that contained the intact RNA was removed to a new tube, then precipitating RNA with 0.5 mL isopropyl alcohol, and washing with 75% ethanol, the RNA was dissolved in 10 μL RNase-free water, and measured by spectrophotometer analysis at 260 nm. RNA from mononuclear cells was transcribed to cDNA by a reverse transcriptase in a total 10 μL RT reaction solution containing 2 μL 5× Reverse Transcriptase Buffer, 1 μL dNTP (10 mM each), 0.25 μL RNase Inhibitor (10 U), 1 μL Oligo (dT)15 Primer (25 pmol), 5.25 μL RNase-free water containing RNA (>0.5 μg), and 0.5 μL Avian myeloblastosis virus (AMV) Reverse Transcriptase (5 U) (TaKaRa, China). The resulting cDNA was subjected to PCR amplification. PCR was composed of 2 μL cDNA, 10 μL Mix, 2 μL primer of Ep-CAM, 6 μL H2O in a total volume of 20 μL. The primer of Ep-CAM was as follows: 5′-GGACCTGACAG TAAATGGGGAAC-3′; 5′-CTCTTCTTTCTGGAAATAACCAG CAC-3′ (19). GAPDH mRNA primer was designed by primer 5.0 and the primer detail was as follows: 5′-TGCACCAC CAACTGCTTAGC-3′; 5′-GGAGGCAGGGATGATGTTCT-3′. The reaction condition was first 95°C for 2 min to activate Taq DNA polymerase, followed by denaturation at 94°C for 30 s, annealing 58°C for 30 s, and extension 72°C for 30 s. The PCR was run for 35 cycles, and finally elongated 72°C for 7 min. The PCR products were detected by ethidium bromide staining on a 1% agarose gel.

Statistical Analysis

Titration experiments were performed on three separate occasions. Correlation, regression analysis, and a Mann-Whitney rank sum test were performed on each dataset. Patient characteristics were tabulated and compared across CTC groups by chi-square test as appropriate. OS was calculated from the date of CTC measurement to the date of death or last follow-up and was estimated using the Kaplan-Meier product limit method and compared across groups using the log-rank test. All statistical tests were two-sided, and P values <0.05 were considered statistically significant. Analyses were performed by using the SPSS 13.0.


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited

Sensitivity and Specificity


Analysis of serial dilutions (0.0001%, 0.001%, 0.005%, 0.05%) of human SKBR-3 tumor cells in normal human blood demonstrated that the lower detection limit for sensitivity of the method was 0.001%, or 10−5, equivalent to one human cell per 100,000 white blood cells (Figs. 1a–1d). Below this level, background events were in an unpredictable fashion. Recovery and linearity were highly reproducible across three separate experiments (Fig. 1e), and the number of tumor events recovered could be positively correlated with the number of tumor events expected based on the serial dilutions (R2 = 0.997). The percentage of tumor cells recovered was not significantly different from the percentage of tumor cells expected based on the serial dilutions (P > 0.6, Mann-Whitney rank sum test).

thumbnail image

Figure 1. The ability to detect human tumor SKBR-3 cells in normal blood by cytomentry is titratable down to a sensitivity of 0.001%. Human tumor cells concentration was normalized adding to the leukocyte count, and serial dilutions (0.0001%, 0.001%, 0.005%, 0.05%) using normal mononucleocytes as the diluent. Samples were lysed, incubated with anti-CD45-PerCP (20 μl), EpCAM (20 μl) and Cytokeratin8, 18, 19 (20 μl) at 4 degrees for 30 minutes, and resuspended in 250 μl PBS before multiparameter flow cytometric analysis. For samples with normal blood cells, up to 1,000,000 total events were collected. Events that fell within the right region were counted as meeting the criteria for SKBR-3 tumor cells (CD45-EpCAM+CK+). Representative SKBR-3 cells are shown for (a) 0.0001% (b) 0.001% (c) 0.005%, (d) 0.05%. (e) Correlation and regression analysis of recovered versus expected number of positive tumor events at dilutions significant at the 0.01 level (2-tailed, R2 = 0.997, three separate experiments.). The percentage of tumor cells recovered was not significantly different from the percentage of tumor cells expected based on the serial dilutions (P > 0.6, Mann-Whitney rank sum test).

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When compared with RT-PCR, multiparameter flow cytometry for this research contributed a higher specificity. We chose six samples including three typical ABC patients (CTCs ≥5) and three LBC patients (CTCs <5) to detect the expression of Ep-CAM. The results (in Fig. 2) showed that six samples were found positive for Ep-CAM, not only three ABC but also three LBC samples. The LBC positive samples had nearly the same representation with the ABC samples. So, it is hard to distinguish LBC with ABC. However, flow cytometry can identify the two groups clearly and quantifiably.

thumbnail image

Figure 2. RT-PCR assay for EpCAM mRNA (a) and GAPDH mRNA (b). 1. DNA ladder; 2. negative control (H2O); 3. positive control (SKBR-3 cells); 4.5.6. ABC samples; 7.8.9. LBC samples. All were positive. Size of EpCAM and GAPDH is 186bp and 177bp, respectively.

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Patient Characteristics

Forty-five patients were identified and included in this analysis (Detail was shown in Table 1); 27 (60.0%) patients and 18 (40.0%) patients had CTCs levels <5 and ≥5, respectively. The age of the patients ranged from 32 to 74 years (median 50). The median age at diagnosis for patients with CTCs levels <5 and ≥5 was 49 years (range, 32–72 years) and 51 years (range, 37–74 years), respectively. Twenty-five (55.6%) patients had metastasis including 10 (22.2%) and 15(33.3%) patients had CTCs levels <5 and ≥5, respectively, whereas 20 (44.4%) patients were no metastasis including 17 (37.8%) and 3 (6.7%) patients had CTCs levels <5 and ≥5, respectively. Chi-square test analyses showed that there was statistically significant difference (P = 0.002) in the proportion of patients with <5 and ≥5 per 7.5 mL of blood between the metastasis group and no metastasis group. There was also statistical difference (P = 0.033) in the proportion of patients with <5 and ≥5 within different TNM stage. It shows that more patients in Stage I, Stage II, and Stage III were in CTCs <5 group compared with CTCs ≥5 group. However, patients in Stage IV contribute more percentage in CTCs ≥5 group. Statistical difference exists in axillary lymph node dissection (ALND) patients or not with different CTCs levels (P = 0.143). There was no statistically significant difference in age, primary tumor sites, clinical pathology, and diameter of tumor with CTCs levels <5 and ≥5 groups (P > 0.05).

Survival Analysis

At the time of last follow-up, 17 (37.8%) patients had died including six (13.3%) patients in CTCs <5 group and 11 (24.5%) patients in CTCs ≥5 group. The median follow-up among all patients was 82.0 weeks (95% confidence interval [CI] 47.70 weeks to 116.305 weeks). The median survival for patients with CTCs <5 and ≥5 was 95.0 weeks (Std. Deviation, 18.67 weeks) and 65.5 weeks (Std. Deviation, 30.0 weeks). ALND had correlation with CTCs level (P = 0.143) and 45.7% ALND patients had CTCs ≥5. During the follow-up, 11 (24.4%) patients lost contact, with seven (15.6%) in <5 CTCs and four (8.9%) in ≥5 CTCs group. Kaplan-Meier was used to analyze the patients' survival (Fig. 3) with Log Rank P = 0.004 and Breslow P = 0.003, both showed that these two groups had statistically significant difference. The population with fewer than 5 CTCs showed significantly higher OS than the group with 5 or more CTCs in Figure 3.

thumbnail image

Figure 3. Kaplan-Meier Plots of overall survival are shown for all patients during the follow-up. 27 patients in CTCs <5 group and the median survival is estimated to be 95 weeks. 18 patients in CTCs ≥ 5 group and the median survival is 65.5 weeks. P value is 2-tailed. Logrank indicates the P value. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley. com.]

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In addition, we performed a Cox regression analysis for the follow-up and the significant level is 0.05. The results (in Table 2) showed that the variables entered in the model, CTCs level (P = 0.041), age of the patients (P = 0.001), metastasis (P = 0.002) retained statistical significance in the multivariate analysis. So the status of a patient whether expired or not was correlated with three factors: CTCs level, age, and metastasis.

Table 2. Cox regression analysis results
     95.0% CI for expb
  1. The P-value of CTCs level, age and metastasis are <0.05, which retained statistical significance in the multivariate analysis.


Therefore, multiparameter flow cytometry technique is capable enough to identify BC patients and assess the progression of disease.


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited

The study of detecting disseminated BC cells in human blood using multiparameter flow cytometric approaches rely on the expression of epithelial-specific markers, such as cytokeratins, which are expressed on epithelial cells but not on leukocytes (2, 5, 20). In particular, cells of higher metastatic potential may lose expression of epithelial-specific markers during the course of metastatic progression (21–24). To avoid possible false-negative, we also chose another epithelial-specific marker: Ep-CAM (25). To detect the tumor cells that come from epithelium tissue, a monoclonal antibody directed against CD45 for negative selection of leukocytes was used (7–9). Therefore, the detection of dual-positive cells (CD45-Ep-CAM+CK+) is expected (such as in the peripheral blood) and has been proposed as a surrogate marker for epithelial tumor cells. BC cells in epithelial blood could be represented. The sensitivity of the assay can be assessed by analysis of serial dilutions of a breast-cancer cell line (SKBR-3) in blood from a healthy volunteer. Because the target population in prospective test samples is anticipated to be in the range of no more than 0.5%, by using all the information generated by the three fluorescence parameters and light scattering, it was possible to decrease the likelihood of a nonspecific event fulfilling the criteria of a target event to very low levels.

From the results of the multiparameter flow cytometric analysis and statistics of three separate serial dilutions experiments, it is easy to see that flow cytometric method had high sensitivity. When compared with RT-PCR method, it has more specificity although RT-PCR method had a higher sensitivity which is the detection of single epithelial cells in up to 107 peripheral blood mononuclear cells (8, 9, 26, 27). However, for nucleic acid techniques, in vitro sensitivity expressed in this way may overestimate the in vivo sensitivity of such assays because the tumor cells may crack and membrane fragments or nucleic acid in blood generally expressing markers remain. Furthermore, inhibitors of the PCR reaction present in tissues and body fluids could limit the in vivo sensitivity of nucleic acid-based techniques. CTCs of the patients that cannot be detected through multiparameter flow cytometric methods had Ep-CAM expression with RT-PCR, and there was no obvious difference of representation between CTCs ≥5 group and CTCs <5 group through RT-PCR. Therefore, in comparative studies, RT-PCR has higher rates of positive than flow cytometric assays. To make sure of the specificity of multiparameter flow cytomety technique, it is important to discard the first few milliliters of sampled blood.

Most researchers have used immunomagnetic combining flow cytometry technique to detect CTCs. However, it always loses an amount of target cells that would have a higher false negative and it is more expensive and multiple process that could not be applied in clinical reality. Additionally, although false-positive are often problematic with imaging or the use of tumor markers, the data from our study showed that patients in stage I, there were no more than 2 CTCs. Budd et al. (28) found that CTCs levels detected disease progression more accurately than imaging. Bone marrow biopsy is traumatic, whereas multiparameter flow cytomety which is atraumatic can be accepted by patients. On account of the above, we chose multiparameter flow cytometry as the appropriate technique.

The primary goal of this retrospective study was to confirm the prognostic value of CTCs in a cluster of patients by multiparameter flow cytometry method in China. This study demonstrated significantly reduced survival for patients with a baseline of ≥5 CTCs. The result suggests that the OS was independent of clinical pathology and diameter of tumor but correlated with age, CTCs level, and metastasis. For the variable of age, four patients who were more than 70 died during the follow-up including three of them who had CTCs ≥5 and two of them also had distinct metastasis. For the variable of CTCs level, in our study, the patients with ≥5 CTCs/7.5 mL of blood had a poorer median OS (65.5 weeks vs. 95 weeks; P < 0.05) compared with patients with <5 CTCs. Although Cristofanilli et al. (29) also observed that patients with ≥5 CTCs/7.5 mL of blood had poorer median OS (10.9 months vs. 21.9 months; P < 0.0001) compared with patients with <5 CTCs. The results of the current study strengthen the validity of previous finding. This outcome implied that measuring CTCs may provide significant value for clinical evaluation and for determining treatment options for patients.

From the outcome of our trial, CTCs can be considered an effective marker for prognosis, and multiparameter flow cytometry test could have great value for patients in China. By multiparameter flow cytometry test, patients who had CTCs <5 can be considered as micro-metastasis that could be treated by synthetic therapy to contain the development of disease, whereas, for the patients who do not have detected CTCs, there is no need to intensify treatments, avoiding the side effect of chemotherapy. However, larger studies are required to definitely establish the clinical usefulness of the technique. Moreover, we wish to isolate the CTSCs which have the marker of CD44+CD24-ESA-expressing and inject CTSCs into the peripheral blood of mice to create a model imitating the progression of BC in human. In conclusion, we have established a good foundation for following research.


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited

Multiparameter flow cytometry can detect CTCs effectively and has the potential to be a valuable tool for prognosis assessment among BC patients in clinical situations in China.


  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited

The authors thank the department of oncology and cell therapy in Union Hospital for providing samples.

Literature Cited

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. Literature Cited
  • 1
    Gao YT,Shu XO,Kushi LH,Ruan Z,Bostick RM,Jin F,Zheng W. Association of menstrual and reproductive factors with breast cancer risk: Results from the Shanghai breast cancer study. Int J Cancer 2000; 87: 295300.
  • 2
    Ring A,Smith IE,Dowsett M. Circulating tumor cells in breast cancer. Lancet Oncol 2004; 5: 7988.
  • 3
    Birchmeier C,Birchmeier W,Gherardi E,Vande Woude GF. Met, metastasis, motility and more. Nat Rev Mol Cell Biol 2003; 4: 915925.
  • 4
    Uhr JW,Scheuermann RH,Street NE,Vitetta ES. Cancer dormancy: Opportunities for newtherapeutic approaches. Nat Med 1997; 3: 505509.
  • 5
    Pantel K,Brakenhoff RH. Dissecting the metastatic cascade. Nat Rev Cancer 2004; 4: 448456.
  • 6
    Blaqosklonny MV. Target for cancer therapy: Proliferating cells or stem cells. Cancer 2006; 20: 385391.
  • 7
    Martin VM,Siewert C,Scharl A, Harms T, Heinze R, Ohl S, Radbruch A, Miltenyi S, Schmitz J. Immunomagnetic enrichment of disseminated epithelial tumor cells from peripheral blood by MACS. Exp Hematol 1998; 26: 252264.
  • 8
    Pachmann K,Heiss P,Demel U,Tilz G. Detection and quantification of small numbers of circulating tumour cells in peripheral blood using laser scanning cytometer (LSC). Clin Chem Lab Med 2001; 39: 811817.
  • 9
    Naume B,Borgen E,Beiske K, Herstad TK, Ravnas G, Renolen A, Trachsel S, Thrane-Steen K, Funderud S, Kvalheim G. Immunomagnetic techniques for the enrichment and detection of isolated breast carcinoma cells in bone marrow and peripheral blood. J Hematother 1997; 6: 103114.
  • 10
    Ross AA,Cooper BW,Lazarus HM, Mackay W, Moss TJ, Ciobanu N, Tallman MS, Kennedy MJ, Davidson NE, Sweet D. Detection and viability of tumor cells in peripheral blood stem cell collections from breast cancer patients using immunocytochemical and clonogenic assay techniques. Blood 1993; 82: 26052610.
  • 11
    Mesker WE,vd Burg JM,Oud PS,Knepfle CF,Ouwerkerk-v Velzen MC,Schipper NW,Tanke HJ. Detection of immunocytochemically stained rare events using image analysis. Cytometry 1994; 17: 209215.
  • 12
    Pelkey TJ,Frierson HFJr,Bruns DE. Molecular and immunological detection of circulating tumor cells and micrometastases from solid tumors. Clin Chem 1996; 42: 13691381.
  • 13
    Schulze R,Schulze M,Wischnik A, Ehnle S, Doukas K, Behr W, Ehret W, Schlimok G. Tumor cell contamination of peripheral blood stem cell transplants and bone marrow in high-risk breast cancer patients. Bone Marrow Transplant 1997; 19: 12231228.
  • 14
    Cote RJ,Beattie EJ,Chaiwun B, Shi SR, Harvey J, Chen SC, Sherrod AE, Groshen S, Taylor CR. Detection of occult bone marrow micrometastasis in patients with operable lung carcinoma. Ann Surg 1995; 4: 415425.
  • 15
    Allan AL,Vantyghem SA,Tuck AB,Chambers AF,Chin-Yee IH,Keeney M. Detection and quantification of circulating tumor cells in mouse models of human breast cancer using immunomagnetic enrichment and multiparameter flow cytometry. Cytometry Part A 2005; 65A: 414.
  • 16
    Leather AJ,Gallegos NC,Kocjan G, Savage F, Smales CS, Hu W, Boulos PB, Northover JM, Phillips RK. Detection and enumeration of circulating tumour cell in colorectal cancer. Br J Surg 1993; 80: 777780.
  • 17
    Rosenberg R,Gertler R,Friederichs J,Fuehrer K,Dahm M,Phelps R,Thorban S,Nekarda H,Siewert JR. Comparison of two density gradient centrifugation systems for the enrichment of disseminated tumor cells in blood. Cytometry 2002; 49: 150158.
  • 18
    Slade MJ,Smith BM,Sinnett HD, Cross NC, Coombes RC. Quantitative polymerase chain reaction for the detection of micrometastases in patients with breast cancer. J Clin Oncol 1999; 17: 870879.
  • 19
    Raynor M,Stephenson S-A,Walsh DCA, Henderson MA, Dobrovic A. Optimisation of the RT-PCR detection of immunomagnetically enriched carcinoma cells. BMC cancer 2002; 5: 14711480.
  • 20
    Moll R. Cytokeratins in the histological diagnosis of malignant tumors. Int J Biol Markers 1994; 9: 6369.
  • 21
    Schaller G,Fuchs I,Pritze W,Ebert A,Herbst H,Pantel K,Weitzel H,Lengyel E. Elevated keratin 18 protein expression indicates a favorable prognosis in patients with breast cancer. Clin Cancer Res 1996; 2: 18791885.
  • 22
    Fuchs IB,Lichtenegger W,Buehler H,Henrich W,Stein H,Kleine-Tebbe A,Schaller G. The prognostic significance of epithelial-mesenchymal transition in breast cancer. Anticancer Res 2002; 22: 34153419.
  • 23
    Gotzmann J,Mikula M,Eger A,Schulte-Hermann R,Foisner R,Beug H,Mikulits W. Molecular aspects of epithelial cell plasticity: Implications for local tumor invasion and metastasis. Mutat Res 2004; 566: 920.
  • 24
    Thiery JP. Epithelial-mesenchymal transitions in tumour progression. Nat Rev Cancer 2002; 2: 442454.
  • 25
    Racila E,Euhus D,Weiss AJ, Rao C, McConnell J, Terstappen LW, Uhr JW. Detection and characterization of carcinoma cells in the blood. Proc Natl Acad Sci USA 1998; 95: 45894594.
  • 26
    Gross HJ,Verwer B,Houck D, Hoffman RA, Recktenwald D. Model study detecting breast cancer cells in peripheral blood mononuclear cells at frequencies as low as 10(-7). Proc Natl Acad Sci USA 1995; 92: 537541.
  • 27
    Palomares MR,Richardson-Lander A,Koehler KM, Gralow JR, Sabath DE. Quantitative real-time RT-PCR for the detection of circulating breast cancer cells: Correlation with stage and treatment. In: Proceedings of 26th Annual San Antonio Breast Cancer Symposium, 2002; abstract 217.
  • 28
    Budd GT,Cristofanilli M,Ellis MJ, Stopeck A, Borden E, Miller MC, Matera J, Repollet M, Doyle GV, Terstappen LW, Hayes DF. Circulating tumor cells versus imaging—predicting overall survival in metastatic breast cancer. Clin Cancer Res 2006; 12: 64036409.
  • 29
    Cristofanilli M,Budd GT,Ellis M, Stopeck A, Matera J, Miller MC, Reuben JM, Doyle GV, Allard WJ, Terstappen LW, Hayes DF. Circulating tumor cells predict progression free survival and overall survival in metastatic breast cancer. N Engl J Med 2004; 351: 781791.