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Minimal residual disease and circulating tumor cells in breast cancer


Tumor cell dissemination in bone marrow or other organs is thought to represent an important step in the metastatic process. The detection of bone marrow disseminated tumor cells is associated with worse outcome in early breast cancer. Moreover, the detection of peripheral blood circulating tumor cells is an adverse prognostic factor in metastatic breast cancer, and emerging data suggest that this is also true for early disease. Beyond enumeration, the characterization of these cells has the potential to improve risk assessment, treatment selection and monitoring, and the development of novel therapeutic agents, and to advance our understanding of the biology of metastasis.


Breast cancer (BC) is the most common cancer in women in Europe [1]. Despite surgery and adjuvant systemic therapy, many women with early BC still relapse and die of their disease. Minimal residual disease (MRD) after potentially curative surgery for BC is thought to contribute to disease relapse and to be the target of adjuvant treatment. MRD is defined as micrometastatic cells undetectable by conventional imaging and laboratory tests. Surrogates of MRD are tumor cells detected in the bone marrow (disseminated tumor cells (DTCs)) and peripheral blood (circulating tumor cells (CTCs)) [2]. The detection and characterization of DTCs/CTCs are expected to lead to personalized treatment strategies and accelerate the development of novel therapeutic agents for BC [2]. Furthermore, genotypic and phenotypic characterization of DTCs/CTCs at the single cell level may provide novel insights into the biology of tumor progression [3].

Detection methods

The detection of DTCs/CTCs in BC is challenging since these cells are rare, occurring at a frequency of one tumor cell per 106 to 107 mononuclear cells. To isolate DTCs/ CTCs, enrichment techniques are therefore typically applied. These techniques are based either on the physical properties of the cells (for example, cell density by ficoll centrifugation or cell size by filtration) or on their immunological characteristics (for example, cell surface antigens of DTCs/CTCs by immunoenrichment or markers of hematopoietic cells by immunodepletion). Ficoll centrifugation was widely used in the initial clinical studies of bone marrow DTCs [4]. Currently, however, enrichment techniques incorporating immunomagnetically labeled monocolonal antibodies are more often used because they improve tumor cell recovery (recovery rates of >50% to 85%) [5, 6] over ficoll enrichment (recovery rate of 40%) [7] in spiking experiments using cell lines. After the initial enrichment step, DTCs/CTCs have been detected using assays based on either antibodies (immunocytochemistry, immunofluorescence) or nucleic acids (mRNA transcripts by reverse transcription PCR (RT-PCR)). Table 1 summarizes the main technologies for CTC detection in breast cancer.

Table 1 Technologies for circulating tumor cell detection in breast cancer

Antibody-based assays

Since there are no universal tumor-specific antigen/ genes, epithelial-specific antigens, including cytokeratins (CKs), epithelial cell adhesion molecule (EpCAM), and growth factor receptors (for example, human epidermal growth factor receptor (HER2)), have been used as markers of choice for the detection of DTCs/CTCs. In consensus meetings, the use of appropriate staining controls, directly labeled fluorescent monoclonal anti-bodies, identification of DTCs/CTCs based on cyto-morphologic criteria/phenotypic features, and validation by two independent observers have been suggested as measures to reduce false-positive results [8, 9].

CellSearch® (Veridex, Warren, NJ, USA) is an automated enrichment and immunostaining system for CTC detection that uses microscopic ferrofluids coated with an antibody against EpCAM to magnetically separate epithelial cells from whole blood [10]. Captured cells are stained with antibodies specific for cytokeratins 8, 18 and 19 (pan-CK) and CD45 (specific for leucocytes) and stained with 4'6-diamidino-2-phenylindole-2 (DAPI; to confirm the presence of a cell nucleus). A CTC is defined as a cell staining for pan-CK and DAPI, but not for CD45. Currently, CellSearch® is the only technology that has received US Food and Drug Administration (FDA) approval for CTC detection as an aid in monitoring patients with metastatic breast, colorectal and prostate cancer [1012]. The performance of CellSearch® for CTC detection in metastatic solid tumors has also been validated in ring studies [13, 14].

Other technologies include the MagSweeper, which uses immunomagnetic separation and gently enriches target cells by 108-fold from blood, eliminating cells that are not bound to magnetic particles [6]. This process has been shown to keep cell function intact and not to perturb rare cell gene expression [6]. CTCs have been also detected using multi-parameter flow cytometry, and their detection with this technology was associated with poor outcome in women with BC [15]. MAINTRAC®, another method, detects circulating epithelial tumor cells from whole unseparated blood, and uses a laser scanning cytometer after staining with anti-human epithelial and anti-CD45 fluorescent antibodies [16]. This technology results in CTC counts up to 105 per milliliter of blood in all women with early BC, consequently raising concerns about the specificity of the method to detect tumor cells [16].

Advances in optical technologies have also improved DTC/CTC detection. Several slide-based automated microscopic scanning devices, such as the Ikoniscope® [17] and the Ariol® system [18, 19], have been applied for standardized micrometastatic cell detection and characterization. Another approach has been developed that uses fiber-optic array scanning technology (FAST) for rare cell detection [20]. It has been demonstrated that FAST cytometry is capable of a 500-fold increase in speed over automated digital microscopy, with comparable sensitivity and superior specificity [20]. The combination of FAST and automated digital microscopy has allowed investigators to detect rare epithelial cells from whole unseparated blood after immunofluorescence staining with a pan-CK antibody.

Nucleic acid-based assays

Nucleic acid-based assays have been initially hampered by false-positive results due to inability to assess tumor cell morphology, expression of target genes in normal cells, and the presence of pseudogenes (genes without protein-coding abilities) [21]. Newer quantitative assays have addressed some of these problems. To detect DTCs/ CTCs in breast cancer, nucleic acid-based assays, either as single genes or as part of multiplex assays [2227], have mainly used CK19, mammaglobin-A (MGB1), HER2 and mucin 1 (MUC1) mRNA. The AdnaTest® BreastCancerSelect (AdnaGen AG, Langenhagen, Germany) is a commercially available molecular assay that utilizes immuno-magnetic separation with antibodies against MUC1 and EpCAM followed by a multiplex RT-PCR for HER2, MUC1 and EpCAM [28].

Emerging detection technologies

Beyond immunomagnetic separators, microfluidic devices have been developed for rare cell tumor capture, and these involve non-electrokinetic methods, such as immo-bilization via antibody [29] and size-based sorting [30, 31], or electrokinetic methods (for example, dielectrophoresis) [32]. An example of a microfluidic platform is the 'CTC-chip', which is capable of efficient and selective separation of viable CTCs from peripheral whole blood samples, mediated by the interaction of target CTCs with EpCAM-coated microposts under precisely controlled laminar flow conditions [29]. A direct comparison between CellSearch® and two commercially available CTC-chips showed that these platforms provided similar sensitivity and yield in patient samples [33]. Stott and colleagues [34] recently reported improved sensitivity of the CTC-chip for CTC detection in patients with localized prostate cancer.

Several other assays have also been developed. For example, a technique named EPISPOT (epithelial immunospot) allows detection of viable DTCs and CTCs owing to their ability to secrete individual proteins after 48 hours of short-term culture [35]. A functional cell separation method called CAM, or the collagen adhesion matrix assay, was reported to detect CTCs with the invasive phenotype and to explore their molecular features [36]. Beyond these assays, new imaging procedures have been developed for the in vivo detection of CTCs [37].

Several investigators have also evaluated the potential utility of circulating cell-free DNA, either as a surrogate to monitor MRD [38], or as a 'liquid biopsy' for real-time monitoring of tumor mutations in cancer patients [39]. Moreover, some investigators have been able to identify patient-specific genomic rearrangements in plasma-circulating DNA as a way to monitor MRD [40]. They employed next-generation sequencing to rapidly identify patient-specific genomic rearrangements in primary tumors and showed that PCR assays could reliably detect these rearrangements in plasma [40]. A recent review has summarized advances in cell-free nucleic acids (DNA, mRNA, microRNA) as potential biomarkers in cancer [41].

Critical interpretation of detection technologies

The different technologies use different enrichment and detection steps and therefore do not always detect the same CTC population (Table 1). In a study comparing two commercially available assays (CellSearch® and AdnaTest®) in the same metastatic BC patient samples, the concordance between the two assays was 64% for CTC detection and 50% for HER2- positive CTC detection [42]. Therefore, it is important to study the clinical utility of the assay-dependent CTC detection and characterization. Moreover, most enrichment methods used by the different assays are biased because they result in loss of a fraction of CTCs due to tumor cell heterogeneity. As an example, some available technologies detect only EpCAM+ CTCs (Table 1). However, it has been shown that BC cell lines with low EpCAM expression and high expression of mesenchymal markers cannot be efficiently captured using a purely EpCAM-based mechanism [33, 43, 44]. Some other technologies are using enrichment based on red blood cell lysis or leukocyte depletion (CD45-negative depletion) aiming at a less biased CTC enrichment (Table 1). Another critical issue with all cell detection technologies is that blood cannot be stored and must be processed soon after it has been drawn, within up to 72 hours [13] depending on the technology used. Therefore, the clinical validation of CTCs depends on the availability of detection technologies in different labs. This is a major difference between CTCs and biomarkers from paraffin-embedded primary tumor blocks, for which real-time processing is not mandatory. Since all currently available platforms will continue to evolve rapidly, the challenge will be to prospectively evaluate the utility of each technology to address specific clinical questions.

Clinical relevance of DTCs/CTCs

CTCs and DTCs were cited for the first time in the 2007 recommendations of the American Society of Clinical Oncology (ASCO) on tumor markers [45]. Recently, in the 7th edition of the American Joint Committee on Cancer Staging Manual (2010), a new M0(i+) category was proposed for TNM (tumor, node, metastasis) staging in BC [46]. This new category is defined as no clinical or radiographic evidence of distant metastases, but deposits of molecularly or microscopically detected tumor cells (no larger than 0.2 mm) in blood, bone marrow, or other non-regional nodal tissue in a patient without symptoms or signs of metastases.

Clinical relevance of DTCs

The inclusion of the M0(i+) category was driven at least in part by a pooled analysis of individual data from several studies, which showed that bone marrow CK-positive DTCs were detected at the time of surgery in 30.6% of 4,703 patients with invasive BC [4]. Bone marrow DTCs were significantly more frequent in women with larger tumors, or tumors with higher histologic grade, hormone receptor negativity, and lymph node metastasis. In multivariate analysis, the presence of bone marrow DTCs predicted for significantly higher risk of death from BC [4]. Recently, in the American College of Surgeons Oncology Group's (ACOSOG) Z0010 multicenter trial, bone marrow DTCs were identified at surgery by immunocytochemistry in only 105 of 3,491 patients (3%) with clinical T1/T2 N0 M0 BC [47]. Although the DTC detection rate was very low, bone marrow DTCs still significantly predicted decreased overall survival [47]. A pooled analysis of individual patient data from 676 women with stage I-III BC from three studies showed that bone marrow DTCs were detected in 15.5% of patients at a median 37-month follow-up after diagnosis [48]. Th e presence of DTCs was an independent indicator of poor prognosis and could be used to select patients for secondary adjuvant treatment strategies [48].

Clinical relevance of CTCs (CellSearch®)

Using CellSearch®, ≥5 CTCs/7.5 ml of blood were detected in 49% of 177 patients with measurable meta-static BC before a new treatment was started [10]. CTC detection was an independent predictor of progression-free survival and overall survival [10]. This and other studies [4952] have provided solid data about the adverse prognostic value when CTCs are detected by CellSearch® in metastatic BC.

Detecting CTCs in non-metastatic BC is more challenging because these cells occur at a very low frequency in this setting. Pierga and colleagues [53] found ≥1 CTC/7.5 ml in 23% of 97 patients before administrating neoadjuvant chemotherapy (NAC) and in 17% of 86 patients after NAC. The detection of ≥1 CTC/7.5 ml before NAC, after NAC, or at both time points in the above study was associated with worse distant metastasis-free survival and overall survival at a median follow-up of 36 months [54]. In another study ≥1 CTC/7.5 ml were detected in 21.6% of 213 patients before NAC and in 10.6% of 207 patients after NAC [55]. In both these studies, however, neither CTC detection before or after NAC, nor changes in CTC detection during treatment, were predictive of pathological complete response [53, 55]. Rack and colleagues [56] detected ≥1 CTC/22.5 ml before the start of adjuvant treatment in 21.5% of 2,026 patients with early BC [56]. In this study, pre-treatment detection of CTCs was confirmed as an independent predictor for both disease-free survival and overall survival [56]. Several other investigators have detected CTCs by CellSearch® in 9% to 38% of patients with early BC without reporting survival data [5759].

These differences in CTC detection rate in early BC could be attributed to the Poisson distribution of rare events [60], to differences in patient populations, sampling time points, blood volume analyzed, the use or not of ficoll enrichment before processing with CellSearch®, and differences in image interpretation between different labs. Most women in this setting have only one detectable CTC/whole blood volume analyzed. Therefore, in order to prospectively test potential clinical applications of CTCs in non-metastatic BC, it is important to standardize image interpretation across labs by taking into account cytomorphologic criteria.

CTCs versus DTCs

Since blood is more easily obtained than bone marrow, an important question is whether peripheral blood CTCs can be used as surrogate markers for bone marrow DTCs. In one study, peripheral blood and bone marrow were collected from 341 patients at a median follow-up of 40 months after initial surgery [61]. In this study, 8 patients were CTC+/DTC+, 26 were CTC+/DTC-, and 40 were CTC-/DTC+. Although both CTCs (10% of the patients) and DTCs (14% of the patients) were significantly associated with worse clinical outcome, DTCs were more informative than CTCs [61]. This and other studies [62] showed that there was no good correlation between CTC and DTC detection. However, it is not clear whether this is because CTCs and DTCs represent different tumor cell populations or whether this is also related to limitations of the detection technologies used. At present there are no data to support that CTCs can replace DTCs.

Clinical relevance of nucleic acid-based assays

In early BC, initial single-center studies have reported that the detection of peripheral blood CK19 mRNA by RT-PCR after ficoll enrichment of mononuclear cells was an independent prognostic factor for reduced disease-free survival and overall survival [63, 64]. In another study, 13% of 431 early BC patients were CTC-positive according to the AdnaTest®; however, no correlation with clinical outcome was reported [65]. In metastatic BC, CTC detection by AdnaTest® was reported in 52% of 42 women and predicted therapy response in 78% of cases [66]. Finally using immunomagnetic tumor cell enrichment and a multi-marker quantitative PCR based assay, CTCs were detected in 7.9% of 733 stage I/II breast cancer patients with a median follow-up time of 7.6 years and their detection was an independent predictor of meta-stasis-free survival and breast cancer specific survival [67]. However, despite these initial results, no nucleic acid-based assay has received FDA approval nor has demonstrated utility in treating patients with BC.

Clinical trials with DTCs/CTCs

Interestingly, CTC or DTC clearance after systemic treatment has been used as an endpoint in BC clinical trials. In one single-center study, it was shown that a short course of trastuzumab (3 cycles every 3 weeks) eliminated chemotherapy-resistant CK19 mRNA-positive cells in peripheral blood or bone marrow in 20 of 30 women with stage I-IV BC [68]. Another study randomized women with stage II and III BC to NAC with or without zolendronic acid [69]. The primary endpoint of the trial was the number of patients with detectable DTCs at 3 months' post-treatment. At 3 months, DTCs were detected in 17 of 56 patients receiving zoledronic acid versus 25 of 53 patients who did not. Although fewer women had detectable DTCs after NAC with concurrent zoledronic acid than with chemotherapy alone, this was not the case when only women who tested DTC- positive at baseline were analyzed. A critical question is if CTC clearance can be used as a 'surrogate' for survival for regulatory purposes. Such an effort is ongoing and investigators are studying CTC detection by CellSearch® before and after treatment in the phase 3 registration trials of abiraterone acetate in prostate cancer [70].

Although data on the adverse prognostic value of CTC detection by CellSearch® in metastatic BC are solid, evidence from prospective trials is needed that CTC detection can lead to changes in treatment decision and thus improve clinical outcome in metastatic BC. Such an effort is ongoing in a phase III trial run by the Southwest Oncology Group, which is testing the strategy of changing chemotherapy versus continuing the same chemotherapy for patients with metastatic BC who have elevated CTC levels at their first follow-up assessment ( NCT00382018).

DTC/CTC characterization

Identification of therapeutic targets

Beyond enumeration, further characterization of DTCs and CTCs holds the promise to improve treatment outcome in women with BC. Because of the availability of anti-HER2 agents, HER2 expression was studied on DTCs [7173] and CTCs [33, 42, 55, 59, 66, 7478] (Table 2) and was correlated with HER2 expression on the primary tumor. In most studies, HER2 expression on DTCs/CTCs is more prevalent in women with HER2-positive BC than in women with HER2-negative BC in both non-meta-static and metastatic settings. Interestingly, among women with HER2-negative primary tumors defined by standard pathology and detectable CTCs, between 14% and 50% may have at least one HER2-positive CTC. However, it is not known whether the discordant cases can be attributed to technical causes or whether there is any underlying biological explanation. Clinical testing for HER2 in the primary tumor is known to result in false-negative and false-positive results [79]. Furthermore, in most cases different technologies are used to evaluate HER2 in the primary tumor and the CTCs. Beyond technical issues, functional HER2 protein up-regulation on CTCs cannot be excluded, and the acquisition of HER2 amplification during the course of the disease has been suggested [74]. It was shown that four out of nine patients with meta-static BC whose primary tumors were HER2-negative and who had CTCs showing HER2 gene amplification derived benefit from trastuzumab-containing therapy [74].

Table 2 HER2 expression on circulating tumor cells and primary breast cancer

Beyond HER2, several other markers have been studied on DTCs/CTCs. Markers related to angiogenesis, such as vascular endothelial growth factor (VEGF), VEGF2, and hypoxia inducible factor (HIF)-1α, were observed in CTC-positive samples from metastatic BC patients [80]. Using the CTC-chip technology to purify CTCs, epidermal growth factor receptor mutations conferring drug resistance were detected in CTCs from non-small-cell lung cancer patients who had received tyrosine kinase inhibitors [81]. Androgen receptor mutations were also identified in CTC-enriched peripheral blood samples from castration-resistant prostate cancer patients [82]. In most of these studies, DTC/CTC characterization was performed in few patients in the metastatic setting, and therefore validation in independent larger patient series is required. Characterizing DTCs/CTCs in non-metastatic tumors poses additional challenges since such cells are only rarely detected in this setting. Finally, clinical trials are needed to demonstrate that CTC characterization is important for patient management.

Identification of DTCs/CTCs with 'tumor-initiating cell' phenotype

Beyond the potential for improving patient outcome, the study of DTCs/CTCs aims to lead to a better understanding of the metastatic process. Research has shown a significant proportion of DTCs to be resistant to conventional chemotherapy [48]. Furthermore, using Ki67 immunostaining, most micrometastatic cells have been found to be in a non-proliferative state [83]. Interestingly, the CD44+CD24-/low tumor-initiating cell phenotype [84] was observed in a significant number of bone marrow DTCs using triple-staining by immunocytochemistry [85]. Moreover, the CK19+/MUC1 stem cell-like phenotype was demonstrated in a significant number of DTCs in BC by the EPISPOT assay [35]. Epithelial mesencymal transition markers and aldehyde dehydrogenase 1 (ALDH1) were also identified in a major proportion of CTCs from patients with metastatic BC [86]. However, clinical studies are needed to associate the presence of CTCs/DTCs with tumor-initiating c cell phenotype with clinical outcome in women with BC.

Tumor dormancy

An issue related to the role of DTCs in the metastatic process is determining which of them will grow into overt metastases and which will not. According to clinical studies on bone marrow DTCs, 50% to 70% of patients with detectable DTCs will not develop metastases, although even patients without DTCs may relapse and die of BC [4]. For patients who relapse without such cells detectable in their bone marrow, it is possible that the DTCs have actually settled into other organs; alternatively, lack of DTCs could be the result of sampling error or reflect the suboptimal sensitivity of CKs as a marker for DTC detection. Indeed, tumor cell dissemination has been linked to epithelial mesencymal transition and the down-regulation of epithelial cell markers [87]. Conversely, it is possible that non-relapse in the case of patients with DTCs/CTCs can be attributed to the detection of apoptotic cells or to tumor dormancy. Interestingly, CTCs have been detected in one-third of women without clinical evidence of disease up to 22 years after mastectomy for BC [88].

There is evidence that several mechanisms of dormancy exist, including cellular dormancy, in which DTCs enter a state of quiescence (G0-G1 arrest), and tumor mass dormancy, in which DTCs divide but the lesion does not grow beyond a certain size [89]. There is also evidence that mechanisms regulating the switch between cellular dormancy and escape from it are related to the cross-talk between DTCs and the microenvironment [89, 90]. For example, loss or absence of a surface receptor like HER2, urokinase-type plasminogen activator receptor (uPAR) or integrins that transduce growth signals from the microenvironment may result in a dormant DTC, whereas the presence of such a receptor and a permissive microenvironment may result in a proliferating DTC. Interestingly, the overexpression of HER2 [71] or uPAR [91] on DTCs was associated with poor prognosis in patients with breast and gastric cancer, respectively.

The mechanisms that regulate the switch between tumor mass dormancy and expansion have been suggested to be related to angiogenesis [92] and the immune system [93]. When there are limitations in blood supply and/or when there is an active immune system, for example, the micrometastasis cannot grow into overt metastasis. By contrast, a shift in favor of pro-angiogenic factors and activation of transcriptional programs that allow the recruitment of new blood vessels (angiogenic switch) or an escape of immune surveillance (immuno-supression) may cause the expansion of the micrometa-static cells into macrometastasis. It is not clear how all these mechanisms operate in a given patient, or how they are influenced by exogenous factors like stress and diet or by host genetic factors [94].

Genomic characterization of DTCs/CTCs

Thus far, only limited information is available about the global gene expression programs that determine the fate of DTCs and CTCs. Some studies have performed molecular characterization of CTC-enriched samples and reported mRNA or microRNA expression of CTC-specific genes in metastatic BC [95, 96]. Using single cell comparative genomic hybridization, it has been shown that bone marrow DTCs are genetically heterogeneous and display fewer genetic aberrations than primary tumor cells [9799]. In addition, the most prevalent chromosomal aberrations of primary breast tumors (including 8q gain, 13q loss, 16q loss and 17p loss) have rarely been found in DTCs with abnormal karyograms isolated at the time of curative surgery [3]. Husemann and colleagues [100] provided evidence that systemic spread occurs early in BC by showing that tumor cells can disseminate from earliest breast epithelial alterations in transgenic mice and from breast ductal carcinoma in situ in women. These results have led to the proposal of a parallel progression model in which tumor cells disseminate early at ectopic sites and evolve in parallel with tumor cells in the primary site [3]. Finally, beyond gene expression profiling and comparative genomic hybridization, the characterization of DTCs/CTCs using next generation sequencing may provide new insights into the cellular programs that regulate tumor dormancy and metastasis.

Future directions

The characterization of DTCs/CTCs might lead to the identification of targets for the design of new drugs. CTCs might also be used to accelerate drug development if ongoing or future trials demonstrate that CTC clearance is a 'surrogate' for drug efficacy. In order to move DTCs/CTCs into clinical practice, prospective trials with innovative designs and endpoints are needed to demonstrate both clinical utility and cost-effectiveness. Such efforts are currently ongoing. Because the technologies used to detect and characterize tumor cells in peripheral blood are rapidly evolving, issues like easy access to newer technologies and standardization across laboratories will be critical for prospective validation. CTC detection and characterization have the potential to improve risk assessment and provide a 'liquid biopsy' for real-time monitoring of tumor genotype/phenotype in metastatic BC. In early BC, the presence of MRD after patients have completed standard adjuvant treatment may contribute to a better selection of patients to evaluate secondary adjuvant treatment strategies. Overall, the integration of information from both the primary tumor and MRD may eventually lead to personalized treatment strategies.



breast cancer




circulating tumor cell




disseminated tumor cell


epithelial cell adhesion molecule


fiber-optic array scanning technology


Food and Drug Administration


human epidermal growth factor receptor


minimal residual disease


neoadjuvant chemotherapy


polymerase chain reaction


reverse transcription


urokinase-type plasminogen activator receptor.


  1. 1.

    Ferlay J, Parkin DM, Steliarova-Foucher E: Estimates of cancer incidence and mortality in Europe in 2008. Eur J Cancer. 2010, 46: 765-781. 10.1016/j.ejca.2009.12.014.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Riethdorf S, Pantel K: Advancing personalized cancer therapy by detection and characterization of circulating carcinoma cells. Ann N Y Acad Sci. 2010, 1210: 66-77. 10.1111/j.1749-6632.2010.05779.x.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Klein CA: Parallel progression of primary tumours and metastases. Nat Rev Cancer. 2009, 9: 302-312. 10.1038/nrc2627.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Braun S, Vogl FD, Naume B, Janni W, Osborne MP, Coombes RC, Schlimok G, Diel IJ, Gerber B, Gebauer G, Pierga JY, Marth C, Oruzio D, Wiedswang G, Solomayer EF, Kundt G, Strobl B, Fehm T, Wong GY, Bliss J, Vincent-Salomon A, Pantel K: A pooled analysis of bone marrow micrometastasis in breast cancer. N Engl J Med. 2005, 353: 793-802. 10.1056/NEJMoa050434.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Allard WJ, Matera J, Miller MC, Repollet M, Connelly MC, Rao C, Tibbe AG, Uhr JW, Terstappen LW: Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin Cancer Res. 2004, 10: 6897-6904. 10.1158/1078-0432.CCR-04-0378.

    Article  PubMed  Google Scholar 

  6. 6.

    Talasaz AH, Powell AA, Huber DE, Berbee JG, Roh KH, Yu W, Xiao W, Davis MM, Pease RF, Mindrinos MN, Jeffrey SS, Davis RW: Isolating highly enriched populations of circulating epithelial cells and other rare cells from blood using a magnetic sweeper device. Proc Natl Acad Sci USA. 2009, 106: 3970-3975. 10.1073/pnas.0813188106.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Choesmel V, Pierga JY, Nos C, Vincent-Salomon A, Sigal-Zafrani B, Thiery JP, Blin N: Enrichment methods to detect bone marrow micrometastases in breast carcinoma patients: clinical relevance. Breast Cancer Res. 2004, 6: R556-R570. 10.1186/bcr898.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Borgen E, Naume B, Nesland JM, Kvalheim G, Beiske K, Fodstad O, Diel IJ, Solomayer EF, Theocharous P, Coombes RC, Smith BM, Wunder E, Marolleau J-P, Garcia JM, Pantel K: Standardization of the immunocytochemical detection of cancer cells in BM and blood: I. Establishment of objective criteria for the evaluation of immunostained cells. Cytotherapy. 1999, 1: 377-388. 10.1080/0032472031000141283.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Fehm T, Braun S, Muller V, Janni W, Gebauer G, Marth C, Schindlbeck C, Wallwiener D, Borgen E, Naume B, Pantel K, Solomayer E: A concept for the standardized detection of disseminated tumor cells in bone marrow from patients with primary breast cancer and its clinical implementation. Cancer. 2006, 107: 885-892. 10.1002/cncr.22076.

    Article  PubMed  Google Scholar 

  10. 10.

    Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Matera J, Miller MC, Reuben JM, Doyle GV, Allard WJ, Terstappen LW, Hayes DF: Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004, 351: 781-791. 10.1056/NEJMoa040766.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Cohen SJ, Punt CJ, Iannotti N, Saidman BH, Sabbath KD, Gabrail NY, Picus J, Morse M, Mitchell E, Miller MC, Doyle GV, Tissing H, Terstappen LW, Meropol NJ: Relationship of circulating tumor cells to tumor response, progressionfree survival, and overall survival in patients with metastatic colorectal cancer. J Clin Oncol. 2008, 26: 3213-3221. 10.1200/JCO.2007.15.8923.

    Article  PubMed  Google Scholar 

  12. 12.

    de Bono JS, Scher HI, Montgomery RB, Parker C, Miller MC, Tissing H, Doyle GV, Terstappen LW, Pienta KJ, Raghavan D: Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer. Clin Cancer Res. 2008, 14: 6302-6309. 10.1158/1078-0432.CCR-08-0872.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Riethdorf S, Fritsche H, Muller V, Rau T, Schindlbeck C, Rack B, Janni W, Coith C, Beck K, Janicke F, Jackson S, Gornet T, Cristofanilli M, Pantel K: Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: a validation study of the CellSearch system. Clin Cancer Res. 2007, 13: 920-928. 10.1158/1078-0432.CCR-06-1695.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Kraan J, Sleijfer S, Strijbos MH, Ignatiadis M, Peeters D, Pierga JY, Farace F, Riethdorf S, Fehm T, Zorzino L, Tibbe AG, Maestro M, Gisbert-Criado R, Denton G, de Bono JS, Dive C, Foekens JA, Gratama JW: External quality assurance of circulating tumor cell enumeration using the CellSearch® system: a feasibility study. Cytometry B Clin Cytom. 2011, 80: 112-118.

    Article  PubMed  Google Scholar 

  15. 15.

    Hu Y, Fan L, Zheng J, Cui R, Liu W, He Y, Li X, Huang S: Detection of circulating tumor cells in breast cancer patients utilizing multiparameter flow cytometry and assessment of the prognosis of patients in different CTCs levels. Cytometry A. 2010, 77: 213-219.

    Article  PubMed  Google Scholar 

  16. 16.

    Pachmann K, Camara O, Kavallaris A, Krauspe S, Malarski N, Gajda M, Kroll T, Jorke C, Hammer U, Altendorf-Hofmann A, Rabenstein C, Pachmann U, Runnebaum I, Hoff ken K: Monitoring the response of circulating epithelial tumor cells to adjuvant chemotherapy in breast cancer allows detection of patients at risk of early relapse. J Clin Oncol. 2008, 26: 1208-1215. 10.1200/JCO.2007.13.6523.

    Article  PubMed  Google Scholar 

  17. 17.

    Ntouroupi TG, Ashraf SQ, McGregor SB, Turney BW, Seppo A, Kim Y, Wang X, Kilpatrick MW, Tsipouras P, Tafas T, Bodmer WF: Detection of circulating tumour cells in peripheral blood with an automated scanning fluorescence microscope. Br J Cancer. 2008, 99: 789-795. 10.1038/sj.bjc.6604545.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Borgen E, Naume B, Nesland JM, Nowels KW, Pavlak N, Ravkin I, Goldbard S: Use of automated microscopy for the detection of disseminated tumor cells in bone marrow samples. Cytometry. 2001, 46: 215-221. 10.1002/cyto.1130.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Deng G, Herrler M, Burgess D, Manna E, Krag D, Burke JF: Enrichment with anti-cytokeratin alone or combined with anti-EpCAM antibodies significantly increases the sensitivity for circulating tumor cell detection in metastatic breast cancer patients. Breast Cancer Res. 2008, 10: R69-10.1186/bcr2131.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Krivacic RT, Ladanyi A, Curry DN, Hsieh HB, Kuhn P, Bergsrud DE, Kepros JF, Barbera T, Ho MY, Chen LB, Lerner RA, Bruce RH: A rare-cell detector for cancer. Proc Natl Acad Sci USA. 2004, 101: 10501-10504. 10.1073/pnas.0404036101.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Zippelius A, Kufer P, Honold G, Kollermann MW, Oberneder R, Schlimok G, Riethmuller G, Pantel K: Limitations of reverse-transcriptase polymerase chain reaction analyses for detection of micrometastatic epithelial cancer cells in bone marrow. J Clin Oncol. 1997, 15: 2701-2708.

    CAS  PubMed  Google Scholar 

  22. 22.

    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: 870-879.

    CAS  PubMed  Google Scholar 

  23. 23.

    De Cremoux P, Extra JM, Denis MG, Pierga JY, Bourstyn E, Nos C, Clough KB, Boudou E, Martin EC, Muller A, Pouillart P, Magdelenat H: Detection of MUC1-expressing mammary carcinoma cells in the peripheral blood of breast cancer patients by real-time polymerase chain reaction. Clin Cancer Res. 2000, 6: 3117-3122.

    CAS  PubMed  Google Scholar 

  24. 24.

    Reinholz MM, Nibbe A, Jonart LM, Kitzmann K, Suman VJ, Ingle JN, Houghton R, Zehentner B, Roche PC, Lingle WL: Evaluation of a panel of tumor markers for molecular detection of circulating cancer cells in women with suspected breast cancer. Clin Cancer Res. 2005, 11: 3722-3732. 10.1158/1078-0432.CCR-04-1483.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Zehentner BK, Secrist H, Hayes DC, Zhang X, Ostenson RC, Loop S, Goodman G, Houghton RL, Persing DH: Detection of circulating tumor cells in peripheral blood of breast cancer patients during or after therapy using a multigene real-time RT-PCR assay. Mol Diagn Ther. 2006, 10: 41-47.

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Van der Auwera I, Peeters D, Benoy IH, Elst HJ, Van Laere SJ, Prove A, Maes H, Huget P, van Dam P, Vermeulen PB, Dirix LY: Circulating tumour cell detection: a direct comparison between the CellSearch System, the AdnaTest and CK-19/mammaglobin RT-PCR in patients with metastatic breast cancer. Br J Cancer. 2010, 102: 276-284. 10.1038/sj.bjc.6605472.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Markou A, Strati A, Malamos N, Georgoulias V, Lianidou ES: Molecular characterization of circulating tumor cells in breast cancer by a liquid bead array hybridization assay. Clin Chem. 2011, 57: 421-30. 10.1373/clinchem.2010.154328.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Zieglschmid V, Hollmann C, Bocher O: Detection of disseminated tumor cells in peripheral blood. Crit Rev Clin Lab Sci. 2005, 42: 155-196. 10.1080/10408360590913696.

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Nagrath S, Sequist LV, Maheswaran S, Bell DW, Irimia D, Ulkus L, Smith MR, Kwak EL, Digumarthy S, Muzikansky A, Ryan P, Balis UJ, Tompkins RG, Haber DA, Toner M: Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature. 2007, 450: 1235-1239. 10.1038/nature06385.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Zheng S, Lin HK, Lu B, Williams A, Datar R, Cote RJ, Tai YC: 3D microfilter device for viable circulating tumor cell (CTC) enrichment from blood. Biomed Microdevices. 2011, 13: 203-213. 10.1007/s10544-010-9485-3.

    Article  PubMed  Google Scholar 

  31. 31.

    Tan SJ, Lakshmi RL, Chen P, Lim WT, Yobas L, Lim CT: Versatile label free biochip for the detection of circulating tumor cells from peripheral blood in cancer patients. Biosens Bioelectron. 2010, 26: 1701-1705. 10.1016/j.bios.2010.07.054.

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Gascoyne PR, Noshari J, Anderson TJ, Becker FF: Isolation of rare cells from cell mixtures by dielectrophoresis. Electrophoresis. 2009, 30: 1388-1398. 10.1002/elps.200800373.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Punnoose EA, Atwal SK, Spoerke JM, Savage H, Pandita A, Yeh RF, Pirzkall A, Fine BM, Amler LC, Chen DS, Lackner MR: Molecular biomarker analyses using circulating tumor cells. PLoS One. 2010, 5: e12517-10.1371/journal.pone.0012517.

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Stott SL, Lee RJ, Nagrath S, Yu M, Miyamoto DT, Ulkus L, Inserra EJ, Ulman M, Springer S, Nakamura Z, Moore AL, Tsukrov DI, Kempner ME, Dahl DM, Wu CL, Iafrate AJ, Smith MR, Tompkins RG, Sequist LV, Toner M, Haber DA, Maheswaran S: Isolation and characterization of circulating tumor cells from patients with localized and metastatic prostate cancer. Sci Transl Med. 2010, 2: 25ra23-10.1126/scitranslmed.3000403.

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Alix-Panabieres C, Vendrell JP, Pelle O, Rebillard X, Riethdorf S, Muller V, Fabbro M, Pantel K: Detection and characterization of putative metastatic precursor cells in cancer patients. Clin Chem. 2007, 53: 537-539. 10.1373/clinchem.2006.079509.

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Lu J, Fan T, Zhao Q, Zeng W, Zaslavsky E, Chen JJ, Frohman MA, Golightly MG, Madajewicz S, Chen WT: Isolation of circulating epithelial and tumor progenitor cells with an invasive phenotype from breast cancer patients. Int J Cancer. 2010, 126: 669-683. 10.1002/ijc.24814.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Galanzha EI, Shashkov EV, Kelly T, Kim JW, Yang L, Zharov VP: In vivo magnetic enrichment and multiplex photoacoustic detection of circulating tumour cells. Nat Nanotechnol. 2009, 4: 855-860. 10.1038/nnano.2009.333.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Schwarzenbach H, Pantel K, Kemper B, Beeger C, Otterbach F, Kimmig R, Kasimir-Bauer S: Comparative evaluation of cell-free tumor DNA in blood and disseminated tumor cells in bone marrow of patients with primary breast cancer. Breast Cancer Res. 2009, 11: R71-10.1186/bcr2404.

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Board RE, Wardley AM, Dixon JM, Armstrong AC, Howell S, Renshaw L, Donald E, Greystoke A, Ranson M, Hughes A, Dive C: Detection of PIK3CA mutations in circulating free DNA in patients with breast cancer. Breast Cancer Res Treat. 2010, 120: 461-467. 10.1007/s10549-010-0747-9.

    CAS  Article  PubMed  Google Scholar 

  40. 40.

    McBride DJ, Orpana AK, Sotiriou C, Joensuu H, Stephens PJ, Mudie LJ, Hamalainen E, Stebbings LA, Andersson LC, Flanagan AM, Durbecq V, Ignatiadis M, Kallioniemi O, Heckman CA, Alitalo K, Edgren H, Futreal PA, Stratton MR, Campbell PJ: Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors. Genes Chromosomes Cancer. 2010, 49: 1062-1069. 10.1002/gcc.20815.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Schwarzenbach H, Hoon DS, Pantel K: Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer. 2011, 11: 426-437. 10.1038/nrc3066.

    CAS  Article  PubMed  Google Scholar 

  42. 42.

    Fehm T, Muller V, Aktas B, Janni W, Schneeweiss A, Stickeler E, Lattrich C, Lohberg CR, Solomayer E, Rack B, Riethdorf S, Klein C, Schindlbeck C, Brocker K, Kasimir-Bauer S, Wallwiener D, Pantel K: HER2 status of circulating tumor cells in patients with metastatic breast cancer: a prospective, multicenter trial. Breast Cancer Res Treat. 2010, 124: 403-412. 10.1007/s10549-010-1163-x.

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Sieuwerts AM, Kraan J, Bolt J, van der SP, Elstrodt F, Schutte M, Martens JW, Gratama JW, Sleijfer S, Foekens JA: Anti-epithelial cell adhesion molecule antibodies and the detection of circulating normal-like breast tumor cells. J Natl Cancer Inst. 2009, 101: 61-66.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Mostert B, Kraan J, Bolt-de Vries J, van der SP, Sieuwerts AM, Schutte M, Timmermans AM, Foekens R, Martens JW, Gratama JW, Foekens JA, Sleijfer S: Detection of circulating tumor cells in breast cancer may improve through enrichment with anti-CD146. Breast Cancer Res Treat. 2011, 127: 33-41. 10.1007/s10549-010-0879-y.

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S, Somerfield MR, Hayes DF, Bast RC: American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol. 2007, 25: 5287-5312. 10.1200/JCO.2007.14.2364.

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    American Joint Committee on Cancer: Breast. AJCC Cancer Staging Manual. Edited by: Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A. 2010, New York, NY: Springer, 347-376. 7

    Chapter  Google Scholar 

  47. 47.

    Cote RJ, Giuliano A, Hawes D, Ballman KV, Whitworth PW, Blumencranz PW, Reintgen DS, Morrow M, Leitch M, Hunt K: ACOSOG Z0010: a multicenter prognostic study of sentinel node (SN) and bone marrow (BM) micrometastases in women with clinical T1/T2 N0 M0 breast cancer. J Clin Oncol Supp. 2010, 28: 18s-abstr CRA504

    Google Scholar 

  48. 48.

    Janni W, Vogl FD, Wiedswang G, Synnestvedt M, Fehm T, Juckstock J, Borgen E, Rack B, Braun S, Sommer H, Solomayer E, Pantel K, Nesland J, Friese K, Naume B: Persistence of disseminated tumor cells in the bone marrow of breast cancer patients predicts increased risk for relapse--a European pooled analysis. Clin Cancer Res. 2011, 17: 2967-2976. 10.1158/1078-0432.CCR-10-2515.

    Article  PubMed  Google Scholar 

  49. 49.

    Pierga JY, Hajage D, Bachelot T, Delaloge S, Brain E, Campone M, Dieras V, Rolland E, Mignot L, Mathiot C, Bidard FC: High independent prognostic and predictive value of circulating tumor cells compared with serum tumor markers in a large prospective trial in first-line chemotherapy for metastatic breast cancer patients. Ann Oncol. 2011 [Epub ahead of print]

    Google Scholar 

  50. 50.

    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: 6403-6409. 10.1158/1078-0432.CCR-05-1769.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    De Giorgi U, Valero V, Rohren E, Dawood S, Ueno NT, Miller MC, Doyle GV, Jackson S, Andreopoulou E, Handy BC, Reuben JM, Fritsche HA, Macapinlac HA, Hortobagyi GN, Cristofanilli M: Circulating tumor cells and [18F] fluorodeoxyglucose positron emission tomography/computed tomography for outcome prediction in metastatic breast cancer. J Clin Oncol. 2009, 27: 3303-3311. 10.1200/JCO.2008.19.4423.

    Article  PubMed  Google Scholar 

  52. 52.

    Liu MC, Shields PG, Warren RD, Cohen P, Wilkinson M, Ottaviano YL, Rao SB, Eng-Wong J, Seillier-Moiseiwitsch F, Noone AM, Isaacs C: Circulating tumor cells: a useful predictor of treatment efficacy in metastatic breast cancer. J Clin Oncol. 2009, 27: 5153-5159. 10.1200/JCO.2008.20.6664.

    Article  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Pierga JY, Bidard FC, Mathiot C, Brain E, Delaloge S, Giachetti S, de Cremoux P, Salmon R, Vincent-Salomon A, Marty M: Circulating tumor cell detection predicts early metastatic relapse after neoadjuvant chemotherapy in large operable and locally advanced breast cancer in a phase II randomized trial. Clin Cancer Res. 2008, 14: 7004-7010. 10.1158/1078-0432.CCR-08-0030.

    CAS  Article  PubMed  Google Scholar 

  54. 54.

    Bidard FC, Mathiot C, Delaloge S, Brain E, Giachetti S, de Cremoux P, Marty M, Pierga JY: Single circulating tumor cell detection and overall survival in nonmetastatic breast cancer. Ann Oncol. 2010, 21: 729-733. 10.1093/annonc/mdp391.

    Article  PubMed  Google Scholar 

  55. 55.

    Riethdorf S, Muller V, Zhang L, Rau T, Loibl S, Komor M, Roller M, Huober J, Fehm T, Schrader I, Hilfrich J, Holms F, Tesch H, Eidtmann H, Untch M, von Minckwitz G, Pantel K: Detection and HER2 expression of circulating tumor cells: prospective monitoring in breast cancer patients treated in the neoadjuvant GeparQuattro trial. Clin Cancer Res. 2010, 16: 2634-2645. 10.1158/1078-0432.CCR-09-2042.

    CAS  Article  PubMed  Google Scholar 

  56. 56.

    Rack B, Schindlbeck C, Andergassen U, Lorenz R, Zwingers T, Schneeweiss A, Lichtenegger W, Beckmann M, Sommer H, Pantel K, Friese K, Janni W: Prognostic relevance of circulating tumor cells in the peripheral blood of primary breast cancer patients. Cancer Res Supp. 2010, Abstract S6-5

    Google Scholar 

  57. 57.

    Almokadem S, Leitzel K, Harvey HA, Bannon E, Ali SM, Miller MC, Repollet M, Allard WJ, Terstappen LW, Lipton A: Circulating tumor cells in adjuvant breast cancer patients. J Clin Oncol Supp. 2005, Abstract 667

    Google Scholar 

  58. 58.

    Sandri MT, Zorzino L, Cassatella MC, Bassi F, Luini A, Casadio C, Botteri E, Rotmensz N, Adamoli L, Nole F: Changes in circulating tumor cell detection in patients with localized breast cancer before and after surgery. Ann Surg Oncol. 2010, 17: 1539-1545. 10.1245/s10434-010-0918-2.

    Article  PubMed  Google Scholar 

  59. 59.

    Ignatiadis M, Rothe F, Chaboteaux C, Durbecq V, Rouas G, Criscitiello C, Metallo J, Kheddoumi N, Singhal SK, Michiels S, Veys I, Rossari J, Larsimont D, Carly B, Pestrin M, Bessi S, Buxant F, Liebens F, Piccart M, Sotiriou C: HER2- positive circulating tumor cells in breast cancer. PLoS One. 2011, 6: e15624-10.1371/journal.pone.0015624.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Tibbe AG, Miller MC, Terstappen LW: Statistical considerations for enumeration of circulating tumor cells. Cytometry A. 2007, 71: 154-162.

    Article  PubMed  Google Scholar 

  61. 61.

    Wiedswang G, Borgen E, Schirmer C, Karesen R, Kvalheim G, Nesland JM, Naume B: Comparison of the clinical significance of occult tumor cells in blood and bone marrow in breast cancer. Int J Cancer. 2006, 118: 2013-2019. 10.1002/ijc.21576.

    CAS  Article  PubMed  Google Scholar 

  62. 62.

    Krishnamurthy S, Cristofanilli M, Singh B, Reuben J, Gao H, Cohen EN, Andreopoulou E, Hall CS, Lodhi A, Jackson S, Lucci A: Detection of minimal residual disease in blood and bone marrow in early stage breast cancer. Cancer. 2010, 116: 3330-3337. 10.1002/cncr.25145.

    Article  PubMed  Google Scholar 

  63. 63.

    Xenidis N, Ignatiadis M, Apostolaki S, Perraki M, Kalbakis K, Agelaki S, Stathopoulos EN, Chlouverakis G, Lianidou E, Kakolyris S, Georgoulias V, Mavroudis D: Cytokeratin-19 mRNA-positive circulating tumor cells after adjuvant chemotherapy in patients with early breast cancer. J Clin Oncol. 2009, 27: 2177-2184. 10.1200/JCO.2008.18.0497.

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Ignatiadis M, Xenidis N, Perraki M, Apostolaki S, Politaki E, Kafousi M, Stathopoulos E, Stathopoulou A, Lianidou E, Chlouverakis G, Sotiriou C, Georgoulias V, Mavroudis D: Different prognostic value of Cytokeratin-19 mRNA-positive circulating tumor cells according to estrogen receptor and HER2 status in early breast cancer. J Clin Oncol. 2007, 25: 5194-5202. 10.1200/JCO.2007.11.7762.

    Article  PubMed  Google Scholar 

  65. 65.

    Fehm T, Hoffmann O, Aktas B, Becker S, Solomayer EF, Wallwiener D, Kimmig R, Kasimir-Bauer S: Detection and characterization of circulating tumor cells in blood of primary breast cancer patients by RT-PCR and comparison to status of bone marrow disseminated cells. Breast Cancer Res. 2009, 11: R59-10.1186/bcr2349.

    Article  PubMed  PubMed Central  Google Scholar 

  66. 66.

    Tewes M, Aktas B, Welt A, Mueller S, Hauch S, Kimmig R, Kasimir-Bauer S: Molecular profiling and predictive value of circulating tumor cells in patients with metastatic breast cancer: an option for monitoring response to breast cancer related therapies. Breast Cancer Res Treat. 2009, 115: 581-590. 10.1007/s10549-008-0143-x.

    Article  PubMed  Google Scholar 

  67. 67.

    Molloy TJ, Bosma AJ, Baumbusch LO, Synnestvedt M, Borgen E, Russnes HG, Schlichting E, Van't Veer LJ, Naume B: The prognostic significance of tumor cell detection in the peripheral blood versus the bone marrow in 733 early-stage breast cancer patients. Breast Cancer Res. 2011, 13: R61-10.1186/bcr2898.

    Article  PubMed  PubMed Central  Google Scholar 

  68. 68.

    Bozionellou V, Mavroudis D, Perraki M, Papadopoulos S, Apostolaki S, Stathopoulos E, Stathopoulou A, Lianidou E, Georgoulias V: Trastuzumab administration can effectively target chemotherapy-resistant cytokeratin-19 messenger RNA-positive tumor cells in the peripheral blood and bone marrow of patients with breast cancer. Clin Cancer Res. 2004, 10: 8185-8194. 10.1158/1078-0432.CCR-03-0094.

    CAS  Article  PubMed  Google Scholar 

  69. 69.

    Aft R, Naughton M, Trinkaus K, Watson M, Ylagan L, Chavez-MacGregor M, Zhai J, Kuo S, Shannon W, Diemer K, Herrmann V, Dietz J, Ali A, Ellis M, Weiss P, Eberlein T, Ma C, Fracasso PM, Zoberi I, Taylor M, Gillanders W, Pluard T, Mortimer J, Weilbaecher K: Effect of zoledronic acid on disseminated tumour cells in women with locally advanced breast cancer: an open label, randomised, phase 2 trial. Lancet Oncol. 2010, 11: 421-428. 10.1016/S1470-2045(10)70054-1.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Diamandis EP, Pantel K, Scher HI, Terstappen L, Lianidou E: Circulating cancer cells and their clinical applications. Clin Chem. 2011 [Epub ahead of print]

    Google Scholar 

  71. 71.

    Braun S, Schlimok G, Heumos I, Schaller G, Riethdorf L, Riethmuller G, Pantel K: ErbB2 overexpression on occult metastatic cells in bone marrow predicts poor clinical outcome of stage I-III breast cancer patients. Cancer Res. 2001, 61: 1890-1895.

    CAS  PubMed  Google Scholar 

  72. 72.

    Vincent-Salomon A, Pierga JY, Couturier J, d'Enghien CD, Nos C, Sigal-Zafrani B, Lae M, Freneaux P, Dieras V, Thiery JP, Sastre-Garau X: HER2 status of bone marrow micrometastasis and their corresponding primary tumours in a pilot study of 27 cases: a possible tool for anti-HER2 therapy management?. Br J Cancer. 2007, 96: 654-659. 10.1038/sj.bjc.6603584.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Krawczyk N, Banys M, Neubauer H, Solomayer EF, Gall C, Hahn M, Becker S, Bachmann R, Wallwiener D, Fehm T: HER2 status on persistent disseminated tumor cells after adjuvant therapy may differ from initial HER2 status on primary tumor. Anticancer Res. 2009, 29: 4019-4024.

    PubMed  Google Scholar 

  74. 74.

    Meng S, Tripathy D, Shete S, Ashfaq R, Haley B, Perkins S, Beitsch P, Khan A, Euhus D, Osborne C, Frenkel E, Hoover S, Leitch M, Cliff E, Vitetta E, Morrison L, Herlyn D, Terstappen LW, Fleming T, Fehm T, Tucker T, Lane N, Wang J, Uhr J: HER-2 gene amplification can be acquired as breast cancer progresses. Proc Natl Acad Sci USA. 2004, 101: 9393-9398. 10.1073/pnas.0402993101.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Wulfing P, Borchard J, Buerger H, Heidl S, Zanker KS, Kiesel L, Brandt B: HER2-positive circulating tumor cells indicate poor clinical outcome in stage I to III breast cancer patients. Clin Cancer Res. 2006, 12: 1715-1720. 10.1158/1078-0432.CCR-05-2087.

    Article  PubMed  Google Scholar 

  76. 76.

    Pestrin M, Bessi S, Galardi F, Truglia M, Biggeri A, Biagioni C, Cappadona S, Biganzoli L, Giannini A, Di Leo A: Correlation of HER2 status between primary tumors and corresponding circulating tumor cells in advanced breast cancer patients. Breast Cancer Res Treat. 2009, 118: 523-530. 10.1007/s10549-009-0461-7.

    CAS  Article  PubMed  Google Scholar 

  77. 77.

    Munzone E, Nole F, Goldhirsch A, Botteri E, Esposito A, Zorzino L, Curigliano G, Minchella I, Adamoli L, Cassatella MC, Casadio C, Sandri MT: Changes of HER2 status in circulating tumor cells compared with the primary tumor during treatment for advanced breast cancer. Clin Breast Cancer. 2010, 10: 392-397. 10.3816/CBC.2010.n.052.

    CAS  Article  PubMed  Google Scholar 

  78. 78.

    Flores LM, Kindelberger DW, Ligon AH, Capelletti M, Fiorentino M, Loda M, Cibas ES, Janne PA, Krop IE: Improving the yield of circulating tumour cells facilitates molecular characterisation and recognition of discordant HER2 amplification in breast cancer. Br J Cancer. 2010, 102: 1495-1502. 10.1038/sj.bjc.6605676.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  79. 79.

    Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, Dowsett M, Fitzgibbons PL, Hanna WM, Langer A, McShane LM, Paik S, Pegram MD, Perez EA, Press MF, Rhodes A, Sturgeon C, Taube SE, Tubbs R, Vance GH, van dV, Wheeler TM, Hayes DF: American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol. 2007, 25: 118-145.

    CAS  Article  PubMed  Google Scholar 

  80. 80.

    Kallergi G, Markomanolaki H, Giannoukaraki V, Papadaki MA, Strati A, Lianidou ES, Georgoulias V, Mavroudis D, Agelaki S: Hypoxia-inducible factor-1alpha and vascular endothelial growth factor expression in circulating tumor cells of breast cancer patients. Breast Cancer Res. 2009, 11: R84-10.1186/bcr2452.

    Article  PubMed  PubMed Central  Google Scholar 

  81. 81.

    Maheswaran S, Sequist LV, Nagrath S, Ulkus L, Brannigan B, Collura CV, Inserra E, Diederichs S, Iafrate AJ, Bell DW, Digumarthy S, Muzikansky A, Irimia D, Settleman J, Tompkins RG, Lynch TJ, Toner M, Haber DA: Detection of mutations in EGFR in circulating lung-cancer cells. N Engl J Med. 2008, 359: 366-377. 10.1056/NEJMoa0800668.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  82. 82.

    Jiang Y, Palma JF, Agus DB, Wang Y, Gross ME: Detection of androgen receptor mutations in circulating tumor cells in castration-resistant prostate cancer. Clin Chem. 2010, 56: 1492-1495. 10.1373/clinchem.2010.143297.

    Article  PubMed  Google Scholar 

  83. 83.

    Pantel K, Schlimok G, Braun S, Kutter D, Lindemann F, Schaller G, Funke I, Izbicki JR, Riethmuller G: Differential expression of proliferation-associated molecules in individual micrometastatic carcinoma cells. J Natl Cancer Inst. 1993, 85: 1419-1424. 10.1093/jnci/85.17.1419.

    CAS  Article  PubMed  Google Scholar 

  84. 84.

    Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF: Prospective identification of tumorigenic breast cancer cells. Proc Natl Acad Sci USA. 2003, 100: 3983-3988. 10.1073/pnas.0530291100.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Balic M, Lin H, Young L, Hawes D, Giuliano A, McNamara G, Datar RH, Cote RJ: Most early disseminated cancer cells detected in bone marrow of breast cancer patients have a putative breast cancer stem cell phenotype. Clin Cancer Res. 2006, 12: 5615-5621. 10.1158/1078-0432.CCR-06-0169.

    CAS  Article  PubMed  Google Scholar 

  86. 86.

    Aktas B, Tewes M, Fehm T, Hauch S, Kimmig R, Kasimir-Bauer S: Stem cell and epithelial-mesenchymal transition markers are frequently overexpressed in circulating tumor cells of metastatic breast cancer patients. Breast Cancer Res. 2009, 11: R46-10.1186/bcr2333.

    Article  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Brabletz T, Jung A, Spaderna S, Hlubek F, Kirchner T: Opinion: migrating cancer stem cells - an integrated concept of malignant tumour progression. Nat Rev Cancer. 2005, 5: 744-749. 10.1038/nrc1694.

    CAS  Article  PubMed  Google Scholar 

  88. 88.

    Meng S, Tripathy D, Frenkel EP, Shete S, Naftalis EZ, Huth JF, Beitsch PD, Leitch M, Hoover S, Euhus D, Haley B, Morrison L, Fleming TP, Herlyn D, Terstappen LW, Fehm T, Tucker TF, Lane N, Wang J, Uhr JW: Circulating tumor cells in patients with breast cancer dormancy. Clin Cancer Res. 2004, 10: 8152-8162. 10.1158/1078-0432.CCR-04-1110.

    Article  PubMed  Google Scholar 

  89. 89.

    Guirre-Ghiso JA: Models, mechanisms and clinical evidence for cancer dormancy. Nat Rev Cancer. 2007, 7: 834-846. 10.1038/nrc2256.

    Article  Google Scholar 

  90. 90.

    Barkan D, Green JE, Chambers AF: Extracellular matrix: a gatekeeper in the transition from dormancy to metastatic growth. Eur J Cancer. 2010, 46: 1181-1188. 10.1016/j.ejca.2010.02.027.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  91. 91.

    Heiss MM, Allgayer H, Gruetzner KU, Funke I, Babic R, Jauch KW, Schildberg FW: Individual development and uPA-receptor expression of disseminated tumour cells in bone marrow: a reference to early systemic disease in solid cancer. Nat Med. 1995, 1: 1035-1039. 10.1038/nm1095-1035.

    CAS  Article  PubMed  Google Scholar 

  92. 92.

    Naumov GN, Akslen LA, Folkman J: Role of angiogenesis in human tumor dormancy: animal models of the angiogenic switch. Cell Cycle. 2006, 5: 1779-1787. 10.4161/cc.5.16.3018.

    CAS  Article  PubMed  Google Scholar 

  93. 93.

    Farrar JD, Katz KH, Windsor J, Thrush G, Scheuermann RH, Uhr JW, Street NE: Cancer dormancy. VII. A regulatory role for CD8+ T cells and IFN-gamma in establishing and maintaining the tumor-dormant state. J Immunol. 1999, 162: 2842-2849.

    CAS  PubMed  Google Scholar 

  94. 94.

    Hunter K: Host genetics influence tumour metastasis. Nat Rev Cancer. 2006, 6: 141-146. 10.1038/nrc1803.

    CAS  Article  PubMed  Google Scholar 

  95. 95.

    Smirnov DA, Zweitzig DR, Foulk BW, Miller MC, Doyle GV, Pienta KJ, Meropol NJ, Weiner LM, Cohen SJ, Moreno JG, Connelly MC, Terstappen LW, O'Hara SM: Global gene expression profiling of circulating tumor cells. Cancer Res. 2005, 65: 4993-4997. 10.1158/0008-5472.CAN-04-4330.

    CAS  Article  PubMed  Google Scholar 

  96. 96.

    Sieuwerts AM, Mostert B, Bolt-de Vries J, Peeters D, de Jongh FE, Stouthard JM, Dirix LY, van Dam PA, Van Galen A, de Weerd V, Kraan J, van der Spoel P, Ramírez-Moreno R, van Deurzen CH, Smid M, Yu JX, Jiang J, Wang Y, Gratama JW, Sleijfer S, Foekens JA, Martens JW: mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients. Clin Cancer Res. 2011, 17: 3600-3618. 10.1158/1078-0432.CCR-11-0255.

    CAS  Article  PubMed  Google Scholar 

  97. 97.

    Klein CA, Blankenstein TJ, Schmidt-Kittler O, Petronio M, Polzer B, Stoecklein NH, Riethmuller G: Genetic heterogeneity of single disseminated tumour cells in minimal residual cancer. Lancet. 2002, 360: 683-689. 10.1016/S0140-6736(02)09838-0.

    CAS  Article  PubMed  Google Scholar 

  98. 98.

    Schmidt-Kittler O, Ragg T, Daskalakis A, Granzow M, Ahr A, Blankenstein TJ, Kaufmann M, Diebold J, Arnholdt H, Muller P, Bischoff J, Harich D, Schlimok G, Riethmuller G, Eils R, Klein CA: From latent disseminated cells to overt metastasis: genetic analysis of systemic breast cancer progression. Proc Natl Acad Sci USA. 2003, 100: 7737-7742. 10.1073/pnas.1331931100.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  99. 99.

    Schardt JA, Meyer M, Hartmann CH, Schubert F, Schmidt-Kittler O, Fuhrmann C, Polzer B, Petronio M, Eils R, Klein CA: Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer. Cancer Cell. 2005, 8: 227-239. 10.1016/j.ccr.2005.08.003.

    CAS  Article  PubMed  Google Scholar 

  100. 100.

    Husemann Y, Geigl JB, Schubert F, Musiani P, Meyer M, Burghart E, Forni G, Eils R, Fehm T, Riethmuller G, Klein CA: Systemic spread is an early step in breast cancer. Cancer Cell. 2008, 13: 58-68. 10.1016/j.ccr.2007.12.003.

    Article  PubMed  Google Scholar 

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We would like to thank Carolyn Straehle for editorial assistance.

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Correspondence to Michail Ignatiadis.

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Competing interests

MI has received consultancy fees and research support from Veridex. MR has no financial competing interests.

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Ignatiadis, M., Reinholz, M. Minimal residual disease and circulating tumor cells in breast cancer. Breast Cancer Res 13, 222 (2011).

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  • Breast Cancer
  • Metastatic Breast Cancer
  • Zoledronic Acid
  • Early Breast Cancer
  • Minimal Residual Disease