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Detection of circulating tumor cells in blood of metastatic breast cancer patients using a combination of cytokeratin and EpCAM antibodies

Ulrike Weissenstein1*, Agnes Schumann2, Marcus Reif2, Susanne Link3, Ulrike D Toffol-Schmidt1 and Peter Heusser4

Author Affiliations

1 Society for Cancer Research, Hiscia Institute, Arlesheim, Switzerland

2 Institute for Clinical Research, Berlin, Germany

3 University Hospital Basel, Basel, Switzerland

4 Center for Integrative Medicine, University of Witten/Herdecke, Witten, Germany

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BMC Cancer 2012, 12:206  doi:10.1186/1471-2407-12-206

Published: 30 May 2012



Circulating tumor cells (CTCs) are detectable in peripheral blood of metastatic breast cancer patients (MBC). In this paper we evaluate a new CTC separation method based on a combination of anti-EpCAM- and anti-cytokeratin magnetic cell separation with the aim to improve CTC detection with low target antigen densities.


Blood samples of healthy donors spiked with breast cancer cell line HCC1937 were used to determine accuracy and precision of the method. 10 healthy subjects were examined to evaluate specificity. CTC counts in 59 patients with MBC were measured to evaluate the prognostic value on overall survival.


Regression analysis of numbers of recovered vs. spiked HCC1937 cells yielded a coefficient of determination of R2 = 0.957. The average percentage of cell recovery was 84%. The average within-run coefficient of variation for spiking of 185, 85 and 30 cells was 14%. For spiking of 10 cells the within-run CV was 30%. No CTCs were detected in blood of 10 healthy subjects examined.

A standard threshold of 5 CTC/7.5 ml blood as a cut-off point between risk groups led to a highly significant prognostic marker (p < 0.001). To assess the prognostic value of medium CTC levels we additionally considered a low (CTC-L: 0 CTC), a medium (CTC-M: 1–4 CTC) and a high risk group (CTC-H: ≥5 CTC). The effect of this CTC-LMH marker on overall survival was significant as well (p < 0.001). A log-ratio test performed to compare the model with 3 vs. the model with 2 risk groups rejected the model with 2 risk groups (p = 0.026). For CTC as a count variable, we propose an offset reciprocal transformation 1/(1 + x) for overall survival prediction (p < 0.001).


We show that our CTC detection method is feasible and leads to accurate and reliable results. Our data suggest that a refined differentiation between patients with different CTC levels is reasonable.