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A microfluidic device for label-free, physical capture of circulating tumor cell clusters

Nature Methods volume 12, pages 685–691 (2015)Cite this article

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Abstract

Cancer cells metastasize through the bloodstream either as single migratory circulating tumor cells (CTCs) or as multicellular groupings (CTC clusters). Existing technologies for CTC enrichment are designed to isolate single CTCs, and although CTC clusters are detectable in some cases, their true prevalence and significance remain to be determined. Here we developed a microchip technology (the Cluster-Chip) to capture CTC clusters independently of tumor-specific markers from unprocessed blood. CTC clusters are isolated through specialized bifurcating traps under low–shear stress conditions that preserve their integrity, and even two-cell clusters are captured efficiently. Using the Cluster-Chip, we identified CTC clusters in 30–40% of patients with metastatic breast or prostate cancer or with melanoma. RNA sequencing of CTC clusters confirmed their tumor origin and identified tissue-derived macrophages within the clusters. Efficient capture of CTC clusters will enable the detailed characterization of their biological properties and role in metastasis.

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Figure 1: Design and operation of the Cluster-Chip.
Figure 2: Characterization of the Cluster-Chip using cell lines spiked in whole blood.
Figure 3: Release of captured clusters from the Cluster-Chip.
Figure 4: Capture of CTC clusters from blood samples of patients with metastatic cancer.
Figure 5: Immunocytochemical and molecular characterization of patient CTC clusters.

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Acknowledgements

We express our gratitude to all patients and healthy volunteers who participated in this study and contributed blood samples. We thank O. Hurtado, A.J. Aranyosi and L. Libby for coordination of the research laboratories; D.M. Lewis for his help in instrumentation; and L. Nieman, J. Walsh and T.N. Lewis for their help with microscopy. N.A. was supported by the Swiss National Science Foundation and the Human Frontiers Science Program. This work was supported by the US National Institutes of Health (NIH) P41 Resource Center (M.T.); an NIH National Institute of Biomedical Imaging and Bioengineering Quantum Grant (M.T. and D.A.H.); Stand Up to Cancer (D.A.H., M.T. and S.M.); the Howard Hughes Medical Institute (D.A.H.); the Prostate Cancer Foundation and the Charles Evans Foundation (D.A.H. and M.T.); and Johnson and Johnson (M.T. and S.M.).

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Author notes

  1. A Fatih Sarioglu

    Present address: Present address: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.,

  2. A Fatih Sarioglu and Nicola Aceto: These authors contributed equally to this work.

Authors and Affiliations

  1. Center for Engineering in Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    A Fatih Sarioglu, Nikola Kojic, Mahnaz Zeinali, Bashar Hamza, Shannon L Stott, Ravi Kapur & Mehmet Toner

  2. Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    A Fatih Sarioglu, Nicola Aceto, Maria C Donaldson, Mahnaz Zeinali, Amanda Engstrom, Huili Zhu, Tilak K Sundaresan, David T Miyamoto, Xi Luo, Aditya Bardia, Ben S Wittner, Sridhar Ramaswamy, Toshi Shioda, David T Ting, Shannon L Stott, Shyamala Maheswaran & Daniel A Haber

  3. Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    A Fatih Sarioglu, Nikola Kojic, Shyamala Maheswaran & Mehmet Toner

  4. Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Nicola Aceto, Aditya Bardia, Sridhar Ramaswamy, David T Ting, Shannon L Stott & Daniel A Haber

  5. Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    David T Miyamoto

  6. Howard Hughes Medical Institute, Chevy Chase, Maryland, USA

    Daniel A Haber

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Contributions

A.F.S., N.A., S.M., D.A.H. and M.T. designed the research, analyzed the data and prepared the manuscript. N.K. performed computer simulations. M.C.D., M.Z. and A.E. processed clinical samples, performed immunofluorescence staining and scanning. B.H. manufactured devices for clinical studies. H.Z. and T.S. performed amplification and RNA sequencing. T.K.S., D.T.M., X.L. and A.B. provided clinical samples. B.S.W. performed statistical analysis on the RNA sequencing data. S.R., D.T.T., S.L.S. and R.K. commented on the manuscript.

Corresponding author

Correspondence to Mehmet Toner.

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Competing interests

A.F.S. and M.T. are inventors on a patent Massachusetts General Hospital filed to protect the Cluster-Chip technology.

Integrated supplementary information

Supplementary Figure 1 Finite-element analysis of cell cluster dynamics in different cluster trap architectures.

(a) Cluster-Chip (b) Filter (c) A structure identical to the Cluster-Chip except that one of the openings is closed d) A filter formed by two triangular pillars. In all cases except the Cluster-Chip, cluster larger than the opening size passes due to its elastic behavior. The cluster being missed points to the importance of split flow fields simultaneously effecting the cluster in the Cluster-Chip and proves that the capture in the Cluster-Chip is not simply due to filtering. In all simulations, the opening widths and diameters of individual cells are 14 μm.

Supplementary Figure 2 Probability of chip-mediated artifact cluster formation from single cells on the Cluster-Chip.

The calculated probabilities are based on simplifying assumptions on chip geometry and cell adhesion. We assume a blood sample with 1000 CTCs. In addition, each of the 4096 parallel cluster traps on the Cluster-Chip is assumed to have equal probability of receiving CTCs and whenever multiple CTCs go into the same trap, a CTC-cluster is formed. We used Poisson approximation to calculate probability of forming a CTC-cluster composed of a specific number of cells. Our model confirms that it is extremely unlikely to form artifact CTC clusters on the Cluster-Chip.

Supplementary Figure 3 Experimental setup used to quantify the capture efficiency of the Cluster-Chip.

A smaller version of the Cluster-Chip is connected to a large microfluidic waste chamber, which permits to accurately identify and analyze non-captured cell clusters in whole blood. Both the chip and waste chamber are imaged using fluorescence microscopy to calculate the cell cluster capture efficiency.

Supplementary Figure 4 Distribution of captured small and large clusters on the Cluster-Chip.

Normalized distribution of (a) 2-cell clusters (b) 3-cell clusters (c) clusters containing 4 or more cells across the Cluster-Chip. We used simulated whole blood samples spiked with artificial clusters of MDA-MB-231 breast cancer cell line. The Cluster-Chip was operated at 2.5 ml/hr and was on a thermoelectric cooler set at 4°C.

Supplementary Figure 5 Characterization of MDA-MB-231 cell cluster size distribution before spiking.

We prepare clusters of fluorescently labeled MDA-MB-231 cancer cells and deposit the suspension on an ultra-low attachment culture dish. Using fluorescence microscopy, we count the number of cells within each cluster and then spike into whole blood in order to prepare a simulated sample containing characterized cluster population for quantitative device testing.

Supplementary Figure 6 Intact and damaged cell clusters captured using a membrane filter.

Fluorescent and brightftield images of intact and damaged MDA-MB-231 cell clusters when captured using a polycarbonate track-etched membrane filter operated under 1.5 psi.

Supplementary Figure 7 Viability of cell clusters released from the Cluster-Chip.

The Cluster-Chip is operated at 4°C and the clusters were released at 250 ml/hr reverse flow rate (A) Fluorescent images of MDA-MB-231 clusters treated with two-color viability (green)/cytotoxicity (red) assay. The cells are divided in two batches: Control and cell clusters captured and released from Cluster-Chip (B) Percentage of viable clusters captured and released using Cluster-Chip against the control. Scale bar 100 μm.

Supplementary Figure 8 Images of CTC -clusters isolated from a breast cancer patient and released in solution.

CTC-clusters isolated from a patient with metastatic breast cancer using the Cluster-Chip operated at 4°C and released with reverse flow. CTC clusters are not fixed and live stained for common breast cancer surface markers. Scale bar 20 μm.

Supplementary Figure 9 Correlation between the number of CTCs and CTC clusters in patients.

Comparison of number of CTC clusters isolated using the Cluster-Chip and number of single CTCs isolated using CTC-iChip from the same patient at the same timepoint. Among the 19 cases studied, we found no correlation between the numbers of CTC-clusters and that of single CTCs.

Supplementary Figure 10 Proliferative index of single CTCs isolated from a breast cancer patient.

Representative images of a Ki67-negative (-) and a Ki67-positive (+) CTC stained with antibodies against wide spectrum cytokeratin (CK, red), Ki67 (yellow) and CD45 (green). Nuclei are stained with DAPI (blue). The bar graph shows the mean percentage of Ki67-positive cells isolated from a breast cancer patient across multiple time points. All together, 439 single CTCs were stained and 162 resulted positive for Ki67.

Supplementary Figure 11 Heat map showing expression levels of CTC clusters isolated from a patient.

Heatmap showing expression levels of representative epithelial-to-mesenchymal transition (EMT) genes in released CTC-clusters and healthy donor white blood cells (WBCs). Epithelial markers E-cadherin (CDH1), EpCAM and Mucin1 (MUC1), as well as mesenchymal markers Vimentin (VIM), Fibronectin1 (FN1), N-cadherin (CDH2) and TWIST1 are shown.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Table 1 (PDF 778 kb)

Real-time capture of cell clusters in whole blood on the Cluster-Chip

Real-time video of the Cluster-Chip processing a simulated sample at 2.5 ml/hr. The sample is prepared by spiking artificially formed clusters of fluorescently labeled MDA-MB-231 cancer cells into whole blood samples collected from a healthy donor. Unlabeled blood cells flowing through the chip are not visible in the fluorescent channel but can be noticed as they obscure the fluorescence emission from captured clusters. (MP4 7507 kb)

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Sarioglu, A., Aceto, N., Kojic, N. et al. A microfluidic device for label-free, physical capture of circulating tumor cell clusters. Nat Methods 12, 685–691 (2015). https://doi.org/10.1038/nmeth.3404

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