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A microfluidic assay for the quantification of the metastatic propensity of breast cancer specimens

Nature Biomedical Engineering volume 3, pages 452–465 (2019)Cite this article

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Abstract

The challenge of predicting which patients with breast cancer will develop metastases leads to the overtreatment of patients with benign disease and to the inadequate treatment of aggressive cancers. Here, we report the development and testing of a microfluidic assay that quantifies the abundance and proliferative index of migratory cells in breast cancer specimens, for the assessment of their metastatic propensity and for the rapid screening of potential antimetastatic therapeutics. On the basis of the key roles of cell motility and proliferation in cancer metastasis, the device accurately predicts the metastatic potential of breast cancer cell lines and of patient-derived xenografts. Compared with unsorted cancer cells, highly motile cells isolated by the device exhibited similar tumourigenic potential but markedly increased metastatic propensity in vivo. RNA sequencing of the highly motile cells revealed an enrichment of motility-related and survival-related genes. The approach might be developed into a companion assay for the prediction of metastasis in patients and for the selection of effective therapeutic regimens.

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Fig. 1: Use of MAqCI for prediction of metastatic potential of breast epithelial and breast cancer cell lines with high accuracy, sensitivity and specificity.
Fig. 2: Migratory cells have similar tumourigenic but markedly enhanced metastatic potential in vivo than unsorted breast cancer cells.
Fig. 3: Characterization of phenotype and genotype of migratory cells.
Fig. 4: MAqCI predicts metastatic potential conferred by activation of PI3K and RAS/MAPK pathways in breast epithelial cells.
Fig. 5: MAqCI accurately predicts the metastatic potential of cells obtained from PDXs.
Fig. 6: MAqCI testing of therapeutic agents from ongoing clinical trials.

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Data availability

The main data supporting the results of this study are available within the paper and its Supplementary Information files. Source data for the figures in this study are available from the corresponding author upon reasonable request. RNA sequencing data are available at the National Center for Biotechnology Information Gene Expression Omnibus, under accession number GSE128313.

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Acknowledgements

This line of research was supported by the National Cancer Institute through grants R01-CA183804 (K.K., A.K.-K., S.S.M.), R01-CA216855 (K.K.), R01-CA154624 (S.S.M.), R01-CA174385 (N.V.) and K01-CA166576 (M.I.V.), as well as by CPRIT RP180466 (N.V.), MRA Award 509800 (N.V.), CDMRP CA160591 (N.V.) and Department of Defense grant W81XWH-17-1-0246 (V.K.B.). M.I.V. was also supported by a Research Scholar Grant, RSG-18-028-01-CSM, from the American Cancer Society.

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Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD, USA

    Christopher L. Yankaskas, Colin D. Paul, Panagiotis Mistriotis, Daniel J. Shea, Kristen M. Manto, Andreas C. Chai & Konstantinos Konstantopoulos

  2. Johns Hopkins Institute for NanoBioTechnology, The Johns Hopkins University, Baltimore, MD, USA

    Christopher L. Yankaskas, Colin D. Paul, Panagiotis Mistriotis & Konstantinos Konstantopoulos

  3. Marlene and Stewart Greenebaum National Cancer Institute Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA

    Keyata N. Thompson, Michele I. Vitolo, Aikaterini Kontrogianni-Konstantopoulos & Stuart S. Martin

  4. Graduate Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Michele I. Vitolo & Stuart S. Martin

  5. Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, USA

    Michele I. Vitolo & Stuart S. Martin

  6. Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA

    Ankit Mahendra & Navin Varadarajan

  7. Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA

    Vivek K. Bajpai

  8. Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, Baltimore, MD, USA

    Aikaterini Kontrogianni-Konstantopoulos

  9. Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA

    Konstantinos Konstantopoulos

  10. Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Konstantinos Konstantopoulos

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  1. Christopher L. Yankaskas
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Contributions

C.L.Y., C.D.P. and K.K. designed the study. C.L.Y. performed experiments, interpreted the data and wrote the manuscript. K.N.T., C.D.P., M.I.V. and P.M. contributed to design the study, performed experiments and interpreted the data. A.M. and V.K.B. helped to design, perform and analyse the RNA sequencing experiments. D.J.S. and K.M.M. performed select experiments. A.C.C. wrote code and used it to analyse data. N.V., A.K.-K. and S.S.M. interpreted data, provided critical insights and edited the manuscript. K.K. designed and supervised the study, and wrote the manuscript.

Corresponding author

Correspondence to Konstantinos Konstantopoulos.

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Competing interests

The PTEN−/− cells are licensed to Horizon Discovery Ltd (Cambridge, UK). M.I.V receives compensation for the sale of these cells. MAqCI is the subject of US Utility Patent applications 15/780,768 and 14/906,055.

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Supplementary information

Supplementary Information

Supplementary figures, tables and video legends.

Reporting Summary

Supplementary Dataset 1

Genes upregulated by migratory compared with unsorted MDA-MB-231 cells.

Supplementary Dataset 2

Genes downregulated by migratory compared with unsorted MDA-MB-231 cells.

Supplementary Dataset 3

Statistical tests.

Supplementary Video 1

Definition of migratory and non-migratory cells in MAqCI.

Supplementary Video 2

Non-migratory MCF7 breast cancer cells in MAqCI.

Supplementary Video 3

Migration of breast cancer cells obtained from patient-derived xenografts in MAqCI.

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Yankaskas, C.L., Thompson, K.N., Paul, C.D. et al. A microfluidic assay for the quantification of the metastatic propensity of breast cancer specimens. Nat Biomed Eng 3, 452–465 (2019). https://doi.org/10.1038/s41551-019-0400-9

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