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A model of breast cancer heterogeneity reveals vascular mimicry as a driver of metastasis

Open access
Wagenblast, Elvin, Soto, Mar, Gutiérrez-Ángel, Sara, Hartl, Christina A., Gable, Annika L., Maceli, Ashley R., Erard, Nicolas, Williams, Alissa M., Kim, Sun Y., Dickopf, Steffen, Harrell, J. Chuck, Smith, Andrew D., Perou, Charles M., Wilkinson, John E., Hannon, Gregory J., Knott, Simon R. V.·2015·Nature

Abstract

Cancer metastasis requires that primary tumour cells evolve the capacity to intravasate into the lymphatic system or vasculature, and extravasate into and colonize secondary sites. Others have demonstrated that individual cells within complex populations show heterogeneity in their capacity to form secondary lesions. Here we develop a polyclonal mouse model of breast tumour heterogeneity, and show that distinct clones within a mixed population display specialization, for example, dominating the primary tumour, contributing to metastatic populations, or showing tropism for entering the lymphatic or vasculature systems. We correlate these stable properties to distinct gene expression profiles. Those clones that efficiently enter the vasculature express two secreted proteins, Serpine2 and Slpi, which were necessary and sufficient to program these cells for vascular mimicry. Our data indicate that these proteins not only drive the formation of extravascular networks but also ensure their perfusion by acting as anticoagulants. We propose that vascular mimicry drives the ability of some breast tumour cells to contribute to distant metastases while simultaneously satisfying a critical need of the primary tumour to be fed by the vasculature. Enforced expression of SERPINE2 and SLPI in human breast cancer cell lines also programmed them for vascular mimicry, and SERPINE2 and SLPI were overexpressed preferentially in human patients that had lung-metastatic relapse. Thus, these two secreted proteins, and the phenotype they promote, may be broadly relevant as drivers of metastatic progression in human cancer.

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Metadata

Authors
Wagenblast, E., Soto, M., Gutiérrez-Ángel, S., Hartl, C. A., Gable, A. L., Maceli, A. R., Erard, N., Williams, A. M., Kim, S. Y., Dickopf, S., Harrell, J. C., Smith, A. D., Perou, C. M., Wilkinson, J. E., Hannon, G. J., & Knott, S. R. V.
Venue
Nature
Published
2015-04
Volume
520
Issue
7547
Pages
358-362
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W1979486580
Cited by
433
References
3
FWCI
15.99
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A model of breast cancer heterogeneity reveals vascular mimicry as a driver of metastasis. https://app.cochat.ai/papers/10.1038/nature14403
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Wagenblast, E., Soto, M., Gutiérrez-Ángel, S., Hartl, C. A., Gable, A. L., Maceli, A. R., Erard, N., Williams, A. M., Kim, S. Y., Dickopf, S., Harrell, J. C., Smith, A. D., Perou, C. M., Wilkinson, J. E., Hannon, G. J., & Knott, S. R. V. (2015). A model of breast cancer heterogeneity reveals vascular mimicry as a driver of metastasis. Nature. https://doi.org/10.1038/nature14403

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.