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Transition to invasion in breast cancer: a microfluidic in vitro model enables examination of spatial and temporal effects
Open accessAbstract
The transition of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) is a critical step in breast cancer progression. We introduce a simple microfluidic 3D compartmentalized system in which mammary epithelial cells (MCF-DCIS) are co-cultured with human mammary fibroblasts (HMFs), which promotes a transition from DCIS to IDC in vitro. The model enables control of both spatial (distance-dependence) and temporal (transition from larger clusters) aspects within the microenvironment, allowing recapitulation of the in vivo environment in ways not practical with existing experimental models. When HMFs were cultured some distance (0.5-1.5 mm) from the MCF-DCIS cells, we observed an initial morphological change, suggesting soluble factors can begin the transition. However, cell-cell contact with HMFs allowed the MCF-DCIS cells to complete the transition to invasion. Uniquely, the compartmentalized platform enables the analysis of the intrinsic second harmonic generation signal of collagen, providing a label-free quantitative analysis of DCIS-associated collagen remodeling. The arrayed microchannel-based model is compatible with existing infrastructure and, for the first time, provides a cost effective approach to test for inhibitors of pathways involved in DCIS progression to IDC allowing a screening approach to the identification of potential therapeutic targets. Importantly, the model can be easily adapted and generalized to a variety of cell-cell signaling studies.
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“The HMFs and MCF10-DCIS cells established a crosstalk at the interface between the cancerous and normal microtissue sections.”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
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“MCF10-DCIS cancer cells adopted different shapes (i.e., their circularity, roundness, and aspect ratio significantly changed) as a function of their distance from the interface”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
In the citing paper
“The change in shape of MCF710-DCIS cells, and their ability to remodel the matrix, suggested the onset of a DCIS to IDS transition.”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
In the citing paper
“and the cell–cell contact between HMFs and MCF-DCIS cells favored the completed transition to an invasive phenotype.”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
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“Clusters of cells in co-culture (HMF and MCF10-DCIS) affected the structure (physical appearance under the microscope) of the matrix significantly more than did monocultured MCF10-DCIS cells.”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
In the citing paper
“This transition strongly depended on the distance between the cells, being more evident around the cell interfaces.”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
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“Sung’s experimental results suggested an underlying two-step molecular mechanism for the transition from DCIS to IDS”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
In the citing paper
“suggesting that soluble factors could initiate the transition”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
The cited source says what the claim attributes to it.
In the citing paper
“An initial morphological change was first observed when HMFs were cultured at some distance (0.5–1.5 mm) from the MCF-DCIS cells”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [33]
In the citing paper
“Based on spheroids, Sung’s group proposed a 3D microfluidic model of breast cancer invasion using surface tension pumping to achieve the sequential loading of cells at different time points177.”
From Tumor-on-a-chip: from bioinspired design to biomedical application (2021) · cites this paper as [177]
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Citations
Cites
The distribution of secondary growths in cancer of the breast.
Paget, S. (1889) · The Lancet · doi:10.1016/s0140-6736(00)49915-0 · Cited by 5,277
Collagen reorganization at the tumor-stromal interface facilitates local invasion
Provenzano, P. P., Eliceiri, K. W., Campbell, J. M., Inman, D. R., White, J. G., & Keely, P. J. (2006) · BMC Medicine · doi:10.1186/1741-7015-4-38 · Cited by 1,804
Self-citationGaggioli, C., Hooper, S., Hidalgo-Carcedo, C., Grosse, R., Marshall, J. F., Harrington, K., & Sahai, E. (2007) · Nature Cell Biology · doi:10.1038/ncb1658 · Cited by 1,589
Interpreting Second-Harmonic Generation Images of Collagen I Fibrils
Williams, R. M., Zipfel, W. R., & Webb, W. W. (2004) · Biophysical Journal · doi:10.1529/biophysj.104.047308 · Cited by 847
Dynamic imaging of collagen and its modulation in tumors in vivo using second-harmonic generation
Brown, E. B., McKee, T. D., DiTomaso, E., Pluen, A., Seed, B., Boucher, Y., & Jain, R. K. (2003) · Nature Medicine · doi:10.1038/nm879 · Cited by 844
Reconstruction of functionally normal and malignant human breast tissues in mice
Kuperwasser, C., Chavarria, T. E., Wu, M., Magrane, G., Gray, J. W., Carey, L., Richardson, A. L., & Weinberg, R. A. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0401064101 · Cited by 807
Ductal Carcinoma in Situ of the Breast
Burstein, H. J., Polyák, K., Wong, J. S., Lester, S. C., & Kaelin, C. M. (2004) · New England Journal of Medicine · doi:10.1056/nejmra031301 · Cited by 769
Biological implications of polydimethylsiloxane-based microfluidic cell culture
Regehr, K. J., Domenech, M., Koepsel, J. T., Carver, K. C., Ellison-Zelski, S. J., Murphy, W. L., Schuler, L. A., Alarid, E. T., & Beebe, D. J. (2009) · Lab on a Chip · doi:10.1039/b903043c · Cited by 719
Self-citationThe actin cytoskeleton in cancer cell motility
Olson, M. F., & Sahai, E. A. (2008) · Clinical & Experimental Metastasis · doi:10.1007/s10585-008-9174-2 · Cited by 577
ErbB2, but not ErbB1, reinitiates proliferation and induces luminal repopulation in epithelial acini
Muthuswamy, S. K., Li, D., Lelièvre, S. A., Bissell, M. J., & Brugge, J. S. (2001) · Nature Cell Biology · doi:10.1038/ncb0901-785 · Cited by 554
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Mazzaglia, C., Sheng, Y., Rodrigues, L. N., Lei, I. M., Shields, J. D., & Huang, Y. Y. S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.08.487692 · Cited by 1
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MacMillan, C. D. (2012) · Scholarship@Western (Western University)
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Zhang, Z. (2016) · Deep Blue (University of Michigan)
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Soltanian‐Zadeh, S. (2016) · VTechWorks (Virginia Tech)
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Qiao, J. (2022) · Digital Archive @ GSU · doi:10.57709/2387856
Dean, T. (2018) · TSpace (University of Toronto)
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Kulwatno, J., Gong, X., DeVaux, R., Herschkowitz, J. I., & Mills, K. L. (2020) · bioRxiv · doi:10.1101/2020.08.06.240242
Tiessen, N., Dabaghi, M., Cao, Q., Chandiramohan, A., Selvaganapathy, P. R., & Hirota, J. A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.19.390674
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He, B. J. (2021) · Georgetown Scientific Research Journal · doi:10.48091/gsr.v1i2.21
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Zhang, X. (2012) · CRC Press eBooks · doi:10.1201/b12935-26
Human organs-on-a-chip for cancer modeling
Hegde, M., Girisa, S., & Harsha, C. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13782-2.00005-x
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Metadata
- Authors
- Sung, K. E., Yang, N., Pehlke, C., Keely, P. J., Eliceiri, K. W., Friedl, A., & Beebe, D. J.
- Affiliations
- University of Wisconsin–Madison (US)
- United States Department of Veterans Affairs (US)
- Corresponding author
- Beebe, David J.
- Venue
- Integr. Biol.
- Publisher
- Oxford University Press (OUP)
- Published
- 2011
- Volume
- 3
- Issue
- 4
- Pages
- 439-450
- ISSN
- 1757-9694 (ISSN-L)
- 1757-9708
- PMC
- PMC3094750
- OpenAlex
- W2103232525
- Cited by
- 226
- References
- 32
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 4 · 2023: 8 · 2022: 14 · 2021: 19 · 2020: 22 · 2019: 12 · 2018: 20 · 2017: 22 · 2016: 15 · 2015: 19 · 2014: 18 · 2013: 23 · 2012: 16
- FWCI
- 8.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Integrative Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA107012, R01CA114462, R33CA137673, K25CA104162)
- U.S. National Library of Medicine (T15LM007359)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular Mechanics and Interactions
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Keywords
- ductal carcinoma in situ, invasive ductal carcinoma, breast cancer progression, mammary epithelial cells, cell-cell contact, collagen remodeling, second harmonic generation microscopy, microchannel arrays, therapeutic target screening, tumor microenvironment
- MeSH terms
- Actins, Animals, Breast Neoplasms, Cell Line, Collagen, Drug Combinations, Female, Fibroblasts, Humans, Laminin, Mice, Nude, Neoplasm Invasiveness, Proteoglycans, Time Factors, Cadherins, Extracellular Matrix Proteins, Coculture Techniques, Fibrillar Collagens, Collagen Type I, Collagen Type IV, Microscopy, Fluorescence, Multiphoton, Carcinoma, Ductal, Cell Line, Tumor, Microfluidic Analytical Techniques, Cell Proliferation, Mice
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