The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip
Open accessAbstract
The performance of current microfluidic methods for exosome detection is constrained by boundary conditions, as well as fundamental limits to microscale mass transfer and interfacial exosome binding. Here, we show that a microfluidic chip designed with self-assembled three-dimensional herringbone nanopatterns can detect low levels of tumour-associated exosomes in plasma (10 exosomes μl−1, or approximately 200 vesicles per 20 μl of spiked sample) that would otherwise be undetectable by standard microfluidic systems for biosensing. The nanopatterns promote microscale mass transfer, increase surface area and probe density to enhance the efficiency and speed of exosome binding, and permit drainage of the boundary fluid to reduce near-surface hydrodynamic resistance, thus promoting particle–surface interactions for exosome binding. We used the device for the detection—in 2 μl plasma samples from 20 ovarian cancer patients and 10 age-matched controls—of exosome subpopulations expressing CD24, epithelial cell adhesion molecule and folate receptor alpha proteins, and suggest exosomal folate receptor alpha as a potential biomarker for early detection and progression monitoring of ovarian cancer. The nanolithography-free nanopatterned device should facilitate the use of liquid biopsies for cancer diagnosis. A microfluidic chip with self-assembled 3D herringbone nanopatterns detects, with high sensitivity and specificity, tumour-associated exosomes in few-microlitre plasma samples from patients.
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Cites
Biological properties of extracellular vesicles and their physiological functions
Yáñez‐Mó, M., Siljander, P. R. ‐., Andreu, Z., Bedina Zavec, A., Borràs, F. E., Buzas, E. I., Buzas, K., Casal, E., Cappello, F., Carvalho, J., et al. (2015) · Journal of Extracellular Vesicles · doi:10.3402/jev.v4.27066 · Cited by 5,926
Skog, J., Würdinger, T., van Rijn, S., Meijer, D. H., Gainche, L., Curry, W. T., Carter, B. S., Krichevsky, A. M., & Breakefield, X. O. (2008) · Nature Cell Biology · doi:10.1038/ncb1800 · Cited by 5,001
Chaotic Mixer for Microchannels
Stroock, A. D., Dertinger, S. K. W., Ajdari, A., Mezić, I., Stone, H. A., & Whitesides, G. M. (2002) · Science · doi:10.1126/science.1066238 · Cited by 3,435
Glypican-1 identifies cancer exosomes and detects early pancreatic cancer
Melo, S. A., Luecke, L. B., Kahlert, C., Fernandez, A. F., Gammon, S. T., Kaye, J., LeBleu, V. S., Mittendorf, E. A., Weitz, J., Rahbari, N., et al. (2015) · Nature · doi:10.1038/nature14581 · Cited by 2,880
Optimized exosome isolation protocol for cell culture supernatant and human plasma
Lobb, R. J., Becker, M., Wen Wen, S., Wong, C. S. F., Wiegmans, A. P., Leimgruber, A., & Möller, A. (2015) · Journal of Extracellular Vesicles · doi:10.3402/jev.v4.27031 · Cited by 1,705
Isolation of circulating tumor cells using a microvortex-generating herringbone-chip
Stott, S. L., Hsu, C.-H., Tsukrov, D. I., Yu, M., Miyamoto, D. T., Waltman, B. A., Rothenberg, S. M., Shah, A. M., Smas, M. E., Korir, G. K., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1012539107 · Cited by 1,634
Evaluating cell lines as tumour models by comparison of genomic profiles
Domcke, S., Sinha, R., Levine, D. A., Sander, C., & Schultz, N. (2013) · Nature Communications · doi:10.1038/ncomms3126 · Cited by 1,418
The biology of ovarian cancer: new opportunities for translation
Bast, R. C., Hennessy, B., & Mills, G. B. (2009) · Nature Reviews Cancer · doi:10.1038/nrc2644 · Cited by 1,358
Label-free detection and molecular profiling of exosomes with a nano-plasmonic sensor
Im, H., Shao, H., Park, Y. I., Peterson, V. M., Castro, C. M., Weissleder, R., & Lee, H. (2014) · Nature Biotechnology · doi:10.1038/nbt.2886 · Cited by 1,321
Quantitative and stoichiometric analysis of the microRNA content of exosomes
Chevillet, J. R., Kang, Q., Ruf, I. K., Briggs, H. A., Vojtech, L. N., Hughes, S. M., Cheng, H. H., Arroyo, J. D., Meredith, E. K., Gallichotte, E. N., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1408301111 · Cited by 1,096
Cited by
Crosby, D., Bhatia, S., Brindle, K. M., Coussens, L. M., Dive, C., Emberton, M., Esener, S., Fitzgerald, R. C., Gambhir, S. S., Kuhn, P., et al. (2022) · Science · doi:10.1126/science.aay9040 · Cited by 1,379
Exosomes as a new frontier of cancer liquid biopsy
Yu, D., Li, Y., Wang, M., Gu, J., Xu, W., Cai, H., Fang, X., & Zhang, X. (2022) · Molecular Cancer · doi:10.1186/s12943-022-01509-9 · Cited by 855
Review on Strategies and Technologies for Exosome Isolation and Purification
Chen, J., Li, P., Zhang, T., Xu, Z., Huang, X., Wang, R., & Du, L. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.811971 · Cited by 585
A one-pot isothermal Cas12-based assay for the sensitive detection of microRNAs
Yan, H., Wen, Y., Tian, Z., Hart, N., Han, S., Hughes, S. J., & Zeng, Y. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01033-1 · Cited by 361
Self-citationAdvances in mesenchymal stem cell exosomes: a review
Tang, Y., Zhou, Y., & Li, H.-J. (2021) · Stem Cell Research & Therapy · doi:10.1186/s13287-021-02138-7 · Cited by 327
Metadata
- Authors
- Zhang, P., Zhou, X., He, M., Shang, Y., Tetlow, A. L., Godwin, A. K., & Zeng, Y.
- Venue
- Nature Biomedical Engineering
- Published
- 2019-02-25
- Volume
- 3
- Issue
- 6
- Pages
- 438-451
- ISSN
- 2157-846X (ISSN-L)
- OpenAlex
- W2917401432
- Cited by
- 554
- References
- 49
- FWCI
- 19.62
- Type
- journal article
- Language
- en
- Open access
- green
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- Zhang, P., Zhou, X., He, M., Shang, Y., Tetlow, A. L., Godwin, A. K., & Zeng, Y. (2019). Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip. Nature Biomedical Engineering. https://doi.org/10.1038/s41551-019-0356-9
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