The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A rapid, automated surface protein profiling of single circulating exosomes in human blood
Open accessAbstract
Circulating exosomes provide a promising approach to assess novel and dynamic biomarkers in human disease, due to their stability, accessibility and representation of molecules from source cells. However, this potential has been stymied by lack of approaches for molecular profiling of individual exosomes, which have a diameter of 30–150 nm. Here we report a rapid analysis approach to evaluate heterogeneous surface protein expression in single circulating exosomes from human blood. Our studies show a differential CD47 expression in blood-derived individual circulating exosomes that is correlated with breast cancer status, demonstrating a great potential of individual exosome profiles in biomarker discovery. The sensitive and high throughput platform of single exosome analysis can also be applied to characterizing exosomes derived from other patient fluids.
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Cites
Isolation and Characterization of Exosomes from Cell Culture Supernatants and Biological Fluids
Théry, C., Amigorena, S., Raposo, G., & Clayton, A. (2006) · Current Protocols in Cell Biology · doi:10.1002/0471143030.cb0322s30 · Cited by 5,766
Tumour exosome integrins determine organotropic metastasis
Hoshino, A., Costa-Silva, B., Shen, T.-L., Rodrigues, G., Hashimoto, A., Tesic Mark, M., Molina, H., Kohsaka, S., Di Giannatale, A., Ceder, S., et al. (2015) · Nature · doi:10.1038/nature15756 · Cited by 5,101
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
Majeti, R., Chao, M. P., Alizadeh, A. A., Pang, W. W., Jaiswal, S., Gibbs, K. D., van Rooijen, N., & Weissman, I. L. (2009) · Cell · doi:10.1016/j.cell.2009.05.045 · Cited by 1,752
Chao, M. P., Jaiswal, S., Weissman-Tsukamoto, R., Alizadeh, A. A., Gentles, A. J., Volkmer, J., Weiskopf, K., Willingham, S. B., Raveh, T., Park, C. Y., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3001375 · Cited by 776
Cited by
Exosomes facilitate therapeutic targeting of oncogenic KRAS in pancreatic cancer
Kamerkar, S., LeBleu, V. S., Sugimoto, H., Yang, S., Ruivo, C. F., Melo, S. A., Lee, J. J., & Kalluri, R. (2017) · Nature · doi:10.1038/nature22341 · Cited by 2,639
Technical challenges of working with extracellular vesicles
Ramirez, M. I., Amorim, M. G., Gadelha, C., Milic, I., Welsh, J. A., Freitas, V. M., Nawaz, M., Akbar, N., Couch, Y., Makin, L., et al. (2018) · Nanoscale · doi:10.1039/c7nr08360b · Cited by 516
Single-Exosome-Counting Immunoassays for Cancer Diagnostics
Liu, C., Xu, X., Li, B., Situ, B., Pan, W., Hu, Y., An, T., Yao, S., & Zheng, L. (2018) · Nano Letters · doi:10.1021/acs.nanolett.8b01184 · Cited by 406
Multiplexed Profiling of Single Extracellular Vesicles
Lee, K., Fraser, K., Ghaddar, B., Yang, K., Kim, E., Balaj, L., Chiocca, E. A., Breakefield, X. O., Lee, H., & Weissleder, R. (2018) · ACS Nano · doi:10.1021/acsnano.7b07060 · Cited by 369
Self-citationShin, H., Jeong, H., Park, J., Hong, S., & Choi, Y. (2018) · ACS Sensors · doi:10.1021/acssensors.8b01047 · Cited by 246
Metadata
- Authors
- Kibria, G., Ramos, E. K., Lee, K. E., Bedoyan, S., Huang, S., Samaeekia, R., Athman, J. J., Harding, C. V., Lötvall, J., Harris, L., Thompson, C. L., & Liu, H.
- Venue
- Scientific Reports
- Published
- 2016-11-07
- Volume
- 6
- Issue
- 1
- Pages
- 36502-36502
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2552535243
- Cited by
- 172
- References
- 5
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kibria, G., Ramos, E. K., Lee, K. E., Bedoyan, S., Huang, S., Samaeekia, R., Athman, J. J., Harding, C. V., Lötvall, J., Harris, L., Thompson, C. L., & Liu, H. (2016). A rapid, automated surface protein profiling of single circulating exosomes in human blood. Scientific Reports. https://doi.org/10.1038/srep36502
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
