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Cited by 499

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Integrated immunoisolation and protein analysis of circulating exosomes using microfluidic technology

Open access
He, Mei, Crow, Jennifer, Roth, Marc, Zeng, Yong, Godwin, Andrew K.·2014·Lab on a Chip

Abstract

Developing blood-based tests is appealing for non-invasive disease diagnosis, especially when biopsy is difficult, costly, and sometimes not even an option. Tumor-derived exosomes have attracted increasing interest in non-invasive cancer diagnosis and monitoring of treatment response. However, the biology and clinical value of exosomes remains largely unknown due in part to current technical challenges in rapid isolation, molecular classification and comprehensive analysis of exosomes. Here we developed a new microfluidic approach to streamline and expedite the exosome analysis pipeline by integrating specific immunoisolation and targeted protein analysis of circulating exosomes. Compared to the conventional methods, our approach enables selective subpopulation isolation and quantitative detection of surface and intravesicular biomarkers directly from a minimally invasive amount of plasma samples (30 μL) within ~100 min with markedly improved detection sensitivity. Using this device, we demonstrated phenotyping of exosome subpopulations by targeting a panel of common exosomal and tumor-specific markers and multiparameter analyses of intravesicular biomarkers in the selected subpopulation. We were able to assess the total expression and phosphorylation levels of IGF-1R in non-small-cell lung cancer patients by probing plasma exosomes as a non-invasive alternative to conventional tissue biopsy. We foresee that the microfluidic exosome analysis platform will form the basis for critically needed infrastructures for advancing the biology and clinical utilization of exosomes.

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Crossref · 10.1039/c4lc00662c

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Metadata

Authors
He, M., Crow, J., Roth, M., Zeng, Y., & Godwin, A. K.
Venue
Lab on a Chip
Published
2014-07-18
Volume
14
Issue
19
Pages
3773
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W2055369603
Cited by
499
References
5
FWCI
9.98
Type
journal article
Language
en
Open access
hybrid

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