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Proteomic profiling of NCI-60 extracellular vesicles uncovers common protein cargo and cancer type-specific biomarkers
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// Stephanie N. Hurwitz 1, * , Mark A. Rider 1, * , Joseph L. Bundy 1, * , Xia Liu 1 , Rakesh K. Singh 1 , David G. Meckes Jr. 1 1 Department of Biomedical Sciences, Florida State University College of Medicine, Tallahassee, FL, 32306, USA * These authors contributed equally to this work Correspondence to: David G. Meckes Jr., email: david.meckes@med.fsu.edu Keywords: exosomes, microvesicles, co-inertia, proteomics, biomarkers Received: September 28, 2016 Accepted: November 07, 2016 Published: November 24, 2016 ABSTRACT Packed with biological information, extracellular vesicles (EVs) offer exciting promise for biomarker discovery and applications in therapeutics and non-invasive diagnostics. Currently, our understanding of EV contents is confined by the limited cells from which vesicles have been characterized utilizing the same enrichment method. Using sixty cell lines from the National Cancer Institute (NCI-60), here we provide the largest proteomic profile of EVs in a single study, identifying 6,071 proteins with 213 common to all isolates. Proteins included established EV markers, and vesicular trafficking proteins such as Rab GTPases and tetraspanins. Differentially-expressed proteins offer potential for cancer diagnosis and prognosis. Network analysis of vesicle quantity and proteomes identified EV components associated with vesicle secretion, including CD81, CD63, syntenin-1, VAMP3, Rab GTPases, and integrins. Integration of vesicle proteomes with whole-cell molecular profiles revealed similarities, suggesting EVs provide a reliable reflection of their progenitor cell content, and are therefore excellent indicators of disease.
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Metadata
- Authors
- Hurwitz, S. N., Rider, M. A., Bundy, J. L., Liu, X., Singh, R. K., & Meckes, D. G.
- Venue
- Oncotarget
- Publisher
- Impact Journals, LLC
- Published
- 2016-11-24
- Volume
- 7
- Issue
- 52
- Pages
- 86999-87015
- ISSN
- 1949-2553 (ISSN-L)
- OpenAlex
- W2556224708
- Cited by
- 305
- References
- 70
- FWCI
- 10.08
- Type
- journal article
- Language
- en
- Open access
- diamond
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