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Proximity Proteomics Has Potential for Extracellular Vesicle Identification
- Source :
- Journal of Proteome Research. 20:3519-3531
- Publication Year :
- 2021
- Publisher :
- American Chemical Society (ACS), 2021.
-
Abstract
- Extracellular vesicles (EVs) are biomarkers and mediators of intercellular communication. In biological samples, EVs are secreted by various types of cells. The proteomic identification of proteins expressed in EVs has potential to contribute to research and clinical applications, particularly for cancer. In this study, the proximity-labeling method-based proteomic approach was used for EV identification, labeling membrane components proximal to a given molecule on the EV membrane surface. Due to the small labeling range, proteins on the surface of the same EVs are likely to be labeled by selecting a given EV surface antigen. The protein group of cancer cell-secreted EV (cEV), which abundantly expresses a close homologue of L1 (CHL1), was examined using a model mouse for lung cancer (LC). cEV-expressed proteins were identified by proteomic analysis of enzyme-mediated activation of radical sources by comparing serum EVs from wild-type and LC mice. SLC4A1 was found to be co-expressed in CHL1-expressing EVs, highlighting EVs expressing both CHL1 and SLC4A1 as candidates for cEVs. Serum EVs expressing both CHL1 and caspase 14 were significantly elevated in LC patients compared with healthy individuals. Thus, the combination of proximity labeling and proteomic analysis allows for effective EV identification.
- Subjects :
- Proteomics
0301 basic medicine
Biochemistry
CHL1
Extracellular Vesicles
Mice
03 medical and health sciences
Antigen
Anion Exchange Protein 1, Erythrocyte
medicine
Animals
Humans
Membrane surface
030102 biochemistry & molecular biology
Chemistry
Proteins
Cancer
General Chemistry
Extracellular vesicle
medicine.disease
Cell biology
030104 developmental biology
Caspase 14
Cell Adhesion Molecules
Biomarkers
Intracellular
Subjects
Details
- ISSN :
- 15353907 and 15353893
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Journal of Proteome Research
- Accession number :
- edsair.doi.dedup.....8d0bd4e0dc94fa83d0e19c42f0df791f
- Full Text :
- https://doi.org/10.1021/acs.jproteome.1c00149