Label-Free Surface Protein Profiling of Extracellular Vesicles by an Electrokinetic Sensor.
biosensor
cancer
electrokinetic effect
extracellular vesicles
label-free
protein profiling
Journal
ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031
Informations de publication
Date de publication:
24 05 2019
24 05 2019
Historique:
pubmed:
26
4
2019
medline:
17
4
2020
entrez:
26
4
2019
Statut:
ppublish
Résumé
Small extracellular vesicles (sEVs) generated from the endolysosomal system, often referred to as exosomes, have attracted interest as a suitable biomarker for cancer diagnostics, as they carry valuable biological information and reflect their cells of origin. Herein, we propose a simple and inexpensive electrical method for label-free detection and profiling of sEVs in the size range of exosomes. The detection method is based on the electrokinetic principle, where the change in the streaming current is monitored as the surface markers of the sEVs interact with the affinity reagents immobilized on the inner surface of a silica microcapillary. As a proof-of-concept, we detected sEVs derived from the non-small-cell lung cancer (NSCLC) cell line H1975 for a set of representative surface markers, such as epidermal growth factor receptor (EGFR), CD9, and CD63. The detection sensitivity was estimated to be ∼175000 sEVs, which represents a sensor surface coverage of only 0.04%. We further validated the ability of the sensor to measure the expression level of a membrane protein by using sEVs displaying artificially altered expressions of EGFR and CD63, which were derived from NSCLC and human embryonic kidney (HEK) 293T cells, respectively. The analysis revealed that the changes in EGFR and CD63 expressions in sEVs can be detected with a sensitivity in the order of 10% and 3%, respectively, of their parental cell expressions. The method can be easily parallelized and combined with existing microfluidic-based EV isolation technologies, allowing for rapid detection and monitoring of sEVs for cancer diagnosis.
Identifiants
pubmed: 31020844
doi: 10.1021/acssensors.9b00418
doi:
Substances chimiques
Biomarkers
0
Tetraspanin 30
0
EGFR protein, human
EC 2.7.10.1
ErbB Receptors
EC 2.7.10.1
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM