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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Exosomes derived from cancer cells have been recognized as a promising biomarker for minimally invasive liquid biopsy. Herein, a novel sandwich-type biosensor was fabricated for highly sensitive detection of exosomes. Amino-functionalized Fe3O4 nanoparticles were synthesized as a sensing interface with a large surface area and rapid enrichment capacity, while two-dimensional MXene nanosheets were used as signal amplifiers with excellent electrical properties. Specifically, CD63 aptamer attached Fe3O4 nanoprobes capture the target exosomes. MXene nanosheets modified with epithelial cell adhesion molecule (EpCAM) aptamer were tethered on the electrode surface to enhance the quantification of exosomes captured with the detection of remaining protein sites. With such a design, the proposed biosensor showed a wide linear range from 102 particles μL−1 to 107 particles μL−1 for sensing 4T1 exosomes, with a low detection limit of 43 particles μL−1. In addition, this sensing platform can determine four different tumor cell types (4T1, Hela, HepG2, and A549) using surface proteins corresponding to aptamers 1 and 2 (CD63 and EpCAM) and showcases good specificity in serum samples. These preliminary results demonstrate the feasibility of establishing a sensitive, accurate, and inexpensive electrochemical sensor for detecting exosome concentrations and species. Moreover, they provide a significant reference for exosome applications in clinical settings, such as liquid biopsy and early cancer diagnosis.

Details

Title
High-Performance Detection of Exosomes Based on Synergistic Amplification of Amino-Functionalized Fe3O4 Nanoparticles and Two-Dimensional MXene Nanosheets
Author
Zhuang, Linlin 1 ; You, Qiannan 1 ; Su, Xue 1 ; Chang, Zhimin 2 ; Ge, Mingfeng 2 ; Qian Mei 2 ; Yang, Li 3 ; Dong, Wenfei 1   VIAFID ORCID Logo  ; Li, Li 1   VIAFID ORCID Logo 

 School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China 
 Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China 
 Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China 
First page
3508
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
14248220
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2799748787
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.