Advances in Extracellular Vesicle Nanotechnology for Precision Theranostics

Page view(s)
39
Checked on Oct 03, 2024
Advances in Extracellular Vesicle Nanotechnology for Precision Theranostics
Title:
Advances in Extracellular Vesicle Nanotechnology for Precision Theranostics
Journal Title:
Advanced Science
Publication Date:
14 November 2022
Citation:
Wu, Q., Fu, S., Xiao, H., Du, J., Cheng, F., Wan, S., Zhu, H., Li, D., Peng, F., Ding, X., & Wang, L. (2022). Advances in Extracellular Vesicle Nanotechnology for Precision Theranostics. Advanced Science, 10(3). Portico. https://doi.org/10.1002/advs.202204814
Abstract:
AbstractExtracellular vesicles (EVs) have increasingly been recognized as important cell surrogates influencing many pathophysiological processes, including cellular homeostasis, cancer progression, neurologic disease, and infectious disease. These behaviors enable EVs broad application prospects for clinical application in disease diagnosis and treatment. Many studies suggest that EVs are superior to conventional synthetic carriers in terms of drug delivery and circulating biomarkers for early disease diagnosis, opening up new frontiers for modern theranostics. Despite these clinical potential, EVs containing diverse cellular components, such as nucleic acids, proteins, and metabolites are highly heterogeneous and small size. The limitation of preparatory, engineering and analytical technologies for EVs poses technical barriers to clinical translation. This article aims at present a critical overview of emerging technologies in EVs field for biomedical applications and challenges involved in their clinic translations. The current methods for isolation and identification of EVs are discussed. Additionally, engineering strategies developed to enhance scalable production and improved cargo loading as well as tumor targeting are presented. The superior clinical potential of EVs, particularly in terms of different cell origins and their application in the next generation of diagnostic and treatment platforms, are clarified.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This work was supported by the Leading-edge Technology Programme of Jiangsu Natural Science Foundation (No. BK20212012), Natural Science Foundation (Nos.22207056 and 21902079) and the Natural Science Foundation of JiangsuProvince (Nos. BK20210580 and BK20190724
Description:
ISSN:
2198-3844