Effective Separation of Cancer‐Derived Exosomes in Biological Samples for Liquid Biopsy: Classic Strategies and Innovative Development
Abstract: Liquid biopsy has remarkably facilitated clinical diagnosis and surveillance of cancer via employing a non‐invasive way to detect cancer‐derived components, such as circulating tumor DNA and circulating tumor cells from biological fluid samples. The cancer‐derived exosomes, which are nano‐sized vesicles secreted by cancer cells have been investigated in liquid biopsy as their important roles in intracellular communication and disease development have been revealed. Given the challenges posed by the complicated humoral microenvironment, which contains a variety of different cells and macromolecular substances in addition to the exosomes, it has attracted a large amount of attention to effectively isolate exosomes from collected samples. In this review, the authors aim to analyze classic strategies for separation of cancer‐derived exosomes, giving an extensive discussion of advantages and limitations of these methods. Furthermore, the innovative multi‐strategy methods to realize efficient isolation of cancer‐derived exosomes in practical applications are also presented. Additionally, the possible development trends of exosome separation in to the future is discussed in this review.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Effective Separation of Cancer‐Derived Exosomes in Biological Samples for Liquid Biopsy: Classic Strategies and Innovative Development ; day:09 ; month:05 ; year:2022 ; extent:16
Global challenges ; (09.05.2022) (gesamt 16)
- Creator
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Xie, Yujiao
Xu, Xiawei
Lin, Jie
Xu, Yanping
Wang, Jing
Ren, Yong
Wu, Aiguo
- DOI
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10.1002/gch2.202100131
- URN
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urn:nbn:de:101:1-2022051015083373941397
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:38 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Xie, Yujiao
- Xu, Xiawei
- Lin, Jie
- Xu, Yanping
- Wang, Jing
- Ren, Yong
- Wu, Aiguo
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