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Advanced Nanotechnologies for Extracellular Vesicle-Based Liquid Biopsy
Li Min1, Binshuai Wang2, Han Bao3,4
1Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, 100050, P. R. China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|August 31, 2021
Summary
Extracellular vesicles (EVs) are promising biomarkers for liquid biopsies. Advanced nanotechnology is improving EV isolation, detection, and analysis for disease diagnosis and treatment.
Area of Science:
- Biotechnology
- Nanotechnology
- Biomarker Discovery
Background:
- Extracellular vesicles (EVs) are crucial in intercellular communication and disease progression.
- Their presence in body fluids makes them ideal candidates for non-invasive liquid biopsy biomarkers.
- Efficient isolation and detection of EVs are critical for clinical applications.
Purpose of the Study:
- To provide an overview of advanced nanotechnology for extracellular vesicle (EV) detection.
- To discuss challenges and recent advances in EV isolation, detection, and analysis.
- To highlight future opportunities in EV detection technologies.
Main Methods:
- Review of current nanotechnologies for EV isolation based on physical and chemical properties.
- Summary of high-sensitivity sensors and single EV detection approaches.
- Discussion of EV analysis in clinical settings, including machine learning applications.
Main Results:
- Key challenges in EV-based liquid biopsies were identified.
- Pivotal advances in nanotechnology for EV isolation and detection were summarized.
- The role of machine learning in EV analysis for clinical scenarios was highlighted.
Conclusions:
- Nanotechnology offers significant advancements for EV isolation, detection, and analysis.
- Improved EV detection technologies are essential for effective liquid biopsy applications.
- Future developments in nanotechnology hold promise for next-generation EV detection platforms.
