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Fusogenic Liposome-Mediated Extracellular Vesicles MicroRNA Profiling for Lung Cancer Diagnosis
Fanyu Meng1,2,3, Ruimin Wang4, Wenjun Yu1
1Department of Clinical Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, P. R. China.
ACS Nano
|April 7, 2026
Summary
We developed a novel liposome nanoreactor for direct profiling of extracellular vesicle-associated microRNAs (EVs-miRNA) in lung cancer (LC) patients. This RNA extraction-free method enables ultrasensitive detection and accurate LC diagnosis and monitoring.
Area of Science:
- Biotechnology
- Molecular Diagnostics
- Oncology
Background:
- Circulating extracellular vesicle-associated microRNAs (EVs-miRNA) are crucial biomarkers for lung cancer (LC) diagnosis and prognosis.
- Current liquid biopsy methods for EVs-miRNA profiling are limited by complex RNA extraction and lack of specific LC signatures.
Purpose of the Study:
- To develop a simplified, ultrasensitive platform for direct profiling of plasma EVs-miRNAs for lung cancer management.
- To identify and validate a lung cancer-specific EVs-miRNA signature.
Main Methods:
- Development of a fusogenic liposome nanoreactor integrating reagent encapsulation, isothermal rolling circle amplification, and CRISPR-Cas12a cleavage for one-pot, direct EVs-miRNA profiling.
- Identification and validation of a lung cancer-specific EVs-miRNA signature using public databases and clinical samples.
- Proof-of-concept study in a clinical cohort (n=141) for diagnosis, therapy monitoring, and prognosis.
Main Results:
- The nanoreactor platform achieved ultrasensitive detection down to fM levels.
- A validated LC-specific EVs-miRNA signature was identified.
- The signature enabled early diagnosis, therapy monitoring, and prognosis evaluation with up to 93.1% accuracy in a clinical cohort.
Conclusions:
- The developed fusogenic liposome nanoreactor offers an RNA extraction-free, streamlined workflow for direct plasma EVs-miRNA profiling.
- This platform provides a promising liquid biopsy framework for early lung cancer diagnosis, monitoring, and prognosis.
