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Updated: Sep 13, 2025

Author Spotlight: Exploring the Mechanisms of MicroRNA Loading into Extracellular Vesicles in Cancer Progression
Published on: October 6, 2023
Extracellular vesicle miRNA detection based on membrane fusion and nucleic acid nanostructures
Jixuan Han1, Xiaoran Liu2, Ying Yan2
1CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing, 100190, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 101408, China; Sino-Danish Centre for Education and Research, Beijing, 101408, China.
Abstract:
Extracellular vesicle miRNAs (EV-miRNAs) are strongly linked to cancer progression, metastasis, and drug resistance, making them promising biomarkers for precision diagnosis. However, the clinical potential of EV-miRNA-based liquid biopsies is hindered by the low abundance of EV-miRNAs and the tedious detection procedure including EV separation, purification and miRNA quantification. Here, we develop a novel one-step catalytic hairpin assembly (CHA)-based fluorescent assay for sensitive detection of EV-miRNAs assisted with DNA-mediated membrane fusion (DMF) and DNA tetrahedron (DT) (DMF-DT-CHA). This DMF-DT-CHA assay facilitates the membrane fusion between liposome and EV through interactions between DNAs for DT-CHA probe delivery into EVs, and followed by DT-CHA, which recognizes target miRNAs to initiate non-enzymatic signal amplification via CHA-based fluorescence emission. We analyzed EVs from three breast cancer cell sources using DMF-DT-CHA and the results were consistent with qPCR and the platform achieved the limit of detection (LoD) of 0.24 fM for EV-miRNAs. We performed a clinical evaluation of the DMF-DT-CHA assay platform. Recipient operating characteristic curves (ROCs) showed that the DMF-DT-CHA platform was an excellent classifier for distinguishing breast cancer (BC) patients from healthy donors and breast cancer patients from benign breast nodule patients, with area under the curve (AUC) values of 0.850 and 0.835, respectively, as well as an accuracy of 81.1 % in response to treatment for triple-negative breast cancer. DMF-CT-CHA assay platform has clinical potential for cancer diagnosis and treatment monitoring.
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