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基于膜融合和核酸纳米结构的细胞外囊泡微小RNA检测

Extracellular vesicle miRNA detection based on membrane fusion and nucleic acid nanostructures.

作者信息

Han Jixuan, Liu Xiaoran, Yan Ying, Ge Jingwen, Zhao Han, Wang Chen, Song Guohong, Zhu Ling, Yang Yanlian

机构信息

CAS 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.

Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Breast Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.

出版信息

Biosens Bioelectron. 2025 Jul 7;288:117763. doi: 10.1016/j.bios.2025.117763.

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.

摘要

细胞外囊泡微小RNA(EV-miRNAs)与癌症进展、转移和耐药性密切相关,使其成为精准诊断中有前景的生物标志物。然而,基于EV-miRNA的液体活检的临床潜力受到EV-miRNAs丰度低以及包括EV分离、纯化和miRNA定量在内的繁琐检测程序的阻碍。在此,我们开发了一种基于催化发夹组装(CHA)的新型一步荧光检测法,用于灵敏检测EV-miRNAs,并辅以DNA介导的膜融合(DMF)和DNA四面体(DT)(DMF-DT-CHA)。这种DMF-DT-CHA检测法通过DNA之间的相互作用促进脂质体与EV之间的膜融合,以便将DT-CHA探针递送至EV中,随后进行DT-CHA,其识别靶标miRNAs以通过基于CHA的荧光发射启动非酶信号放大。我们使用DMF-DT-CHA分析了来自三种乳腺癌细胞来源的EV,结果与qPCR一致,该平台实现了对EV-miRNAs 0.24 fM的检测限。我们对DMF-DT-CHA检测平台进行了临床评估。受试者操作特征曲线(ROCs)表明,DMF-DT-CHA平台是区分乳腺癌(BC)患者与健康供体以及乳腺癌患者与乳腺良性结节患者的优秀分类器,曲线下面积(AUC)值分别为0.850和0.835,以及在三阴性乳腺癌治疗反应中的准确率为81.1%。DMF-CT-CHA检测平台在癌症诊断和治疗监测方面具有临床潜力。

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