肝细胞癌
细胞外小泡
流式细胞术
癌症研究
肝硬化
纳米技术
医学
计算机科学
材料科学
生物
内科学
免疫学
细胞生物学
作者
Xinyu Li,Yuan-jie Liu,Yunpeng Fan,Gang Tian,Bo Shen,Songzhi Zhang,Xuhuai Fu,Wen He,Xingyu Tao,Xiaojuan Ding,Xinmin Li,Shijia Ding
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-04-17
卷期号:18 (17): 11389-11403
被引量:2
标识
DOI:10.1021/acsnano.4c01310
摘要
Tumor-derived extracellular vesicles (tEVs) hold immense promise as potential biomarkers for the precise diagnosis of hepatocellular carcinoma (HCC). However, their clinical translation is hampered by their inherent characteristics, such as small size and high heterogeneity and complex environment, including non-EV particles and normal cell-derived EVs, which prolong separation procedures and compromise detection accuracy. In this study, we devised a DNA cascade reaction-triggered individual EV nanoencapsulation (DCR-IEVN) strategy to achieve the ultrasensitive and specific detection of tEV subpopulations via routine flow cytometry in a one-pot, one-step fashion. DCR-IEVN enables the direct and selective packaging of multiple tEV subpopulations in clinical serum samples into flower-like particles exceeding 600 nm. This approach bypasses the need for EV isolation, effectively reducing interference from non-EV particles and nontumor EVs. Compared with conventional analytical technologies, DCR-IEVN exhibits superior efficacy in diagnosing HCC owing to its high selectivity for tEVs. Integration of machine learning algorithms with DCR-IEVN resulted in differential diagnosis accuracy of 96.7% for the training cohort (
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