细胞外小泡
纳米技术
DNA
硫黄素
适体
化学
生物标志物发现
生物标志物
计算生物学
分子生物学
生物
蛋白质组学
材料科学
细胞生物学
生物化学
医学
疾病
基因
病理
阿尔茨海默病
作者
Yuanjie Liu,Yunpeng Fan,Xiaoqiang Li,Gang Tian,Bo Shen,Menghan Li,Kai Su,Xuhuai Fu,Mengxuan Zhang,Yonghong Wang,Xinyu Li,Xinmin Li,Shijia Ding
标识
DOI:10.1002/anie.202501804
摘要
Specific subpopulations of extracellular vesicles (EVs) hold significant clinical potential for biomarker discovery, disease diagnosis, and therapeutic agents. However, this field remains underutilized due to the lack of straightforward and versatile techniques for isolating EV subpopulations from biofluids. Here, we present LODGE, a long DNA probe‐guided EV entanglement strategy for the simple, rapid, and selective enrichment of tumor‐derived EVs (tEVs) from clinical specimens. LODGE uses two long DNA affinity probes to recognize specific subpopulations, causing them to aggregate with the assistance of splint strands, thereby achieving non‐destructive, high‐yield, and high‐purity separation of tEVs within a short period. Proteomic analysis revealed that the isolated tEVs contributed to the identification of tumor‐associated biomarkers compared to total EVs. Additionally, by incorporating a split G‐quadruplex‐containing molecular trap domain, a novel structure that significantly improves the fluorescence emission of thioflavin T (ThT), into DNA affinity probes, we developed an innovative LODGE‐ThT sensing strategy for the highly sensitive profiling of multiple tEV subpopulations. Using data from the tEVs alongside clinical indicators processed with machine learning algorithms, we effectively classified five tumor types. Our results show that LODGE is a promising tool for identifying specific EV subpopulations, fostering their biomedical applications.
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