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Encoded Fusion-Mediated MicroRNA Signature Profiling of Tumor-Derived Extracellular Vesicles for Pancreatic Cancer Diagnosis.

Jianzhou FengYun ShuYu AnQi NiuQian FanYanmei LeiYanli GongXiao-Ya HuPeng ZhangYingbin LiuChaoyong James YangLingling Wu
Published in: Analytical chemistry (2023)
MicroRNAs (miRNAs) in tumor-derived extracellular vesicles (tEVs) are important cancer biomarkers for cancer screening and early diagnosis. Multiplex detection of miRNAs in tEVs facilitates accurate diagnosis but remains a challenge. Herein, we propose an encoded fusion strategy to profile the miRNA signature in tEVs for pancreatic cancer diagnosis. A panel of encoded-targeted-fusion beads was fabricated for the selective recognition and fusion of tEVs, with the turn-on fluorescence signals of molecule beacons for miRNA quantification and barcode signals for miRNA identification using readily accessible flow cytometers. Using this strategy, six types of pancreatic-cancer-associated miRNAs can be profiled in tEVs from 2 μL plasma samples ( n = 36) in an isolation-free and lysis-free manner with only 2 h of processing, offering a high accuracy (98%) to discriminate pancreatic cancer, pancreatitis, and healthy donors. This encoded fusion strategy exhibits great potential for multiplex profiling of miRNA in tEVs, offering new avenues for cancer diagnosis and screening.
Keyphrases
  • papillary thyroid
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  • risk assessment
  • single molecule
  • cancer therapy
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  • label free