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Updated: Aug 17, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
In Situ MicroRNA Profiling of Single Tumor Extracellular Vesicles for Precise Prostate Cancer Diagnosis
Aipeng Chen1, Fangzhou Lan1, Yue Ding2
1School of Pharmacy, Fudan University, Shanghai 200000, China.
Abstract:
MicroRNAs (miRNAs) packaged within extracellular vesicles (EV) exhibit remarkable stability in circulation and reflect the genetic and epigenetic characteristics of their parent cells, making them promising biomarkers for cancer diagnosis. However, the intrinsic heterogeneity of EV populations and the low abundance of miRNAs in early stage cancer pose a challenge in the sensitive detection of miRNAs in tumor-cell-derived EV (TEV). Herein, we present a one-pot strategy named miR-nSTEV for specific recognition and in situ miRNA profiling of TEV at the single-particle level for precise prostate cancer (PCa) diagnosis. Utilizing dual-surface protein recognition (CD63 and EpCAM) and orthogonal DNA barcoding-based fusion between the identified TEV and DNA-tagged liposome encapsulating variant miRNA probes (Tag-Lipo probes), our approach enables selective isolation and precise miRNA analysis of individual TEVs by nanoflow cytometry (nFCM). By integrating dual-protein sorting, DNA-directed fusion, and nFCM detection into one platform, miR-nSTEV effectively eliminates interference from free nucleic acids and RNases, significantly enhancing the detection fidelity. As a proof of concept, we profiled six PCa-associated miRNAs (miR-153, miR-183, miR-18A, miR-181, miR-429, and miR-940) in both cell culture medium and clinical plasma samples. The miR-nSTEV assay demonstrated superior diagnostic performance, achieving 100% accuracy in distinguishing PCa patients from healthy donors (HD), outperforming conventional RT-qPCR while simplifying the workflow. Overall, miR-nSTEV offers a robust, sensitive, and noninvasive tool for real-time TEV miRNA analysis, paving the way for early detection and precision diagnostics in PCa patients.
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