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Updated: Jan 10, 2026

Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
Published on: May 27, 2016
Sensitive and Specific Analysis of miRNAs in Single Tumor-Derived Extracellular Vesicles Using CRISPR-Based Nanoflow
Fangzhou Lan1, Aipeng Chen1, Yue Ding2
1School of Pharmacy, State Key Laboratory of Advanced Drug Formulations for Overcoming Delivery Barriers, Fudan University, Shanghai 201203, China.
Abstract:
Tumor-derived extracellular vesicle (TEV) microRNAs (miRNAs) are promising cancer biomarkers but pose detection challenges due to their low abundance and sequence homology. Here, we present a CRISPR/Cas13a-based nanoflow cytometry (nFCM) platform integrated with a DNA-guided orthogonal membrane fusion strategy for ultrasensitive miRNA detection of TEVs at the single particle level. TEVs were identified with aptamers against CD63 and EpCAM markers to create an orthogonal barcode-anchored TEV (Orth-TEV). Meanwhile, liposomes preloaded with CRISPR/Cas13a molecular sensing components were modified with cholesterol-tagged DNA probes to produce Tags-CRISPR/Cas13a@Lipo. The complementary DNA sequences on the Orth-TEV and Tags-CRISPR/Cas13a@Lipo vesicles facilitated zipper-like hybridization, thereby achieving specific membrane fusion to effectively eliminate the interference of nontarget vesicles or free molecules. The resulting TEV-CRISPR/Cas13a@Lipo vesicles allow in situ detection of three prostate cancer (PCa)-associated miRNAs in a single TEV via nFCM with a low detection limit (LOD) of 14.7 (miR-153), 16.0 (miR-183), and 23.7 (miR-940) particles/mL, respectively. The approach was further applied to plasma samples from PCa patients and healthy donors, showing significantly elevated miRNA signals in PCa-derived TEV. ROC analysis yielded AUC values of 0.931, 0.923, and 0.869 for the three target miRNAs, confirming excellent diagnostic performance. To enhance classification accuracy, we conducted a statistical multivariate analysis based on the PCA-LDA model, which achieved perfect group separation and a diagnostic accuracy of 91.3%. Overall, this CRISPR/Cas13a-based nFCM platform offers a robust, accurate, and clinically applicable platform for single-vesicle miRNA profiling with broad potential in liquid biopsy-based cancer diagnosis.

