Molecular Analysis of Single Tumor-Derived Extracellular Vesicles with Improved Robustness and Accuracy.

Extracellular vesicles (EVs) have emerged as key analytes in liquid biopsy analysis, as they inherit the molecular characteristics of their parental cells. For cancer diagnosis and treatment monitoring, tumor-derived EVs can serve as surrogate markers of their originating tumor cells. However, technical challenges arise from EV heterogeneity, as molecular signals from a rare EV subpopulation are often neglected in bulk-EV analysis. This limitation underscores the importance of single-EV analysis, enabling the detection and analysis of individual tumor EVs. While multiple single-EV technologies have been introduced, accurately detecting and quantifying rare target EVs in clinical samples remains challenging in practice. Here, we developed a set of protocols that improve the selectivity and accuracy of single-EV analysis by minimizing false-positive signals and enhancing assay robustness. Specifically, we improved the validity of data processing for single-EV imaging, optimized EV labeling procedures, and applied colocalization analysis between cancer-specific markers and EV signals. We demonstrated that the approach is applicable to two orthogonal single-EV technologies, fluorescence imaging and nanoflow cytometry, yielding consistent results across the two methods and significantly improving the detection accuracy of tumor-derived EVs spiked in plasma samples. Collectively, we demonstrated precise single-EV profiling with high accuracy and selectivity, with evident benefits for the applicability of EV analysis in clinical studies.