Detection of plasma EV-associated TRAIL by nanoscale flow cytometry for liver metastasis prediction in PDAC

Extracellular vesicles (EVs) mediate tumor-host communication and represent a promising liquid biopsy source for metastasis risk assessment, yet quantitative detection of low-abundance, epitope-defined EV subpopulations in plasma remains technically challenging. Here, we establish a nanoscale flow cytometry workflow on the CytoFLEX platform for sensitive single-EV phenotyping by optimizing violet side scatter (VSSC) triggering, defining an acquisition window that minimizes coincidence or "swarm" effects, and applying fluorescence-based analysis with stringent background controls. Using this framework, we quantified EV-associated tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) at the single particle level, with good inter-assay reproducibility (CV ~ 11-13%), and resolved low-abundance TRAIL⁺ EVs at approximately 1% abundance within total EV events. Due to the low abundance of EV-associated TRAIL in pancreatic ductal adenocarcinoma (PDAC) plasma, ELISA lacked sufficient analytical sensitivity to accurately reflect EV-associated TRAIL levels, whereas flow-based enumeration preserved quantitative resolution. Clinically, plasma EV-associated TRAIL was significantly elevated in PDAC patients with liver metastasis and demonstrated predictive utility for postoperative liver metastatic recurrence (AUC = 0.766). These results support nanoscale flow cytometry as a robust platform for plasma EV biomarker profiling and identify EV-associated TRAIL as an informative indicator of liver metastatic risk in PDAC.