Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy.

Pancreatic cancer has the highest mortality rate among all major cancers, which highlights the urgent needs of non-invasive early detection. Circulating extracellular vesicles (EVs) have gained significant attention for discovering tumor biomarkers. However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different methods have been found to derive different EV populations carrying different biomolecules, which significantly confound biomarker discovery for developing clinical diagnostics. Building a rigorous EV isolation and standardizing assessment platform associated with -omics is essential to overcome this challenge. We introduced a novel isolation approach using a pH-responsive peptide conjugated with NanoPom magnetic beads (ExCy) for homogeneous EV isolation. Additionally, we introduced the first statistical algorithm for EV quality assessment (ExoQuality Index, EQI), which enables multi-assay quantification to provide a consistent and accurate definition of EV purity and quality; ExoQuality's algorithm intakes multi-assay information to deconvolute complex EV heterogeneity. We performed the next generation sequencing on EV RNAs from pancreatic cancer patient plasma using four isolation methods; results highlighting ExCy's isolation and EQI assessment improved biomarker identification. We identified a novel EV biomarker for pancreatic tumor, ATP6V0b, validated with quantitative PCR (qPCR) by screening a pilot cohort of 22 plasma samples. 16 were from pancreatic cancer patients, 6 with matched tumor tissue, and 6 healthy plasma samples. Through modelling the ATP6V0B cycling threshold, we reported 3 models with AUCs between 0.86 and 0.88, showcasing an enabling and clinically translatable liquid biopsy approach for early detection of pancreatic cancer using circulating EVs.