Single-EV analysis (sEVA) of mutated proteins allows detection of stage 1 pancreatic cancer

Tumor cell derived extracellular vesicles (EV) are being explored as circulating biomarkers for cancer detection. Up to now however, clinical results have been mixed for a number of reasons including the predominant use of bulk measurements, the inability to differentiate tumor from host cell derived vesicles, the general absence of uniquely identifying biomarkers and the unknown frequency of stochastically distributed biomarkers into single circulating vesicles. We hypothesized that a single EV analysis (sEVA) technique could potentially improve diagnostic accuracy necessary to detect early cancers but the actual biomarker frequency and practical detection limits are currently unknown. Using pancreatic cancer, we carefully analyzed the composition of putative cancer markers in 11 established and new patient derived models. In parental PDAC cells positive for KRASmutand/or P53mutproteins only ∼40% of EVs were also positive (range: 30-64%). This rate of positivity increased to 57% when additional PDAC biomarkers were considered (MUC1, EGFR, ⍺FG-P4OH) in cell lines. In a blinded study involving 16 patients with surgically proven stage 1 PDAC, KRASmutand P53mutprotein was detectable at much lower levels, generally in < 0.1% of vesicles. With the analytical capabilities of sEVA however, 15 of the 16 patients with stage 1 PDAC expressed low levels of biomarker positive EV. Using a modeling approach, we estimate that the current PDAC detection limit is at ∼0.1 cm3tumor volume, below clinical imaging capabilities. These findings establish the potential for single-EV analysis for early cancer detection.