Ultrasensitive detection of cancer biomarkers by nickel-based isolation of polydisperse extracellular vesicles from blood

Background: Extracellular vesicles (EVs) are secreted membranous particles intensively studied for their potential cargo of diagnostic markers. Efficient and cost-effective isolation methods need to be established for the reproducible and high-throughput study of EVs in the clinical practice.

Methods: We designed the nickel-based isolation (NBI) to rapidly isolate EVs and combined it with newly-designed amplified luminescent proximity homogeneous assay or digital PCR to detect biomarkers of clinical utility.

Findings: From plasma of 46 healthy donors, we systematically recovered small EV (~250 nm of mean diameter; ~3 × 10¹⁰/ml) and large EV (~560 nm of mean diameter; ~5 × 10⁸/ml) lineages ranging from 50 to 700 nm, which displayed hematopoietic/endothelial cell markers that were also used in spike-in experiments using EVs from tumor cell lines. In retrospective studies, we detected picomolar concentrations of prostate-specific membrane antigen (PSMA) in fractions of EVs isolated from the plasma of prostate cancer patients, discriminating them from control subjects. Directly from oil-encapsulated EVs for digital PCR, we identified somatic BRAF and KRAS mutations circulating in the plasma of metastatic colorectal cancer (CRC) patients, matching 100% of concordance with tissue diagnostics. Importantly, with higher sensitivity and specificity compared with immuno-isolated EVs, we revealed additional somatic alterations in 7% of wild-type CRC cases that were subsequently validated by further inspections in the matched tissue biopsies.

Interpretation: We propose NBI-combined approaches as simple, fast, and robust strategies to probe the tumor heterogeneity and contribute to the development of EV-based liquid biopsy studies. FUND: Associazione Italiana per la Ricerca sul Cancro (AIRC), Fondazione Cassa di Risparmio Trento e Rovereto (CARITRO), and the Italian Ministero Istruzione, Università e Ricerca (Miur).