Integrated Techniques for Extracellular Particle Separation and Single-Particle Multiparametric Characterization to Track Cancer Biomarkers from Tissue to Biofluids

Abstract

Gastric cancer (GC) remains a formidable global health challenge, with late-stage diagnosis and high recurrence rates resulting in poor patient outcomes. This study explores the potential of advanced technologies, namely Bessel Beam Excitation Separation Technology (BEST) and multiparametric biochip assay (MBA), to track single extracellular vesicle and particle (EVP) cargo from organs of pathology into biofluids such as plasma and saliva. Using GC as a study model, we conducted high throughput, multiparametric analyses of EVPs derived from plasma, saliva, and tissue samples. Our findings demonstrate the feasibility of these techniques in isolating and characterizing EVPs, revealing consistent EVP morphology and size across biofluids. Furthermore, differential expression patterns of the developed and validated salivary GC biomarkers, miR-140-5p and miR-301a-3p, were observed in GC patient biofluids, supporting the diagnostic relevance of EVP cargo. Notably, saliva emerged as the most promising biofluid for GC diagnosis, achieving superior Receiver Operating Characteristic (ROC) curve values compared to plasma and tissue. This study highlights the role of BEST and MBA in advancing single-EVP analysis and elucidating EVP trafficking, paving the way for future diagnostic applications of EVP cargo.