Abstract

The pEVs have strong potential to be used as clinical biomarkers in various pathological conditions by providing unique, additional proteomics information that could not be obtained from plasma alone. Our study provides an advanced proteomics workflow for in-depth proteome profiling and detection of disease-specific proteins present in plasma and pEVs. Size-exclusion chromatography-based columns were used for EV isolation from plasma. The particle size, concentration, and distribution of pEVs were characterized using the Coomassie brilliant blue protein gel staining, nanoparticle tracking analysis, and flow cytometry bead-based assay. For workflow optimization pEVs (healthy donor plasma) proteome was generated using long-gradient (LG) and HiRIEF methods. The workflow performance was validated using a cohort of 6 metastatic melanoma (MM) and 6 lung adenocarcinoma (LUAD) patients. HiRIEF pre-fractionation and tandem mass tags (TMT)-16plex based peptide quantification, was used to generate cancer pEVs and corresponding albumin-depleted plasma proteomes. We achieved high proteome coverage in pEVs, and detected traditional EV-marker proteins (CD81, CD9, HSPA8, FLOT1/2, LGALS3BP, HSP90AA1/AB1), ESCRTs, and several other EV-specific proteins associated to cargo selection, trafficking/sorting, and exosome biogenesis. Some well-known clinical biomarkers for LUAD and MM, as well as many other cancer-related proteins, were present in the cancer cohort plasma and pEVs. The differentially expressed proteins (DEPs) in pEVs and plasma show no overlap, supporting the unique protein information carried by pEVs in plasma. Some of the DEPs identified in pEVs and plasma are frequently reported as prognostic biomarkers for LUAD and MM. We present an optimized workflow for extensive proteome profiling of plasma and pEVs in parallel using the advanced HiRIEF LC-MS method. The workflow exhibits high proteome coverage and the ability to detect potential disease-specific markers in pEVs enriched from clinical plasma samples.