Abstract
Cancer cells secrete membranous extracellular vesicles (EVs) which contain specific oncogenic molecular cargo (including oncoproteins, oncopeptides, and RNA) into their microenvironment and the circulation. As such, EVs including exosomes (small EVs) and microvesicles (large EVs) represent important circulating biomarkers for various diseases, including cancer and its progression. These circulating biomarkers offer a potentially minimally invasive and repeatable targets for analysis (liquid biopsy) that could aid in the diagnosis, risk stratification, and monitoring of cancer. Although their potential as cancer biomarkers has been promising, the identification and quantification of EVs in clinical samples remain challenging. Like EVs, other types of circulating biomarkers (including cell-free nucleic acids, cf-NAs; or circulating tumor cells, CTCs) may represent a complementary or alternative approach to cancer diagnosis. In the context of multiple myeloma (MM), a systemic cancer type that causes cancer cells to accumulate in the bone marrow, the specific role for EVs as biomarkers for diagnosis and monitoring remains undefined. Tumor heterogeneity along with the various subtypes of MM (such as non-secretory MM) that cannot be monitored using conventional testing (e.g. sequential serological testing and bone marrow biopsies) render liquid biopsy and circulating tumor-derived EVs a promising approach. In this protocol, we describe the isolation and purification of EVs from peripheral blood plasma (PBPL) collected from healthy donors and patients with MM for a biomarker discovery strategy. Our results demonstrate detection of circulating EVs from as little as 1 mL of MM patients' PBPL. High-resolution mass spectrometry (MS)-based proteomics promises to provide new avenues in identifying novel markers for detection, monitoring, and therapeutic intervention of disease. We describe biophysical characterization and quantitative proteomic profiling of disease-specific circulating EVs which may provide important implications for the development of cancer diagnostics in MM.