Tandem SERS and MS/MS Profiling of Plasma Extracellular Vesicles for Early Ovarian Cancer Biomarker Discovery.

Extracellular vesicles (EVs) are vectors of biomolecular cargo that play essential roles in intercellular communication across a range of cells. Protein, lipid, and nucleic acid cargo harbored within EVs may serve as biomarkers at all stages of disease; however, the choice of methodology may challenge the specificity and reproducibility of discovery. To address these challenges, the integration of rigorous EV purification methods, cutting-edge spectroscopic technologies, and data analysis are critical to uncover diagnostic signatures of disease. Herein, we demonstrate an EV isolation and analysis pipeline using surface-enhanced Raman spectroscopy (SERS) and mass spectrometry (MS) techniques on plasma samples obtained from umbilical cord blood, healthy donor (HD) plasma, and plasma from women with early stage high-grade serous carcinoma (HGSC). Plasma EVs were purified by size exclusion chromatography and analyzed by surface-enhanced Raman spectroscopy (SERS), mass spectrometry (MS), and atomic force microscopy. After determining the fraction of highest EV purity, SERS and MS were used to characterize EVs from HDs, pooled donors with noncancerous gynecological ailments (n = 6), and donors with early stage [FIGO (I/II)] with HGSC. SERS spectra were subjected to different machine learning algorithms such as PCA, logistic regression, support vector machine, naïve Bayes, random forest, neural network, and k nearest neighbors to differentiate healthy, benign, and HGSC EVs. Collectively, we demonstrate a reproducible workflow with the potential to serve as a diagnostic platform for HGSC.

Extracellular vesicles tell all: How vesicle-mediated cellular communication shapes hematopoietic stem cell biology with increasing age.

Extracellular vesicles (EVs) are small lipid bilayer particles containing biologically important cargo and impart regulatory changes in target cells. Despite the importance of EVs in cellular communication, there remains a gap in our understanding of how EVs influence HSC fate and, in turn, how aging and longevity are affected. This review summarizes the current literature dealing with how age-altered intercellular communication mediated by EVs influences HSC biology.

Blood extracellular vesicles from healthy individuals regulate hematopoietic stem cells as humans age.

Hematopoietic stem cells (HSCs) maintain balanced blood cell production in a process called hematopoiesis. As humans age, their HSCs acquire mutations that allow some HSCs to disproportionately contribute to normal blood production. This process, known as age-related clonal hematopoiesis, predisposes certain individuals to cancer, cardiovascular and pulmonary pathologies. There is a growing body of evidence suggesting that factors outside cells, such as extracellular vesicles (EVs), contribute to the disruption of stem cell homeostasis during aging. We have characterized blood EVs from humans and determined that they are remarkably consistent with respect to size, concentration, and total protein content, across healthy subjects aged 20-85 years. When analyzing EV protein composition from mass spectroscopy data, our machine-learning-based algorithms are able to distinguish EV proteins based on age and suggest that different cell types dominantly produce EVs released into the blood, which change over time. Importantly, our data show blood EVs from middle and older age groups (>40 years) significantly stimulate HSCs in contrast to untreated and EVs sourced from young subjects. Our study establishes for the first time that although EV particle size, concentration, and total protein content remain relatively consistent over an adult lifespan in humans, EV content evolves during aging and potentially influences HSC regulation.