Multiple Sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS). There is currently no single definitive test for MS. Circulating exosomes represent promising candidate biomarkers for a host of human diseases. Exosomes contain RNA, DNA, and proteins, can cross the blood-brain barrier, and are secreted from almost all cell types including cells of the CNS. We hypothesized that serum exosomal miRNAs could present a useful blood-based assay for MS disease detection and monitoring. Exosome-associated microRNAs in serum samples from MS patients (n = 25) and matched healthy controls (n = 11) were profiled using small RNA next generation sequencing. We identified differentially expressed exosomal miRNAs in both relapsing-remitting MS (RRMS) (miR-15b-5p, miR-451a, miR-30b-5p, miR-342-3p) and progressive MS patient sera (miR-127-3p, miR-370-3p, miR-409-3p, miR-432-5p) in relation to controls. Critically, we identified a group of nine miRNAs (miR-15b-5p, miR-23a-3p, miR-223-3p, miR-374a-5p, miR-30b-5p, miR-433-3p, miR-485-3p, miR-342-3p, miR-432-5p) that distinguished relapsing-remitting from progressive disease. Eight out of nine miRNAs were validated in an independent group (n = 11) of progressive MS cases. This is the first demonstration that microRNAs associated with circulating exosomes are informative biomarkers not only for the diagnosis of MS, but in predicting disease subtype with a high degree of accuracy.

Extracellular vesicles (EVs) play key roles in glioblastoma (GBM) biology and represent novel sources of biomarkers that are detectable in the peripheral circulation. Despite this notionally non-invasive approach to assess GBM tumours in situ, a comprehensive GBM EV protein signature has not been described. Here, EVs secreted by six GBM cell lines were isolated and analysed by quantitative high-resolution mass spectrometry. Overall, 844 proteins were identified in the GBM EV proteome, of which 145 proteins were common to EVs secreted by all cell lines examined; included in the curated EV compendium (Vesiclepedia_559; http://microvesicles.org). Levels of 14 EV proteins significantly correlated with cell invasion (invadopodia production; r2 > 0.5, p < 0.05), including several proteins that interact with molecules responsible for regulating invadopodia formation. Invadopodia, actin-rich membrane protrusions with proteolytic activity, are associated with more aggressive disease and are sites of EV release. Gene levels corresponding to invasion-related EV proteins showed that five genes (annexin A1, actin-related protein 3, integrin-β1, insulin-like growth factor 2 receptor and programmed cell death 6-interacting protein) were significantly higher in GBM tumours compared to normal brain in silico, with common functions relating to actin polymerisation and endosomal sorting. We also show that Cavitron Ultrasonic Surgical Aspirator (CUSA) washings are a novel source of brain tumour-derived EVs, demonstrated by particle tracking analysis, TEM and proteome profiling. Quantitative proteomics corroborated the high levels of proposed invasion-related proteins in EVs enriched from a GBM compared to low-grade astrocytoma tumour. Large-scale clinical follow-up of putative biomarkers, particularly the proposed survival marker annexin A1, is warranted.Electronic supplementary materialThe online version of this article (doi:10.1007/s11060-016-2298-3) contains supplementary material, which is available to authorized users.

The role of astrocytes is becoming increasingly important to understanding how glioblastoma (GBM) tumor cells diffusely invade the brain. Yet, little is known of the contribution of extracellular vesicle (EV) signaling in GBM/astrocyte interactions. We modeled GBM-EV signaling to normal astrocytes in vitro to assess whether this mode of intercellular communication could support GBM progression. EVs were isolated and characterized from three patient-derived GBM stem cells (NES + /CD133 + ) and their differentiated ( diff ) progeny cells (NES − /CD133 − ). Uptake of GBM-EVs by normal primary astrocytes was confirmed by fluorescence microscopy, and changes in astrocyte podosome formation and gelatin degradation were measured. Quantitative mass spectrometry-based proteomics was performed on GBM-EV stimulated astrocytes. Interaction networks were generated from common, differentially abundant proteins using Ingenuity® (Qiagen Bioinformatics) and predicted upstream regulators were tested by qPCR assays. Podosome formation and Cy3-gelatin degradation were induced in astrocytes following 24-h exposure to GBM- stem and - diff EVs, with EVs released by GBM- stem cells eliciting a greater effect. More than 1700 proteins were quantified, and bioinformatics predicted activations of MYC, NFE2L2, FN1, and TGFβ1 and inhibition of TP53 in GBM-EV stimulated astrocytes that were then confirmed by qPCR. Further qPCR studies identified significantly decreased Δ133p53 and increased p53 β in astrocytes exposed to GBM-EVs that might indicate the acquisition of a pro-inflammatory, tumor-promoting senescence-associated secretory phenotype (SASP). Inhibition of TP53 and activation of MYC signaling pathways in normal astrocytes exposed to GBM-EVs may be a mechanism by which GBM manipulates astrocytes to acquire a phenotype that promotes tumor progression. Electronic supplementary material The online version of this article (10.1007/s12035-018-1385-1) contains supplementary material, which is available to authorized users.

Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell of origin, including microRNA. Exosomes released by glioblastoma cross the blood–brain barrier into the peripheral circulation and carry molecular cargo distinct to that of “free-circulating” miRNA. In this pilot study, serum exosomal microRNAs were isolated from glioblastoma (n = 12) patients and analyzed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls and to grade II–III (n = 10) glioma patients. Significant differentially expressed microRNAs were identified, and the predictive power of individual and subsets of microRNAs were tested using univariate and multivariate analyses. Additional sera from glioblastoma patients (n = 4) and independent sets of healthy (n = 9) and non-glioma (n = 10) controls were used to further test the specificity and predictive power of this unique exosomal microRNA signature. Twenty-six microRNAs were differentially expressed in serum exosomes from glioblastoma patients relative to healthy controls. Random forest modeling and data partitioning selected seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p, and miR-543) as the most stable for classifying glioblastoma. Strikingly, within this model, six iterations of these miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. The seven miRNA panel was able to correctly classify all specimens in validation cohorts (n = 23). Also identified were 23 dysregulated miRNAs in IDHMUT gliomas, a partially overlapping yet distinct signature of lower-grade glioma. Serum exosomal miRNA signatures can accurately diagnose glioblastoma preoperatively. miRNA signatures identified are distinct from previously reported “free-circulating” miRNA studies in GBM patients and appear to be superior.

243; References, 36; Figure legends, 533. 32 ABSTRACT 34 Exosomes are nano-sized extracellular vesicles released by many cells that contain 35 molecules characteristic of their cell-of-origin, including microRNA. Exosomes released 36 by glioblastoma cross the blood-brain-barrier into the peripheral circulation, and carry 37 molecular cargo distinct to that of 'free-circulating' miRNA. In this pilot study, serum 38 exosomal-microRNAs were isolated from glioblastoma (n=12) patients and analyzed 39 using unbiased deep sequencing. Results were compared to sera from age-and gender-40 matched healthy controls, and to grades II-III (n=10) glioma patients. Significant 41 differentially expressed microRNAs were identified, and the predictive power of 42 individual and subsets of microRNAs were tested using univariate and multivariate 43 analyses. Additional sera from glioblastoma patients (n=4) and independent sets of 44 healthy (n=9) and non-glioma (n=10) controls were used to further test the specificity and 45 predictive power of this unique exosomal-microRNA signature. Twenty-six microRNAs 46 were differentially expressed in serum exosomes from glioblastoma patients' relative to 47 59

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