Glioblastoma multiforme (GBM) are mortifying brain tumours that contain a subpopulation of tumour cells with stem-like properties, termed glioblastoma stem-like cells (GSCs). GSCs largely contribute to tumour initiation, propagation and resistance to current anti-cancer therapies. GSCs are situated in perivascular niches, closely associated with brain microvascular endothelial cells, thereby involved in bidirectional molecular and cellular interactions. Moreover, extracellular vesicles are suspected to carry essential information that can adapt the microenvironment to the tumour’s needs, including tumour-induced angiogenesis. In GBM, extracellular vesicles produced by differentiated tumour cells and GSCs were demonstrated to disseminate locally and at distance. Here, we report that the pro-angiogenic pro-permeability factor VEGF-A is carried in extracellular vesicles secreted from ex vivo cultured patient-derived GSCs. Of note, extracellular vesicle-derived VEGF-A contributes to the in vitro elevation of permeability and angiogenic potential in human brain endothelial cells. Indeed, VEGF-A silencing in GSCs compromised in vitro extracellular vesicle-mediated increase in permeability and angiogenesis. From a clinical standpoint, extracellular vesicles isolated from circulating blood of GBM patients present higher levels of VEGF-A, as compared to healthy donors. Overall, our results suggest that extracellular vesicle-harboured VEGF-A targets brain endothelial cells and might impact their ability to form new vessels. Thus, tumour-released EV cargo might emerge as an instrumental part of the tumour-induced angiogenesis and vascular permeability modus operandi in GBM.

Glioblastoma are malignant highly vascularized brain tumours, which feature large oedema resulting from tumour-promoted vascular leakage. The pro-permeability factor Semaphorin3A (Sema3A) produced within glioblastoma has been linked to the loss of endothelial barrier integrity. Here, we report that extracellular vesicles (EVs) released by patient-derived glioblastoma cells disrupt the endothelial barrier. EVs expressed Sema3A at their surface, which accounted for in vitro elevation of brain endothelial permeability and in vivo vascular permeability, in both skin and brain vasculature. Blocking Sema3A or its receptor Neuropilin1 (NRP1) hampered EV-mediated permeability. In vivo models using ectopically and orthotopically xenografted mice revealed that Sema3A-containing EVs were efficiently detected in the blood stream. In keeping with this idea, sera from glioblastoma multiforme (GBM) patients also contain high levels of Sema3A carried in the EV fraction that enhanced vascular permeability, in a Sema3A/NRP1-dependent manner. Our results suggest that EV-delivered Sema3A orchestrates loss of barrier integrity in glioblastoma and may be of interest for prognostic purposes.

RIL can be defined by clinical symptoms (subcortical frontal decline, gait apraxia, urinary incontinence) and MRI criteria (cortico-subcortical atrophy, spread FLAIR HI, T2* asignals). This condition mimics a diffuse progressive cerebral small vessel disease triggered by RT, independent of RT protocol.

Background: Objective gait assessment is key for the follow-up of patients with progressive multiple sclerosis (pMS). Inertial measurement units (IMUs) provide reliable and yet easy quantitative gait assessment in routine clinical settings. However, to the best of our knowledge, no automated step-detection algorithm performs well in detecting severely altered pMS gait.Method: This article elaborates on a step-detection method based on personalized templates tested against a gold standard. Twenty-two individuals with pMS and 10 young healthy subjects (HSs) were instructed to walk on an electronic walkway wearing synchronized IMUs. Templates were derived from the IMU signals by using Initial and Final Contact times given by the walkway. These were used to detect steps from other gait trials of the same individual (intra-individual template-based detection, IITD) or another participant from the same group (pMS or HS) (intra-group template-based detection, IGTD). All participants were seen twice with a 6-month interval, with two measurements performed at each visit. Performance and accuracy metrics were computed, along with a similarity index (SId), which was computed as the mean distance between detected steps and their respective closest template.Results: For HS participants, both the IITD and the IGTD algorithms had precision and recall of 1.00 for detecting steps. For pMS participants, precision and recall ranged from 0.94 to 1.00 for IITD and 0.85 to 0.95 for IGTD depending on the level of disability. The SId was correlated with performance and the accuracy of the result. An SId threshold of 0.957 (IITD) and 0.963 (IGTD) could rule out decreased performance (F-measure ≤ 0.95), with negative predictive values of 0.99 and 0.96 with the IITD and IGTD algorithms. Also, the SId computed with the IITD and IGTD algorithms could distinguish individuals showing changes at 6-month follow-up.Conclusion: This personalized step-detection method has high performance for detecting steps in pMS individuals with severely altered gait. The algorithm can be Vienne-Jumeau et al. PersonalizedStep Detection in Multiple Sclerosis self-evaluating with the SI, which gives a measure of the confidence the clinician can have in the detection. What is more, the SId can be used as a biomarker of change in disease severity occurring between the two measurement times.

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