The blood-brain barrier is dysregulated in COVID-19 and serves as a CNS entry route for SARS-CoV-2.

Neurological complications are common in COVID-19. Although SARS-CoV-2 has been detected in patients' brain tissues, its entry routes and resulting consequences are not well understood. Here, we show a pronounced upregulation of interferon signaling pathways of the neurovascular unit in fatal COVID-19. By investigating the susceptibility of human induced pluripotent stem cell (hiPSC)-derived brain capillary endothelial-like cells (BCECs) to SARS-CoV-2 infection, we found that BCECs were infected and recapitulated transcriptional changes detected in vivo. While BCECs were not compromised in their paracellular tightness, we found SARS-CoV-2 in the basolateral compartment in transwell assays after apical infection, suggesting active replication and transcellular transport of virus across the blood-brain barrier (BBB) in vitro. Moreover, entry of SARS-CoV-2 into BCECs could be reduced by anti-spike-, anti-angiotensin-converting enzyme 2 (ACE2)-, and anti-neuropilin-1 (NRP1)-specific antibodies or the transmembrane protease serine subtype 2 (TMPRSS2) inhibitor nafamostat. Together, our data provide strong support for SARS-CoV-2 brain entry across the BBB resulting in increased interferon signaling

Minimal information for studies of extracellular vesicles 2018 (MISEV2018):a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points

MicroRNA-Mediated Dynamic Bidirectional Shift between the Subclasses of Glioblastoma Stem-like Cells

Large-scale transcriptomic profiling of glioblastoma (GBM) into subtypes has provided remarkable insight into the pathobiology and heterogeneous nature of this disease. The mechanisms of speciation and inter-subtype transitions of these molecular subtypes require better characterization to facilitate the development of subtype-specific targeting strategies. The deregulation of microRNA expression among GBM subtypes and their subtype-specific targeting mechanisms are poorly understood. To reveal the underlying basis of microRNA-driven complex subpopulation dynamics within the heterogeneous intra-tumoral ecosystem, we characterized the expression of the subtype-enriched microRNA-128 (miR-128) in transcriptionally and phenotypically diverse subpopulations of patient-derived glioblastoma stem-like cells. Because microRNAs are capable of re-arranging the molecular landscape in a cell-type-specific manner, we argue that alterations in miR-128 levels are a potent mechanism of bidirectional transitions between GBM subpopulations, resulting in intermediate hybrid stages and emphasizing highly intricate intra-tumoral networking

Oncolytic Virus Therapy Alters the Secretome of Targeted Glioblastoma Cells

Oncolytic virus (OV) therapy, which is being tested in clinical trials for glioblastoma, targets cancer cells, while triggering immune cells. Yet OV sensitivity varies from patient to patient. As OV therapy is regarded as an anti-tumor vaccine, by making OV-infected cancer cells secrete immunogenic proteins, linking these proteins to transcriptome would provide a measuring tool to predict their sensitivity. A set of six patient-derived glioblastoma cells treated ex-vivo with herpes simplex virus type 1 (HSV1) modeled a clinical setting of OV infection. The cellular transcriptome and secreted proteome (separated into extracellular vesicles (EV) and EV-depleted fractions) were analyzed by gene microarray and mass-spectroscopy, respectively. Data validation and in silico analysis measured and correlated the secretome content with the response to infection and patient survival. Glioblastoma cells reacted to the OV infection in a seemingly dissimilar fashion, but their transcriptomes changed in the same direction. Therefore, the upregulation of transcripts encoding for secreted proteins implies a common thread in the response of cancer cells to infection. Indeed, the OV-driven secretome is linked to the immune response. While these proteins have distinct membership in either EV or EV-depleted fractions, it is their co-secretion that augments the immune response and associates with favorable patient outcomes

The Long Non-coding RNA HIF1A-AS2 Facilitates the Maintenance of Mesenchymal Glioblastoma Stem-like Cells in Hypoxic Niches

Long non-coding RNAs (lncRNAs) have an undefined role in the pathobiology of glioblastoma multiforme (GBM). These tumors are genetically and phenotypically heterogeneous with transcriptome subtype-specific GBM stem-like cells (GSCs) that adapt to the brain tumor microenvironment, including hypoxic niches. We identified hypoxia-inducible factor 1 alpha-antisense RNA 2 (HIF1A-AS2) as a subtype-specific hypoxia-inducible lncRNA, upregulated in mesenchymal GSCs. Its deregulation affects GSC growth, self-renewal, and hypoxia-dependent molecular reprogramming. Among the HIF1A-AS2 interactome, IGF2BP2 and DHX9 were identified as direct partners. This association was needed for maintenance of expression of their target gene, HMGA1. Downregulation of HIF1A-AS2 led to delayed growth of mesenchymal GSC tumors, survival benefits, and impaired expression of HMGA1 in vivo. Our data demonstrate that HIF1A-AS2 contributes to GSCs’ speciation and adaptation to hypoxia within the tumor microenvironment, acting directly through its interactome and targets and indirectly by modulating responses to hypoxic stress depending on the subtype-specific genetic context

Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage

Prognosis of patients with high-grade aneurysmal subarachnoid hemorrhage (aSAH) is only insufficiently displayed by current standard prognostic scores. This study aims to evaluate the role of pupil status for mortality prediction and provide improved prognostic models. Anonymized data of 477 aSAH patients admitted to our medical center from November 2010 to August 2018 were retrospectively analyzed. Identification of variables independently predicting in-hospital mortality was performed by multivariable logistic regression analysis. Final regression models included Hunt & Hess scale (H&H), pupil status and age or in a simplified variation only H&H and pupil status, leading to the design of novel H&H-Pupil-Age score (HHPA) and simplified H&H-Pupil score (sHHP), respectively. In an external validation cohort of 402 patients, areas under the receiver operating characteristic curves (AUROC) of HHPA (0.841) and sHHP (0.821) were significantly higher than areas of H&H (0.794; p<0.001) or World Federation of Neurosurgical Societies (WFNS) scale (0.775; p<0.01). Accordingly, including information about pupil status improves the predictive performance of prognostic scores for in-hospital mortality in patients with aSAH. HHPA and sHHP allow simple, early and detailed prognosis assessment while predictive performance remained strong in an external validation cohort suggesting adequate generalizability and low interrater variability

Machine learning based outcome prediction of microsurgically treated unruptured intracranial aneurysms

Abstract Machine learning (ML) has revolutionized data processing in recent years. This study presents the results of the first prediction models based on a long-term monocentric data registry of patients with microsurgically treated unruptured intracranial aneurysms (UIAs) using a temporal train-test split. Temporal train-test splits allow to simulate prospective validation, and therefore provide more accurate estimations of a model’s predictive quality when applied to future patients. ML models for the prediction of the Glasgow outcome scale, modified Rankin Scale (mRS), and new transient or permanent neurological deficits (output variables) were created from all UIA patients that underwent microsurgery at the Kepler University Hospital Linz (Austria) between 2002 and 2020 (n = 466), based on 18 patient- and 10 aneurysm-specific preoperative parameters (input variables). Train-test splitting was performed with a temporal split for outcome prediction in microsurgical therapy of UIA. Moreover, an external validation was conducted on an independent external data set (n = 256) of the Department of Neurosurgery, University Medical Centre Hamburg-Eppendorf. In total, 722 aneurysms were included in this study. A postoperative mRS > 2 was best predicted by a quadratic discriminant analysis (QDA) estimator in the internal test set, with an area under the receiver operating characteristic curve (ROC-AUC) of 0.87 ± 0.03 and a sensitivity and specificity of 0.83 ± 0.08 and 0.71 ± 0.07, respectively. A Multilayer Perceptron predicted the post- to preoperative mRS difference > 1 with a ROC-AUC of 0.70 ± 0.02 and a sensitivity and specificity of 0.74 ± 0.07 and 0.50 ± 0.04, respectively. The QDA was the best model for predicting a permanent new neurological deficit with a ROC-AUC of 0.71 ± 0.04 and a sensitivity and specificity of 0.65 ± 0.24 and 0.60 ± 0.12, respectively. Furthermore, these models performed significantly better than the classic logistic regression models (p  2, a pre- and postoperative difference in mRS > 1 point and a GOS < 5. Therefore, generalizability of the models could not be demonstrated in the external validation. A SHapley Additive exPlanations (SHAP) analysis revealed that this is due to the most important features being distributed quite differently in the internal and external data sets. The implementation of newly available data and the merging of larger databases to form more broad-based predictive models is imperative in the future

Genome-wide DNA methylation profiles distinguish silent from non-silent ACTH adenomas

Early active multiple sclerosis (MS) lesions can be classified histologically into three main immunopathological patterns of demyelination (patterns I-III), which suggest pathogenic heterogeneity and may predict therapy response. Patterns I and II show signs of immune-mediated demyelination, but only pattern II is associated with antibody/complement deposition. In pattern III lesions, which include Baló's concentric sclerosis, primary oligodendrocyte damage was proposed. Serum antibody reactivities could reflect disease pathogenesis and thus distinguish histopathologically defined MS patterns. We established a customized microarray with more than 700 peptides that represent human and viral antigens potentially relevant for inflammatory demyelinating CNS diseases, and tested sera from 66 patients (pattern I n = 12; II n = 29; III n = 25, including 8 with Baló's), healthy controls, patients with Sjögren's syndrome and stroke patients. Cell-based assays were performed for aquaporin 1 (AQP1) and AQP4 antibody detection. No single peptide showed differential binding among study cohorts. Because antibodies can react with different peptides from one protein, we also analyzed groups of peptides. Patients with pattern II showed significantly higher reactivities to Nogo-A peptides as compared to patterns I (p = 0.02) and III (p = 0.02). Pattern III patients showed higher reactivities to AQP1 (compared to pattern I p = 0.002, pattern II p = 0.001) and varicella zoster virus (VZV, compared to pattern II p = 0.05). In patients with Baló's, AQP1 reactivity was also significantly higher compared to patients without Baló's (p = 0.04), and the former revealed distinct antibody signatures. Histologically, Baló's patients showed loss of AQP1 and AQP4 in demyelinating lesions, but no antibodies binding conformational AQP1 or AQP4 were detected. In summary, higher reactivities to Nogo-A peptides in pattern II patients could be relevant for enhanced axonal repair and remyelination. Higher reactivities to AQP1 peptides in pattern III patients and its subgroup of Baló's patients possibly reflect astrocytic damage. Finally, latent VZV infection may cause peripheral immune activation

MicroRNA Signatures and Molecular Subtypes of Glioblastoma: The Role of Extracellular Transfer

Summary Despite the importance of molecular subtype classification of glioblastoma (GBM), the extent of extracellular vesicle (EV)-driven molecular and phenotypic reprogramming remains poorly understood. To reveal complex subpopulation dynamics within the heterogeneous intratumoral ecosystem, we characterized microRNA expression and secretion in phenotypically diverse subpopulations of patient-derived GBM stem-like cells (GSCs). As EVs and microRNAs convey information that rearranges the molecular landscape in a cell type-specific manner, we argue that intratumoral exchange of microRNA augments the heterogeneity of GSC that is reflected in highly heterogeneous profile of microRNA expression in GBM subtypes