Posterior fossa ependymoma comprises two distinct molecular variants termed EPN_PFA and EPN_PFB that have a distinct biology and natural history. The therapeutic value of cytoreductive surgery and radiation therapy for posterior fossa ependymoma after accounting for molecular subgroup is not known.

GPIHBP1, a GPI-anchored protein of capillary endothelial cells, binds lipoprotein lipase (LPL) within the subendothelial spaces and shuttles it to the capillary lumen. GPIHBP1-bound LPL is essential for the margination of triglyceride-rich lipoproteins (TRLs) along capillaries, allowing the lipolytic processing of TRLs to proceed. In peripheral tissues, the intravascular processing of TRLs by the GPIHBP1-LPL complex is crucial for the generation of lipid nutrients for adjacent parenchymal cells. GPIHBP1 is absent from the capillaries of the brain, which uses glucose for fuel; however, GPIHBP1 is expressed in the capillaries of mouse and human gliomas. Importantly, the GPIHBP1 in glioma capillaries captures locally produced LPL. We use NanoSIMS imaging to show that TRLs marginate along glioma capillaries and that there is uptake of TRL-derived lipid nutrients by surrounding glioma cells. Thus, GPIHBP1 expression in gliomas facilitates TRL processing and provides a source of lipid nutrients for glioma cells.

The domestic dog segregates a significant number of inherited progressive retinal diseases, several of which mirror human retinal diseases and which are collectively termed progressive retinal atrophy (PRA). In 2014, a novel form of PRA was reported in the Swedish Vallhund breed, and the disease was mapped to canine chromosome 17. The causal mutation was not identified, but expression analyses of the retinas of affected Vallhunds demonstrated a 6-fold increased expression of the MERTK gene compared to unaffected dogs. Using 24 retinopathy cases and 97 controls with no clinical signs of retinopathy, we replicated the chromosome 17 association in Swedish Vallhunds from the UK and aimed to elucidate the causal variant underlying this association using whole genome sequencing (WGS) of an affected dog. This revealed a 6-8 kb insertion in intron 1 of MERTK that was not present in WGS of 49 dogs of other breeds. Sequencing and BLASTN analysis of the inserted segment was consistent with the insertion comprising a full-length intact LINE-1 retroelement. Testing of the LINE-1 insertion for association with retinopathy in the UK set of 24 cases and 97 controls revealed a strong statistical association (P-value 6.0 x 10-11) that was subsequently replicated in the original Finnish study set (49 cases and 89 controls (P-value 4.3 x 10-19). In a pooled analysis of both studies (73 cases and 186 controls), the LINE-1 insertion was associated with a ~20-fold increased risk of retinopathy (odds ratio 23.41, 95% confidence intervals 10.99-49.86, P-value 1.3 x 10-27). Our study adds further support for regulatory disruption of MERTK in Swedish Vallhund retinopathy; however, further work is required to establish a functional overexpression model. Future work to characterise the mechanism by which this intronic mutation disrupts gene regulation will further improve the understanding of MERTK biology and its role in retinal function.

The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens' motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study.

Differentiating WHO grade I-III of meningioma by non-invasive imaging is challenging. This study investigated the potential of MR arterial spin labeling (ASL) to establish tumor grade in meningioma patients.

Human cells have twenty-three pairs of chromosomes. In cancer, however, genes can be amplified in chromosomes or in circular extrachromosomal DNA (ecDNA), although the frequency and functional importance of ecDNA are not understood. We performed whole-genome sequencing, structural modelling and cytogenetic analyses of 17 different cancer types, including analysis of the structure and function of chromosomes during metaphase of 2,572 dividing cells, and developed a software package called ECdetect to conduct unbiased, integrated ecDNA detection and analysis. Here we show that ecDNA was found in nearly half of human cancers; its frequency varied by tumour type, but it was almost never found in normal cells. Driver oncogenes were amplified most commonly in ecDNA, thereby increasing transcript level. Mathematical modelling predicted that ecDNA amplification would increase oncogene copy number and intratumoural heterogeneity more effectively than chromosomal amplification. We validated these predictions by quantitative analyses of cancer samples. The results presented here suggest that ecDNA contributes to accelerated evolution in cancer.

As treatments for diffuse gliomas have advanced, survival for patients with gliomas has also increased. However, there remains limited knowledge on the relationships between brain connectivity and the lasting changes to cognitive function that glioma survivors often experience long after completing treatment. This resting-state functional magnetic resonance imaging (rs-fMRI) study explored functional connectivity (FC) alterations associated with cognitive function in survivors of gliomas. In this pilot study, 22 patients (mean age 43.8 ± 11.9) with diffuse gliomas who completed treatment within the past 10 years were evaluated using rs-fMRI and neuropsychological measures. Novel rs-fMRI analysis methods were used to account for missing brain in the resection cavity. FC relationships were assessed between cognitively impaired and non-impaired glioma patients, along with self-reported cognitive impairment, non-work daily functioning, and time with surgery. In the cognitively non-impaired patients, FC was stronger in the medial prefrontal cortex, rostral prefrontal cortex, and intraparietal sulcus compared to the impaired survivors. When examining non-work daily functioning, a positive correlation with FC was observed between the accumbens and the intracalcarine cortices, while a negative correlation with FC was observed between the parietal operculum cortex and the cerebellum. Additionally, worse self-reported cognitive impairment and worse non-work daily functioning were associated with increased FC between regions involved in cognition and sensorimotor processing. These preliminary findings suggest that neural correlates for cognitive and daily functioning in glioma patients can be revealed using rs-fMRI. Resting-state network alterations may serve as a biomarker for patients' cognition and functioning.

Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice.

This pilot study investigates structural alterations and their relationships with cognitive function in survivors of diffuse gliomas. Twenty-four survivors of diffuse gliomas (mean age 44.5 ± 11.5), from whom high-resolution T1-weighted images, neuropsychological tests, and self-report questionnaires were obtained, were analyzed. Patients were grouped by degree of cognitive impairment, and interregional correlations of cortical thickness were computed to generate morphometric correlation networks (MCNs). The results show that the cortical thickness of the right insula (R2 = 0.3025, p = 0.0054) was negatively associated with time since the last treatment, and the cortical thickness of the left superior temporal gyrus (R2 = 0.2839, p = 0.0107) was positively associated with cognitive performance. Multiple cortical regions in the default mode, salience, and language networks were identified as predominant nodes in the MCNs of survivors of diffuse gliomas. Compared to cognitively impaired patients, cognitively non-impaired patients tended to have higher network stability in network nodes removal analysis, especially when the fraction of removed nodes (among 66 nodes in total) exceeded 55%. These findings suggest that structural networks are altered in survivors of diffuse gliomas and that their cortical structures may also be adapting to support cognitive function during survivorship.

Glioblastoma (GBM) represents the most aggressive subtype of glioma, noted for its profound invasiveness and molecular heterogeneity. The mesenchymal (MES) transcriptomic subtype is frequently associated with therapy resistance, rapid recurrence, and increased tumor-associated macrophages. Notably, activation of the NF-κB pathway and alterations in the PTEN gene are both associated with this malignant transition. Although PTEN aberrations have been shown to be associated with enhanced NF-κB signaling, the relationships between PTEN, NF-κB and MES transition are poorly understood in GBM. Here, we show that PTEN regulates the chromatin binding of bromodomain and extraterminal (BET) family proteins, BRD2 and BRD4, mediated by p65/RelA localization to the chromatin. By utilizing patient-derived glioblastoma stem cells and CRISPR gene editing of the RELA gene, we demonstrate a crucial role for RelA lysine 310 acetylation in recruiting BET proteins to chromatin for MES gene expression and GBM cell invasion upon PTEN loss. Remarkably, we found that BRD2 is dependent on chromatin associated acetylated RelA for its recruitment to MES gene promoters and their expression. Furthermore, loss of BRD2 results in the loss of MES signature, accompanied by an enrichment of proneural signature and enhanced therapy responsiveness. Finally, we demonstrate that disrupting the NFκB/BRD2 interaction with a brain penetrant BET-BD2 inhibitor reduces mesenchymal gene expression, GBM invasion, and therapy resistance in GBM models. This study uncovers the role of hitherto unexplored PTEN-NF-κB-BRD2 pathway in promoting MES transition and suggests inhibiting this complex with BET-BD2 specific inhibitors as a therapeutic approach to target the MES phenotype in GBM.

Glioblastoma (GBM), the most common primary malignant brain tumor, is a highly lethal form of cancer with a very limited set of treatment options. High heterogeneity in the tumor cell population and the invasive nature of these cells decrease the likely efficacy of traditional cancer treatments, thus requiring research into novel treatment options. The use of oncolytic viruses as potential therapeutics has been researched for some time. Zika virus (ZIKV) has demonstrated oncotropism and oncolytic effects on GBM stem cells (GSCs). To address the need for safe and effective GBM treatments, we designed an attenuated ZIKV strain (ZOL-1) that does not cause paralytic or neurological diseases in mouse models compared with unmodified ZIKV. Importantly, we found that patient-derived GBM tumors exhibited susceptibility (responders) and non-susceptibility (non-responders) to ZOL-1-mediated tumor cell killing, as evidenced by differential apoptotic cell death and cell viability upon ZOL-1 treatment. The oncolytic effect observed in responder cells was seen both in vitro in neurosphere models and in vivo upon xenograft. Finally, we observed that the use of ZOL-1 as combination therapy with multiple PI3K-AKT inhibitors in non-responder GBM resulted in enhanced chemotherapeutic efficacy. Altogether, this study establishes ZOL-1 as a safe and effective treatment against GBM and provides a foundation to conduct further studies evaluating its potential as an effective adjuvant with other chemotherapies and kinase inhibitors.

Expert opinion is that about 20% of emergency stroke patients should receive thrombolysis. Currently, 11% to 12% of patients in England and Wales receive thrombolysis, ranging from 2% to 24% between hospitals. The aim of this study was to assess how much variation is due to differences in local patient populations, and how much is due to differences in clinical decision-making and stroke pathway performance, while estimating a realistic target thrombolysis use.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.

Current therapies for glioblastoma (GBM) target bulk tumor through measures such as resection and radiotherapy. However, recent evidence suggests that targeting a subset of tumor cells, so-called cancer stem cells, may be critical for inhibiting tumor growth and relapse. The subventricular zone (SVZ), which lines the ventricles of the brain, is thought to be the origin for the majority of neural stem cells and potentially cancer stem cells. Therefore, we assessed the relationship between tumor contact with the SVZ as determined by MRI, cancer stem cell gene expression and survival in 47 patients with GBM. Using DNA microarrays, we found that genes associated with cancer stem cells were not over-expressed in tumors contacting the SVZ. Contact with the SVZ trended with shorter survival (median 358 versus 644, P = 0.066). Over-expression of CD133 (prominin-1) and maternal embryonic leucine zipper kinase (MELK) was associated with shorter survival, whereas mitogen activated protein kinase 8 (MAPK8) was associated with longer survival (P values 0.008, 0.005 and 0.002 respectively). Thus we found no evidence of a stem-cell derived genetic signature specific for GBM in contact with the SVZ, but there was a relationship between stem cell gene expression and survival. More research is required to clarify the relationship between the SVZ, cancer stem cells and survival.

The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsupervised, two-level clustering approach followed by support vector machine in order to classify the isocitrate dehydrogenase (IDH) status of gliomas.

Evidence from single and multicenter phase II trials have suggested diffusion MRI is a predictive imaging biomarker for survival benefit in recurrent glioblastoma (rGBM) treated with anti-VEGF therapy. The current study confirms these findings in a large, randomized phase III clinical trial.

To identify clinically relevant magnetic resonance imaging (MRI) features of different types of metastatic brain lesions, including standard anatomical, diffusion weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion MRI.

Dynamic susceptibility contrast (DSC)-MRI is a well-established perfusion MR imaging technique for estimating relative cerebral blood volume (CBV) in primary brain tumors; however, tumors localized to regions with naturally elevated perfusion, including cortical tissue and common vascular territories, make evaluation of tumor vascularity difficult to assess. In the current study, we have constructed a large-scale radiographic atlas of CBV to assess treatment response to bevacizumab in individual patients with recurrent glioblastoma.

Promoter methylation of O6-methylguanine DNA methyltransferase (MGMT) is associated with a favorable prognosis in glioblastoma multiforme (GBM) and has been hypothesized to occur early in tumor transformation of glial cells. Thus, a possible link exists between the site of malignant transformation and MGMT promoter methylation status. Using the Analysis of Differential Involvement (ADIFFI) statistical mapping technique in a total of 358 patients with GBM, we demonstrate that human de novo GBMs occur in a high frequency contiguous with the posterior subventricular zone (SVZ); MGMT promoter methylated GBMs are lateralized to the left hemisphere, while MGMT unmethylated GBMs are lateralized to the right hemisphere; and tumors near the left temporal lobe have a significantly longer overall survival compared with tumors occurring elsewhere, independent of treatment or MGMT methylation status.