DNA methylation-based classification of glioneuronal tumours synergises with histology and radiology to refine accurate molecular stratification.

AIMS: Glioneuronal tumours (GNTs) are poorly distinguished by their histology and lack robust diagnostic indicators. Previously, we showed that common GNTs comprise two molecularly distinct groups, correlating poorly with histology. To refine diagnosis, we constructed a methylation-based model for GNT classification, subsequently evaluating standards for molecular stratification by methylation, histology and radiology. METHODS: We comprehensively analysed methylation, radiology and histology for 83 GNT samples: a training cohort of 49, previously classified into molecularly defined groups by genomic profiles, plus a validation cohort of 34. We identified histological and radiological correlates to molecular classification and constructed a methylation-based support vector machine (SVM) model for prediction. Subsequently, we contrasted methylation, radiological and histological classifications in validation GNTs. RESULTS: By methylation clustering, all training and 23/34 validation GNTs segregated into two groups, the remaining 11 clustering alongside control cortex. Histological review identified prominent astrocytic/oligodendrocyte-like components, dysplastic neurons and a specific glioneuronal element as discriminators between groups. However, these were present in only a subset of tumours. Radiological review identified location, margin definition, enhancement and T2 FLAIR-rim sign as discriminators. When validation GNTs were classified by SVM, 22/23 classified correctly, comparing favourably against histology and radiology that resolved 17/22 and 15/21, respectively, where data were available for comparison. CONCLUSIONS: Diagnostic criteria inadequately reflect glioneuronal tumour biology, leaving a proportion unresolvable. In the largest cohort of molecularly defined glioneuronal tumours, we develop molecular, histological and radiological approaches for biologically meaningful classification and demonstrate almost all cases are resolvable, emphasising the importance of an integrated diagnostic approach.

Evaluating metagenomics and targeted approaches for diagnosis and surveillance of viruses.

BACKGROUND: Metagenomics is a powerful approach for the detection of unknown and novel pathogens. Workflows based on Illumina short-read sequencing are becoming established in diagnostic laboratories. However, high sequencing depth requirements, long turnaround times, and limited sensitivity hinder broader adoption. We investigated whether we could overcome these limitations using protocols based on untargeted sequencing with Oxford Nanopore Technologies (ONT), which offers real-time data acquisition and analysis, or a targeted panel approach, which allows the selective sequencing of known pathogens and could improve sensitivity. METHODS: We evaluated detection of viruses with readily available untargeted metagenomic workflows using Illumina and ONT, and an Illumina-based enrichment approach using the Twist Bioscience Comprehensive Viral Research Panel (CVRP), which targets 3153 viruses. We tested samples consisting of a dilution series of a six-virus mock community in a human DNA/RNA background, designed to resemble clinical specimens with low microbial abundance and high host content. Protocols were designed to retain the host transcriptome, since this could help confirm the absence of infectious agents. We further compared the performance of commonly used taxonomic classifiers. RESULTS: Capture with the Twist CVRP increased sensitivity by at least 10-100-fold over untargeted sequencing, making it suitable for the detection of low viral loads (60 genome copies per ml (gc/ml)), but additional methods may be needed in a diagnostic setting to detect untargeted organisms. While untargeted ONT had good sensitivity at high viral loads (60,000 gc/ml), at lower viral loads (600-6000 gc/ml), longer and more costly sequencing runs would be required to achieve sensitivities comparable to the untargeted Illumina protocol. Untargeted ONT provided better specificity than untargeted Illumina sequencing. However, the application of robust thresholds standardized results between taxonomic classifiers. Host gene expression analysis is optimal with untargeted Illumina sequencing but possible with both the CVRP and ONT. CONCLUSIONS: Metagenomics has the potential to become standard-of-care in diagnostics and is a powerful tool for the discovery of emerging pathogens. Untargeted Illumina and ONT metagenomics and capture with the Twist CVRP have different advantages with respect to sensitivity, specificity, turnaround time and cost, and the optimal method will depend on the clinical context.

Inhibition of Myostatin Reduces Collagen Deposition in a Mouse Model of Oculopharyngeal Muscular Dystrophy (OPMD) With Established Disease.

BACKGROUND: Oculopharyngeal muscular dystrophy (OPMD) is a late-onset muscle disease presented by ptosis, dysphagia, and limb weakness. Affected muscles display increased fibrosis and atrophy, with characteristic inclusion bodies in the nucleus. Myostatin is a negative regulator of muscle mass, and inhibition of myostatin has been demonstrated to improve symptoms in models of muscular dystrophy. METHODS: We systemically administered a monoclonal antibody to block myostatin in the A17 mouse model of OPMD at 42 weeks of age. The mice were administered a weekly dose of 10 mg/kg RK35 intraperitonially for 10 weeks, following which serum and histological analyses were performed on muscle samples. RESULTS: The administration of the antibody resulted in a significant decrease in serum myostatin and collagen deposition in muscles. However, minimal effects on body mass, muscle mass and myofiber diameter, or the density of intranuclear inclusions (INIs) (a hallmark of disease progression of OPMD) were observed. CONCLUSION: This study demonstrates that inhibition of myostatin does not revert muscle atrophy in a mouse model with established OPMD disease, but is effective at reducing observed histological markers of fibrosis in the treated muscles.

Inhibition of myostatin improves muscle atrophy in oculopharyngeal muscular dystrophy (OPMD).

BACKGROUND: Oculopharyngeal muscular dystrophy (OPMD) is a late-onset muscle disease affecting one per 80 000 of the general population characterized by profound dysphagia and ptosis, and limb weakness at later stages. Affected muscles are characterized by increased fibrosis and atrophy. Myostatin is a negative regulator of muscle mass, and inhibition of myostatin has been demonstrated to ameliorate symptoms in dystrophic muscles. METHODS: In this study, we performed a systemic delivery of a monoclonal antibody to immunologically block myostatin in the A17 mouse model of OPMD. The mice were administered a weekly dose of 10 mg/kg RK35 intraperitonially for 10 weeks, following which histological analyses were performed on the samples. RESULTS: This treatment significantly (P < 0.01) improved body mass (11%) and muscle mass (for the tibialis anterior and extensor digitorum longus by 19% and 41%) in the A17 mice treated with RK35 when compared to saline controls. Similarly, a significantly (P < 0.01) increased muscle strength (18% increase in maximal tetanic force) and myofibre diameter (17% and 44% for the tibialis anterior and extensor digitorum longus), and reduced expression of markers of muscle fibrosis (40% reduction in area of expression), was also observed. No change in the density of intranuclear inclusions (a hallmark of disease progression of OPMD) was however observed. CONCLUSIONS: Our study supports the clinical translation of such antibody-mediated inhibition of myostatin as a treatment of OPMD. This strategy has implications to be used as adjuvant therapies with gene therapy based approaches, or to stabilize the muscle prior to myoblast transplantation.