Prognostic microRNAs in high-grade glioma reveal a link to oligodendrocyte precursor differentiation.

MicroRNA expression can be exploited to define tumor prognosis and stratification for precision medicine. It remains unclear whether prognostic microRNA signatures are exclusively tumor grade and/or molecular subtype-specific, or whether common signatures of aggressive clinical behavior can be identified. Here, we defined microRNAs that are associated with good and poor prognosis in grade III and IV gliomas using data from The Cancer Genome Atlas. Pathway analysis of microRNA targets that are differentially expressed in good and poor prognosis glioma identified a link to oligodendrocyte development. Notably, a microRNA expression profile that is characteristic of a specific oligodendrocyte precursor cell type (OP1) correlates with microRNA expression from 597 of these tumors and is consistently associated with poor patient outcome in grade III and IV gliomas. Our study reveals grade-independent and subtype-independent prognostic molecular signatures in high-grade glioma and provides a framework for investigating the mechanisms of brain tumor aggressiveness

Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data

Intratumour heterogeneity provides tumours with the ability to adapt and acquire treatment resistance. The development of more effective and personalised treatments for cancers, therefore, requires accurate characterisation of the clonal architecture of tumours, enabling evolutionary dynamics to be tracked. Many methods exist for achieving this from bulk tumour sequencing data, involving identifying mutations and performing subclonal deconvolution, but there is a lack of systematic benchmarking to inform researchers on which are most accurate, and how dataset characteristics impact performance. To address this, we use the most comprehensive tumour genome simulation tool available for such purposes to create 80 bulk tumour whole exome sequencing datasets of differing depths, tumour complexities, and purities, and use these to benchmark subclonal deconvolution pipelines. We conclude that i) tumour complexity does not impact accuracy, ii) increasing either purity or purity-corrected sequencing depth improves accuracy, and iii) the optimal pipeline consists of Mutect2, FACETS and PyClone-VI. We have made our benchmarking datasets publicly available for future use

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing

Summary: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data

A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms

Expression profiling of single cells and patient cohorts identifies multiple immunosuppressive pathways and an altered NK cell phenotype in glioblastoma.

Glioblastoma (GBM) is an aggressive cancer with a very poor prognosis. Generally viewed as weakly immunogenic, GBM responds poorly to current immunotherapies. To understand this problem more clearly we used a combination of natural killer (NK) cell functional assays together with gene and protein expression profiling to define the NK cell response to GBM and explore immunosuppression in the GBM microenvironment. In addition, we used transcriptome data from patient cohorts to classify GBM according to immunological profiles. We show that glioma stem-like cells, a source of post-treatment tumour recurrence, express multiple immunomodulatory cell surface molecules and are targeted in preference to normal neural progenitor cells by natural killer (NK) cells ex vivo. In contrast, GBM-infiltrating NK cells express reduced levels of activation receptors within the tumour microenvironment, with hallmarks of transforming growth factor (TGF)-β-mediated inhibition. This NK cell inhibition is accompanied by expression of multiple immune checkpoint molecules on T cells. Single-cell transcriptomics demonstrated that both tumour and haematopoietic-derived cells in GBM express multiple, diverse mediators of immune evasion. Despite this, immunome analysis across a patient cohort identifies a spectrum of immunological activity in GBM, with active immunity marked by co-expression of immune effector molecules and feedback inhibitory mechanisms. Our data show that GBM is recognized by the immune system but that anti-tumour immunity is restrained by multiple immunosuppressive pathways, some of which operate in the healthy brain. The presence of immune activity in a subset of patients suggests that these patients will more probably benefit from combination immunotherapies directed against multiple immunosuppressive pathways

Hematopoietic stem cell gene therapy for brain metastases using myeloid cell-specific gene promoters

Background: Brain metastases (BrM) develop in 20-40% of cancer patients and represent an unmet clinical need. Limited access of drugs into the brain due to the blood-brain barrier is at least partially responsible for therapeutic failure, necessitating improved drug delivery systems. Methods: Green fluorescent protein (GFP)-transduced murine and non-transduced human hematopoietic stem cells (HSCs) were administered into mice (n = 10 and 3). The HSC progeny in mouse BrM and in patient-derived BrM tissue (n = 6) was characterized by flow cytometry and immunofluorescence. Promoters driving gene expression, specifically within the BrM-infiltrating HSC progeny, were identified through differential gene expression analysis and subsequent validation of a series of promoter-GFP-reporter constructs in mice (n = 5). One of the promoters was used to deliver TNF-related apoptosis-inducing ligand (TRAIL) to BrM in mice (n = 17/21 for TRAIL versus control group). Results: HSC progeny (consisting mostly of macrophages) efficiently homed to macrometastases (37.6% [SD = 7.2%] of all infiltrating cells for murine HSC progeny; 27.9% [SD = 4.9%] of infiltrating CD45+ hematopoietic cells for human HSC progeny) and micrometastases in mice (19.3-53.3% of all macrophages for murine HSCs). Macrophages were also abundant in patient-derived BrM tissue (8.8%, SD = 7.8%). Collectively, this provided a rationale to optimize the delivery of gene therapy to BrM within myeloid cells. MMP14 promoter emerged as the strongest promoter construct capable of limiting gene expression to BrM-infiltrating myeloid cells in mice TRAIL delivered under MMP14 promoter statistically significantly prolonged survival in mice (19.0 [SD = 3.4] versus 15.0 [SD = 2.0] days for TRAIL versus control group; two-sided p = 0.006), demonstrating therapeutic and translational potential of our approach. Conclusions: Our study establishes HSC gene therapy using a myeloid cell-specific promoter as a new strategy to target BrM. This approach, with strong translational value, has potential to overcome the blood-brain barrier, target micrometastases, and control multifocal lesions

Differential CpG DNA methylation in peripheral naïve CD4+ T-cells in early rheumatoid arthritis patients

Background: The genetic risk associated with rheumatoid arthritis (RA) includes genes regulating DNA methylation, one of the hallmarks of epigenetic re-programing, as well as many T-cell genes, with a strong MHC association, pointing to immunogenetic mechanisms as disease triggers leading to chronicity. The aim of our study was to explore DNA methylation in early, drug-naïve RA patients, towards a better understanding of early events in pathogenesis. Result: Monocytes, naïve and memory CD4+ T-cells were sorted from 6 healthy controls and 10 RA patients. DNA methylation was assessed using a genome-wide Illumina 450K CpG promoter array. Differential methylation was confirmed using bisulfite sequencing for a specific gene promoter, ELISA for several cytokines and flow cytometry for cell surface markers. Differentially methylated (DM) CpGs were observed in 1047 genes in naïve CD4+ T-cells, 913 in memory cells and was minimal in monocytes with only 177 genes. Naive CD4+ T-cells were further investigated as presenting differential methylation in the promoter of > 500 genes associated with several disease-relevant pathways, including many cytokines and their receptors. We confirmed hypomethylation of a region of the TNF-alpha gene in early RA and differential expression of 3 cytokines (IL21, IL34 and RANKL). Using a bioinformatics package (DMRcate) and an in-house analysis based on differences in β values, we established lists of DM genes between health and RA. Publicly available gene expression data were interrogated to confirm differential expression of over 70 DM genes. The lists of DM genes were further investigated based on a functional relationship database analysis, which pointed to an IL6/JAK1/STAT3 node, related to TNF-signalling and engagement in Th17 cell differentiation amongst many pathways. Five DM genes for cell surface markers (CD4, IL6R, IL2RA/CD25, CD62L, CXCR4) were investigated towards identifying subpopulations of CD4+ T-cells undergoing these modifications and pointed to a subset of naïve T-cells, with high levels of CD4, IL2R, and CXCR4, but reduction and loss of IL6R and CD62L, respectively. Conclusion: Our data provided novel conceptual advances in the understanding of early RA pathogenesis, with implications for early treatment and prevention

RNA sequencing and functional studies of patient-derived cells reveal that neurexin-1 and regulators of this pathway are associated with poor outcomes in Ewing sarcoma

Purpose The development of biomarkers and molecularly targeted therapies for patients with Ewing sarcoma (ES) in order to minimise morbidity and improve outcome is urgently needed. Here, we set out to isolate and characterise patient-derived ES primary cell cultures and daughter cancer stem-like cells (CSCs) to identify biomarkers of high-risk disease and candidate therapeutic targets. Methods Thirty-two patient-derived primary cultures were established from treatment-naïve tumours and primary ES-CSCs isolated from these cultures using functional methods. By RNA-sequencing we analysed the transcriptome of ES patient-derived cells (n = 24) and ES-CSCs (n = 11) to identify the most abundant and differentially expressed genes (DEGs). Expression of the top DEG(s) in ES-CSCs compared to ES cells was validated at both RNA and protein levels. The functional and prognostic potential of the most significant gene (neurexin-1) was investigated using knock-down studies and immunohistochemistry of two independent tumour cohorts. Results ES-CSCs were isolated from all primary cell cultures, consistent with the premise that ES is a CSC driven cancer. Transcriptional profiling confirmed that these cells were of mesenchymal origin, revealed novel cell surface targets for therapy that regulate cell-extracellular matrix interactions and identified candidate drivers of progression and relapse. High expression of neurexin-1 and low levels of regulators of its activity, APBA1 and NLGN4X, were associated with poor event-free and overall survival rates. Knock-down of neurexin-1 decreased viable cell numbers and spheroid formation. Conclusions Genes that regulate extracellular interactions, including neurexin-1, are candidate therapeutic targets in ES. High levels of neurexin-1 at diagnosis are associated with poor outcome and identify patients with localised disease that will relapse. These patients could benefit from more intensive or novel treatment modalities. The prognostic significance of neurexin-1 should be validated independently