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Diffuse intrinsic pontine glioma (DIPG) is one of the most devastating types of pediatric cancer. Accumulating evidence suggests that the dysregulated expression of long non-coding (lnc)-RNAs is associated with various pathologies of the CNS. However, the expression patterns and prognostic roles of lncRNAs in DIPG have not yet been systematically determined. In the present study, lncRNA expression profiles were obtained from the Gene Expression Omnibus (GEO) database using the lncRNA-mining approach and a differential expression analysis for lncRNAs was performed between DIPG and low-grade brainstem glioma and DIPG and normal pediatric brainstem tissue. Using a two-tailed t-test, 58 and 197 lncRNAs were found to be significantly deferentially expressed (Fold change >2 or <0.5, FDR adjusted P<0.05). To identify the prognostic value of these 255 differentially expressed lncRNAs, univariate and multivariate Cox proportional hazards regression analysis were performed and a 9-lncRNA signature as a potential biomarker for predicting the prognosis of DIPG was constructed. Kaplan-Meier curve analysis showed that patients in the high-risk group exhibited a reduced survival time compared with patients in the low-risk group (median survival of 230 vs. 460 days, log-rank test P<0.001). Moreover, this lncRNA-signature could be used as an independent prognostic marker for DIPG patient survival. The present study provided novel candidates for the investigation of potential diagnostic or prognostic biomarkers and/or therapeutic targets of DIPG, as well as a novel insight into the underlying mechanisms of DIPG.
Pubmed ID: 30405776 RIS Download
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Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsA Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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