Dataset Information

Expression of lncRNAs in Low-Grade Gliomas and Glioblastoma Multiforme: An In Silico Analysis.

ABSTRACT:

Background

Each year, over 16,000 patients die from malignant brain cancer in the US. Long noncoding RNAs (lncRNAs) have recently been shown to play critical roles in regulating neurogenesis and brain tumor progression. To better understand the role of lncRNAs in brain cancer, we performed a global analysis to identify and characterize all annotated and novel lncRNAs in both grade II and III gliomas as well as grade IV glioblastomas (glioblastoma multiforme [GBM]).

Methods and findings

We determined the expression of all lncRNAs in over 650 brain cancer and 70 normal brain tissue RNA sequencing datasets from The Cancer Genome Atlas (TCGA) and other publicly available datasets. We identified 611 induced and 677 repressed lncRNAs in glial tumors relative to normal brains. Hundreds of lncRNAs were specifically expressed in each of the three lower grade glioma (LGG) subtypes (IDH1/2 wt, IDH1/2 mut, and IDH1/2 mut 1p19q codeletion) and the four subtypes of GBMs (classical, mesenchymal, neural, and proneural). Overlap between the subtype-specific lncRNAs in GBMs and LGGs demonstrated similarities between mesenchymal GBMs and IDH1/2 wt LGGs, with 2-fold higher overlap than would be expected by random chance. Using a multivariate Cox regression survival model, we identified 584 and 282 lncRNAs that were associated with a poor and good prognosis, respectively, in GBM patients. We developed a survival algorithm for LGGs based on the expression of 64 lncRNAs that was associated with patient prognosis in a test set (hazard ratio [HR] = 2.168, 95% CI = 1.765-2.807, p < 0.001) and validation set (HR = 1.921, 95% CI = 1.333-2.767, p < 0.001) of patients from TCGA. The main limitations of this study are that further work is needed to investigate the clinical relevance of our findings, and that validation in an independent dataset is needed to determine the robustness of our survival algorithm.

Conclusions

This work identifies a panel of lncRNAs that appear to be prognostic in gliomas and provides a critical resource for future studies examining the role of lncRNAs in brain cancers.

SUBMITTER: Reon BJ

PROVIDER: S-EPMC5140055 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

Expression of lncRNAs in Low-Grade Gliomas and Glioblastoma Multiforme: An In Silico Analysis.

Reon Brian J BJ Anaya Jordan J Zhang Ying Y Mandell James J Purow Benjamin B Abounader Roger R Dutta Anindya A

PLoS medicine 20161206 12

<h4>Background</h4>Each year, over 16,000 patients die from malignant brain cancer in the US. Long noncoding RNAs (lncRNAs) have recently been shown to play critical roles in regulating neurogenesis and brain tumor progression. To better understand the role of lncRNAs in brain cancer, we performed a global analysis to identify and characterize all annotated and novel lncRNAs in both grade II and III gliomas as well as grade IV glioblastomas (glioblastoma multiforme [GBM]).<h4>Methods and finding ...[more]

PMID: 27923049

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Project description:MicroRNAs (miRNAs or miRs) contribute to the development of various malignant neoplasms, including glioblastoma multiforme (GBM). The present study aimed to explore the pathogenesis of GBM and to identify latent therapeutic agents for patients with GBM, based on an in silico analysis. Gene chips that provide miRNA expression profiling in GBM were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEMs) were also determined via the RobustRankAggreg algorithm. The target genes of DEMs were predicted and then intersected with GBM?associated genes that were collected from the Gene Expression Profiling Interactive Analysis. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the overlapping genes were then performed. Simultaneously, a connectivity map (CMap) analysis was performed to screen for potential therapeutic agents for GBM. A total of 10 DEMs (hsa?miR?196a, hsa?miR?10b, hsa?miR?196b, hsa?miR?18b, hsa?miR?542?3p, hsa?miR?129?3p, hsa?miR?1224?5p, hsa?miR?876?3p and hsa?miR?770?5p) were obtained from three GEO gene chips (GSE25631, GSE42657 and GSE61710). Then, 1,720 target genes of the 10 miRNAs and 4,185 differently expressed genes in GBM were collected. By intersecting the aforementioned gene clusters, the present study identified 390 overlapping genes. GO and KEGG analyses of the 390 genes demonstrated that these genes were involved in certain cancer?associated biological functions and pathways. Eight genes [(GTPase NRas (NRAS), calcium/calmodulin?dependent protein kinase type II subunit Gamma (CAMK2G), platelet?derived growth factor receptor alpha (PDGFRA), calmodulin 3 (CALM3), cyclin?dependent kinase 6 (CDK6), calcium/calmodulin?dependent protein kinase type II subunit beta (CAMK2B), retinoblastoma?associated protein (RB1) and protein kinase C beta type (PRKCB)] that were centralized in the glioma pathway were selected for CMap analysis. Three chemicals (W?13, gefitinib and exemestane) were identified as putative therapeutic agents for GBM. In summary, the present study identified three miRNA?based chemicals for use as a therapy for GBM. However, more experimental data are needed to verify the therapeutic properties of these latent drugs in GBM.

Dataset Information

Expression of lncRNAs in Low-Grade Gliomas and Glioblastoma Multiforme: An In Silico Analysis.

Background

Methods and findings

Conclusions

Publications

Expression of lncRNAs in Low-Grade Gliomas and Glioblastoma Multiforme: An In Silico Analysis.

Similar Datasets

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