Dataset Information

Identification of a long noncoding RNA signature to predict outcomes of glioblastoma.

ABSTRACT: Long noncoding RNAs (lncRNAs) are a novel class of gene regulators involved in tumor biogenesis. Glioblastoma is the most common and malignant type of brain tumor. The function and prognostic significance of lncRNAs in glioblastoma remain unclear. In the present study, updated gene annotations were adopted to investigate lncRNA expression profiles in publicly available glioma microarray datasets from the Gene Expression Omnibus and the Repository for Molecular Brain Neoplasia Data. In a training set of 108 samples of glioblastoma, using univariate Cox regression analysis with a permutation P<0.005, four lncRNAs, including insulin?like growth factor binding protein 7?antisense 1 (IGFBP7?AS1), were significantly associated with patient overall survival. These four lncRNAs were integrated as an expression?based molecular signature to divide patients in the training set into high?risk and low?risk subgroups, with distinct survival rates (hazard ratio, 2.72; 95% CI, 1.71?4.31; P<0.001). The prognostic value of the lncRNA signature was confirmed in two additional datasets comprising a total of 147 samples from patients with glioblastoma. The prognostic value of this signature was independent of age and Karnofsky performance status. This signature was also able to predict different outcomes in cases of glioblastoma associated with an isocitrate dehydrogenase 1 mutation. Further bioinformatics analyses revealed that 'epithelial?mesenchymal transition' and 'p53 pathway' gene sets were enriched in glioblastoma samples with higher IGFBP7?AS1 expression. Furthermore, in vitro experiments demonstrated that knockdown of IGFBP7?AS1 inhibited the viability, migration and invasion of U87 and U251 glioma cells. In conclusion, the present study identified a lncRNA signature able to predict glioblastoma outcomes, and provided novel information regarding the role of IGFBP7?AS1 in glioma development.

SUBMITTER: Li D

PROVIDER: S-EPMC6522932 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Identification of a long noncoding RNA signature to predict outcomes of glioblastoma.

Li Depei D Lu Jie J Li Hong H Qi Songtao S Yu Lei L

Molecular medicine reports 20190424 6

Long noncoding RNAs (lncRNAs) are a novel class of gene regulators involved in tumor biogenesis. Glioblastoma is the most common and malignant type of brain tumor. The function and prognostic significance of lncRNAs in glioblastoma remain unclear. In the present study, updated gene annotations were adopted to investigate lncRNA expression profiles in publicly available glioma microarray datasets from the Gene Expression Omnibus and the Repository for Molecular Brain Neoplasia Data. In a training ...[more]

PMID: 31059035

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Project description:OBJECTIVES:The long-noncoding RNAs (lncRNAs) are identified as new crucial regulators of diverse cellular processes in glioblastoma (GBM) tissues. However, the expression pattern and biological function of lncRNAs remain largely unknown. Here, for the first time, the effects of lncRNA lymphoid enhancer-binding factor 1 antisense RNA 1 (LEF1-AS1) on GBM progression both in vitro and in vivo are investigated. MATERIALS AND METHODS:Expression profiles of LEF1-AS1 in GBM specimens were investigated by bioinformatics analyses. LEF1-AS1 expression in GBM tissues was detected using a quantitative polymerase chain reaction. LEF1-AS1 expression was inhibited by transfecting the LEF1-AS1-specific small interfering RNAs (siRNAs) and stable cell lines established were inhibited by transfecting si-LEF1-AS1 viruses. The Cell Counting Kit-8, ethynyl deoxyuridine, and colony formation assay were used to examine proliferation function. The flow cytometry detected cell-cycle change and apoptosis. Migration effects were detected by a Transwell assay. The tumor xenografts and immunohistochemistry were performed to evaluate tumor growth in vivo. RESULTS:In this study, LEF1-AS1 expression was found significantly upregulated in GBM specimens compared with normal tissues. The 5-year overall survival in GBM patients from The Cancer Genome Atlas with high expression of LEF1-AS1 was inferior to that with low expression. It was confirmed that expression of LEF1-AS1 was higher in GBM tissues than normal ones. Knockdown of LEF1-AS1 significantly inhibited the malignancy of GBM cells, including proliferation and invasion, and promoted cell apoptosis. The result of Western blot assays indicated that knockdown of LEF1-AS1-mediated tumor suppression in GBM cells may be via the reduction of ERK and Akt/mTOR signaling activities. Finally, the in vivo experiment also demonstrated that knockdown LEF1-AS1 inhibited the growth-promoting effect of LEF1-AS1 of U87 cells. CONCLUSION:Our result indicated that lncRNA LEF1-AS1 acts as an oncogene in GBM and may be a pivotal target for this disease.

Project description:Due to the increasing prevalence of type 1 diabetes mellitus (T1DM) and its complications, there is an urgent need to identify novel methods for predicting the occurrence and understanding the pathogenetic mechanisms of the disease. Accumulated data have demonstrated the potential of long noncoding RNAs (lncRNAs), as biomarkers in establishing diagnosis and predicting prognosis of numerous diseases. Yet, little is known about the expression patterns and regulatory roles of lncRNAs in the pathogenesis of T1DM and whether they can be used as diagnostic biomarkers for the disease. To further explore these questions, in the present study, we conducted a comparative analysis of the expression patterns of lncRNAs between 20 T1DM patients and 42 health controls by retrospectively analyzing a published microarray data set. Our results indicate that, compared with healthy controls, diabetic patients had altered levels of lncRNAs. Then, we used three time cross-validation strategy and support vector machine to propose a specific 26-lncRNA signature (termed 26LncSigT1DM). This 26LncSigT1DM signature can be used to effectively distinguish between healthy and diabetic individuals (area under the curve = 0.825) of a validation cohort. After the 26LncSigT1DM was prospectively validated, we used Pearson correlation to identify 915 mRNAs, whose expression levels were positively correlated with those of the 26 lncRNAs. According to their Gene Ontology annotations, these mRNAs participate in processes including cellular response to stimulus, cell communication, multicellular organismal process, and cell motility. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the genes encoding the 915 mRNAs may be associated with the NOD-like receptor signaling pathway, transforming growth factor β signaling pathway, and mineral absorption, suggesting that the deregulation of these lncRNAs may mediate inflammatory abnormalities and immune dysfunctions, which jointly promote the pathogenesis of T1DM. Thus, our study identifies a novel diagnostic tool and may shed more light on the molecular mechanisms underlying the pathogenesis of T1DM.

Dataset Information

Identification of a long noncoding RNA signature to predict outcomes of glioblastoma.

Publications

Identification of a long noncoding RNA signature to predict outcomes of glioblastoma.

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