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Research Article

lncRNA and mRNA signature for prognosis prediction of glioblastoma

    Guohong Liu‡

    Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, PR China

    ‡Equal contribution and co-first authors

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    ,
    Yunbao Pan‡

    Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, PR China

    ‡Equal contribution and co-first authors

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    ,
    Yueying Li

    Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, PR China

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    &
    Haibo Xu

    *Author for correspondence:

    E-mail Address: xuhaibo1120@hotmail.com

    Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, PR China

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    Published Online:6 Apr 2020https://doi.org/10.2217/fon-2019-0538

    Abstract

    Aims: We aimed to find out potential novel biomarkers for prognosis of glioblastoma (GBM). Materials & methods: We downloaded mRNA and lncRNA expression profiles of 169 GBM and five normal samples from The Cancer Genome Atlas and 129 normal brain samples from genotype-tissue expression. We use R language to perform the following analyses: differential RNA expression analysis of GBM samples using ‘edgeR’ package, survival analysis taking count of single or multiple gene expression level using ‘survival’ package, univariate and multivariate Cox regression analysis using Cox function plugged in ‘survival’ package. Gene ontology and Kyoto encyclopedia of genes and genomes pathway analysis were performed using FunRich tool online. Results and conclusion: We obtained differentially DEmRNAs and DElncRNAs in GBM samples. Most prognostically relevant mRNAs and lncRNAs were filtered out. ‘GPCR ligand binding’ and ‘Class A/1’ are found to be of great significance. In short, our study provides novel biomarkers for prognosis of GBM.

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