| Literature DB >> 32250161 |
Guohong Liu1, Yunbao Pan2, Yueying Li2, Haibo Xu1.
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.Entities:
Keywords: The Cancer Genome Atlas; biomarker; cox regression; glioblastoma; lncRNA; mRNA; prognosis; survival
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Year: 2020 PMID: 32250161 DOI: 10.2217/fon-2019-0538
Source DB: PubMed Journal: Future Oncol ISSN: 1479-6694 Impact factor: 3.404