基于生物信息学的脑胶质瘤预后风险长链非编码RNA筛选

doi:10.3969/j.issn.2095-9400.2020.03.007

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Abstract Objective: To screen long-chain non-coding RNA (lncRNA) for prognostic risk of gliomas based on bioinformatics. Methods: Transcript data of glioma samples were downloaded from the open Cancer Gene Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data platform, using R language to compare and analyze glioma and normal differentially expressed genes. The risk model was constructed by Cox analysis. Functional annotation and pathway enrichment analysis of differentially expressed genes were performed through the DAVID gene function and KEGG pathway database. The relationship between the expression of HOXA-AS2 and the clinical tissue characteristics of glioma was evaluated by qPCR. Results: By comparing the gene transcription level data between glioma and normal brain tissue samples, 424 differentially expressed lncRNA (211 up-regulated and 213 down-regulated) and 3 827 differentially expressed mRNA (1 618 up-regulated and 2209 down-regulated) were obtained. A risk model containing 9 lncRNAs was constructed. The results of the enrichment analysis of co-expressed genes showed that they were mainly enriched in the control of channel protein activity and molecular adhesion. The high expression of HOXA-AS2 in glioma was verified by qPCR. Conclusion: HOXA-AS2 may be a prognostic risk lncRNA for glioma, which can be a reference for subsequent studies on the mechanism of glioma.

Key words： glioma TCGA database GTEx database long non-coding RNA mRNA Cox analysis

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	U Shengjian
	MA Huailu
	CHEN Wangyang
	DING Xiaofei
	CHEN Guang
	LIANG Yong

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https://xb.wmu.edu.cn/EN/10.3969/j.issn.2095-9400.2020.03.007 OR https://xb.wmu.edu.cn/EN/Y2020/V50/I3/199

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