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基于生物信息学分析的鼻咽癌中与ceRNA网络相关关键基因的综合分析

Comprehensive analysis of key genes associated with ceRNA networks in nasopharyngeal carcinoma based on bioinformatics analysis.

作者信息

Xu Yuanji, Huang Xinyi, Ye Wangzhong, Zhang Yangfan, Li Changkun, Bai Penggang, Lin Zhizhong, Chen Chuanben

机构信息

Department of Radiation Oncology, Fujian Medical University Cancer Hospital & Fujian Cancer Hospital, No. 420, Fuma Road, Fuzhou, 350014 Fujian People's Republic of China.

Fujian Medical University, Fuzhou, Fujian People's Republic of China.

出版信息

Cancer Cell Int. 2020 Aug 26;20:408. doi: 10.1186/s12935-020-01507-1. eCollection 2020.

DOI:10.1186/s12935-020-01507-1
PMID:32863767
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7448472/
Abstract

BACKGROUND

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy with high morbidity rates in the east and southeast Asia. The molecular mechanisms of NPC remain largely unknown. We explored the pathogenesis, potential biomarkers, and prognostic indicators of NPC.

METHODS

We analyzed mRNAs, long non-coding RNAs (lncRNAs), and microRNAs (miRNAs) in the whole transcriptome sequencing dataset of our hospital (five normal tissues vs. five NPC tissues) and six microarray datasets (62 normal tissues vs. 334 NPC tissues) downloaded from the Gene Expression Omnibus (GSE12452, GSE13597, GSE95166, GSE126683, and GSE70970, GSE43039). Differential expression analyses, gene ontology (GO) enrichment, kyoto encyclopedia of genes and genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) were conducted. The lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks were constructed using the miRanda and TargetScan database, and a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) was built using Search Tool for the Retrieval of Interacting Genes (STRING) software. Hub genes were identified using Molecular Complex Detection (MCODE), NetworkAnalyzer, and CytoHubba.

RESULTS

We identified 61 mRNAs, 14miRNAs, and 10 lncRNAs as shared DEGs related to NPC in seven datasets. Changes in NPC were enriched in the chromosomal region, sister chromatid segregation, and nuclear chromosome segregation. GSEA indicated that the mitogen-activated protein kinase (MAPK) pathway, phosphatidylinositol-3 OH kinase/protein kinase B (PI3K-Akt) pathway, apoptotic pathway, and tumor necrosis factor (TNF) were involved in the initiation and development of NPC. Finally, 20 hub genes were screened out via the PPI network.

CONCLUSIONS

Several DEGs and their biological processes, pathways, and interrelations were found in our current study by bioinformatics analyses. Our findings may offer insights into the biological mechanisms underlying NPC and identify potential therapeutic targets for NPC.

摘要

背景

鼻咽癌(NPC)是一种上皮性恶性肿瘤,在东亚和东南亚发病率较高。鼻咽癌的分子机制在很大程度上仍不清楚。我们探讨了鼻咽癌的发病机制、潜在生物标志物和预后指标。

方法

我们分析了我院全转录组测序数据集(5个正常组织与5个鼻咽癌组织)以及从基因表达综合数据库(GSE12452、GSE13597、GSE95166、GSE126683、GSE70970、GSE43039)下载的6个微阵列数据集(62个正常组织与334个鼻咽癌组织)中的mRNA、长链非编码RNA(lncRNA)和微小RNA(miRNA)。进行了差异表达分析、基因本体(GO)富集分析、京都基因与基因组百科全书(KEGG)分析以及基因集富集分析(GSEA)。使用miRanda和TargetScan数据库构建lncRNA-miRNA-mRNA竞争性内源RNA(ceRNA)网络,并使用搜索相互作用基因的工具(STRING)软件构建差异表达基因(DEG)的蛋白质-蛋白质相互作用(PPI)网络。使用分子复合物检测(MCODE)、网络分析仪(NetworkAnalyzer)和细胞枢纽基因(CytoHubba)鉴定枢纽基因。

结果

我们在7个数据集中鉴定出61个mRNA、14个miRNA和10个lncRNA作为与鼻咽癌相关的共享DEG。鼻咽癌的变化在染色体区域、姐妹染色单体分离和核染色体分离中富集。GSEA表明丝裂原活化蛋白激酶(MAPK)途径、磷脂酰肌醇-3-OH激酶/蛋白激酶B(PI3K-Akt)途径、凋亡途径和肿瘤坏死因子(TNF)参与了鼻咽癌的发生和发展。最后,通过PPI网络筛选出20个枢纽基因。

结论

通过生物信息学分析,我们在当前研究中发现了几个DEG及其生物学过程、途径和相互关系。我们的发现可能为鼻咽癌的生物学机制提供见解,并确定鼻咽癌潜在的治疗靶点。

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