星型胶质细胞瘤预后生物标志物的筛选

doi:10.3969/j.issn.1000-8535.2020.04.002

摘要/Abstract

摘要： 目的应用生物信息学的方法筛选参与星型胶质细胞瘤的预后生物标志物。方法首先,下载GEO(gene expression omnibus,GEO)数据库中星型胶质细胞瘤的基因芯片数据,通过R语言将来自4个数据集的基因芯片数据进行合并,将合并后的194人来源的脑组织样本分为:星型胶质细胞瘤组和正常组。然后对原始基因芯片数据进行批次效应去除和标准化处理,并使用密度图和主成分分析监测处理前后的效果。利用R语言中的limma包对处理后的基因芯片数据进行差异表达分析,从而筛选得到星型胶质细胞瘤组和正常组中之间的差异表达基因(differentially expressed genes,DEGs)。接着对差异表达基因进行GO(gene ontology,GO)分析和KEGG(kyoto encyclopedia of genes and genomes,KEGG)分析,并对所有基因的表达矩阵进行GSEA(gene set enrichment analysis,GSEA)分析。通过STRING数据库构建差异表达基因的蛋白—蛋白相互作用网络(protein-protein interaction,PPI),通过Cytoscape中的cytoHubba插件筛选Hub基因。为了探索Hub基因在星型胶质细胞中的诊断价值和预后价值,我们下载TCGA(the cancer genome atlas,TCGA)数据库中的基因表达数据和临床预后资料,使用ROC曲线评价Hub基因的诊断价值,并对诊断价值较高的Hub基因进行COX回归,筛选HR值最有意义的基因进行总生存分析(overall survival,OS)。结果通过limma包总共分析得到1 043个差异表达基因。GO分析结果表明差异表达基因主通过影响神经突触的功能而发挥作用。KEGG分析结果显示钙信号通路、cAMP信号通路、MAPK信号通路、PI3K-Akt信号通路、Rap1信号通路和Ras信号通路等通路等在星型胶质细胞瘤中发挥着重要的作用。GSEA富集分析结果主要富集于细胞因子-细胞因子受体相互作用、JAK-STAT信号通路、逆行内源性大麻素信号、神经活性配体-受体相互作用、GABA能突触和钙信号通路等通路。通过PPI网络总共分析得到ADCY1、ANXA1和PENK等20个Hub基因。通过对Hub基因的诊断价值和预后价值进行评价,发现SST在星型胶质细胞瘤既可作为诊断标志物,也可作为预后生物标志物。结论我们通过生物信息学分析发现SST可作为星型胶质细胞的预后生物标志物,又预测了Rap1信号通路有可能成为星型胶质细胞分子机制中的新通路。

关键词: 星型胶质细胞瘤, 生物信息学, 差异表达基因, 基因芯片

Abstract: Objective To screen biomarkers involved in the prognosis of astrocytoma by bioinformatics. Methods Firstly,the gene chip data of astrocytoma in GEO database were downloaded. The gene chip data from four data sets were combined by R language. The combined 194 human brain samples were divided into astrocytoma group and normal group. Then,the original microarray data were processed by batch effect removal and standardization,and the effects before and after processing were monitored by density map and principal component analysis. The differentially expression genes (DEGs) between astrocytoma group and normal group were screened by using limma package of R language to analyze the differentially expression of the processed gene chip data. Then gene ontology(GO) analysis and Kyoto encyclopedia of genes and genes (KEGG) analysis were carried out for the differentially expressed genes,and gene set enrichment analysis (GSEA) was carried out for the expression matrix of all genes. The protein-protein interaction (PPI) network of differentially expressed genes was constructed by using string database,and the Hub gene was screened by using the cytohubba plug-in of Cytoscape. In order to explore the diagnostic value and prognostic value of Hub gene in astrocytes,we downloaded the gene expression data and clinical prognostic data in the Cancer Genome Atlas(TCGA) database,used ROC curve to evaluate the diagnostic value of hub gene,and Cox regression for Hub gene with high diagnostic value,and screen the most significant gene of HR value for overall survival(OS) analysis. Results A total of 1 043 differentially expressed genes were obtained by limma analysis. Go analysis showed that the differentially expressed genes played an important role by affecting the function of synapses. KEGG analysis showed that calcium signaling pathway,cAMP signaling pathway,MAPK signaling pathway,PI3K Akt signaling pathway,Rap1 signaling pathway and Ras signaling pathway played an important role in astrocytoma. The results of GSEA enrichment analysis were mainly enriched in cytokine cytokine receptor interaction,JAK-STAT signaling pathway,retrograde endogenous cannabinoid signaling,neuroactive ligand receptor interaction,GABAergic synapse and calcium signaling pathway. A total of 20 Hub genes such as ADCY1,ANXA1 and PINK were obtained by PPI network analysis. By evaluating the diagnostic and prognostic value of hub gene,we found that SST could be used as both a diagnostic marker and a prognostic biomarker in astrocytoma. Conclusion We found that SST could be used as a biomarker for the prognosis of astrocytes by bioinformatics analysis,and predicted that Rap1 signaling pathway may be a new pathway in the molecular mechanism of astrocytes.

Key words: Astroglioma, Bioinformatics, Differential gene, Gene chip

王圆圆, 义勇军. 星型胶质细胞瘤预后生物标志物的筛选[J]. 广州医药, 2020, 51(4): 5-12.

WANG Yuanyuan, YI Yongjun. Screening of prognostic biomarkers for astrocytoma[J]. Guangzhou Medical Journal, 2020, 51(4): 5-12.

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