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本研究通过多种生物信息学手段寻找参与肺腺癌发生和预后的相关性基因，为探索肺腺癌的分子机制提供理论依据。首先从基因表达汇编(gene expression omnibus, GEO)数据库中下载Ⅰ期肺腺癌的基因表达芯片和基因甲基化芯片，利用GEO2R工具分析肺腺癌组织与正常肺组织之间的差异基因，鉴定出199个低甲基化高表达基因和403个高甲基化低表达基因，使用注释、可视化和集成发现(the database for annotation,visualization and integrated discovery, DAVID)数据库分析其功能。然后，通过STRING构建选定基因的蛋白质间相互作用(PPI)网络，并在Cytoscape软件中可视化，通过插件MCODE和cytoHubba进一步对PPI网络进行分析，筛选出7个关键基因(FGF2、VWF、CDH5、CD34、KITLG、BMP2和TEK)，通过癌症基因组图谱(the cancer genome atlas, TCGA)数据库和人类蛋白质图谱(HPA)进行验证，并截取了免疫组化代表性图像。最后，使用Kaplan-Meier Plotter在线工具验证每个关键基因在肺腺癌患者中的独立预后价值，发现这7个关键基因均与患者总生存时间密切相关。本研究通过结合基因表达谱和甲基化谱芯片数据的分析获得了7个与早期肺腺癌相关的关键基因，有助于更全面地了解肺腺癌的分子机制，可作为肺腺癌基于甲基化的异常生物标志物及潜在的治疗分子靶标。
Abstract：In this study, a variety of bioinformatics methods were used to find the key genes involved in the occurrence and prognosis of lung adenocarcinoma, so as to provide a theoretical basis for exploring the molecular mechanism of lung adenocarcinoma. Firstly, 199 hypomethylation-high expression genes and 403 hypermethylation-low expression genes were obtained from the GEO(gene expression omnibus) database, and their functions were analyzed by using the DAVID(database for annotation, visualization and integrated discovery) database.Then, the protein-protein interaction(PPI) network of selected genes was constructed by STRING and visualized in Cytoscape. The module analysis and hub genes selection of the PPI network were further analyzed by plugin MCODE and CytoHubba. Then, the analyzed results were verified by the cancer genome atlas(TCGA) analysis and the human protein atlas(HPA). Seven hub genes were ultimately identified due to significantly different hub genes. Finally, the independent prognostic value of each hub gene in lung adenocarcinoma patients was further verified through Kaplan-Meier plotter. All the seven hub genes were closely associated with the overall survival time. Our study indicated the correlation of aberrantly methylated-differential expressed genes(MDEGs) and related pathways with lung adenocarcinoma(LUAD), which would help understanding the molecular mechanisms during progression of LUAD. Hub genes with high methylation including FGF2, VWF, CDH5, CD34,KITLG, BMP2 and TEK might serve as aberrantly methylation-based biomarkers for precise diagnosis and prognosis of LUAD in the future.
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基本信息:
DOI：10.13417/j.gab.040.003797
中图分类号:R734.2
引用信息:
[1]刘彦君,谢倩,梁子豪.基于GEO芯片数据的I期肺腺癌特征基因生物信息学及预后关联性分析[J].基因组学与应用生物学,2021,40(Z4):3797-3807.DOI:10.13417/j.gab.040.003797.
基金信息:
国家自然科学基金项目(81470210; 81770014); 江苏高校优势学科建设工程项目共同资助
2021-07-26
2021-07-26
2021-07-26