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Plaisier, C.L., Horvath, S., Huertas-Vazquez, A., et al. (2009) A Systems Genetics Approach Implicates USF1, FADS3, and Other Causal Candidate Genes for Familial Combined Hyperlipidemia. PLoS Genets, 5, e1000642.
http://dx.doi.org/10.1371/journal.pgen.1000642

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  • 标题: 与肺癌相关的基因共表达网络的构建与分析The Construction and Analysis of Gene Co-Expression Network in Lung Cancer

    作者: 翟媛媛, 陈颖丽, 薛济先

    关键字: 肺癌, 基因共表达网络, 枢纽基因, WGCNALung Cancer, Gene Co-Expression Network, Hub Gene, WGCNA

    期刊名称: 《Hans Journal of Computational Biology》, Vol.6 No.2, 2016-06-28

    摘要: 肺癌是目前世界范围内发病率和死亡率最高的恶性肿瘤,它是一种复杂的分子网络疾病。为了进一步了解肺癌致病的分子机制,我们使用加权基因共表达网络分析(WGCNA)方法,对肺癌组织与其癌旁正常组织的差异表达基因进行分析,进而对差异表达基因进行模块的划分以及枢纽基因(hub gene)的识别,共得到了八个模块。通过计算每个模块特征向量基因(module eigengene)与样本特征的皮尔森相关系数,最终得到一个与肺癌高关联的模块(blue模块),发现blue模块的枢纽基因为碳酸酐酶4 (carbonic anhydrase 4, CA4),这一枢纽基因在模块中起着重要的作用。使用在线工具DAVID (Database for Annotation, Visualization and Integrated Discovery)对blue模块进行GO功能富集及KEGG通路分析。GO分析显示blue模块具有Rho 蛋白的信号转导调控、生物粘附、糖结合等生物功能;KEGG分析显示blue模块参与了轴突导向和O 型聚糖的生物合成通路。这些分析结果表明,文中识别的肺癌高关联模块和枢纽基因在肺癌的发生发展过程中起着潜在的重要作用。 Lung cancer, a complex molecular network disease, is a malignant tumor with the highest inci-dence and mortality around the world at present. In order to further understand the pathogenic molecular mechanism of lung cancer, we firstly identified differentially expressed gene (DEG) between cancer tissue and the corresponding adjacent normal tissue. Then, we used weighted gene co-expression network analysis (WGCNA) to screen for the DEG. In total, eight gene modules of DEG were detected and hub genes were identified. By calculating the Pearson’s correlation coefficient between module eigengene and sample traits, we obtained the blue module which was highly associated with lung cancer, and found the hub gene of blue module was carbonic anhydrase 4. Hub gene plays an important role in the blue module. By using Database for Annotation, Visualization and Integrated Discovery (DAVID), the Gene Ontology (GO) enrichment analysis and KEGG pathway analysis were performed for blue module. The analysis of GO showed that blue module played important roles in biological functions, such as regulation of Rho protein signal transduction, biological adhesion, and carbohydrate binding. The analysis of KEGG indicated that blue module took part in the pathways of axon guidance and O-Glycan biosynthesis. The results showed that high correlations modules of lung cancer and hub gene identified in this paper played a potentially important role in the development of lung cancer.

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