Background and objective: Lung cancer is the most common cancer in the world. The gene expression profiling of lung cancer has been extensively investigated. However, only a few studies have identified the possible pathways and significant genes related to lung cancer. The aim of this study is to explore the large number of lung cancer-related microarray datasets and identify the crucial genes that can benefit the understanding of the progression and development of this disease.
Methods: To identify the genes that effected lung cancer at the mRNA level, gene set enrichment analysis was used to analyze six selected gene expression datasets.
Results: Among the six gene expression datasets, 3 up-regulated and 26 down-regulated pathways were found by gene set enrichment analysis. We found 11 significant genes with P < 0.05 from the results of tight junction meta-analysis of the six data sets.
Conclusions: The tight junction pathway plays an important role in the study of the occurrence and development of lung cancer. Significant genes within the pathways will be further discussed in future studies.
背景与目的: 肺癌是最常见的恶性肿瘤之一。对于肺癌基因芯片的研究已在很多报道里提及，但是鲜有报道汇总所有的基因芯片数据来研究肺癌的共同表达通路从而挖掘出特殊的基因标记来作为治疗肺癌的靶点。本研究从肺癌相关的基因芯片数据库（GEO DataSets）中初步筛选出与肺癌发生发展有关键联系的基因与通路。
方法: 运用基因富集（gene set enrichment analysis, GSEA）等生物信息学方法比较选择出的6套肺癌基因芯片表达谱数据，初步筛选出在转录水平上影响肺癌的通路及基因。
结果: 用GSEA方法分析6组芯片集中所得的通路对比，上调中皆有的通路有3条；下调中皆有的通路有26条。本研究挑选共同存在于6套芯片数据集的下调通路即紧密连接（tight junction）通路里的基因进行meta分析，可得差异有统计学意义（P < 0.05）的基因11个。
结论: 紧密连接通路在肺癌发生发展过程中的共性可能有一定研究意义，可在后续研究中探讨通路里的显著性基因。