Background and objective: Lung adenocarcinoma (AC) is the most common type of lung cancer, however, its mechanism of oncongenesis is still unknown. The aim of this study is to screen candidate genes of lung adenocarcinoma using bioinformatics strategy and elucidate the mechanism of lung adenocarcinoma.
Methods: Two published microarray data (GSE7670 and GSE10072) was obtained from Gene Expression Omnibus (GEO). Significance analysis of microarrays was performed with the software dchip, and differential expression genes from dchip analysis were defined as "test gene set". Genes correlated with lung adenocarcinoma, obtained by data mining tools genecard and Fable were regarded as "train gene set". Finally, candidate genes of lung adenocarcinoma were screened by the tool "Toppgene".
Results: Three hundred and forty-four differential genes were defined as "test gene set", and 277 genes correlated with lung adenocarcinoma were regarded as "train gene set". Thirty-six candidate genes were screened out by Toppgene, among them, 21 genes had nearly no report in cancer. In the following QRT-PCR experiment, CD36, PMAIP1 and FABP4 were down-regulated expression in A549, which coincided with the gene chip.
Conclusion: It is demonstrated that Toppgene is useful in identification of the candidate genes of lung adenocacinoma, which provides the proof for the discovery of the specific disease genes.
背景与目的: 肺腺癌是危害人类健康最主要的肺癌类型之一，其发生机制仍不清楚。本研究利用生物信息学方法，筛选新的肺腺癌候选基因，为揭示肺腺癌发病机制提供依据。
方法: 从GEO数据库中获得GSE10072和GSE7670两个数据集，然后利用dchip软件进行差异表达基因分析，将其获得的差异基因定义为“检测基因集”（test gene set）；采用genecard和Fable文献挖掘已知肺腺癌疾病基因，并将其定义为“训练基因集”（train gene set）；最后，利用Toppgene筛选肺腺癌候选基因，并通过荧光定量PCR对其获得的部分基因进行验证。
结果: 获得一个含344个基因的“检测基因集”和含277个基因的“训练基因集”。采用Toppgene共获得36个候选疾病基因，其中21个基因则在肿瘤方面的研究几无报道。荧光定量PCR实验研究发现，CD36、PMAIP1及FABP4三个基因在A549细胞中均为下调表达，与芯片数据一致。
结论: Toppgene可发现新的肺腺癌候选疾病基因，为下一步发现特异性肺腺癌致病基因提供理论依据。