通过生物信息学分析鉴定九个关键基因以预测吸烟诱导的肺腺癌预后不良

Ren Chuanli, Sun Weixiu, Lian Xu, Han Chongxu

Department of Laboratory Medicine, Clinical Medical College, Yangzhou University, Yangzhou, PR China.

Clinical Laboratory Diagnostics, Clinical Medical College, Dalian Medical University, Dalian, PR China.

Lung Cancer Manag. 2020 Apr 27;9(2):LMT30. doi: 10.2217/lmt-2020-0009.

AIM

To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).

MATERIALS & METHODS: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan-Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.

RESULTS

Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.

CONCLUSION

23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

目的

筛选并鉴定与吸烟诱导的肺腺癌（LUAD）发生发展相关的关键基因。

材料与方法

我们从GEO芯片数据集GSE31210获取数据。通过GEO2R筛选差异表达基因。利用STRING和Cytoscape构建差异表达基因的蛋白质相互作用网络。最后筛选出核心基因。采用Kaplan-Meier法分析具有核心基因的患者的总生存时间。通过DAVID计算基因本体和京都基因与基因组百科全书生物累积。