小鼠舌癌模型差异基因的筛选及生物信息学分析

Differentially expressed gene screening of rats tongue cancer and bioinformatics analysis

目的:对小鼠舌癌模型差异表达基因进行筛选及基因功能分析,为舌癌发病机制相关的分子标志物及药物靶点提供理论基础。方法:从高通量基因表达(GEO)数据库中选取GSE64271和GSE75421数据包,获取其中小鼠舌癌模型的芯片数据,分为舌癌组和非舌癌组,利用R语言的limma包分析筛选差异基因。利用DAVID和STRING数据库对差异表达基因进行基因本体论(GO)及京都基因与基因组百科全书(KEGG)基因功能分析、蛋白相互作用分析。结果:对差异基因筛选后,将两个数据集的数据取交集后最终得到303个基因,其中31个基因上调与细胞周期(Cell Cycle)和卵母细胞分裂有关,说明在肿瘤发生发展的过程中,通过上调这些基因促进肿瘤增殖。而其余基因的KEGG分析结果则表明这些基因与代谢过程密切相关。通过蛋白互作网络(PPI)筛选出cross-talk基因:整合素a1(Itga1)和整合素a6(Itga6)。结论:筛选出的差异基因可能在舌癌的分子层面发挥了重要的作用,为舌癌发生、发展的机制、肿瘤标志物的筛选等提供了理论依据。

Objective: To identify differentially expressed genes in tongue cancer of rats by bioinformatics analysis method and provide potential basis for drug targets and molecular biomarkers that were involved in the development of tongue cancer.Methods: The gene expression profile datasets GSE64271 and GSE75421,which included tongue cancer and normal tissues,respectively,were downloaded from Gene Expression Omnibus( GEO). The differentially expressed genes were screened by using R language limma package. Differential expression were analyzed by GO and KEGG pathway. The gene functions,genome pathways and protein-protein interaction were analyzed by DAVID and STRING database. Results: Total of 303 differentially expressed genes and 31 differentially express genes mainly involved in cell cycle and oocyte meiosis. Genes were located in the hubs of protein-protein interaction network by STRING database and cross-talk gene contains Itga1 and Itga6. Conclusion:Through the bioinformatics method,the present study may improve understanding the molecular mechanism,biological process and molecular function of tongue cancer. Furthermore,the present study may aid in the development of novel means of prevention,diagnosis and treatment of tongue cancer.