肺腺癌关键基因及潜在药物的生物信息学分析

Bioinformatics analysis of hub genes and potential drugs in lung adenocarcinoma

目的基于生物信息学筛选肺腺癌预后基因, 探讨预后基因与免疫治疗反应性的关系, 同时筛选其潜在药物。方法在基因表达谱(GEO)数据库用GEO2R对GSE30219、GSE31210、GSE32863、GSE33532、GSE40791和GSE75037数据集进行差异表达分析, 取P<0.05且Log2(fold change)≥1的基因, 用在线网站取交集得共同上调基因。在GSE31210、GSE42127、GSE68465、GSE72094数据集和癌症基因图谱计划(TCGA)数据库中获取生存资料, 用R软件对上调基因行单因素COX回归分析, 得到7个预后关键基因。通过基因表达谱交互分析(GEPIA2)网站验证基因表达与预后的关系。使用人类蛋白图集(HPA)在线工具验证关键基因的蛋白表达水平。京东基因组百科全书(KEGG)和基因本体论(GO)进行基因功能富集分析。使用仙桃学术分析关键基因与免疫治疗反应的相关性。最后通过CellMiner数据库筛选关键基因的敏感性药物。两组间的比较通过Student’st检验评估。结果共获得142个共同上调基因, 经单因素COX回归分析和GEPIA2网站验证得到7个预后关键基因, 即细胞周期蛋白B2(CCNB2)、细胞分裂周期蛋白20(CDC20)、瓣状核酸内切酶1(FEN1)、鸟嘌呤核苷酸交换因子(GEF)上皮细胞转化序列2(ECT2)、微小染色体维持蛋白4(MCM4)、母胚亮氨酸拉链激酶(MELK)和溶质载体家族2成员1(SLC2A1)。通过GO和KEGG功能富集分析, 关键基因生物学功能主要富集在作用于DNA的催化活性方面, 以及在细胞周期、人类T细胞白血病病毒1感染等信号通路上。此外, 免疫相关性分析显示7个关键基因与肿瘤突变负荷(TMB)、表面抗原分化簇274(CD274)表达以及肿瘤免疫功能障碍和排斥评分(TIDE)明显相关。最后, 7个关键基因得到37个对应的敏感性药物。结论 CCNB2、CDC20、FEN1、ECT2、MCM4、MELK和SLC2A1可以作为肺腺癌预后不良标志物, 且可能与免疫治疗低反应性相关, 同时得到37个对应的敏感性药物。

Objective To screen hub genes related to the prognosis of lung adenocarcinoma based on bioinformatics analysis and discuss the relationship between the hub genes and immunotherapeutic response,and to identify potential drugs.Methods The GEO2R was utilized to analyze GSE30219,GSE31210,GSE32863,GSE33532,GSE40791 and GSE75037 datasets in Gene Expression Omnibus database(GEO)for obtaining overlapping upregulated genes.A total of 142 common upregulated genes were obtained.The GSE31210,GSE42127,GSE68465,GSE72094 datasets and The Cancer Genome Atlas(TCGA)database were used to acquire survival data.The above genes were analyzed by univariate Cox regression analysis using R software and 7 prognostic hub genes were obtained.The Gene Expression Profiling Interactive Analysis version 2(GEPIA2)website was used to analyze the relationship between gene expression and prognosis.The Human Protein Atlas(HPA)online website was used to validate protein expression levels of 7 hub genes.The Kyoto Encyclopedia of genes and genomes(KEGG)and Gene Ontology(GO)were used for functional enrichment analysis.The Xiantao Academy was used to analyze the correlation between hub genes and immunotherapy response.Finally,the CellMiner database was utilized to screen sensitive drugs of hub genes.The comparison between the two groups was evaluated by Student’s t test.Results A total of 142 common upregulated genes were obtained,and 7 hub genes related to prognosis were identified by univariate COX regression analysis and validated on GEPIA2 website,comprising cyclin B2(CCNB2),cell division cycle 20(CDC20),flap endonuclease 1(FEN1),guanine nucleotide exchange factor(GEF)epithelial transformation sequence 2(ECT2),minichromosome maintenance protein 4(MCM4),maternal embryonic leucine zipper kinase(MELK)and solute carrier family 2 member 1(SLC2A1).Through GO and KEGG enrichment analysis,7 hub genes were mainly enriched in functions such as catalytic activity acing on DNA,and signaling pathways like cell cycle and human T-cell leukemia virus 1 infection.In addition,immuno-correlation analysis showed that 7 hub genes were significantly associated with tumor mutation burden(TMB),cluster of differentiation 274(CD274)expression and T cell dysfunction and exclusion(TIDE).Meanwhile,37 sensitive drugs were yielded according to 7 hub genes.Conclusion High expression of CCNB2,CDC20,FEN1,ECT2,MCM4,MELK and SLC2A1 can be used as markers of poor prognosis of lung adenocarcinoma,which might be associated with low response to immunotherapy and acquired 37 corresponding sensitive drugs.