基于生物信息学分析鉴定促进非小细胞肺癌耐药的关键基因

Identification of key genes promoting drug resistance of non-small cell lung cancer based on bioinformatics analysis

目的通过生物信息学分析基因表达综合数据库(GEO数据库)中吉非替尼敏感和耐药非小细胞肺癌(NSCLC)细胞的基因表达谱,研究导致NSCLC获得性耐药的潜在关键基因,为耐药NSCLC患者的预后评价提供新思路。方法通过GEO2R网络工具分析GSE123066和GSE83666数据集识别差异表达基因(DEGs)。通过韦恩图比较2组数据之间的DEGs找出关键的候选基因,然后对候选基因进行基因本体(GO)分析、京都基因与基因组百科全书(KEGG)分析及蛋白质-蛋白质相互作用(PPI)分析,并对所得到的基因进行临床预后分析、肿瘤组织及不同分期中的表达水平进行分析。结果筛选到46个核心DEGs与NSCLC耐药显著相关,通过Cytoscape确定8个关键基因在NSCLC细胞的吉非替尼耐药进展中起重要作用,分别是SOD2、GADD45A、NCF2、LOX、CYR61、SOX2、JUP和MUC1,最后生存分析发现SOD2与NSCLC吉非替尼耐药高度相关。结论SOD2可能是导致NSCLC细胞对吉非替尼获得性耐药的关键基因,其高表达与NSCLC不良预后相关,表明SOD2可能是未来具有临床应用价值的潜在治疗靶点。

Objective To analyze the gene expression profiles of gefitinib-sensitive and drug-resistant non-small cell lung cancer(NSCLC)cells in GEO database by bioinformatics,to study the potential key genes leading to acquired drug resistance of NSCLC,and to provide new ideas for the prognosis evaluation of patients with drug-resistant NSCLC.Methods The GEO2R network tool was used to analyze the GSE123066 and GSE83666 data sets to identify differentially expressed genes(DEGs).The key candidate genes were identified by comparing the DEGs between the two groups of data through the Wayne diagram,and then GO analysis,KEGG analysis and protein-protein interaction(PPI)analysis were performed on the candidate genes.The clinical prognosis analysis and expression level analysis of tumor tissues and different stages were performed on the obtained genes.Results A total of 46 core DEGs were significantly associated with drug-resistant NSCLC.Cytoscape identified eight key genes that play an important role in the progression of gefitinib resistance in NSCLC cells,namely SOD2,GADD45A,NCF2,LOX,CYR61,SOX2,JUP and MUC1,respectively.Among them,SOD2 was highly correlated with gefitinib resistance in NSCLC.Conclusion SOD2 may be the key genes leading to acquired drug resistance of NSCLC cells to gefitinib,and their high expression is associated with poor prognosis of NSCLC,indicating that SOD2 may be potential therapeutic targets with clinical application value in the future.