基于网络拓扑分析识别非小细胞肺癌的关键基因  

Identification of essential genes of non-small cell lung cancer based on topology network analysis

作　　者：葛泳 吴泽童 程桉桉 杨文武 张洁 肖剑虹 陈丹丹 李红东 GE Yong;WU Ze-tong;CHENG An-an;YANG Wen-wu;ZHANG Jie;XIAO Jian-hong;CHEN Dan-dan;LI Hong-dong(School of Medical Information Engineering of Gannan Medical University,Ganzhou,Jiangxi 341000)

机构地区：[1]赣南医科大学医学信息工程学院,江西赣州341000

出　　处：《赣南医科大学学报》2024年第9期873-879,共7页JOURNAL OF GANNAN MEDICAL UNIVERSITY

基　　金：赣南医学院校级课题(ZR2213)。

摘　　要：目的:通过分析非小细胞肺癌(Non-small cell lung cancer,NSCLC)的差异基因蛋白质互作网络和加权基因共表达网络,挖掘NSCLC潜在的生物标志物。方法:从公共数据库收集3套NSCLC的表达谱数据集为研究对象,首先利用NSCLC中发生差异表达的基因构建蛋白质-蛋白质互作网络,并根据网络的拓扑结构挖掘网络中的关键基因。再通过构建NSCLC加权基因共表达网络对关键基因进一步验证。最后,利用Logistic回归、功能富集、生存分析等方法评估关键基因作为NSCLC生物标志物的潜力。结果:在3套独立的NSCLC数据集中,通过差异基因蛋白互作网络和加权基因共表达网络的筛选,共得到6个与NSCLC相关的关键基因,分别为CDK1、CCNA2、CDC20、TOP2A、KIF11和BUB1B。Logistic回归分析表明,这些关键基因具有良好的NSCLC预测潜能,其在3套数据集中的平均AUC为0.945(范围为0.895~1)。利用KM-Plotter在线生存分析网站进行分析,发现这6个关键基因的表达水平均与NSCLC患者的预后显著相关。功能富集分析结果显示,这些基因主要在细胞周期、细胞衰老等癌症相关的生物学通路中富集。结论:基因CDK1、CCNA2、CDC20、TOP2A、KIF11、BUB1B与NSCLC发生发展密切相关,可能是其潜在的生物标志物。Objective:To explore potential biomarkers for non-small cell lung cancer(NSCLC)by analyzing the differential genes protein-protein interaction network and weighted gene co-expression network of NSCLC.Methods:Three sets of NSCLC expression profiles were collected from public databases as the research subjects.Firstly,the protein-protein interaction network was constructed using genes that had exhibited differential expression in NSCLC,and essential genes were identified based on the topological structures of the network.Subsequently,the essential genes were further validated using the NSCLC weighted gene co-expression network analysis.Finally,Logistic regression,functional enrichment,survival analysis and other methods were employed to evaluate the potential of essential genes as NSCLC biomarkers.Results:In three independent NSCLC datasets,a screening using differential genes protein-protein interaction networks and weighted gene co-expression networks identified six essential genes associated with NSCLC:CDK1,CCNA2,CDC20,TOP2A,KIF11,and BUB1B.The Logistic regression analysis indicated that these essential genes had significant predictive potential for NSCLC,with an average AUC of 0.945(range:0.895-1)across the three datasets.By performing analysis using the KM-Plotter online survival analysis website,it was found that the expression levels of these six essential genes were all significantly associated with the prognosis of NSCLC patients.Functional enrichment analysis results showed that these genes mainly enriched in cancer-related biological pathways in cell cycle,cellular senescence,etc.Conclusion:Genes CDK1,CCNA2,CDC20,TOP2A,KIF11,and BUB1B are closely associated with the occurrence and development of NSCLC and may serve as potential biomarkers for NSCLC.

关 键 词：癌 非小细胞肺 蛋白质互作网络 加权共表达网络 功能富集 生存分析 

分 类 号：R730.49[医药卫生—肿瘤]