基于生物信息学分析宫颈癌关键基因及预后相关生物标志物  

Bioinformatical analysis of the key genes and prognostic biomarkers in cervical cancer

作　　者：鲁伟[1] 姚轶敏 陈平[1] 陈婷婷[1] LU Wei;YAO Yi-min;CHEN Ping;CHEN Ting-ting(Department of Clinical Laboratory,The First Affiliated Hospital of Zhejiang Chinese Medical University,Hangzhou 310006,China)

机构地区：[1]浙江中医药大学附属第一医院医学检验科,杭州310006

出　　处：《浙江中西医结合杂志》2021年第12期1105-1110,共6页Zhejiang Journal of Integrated Traditional Chinese and Western Medicine

基　　金：浙江省基础公益研究计划项目(No.LGF18H160021);浙江医药卫生科技计划项目(No.2018PY035)。

摘　　要：目的从公共数据库筛选并探讨宫颈鳞状细胞癌的关键致病基因。方法从GEO数据库GSE122697、GSE89657里下载宫颈组织表达谱芯片数据。利用R软件和韦恩图查找数据集的差异表达基因(DEGs)交集,进行GO和KEGG通路富集分析。利用STRING数据库构建了DEGs的蛋白质-蛋白质相互作用网络(PPIs)并导入Cytoscape软件进一步分析,通过CytoHubba插件和MCC算法筛选出DEGs。利用癌症基因组图谱(TCGA)数据库对已初步筛选的DEGs进行验证及生存曲线分析,并进一步筛选与宫颈癌总生存率相关的DEGs进行ROC分析,获得关键基因。结果宫颈鳞状细胞癌差异基因56个,其中15个上调和41个下调。GO及KEGG分析结果显示,这些mRNA主要参与细胞核分裂、细胞外基质代谢调控等生物学进程;主要富集于细胞周期、减数分裂、PI3K-Akt信号通路、ECM受体相互作用通路等。通过PPI网络中筛选出18个核心基因,并在TCGA数据集中得以验证,生存曲线分析的结果表明18个差异基因中的ASF1B基因对宫颈癌患者生存预后具有显著影响[HR=0.437(0.272~0.704),P<0.01],ROC分析的结果表明其对宫颈癌患者具有很好的诊断价值(AUC=0.998)。结论本研究通过综合生物信息学分析,有望为宫颈癌诊断和预后提供可靠的分子生物标志物和治疗靶点。Objective To profile and identify the key pathogenic genes and biomarkers in cervical squamous cell carcinoma using the public database.Methods The microarray datasets of GSE122697 and GSE89657 with cervical tissue expression profiles were downloaded from the Gene Expression Omnibus(GEO database).The intersection of differentially expressed genes(DEGs)was identified using the R package and Wenn diagram,and further analyzed using the GO terms and KEGG pathway analyses.The protein-protein interaction(PPI)network of these DEGs was then constructed by using the string database and subsequently imported into the Cytoscape software for further analysis.These DEGs were screened using the CytoHubba plug-in and MCC algorithm.After that,the key DEGs were further validated using The Cancer Genome Atlas(TCGA)data.KM analysis was performed in TCGA data using the key DEGs to further isolate key genes associated with the overall survival of patients with cervical cancer.ROC analysis was performed to evaluate the performance of key genes.Results This study identified 56 DEGs(15 upregulated and 41 downregulated)in cervical squamous cell carcinoma.The GO and KEGG analyses showed that these DEGs were mainly involved in the biological processes,such as nuclear division and extracellular matrix metabolic regulation and mainly concentrated in the cell cycle,meiosis,PI3 K-Akt signaling pathway,and ECM receptor interaction pathway.The PPI network identified 18 core genes which were verified in TCGA dataset.Anti silencing function protein 1 B(ASF1 B)among these 18 DEGs had a significant impact on survival and prognosis of cervical cancer patients[HR,0.437(0.272-0.704);P<0.01].The results of ROC analysis showed that there was a good diagnostic value of ASF1 B for cervical cancer patients(AUC,0.998).Conclusion The comprehensive bioinformatic analysis could help to identify diagnostic and prognostic markers and therapeutic targets for cervical cancer patients.

关 键 词：宫颈鳞状细胞癌 生物信息学 抗沉默功能蛋白1B 

分 类 号：R737.33[医药卫生—肿瘤] Q811.4[医药卫生—临床医学]