| 鲁伟,姚轶敏,陈平,陈婷婷.基于生物信息学分析宫颈癌关键基因及预后相关的生物标志物[J].浙江中西医结合杂志,2021,31(12): |
| 基于生物信息学分析宫颈癌关键基因及预后相关的生物标志物 |
| Analysis of key genes and prognostic biomarkers of cervical cancer based on Bioinformatics |
| 投稿时间：2021-08-11 修订日期：2021-11-17 |
| DOI： |
| 中文关键词: 宫颈鳞状细胞癌 生物信息学 抗沉默功能蛋白1B |
| 英文关键词:cervical squamous cell carcinoma bioinformatics anti silencing function protein 1B |
| 基金项目:浙江省基础公益研究计划项目(LGF18H160021)；浙江医药卫生科技计划项目(2018PY035) |
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| 中文摘要: |
| 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数据(TCGA)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、PIK-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。 |
| 英文摘要: |
| Objective To screen and explore the key pathogenic genes of cervical squamous cell carcinoma from the public database. Methods Download the microarray data of cervical tissue expression profile from GEO database GSE122697 and GSE89657. The intersection of differentially expressed genes (DEGs) in the data set was found by R software and Wenn diagram, and the enrichment analysis of go and KEGG pathways was carried out. The protein-protein interaction network (PPIs) of DEGs was constructed by using string database and imported into Cytoscape software for further analysis. DEGs were screened by cytohubba plug-in and MCC algorithm. Using Cancer Genome Atlas data (TCGA) to verify and analyze the survival curve of the preliminarily screened DEGs, and further screen the DEGs related to the overall survival rate of cervical cancer for ROC analysis to obtain the key genes. Results There were 56 DEGs in cervical squamous cell carcinoma, of which 15 were up-regulated and 41 were down regulated. Go and KEGG analysis showed that these mRNAs were mainly involved in biological processes such as nuclear division and extracellular matrix metabolic regulation; It is mainly concentrated in cell cycle, meiosis, Pik Akt signaling pathway, ECM receptor interaction pathway and so on. 18 core genes were screened from PPI network and verified in TCGA data set. The results of survival curve analysis showed that ASF1B gene among the 18 DEGs has a significant impact on the survival and prognosis of cervical cancer patients (HR = 0.437 (0.272-0.704), P < 0.01). The results of ROC analysis show that it has a good diagnostic value for cervical cancer patients (AUC = 0.998). Conclusion Through comprehensive bioinformatics analysis, this study is expected to provide reliable molecular biomarkers and therapeutic targets for the diagnosis and prognosis of cervical cancer. |
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