WGCNA共表达网络显示CDC45和MCM2与宫颈癌预后相关

摘要/Abstract

摘要： 目的使用加权基因共表达网络分析的方法研究宫颈癌细胞中相关基因表达状况及其与预后的相关性。方法从美国国家生物技术信息中心（NCBI）的Gene Expression Omnibus数据库中获得104例宫颈癌（CC）和24例正常样本的基因表达数据。通过加权基因共表达网络分析（WGCNA）构建共表达网络。将表达模式类似的基因汇总组成模块,筛选出与肿瘤相关性最强的模块以及显著表达差异的基因。对差异基因进行GO富集分析和KEGG富集分析,同时构建差异基因的PPI网络。进行生存分析,筛选出与宫颈癌预后及分级显著相关的基因,使用Oncomine在线数据库对该结果进行验证。结果共表达网络显示MEblack模块与组织癌变的关联性最显著。CDC45、MCM2、CDC6、CHEK1、CDT1、CDC7、MCM10、GMNN、BUB1B、MAD2L1等10个基因为核心基因。GEPIA2生存分析提示CDC4和MCM2与生存期显著相关,并得到Oncomine数据库验证。结论 CDC45和MCM2的表达量对宫颈癌病情发展状态判断以及预后状况的预测具有一定参考意义。

关键词: 宫颈癌, WGCNA, PPI网络, CDC45, MCM2

Abstract: Objective This study is to investigate the expression profile of related genes and its correlation with the prognosis of cervical cancer cells by using weighted gene co-expression network analysis. Methods The expression data of cervical cancer (CC) with accession number GSE63514 were obtained from gene expression omnibus database of National Center for Biotechnology Information (NCBI). The gene expression data of cervical squamous cell carcinoma and adenocarcinoma (Cesc) were downloaded from the Cancer Genome Atlas (TCGA) database for verification. A total of 104 tumor samples and 24 normal samples were screened from GSE63514 dataset. Co-expression network of the differentially expressed mRNA was constructed by weighted gene co expression network analysis (WGCNA) using these 128 samples. Genes with similar expression patterns were aggregated into the same module and the most relevant module was selected. Then, genes with significant expression differences in tumor tissues were identified and Go enrichment analysis and KEGG enrichment analysis were performed with genes that were obtained. Additionally, protein-protein interaction (PPI) network of these differentially expressed genes was constructed and 10 hub genes were screened out. Survival analysis was carried out to identify genes that are significantly related to the prognosis and grading of cervical cancer. Finally, the online database of Oncomine is used to verify the results. Results MEblack module had the most significant correlation with tissue carcinogenesis. Then 10 core genes, namely CDC45, MCM2, CDC6, CHEK1, CDT1, CDC7, MCM10, GMNN, BUB1B and MAD2L1 were screened out. Survival analysis of these 10 core genes by gepia2 showed that CDC4 and MCM2 genes were significantly associated with survival, which was validated by Oncomine database. Conclusion The expression of CDC45 and MCM2 has certain reference significance for judging the disease development and predicting the prognosis of cervical cancer.

Key words: cervical cancer, WGCNA, PPI network, CDC45, MCM2

中图分类号:

R737.33

李昊晨, 耿静, 张子威, 李素婷. WGCNA共表达网络显示CDC45和MCM2与宫颈癌预后相关[J]. 承德医学院学报, 2022, 39(4): 277-283.

LI Hao-chen, GENG Jing, ZHANG Zi-wei, LI Su-ting. WGCNA Co-expression Network Showed Highly Correlation Between CDC45 and MCM2 with the Prognosis of Cervical Cancer[J]. Journal of Chengde Medical University, 2022, 39(4): 277-283.

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