生物信息学方法筛选与宫颈鳞癌预后相关的关键基因

Bioinformatics Screening of Key Genes Related to the Prognosis of Cervical Squamous Carcinoma

目的:运用加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)筛选与宫颈鳞癌(squamous carcinoma of the cervix,SCC)预后相关的关键基因。方法:从癌症基因组图谱(the cancer genome atlas,TCGA)和基因综合表达(gene expression omnibus,GEO)数据库中下载SCC转录组及临床数据。R语言分别筛选TCGA、GEO数据库中SCC相关的差异基因(differentially expressed genes,DEGs)和枢纽基因模块。DEGs与枢纽基因模块取交集找到差异共表达基因并进行通路富集分析。STRING数据库对共表达基因行蛋白互作分析并筛选与SCC相关的核心Hub基因行预后分析。免疫组织化学对预后相关Hub基因蛋白表达进行验证。结果:WGCNA示与SCC相关性较高的基因模块分别是TCGA的绿黄色模块(r=0.24,P<0.01)和GSE52903数据集中的青绿色模块(r=0.86,P<0.01)。分别从TCGA、GSE52903数据集中得到3066和934个DEGs。模块基因与DEGs取交集得到80个差异共表达基因。功能富集发现差异共表达基因主要与细胞核分裂、细胞器分裂、染色体分离相关。通路富集示主要与细胞周期、DNA复制、同源重组信号通路相关。蛋白互作网络筛选出与SCC最相关的20个Hub基因。预后分析发现SMC2基因低表达与患者的总体生存期和无病生存期缩短相关,差异有统计学意义(P<0.05)。免疫组织化学验证显示,SMC2基因在SCC组织中的蛋白表达低于NC组织。结论:通过生物信息分析发现了20个与SCC密切相关的Hub基因,其中SMC2在SCC组织中表达下调且与预后不良相关。SMC2可能作为SCC发病的风险基因和潜在治疗靶点。

Objective Weighted gene co-expression network analysis(WGCNA)was used to screen the key genes associated with the prognosis of squamous carcinoma of the cervix(SCC).Methods SCC transcriptome and clinical data were downloaded from the cancer genome atlas(TCGA)and gene expression omnibus(GEO)database.R language was used to screen SCC related differentially expressed genes(DEGs)and hub gene modules in TCGA and GEO databases respectively.The intersection of DEGs and hub gene modules was used to find differentially co-expressed genes and pathway enrichment analysis was performed.The STRING database was used to analyze the protein interaction of the co-expressed genes and screened the core Hub genes related to SCC for prognostic analysis.Immunohistochemistry was used to verify the protein expression of prognosis-related Hub gene.Results WGCNA showed that the green and yellow modules of TCGA(r=0.24,P<0.01)and the green and green modules of GSE52903 dataset were highly correlated with SCC(r=0.86,P<0.01).3066 and 934 DEGs were obtained from TCGA and GSE52903 datasets respectively.80 differentially co-expressed genes were obtained by intersection of modular genes with DEGs.Functional enrichment found that differentially co-expressed genes were mainly related to nuclear division,organelle division and chromosome separation.The enrichment of the pathway was mainly related to cell cycle,DNA replication and homologous recombination signal pathways.The protein interaction network screened 20 Hub genes most related to SCC.The prognosis analysis showed that the low expression of SMC2 gene was related to the shortened overall survival and disease-free survival(P<0.05).Immunohistochemical examination showed that the protein expression of SMC2 gene in SCC tissues was lower than that in NC tissues.Conclusion Through bioinformatics analysis,20 Hub genes closely related to SCC were found.Among them,SMC2 was downregulated in SCC tissues and was associated with poor prognosis.SMC2 may be a risk gene and a potential therapeutic target for SCC.