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目的 采用生物信息学方法筛选宫颈癌预后相关的差异表达基因(DEGs)及枢纽基因。方法 从GEO数据库获取GSE6791、GSE7803、GSE9750三个基因表达数据集(正常对照42例、宫颈癌74例)，经R 4.1.0软件SVA工具包批次校正后合并，以|log_2FC|≥1且P<0.01筛选DEGs，并通过维恩图取三数据集共有DEGs。利用DAVID进行GO和KEGG富集分析，借助STRING与Cytoscape构建蛋白-蛋白相互作用(PPI)网络并筛选枢纽基因。采用Kaplan-Meier plotter数据库(304例宫颈癌)及UALCAN(TCGA,305例宫颈癌)评估枢纽基因表达与总生存期(OS)及组间表达差异。结果 共获得294个共有DEGs(上调177个、下调117个)，主要富集于细胞周期、DNA复制、卵母细胞减数分裂及p53信号通路。PPI网络含254个节点、3 871条边(P<0.01)，筛选出MCM10、CDC20、AURKA、NCAPG、CDC45、CDK1、MELK、AR、CCND1、ESR1共10个枢纽基因；其中AR、CDK1、CDC45、AURKA与CC患者OS显著相关(P<0.05),CDK1、CDC45、AR高表达者OS更长(P<0.01),AURKA高表达者OS更短(P<0.05)。UALCAN验证显示宫颈癌组CDK1、CDC45、AURKA表达上调、AR表达下调(均P<0.01)。结论 AR、CDK1、CDC45、AURKA 4个枢纽基因与宫颈癌预后相关，可作为宫颈癌预后评估的潜在生物标志物及治疗靶点。
Abstract：Objective Bioinformatics methods were employed to screen for differentially expressed genes(DEGs) and hub genes associated with the prognosis of cervical cancer. Methods Three gene expression datasets(42 normal controls and 74 cervical cancer cases) from the GEO database, namely GSE6791, GSE7803, and GSE9750, were obtained. After batch correction using the SVA toolkit of R 4.1.0 software, they were merged. DEGs were selected based on |log2 FC| ≥ 1 and P < 0.01. The common DEGs among the three datasets were obtained through the Venn diagram. GO and KEGG enrichment analyses were performed using DAVID. Protein-protein interaction(PPI) networks were constructed with STRING and Cytoscape, and hub genes were screened. The expression of hub genes and the overall survival time(OS) as well as the expression differences between groups were evaluated using the Kaplan-Meier plotter database(304 cases of cervical cancer) and UALCAN(TCGA, 305 cases of cervical cancer). Results A total of 294 common differentially expressed genes(177 up-regulated and 117 down-regulated) were identified, mainly enriched in cell cycle, DNA replication, oocyte meiotic division and p53 signaling pathway. The PPI network contained 254 nodes and 3871 edges(P<0.01), and 10 hub genes including MCM10, CDC20, AURKA, NCAPG, CDC45, CDK1, MELK, AR, CCND1, and ESR1 were screened out. Among them, AR, CDK1, CDC45, and AURKA were significantly associated with OS in cervical cancer patients(P<0.05), and patients with high expression of CDK1, CDC45, and AR had longer OS(P<0.01), while patients with high expression of AURKA had shorter OS(P<0.05). UALCAN validation showed that the expression of CDK1, CDC45, and AURKA was upregulated and the expression of AR was downregulated in the cervical cancer group(all P<0.01). Conclusion The four pivotal genes, AR, CDK1, CDC45, and AURKA, are associated with the prognosis of cervical cancer and can serve as potential biomarkers and therapeutic targets for evaluating cervical cancer prognosis.
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基本信息:
中图分类号:R737.33
引用信息:
[1]欧阳慧玲,亢晶,郝杰,等.宫颈癌差异表达基因及枢纽基因的筛选与预后价值：一项生物信息学分析[J].临床肿瘤学杂志,2026,31(09):904-909.
基金信息:
陕西省科技厅重点研发计划（2023-YBSF-494）; 西安市卫生健康委员会一般科研项目（2023yb29）
2026-09-28
2026-09-28