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山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (10): 99-109.doi: 10.6040/j.issn.1671-7554.0.2022.0265

• 公共卫生与管理学 • 上一篇    下一篇

生物信息学方法分析与宫颈癌有关联的基因

修德健1,2,高正文3,宋婷婷4,崔楠5,崔静6,孙健平6   

  1. 1.青岛大学公共卫生学院, 山东 青岛 266000;2.青岛市崂山区疾病预防控制中心, 山东 青岛 266100;3.青岛城阳古镇正骨医院麻醉科, 山东 青岛 266000;4.青岛大学附属青岛市中心医院质控部, 山东 青岛 266000;5.青岛大学附属医院医院管理研究所, 山东 青岛 266000;6.青岛市疾病预防控制中心 青岛市预防医学研究院, 山东 青岛 266033
  • 发布日期:2022-09-30
  • 通讯作者: 孙健平. E-mail:qdcdcsjp@126.com崔静. E-mail:cuijing_0623@163.com
  • 基金资助:
    青岛糖尿病预防项目(WDF05-108,WDF07-308);青岛市科技局立项(19-6-1-5-nsh);青岛市2017年度医药科研指导计划(2017-WJZD129,2017-WJZD134);青岛市医疗卫生优秀人才培养项目

Genes associated with cervical cancer by integrated bioinformatics analysis

XIU Dejian1,2, GAO Zhengwen3, SONG Tingting4, CUI Nan5, CUI Jing6, SUN Jianping6   

  1. 1. School of Public Health, Qingdao University, Qingdao 266000, Shandong, China;
    2. Laoshan Municipal Center for Disease Control and Prevention, Qingdao 266100, Shandong, China;
    3. Anesthesiology Department, Guzhen Orthopedic Hospital of Chengyang, Qingdao 266000, Shandong, China;
    4. Quality Control Department, Affiliated Qingdao Central Hospital, Qingdao University, Qingdao 266000, Shandong, China;
    5. Hospital Management Institute, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China;
    6. Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Preventive Medicine, Qingdao 266033, Shandong, China
  • Published:2022-09-30

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摘要： 目的 通过TCGA和GEO数据库筛选与宫颈癌相关的关键基因,探讨其分子机制及临床意义。 方法 通过TCGA和GEO数据库获取宫颈癌的基因表达谱数据,采用加权基因共表达网络分析(WGCNA)获取宫颈癌与正常宫颈组织差异表达基因(DEGs),对DEGs进行富集分析、蛋白-蛋白互作网络(PPI)分析并识别关键基因,进一步对关键基因与预后及蛋白表达、以及与宫颈癌免疫浸润的关系进行分析。 结果 通过TCGA与GEO数据库中共得到88个宫颈癌DEGs,GO分析发现大部分基因与核染色体减速分裂、核染色体分裂、染色体集缩、核染色体等相关;KEGG信号通路分析发现宫颈癌DEGs参与了细胞周期、DNA复制、卵母细胞减数分裂、p53信号通路、同源重组等信号通路。鉴定出20个宫颈癌关键基因,仅有丝分裂阻滞缺陷2样蛋白1(MAD2L1)低表达患者的总生存期(OS)长于MAD2L1高表达患者(P=0.013),但MAD2L1高表达患者的无病生存期(DFS)与低表达患者差异无统计学意义(P>0.05),宫颈癌组织中MAD2L1蛋白高于正常组织。TIMER在线软件分析显示,MAD2L1与肿瘤的免疫浸润水平均相关(P<0.05)。 结论 发现了与宫颈癌相关的候选基因MAD2L1,其与宫颈癌患者的预后及免疫浸润均有关,可能成为宫颈癌预后预测及治疗的新靶点。

关键词: 宫颈癌, 差异表达基因, 加权基因共表达网络分析, 富集分析, 蛋白互作分析, 生物标志物

Abstract: Objective To identify the key genes associated with cervical cancer in TCGA and GEO databases, and to explore the molecular mechanism and clinical values. Methods Gene expression profiles of cervical cancer were obtained from TCGA and GEO databases. The differentially expressed genes(DEGs)of cervical cancer were screened with weighted gene co-expression network analysis(WGCNA). Enrich analysis and protein-protein interaction(PPI)network were performed and hub genes were identified. The associations between hub genes and prognosis, and immune cell infiltration were analyzed. Results A total of 88 DEGs were screened out. GO analysis showed that most DEGs were enriched in nuclear chromosome segregation, meiotic nuclear division, condensed chromosome and nuclear chromosome. KEGG pathway analysis showed that those DEGs were enriched in cell cycle, DNA replication, oocyte meiosis, p53 signaling pathway and homologous recombination. A total of 20 hub genes were identified. The lower expression of mitotic arrest deficient 2 like 1(MAD2L1)was associated with longer overall survival(OS)(P=0.013). The lower expression of MAD2L1 was not associated with disease-free survival(DFS)(P>0.05). The protein level of MAD2L1 was up-regulated in cervical cancer. TIMER analysis showed that the level of MAD2L1 was significantly associated with tumor-infiltrating immune cells(P<0.05). Conclusion The candidate gene MAD2L1 associated with cervical cancer was identified, which was associated with the prognosis and immune cell infiltration of patients with cervical cancer, and may become a new target for prognosis and treatment of cervical cancer.

Key words: Cervical cancer, Differentially expressed genes, Weighted gene co-expression network analysis, Enrichment analysis, Protein-protein interaction, Biomarkers

中图分类号: 

  • R737.3
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