中国口腔颌面外科杂志 ›› 2024, Vol. 22 ›› Issue (2): 128-136.doi: 10.19438/j.cjoms.2024.02.003

• 论著 • 上一篇    下一篇

整合WGNCA和PPI网络鉴定口腔鳞状细胞癌的关键基因

李锦存1, 翟堃1, 胡晨1, 刘絮影1, 马兴平2, 马坚1,3   

  1. 1.宁夏医科大学口腔医学院,宁夏 银川 750004;
    2.吴忠同心县人民医院,宁夏 吴忠 751300;
    3.宁夏医科大学口腔医学院颅颌面畸形重点实验室,宁夏 银川 750001
  • 收稿日期:2023-08-08 修回日期:2023-11-03 发布日期:2024-03-27
  • 通讯作者: 马坚,E-mail: majianhs310@163.com
  • 作者简介:李锦存(1995-),男,在读硕士研究生,住院医师,E-mail: 1443216409@qq.com
  • 基金资助:
    宁夏自然科学基金(2020AAC03413、2021AAC03377、2021AAC03357、2022AAC03473); 宁夏医科大学口腔医学院一流学科二期建设项目(0019110104)

Integration of WGNCA and PPI networks to identify key genes for oral squamous cell carcinoma

LI Jin-cun1, ZHAI Kun1, HU Chen1, LIU Xu-ying1, MA Xing-ping2, MA Jian1,3   

  1. 1. School of Stomatology, Ningxia Medical University. Yinchuan750004;
    2. Tongxin County People's Hospital of Wuzhong City. Wuzhong751300;
    3. Key Laboratory of Craniomaxillofacial Deformities, School of Stomatology, Ningxia Medical University. Yinchuan750001, Ningxia Province, China
  • Received:2023-08-08 Revised:2023-11-03 Published:2024-03-27

摘要: 目的: 应用生物信息技术筛查与口腔鳞状细胞癌(OSCC)相关的重要生物标志物。方法:从GEO数据库获取OSCC基因表达谱,鉴定出差异表达基因(DEGs)。利用加权基因共表达网络分析(WGCNA)获得与OSCC关系最密切模块中的核心基因并与DEGs取交集。对重叠DEGs进行通路分析及蛋白网络分析(PPI),以CytoHubba提取候选关键基因,通过生存分析确定关键基因,验证其在OSCC中的表达,进一步探索关键基因在OSCC中与免疫浸润细胞、免疫检查点之间的关系。采用GraphPad Prism 8软件进行统计学分析。结果: 共鉴定出53个共DEGs,富集分析其主要参与细胞外基质、细胞外区域、PI3K-Akt等通路。从PPI网络中鉴定20个候选核心基因,通过生存分析确定5个(SERPINE1、SERPINH1、LAMC2、ITGA5和ITGA3)与OSCC总生存期相关的基因作为关键基因(P<0.05)。通过GEPIA、GSE30784数据从基因水平证明这5个基因在OSCC组织中存在差异表达(P<0.05),通过HPA数据库发现SERPINE1在OSCC的蛋白水平上不表达,SERPINH1、LAMC2、ITGA5和ITGA3高表达。另外,5个关键基因与CD8+T细胞、树突状细胞等免疫浸润细胞和CD276、VEGFA、PDCD1等免疫检查点明显相关(P<0.05)。结论: SERPINE1、SERPINH1、LAMC2、ITGA5、ITGA3可视为OSCC的生物标志物,其为OSCC的诊断、预后及治疗提供了新的视野。

关键词: 加权基因共表达网络分析, 口腔鳞状细胞癌, 生存分析, 关键基因, 免疫浸润

Abstract: PURPOSE: To screen important biomarkers associated with oral squamous cell carcinoma (OSCC) by using bioinformation technology. METHODS: The gene expression profiles of OSCC were obtained from GEO database and differentially expressed genes (DEGs) extracted. WGCNA was used to obtain the core genes in the module with the most significant relationship with OSCC and intersected with DEGs. At the same time, pathway analysis as well as protein network analysis(PPI) were performed. The CytoHubba was used to extract candidate key genes. Secondly, survival analysis was used to identify key genes, and verify expression in OSCC. Furthermore, the association between key genes and immune infiltrating cells and immune checkpoints was explored in OSCC. GraphPad Prism 8 software was used for data analysis. RESULTS: A total of 53 co-expressed DEGs were identified. Enrichment analysis revealed that these genes mainly involved in extracellular matrix, extracellular region, PI3K-Akt and other pathways. Twenty candidate core genes were identified from PPI networks, among which 5 key genes(SERPINE1, SERPINH1, LAMC2, ITGA5 and ITGA3) were identified using survival analysis. GEPIA and GSE30784 showed that these five genes had differential expression in OSCC tissues (P< 0.05). SERPINE1 was not expressed at the protein level of OSCC through HPA database, but SERPINH1, LAMC2, ITGA5 and ITGA3 were highly expressed. They significantly correlated with immune infiltration cells such as CD8+ T cells and dendritic cells and immune checkpoints such as CD276, VEGFA, and PDCD1(P< 0.05). CONCLUSIONS: SERPINE1, SERPINH1, LAMC2, ITGA5 and ITGA3 can be used as biomarkers of OSCC, providing new clues for the diagnosis, prognosis and treatment of OSCC.

Key words: Weighted gene co-expression network analysis, Oral squamous cell carcinoma, Survival analysis, Key genes, Immune infiltration

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