腺样囊性癌关键基因表达的生物信息学分析

doi:10.6040/j.issn.1673-3770.0.2022.278

摘要/Abstract

摘要： 目的研究使用生物信息学的方法来获得腺样囊性癌(adenoid cystic carcinoma, ACC)相关的关键基因,探寻其病因和发病机制。方法通过GEO数据库中GSE36820和GSE88804数据集获取腺样囊性癌的基因表达谱,筛选出腺样囊性癌组织与正常涎膜组织共同差异表达基因(DEGs),对DEGs进行基因本体论(GO)分析、京都基因与基因组百科全书(KEGG)信号通路分析,并通过String在线软件和Cytoscape软件构建DEGs蛋白互作网络,经cytoHubba获得关键基因,在GSE59702数据集对关键基因表达进行验证。结果 GO分析在生物过程中包括多细胞生物的体内平衡、抗菌体液反应、视网膜内稳态;KEGG通路富集于唾液分泌、PPAR信号通路和酪氨酸代谢;GSEA分析基因在细胞循环有丝分裂、TP53介导的转录调节、Rho家族的鸟苷三磷酸酶介导的信号、肿瘤通路和M期富集。在PPI网络筛选出前10个关键基因,对关键基因表达验证显示,DTL、CENPU、BUB1B、ANLN、CENPF、TOP2A的mRNA表达水平在肿瘤组织中显著升高,而CDK1、NUSAP1、CCNB2和KIF11的mRNA表达无统计学意义。结论本研究中发现的关键基因可能参与ACC的发病机制,为获得新的诊断方法和治疗手段提供研究方向。

关键词: 基因, 腺样囊性癌, 生物信息学, 基因表达谱, 生物指标

Abstract: Objective This paper used a bioinformatics approach to identify key genes associated with adenoid cystic carcinoma(ACC)to explore the etiology and pathogenesis. Methods The microarray datasets GSE36820 and GSE88804 were obtained from the Gene Expression Omnibus database(GEO). Common differentially expressed genes(DEGs)between ACC and normal tissues were identified. Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). A protein-protein interaction(PPI)network incorporating the discovered DEGs was constructed using String online software and Cytoscape software. Key genes were obtained by cytoHubba of Cytoscape. The mRNA level expression of key genes was validated using the GSE59702 dataset. Results GO analysis revealed that the DEGs were enriched in biological processes including multicellular organismal homeostasis, antimicrobial humoral response, and retina homeostasis. KEGG pathway analysis indicated that the DEGs were enriched in salivary secretion, PPAR signaling, and tyrosine metabolism. GSEA enrichment analysis found genes that were enriched in cell cycle mitosis, TP53-mediated transcriptional regulation, Rho family guanosine triphosphatase mediated signaling, tumor pathways, and mitosis. The mRNA expression levels of DTL, CENPU, BUB1B, ANLN, CENPF and TOP2A were significantly increased in tumor tissues. Conclusion The key candidate genes identified in the present study may be involved in ACC growth and pathogenesis, and offer new research directions in the quest for therapeutic targets and diagnostic markers.

Key words: Genes, Adenoid cystic carcinoma, Bioinformatics, Gene expression profiles, Biomarkers

中图分类号:

R739.6

郝红,陈钢,王林娥. 腺样囊性癌关键基因表达的生物信息学分析[J]. 山东大学耳鼻喉眼学报, 2023, 37(5): 99-106.

HAO Hong, CHEN Gang, WANG Lin’e. Key candidate genes associated with the molecular mechanisms of adenoid cystic carcinoma identified by bioinformatics[J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2023, 37(5): 99-106.

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