Journal of Otolaryngology and Ophthalmology of Shandong University ›› 2023, Vol. 37 ›› Issue (5): 99-106.doi: 10.6040/j.issn.1673-3770.0.2022.278

• Original Article • Previous Articles     Next Articles

Key candidate genes associated with the molecular mechanisms of adenoid cystic carcinoma identified by bioinformatics

HAO Hong1, CHEN Gang2, WANG Lin’e2   

  1. 1. Department of Otolaryngology, The 401 Hospital of the China Nuclear Industry, Beijing 102413, China2. Department of Otorhinolaryngology & Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
  • Published:2023-10-13

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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

CLC Number: 

  • R739.6
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