Screening and identification of potential target genes in head and neck cancer using bioinformatics analysis

Head and neck cancer (HNC) is the sixth most common cancer worldwide. Recent studies on the pathogenesis of HNC have identified some biochemical associations of this disease, but the molecular mechanisms are not clear. To explore the genetic alterations in head and neck tumors, to identify new high-specificity and high-sensitivity tumor markers, and to investigate potentially effective therapeutic targets, in silico methods were used to study HNC. The GSE58911 microarray dataset was downloaded from the Gene Expression Omnibus online database to identify potential target genes in the carcinogenesis and progression of HNC. Differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. In addition, a protein-protein interaction network was also constructed, and gene analysis was undertaken using Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 648 differentially expressed genes were identified. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology functional enrichment analysis of DEGs included muscle system process, extracellular matrix organization, actin binding, structural molecule activity, structural constituent of muscle, extracellular region part, ECM-receptor interaction, amoebiasis, focal adhesion, drug metabolism-cytochrome P450, and chemical carcinogenesis. There were 26 hub genes identified and biological process analysis revealed that these genes were mainly enriched in extracellular matrix organization, serine-type endopeptidase activity, extracellular matrix, and complement and coagulation cascades. Survival analysis revealed that interleukin (IL)-8 (C-X-C motif chemokine ligand 8), IL1B, and serpin family A member 1 may be involved in the carcinogenesis of HNC. In summary, the DEGs and hub genes identified in the present study may increase understanding of the molecular mechanisms of development of HNC and provide potential target genes for clinical diagnosis and targeted therapy.