14 December 2017 : Laboratory Research
Identification of Key Genes and Pathways in Tongue Squamous Cell Carcinoma Using Bioinformatics Analysis
Huayong Zhang12BCE, Jianmin Liu3CDF, Xiaoyan Fu1DF, Ankui Yang1AEG*DOI: 10.12659/MSM.905035
Med Sci Monit 2017; 23:5924-5932
Abstract
BACKGROUND: Tongue squamous cell carcinoma (TSCC) is a major type of oral cancers and has remained an intractable cancer over the past decades. The aim of this study was to identify differentially expressed genes (DEGs) during TSCC and reveal their potential mechanisms.
MATERIAL AND METHODS: The gene expression profiles of GSE13601 were downloaded from the GEO database. The GSE13601 dataset contains 57 samples, including 31 tongue SCC samples and 26 matched normal mucosa samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; Cytoscape software was used for the protein-protein interaction (PPI) network and module analysis of the DEGs.
RESULTS: We identified a total of 1,050 upregulated DEGs (uDEGs) and 702 downregulated DEGs (dDEGs) of TSCC. The GO analysis results showed that uDEGs were significantly enriched in the following biological processes (BP): signal transduction, positive or negative regulation of cell proliferation, and negative regulation of cell proliferation. The dDEGs were significantly enriched in the following biological processes: signal transduction, cell adhesion, and apoptotic process. The KEGG pathway analysis showed that uDEGs were enriched in metabolic pathways, pathways in cancer, and PI3K-Akt signaling pathway, while the dDEGs were enriched in focal adhesion and ECM-receptor interaction. The top centrality hub genes RAC1, APP, EGFR, KNG1, AGT, and HRAS were identified from the PPI network. Module analysis revealed that TSCC was associated with significant pathways, including neuroactive ligand-receptor interaction, calcium signaling pathway, and chemokine signaling pathway.
CONCLUSIONS: The present study identified key genes and signal pathways, which deepen our understanding of the molecular mechanisms of carcinogenesis and development of the disease, and might be used as diagnostic and therapeutic molecular biomarkers for TSCC.
Keywords: Computational Biology, Tongue Neoplasms
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