Identification of genes associated with laryngeal squamous cell carcinoma samples based on bioinformatic analysis

• Published in: Molecular medicine reports Vol. 12; no. 3; pp. 3386 - 3392
• Main Authors: YANG, BO, BAO, XUELI
• Format: Journal Article
• Language: English
• Published: Greece D.A. Spandidos 01.09.2015; Spandidos Publications; Spandidos Publications UK Ltd
• Subjects: Adult; Aged; Algorithms; Cell cycle; Cell division; clustering analysis; Datasets; Deoxyribonucleic acid; differentially expressed genes; DNA; DNA methylation; Encyclopedias; Female; function enrichment; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene Ontology; Gene Regulatory Networks; Genes; Genomes; Head & neck cancer; Humans; interaction network; Investigations; Laryngeal cancer; Laryngeal Neoplasms - genetics; Laryngeal Neoplasms - metabolism; Laryngeal Neoplasms - pathology; laryngeal squamous cell carcinoma; Larynx; Lymphatic Metastasis; Male; Medical prognosis; Metabolism; Middle Aged; Neoplasms, Squamous Cell - genetics; Neoplasms, Squamous Cell - metabolism; Neoplasms, Squamous Cell - secondary; Ontology; Pathogenesis; Physiological aspects; Protein interaction; Proteins; Software; Squamous cell carcinoma; Transcriptome; China
• ISSN: 1791-2997; 1791-3004
• DOI: 10.3892/mmr.2015.3794

The present study aimed to investigate the differentially expressed genes (DEGs) between laryngeal squamous cell carcinoma (LSCC) samples and non-neoplastic laryngeal squamous cell samples, and the underlying biological mechanism. Gene expression profile data of GSE51985 and GSE10288 were obtained from the Gene Expression Omnibus database. The DEGs between the LSCC and normal samples were identified using the rowtest function in the genefilter package. Hierarchical clustering for DEGs was performed to confirm the distinction between the identified DEGs, and Gene Ontology term and pathway enrichment analyses were performed to determine the underlying function of the DEGs. In addition, protein-protein interaction networks were established to investigate the interactive mechanism of the DEGs. A total of 1,288 upregulated genes and 317 downregulated genes were identified between the LSCC samples and non-neoplastic LSC samples in the GSE51985 dataset, and five upregulated and 26 downregulated genes were identified in the samples from the GSE10288 dataset. The DEGs were clearly distinguished between the LSCC sample and the non-neoplastic LSCC sample by hierarchical clustering. The upregulated genes were predominantly involved in the cell cycle, cell division or focal adhesion, and the 295 upregulated genes formed 374 protein interaction pairs in interaction network analysis. The results revealed that the genes involved in the cell cycle, in cell division or in focal adhesion were associated with the development and progression of LSCC.