Functional analysis of the nasopharyngeal carcinoma primary tumor-associated gene interaction network

Abstract

The aim of the present study was to investigate the molecular mechanism of nasopharyngeal carcinoma (NPC) primary tumor development through the identification of key genes using bioinformatics approaches. Using the GSE53819 microarray dataset, acquired from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened out between NPC primary tumor and control samples, followed by hierarchical clustering analysis. The Search Tool for the Retrieval of Interacting Genes database was utilized to build a protein-protein interaction network to identify key node proteins. In total, 1,067 DEGs, including 326 upregulated genes and 741 downregulated genes, were identified between the NPC and control samples. The results of the hierarchical clustering analysis demonstrated that 95% of the DEGs were sample-specific. Furthermore, PDZ binding kinase (PBK), centromere protein F (CENPF), actin-binding protein anillin (ANLN), exonuclease 1 (EXO1) and chromosome 15 open reading frame 42 (C15ORF42) were included in the obtained network module, which was closely associated with the cell cycle and nucleic acid metabolic process GO functions. The results of the present study revealed that EXO1, CENPF, ANLN, PBK and C15ORF42 may be involved in the mechanism of NPC via modulating the cell cycle and nucleic acid metabolic processes, and may serve as molecular biomarkers for the diagnosis of this disease.

Bioinformatic identification of candidate biomarkers and related transcription factors in nasopharyngeal carcinoma

“…Chen’s research based on two gene expression profiles (GSE12452 and GSE13597) identified 179 upregulated and 238 downregulated DEGs, including 10 hub genes for which authors supposed to be useful for facilitating the early diagnosis and curative treatment of NPC [18]. Similar studies take out by An and colleagues applied GSE53819 microarray dataset for bioinformatic analysis and revealed that EXO1, CENPF, ANLN, PBK, and C15ORF42 may be involved in the mechanism of NPC via modulating the cell cycle and nucleic acid metabolic processes [19]. But in the present study, except for the dataset GSE12452, another dataset GSE64634 was also acquired for the identification of DEGs; 10 upregulated and 142 downregulated were identified based on these two datasets.…”

SOX9, miR-495, miR-590-3p, and miR-320d were identified as chemoradiotherapy-sensitive genes and miRNAs in colorectal cancer patients based on a microarray dataset

“…Genes that were up-regulated/down-regulated in tumor vs. normal tissues and simultaneously down-regulated/up-regulated in tumor-CRT vs. tumor-non-CRT samples were regarded as potential CRT-sensitive genes. Then, two-way hierarchical clustering analysis was applied for these CRT-sensitive genes using the heatmap package [17].…”

Novel Significant Stage-Specific Differentially Expressed Genes in Liver Hepatocellular Carcinoma

“…An independent analysis of TCGA RNA-Seq data encompassing 12 cancer tissues has uncovered liver cancer-specific genes (Peng et al, 2015). Zhang et al (2015) have performed mutation analysis of LIHC, and Yang et al (2017) combined TCGA expression data and natural language processing techniques to identify cancer-specific markers.…”