Identification of potentially critical differentially methylated genes in nasopharyngeal carcinoma: A comprehensive analysis of methylation profiling and gene expression profiling.

The present study aimed to identify potentially critical differentially methylated genes associated with the progression of nasopharyngeal carcinoma (NPC). Methylation profiling data of GSE62336 deposited in the Gene Expression Omnibus database were used to identify differentially methylated regions (DMRs) and differentially methylated CpG islands (DMIs). Concurrently, differentially expressed genes (DEGs) were identified using a meta-analysis of three gene expression datasets (GSE53819, GSE13597 and GSE12452). Subsequently, methylated DEGs were identified by comparing DMRs and DEGs. Furthermore, functional associations of these methylated DEGs were analyzed via constructing a functional network using GeneMANIA prediction server. In total, 1,676 hypermethylated genes, 28 hypomethylated genes, 17 DMIs and 2,983 DEGs (1,655 upregulated and 1,328 downregulated) were identified. Among these DEGs, 135 downregulated genes were hypermethylated; of these, dual specificity phosphatase 6 (DUSP6) and tenascin XB (TNXB) contained DMIs. In the functional network, 154 genes and 1,651 association pairs were included. DUSP6 was predicted to exhibit genetic interactions with other hypermethylated DEGs such as malic enzyme 3 and ST3 ß-galactoside α-2,3-sialyltransferase 5; TNXB was predicted to be co-expressed with a set of hypermethylated DEGs, including EPH receptor B6, aldehyde dehydrogenase 1 family, member L1 and glutathione peroxidase 3. The hypermethylated DEGs may be involved in the progression of NPC, and they may become novel therapeutic targets for NPC.

Identification of prognostic microRNA candidates for head and neck squamous cell carcinoma.

The aim of the present study was to uncover potential prognostic microRNA (miRNA) markers in head and neck squamous cell carcinoma (HNSCC). miRNA expression profile and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Survival analysis was conducted by Kaplan-Meier method. Then, candidate prognostic miRNAs were screened via Cox proportional hazards regression analysis. Furthermore, target genes of miRNAs were predicted, and their interactions and functions were then analyzed. A total of 15 miRNAs were discovered to be significantly related to overall survival. Among them, miR-1251, miR-618 and miR-328 with p<0.05 were potentially significant prognostic factors of HNSCC. In the protein-protein interaction (PPI) network, the target gene of miR-328, MAX, interacted with multiple genes. The target gene of miR-618, E2F1, interacted with genes such as MAX, SMAD3 and IGF1. Furthermore, the target genes of miR-618 (e.g. E2F1 and SMAD3), and the target genes of miR-328 (e.g. MAX) were significantly enriched in the functions of transcriptional regulation. The target gene of miR-1251, IGF1, was associated with functions such as signal transduction. The above miRNAs (miR-1251, miR-618 and miR-328) may be potential prognostic markers in HNSCC.

Identification of biomarkers with a tumor stage-dependent expression and exploration of the mechanism involved in laryngeal squamous cell carcinoma.

The aim of this study was to identify biomarkers with a tumor stage-dependent expression manner and explore the regulatory mechanisms of laryngeal squamous cell carcinoma (LSCC) progression. Microarray data GSE59102 was used for differential analysis using a limma package. Enrichment analyses were performed for the differentially expressed genes (DEGs) between tumor tissues and normal tissues at different stages. A co-expressed network involving the overlapped DEGs in two stages was established based on Pearson's correlation coefficients. Furthermore, for the tumor stage­dependent expressed DEGs, a protein­protein interaction (PPI) network was constructed by mapping the genes using the STRING database. Transcription factors (TFs), oncogenes and tumor­associated genes (TSGs) among the DEGs were predicted, following a search of the TRANSFAC, tumor-associated gene (TAG) and TSG databases. The CDT database was used to identify LSCC­associated genes. In total, 696 DEGs from early stage and control samples and 622 DEGs from advanced sttage and control samples were selected, which were mainly enriched in the cell cycle pathway. In the co-expressed network, BUB1, TTK, E2F1 and CEP55 were prominent, with E2F1 being predicted as a TSG and CEP55 as an oncogene. The HOX family members were predicted as TFs. MMP1, MMP9, MMP3 and PLAU were the most evident nodes in the PPI network, where MMP3 was connected with MMP1. The ADH family was correlated with LSCC. Several biomarkers with tumor stage-dependent expression were identified including MMP1, MMP3, MMP9, PLAU and ADHs. Additionally, the dysregulated cell cycle pathway involving BUB1, TTK, E2F1 and CEP55, and the mediation of MMP1 by MMP3 as well as the predicted TF HOX, may all play significant roles in LSCC progression.