Dataset Information

Identification and verification of differentially expressed microRNAs and their target genes for the diagnosis of esophageal cancer.

ABSTRACT: Bioinformatic tools were used to analyze GSE6188, GSE13937 and GSE43732 microarrays, and the top 10 upregulated and downregulated genes of each microarray were identified. It was determined that human microRNA (hsa-miR)-1 and hsa-miR-203 were two downregulated genes in common. Subsequently, it was identified that there were 145 and 335 genes in common targeted by hsa-miR-1 and hsa-miR-203, respectively. In order to narrow the number of target genes down further, the target genes were compared with GSE26886 microarray data. There were five upregulated genes in common with hsa-miR-1, i.e., MMD, BICD1, PTPRG, SDC2 and SEMA6D, and there were eight upregulated genes in common with hsa-miR-203, i.e., PXDN, NRCAM, FMNL2, EIF5A2, GLI3, FSL1, GREM1 and AHR. These genes may become promising biomarkers for the diagnosis of esophageal cancer.

SUBMITTER: Cai X

PROVIDER: S-EPMC6096065 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification and verification of differentially expressed microRNAs and their target genes for the diagnosis of esophageal cancer.

Cai Xiaoyue X Yang Xiwen X Jin Changjuan C Li Lei L Cui Qing Q Guo Yijun Y Dong Yun Y Yang Xiaohua X Guo Lili L Zhang Ming M

Oncology letters 20180704 3

Bioinformatic tools were used to analyze GSE6188, GSE13937 and GSE43732 microarrays, and the top 10 upregulated and downregulated genes of each microarray were identified. It was determined that human microRNA (hsa-miR)-1 and hsa-miR-203 were two downregulated genes in common. Subsequently, it was identified that there were 145 and 335 genes in common targeted by hsa-miR-1 and hsa-miR-203, respectively. In order to narrow the number of target genes down further, the target genes were compared wi ...[more]

PMID: 30127973

Similar Datasets

Project description:Aberrant methylated genes (DMGs) play an important role in the etiology and pathogenesis of esophageal squamous cell carcinoma (ESCC). In this study, we aimed to integrate three cohorts profile datasets to ascertain aberrant methylated-differentially expressed genes and pathways associated with ESCC by comprehensive bioinformatics analysis. We downloaded data of gene expression microarrays (GSE20347, GSE38129) and gene methylation microarrays (GSE52826) from the Gene Expression Omnibus (GEO) database. Aberrantly differentially expressed genes (DEGs) were obtained by GEO2R tool. The David database was then used to perform Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses on selected genes. STRING and Cytoscape software were used to construct a protein-protein interaction (PPI) network, then the modules in the PPI networks were analyzed with MCODE and the hub genes chose from the PPI networks were verified by Oncomine and TCGA database. In total, 291 hypomethylation-high expression genes and 168 hypermethylation-low expression genes were identified at the screening step, and finally found six mostly changed hub genes including KIF14, CDK1, AURKA, LCN2, TGM1, and DSG1. Pathway analysis indicated that aberrantly methylated DEGs mainly associated with the P13K-AKT signaling, cAMP signaling and cell cycle process. After validation in multiple databases, most hub genes remained significant. Patients with high expression of AURKA were associated with shorter overall survival. To summarize, we have identified six feasible aberrant methylated-differentially expressed genes and pathways in ESCC by bioinformatics analysis, potentially providing valuable information for the molecular mechanisms of ESCC. Our data combined the analysis of gene expression profiling microarrays and gene methylation profiling microarrays, simultaneously, and in this way, it can shed a light for screening and diagnosis of ESCC in future.

Dataset Information

Identification and verification of differentially expressed microRNAs and their target genes for the diagnosis of esophageal cancer.

Publications

Identification and verification of differentially expressed microRNAs and their target genes for the diagnosis of esophageal cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets