Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

Identification of crucial miRNAs and genes in esophageal squamous cell carcinoma by miRNA-mRNA integrated analysis.

Xiaowu Zhong | Guangcheng Huang | Qiang Ma | Hebin Liao | Chang Liu | Wenjie Pu | Lei Xu | Yan Cai | Xiaolan Guo
Medicine | 2019

Esophageal squamous cell carcinoma (ESCC) is a malignancy that severely threatens human health and carries a high incidence rate and a low 5-year survival rate. MicroRNAs (miRNAs) are commonly accepted as a key regulatory function in human cancer, but the potential regulatory mechanisms of miRNA-mRNA related to ESCC remain poorly understood.The GSE55857, GSE43732, and GSE6188 miRNA microarray datasets and the gene expression microarray datasets GSE70409, GSE29001, and GSE20347 were downloaded from Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using GEO2R. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network and functional modules were established using the STRING database and were visualized by Cytoscape. Kaplan-Meier analysis was constructed based on The Cancer Genome Atlas (TCGA) database.In total, 26 DEMs and 280 DEGs that consisted of 96 upregulated and 184 downregulated genes were screened out. A functional enrichment analysis showed that the DEGs were mainly enriched in the ECM-receptor interaction and cytochrome P450 metabolic pathways. In addition, MMP9, PCNA, TOP2A, MMP1, AURKA, MCM2, IVL, CYP2E1, SPRR3, FOS, FLG, TGM1, and CYP2C9 were considered to be hub genes owing to high degrees in the PPI network. MiR-183-5p was with the highest connectivity target genes in hub genes. FOS was predicted to be a common target gene of the significant DEMs. Hsa-miR-9-3p, hsa-miR-34c-3p and FOS were related to patient prognosis and higher expression of the transcripts were associated with a poor OS in patients with ESCC.Our study revealed the miRNA-mediated hub genes regulatory network as a model for predicting the molecular mechanism of ESCC. This may provide novel insights for unraveling the pathogenesis of ESCC.

Pubmed ID: 31277149

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


DAVID (tool)

RRID:SCR_001881

Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

View all literature mentions

Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

View all literature mentions

STRING (tool)

RRID:SCR_005223

Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)

View all literature mentions

TargetScan (tool)

RRID:SCR_010845

Web tool to predict biological targets of miRNAs by searching for presence of conserved 8mer, 7mer and 6mer sites that match seed region of each miRNA. Nonconserved sites are also predicted and sites with mismatches in seed region that are compensated by conserved 3' pairing. Used to search for predicted microRNA targets in mammals.

View all literature mentions

KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

View all literature mentions