Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis

Biomedical Reports
Feng HeLei Tian

Abstract

Esophageal adenocarcinoma (EAC) is one of the most common subtypes of esophageal cancer, and is associated with a low 5-year survival rate. The present study aimed to identify key genes and pathways associated with EAC using bioinformatics analysis. The gene expression profiles of GSE92396, which includes 12 EAC samples and 9 normal esophageal samples, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the EAC and normal samples were identified using the limma package in R language. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the identified DEGs were conducted using the online analysis tool, the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. Finally, module analysis was conducted for the PPI network using the MCODE plug-in in Cytoscape. Of the 386 DEGs identified, the 150 upregulated genes were mainly enriched in the KEGG pathways of complement and coagulation cascades, maturity onset diabetes of the young and protein digestion and ab...Continue Reading

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Citations

Feb 23, 2020·Cells·Antonio PalumboLuiz Eurico Nasciutti
Aug 7, 2019·Cells·Anne-Sophie LamortGeorgios T Stathopoulos

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Software Mentioned

Search Tool for the Retrieval of Interacting Genes ( STRING
CentiScaPe
MCODE
R
gplots
limma
DAVID
Cytoscape

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