ArticleMolecular medicine reports2018
Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods.
Article in Molecular medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Amprenavir Mitigates Pepsin-Induced Transcriptomic Changes in Normal and Precancerous Esophageal Cells.International journal of molecular sciences · 2025Article
- Identification of hub genes and key pathways in arsenic-treated rice (Oryza sativa L.) based on 9 topological analysis methods of CytoHubba.Environmental health and preventive medicine · 2024Article
- Analysis of immune related gene expression profiles and immune cell components in patients with Barrett esophagus.Scientific reports · 2022Article
- Screening strategy for gastrointestinal and hepatopancreatobiliary cancers in cystic fibrosis.World journal of gastrointestinal oncology · 2021Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Barrett's esophagus (BE) is a premalignant lesion of esophageal adenocarcinoma. The aim of the present study was to investigate the possible mechanisms and biomarkers of BE. To identify the differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) in BE, the miRNA expression profile GSE20099 and the gene expression profiles GSE26886, GSE13083 and GSE34619 were obtained from the Gene Expression Omnibus (GEO) database. DEGs and DEmiRNAs were screened for using the GEO2R tool. Using DAVID, functional and pathway enrichment analysis was performed to explore the biological function of identified DEGs. The protein‑protein interaction (PPI) network was detected using STRING and constructed by Cytoscape software. Furthermore, targets of identified DEmiRNAs were predicted by the miRecords database, then integrated with the identified DEGs to obtain key genes involved in BE. In total, 311 DEGs were identified. These genes were significantly enriched in the pancreatic secretion, metabolic pathways and cytochrome P450 drug metabolism pathways. In the PPI network, 16 hub genes, including keratin 16, cystic fibrosis transmembrane conductance regulator, involucrin, protein kinase C α and cadherin 17 were identified. Following integration of the predicted target genes of DEmiRNAs with DEGs, three key BE genes were identified: PRKCA, CDH17 and epiregulin. In conclusion, a comprehensive bioinformatics analysis of identified DEGs and DEmiRNAs was performed to elucidate potential pathways and biomarkers involved in the development of BE.
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