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Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods

  • Authors:
    • Cong Zhang
    • Yujie Shen
    • Jiazheng Wang
    • Mingxia Zhou
    • Yingwei Chen
  • View Affiliations / Copyright

    Affiliations: Department of Gastroenterology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, P.R. China
    Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 3069-3077
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    Published online on: December 12, 2017
       https://doi.org/10.3892/mmr.2017.8274
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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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Copy and paste a formatted citation
Spandidos Publications style
Zhang C, Shen Y, Wang J, Zhou M and Chen Y: Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods. Mol Med Rep 17: 3069-3077, 2018.
APA
Zhang, C., Shen, Y., Wang, J., Zhou, M., & Chen, Y. (2018). Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods. Molecular Medicine Reports, 17, 3069-3077. https://doi.org/10.3892/mmr.2017.8274
MLA
Zhang, C., Shen, Y., Wang, J., Zhou, M., Chen, Y."Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods". Molecular Medicine Reports 17.2 (2018): 3069-3077.
Chicago
Zhang, C., Shen, Y., Wang, J., Zhou, M., Chen, Y."Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods". Molecular Medicine Reports 17, no. 2 (2018): 3069-3077. https://doi.org/10.3892/mmr.2017.8274
Copy and paste a formatted citation
x
Spandidos Publications style
Zhang C, Shen Y, Wang J, Zhou M and Chen Y: Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods. Mol Med Rep 17: 3069-3077, 2018.
APA
Zhang, C., Shen, Y., Wang, J., Zhou, M., & Chen, Y. (2018). Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods. Molecular Medicine Reports, 17, 3069-3077. https://doi.org/10.3892/mmr.2017.8274
MLA
Zhang, C., Shen, Y., Wang, J., Zhou, M., Chen, Y."Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods". Molecular Medicine Reports 17.2 (2018): 3069-3077.
Chicago
Zhang, C., Shen, Y., Wang, J., Zhou, M., Chen, Y."Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods". Molecular Medicine Reports 17, no. 2 (2018): 3069-3077. https://doi.org/10.3892/mmr.2017.8274
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