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Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer

  • Authors:
    • Tianyu Ren
    • Xiaofei Xue
    • Xiaogang Wang
    • Xingtong Zhou
    • Shengchun Dang
  • View Affiliations / Copyright

    Affiliations: Department of General Surgery, The Affiliated Hospital, Jiangsu University, Zhenjiang, Jiangsu 212001, P.R. China, Department of General Surgery, Pucheng Hospital, Weinan, Shaanxi 715500, P.R. China
    Copyright: © Ren et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 1359
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    Published online on: September 24, 2021
       https://doi.org/10.3892/etm.2021.10794
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Abstract

The present study aimed to screen the key genes in pancreatic cancer and to explore the pathogenesis of pancreatic cancer. A total of three expression profiling datasets (GSE28735, GSE16515 and GSE15471) associated with pancreatic cancer were retrieved from the public gene chip database. The differentially expressed genes (DEGs) were screened by GEO2R and subjected to Gene Ontology (GO) and signaling pathway enrichment analysis. Furthermore, a protein interaction network was constructed. The GEPIA online database was used to screen for genes that affect the prognosis of pancreatic cancer. Finally, cell functional experiments were performed on the selected key genes. A total of 72 DEGs were identified, including 52 upregulated and 20 downregulated genes. Enrichment analysis revealed roles of the DEGs in endodermal cell differentiation, cell adhesion, extracellular matrix‑receptor interaction and PI3K‑Akt signaling pathway. In total, 10 key nodal genes were identified, including integrin subunit α 2 (ITGA2), ITGB6 and collagen α 1 chain 1. Through survival analysis, two genes with an impact on the prognosis of pancreatic cancer were identified, namely ITGA2 and ITGB6. Silencing of ITGB6 in a pancreatic cancer cell line significantly suppressed cell proliferation and induced cell cycle arrest at G2/M phase. The identified key genes and signaling pathways may help to deepen the understanding of the molecular mechanisms involved in pancreatic cancer and provide a theoretical basis to develop novel therapies.
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Copy and paste a formatted citation
Spandidos Publications style
Ren T, Xue X, Wang X, Zhou X and Dang S: Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer. Exp Ther Med 22: 1359, 2021.
APA
Ren, T., Xue, X., Wang, X., Zhou, X., & Dang, S. (2021). Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer. Experimental and Therapeutic Medicine, 22, 1359. https://doi.org/10.3892/etm.2021.10794
MLA
Ren, T., Xue, X., Wang, X., Zhou, X., Dang, S."Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer". Experimental and Therapeutic Medicine 22.6 (2021): 1359.
Chicago
Ren, T., Xue, X., Wang, X., Zhou, X., Dang, S."Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer". Experimental and Therapeutic Medicine 22, no. 6 (2021): 1359. https://doi.org/10.3892/etm.2021.10794
Copy and paste a formatted citation
x
Spandidos Publications style
Ren T, Xue X, Wang X, Zhou X and Dang S: Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer. Exp Ther Med 22: 1359, 2021.
APA
Ren, T., Xue, X., Wang, X., Zhou, X., & Dang, S. (2021). Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer. Experimental and Therapeutic Medicine, 22, 1359. https://doi.org/10.3892/etm.2021.10794
MLA
Ren, T., Xue, X., Wang, X., Zhou, X., Dang, S."Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer". Experimental and Therapeutic Medicine 22.6 (2021): 1359.
Chicago
Ren, T., Xue, X., Wang, X., Zhou, X., Dang, S."Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer". Experimental and Therapeutic Medicine 22, no. 6 (2021): 1359. https://doi.org/10.3892/etm.2021.10794
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