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Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis

  • Authors:
    • Jun Liu
    • Zhanzhong Ma
    • Yanming Liu
    • Liangyin Wu
    • Zhiwei Hou
    • Wenli Li
  • View Affiliations / Copyright

    Affiliations: Department of Laboratory Medicine, Yue Bei People's Hospital, Shaoguan, Guangdong 512026, P.R. China, Reproductive Medicine Center, Yue Bei People's Hospital, Shaoguan, Guangdong 512026, P.R. China
    Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 2500-2508
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    Published online on: July 5, 2019
       https://doi.org/10.3892/ol.2019.10578
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Abstract

Evidence suggests that hepatitis C virus (HCV) infection is among the main causes of hepatocellular carcinoma (HCC). In addition, HCV‑induced HCC (HCV‑HCC) exhibits adverse clinical outcomes and limited therapeutic treatments are available for this condition. To investigate key biomarkers in the occurrence and development of HCV‑HCC, microarray datasets GSE62232, GSE69715 and GSE107170 were downloaded from the Gene Expression Omnibus database for analysis. The differentially expressed genes between HCV‑HCC and normal tissue were identified using the GEO2R online tool. The function enrichment analyses including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were performed using the Database for Annotation, Visualization and Integrated Discovery online tool. A protein‑protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape. A total of 368 DEGs were identified, and the top 10 hub genes with a high degree of connectivity were selected for further analysis. Subsequently, overall survival and disease‑free survival analysis revealed that there was a significant association between altered expression of HMMR, CCNB1 and KIF20A, and poor clinical outcome. In summary, these results indicate that HMMR, CCNB1 and KIF20A are potential targets for diagnosis and therapy of HCV‑HCC.
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Copy and paste a formatted citation
Spandidos Publications style
Liu J, Ma Z, Liu Y, Wu L, Hou Z and Li W: Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis. Oncol Lett 18: 2500-2508, 2019.
APA
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., & Li, W. (2019). Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis. Oncology Letters, 18, 2500-2508. https://doi.org/10.3892/ol.2019.10578
MLA
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., Li, W."Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis". Oncology Letters 18.3 (2019): 2500-2508.
Chicago
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., Li, W."Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis". Oncology Letters 18, no. 3 (2019): 2500-2508. https://doi.org/10.3892/ol.2019.10578
Copy and paste a formatted citation
x
Spandidos Publications style
Liu J, Ma Z, Liu Y, Wu L, Hou Z and Li W: Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis. Oncol Lett 18: 2500-2508, 2019.
APA
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., & Li, W. (2019). Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis. Oncology Letters, 18, 2500-2508. https://doi.org/10.3892/ol.2019.10578
MLA
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., Li, W."Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis". Oncology Letters 18.3 (2019): 2500-2508.
Chicago
Liu, J., Ma, Z., Liu, Y., Wu, L., Hou, Z., Li, W."Screening of potential biomarkers in hepatitis C virus‑induced hepatocellular carcinoma using bioinformatic analysis". Oncology Letters 18, no. 3 (2019): 2500-2508. https://doi.org/10.3892/ol.2019.10578
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