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Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis

  • Authors:
    • Tonghai Xing
    • Tingmang Yan
    • Qiang Zhou
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    Affiliations: Department of General Surgery, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, P.R. China, Department of Urology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, P.R. China
    Copyright: © Xing et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 4932-4942
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    Published online on: April 16, 2018
       https://doi.org/10.3892/etm.2018.6075
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Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expression profiles GSE25097, GSE45267, GSE57957 and GSE62232 were downloaded from the Gene Expression Omnibus database, including 436 HCC and 94 normal liver tissues. A total of 185 differentially expressed genes (DEGs) were identified in HCC, including 92 upregulated genes and 92 downregulated genes. Gene ontology (GO) was performed, which revealed that the upregulated DEGs were primarily enriched in cell division, mitotic nuclear division, mitotic cytokinesis and G1/S transition of the mitotic cell cycle. Pathway enrichment was analyzed based on the Kyoto Encyclopedia of Genes and Genomes database to assess the functional relevance of DEGs. The most significant module was selected from protein‑protein interactions and 15 important hub genes were identified. The sub‑networks of hub genes were involved in cell division, p53 signaling, and T lymphotropic virus type I infection signaling pathways. In conclusion, the present study revealed that the identified DEG candidate genes may promote the understanding of the cause and molecular mechanisms underlying the development of HCC and that these candidates and signal pathways may be potential targets of clinical therapy for HCC.
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Copy and paste a formatted citation
Spandidos Publications style
Xing T, Yan T and Zhou Q: Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis. Exp Ther Med 15: 4932-4942, 2018.
APA
Xing, T., Yan, T., & Zhou, Q. (2018). Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis. Experimental and Therapeutic Medicine, 15, 4932-4942. https://doi.org/10.3892/etm.2018.6075
MLA
Xing, T., Yan, T., Zhou, Q."Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis". Experimental and Therapeutic Medicine 15.6 (2018): 4932-4942.
Chicago
Xing, T., Yan, T., Zhou, Q."Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis". Experimental and Therapeutic Medicine 15, no. 6 (2018): 4932-4942. https://doi.org/10.3892/etm.2018.6075
Copy and paste a formatted citation
x
Spandidos Publications style
Xing T, Yan T and Zhou Q: Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis. Exp Ther Med 15: 4932-4942, 2018.
APA
Xing, T., Yan, T., & Zhou, Q. (2018). Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis. Experimental and Therapeutic Medicine, 15, 4932-4942. https://doi.org/10.3892/etm.2018.6075
MLA
Xing, T., Yan, T., Zhou, Q."Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis". Experimental and Therapeutic Medicine 15.6 (2018): 4932-4942.
Chicago
Xing, T., Yan, T., Zhou, Q."Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis". Experimental and Therapeutic Medicine 15, no. 6 (2018): 4932-4942. https://doi.org/10.3892/etm.2018.6075
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