Open Access

Integrative module analysis of HCC gene expression landscapes

  • Authors:
    • Hongshi Li
    • Ning Wei
    • Yi Ma
    • Xiaozhou Wang
    • Zhiqiang Zhang
    • Shuang Zheng
    • Xi Yu
    • Shuang Liu
    • Lijie He
  • View Affiliations

  • Published online on: January 8, 2020     https://doi.org/10.3892/etm.2020.8437
  • Pages: 1779-1788
  • Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Despite hepatocellular carcinoma (HCC) being a common cancer globally, its initiation and progression are not well understood. The present study was designed to investigate the hub genes and biological processes of HCC, which change substantially during its progression. Three gene expression profiles of 480 patients with HCC were obtained from the Gene Expression Omnibus database. Subsequent to performing functional annotations and constructing protein‑protein interaction (PPI) networks, 657 differentially expressed genes were identified, which were subsequently used to screen candidate hub genes. PPI networks were modularized using the weighted gene correlation network analysis algorithm, the topological overlapping matrix and the hierarchical cluster tree, which were utilized via STRING. Clinical data obtained from The Cancer Genome Atlas were then analyzed to validate the experiments performed using six hub genes. Additionally, a transcription factor and microRNA‑mRNA network were constructed to determine the potential regulatory mechanisms of six hub genes. The results revealed that the oxidation‑reduction process and cell cycle associated processes were markedly involved in HCC progression. Six highly expressed genes, including cyclin B2, cell division cycle 20, mitotic arrest deficient 2 like 1, minichromosome maintenance complex component 2, centromere protein F and BUB mitotic checkpoint serine/threonine kinase B, were confirmed as hub genes and validated via experiments associated with cell division. These hub genes are necessary for confirmatory experiments and may be used in clinical gene therapy as biomarkers or drug targets.

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March 2020
Volume 19 Issue 3

Print ISSN: 1792-0981
Online ISSN:1792-1015

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APA
Li, H., Wei, N., Ma, Y., Wang, X., Zhang, Z., Zheng, S. ... He, L. (2020). Integrative module analysis of HCC gene expression landscapes. Experimental and Therapeutic Medicine, 19, 1779-1788. https://doi.org/10.3892/etm.2020.8437
MLA
Li, H., Wei, N., Ma, Y., Wang, X., Zhang, Z., Zheng, S., Yu, X., Liu, S., He, L."Integrative module analysis of HCC gene expression landscapes". Experimental and Therapeutic Medicine 19.3 (2020): 1779-1788.
Chicago
Li, H., Wei, N., Ma, Y., Wang, X., Zhang, Z., Zheng, S., Yu, X., Liu, S., He, L."Integrative module analysis of HCC gene expression landscapes". Experimental and Therapeutic Medicine 19, no. 3 (2020): 1779-1788. https://doi.org/10.3892/etm.2020.8437