Open Access

Identification of potential biomarkers for diagnosis of hepatocellular carcinoma

  • Authors:
    • Xing-Hua Liang
    • Zheng-Ping Feng
    • Fo-Qiu Liu
    • Rong Yan
    • Liang-Yu Yin
    • Hao Shen
    • Hai-Lin Lu
  • View Affiliations

  • Published online on: November 15, 2021     https://doi.org/10.3892/etm.2021.10973
  • Article Number: 51
  • Copyright: © Liang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan‑Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression‑free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression‑free survival of patients with HCC, providing valuable information for the prognosis of HCC.
View Figures
View References

Related Articles

Journal Cover

January-2022
Volume 23 Issue 1

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

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Liang X, Feng Z, Liu F, Yan R, Yin L, Shen H and Lu H: Identification of potential biomarkers for diagnosis of hepatocellular carcinoma. Exp Ther Med 23: 51, 2022
APA
Liang, X., Feng, Z., Liu, F., Yan, R., Yin, L., Shen, H., & Lu, H. (2022). Identification of potential biomarkers for diagnosis of hepatocellular carcinoma. Experimental and Therapeutic Medicine, 23, 51. https://doi.org/10.3892/etm.2021.10973
MLA
Liang, X., Feng, Z., Liu, F., Yan, R., Yin, L., Shen, H., Lu, H."Identification of potential biomarkers for diagnosis of hepatocellular carcinoma". Experimental and Therapeutic Medicine 23.1 (2022): 51.
Chicago
Liang, X., Feng, Z., Liu, F., Yan, R., Yin, L., Shen, H., Lu, H."Identification of potential biomarkers for diagnosis of hepatocellular carcinoma". Experimental and Therapeutic Medicine 23, no. 1 (2022): 51. https://doi.org/10.3892/etm.2021.10973