Open Access

Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis

  • Authors:
    • Zengmiao Xing
    • Zuojie Luo
    • Haiyan Yang
    • Zhenxing Huang
    • Xinghuan Liang
  • View Affiliations

  • Published online on: September 6, 2019     https://doi.org/10.3892/ol.2019.10817
  • Pages: 4667-4676
  • Copyright: © Xing et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. The presently available understanding of the pathogenesis of ACC is incomplete and the treatment options for patients with ACC are limited. Gene marker identification is required for accurate and timely diagnosis of the disease. In order to identify novel candidate genes associated with the occurrence and progression of ACC, the microarray datasets, GSE12368 and GSE19750, were obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed. A protein‑protein interaction network (PPI) was constructed to identify significantly altered modules, and module analysis was performed using Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 228 DEGs were screened, consisting of 29 up and 199 downregulated genes. The enriched functions and pathways of the DEGs primarily included ‘cell division’, ‘regulation of transcription involved in G1/S transition of mitotic cell cycle’, ‘G1/S transition of mitotic cell cycle’, ‘p53 signaling pathway’ and ‘oocyte meiosis’. A total of 14 hub genes were identified, and biological process analysis revealed that these genes were significantly enriched in cell division and mitotic cell cycle. Furthermore, survival analysis revealed that AURKA, TYMS, GINS1, RACGAP1, RRM2, EZH2, ZWINT, CDK1, CCNB1, NCAPG and TPX2 may be involved in the tumorigenesis, progression or prognosis of ACC. In conclusion, the 14 hub genes identified in the present study may aid researchers in elucidating the molecular mechanisms associated with the tumorigenesis and progression of ACC, and may be powerful and promising candidate biomarkers for the diagnosis and treatment of ACC.
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November-2019
Volume 18 Issue 5

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Copy and paste a formatted citation
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Spandidos Publications style
Xing Z, Luo Z, Yang H, Huang Z and Liang X: Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis. Oncol Lett 18: 4667-4676, 2019
APA
Xing, Z., Luo, Z., Yang, H., Huang, Z., & Liang, X. (2019). Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis. Oncology Letters, 18, 4667-4676. https://doi.org/10.3892/ol.2019.10817
MLA
Xing, Z., Luo, Z., Yang, H., Huang, Z., Liang, X."Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis". Oncology Letters 18.5 (2019): 4667-4676.
Chicago
Xing, Z., Luo, Z., Yang, H., Huang, Z., Liang, X."Screening and identification of key biomarkers in adrenocortical carcinoma based on bioinformatics analysis". Oncology Letters 18, no. 5 (2019): 4667-4676. https://doi.org/10.3892/ol.2019.10817