Open Access

Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses

  • Authors:
    • Yubo Xiao
    • Min Feng
    • Haiying Ran
    • Xiao Han
    • Xuegang Li
  • View Affiliations

  • Published online on: March 9, 2018     https://doi.org/10.3892/mmr.2018.8726
  • Pages: 6379-6386
  • Copyright: © Xiao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Increasing evidence has indicated that the abnormal expressions of certain genes serve important roles in tumorigenesis, progression and metastasis. The aim of the present study was to explore the key differentially expressed genes (DEGs) between non‑small cell lung cancer (NSCLC) and matched normal lung tissues by analyzing 4 different mRNA microarray datasets downloaded from the Gene Expression Omnibus (GEO) database. In improving the reliability of the bioinformatics analysis, the DEGs in each dataset that met the cut‑off criteria (adjust P‑value <0.05 and |log2fold‑change (FC)|>1) were intersected with each other, from which 195 were identified (consisting of 57 upregulated and 138 downregulated DEGs). The GO analysis results revealed that the upregulated DEGs were significantly enriched in various biological processes (BP), including cell cycle, mitosis and cell proliferation while the downregulated DEGs were significantly enriched in angiogenesis and response to drug and cell adhesion. The hub genes, including CCNB1, CCNA2, CEP55, PBK and HMMR, were identified based on the protein‑protein interaction (PPI) network. The Kaplan‑Meier survival analysis indicated that the high expression level of each of these hub genes correlates with poorer overall survival in all patients with NSCLC, which indicates that they may serve important roles in the progression of NSCLC. In conclusion, the DEGs and hub genes identified in the present study may contribute to the comprehensive understanding of the molecular mechanisms of NSCLC and may be used as diagnostic and prognostic biomarkers as well as molecular targets for the treatment of NSCLC.
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May-2018
Volume 17 Issue 5

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Copy and paste a formatted citation
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Spandidos Publications style
Xiao Y, Feng M, Ran H, Han X and Li X: Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses. Mol Med Rep 17: 6379-6386, 2018
APA
Xiao, Y., Feng, M., Ran, H., Han, X., & Li, X. (2018). Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses. Molecular Medicine Reports, 17, 6379-6386. https://doi.org/10.3892/mmr.2018.8726
MLA
Xiao, Y., Feng, M., Ran, H., Han, X., Li, X."Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses". Molecular Medicine Reports 17.5 (2018): 6379-6386.
Chicago
Xiao, Y., Feng, M., Ran, H., Han, X., Li, X."Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analyses". Molecular Medicine Reports 17, no. 5 (2018): 6379-6386. https://doi.org/10.3892/mmr.2018.8726