Open Access

Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray

  • Authors:
    • Junkui Sun
    • Hongen Xu
    • Muge Qi
    • Chi Zhang
    • Jianxiang Shi
  • View Affiliations

  • Published online on: July 31, 2019     https://doi.org/10.3892/mmr.2019.10543
  • Pages: 3075-3084
  • Copyright: © Sun et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Osteosarcoma (OS) is one of the most malignant tumors in children and young adults. To better understand the underlying mechanism, five related datasets deposited in the Gene Expression Omnibus were included in the present study. The Bioconductor ‘limma’ package was used to identify differentially expressed genes (DEGs) and the ‘Weighted Gene Co‑expression Network Analysis’ package was used to construct a weighted gene co‑expression network to identify key modules and hub genes, associated with OS. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes overrepresentation analyses were used for functional annotation. The results indicated that 1,405 genes were dysregulated in OS, including 927 upregulated and 478 downregulated genes, when the cut off value was set at a ≥2 fold‑change and an adjusted P‑value of P<0.01 was used. Functional annotation of DEGs indicated that these genes were involved in the extracellular matrix (ECM) and that they function in several processes, including biological adhesion, ECM organization, cell migration and leukocyte migration. These findings suggested that dysregulation of the ECM shaped the tumor microenvironment and modulated the OS hallmark. Genes assigned to the yellow module were positively associated with OS and could contribute to the development of OS. In conclusion, the present study has identified several key genes that are potentially druggable genes or therapeutics targets in OS. Functional annotations revealed that the dysregulation of the ECM may contribute to OS development and, therefore, provided new insights to improve our understanding of the mechanisms underlying OS.
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October-2019
Volume 20 Issue 4

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
Sun J, Xu H, Qi M, Zhang C and Shi J: Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray. Mol Med Rep 20: 3075-3084, 2019
APA
Sun, J., Xu, H., Qi, M., Zhang, C., & Shi, J. (2019). Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray. Molecular Medicine Reports, 20, 3075-3084. https://doi.org/10.3892/mmr.2019.10543
MLA
Sun, J., Xu, H., Qi, M., Zhang, C., Shi, J."Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray". Molecular Medicine Reports 20.4 (2019): 3075-3084.
Chicago
Sun, J., Xu, H., Qi, M., Zhang, C., Shi, J."Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray". Molecular Medicine Reports 20, no. 4 (2019): 3075-3084. https://doi.org/10.3892/mmr.2019.10543