Open Access

Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers

  • Authors:
    • Xuqing Yin
    • Jiubo Sun
    • Haiyang Zhang
    • Shuai Wang
  • View Affiliations

  • Published online on: September 3, 2018     https://doi.org/10.3892/mmr.2018.9432
  • Pages: 4229-4238
  • Copyright: © Yin et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Ewing sarcoma (ES) is a common primary malignancy in children and adolescents. Progression of treatment methods hasn't contributed a lot to the imrovement of prognosis. To identify potential prognostic biomarkers, a meta‑analysis pipeline of multi‑gene expression datasets for ES from the Gene Expression Omnibus (GEO) was performed. Three datasets were screened and differential expression genes (DEGs) in ES samples compared with normal tissues were identified through limma package and subjected to network analysis. As a result, 1,470 DEGs were obtained which were mainly involved in biological processes associated with immune response and transcription regulation. Network analysis obtained 22 core genes with high network degree and fold change. Kaplan‑Meier analysis based on ES datasets from The Cancer Genome Atlas identified five genes, including glycogen phosphorylase, muscle‑associated, myocyte‑specific enhancer factor 2C, tripartite motif containing 63, budding uninhibited by benzimidazoses1 and Ras GTPase‑activating protein 1, whose altered expression profiles are significantly associated with survival. Changes of their expression values were further confirmed through RT‑qPCR in ES cell and normal cell lines. Those genes may be considered as potential prognostic biomarkers of ES and should be helpful for its early diagnosis and treatment.
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November-2018
Volume 18 Issue 5

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

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Spandidos Publications style
Yin X, Sun J, Zhang H and Wang S: Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers. Mol Med Rep 18: 4229-4238, 2018
APA
Yin, X., Sun, J., Zhang, H., & Wang, S. (2018). Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers. Molecular Medicine Reports, 18, 4229-4238. https://doi.org/10.3892/mmr.2018.9432
MLA
Yin, X., Sun, J., Zhang, H., Wang, S."Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers". Molecular Medicine Reports 18.5 (2018): 4229-4238.
Chicago
Yin, X., Sun, J., Zhang, H., Wang, S."Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers". Molecular Medicine Reports 18, no. 5 (2018): 4229-4238. https://doi.org/10.3892/mmr.2018.9432