Open Access

Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML

  • Authors:
    • Zhen Zhang
    • Lin Zhao
    • Xijin Wei
    • Qiang Guo
    • Xiaoxiao Zhu
    • Ran Wei
    • Xunqiang Yin
    • Yunhong Zhang
    • Bin Wang
    • Xia Li
  • View Affiliations

  • Published online on: July 31, 2018     https://doi.org/10.3892/ol.2018.9237
  • Pages: 5147-5159
  • Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 4.0].

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Abstract

Myeloid disorders, especially myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), cause significant mobility and high mortality worldwide. Despite numerous attempts, the common molecular events underlying the development of MDS and AML remain to be established. In the present study, 18 microarray datasets were selected, and a meta‑analysis was conducted to identify shared gene signatures and biological processes between MDS and AML. Using NetworkAnalyst, 191 upregulated and 139 downregulated genes were identified in MDS and AML, among which, PTH2R, TEC, and GPX1 were the most upregulated genes, while MME, RAG1, and CD79B were mostly downregulated. Comprehensive functional enrichment analyses revealed oncogenic signaling related pathway, fibroblast growth factor receptor (FGFR) and immune response related events, ‘interleukine‑6/interferon signaling pathway, and B cell receptor signaling pathway’, were the most upregulated and downregulated biological processes, respectively. Network based meta‑analysis ascertained that HSP90AA1 and CUL1 were the most important hub genes. Interestingly, our study has largely clarified the link between MDS and AML in terms of potential pathways, and genetic markers, which shed light on the molecular mechanisms underlying the development and transition of MDS and AML, and facilitate the understanding of novel diagnostic, therapeutic and prognostic biomarkers.
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October-2018
Volume 16 Issue 4

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

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Spandidos Publications style
Zhang Z, Zhao L, Wei X, Guo Q, Zhu X, Wei R, Yin X, Zhang Y, Wang B, Li X, Li X, et al: Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML. Oncol Lett 16: 5147-5159, 2018
APA
Zhang, Z., Zhao, L., Wei, X., Guo, Q., Zhu, X., Wei, R. ... Li, X. (2018). Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML. Oncology Letters, 16, 5147-5159. https://doi.org/10.3892/ol.2018.9237
MLA
Zhang, Z., Zhao, L., Wei, X., Guo, Q., Zhu, X., Wei, R., Yin, X., Zhang, Y., Wang, B., Li, X."Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML". Oncology Letters 16.4 (2018): 5147-5159.
Chicago
Zhang, Z., Zhao, L., Wei, X., Guo, Q., Zhu, X., Wei, R., Yin, X., Zhang, Y., Wang, B., Li, X."Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML". Oncology Letters 16, no. 4 (2018): 5147-5159. https://doi.org/10.3892/ol.2018.9237