Gene coexpression network analysis revealed biomarkers correlated with blast cells and survival in acute myeloid leukemia

  • Authors:
    • Yuming Pan
    • Qiaoxia Zhang
    • Xiaopeng Deng
    • Na An
    • Xin Du
    • Jiajun Liu
  • View Affiliations

  • Published online on: February 26, 2020     https://doi.org/10.3892/mco.2020.2006
  • Pages: 475-484
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Abstract

Acute myeloid leukemia (AML) is a hematological malignancy with a poorly understood pathogenesis, especially among patients with no known cytogenetic abnormalities. Furthermore, there is a lack of therapeutic gene targets and diagnostic biomarkers for the effective treatment of AML. The present study aimed to identify candidate biomarkers correlated with the clinical prognosis of patients with AML. Leukemic cells from 5 patients with AML exhibiting a normal karyotype, and hematopoietic cells from 5 healthy donors were processed for RNA sequencing (RNA‑seq), and the obtained RNA expression profiles were subjected to weighted gene correlation network analysis. A novel group of genes (the red module) were identified to be significantly associated with AML, and this module contained a closely connected network with 147 nodes, which corresponded to 114 mRNAs. Analysis of the correlation between these mRNAs and blast cell percentage, overall survival (OS) and disease‑free survival (DFS) using cases from The Cancer Genome Atlas (TCGA) database revealed that CSF3R, ALPL and LMTK2 were negatively associated with the percentage of blast cells, while high expression of these genes was associated with longer OS and DFS in patients with AML. The differential expression of these three genes between patients with AML and healthy control subjects was supported using the Genotype‑Tissue Expression and TCGA databases and was further confirmed using reverse transcription‑quantitative (RT‑qPCR). These genes exhibited significantly lower expression in patients with AML compared with control subjects. The results indicated that CSF3R, ALPL and LMTK2 exhibit the potential to be prognostic biomarkers. However, the biological functions of these three candidate genes need to be assessed in further studies.
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May-2020
Volume 12 Issue 5

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Spandidos Publications style
Pan Y, Zhang Q, Deng X, An N, Du X and Liu J: Gene coexpression network analysis revealed biomarkers correlated with blast cells and survival in acute myeloid leukemia. Mol Clin Oncol 12: 475-484, 2020.
APA
Pan, Y., Zhang, Q., Deng, X., An, N., Du, X., & Liu, J. (2020). Gene coexpression network analysis revealed biomarkers correlated with blast cells and survival in acute myeloid leukemia. Molecular and Clinical Oncology, 12, 475-484. https://doi.org/10.3892/mco.2020.2006
MLA
Pan, Y., Zhang, Q., Deng, X., An, N., Du, X., Liu, J."Gene coexpression network analysis revealed biomarkers correlated with blast cells and survival in acute myeloid leukemia". Molecular and Clinical Oncology 12.5 (2020): 475-484.
Chicago
Pan, Y., Zhang, Q., Deng, X., An, N., Du, X., Liu, J."Gene coexpression network analysis revealed biomarkers correlated with blast cells and survival in acute myeloid leukemia". Molecular and Clinical Oncology 12, no. 5 (2020): 475-484. https://doi.org/10.3892/mco.2020.2006