Open Access

Exploring the molecular pathogenesis associated with T‑cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis

  • Authors:
    • Zhangzhen Shi
    • Jing Yu
    • Hui Shao
    • Kailiang Cheng
    • Jingjie Zhai
    • Qi Jiang
    • Hongjun Li
  • View Affiliations

  • Published online on: May 2, 2018     https://doi.org/10.3892/ol.2018.8615
  • Pages: 301-307
  • Copyright: © Shi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

As a rare hematological malignancy, T‑cell prolymphocytic leukemia (T‑PLL) has a high mortality rate. However, the comprehensive mechanisms of the underlying pathogenesis of T‑PLL are unknown. The purpose of the present study was to investigate the pathogenesis of T‑PLL based on a comprehensive bioinformatics analysis. The differentially expressed genes (DEGs) between T‑PLL blood cell samples and normal peripheral blood cell samples were investigated using the GSE5788 Affymetrix microarray data from the Gene Expression Omnibus database. To investigate the functional changes associated with tumor progression, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used on the identified DEGs, followed by protein‑protein interaction (PPI) and sub‑PPI analysis. Transcription factors and tumor‑associated genes (TAGs) were investigated further. The results identified 84 upregulated genes and 354 downregulated genes in T‑PLL samples when compared with healthy samples. These DEGs featured in various functions including cell death and various pathways including apoptosis. The functional analysis of DEGs revealed 17 dysregulated transcription factors and 37 dysregulated TAGs. Furthermore, the PPI network analysis based on node degree (a network topology attribute) identified 61 genes, including the core downregulated gene of the sub‑PPI network, signal transducer and activator of transcription 3 (STAT3; degree, 13) and the core upregulated gene, insulin receptor substrate‑1 (IRS1; degree, 5), that may have important associations with the progression of T‑PLL. Alterations to cell functions, including cell death, and pathways, including apoptosis, may contribute to the process of T‑PLL. Candidate genes identified in the present study, including STAT3 and IRS1, should be targets for additional studies.
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July-2018
Volume 16 Issue 1

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

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Spandidos Publications style
Shi Z, Yu J, Shao H, Cheng K, Zhai J, Jiang Q and Li H: Exploring the molecular pathogenesis associated with T‑cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis. Oncol Lett 16: 301-307, 2018
APA
Shi, Z., Yu, J., Shao, H., Cheng, K., Zhai, J., Jiang, Q., & Li, H. (2018). Exploring the molecular pathogenesis associated with T‑cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis. Oncology Letters, 16, 301-307. https://doi.org/10.3892/ol.2018.8615
MLA
Shi, Z., Yu, J., Shao, H., Cheng, K., Zhai, J., Jiang, Q., Li, H."Exploring the molecular pathogenesis associated with T‑cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis". Oncology Letters 16.1 (2018): 301-307.
Chicago
Shi, Z., Yu, J., Shao, H., Cheng, K., Zhai, J., Jiang, Q., Li, H."Exploring the molecular pathogenesis associated with T‑cell prolymphocytic leukemia based on a comprehensive bioinformatics analysis". Oncology Letters 16, no. 1 (2018): 301-307. https://doi.org/10.3892/ol.2018.8615