4.5 Article

Illuminating (HTLV-1)-induced adult T-cell leukemia/lymphoma transcriptomic signature: A systems virology approach

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VIRUS RESEARCH
卷 338, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.virusres.2023.199237

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Adult T -cell lymphoma/leukemia; HTLV-1; Network analysis; WGCNA; Bioinformatics; RT-qPCR

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This study used bioinformatics methods to investigate the expression of genes and the affected cellular signaling pathways in adult T-cell leukemia/lymphoma (ATLL). The results revealed the key roles of pathways related to immune response regulation, T-cell receptor and activation, regulation of cell signaling, Wnt signaling pathway, and apoptosis in the pathogenesis of ATLL. Possible biomarkers were also identified. Further research is needed to validate these genes as biomarkers and treatment targets.
Background: Adult T-cell leukemia/lymphoma (ATLL) is a poor prognosis malignancy of peripheral T-cells caused by human T-cell leukemia virus type 1 (HTLV-1). The low survival rates observed in the patients are the result of the lack of sufficient knowledge about the disease pathogenesis.Methods: In the present study, we first identified differentially expressed genes in ATLL patients and the cellular signaling pathways affected by them. Then, genes of these pathways were subjected to more comprehensive evaluations, including WGCNA and module validation studies on five external datasets. Finally, potential biomarkers were selected for qRT-PCR validation.Results: Thirteen signaling pathways, including Apoptosis, Human T-cell leukemia virus 1 infection, IL-17 signaling pathway, pathways in cancer, T cell receptor signaling pathway, Th1 and Th2 cell differentiation, and seven others were selected for deeper investigations. Results of our in-depth bioinformatics evaluations, highlighted pathways related to regulation of immune responses, T-cell receptor and activation, regulation of cell signaling receptors and messengers, Wnt signaling pathway, and apoptosis as key players in ATLL pathogenesis. MAPK3, PIK3CD, KRAS, NFKB1, TNF, PLCB3, PLCB2, PLCB1, MAPK11, JUN, ITPR1, ADCY1, GNAQ, ADCY3, ADCY4, CHEK1, CCND1, SOS2, BAX, FOS and GNA12 were identified as possible biomarkers. Upregulation of ADCY1 and ADCY3 genes was confirmed via qRT-PCR.Conclusions: In this study, we performed a deep bioinformatic examination on a limited set of genes with high probabilities of involvement in the pathogenesis of ATLL. Our results highlighted signaling pathways and genes with potential key roles in disease formation and resistance against current treatment strategies. Further studies are required to test the possible benefits of highlighted genes as biomarkers and targets of treatment.

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