Volume 6, Number 1 (Vol.6 No.1 Oct 2017)                   rbmb.net 2017, 6(1): 88-94 | Back to browse issues page


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Torshizi R, Ghayour Karimani E, Etminani K, Akbarin M M, Jamialahmadi K, Shirdel A, et al . Altered expression of cell cycle regulators in adult T-cell leukemia/lymphoma patients. rbmb.net. 2017; 6 (1) :88-94
URL: http://rbmb.net/article-1-138-en.html

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran, Iran
Abstract:   (833 Views)

Abstract

Background: Adult T-cell leukemia/lymphoma (ATLL) is caused by human T-cell lymphotropic virus type-1 (HTLV-1).  HTLV-1 oncogenes can induce malignancy through controlled gene expression of cell cycle checkpoints in the host cell. HTLV-I genes play a pivotal role in overriding cell cycle checkpoints and deregulate cellular division. In this study, we aimed to determine and compare the HTLV-1 proviral load and the gene expression levels of cyclin-dependent kinase-2 (CDK2), CDK4, p53, and retinoblastoma (Rb) in ATLL and carriers groups.

Methods: A total of twenty-five ATLL patients (12 females and 13 males) and 21 asymptomatic carriers (10 females and 11 males) were included in this study. TaqMan real-time polymerase chain reaction assay was used for evaluation of proviral load and gene expression levels of CDK2, CDK4, p53, and Rb. Statistical analysis was used to compare proviral load and gene expression levels between two groups, using SPSS version 18.

Results: The mean scores of the HTLV-1 proviral load in the ATLL patients and healthy carriers were 13067.20±6400.41 and 345.79±78.80 copies/104 cells, respectively (P=0.000). There was a significant correlation between the gene expression levels of CDK2 and CDK4 (P=0.01) in the ATLL group.

Conclusions: Our findings demonstrated a significant difference between the ATLL patients and healthy carriers regarding the rate of proviral load and the gene expression levels of p53 and CDK4; accordingly, proviral load and expression levels of these genes may be useful in the assessment of disease progression and prediction of HTLV-1 infection outcomes. 

Full-Text [PDF 387 kb]   (179 Downloads)    
Type of Article: Original Article | Subject: Molecular Biology
Received: 2017/02/3 | Accepted: 2017/03/12 | Published: 2017/06/17

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