Literature DB >> 33630973

Deciphering microRNA-mRNA regulatory network in adult T-cell leukemia/lymphoma; the battle between oncogenes and anti-oncogenes.

Mohadeseh Zarei Ghobadi1, Rahman Emamzadeh1, Sayed-Hamidreza Mozhgani2,3.   

Abstract

Adult T-cell leukemia/lymphoma (ATLL) is virus-caused cancer that originates from the infection by human T-cell leukemia virus type 1. ATLL dysregulates various biological pathways related to the viral infection and cancer progression through the dysexpression of miRNAs and mRNAs. In this study, the potential regulatory subnetworks were constructed aiming to shed light on the pathogenesis mechanism of ATLL. For this purpose, two mRNA and one miRNA expression datasets were firstly downloaded from the GEO database. Next, the differentially expressed genes and miRNAs (DEGs and DE-miRNAs, respectively), as well as differentially co-expressed gene pairs (DCGs), were determined. Afterward, common DEGs and DCGs targeted by experimentally validated DE-miRNAs were explored. The oncogenic and anti-oncogenic miRNA-mRNA regulatory subnetworks were then generated. The expression levels of four genes and two miRNAs were examined in the blood samples by qRT-PCR. The members of three oncogenic/anti-oncogenic subnetworks were generally enriched in immune, virus, and cancer-related pathways. Among them, FZD6, THBS4, SIRT1, CPNE3, miR-142-3p, and miR-451a were further validated by real-time PCR. The significant up-regulation of FZD6, THBS4, and miR-451a as well as down-regulation of CPNE3, SIRT1, and miR-142-3p were found in ATLL samples than normal samples. The identified oncogenic/anti-oncogenic subnetworks are pieces of the pathogenesis puzzle of ATLL. The ultimate winner is probably an oncogenic network that determines the final fate of the disease. The identified genes and miRNAs are proposed as novel prognostic biomarkers for ATLL.

Entities:  

Year:  2021        PMID: 33630973     DOI: 10.1371/journal.pone.0247713

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  3 in total

1.  Decoding pathogenesis factors involved in the progression of ATLL or HAM/TSP after infection by HTLV-1 through a systems virology study.

Authors:  Mohadeseh Zarei Ghobadi; Rahman Emamzadeh; Majid Teymoori-Rad; Sayed-Hamidreza Mozhgani
Journal:  Virol J       Date:  2021-08-26       Impact factor: 4.099

2.  Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning.

Authors:  Mohadeseh Zarei Ghobadi; Rahman Emamzadeh; Elaheh Afsaneh
Journal:  BMC Cancer       Date:  2022-04-21       Impact factor: 4.638

3.  Integration of gene co-expression analysis and multi-class SVM specifies the functional players involved in determining the fate of HTLV-1 infection toward the development of cancer (ATLL) or neurological disorder (HAM/TSP).

Authors:  Mohadeseh Zarei Ghobadi; Rahman Emamzadeh
Journal:  PLoS One       Date:  2022-01-18       Impact factor: 3.240

  3 in total

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