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Identification of Novel Mirnas Potentially Involved in the Pathogenesis of Adult T-Cell Leukemia/Lymphoma Using Wgcna Followed by Rt-Qpcr Test of Hub Genes Publisher



Shayeghpour A1 ; Forghaniramandi MM1 ; Solouki S1 ; Hosseini A2 ; Hosseini P3, 4 ; Khodayar S5 ; Hasani M1 ; Aghajanian S1 ; Siami Z6 ; Zarei Ghobadi M7 ; Mozhgani SH5, 8
Authors
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Authors Affiliations
  1. 1. School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
  2. 2. Department of Computer, Faculty of Engineering, Raja University, Qazvin, Iran
  3. 3. Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Research Center for Clinical Virology, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Microbiology, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
  6. 6. Department of Infectious Diseases, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
  7. 7. Independent Researcher, Tehran, Iran
  8. 8. Non-Communicable Disease Research Center, Alborz University of Medical Sciences, Karaj, Iran

Source: Infectious Agents and Cancer Published:2023


Abstract

Background: Adult T-cell Lymphoma/Leukemia (ATLL) is characterized by the malignant proliferation of T-cells in Human T-Lymphotropic Virus Type 1 and a high mortality rate. Considering the emerging roles of microRNAs (miRNAs) in various malignancies, the analysis of high-throughput miRNA data employing computational algorithms helps to identify potential biomarkers. Methods: Weighted gene co-expression network analysis was utilized to analyze miRNA microarray data from ATLL and healthy uninfected samples. To identify miRNAs involved in the progression of ATLL, module preservation analysis was used. Subsequently, based on the target genes of the identified miRNAs, the STRING database was employed to construct protein–protein interaction networks (PPIN). Real-time quantitative PCR was also performed to validate the expression of identified hub genes in the PPIN network. Results: After constructing co-expression modules and then performing module preservation analysis, four out of 15 modules were determined as ATLL-specific modules. Next, the hub miRNA including hsa-miR-18a-3p, has-miR-187-5p, hsa-miR-196a-3p, and hsa-miR-346 were found as hub miRNAs. The protein–protein interaction networks were constructed for the target genes of each hub miRNA and hub genes were identified. Among them, UBB, RPS15A, and KMT2D were validated by Reverse-transcriptase PCR in ATLL patients. Conclusion: The results of the network analysis of miRNAs and their target genes revealed the major players in the pathogenesis of ATLL. Further studies are required to confirm the role of these molecular factors and to discover their potential benefits as treatment targets and diagnostic biomarkers. © 2023, The Author(s).
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