Background Human T-lymphotropic virus 1 (HTLV-1) infection may lead to the development of Adult T-cell leukemia/lymphoma (ATLL). To further elucidate the pathophysiology of this aggressive CD4+ T-cell malignancy, we have performed an integrated systems biology approach to analyze previous transcriptome datasets focusing on differentially expressed miRNAs (DEMs) in peripheral blood of ATLL patients. Methods Datasets GSE28626, GSE31629, GSE11577 were used to identify ATLL-specific DEM signatures. The target genes of each identified miRNA were obtained to construct a protein-protein interactions network using STRING database. The target gene hubs were subjected to further analysis to demonstrate significantly enriched gene ontology terms and signaling pathways. Quantitative reverse transcription Polymerase Chain Reaction (RTqPCR) was performed on major genes in certain pathways identified by network analysis to highlight gene expression alterations. Results High-throughput in silico analysis revealed 9 DEMs hsa-let-7a, hsa-let-7g, hsa-mir-181b, hsa-mir-26b, hsa-mir-30c, hsa-mir-186, hsa-mir-10a, hsa-mir-30b, and hsa-let-7f between ATLL patients and healthy donors. Further analysis revealed the first 5 of DEMs were directly associated with previously identified pathways in the pathogenesis of HTLV-1. Network analysis demonstrated the involvement of target gene hubs in several signaling cascades, mainly in the MAPK pathway. RT-qPCR on human ATLL samples showed significant upregulation of EVI1, MKP1, PTPRR, and JNK gene vs healthy donors in MAPK/JNK pathway. Discussion The results highlighted the functional impact of a subset dysregulated microRNAs in ATLL on cellular gene expression and signal transduction pathways. Further studies are needed to identify novel biomarkers to obtain a comprehensive mapping of deregulated biological pathways in ATLL.
Acute myeloid leukemia (AML) is the most common acute leukemia in adults.Over the past decades, there has been a great challenge in the treatment of AML. A combination of gene expression profiling with computational approaches can lead to the identification of hub genes in AML. However, it is important to study the structure of these hub genes considering their importance in the proteinprotein interaction (PPI) network of specific cancer. In this study, we designed an integrated method to analyze the presence of intrinsically disordered regions (IDRs) in selected hub genes of AML. A gene expression profile of AML was obtained from Gene Expression Omnibus (GEO) database. Further analysis identified differentially expressed genes (DEGs) in AML. Additionally, the top 15 hub genes following construction and analysis of the PPI network of DEGs were selected. Validation of hub genes revealed that there is a reverse relationship between overexpression of FLT3, PPBP, and PF4 genes and the survival of AML patients. Based on IDRs investigation, FLT3 and PF4 are partially disordered, while PPBP is mostly disordered. Through clustering the network into structural modules, we identified two important modules in the PPI network of DEGs that showed the important position of PPBP in module 1. Based on further analysis of protein flexibility and its important role in biological processes, we suggest that PPBP can be considered as a potential drug target in AML. K E Y W O R D Sacute myeloid leukemia (AML), hub genes, intrinsically disordered regions (IDRs), PPI network Abbreviations: AML, Acute myeloid leukemia; PPI, protein-protein interaction; IDRs, intrinsically disordered regions; GEO, gene expression omnibus; DEGs, differentially expressed genes; BM, bone marrow; PB, peripheral blood; allo-HSCT, allogeneic hematopoietic stem cell transplantation; KEGG, kyoto encyclopedia of genes and genomes; GEPIA, gene expression profiling interactive analysis.
Background and Objectives: Human T-lymphotropic virus type-1 (HTLV-1) belongs to retrovirus family that causes the neurological disorder HTLV-1 adult T-cell leukemia/lymphoma (ATLL). Since 1980, seven subtypes of the virus have been recognized. HTLV-1 is prevalent and endemic in some regions, such as Africa, Japan, South America and Iran as the endemic regions of the HTLV-1 in the Middle East. To study HTLV-1 subtypes and routes of virus spread in Iran, phylogenetic and phylodynamic analyses were performed and for as much as no previous phylogenetic studies were conducted in Tehran, we do this survey. To this purpose, the Tax region of HTLV-1 was used. Materials and Methods: In this study 100 samples were collected from blood donors in Tehran. All samples were screened for anti-HTLV-I antibodies by ELISA. Then, genomic DNA was extracted from all positive samples (10 people), and for confirmation of infection, ordinary PCR was performed for both the HBZ and LTR regions. Moreover, the Tax region was amplified and purified PCR products were sequenced and analyzed, and finally, a phylogenetic tree was constructed using Mega X software. Results: Phylogenetic analysis confirmed that isolates from Iran, Japan, Brazil, and Africa are located within the extensive ‘‘transcontinental’’ subgroup A clade of HTLV-1 Cosmopolitan subtype a. The Japanese sequences are the closest to the Iranian sequences and have the most genetic similarity with them. Conclusion: Through phylogenetic and phylodynamic analyses HTLV-1 strain in Tehran were characterized in Iran. The appearance of HTLV-1 in Iran was probably happened by the ancient Silk Road which linked China to Antioch.
Background: Hemodialysis (HD) patients and kidney transplant (KT) recipients are exposed to be infected by blood-borne viruses (BBVs). Current study was conducted to evaluate the prevalence of BBVs in HD and KT patients in the whole Iranian population. Methods: From Jan 2016 to Dec 2017, 174 hemodialysis and 139 kidney transplant recipients enrolled in this survey. After blood sampling, serum samples were detected for HBV, HCV, HCMV, HIV and HTLV antibodies. Seropositive samples confirmed by Polymerase chain reaction (PCR) method. Results: Overall, 6 (3.44%) and 3 (2.15%) of hemodialysis-dependent and transplantation patients had evidence of HCV infection, whereas no patients were HIV and HBV positive, two cases (1.14%) of hemodialysis and one case (0.71%) of transplantation patients demonstrated the HTLV-1 infection. 52 (37.4%) of patients received graft were positive for HCMV antibody. In addition, our study showed a co-infection of HCMV with HCV (3 patients, 2.15%) in transplantation patients. Conclusion: Prevalence of BBVs infection was lower in comparison to the previous studies. The current strict infection control practices in Iran appear to be effective in limiting dialysis and related infections after transplantation. Because BBVs infections constantly occur especially in dialysis and after transplantation units, our data will be useful to build a new strategic plan for the elimination of BBVs infection in kidney therapycenters.
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