Evaluation of Expression Profile of Patients with Acute Myeloid Leukemia in Response to Azacitidine with Biological System Approach.

Rasta Hejab, Hamzeh Rahimi, Hamid Abedinlou, Pegah Ghoraeian
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Abstract

Background: Acute myeloid leukemia (AML) is a prevalent type of leukemia that is associated with high rates of chemoresistance, including resistance to Azacitidine (AZA). Understanding the molecular mechanisms of chemoresistance can lead to the development of novel therapeutic approaches. In this study, we aimed to identify dysregulated miRNAs and their target genes involved in chemoresistance to AZA in AML patients.

Methods: We analyzed expression profiles from two GEO datasets (GSE16625 and GSE77750) using the "Limma" package in R. We identified 29 differentially expressed miRNAs between AML patients treated with AZA and healthy individuals. MultiMiR package of R was used to predict target genes of identified miRNAs, and functional enrichment analysis was performed using FunRich software. Protein-protein interaction networks were constructed using STRING and visualized using Cytoscape. MiR-582 and miR- 597 were the most up- and down-regulated miRNAs, respectively. Functional enrichment analysis revealed that metal ion binding, regulation of translation, and proteoglycan syndecan-mediated signaling events were the most enriched pathways. The tumor necrosis factor (TNF) gene was identified as a hub gene in the protein-protein interaction network.

Discussion: Our study identified dysregulated miRNAs and their target genes in response to AZA treatment in AML patients. These findings provide insights into the molecular mechanisms of chemoresistance and suggest potential therapeutic targets for the treatment of AML.

Conclusion: Further experimental validation of the identified miRNAs and their targets is warranted.

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用生物系统法评价急性髓系白血病患者对阿扎胞苷的表达谱。
背景:急性髓系白血病(AML)是一种常见的白血病类型,与高耐药率相关,包括对阿扎胞苷(AZA)的耐药。了解化疗耐药的分子机制可以导致新的治疗方法的发展。在这项研究中,我们旨在鉴定AML患者中参与AZA化疗耐药的异常mirna及其靶基因。方法:我们使用r中的“Limma”软件包分析了两个GEO数据集(GSE16625和GSE77750)的表达谱。我们在接受AZA治疗的AML患者和健康个体之间鉴定了29种差异表达的mirna。使用R的MultiMiR包预测鉴定的miRNAs的靶基因,并使用FunRich软件进行功能富集分析。使用STRING构建蛋白-蛋白相互作用网络,并使用Cytoscape进行可视化。miR- 582和miR- 597分别是上调和下调最多的mirna。功能富集分析显示,金属离子结合、翻译调控和蛋白聚糖syndecan介导的信号通路富集最多。肿瘤坏死因子(TNF)基因被确定为蛋白-蛋白相互作用网络中的枢纽基因。讨论:我们的研究确定了AML患者对AZA治疗的反应中失调的mirna及其靶基因。这些发现为化疗耐药的分子机制提供了见解,并为AML的治疗提供了潜在的治疗靶点。结论:对鉴定的mirna及其靶标进行进一步的实验验证是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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