Screening and in Silico Functional Analysis of MiRNAs Associated with Acute Myeloid Leukemia Relapse

Abstract

Background: Hematologic malignancies are among fatal diseases with different subtypes. Acute myeloid leukemia (AML) is a subtype that shows a high rate of invasion to different tissues. Objective: AML patients even after treatment show an increased rate of recurrence and this relapsed profile of AML has turned this malignancy into big challenges in the medical scope. Methods: In the current study, we aimed to investigate hub-genes and potential signaling pathways in AML recurrence. Two expression profiles of genes and non-coding RNAs were extracted from Gene Expression Omnibus (GEO) database. Target genes of identified miRNAs were predicted through bioinformatics tools. GO and KEGG pathway enrichment analyses were conducted to discover common target genes and differentially expressed genes. Protein‐protein interaction (PPI) network constructed and visualized through STRING online database and Cytoscape software respectively. Hub-genes of constructed PPI were found through the CytoHubba plugin of Cytoscape software. Results: As a result, 109 differentially expressed genes and 45 differentially expressed miRNAs were found, and the top enriched pathways were Immune response, Chemokine activity, Immune System, and Plasma membrane. The hub-genes were TNF, IL6, TLR4, VEGFA, PTPRC, TLR7, TLR1, CD44, CASP1, and CD68. Conclusion: The present investigation based on the in silico analysis and microarray GEO databases may provide a novel understanding regarding the mechanisms related to AML relapse. Keywords: Acute myeloid leukemia, AML, Bioinformatics, microRNA, Protein‐protein interaction, Cancer.