AI Summary & Key Takeaways
AI InsightWe have utilized the GEPIA tool to determine the Overall Survival of the hub genes.
📌 3 Key Takeaways
Abstract
Objective: Acute myeloid leukemia (AML) is a lethal type of cancer associated with dysregulation of progenitor hematopoietic stem cell behavior and its incidence is, unfortunately, increasing. Although there are various applications in treatment, since most of them are insufficient in early diagnosis, treatment and new prognostic biomarkers should be investigated. Materials and Methods: In this study, three Gene Expression Omnibus (GEO) datasets Genomic Spatial Event (GSE); GSE94591, GSE116617, and GSE163386) were used to investigate dysregulated expressions of circular RNAs (circRNAs), and the GSE142699 and GSE142698 datasets were analyzed to detect dysregulated expressions of microRNAs (miRNAs) and mRNAs, respectively. Filtering was applied with p value <0.05, log2FC≥0.5 (circRNA), and log2FC≥1 (miRNA and mRNA) from the raw data analyzed using the limma R package (v.3.46.0). We investigated circRNA-miRNA-mRNA interactions using special tools including CSCDv2.0, circBank, miRTarBase, miRDB, multiMiR, miRWalk, DIANA-microT, TarBase, miRanda, and TargetScan. The pathway analysis was performed using KEGG and GO programs. The STRING database and Cytoscape tool were used to construct and view protein interaction. Hub gene analysis was constructed using the MCODE tool. We have utilized the GEPIA tool to determine the Overall Survival of the hub genes. Results: In our study, 4 circRNAs, 3 miRNAs, and 6 genes that may be closely related to AML were detected. Conclusion: According to our bioinformatics analysis results, hsa_circ_0012152/miR-199a-5p/HOXA9 axis could be more important in AML. Therefore, in vitro and in vivo investigations are recommended.