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MicroRNA-363-3p promote the development of acute myeloid leukemia with RUNX1 mutation by targeting SPRYD4 and FNDC3B

BACKGROUND: Runt-related transcription factor 1 (RUNX1) is one of the most frequently mutated genes in most of hematological malignancies, especially in acute myeloid leukemia. In the present study, we aimed to identify the key genes and microRNAs based on acute myeloid leukemia with RUNX1 mutation....

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Detalles Bibliográficos
Autores principales: Chen, Yimin, Chen, Shuyi, Lu, Jielun, Yuan, Danyun, He, Lang, Qin, Pengfei, Tan, Huo, Xu, Lihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8104143/
https://www.ncbi.nlm.nih.gov/pubmed/33950983
http://dx.doi.org/10.1097/MD.0000000000025807
Descripción
Sumario:BACKGROUND: Runt-related transcription factor 1 (RUNX1) is one of the most frequently mutated genes in most of hematological malignancies, especially in acute myeloid leukemia. In the present study, we aimed to identify the key genes and microRNAs based on acute myeloid leukemia with RUNX1 mutation. The newly finding targeted genes and microRNA associated with RUNX1 may benefit to the clinical treatment in acute myeloid leukemia. MATERIAL/METHODS: The gene and miRNA expression data sets relating to RUNX1 mutation and wild-type adult acute myeloid leukemia (AML) patients were downloaded from The Cancer Genome Atlas database. Differentially expressed miRNAs and differentially expressed genes (DEGs) were identified by edgeR of R platform. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by Metascape and Gene set enrichment analysis. The protein–protein interaction network and miRNA-mRNA regulatory network were performed by Search Tool for the Retrieval of Interacting Genes database and Cytoscape software. RESULTS: A total of 27 differentially expressed miRNAs (25 upregulated and 2 downregulated) and 561 DEGs (429 upregulated and 132 downregulated) were identified. Five miRNAs (miR-151b, miR-151a-5p, let-7a-2-3p, miR-363-3p, miR-20b-5p) had prognostic significance in AML. The gene ontology analysis showed that upregulated DEGs suggested significant enrichment in MHC class II protein complex, extracellular structure organization, blood vessel development, cell morphogenesis involved in differentiation, embryonic morphogenesis, regulation of cell adhesion, and so on. Similarly, the downregulated DEGs were mainly enriched in secretory granule lumen, extracellular structure organization. In the gene set enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways, the RUNX1 mutation was associated with adherent junction, WNT signaling pathway, JAK-STAT signaling pathway, pathways in cancer, cell adhesion molecules CAMs, MAPK signaling pathway. Eleven genes (PPBP, APP, CCR5, HLA-DRB1, GNAI1, APLNR, P2RY14, C3AR1, HTR1F, CXCL12, GNG11) were simultaneously identified by hub gene analysis and module analysis. MicroRNA-363-3p may promote the development of RUNX1 mutation AML, targeting SPRYD4 and FNDC3B. In addition, the RUNX1 mutation rates in patient were obviously correlated with age, white blood cell, FAB type, risk(cyto), and risk(molecular) (P < .05). CONCLUSION: Our findings have indicated that multiple genes and microRNAs may play a crucial role in RUNX1 mutation AML. MicroRNA-363-3p may promote the development of RUNX1 mutation AML by targeting SPRYD4 and FNDC3B.