Identification of prognostic biomarkers and potential regulatory axes for acute myeloid leukemia based on a competitive endogenous RNA network
Background Acute myeloid leukemia (AML) is a common heterogeneous hematological malignancy with unclear pathogenesis and high mortality. Non-coding RNAs have recently received extensive attention. This study explored the potential mechanisms of interaction during the development of AML by analyzing a competitive endogenous RNA (ceRNA) network. Methods To obtain differentially expressed genes (DEGs), the transcripts and clinical AML data were downloaded from The Cancer Genome Atlas (TCGA)
... Atlas (TCGA) database. Bioinformatic analysis was used to predict the function annotation and RNA interaction. The data were used to construct a ceRNA regulatory network and survival analysis was used to discover key genes and predict potential regulatory axes. Quantitative Real-time PCR (qRT-PCR) was used to detect DEGs in HL-60 and THP-1 cell lines to verify the prediction. Results A ceRNA regulatory AML network with 164 lncRNA-miRNA-mRNA regulatory axes was constructed and visualized by Cytoscape software. Six lncRNAs were screened as potential prognostic factors for AML by survival analysis. Additionally, hsa-mir-206 and NFAT5 were discovered as key nodes in the ceRNA network. A CTB-193M12.1/hsa-mir-206/NFAT5 axis that was consistent with the ceRNA theory was identified. The qRT-PCR result showed that, compared with the normal control group, the expression of hsa-mir-206 in HL-60 and THP-1 cells was significantly decreased, while that of NFAT5 was moderately increased. Conclusions Therefore, the obtained ceRNA network and the CTB-193M12.1/hsa-mir-206/NFAT5 axis here may provide new view for exploring the pathogenic mechanisms of AML. NFAT5 and hsa-mir-206 were novel clinical predictors that may become key genes in AML.