Identification of prognostic biomarkers and potential regulatory axes for acute myeloid leukemia based on a competitive endogenous RNA network [post]

Mingde Li, Ying Chen, Zhaowu Chen, Ming Chen, Xingxing Huo, Su Bu
2021 unpublished
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)
more » ... 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.
doi:10.21203/rs.3.rs-206813/v1 fatcat:3iwlts45n5ds3n3w53whgy4h4a