Comprehensive investigation of the clinical significance of long non-coding RNA HOXA-AS2 in acute myeloid leukemia using genome-wide RNA sequencing dataset.

2021 
Objective: The present study aimed to determine the prognostic value of HOXA cluster antisense RNA2 (HOXA-AS2) in acute myeloid leukemia (AML), and to explore its potential molecular mechanisms. We also screening of potential drugs targeting HOXA-AS2 in AML. Methods: The level 3 raw genome-wide RNA sequencing dataset of AML was download from The Cancer Genome Atlas (TCGA) Data Portal, and the potential molecular mechanisms and drugs prediction of HOXA-AS2 in AML were explored using multiple bioinformatics analysis approaches. Results: TCGA AML cohort dataset indicated that HOXA-AS2 was significantly up-regulated in AML bone marrow tissues, and high HOXA-AS2 expression was related to poor overall survival (log-rank P=0.0284, hazard ratio 1.640, 95% confidence interval 1.046-2.573). Functional enrichment of differentially expressed genes (DEGs) suggested that the difference in prognosis between AML patients with high- and low-HOXA-AS2 expression may be due to differences in biological processes and pathways, including cell adhesion, angiogenesis, mitogen-activated protein kinase, cell differentiation, and other biological processes, and phosphatidylinositol 3 kinase-protein kinase B and Wnt signaling pathways. We also screened out three potential HOXA-AS2-targeted therapeutic drugs for AML, megestrol, carmustine, and cefoxitin, based on these DEGs. Functional enrichment analysis of HOXA-AS2-co-expressed genes revealed that HOXA-AS2 may act a part in AML by regulating nuclear factor-κB transcription factor activity, DNA methylation, angiogenesis, apoptosis, cell migration, Toll-like receptor 4, and Wnt signaling pathways. Conclusion: Our findings suggest that HOXA-AS2 is up-regulated in the bone marrow in patients with AML, and may serve as a novel prognostic biomarker for AML.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    70
    References
    0
    Citations
    NaN
    KQI
    []