| Summary: | Abstract Background MiRNAs that are potential biomarkers for predicting prognosis for acute myeloid leukemia (AML) have been identified. However, comprehensive analyses investigating the association between miRNA expression profiles and AML survival remain relatively deficient. Method In the present study, we performed multivariate Cox’s analysis and principal component analysis (PCA) using data from The Cancer Genome Atlas (TCGA) to identify potential molecular signatures for predicting non-M3 AML prognosis. Result We found that patients who were still living were significantly younger at diagnosis than those who had died (P = 0.001). In addition, there was a marked difference in living status among different risk category groups (P = 0.022). A multivariate Cox model suggested that three miRNAs were potential biomarkers of non-M3 AML prognosis, including miR-181a-2, miR-25 and miR-362. Subsequently, PCA analyses were conducted to comprehensively represent the expression levels of these three miRNAs in each patient with a PCA value. According to the log-rank test, AML outcome for patients with lower PCA values was significantly different from those with higher PCA values (P < 0.001). Further bioinformatic analysis revealed the biological functions of the selected miRNAs. Conclusion We conducted a comprehensive analysis of TCGA non-M3 AML data, identifying three miRNAs that are significantly correlated with AML survival. PCA values for the identified miRNAs are valuable for predicting AML prognosis.
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