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Updated: Sep 14, 2025

Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants
Published on: June 6, 2025
Identification of Prognostic-Related Genes in Acute Myeloid Leukemia: A Study Based on TCGA Data Analysis
Fatemeh Sadat Shafiei1, Saeid Abroun2, Sadaf Vahdat3
1Department of Medical Laboratory Sciences, School of Paramedical Sciences, Zanjan University of Medical Sciences, Zanjan, Zanjan Province, Iran.
Abstract:
Acute myeloid leukemia (AML) is the most common type of leukemia in adults, primarily caused by multiple gene mutations and abnormal gene expression. Molecular heterogeneity among AML patients can lead to the variation of treatment outcomes, and the prognostic significance of genetic disruptions is crucial for treatment decisions. Therefore, in this study, we intended to identify novel potential prognosis-related genes in AML patients. This study comprehensively assessed transcriptomic data of primary AML patients from TARGET and BEAT-AML cohorts from the TCGA database. The common differentially expressed mRNAs (DEmRNAs) of the study groups were determined and screened to identify genes that indicated a correlation between their expression levels and the overall survival (OS) of AML patients. Moreover, RT-PCR was used to compare the expression of the identified prognosis-related genes between AML patients and non-leukemic groups to confirm the obtained bioinformatics data. The analysis resulted in the identification of 39 common significant DEmRNAs in both cohorts. Moreover, among the identified common genes, the expression levels of two genes, MME and RBM11, significantly correlated with the OS of AML patients; it was revealed that there was a significant negative correlation between a higher survival rate in AML patients and the lower expression of MME (log-rank P = 1.3*10-7 and Hazard Ratio (HR = 1.38 (1.22-1.56)) and RBM11 (log-rank P = 0.016 and HR = 1.25 (1.04-1.5)). Furthermore, RT-PCR data confirmed the expected differential expression of identified genes between patient and control samples. In conclusion, our investigation resulted in the identification of two potential prognosis-related genes that can be used in further prognostic evaluation studies.

