Abstract
PURPOSE: The study aims to investigate the impact of m6A modulators on drug resistance and the immune microenvironment in acute myeloid leukemia (AML). The emergence of drug resistance is a significant factor that contributes to relapse and refractory AML, leading to a poor prognosis. METHODS: The AML transcriptome data were retrieved from the TCGA database. The "oncoPredict" R package was utilized to assess the sensitivity of each sample to cytarabine (Ara-C) and classify them into distinct groups. Differential expression analysis was performed to identify m6A modulators differentially expressed between the two groups. Select Random Forest (RF) to build a predictive model. Model performance was evaluated using calibration curve, clinical decision curve, and clinical impact curve. The impacts of METTL3 on Ara-C sensitivity and immune microenvironment in AML were examined using GO, KEGG, CIBERSORT, and GSEA analyses. RESULTS: Seventeen out of 26 m6A modulators exhibited differential expression between the Ara-C-sensitive and resistant groups, with a high degree of correlation. We selected the 5 genes with the highest scores in the RF model to build a reliable and accurate prediction model. METTL3 plays a vital role in m6A modification, and further analysis shows its impact on the sensitivity of AML cells to Ara-C through its interaction with 7 types of immune-infiltrating cells and autophagy. CONCLUSION: This study utilizes m6A modulators to develop a prediction model for the sensitivity of AML patients to Ara-C, which can assist in treating AML drug resistance by targeting mRNA methylation.