A novel N7-Methylguanine-related gene signature for predicting prognosis in acute myeloid leukemia: bioinformatic analysis and experimental verification

Background: The involvement of N7-Methylguanine (m7G) RNA methylation regulators in the progression of different types of solid cancers in humans has been established. However, the specific impact of m7G-related genes on Acute myeloid leukemia (AML) remains uncertain. Our research aims to build a novel signature of M7Gs that could enhance our understanding of the molecular heterogeneity in leukemia.Methods: The RNA-seq and clinical data of patients with AML were acquired from the UCSC XENA website. Prognostic-related genes were selected using LASSO to construct a risk-scoring model. External datasets were utilized to validate the effectiveness of the model, and the mRNA expressions of candidate genes were measured using RT-qPCR.Results: A prognostic model was developed using a risk-scoring approach based on three candidate genes (IFIT5, EIF4E2, and LARP1) and their respective risk coefficients. Multivariate Cox regression analysis revealed a significant association between the risk score and overall survival (p