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

Abstract

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<0.001). In both the experimental and validation cohorts, individuals classified as high risk exhibited a poorer prognosis. The 5-year area under the curve (AUC) was calculated as 0.715 for the TCGA-LAML cohort and 0.646 for GSE37642. Additionally, analysis using ssGSEA demonstrated that the high-risk group exhibited higher levels of immune cell infiltration compared to low-risk group. RT-qPCR results indicated that the expression levels of LARP1, EIF4E2 and IFIT5 were consistent with the results of the bioinformatic analysis.Conclusions: In summary, the m7G-related genes are potential prognostic biomarkers for patients with AML.

Keywords

• Acute myeloid leukemia
• N7-Methylguanine RNA methylation
• prognostic signature
• LASSO cox regression analysis
• immune cell infiltration
• real-time quantitative PCR