ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2023
A novel prognostic model of methylation-associated genes in acute myeloid leukemia.
Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Artificial intelligence-based prognostic models in acute myeloid leukemia: systematic review and meta-analysis.Blood neoplasia · 2026Article
- Prediction of discoid lateral meniscus based on tibial plateau anatomical factors and machine learning.Frontiers in medicine · 2026Article
- Predictive Model of Gemtuzumab Ozogamicin Response in Childhood Acute Myeloid Leukemia on Event-Free Survival: Data Analysis Based on Trial AAML0531.Bioengineering (Basel, Switzerland) · 2025Article
- Bioinformatics-guided construction of a tumor microenvironment-derived prognostic model in acute myeloid leukemia.PloS one · 2025Article
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6 authors.
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Abstract
backgroundThere is growing evidence that methylation-associated genes (MAGs) play an important role in the prognosis of acute myeloid leukemia (AML) patients. Thus, the aim of this research was to investigate the impact of MAGs in predicting the outcomes of AML patients.
methodsThe expression profile and clinical information of patients were downloaded from public databases. A novel prognostic model based on 7 MAGs was established in the TCGA training cohort and validated in the GSE71014 dataset. To validate the clinical implications, the correlation between MAGs signature and drug sensitivity was further investigated.
results76 genes were screened out by the univariate Cox regression and significantly enriched in multiple methylation-related pathways. After filtering variables using LASSO regression analysis, 7 MAGs were introduced to construct the predictive model. The survival analysis showed overall survival of patients with the high-risk score was considerably poorer than that with the low-risk score in both the training and validating cohorts (p < 0.01). Furthermore, the risk score system as a prognostic factor also worked in the intermediate-risk patients based on ELN-2017 classification. Importantly, the risk score was demonstrated to be an independent prognostic factor for AML in the univariate and multivariate Cox regression analysis. Interestingly, GSEA analysis revealed that multiple metabolism-related pathways were significantly enriched in the high-risk group. Drug sensitivity analysis showed there was a significant difference in sensitivity of some drugs between the two groups.
conclusionWe developed a robust and accurate prognostic model with 7 MAGs. Our findings might provide a reference for the clinical prognosis and management of AML.
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