ArticleDiscover oncology2025
Prognostic and immunological characterization of elderly acute myeloid leukemia evaluated by butyrate metabolism-related genes.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe diagnostic and therapeutic value of butyrate metabolism-related genes (BMRGs) in cancer has been widely applied, however, their prognosis and potential therapeutic value in elderly acute myeloid leukemia (EAML) have not been fully elucidated.
methodsThe clinical information and gene expression data of the EAML patients were obtained from the GEO database and TCGA database. Firstly, Least Absolute Shrinkage and Selection Operator (LASSO) and univariate Cox regression were used to screen for BMRGs significantly associated with the prognosis of EAML patients. A prognostic risk stratification model for EAML patients was then constructed based on multivariate COX regression. Prognostic value of the prognostic risk stratification model was confirmed by Kaplan-Meier curves and validated on an independent external queue dataset. Meanwhile, the biological pathways, immune microenvironment and drug sensitivity of EAML patients with different prognostic risk stratification were further analyzed.
results4 BMRGs (CCT5, CYP19A1, SECISBP2 and SERINC5) were ultimately identified as genes associated with the prognosis of EAML. A prognostic risk model was constructed based on multivariate COX regression and 4 BMRGs. The Kaplan-Meier curves and independent external queue dataset confirm the prognostic model’s excellent diagnostic value. Immune infiltration analysis’ results confirm 4 BMRGs are correlated with various immune cells significantly.
conclusionThis was the first comprehensive analysis highlighting the prognostic significance of BMRGs in EAML. The findings not only reveal novel gene biomarkers with potential clinical value but also offer a theoretical foundation for advancing personalized treatment strategies in EAML.
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