Constructing a tumor immune microenvironment-driven prognostic model in acute myeloid leukemia using bioinformatics and validation data.

ABSTRACT: The tumor immune microenvironment (TIME) is a critical determinant of prognosis in acute myeloid leukemia (AML). This study aimed to develop a prognostic model based on immune-related hub differentially expressed genes (hub-DEGs) to refine risk stratification and identify therapeutic targets. Transcriptomic and clinical data from 149 TCGA-AML patients were analyzed using ESTIMATE and xCell algorithms to infer immune scores. Differentially expressed genes (DEGs) between high/low immune score groups were identified, followed by functional enrichment, protein-protein interaction (PPI) network analysis for selecting the hub-DEGs with the highest degree scores, and univariate Cox regression to pinpoint prognostic genes. External validation was performed on 562 GEO-AML patients. The final genes

SUBMITTER: Navidinia AA 

PROVIDER: S-EPMC12274339 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature