Integrated Gene Expression and Network Analysis Identifies Molecular Differences Between FLT3-Positive and FLT3-Negative AML

FLT3 mutations, particularly internal tandem duplications (FLT3-ITD), occur in a substantial proportion of acute myeloid leukemia (AML) cases and are associated with aggressive disease biology and poor clinical outcomes. Although the introduction of FLT3 inhibitors has improved response rates, relapse remains frequent, highlighting the need to identify additional molecular targets that cooperate with FLT3 signaling. In this study, we performed an integrative transcriptomic and network-based analysis comparing FLT3-mutant (FLT3+) and FLT3-wildtype (FLT3-) AML to uncover reproducible molecular alterations and functionally relevant gene networks. Differential gene expression analysis was conducted using two independent public AML datasets (GSE10358 and GSE14468). Shared differentially expressed genes (DEGs) were identified and subjected to protein–protein interaction and pathway enrichment analyses to define coordinated functional modules. This approach revealed a robust set of common DEGs (n = 29) consistently dysregulated across cohorts, with enrichment of genes involved in cell adhesion, migration, and cytoskeletal organization. Network analysis highlighted a highly interconnected module related to cytoskeletal dynamics and cell–microenvironment interactions, suggesting altered niche engagement in FLT3-mutant AML. From these analyses, four network-prioritized genes (EPAS1, IQGAP1, PTPN4, and CTHRC1) were selected for experimental validation. Quantitative real-time PCR confirmed significantly increased expression of all four genes in FLT3+ AML compared to FLT3- controls. Furthermore, survival analysis identified EPAS1, encoding the hypoxia-inducible factor HIF-2?, as prognostically relevant, with higher expression associated with shorter overall survival. Together, these findings demonstrate that FLT3-mutant AML is characterized by coordinated dysregulation of cytoskeletal, adhesion, and microenvironment-adaptive pathways. The identified gene network provides mechanistic insight into FLT3-driven disease biology and highlights candidate targets that may complement existing FLT3-directed therapies to improve patient outcomes.