Uncovering prognostic markers and therapeutic targets in acute myeloid leukemia: Insights from differential gene expression and Mendelian randomization analysis

• This study utilizes bioinformatics to identify over 100 differentially expressed genes in acute myeloid leukemia (AML), with MIR9-1 downregulated and FLT3LG emerging as a predictive factor and therapeutic target. • Consistency clustering analysis reveals distinct subgroups with significant differences in overall survival rates, highlighting the prognostic significance of gene expression patterns in AML. • Univariate/multivariate independent prognostic analysis identifies 23 key genes, including DEFA1B, FLT3LG, CUX1, and ZMYM2, contributing to the differential prognosis of AML subgroups. • Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis uncovers important signaling pathways associated with AML development and progression. • Mendelian Randomization (MR) analysis demonstrates a negative correlation between the Transcriptional misregulation in cancer pathway and hypermethylation of CpG island pathway with AML, validating their potential protective roles. • FLT3LG involvement in cancer pathways and the PI3K-Akt signaling pathway, along with the protective role of the Transcriptional misregulation in cancer pathway and hypermethylation of CpG island pathway, suggests novel avenues for AML prognostication and therapeutic intervention. The development and prognosis of acute myeloid leukemia (AML) are influenced by multiple factors. This study utilized bioinformatics analysis to explore differentially expressed genes (DEGs) in acute myeloid leukemia (AML) and non-tumor tissues, evaluating their prognostic significance. Target gene data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were extracted for analysis. Over 100 DEGs were identified, with MIR9-1 exhibiting downregulated expression in AML. Survival analysis revealed significant differences in overall survival rates between subgroups, with Cluster 2 showing better outcomes. Notable DEGs, including DEFA1B, FLT3LG, CUX1, and ZMYM2, were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted relevant signaling pathways. Mendelian Randomization (MR) analysis unveiled a negative correlation between the “transcriptional misregulation in cancer pathway” and “hypermethylation of CpG island pathway” with AML. Sensitivity analysis demonstrated no heterogeneity or pleiotropy. Bayesian Weighted Mendelian Randomization (BWMR) validated MR results. Overall, this study identified potential therapeutic targets like FLT3LG, elucidated key genes for AML prognosis, and revealed protective roles of pathways through comprehensive bioinformatics analysis and Mendelian randomization.