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

Abstract

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.

Keywords

• Mendelian Randomization
• Acute myeloid leukemia
• FLT3LG
• KEGG