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Identification of MTMR2 as an AML-associated candidate biomarker derived from lipid metabolism-related transcriptomic
Chenchen Liu1, Yueyuan Pan1, Minggui Chen2
1Zhanjiang Institute of Clinical Medicine, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, China.
Background:
Acute myeloid leukemia (AML) is a diverse malignant hematologic disorder with poor clinical outcomes. Increasing evidence suggests that metabolic reprogramming, particularly lipid metabolism, contributes to AML progression and may offer new opportunities for biomarker discovery and therapeutic targeting. However, lipid metabolism-related hub genes with diagnostic and prognostic relevance in AML have not been systematically characterized.
Methods:
Expression profiles from GSE114868 and GSE9476 were analyzed to identify lipid metabolism-associated differentially expressed genes. Functional enrichment, single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA), machine-learning-based feature selection, diagnostic receiver operating characteristic (ROC) analysis, survival analysis, and immune infiltration analysis were performed. MTMR2 expression was further validated by RT-qPCR in an expanded clinical cohort of AML patients and healthy controls, and selected lipid-related clinical parameters were explored.
Results:
Lipid metabolism-related pathways were significantly altered in AML samples. Integration of differential expression analysis, WGCNA, LASSO regression, random forest analysis, and SVM-RFE identified MTMR2 as a candidate lipid metabolism-associated biomarker. MTMR2 was markedly upregulated in AML across independent datasets and showed good diagnostic performance. Kaplan-Meier analysis suggested an association between high MTMR2 expression and poorer overall survival. High MTMR2 expression was also associated with immune- and inflammation-related transcriptional features and with altered inferred immune-cell infiltration patterns. RT-qPCR analysis confirmed higher MTMR2 expression in AML samples, and exploratory clinical analysis showed lower ApoA1 and LDL-C levels and higher TG levels in AML patients than in healthy controls.
Conclusion:
This study identifies MTMR2 as a lipid metabolism-associated candidate biomarker in AML and provides preliminary clinical evidence supporting its increased expression and association with altered lipid-related parameters. These findings support further mechanistic and clinical validation of MTMR2 in larger independent AML cohorts.
