ArticleFrontiers in oncology2022
A distinct lipid metabolism signature of acute myeloid leukemia with prognostic value.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Integrative phosphoproteomic network analysis identifies CAMK2D as a shared regulator of TPD52 family proteins in cancer.Protoplasma · 2026Article
- Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.Scientific reports · 2025Article
- From "metabolic storm" to "immune paralysis": the dynamic evolution of macrophages and metabolism reprogramming in ARDS.Frontiers in immunology · 2025Review
- Review
- Identifying cancer prognosis genes through causal learning.Briefings in bioinformatics · 2024Article
- Lipid metabolism-related gene signature predicts prognosis and unveils novel anti-tumor drugs in specific type of diffuse large B cell lymphoma.Molecular medicine (Cambridge, Mass.) · 2024Article
- RummaGEO: Automatic mining of human and mouse gene sets from GEO.Patterns (New York, N.Y.) · 2024Article
- RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO.bioRxiv : the preprint server for biology · 2024Article
- Prognostic implications of metabolism-related genes in acute myeloid leukemia.Frontiers in genetics · 2024Article
- Article
- An Overview on Lipid Droplets Accumulation as Novel Target for Acute Myeloid Leukemia Therapy.Biomedicines · 2023Review
- Diverse targets of SMN2-directed splicing-modulating small molecule therapeutics for spinal muscular atrophy.Nucleic acids research · 2023Article
- Role of Diacylglycerol Kinases in Acute Myeloid Leukemia.Biomedicines · 2023Article
- Melatonin: a modulator in metabolic rewiring in T-cell malignancies.Frontiers in oncology · 2023Review
- A novel prognostic classification integrating lipid metabolism and immune co-related genes in acute myeloid leukemia.Frontiers in immunology · 2023Article
- Orchestral role of lipid metabolic reprogramming in T-cell malignancy.Frontiers in oncology · 2023Review
- Untargeted metabolomic and lipidomic analyses reveal lipid dysregulation in the plasma of acute leukemia patients.Frontiers in molecular biosciences · 2023Article
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8 authors.
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Abstract
Background: Acute myeloid leukemia (AML) is a highly aggressive hematological malignancy characterized by extensive genetic abnormalities that might affect the prognosis and provide potential drug targets for treatment. Reprogramming of lipid metabolism plays important roles in tumorigenesis and progression and has been newly recognized a new hallmark of malignancy, and some related molecules in the signal pathways could be prognostic biomarkers and potential therapeutic targets for cancer treatment. However, the clinical value of lipid metabolism reprogramming in AML has not been systematically explored. In this study, we aim to explore the clinical value of lipid metabolism reprogramming and develop a prognostic risk signature for AML. Methods: We implemented univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO analysis to develop the risk signature with six lipid metabolism-related genes (LDLRAP1, PNPLA6, DGKA, PLA2G4A, CBR1, and EBP). The risk scores of samples were calculated and divided into low- and high-risk groups by the median risk score. Results: Survival analysis showed the high-risk group hold the significantly poorer outcomes than the low-risk group. The signature was validated in the GEO datasets and displayed a robust prognostic value in the stratification analysis. Multivariate analysis revealed the signature was an independent prognostic factor for AML patients and could serve as a potential prognostic biomarker in clinical evaluation. Furthermore, the risk signature was also found to be closely related to immune landscape and immunotherapy response in AML. Conclusions: Overall, we conducted a comprehensive analysis of lipid metabolism in AML and constructed a risk signature with six genes related to lipid metabolism for the malignancy, prognosis, and immune landscape of AML, and our study might contribute to better understanding in the use of metabolites and metabolic pathways as the potential prognostic biomarkers and therapeutic targets for AML.
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