ReviewCancers2025
Understanding and Targeting Metabolic Vulnerabilities in Acute Myeloid Leukemia: An Updated Comprehensive Review.
Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Exploiting Metabolic Vulnerabilities in Acute Myeloid Leukemia: Rationale and Evidence for Combining Metabolic Modulators with Conventional Chemotherapy.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Off-target anti-leukemic effects of antibiotics: mechanisms and therapeutic insights.Cancer chemotherapy and pharmacology · 2026Review
- Peroxisomal Lipid Metabolism as a Therapeutic Target in Leukemia.Molecular nutrition & food research · 2026Review
- Solubility based mechanistic profiling of combinatorial drug therapy.Nature communications · 2026Article
- Review
- Integrative single-cell and bulk transcriptomics define polyamine-associated cell states in acute myeloid leukemia and implicate CCT6A in polyamine homeostasis.Frontiers in immunology · 2026Article
- Leukemic Transdifferentiation: From Pathological Plasticity to Dendritic Cell-Based Immunotherapy.Biomedicines · 2025Review
- Metabolic Signature ofJournal of personalized medicine · 2025Review
- Targeting lipid metabolic vulnerabilities with small-molecule inhibitors in acute myeloid leukemia: Emerging insights and therapeutic opportunities.Tzu chi medical journalReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute Myeloid Leukemia (AML) is characterized by aggressive proliferation and metabolic reprogramming that support its survival and resistance to therapy. This review explores the metabolic distinctions between AML cells and normal hematopoietic stem cells (HSCs), emphasizing the role of altered mitochondrial function, oxidative phosphorylation (OXPHOS), and biosynthetic pathways in leukemic progression. AML cells exhibit distinct metabolic vulnerabilities, including increased mitochondrial biogenesis, reliance on glycolysis and amino acid metabolism, and unique signaling interactions that sustain leukemic stem cells (LSCs). These dependencies provide potential therapeutic targets, as metabolic inhibitors have demonstrated efficacy in disrupting AML cell survival while sparing normal hematopoietic cells. We examine current and emerging metabolic therapies, such as inhibitors targeting glycolysis, amino acid metabolism, and lipid biosynthesis, highlighting their potential in overcoming drug resistance. However, challenges remain in translating these strategies into clinical practice due to AML's heterogeneity and adaptability. Further research into AML's metabolic plasticity and precision medicine approaches is crucial for improving treatment outcomes. Understanding and exploiting AML's metabolic vulnerabilities could pave the way for novel, more effective therapeutic strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.