Metformin Triggers Ferroptosis in Leukemia Cells by Disrupting Lipid Metabolism
Metformin, the common diabetes drug, kills AML leukemia cells via ferroptosis—especially in IDH1/2- and FLT3-mutant subtypes with disrupted lipid metabolism.
Summary
Researchers found that metformin, an FDA-approved diabetes drug widely studied for longevity, induces a form of cell death called ferroptosis in acute myeloid leukemia (AML) cells. This effect was strongest in AML subtypes carrying IDH1/2 or FLT3 mutations, which already have disturbed lipid metabolism. By analyzing proteins, metabolites, and lipids from primary patient samples, the team identified that metformin increases reactive oxygen species and reshapes lipid profiles, pushing cells toward ferroptosis. Blocking lipid droplet formation with a DGAT1 inhibitor strongly amplified this effect, while iron chelators blocked it—confirming ferroptosis as the mechanism. These findings open a path for repurposing metformin as a targeted, mutation-aware cancer therapy.
Detailed Summary
Acute myeloid leukemia (AML) is an aggressive blood cancer with high relapse rates and limited treatment options. Leukemic cells are known to rewire their metabolism to sustain growth and resist therapy, with many AML subtypes showing strong reliance on oxidative phosphorylation (OXPHOS). While OXPHOS inhibitors have shown promise, most fail in clinical translation due to severe toxicities—such as lactic acidosis with IACS-010759. This study explored whether metformin, an FDA-approved, well-tolerated antidiabetic drug that inhibits mitochondrial complex I, could exploit metabolic vulnerabilities in AML while sparing healthy cells.
The researchers treated a genetically diverse panel of 27 primary AML patient samples ex vivo with metformin for 72 hours and measured apoptosis via Annexin V/DAPI staining. Metformin induced significant cell death across patient samples, while healthy cord blood-derived CD34+ cells showed no significant loss of viability—a favorable therapeutic window. To identify predictors of sensitivity, the team used label-free quantitative proteomics (11,272 proteins; n=30) and LC-MS metabolomics (172 metabolites; n=26) on sorted CD34+/CD117+ AML blasts. Single-sample gene set enrichment analysis (ssGSEA) revealed that metformin sensitivity positively correlated with enrichment in lipid biology, cholesterol metabolism, and ferroptosis gene sets.
Samples harboring FLT3-ITD and IDH1/2 mutations showed the highest enrichment for these metabolic signatures and greater metformin sensitivity. These mutant samples also displayed elevated CD36 expression—a major fatty acid transporter linked to AML relapse—and metabolomic profiling showed decreased levels of long-chain acylcarnitines, indicating elevated fatty acid oxidation (FAO). In isogenic TF1 IDH2-R140Q cell lines, metformin sensitivity was consistently greater than in wild-type TF1 cells, and RNA-seq confirmed upregulation of FAO enzymes (ACOX1, ACADVL) alongside downregulation of de novo FA synthesis enzymes including SCD.
Lipidomic analysis performed after metformin treatment revealed profound remodeling: increased triglyceride and polyunsaturated fatty acid production alongside upregulation of DGAT1, a key enzyme in lipid droplet formation. Functionally, metformin increased reactive oxygen species (ROS) levels and markers of ferroptosis—an iron-dependent, lipid peroxidation-driven cell death mechanism. Co-treatment of IDH2-mutant cells with palmitate (a saturated fatty acid) increased metformin sensitivity, and CD36 knockdown partially rescued cells from this effect. Critically, DGAT1 inhibition was strongly synergistic with metformin treatment, while iron chelators acted antagonistically, confirming that ferroptosis is the primary cell death modality.
These findings position metformin as a metabolically targeted agent that is especially effective in AML subtypes already primed for ferroptosis by their genetic mutations. The synergy with DGAT1 inhibition—which impairs cells' ability to sequester toxic lipids into protective lipid droplets—suggests a rational combination strategy. Clinically, this could translate into a genotype-guided use of metformin in IDH1/2- and FLT3-mutant AML, potentially combined with DGAT1 inhibitors. The study also highlights ferroptosis induction as a broader mechanism worth exploring for OXPHOS-dependent cancers, and reinforces metformin's growing relevance beyond diabetes in oncology and aging-related disease.
Key Findings
- Metformin induced significant apoptosis in 27 primary AML patient samples after 72 hours ex vivo, while healthy cord blood CD34+ cells (n=4 donors) showed no significant viability loss.
- ssGSEA on proteomics data (11,272 proteins, n=30) revealed that metformin sensitivity positively correlated (Spearman rho) with enrichment in lipid import, cholesterol metabolism, and ferroptosis gene sets.
- FLT3-ITD and IDH1/2-mutant AML samples showed the highest enrichment scores for lipid metabolism signatures and elevated CD36 protein expression vs. wild-type samples.
- Isogenic TF1 IDH2-R140Q cells were significantly more sensitive to metformin (1–25 mM range over 72h) than wild-type TF1 cells, with LC-MS metabolomics confirming reduced acylcarnitines indicating elevated FAO.
- Metformin treatment caused lipidomic remodeling including increased triglycerides and polyunsaturated fatty acids, and upregulated DGAT1 expression in AML cells.
- DGAT1 inhibition was strongly synergistic with metformin, while iron chelators acted antagonistically—confirming ferroptosis as the operative cell death mechanism.
- CD36 knockdown in IDH2-mutant cells partially rescued them from palmitate-enhanced metformin sensitivity, directly linking fatty acid uptake to ferroptosis susceptibility.
Methodology
The study used ex vivo treatment of 27 genetically characterized primary AML patient samples with metformin (72 hours), paired with label-free quantitative proteomics (11,272 proteins; n=30), LC-MS metabolomics (172 metabolites; n=26), lipidomics, and RNA sequencing on sorted CD34+/CD117+ blasts. Isogenic TF1 IDH2-R140Q and wild-type cell lines were used for mechanistic validation. Statistical methods included Spearman correlation, Mann-Whitney two-tailed t-tests, two-way ANOVA with Tukey's correction, and one-way ANOVA with Dunnett's correction. ssGSEA was applied to correlate metabolic pathway enrichment with metformin sensitivity.
Study Limitations
The study is primarily preclinical, relying on ex vivo patient samples and cell lines; in vivo validation in animal models and ultimately clinical trials are needed to confirm efficacy and safety at pharmacologically relevant concentrations. The metformin doses used (1–25 mM) exceed standard plasma levels achieved with oral antidiabetic dosing, raising questions about clinical translatability without dose optimization or alternative delivery strategies. The authors note genetic heterogeneity within patient samples as a potential confounding factor in sensitivity analyses.
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