Mitochondria Transfer from Mesenchymal Stem Cells Confers Chemoresistance to Glioblastoma Stem Cells through Metabolic Rewiring
Bibliographic record
Abstract
Glioblastomas (GBM) are heterogeneous tumors with high metabolic plasticity. Their poor prognosis is linked to the presence of glioblastoma stem cells (GSC), which support resistance to therapy, notably to temozolomide (TMZ). Mesenchymal stem cells (MSC) recruitment to GBM contributes to GSC chemoresistance, by mechanisms still poorly understood. Here, we provide evidence that MSCs transfer mitochondria to GSCs through tunneling nanotubes, which enhances GSCs resistance to TMZ. More precisely, our metabolomics analyses reveal that MSC mitochondria induce GSCs metabolic reprograming, with a nutrient shift from glucose to glutamine, a rewiring of the tricarboxylic acid cycle from glutaminolysis to reductive carboxylation and increase in orotate turnover as well as in pyrimidine and purine synthesis. Metabolomics analysis of GBM patient tissues at relapse after TMZ treatment documents increased concentrations of AMP, CMP, GMP, and UMP nucleotides and thus corroborate our in vitro analyses. Finally, we provide a mechanism whereby mitochondrial transfer from MSCs to GSCs contributes to GBM resistance to TMZ therapy, by demonstrating that inhibition of orotate production by Brequinar (BRQ) restores TMZ sensitivity in GSCs with acquired mitochondria. Altogether, these results identify a mechanism for GBM resistance to TMZ and reveal a metabolic dependency of chemoresistant GBM following the acquisition of exogenous mitochondria, which opens therapeutic perspectives based on synthetic lethality between TMZ and BRQ. Significance: Mitochondria acquired from MSCs enhance the chemoresistance of GBMs. The discovery that they also generate metabolic vulnerability in GSCs paves the way for novel therapeutic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".