Metformin-induced ablation of microRNA 21-5p releases Sestrin-1 and CAB39L antitumoral activities
Bibliographic record
Abstract
Metformin is a commonly prescribed type II diabetes medication that exhibits promising anticancer effects. Recently, these effects were found to be associated, at least in part, with a modulation of microRNA expression. However, the mechanisms by which single modulated microRNAs mediate the anticancer effects of metformin are not entirely clear and knowledge of such a process could be vital to maximize the potential therapeutic benefits of this safe and well-tolerated therapy. Our analysis here revealed that the expression of miR-21-5p was downregulated in multiple breast cancer cell lines treated with pharmacologically relevant doses of metformin. Interestingly, the inhibition of miR-21-5p following metformin treatment was also observed in mouse breast cancer xenografts and in sera from 96 breast cancer patients. This modulation occurred at the levels of both pri-miR-21 and pre-miR-21, suggesting transcriptional modulation. Antagomir-mediated ablation of miR-21-5p phenocopied the effects of metformin on both the clonogenicity and migration of the treated cells, while ectopic expression of miR-21-5p had the opposite effect. Mechanistically, this reduction in miR-21-5p enhanced the expression of critical upstream activators of the AMP-activated protein kinase, calcium-binding protein 39-like and Sestrin-1, leading to AMP-activated protein kinase activation and inhibition of mammalian target of rapamycin signaling. Importantly, these effects of metformin were synergistic with those of everolimus, a clinically relevant mammalian target of rapamycin inhibitor, and were independent of the phosphatase and tensin homolog status. This highlights the potential relevance of metformin in combinatorial settings for the treatment of breast cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".