Metformin Induces Apoptosis and Cell Cycle Arrest Mediated by Oxidative Stress, AMPK and FOXO3a in MCF-7 Breast Cancer Cells
Bibliographic record
Abstract
Recent studies have demonstrated that the anti-diabetic drug, metformin, can exhibit direct antitumoral effects, or can indirectly decrease tumor proliferation by improving insulin sensitivity. Despite these recent advances, the underlying molecular mechanisms involved in decreasing tumor formation are not well understood. In this study, we examined the antiproliferative role and mechanism of action of metformin in MCF-7 cancer cells treated with 10 mM of metformin for 24, 48, and 72 hours. Using BrdU and the MTT assay, it was found that metformin demonstrated an antiproliferative effect in MCF-7 cells that occurred in a time- and concentration-dependent manner. Flow cytometry was used to analyze markers of cell cycle, apoptosis, necrosis and oxidative stress. Exposure to metformin induced cell cycle arrest in G0-G1 phase and increased cell apoptosis and necrosis, which were associated with increased oxidative stress. Gene and protein expression were determined in MCF-7 cells by real time RT-PCR and western blotting, respectively. In MCF-7 cells metformin decreased the activation of IRβ, Akt and ERK1/2, increased p-AMPK, FOXO3a, p27, Bax and cleaved caspase-3, and decreased phosphorylation of p70S6K and Bcl-2 protein expression. Co-treatment with metformin and H2O2 increased oxidative stress which was associated with reduced cell number. In the presence of metformin, treating with SOD and catalase improved cell viability. Treatment with metformin resulted in an increase in p-p38 MAPK, catalase, MnSOD and Cu/Zn SOD protein expression. These results show that metformin has an antiproliferative effect associated with cell cycle arrest and apoptosis, which is mediated by oxidative stress, as well as AMPK and FOXO3a activation. Our study further reinforces the potential benefit of metformin in cancer treatment and provides novel mechanistic insight into its antiproliferative role.
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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 | 0.000 |
| 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".