Molecular mechanisms underlining the role of metformin as a therapeutic agent in lung cancer
Bibliographic record
Abstract
BACKGROUND: Metformin, a first-line therapeutic for type 2 diabetes, has been studied for its potential use in cancer treatment following a number of epidemiological studies that have demonstrated reduced cancer incidence and mortality rates among patients treated with the drug. As yet, however, there remains significant uncertainty about the molecular mechanisms by which metformin exerts its anti-cancer effects. Herein, we summarize the evidence surrounding the anti-lung cancer effects of metformin. CONCLUSIONS: Specifically, we explore protein targets of metformin, including AMPK, PP2A, IRF-1/YAP and HGF and we outline the proposed mechanisms of action for metformin in lung cancer, with particular attention given to apoptosis and autophagy. We also closely examine the synergistic activity of metformin with existing cancer treatment regimens, such as TKI's, platinum-based agents and immune therapeutics. In addition to considering preclinical and clinical studies, we also dissect and contextualize the limitations and inconsistencies of the current literature, especially those of epidemiological studies. Finally, we offer a potential trajectory for future research in this rapidly evolving area of basic and clinical oncology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".