Abstract LB-169: Metformin reduces somatic cell mutation rate by inhibiting mitochondrial ROS production: relevance to cancer prevention
Bibliographic record
Abstract
Abstract Pharmacoepidemiological studies provide evidence that use of metformin, a drug commonly prescribed for type II diabetes, is associated with a substantial reduction in cancer risk. Experimental models show that metformin inhibits the growth of certain neoplasms by cell autonomous mechanisms such as activation of AMP kinase with secondary inhibition of protein synthesis, or by an indirect mechanism involving reduction in gluconeogenesis leading to a decline in insulin levels and reduced proliferation of insulin-responsive cancers. Here we show that metformin attenuates paraquat-induced elevations in reactive oxygen species (ROS), DNA damage and mutations, but has no effect on similar changes induced by H202, indicating a reduction in endogenous ROS production. Metformin also inhibited Ras-induced ROS production and DNA damage. Our results reveal previously unrecognized inhibitory effects of metformin on ROS production and somatic cell mutation, providing a novel mechanism for the reduction in cancer risk associated with exposure to this drug. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-169. doi:1538-7445.AM2012-LB-169
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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) | 0.010 | 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".