Metformin in cancer: translational challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The anti-diabetic drug metformin is rapidly emerging as a potential anti-cancer agent. Metformin, effective in treating type 2 diabetes and the insulin resistance syndromes, improves insulin resistance by reducing hepatic gluconeogenesis and by enhancing glucose uptake by skeletal muscle. Epidemiological studies have consistently associated metformin use with decreased cancer incidence and cancer-related mortality. Furthermore, numerous preclinical and clinical studies have demonstrated anti-cancer effects of metformin, leading to an explosion of interest in evaluating this agent in human cancer. The effects of metformin on circulating insulin levels indicate a potential efficacy towards cancers associated with hyperinsulinaemia; however, metformin may also directly inhibit tumour growth. In this review, we describe the mechanism of action of metformin and summarise the epidemiological, clinical and preclinical evidence supporting a role for metformin in the treatment of cancer. In addition, the challenges associated with translating preclinical results into therapeutic benefit in the clinical setting will be discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 it