1,25‐Dihydroxy vitamin D prevents tumorigenesis by inhibiting oxidative stress and inducing tumor cellular senescence in mice
Bibliographic record
Abstract
Human epidemiological studies suggest that 1,25(OH)2D3 deficiency might increase cancer incidence, but no spontaneous tumors have been reported in mice lacking 1,25(OH)2D3 or deficient in its receptor. In our study, we detected, for the first time, diverse types of spontaneous tumors in l,25(OH)2D3 deficient mice more than 1 year of age. This was associated with increased oxidative stress, cellular senescence and senescence‐associated secretory phenotype molecules, such as hepatocyte growth factor, mediated via its receptor c‐Met. Furthermore, 1,25(OH)2D3 prevented spontaneous tumor development. We also demonstrated that l,25(OH)2D3 deficiency accelerates allograft tumor initiation and growth by increasing oxidative stress and DNA damage, activating oncogenes, inactivating tumor suppressor genes, stimulating malignant cell proliferation and inhibiting their senescence; in contrast, supplementation with exogenous l,25(OH)2D3 or antioxidant, or knock‐down of the Bmi1 or c‐Met oncogene, largely rescued the phenotypes of allograft tumors. Results from our study suggest that 1,25(OH)2D3 deficiency enhances tumorigenesis by increasing malignant cell oxidative stress and DNA damage, stimulating microenvironmental cell senescence and a senescence‐associated secretory phenotype, and activating oncogenes and inactivating tumor suppressor genes, thus increasing malignant cell proliferation. Our study provides direct evidence supporting the role of vitamin D deficiency in increasing cancer incidence. Conversely, 1,25(OH)2D3 prevented spontaneous tumor development, suggesting that this inhibitory effect prevents the initiation and progression of tumorigenesis, thus provides a mechanistic basis for 1,25(OH)2D3 to prevent tumorigenesis in an aging organism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".