Chemoprevention Activity of 25-Hydroxyvitamin D in the MMTV-PyMT Mouse Model of Breast Cancer
Bibliographic record
Abstract
Development of oncologic conditions is often accompanied by inadequate vitamin D status. The chemoprevention ability of this molecule is of high interest for breast cancer, the most common malignancy in women worldwide. Because current effective vitamin D analogues, including the naturally occurring active metabolite 1,25-dihydroxycholecalciferol (1,25(OH)2D), frequently cause hypercalcemia at pharmacologic doses, the development of safer molecules for clinical chemopreventive use is essential. This study examines whether exogenously supplied prohormone 25-hydroxycholecalciferol (25(OH)D) can delay tumor progression in vivo without hypercalcemic effects. A low vitamin D diet (25 IU/kg) in the non-immunodeficient MMTV-PyMT mouse model of metastatic breast cancer revealed a significant acceleration of mammary neoplasia compared with normal diet (1,000 IU/kg). Systemic perfusion of MMTV-PyMT mice with 25(OH)D or 1,25(OH)2D delayed tumor appearance and significantly decreased lung metastasis, and both metabolites reduced Ki-67, cyclin D1, and ErbB2 levels in tumors. Perfusion with 25(OH)D caused a 50% raise in tumor 1,25(OH)2D levels, indicating good tumor penetration and effective activation. Importantly, in contrast with 1,25(OH)2D, perfusion with 25(OH)D did not cause hypercalcemia. In vitro treatment of cultured MMTV-PyMT mammary tumor cells with 25(OH)D inhibited proliferation, confirming local activation of the prohormone in this system. This study provides an in vivo demonstration in a non-immunodeficient model of spontaneous breast cancer that exogenous 25(OH)D delays neoplasia, tumor growth, and metastasis, and that its chemoprevention efficacy is not accompanied by hypercalcemia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".