Tumor Suppressor microRNAs, miR-100 and -125b, Are Regulated by 1,25-dihydroxyvitamin D in Primary Prostate Cells and in Patient Tissue
Bibliographic record
Abstract
MiR-100 and miR-125b are lost in many cancers and have potential function as tumor suppressors. Using both primary prostatic epithelial cultures and laser capture-microdissected prostate epithelium from 45 patients enrolled in a vitamin D3 randomized trial, we identified miR-100 and -125b as targets of 1,25-dihydroxyvitamin D3 (1,25D). In patients, miR-100 and -125b levels were significantly lower in tumor tissue than in benign prostate. Similarly, miR-100 and -125b were lower in primary prostate cancer cells than in cells derived from benign prostate. Prostatic concentrations of 1,25D positively correlated with these miRNA levels in both prostate cancer and benign epithelium, showing that patients with prostate cancer may still benefit from vitamin D3. In cell assays, upregulation of these miRNAs by 1,25D was vitamin D receptor dependent. Transfection of pre-miR-100 and pre-miR-125b in the presence or absence of 1,25D decreased invasiveness of cancer cell, RWPE-2. Pre-miR-100 and pre-miR-125b decreased proliferation in primary cells and cancer cells respectively. Pre-miR-125b transfection suppressed migration and clonal growth of prostate cancer cells, whereas knockdown of miR-125b in normal cells increased migration indicates a tumor suppressor function. 1,25D suppressed expression of previously bona fide mRNA targets of these miRNAs, E2F3 and Plk1, in a miRNA-dependent manner. Together, these findings show that vitamin D3 supplementation augments tumor suppressive miRNAs in patient prostate tissue, providing evidence that miRNAs could be key physiologic mediators of vitamin D3 activity in prevention and early treatment of prostate cancer.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".