The tumor suppressor FBW7 and the vitamin D receptor are mutual cofactors
Bibliographic record
Abstract
ABSTRACT The E3 ligase FBW7 targets drivers of cell cycle progression such as c-MYC for proteasomal degradation. It is frequently mutated in cancer, and is a tumor suppressor. Extensive epidemiological data links vitamin D deficiency to increased incidence of several cancers, although the underlying cancer-preventive mechanisms are poorly understood. Here, we show that hormonal 1,25-dihydroxyvitamin D3 (1,25D) rapidly stimulates the interaction of the VDR with FBW7, and that of FBW7 with c-MYC. In contrast, it blocks the association of FBW7 with c-MYC antagonist MXD1. 1,25D also enhances the association of FBW7, proteasome subunits, and ubiquitin with DNA-bound c-MYC, consistent with induced degradation of c-MYC on DNA. In addition to c-MYC, 1,25D accelerates the turnover of other FBW7 target proteins. Intriguingly, FBW7 is essential for optimal VDR gene expression. It is also recruited to VDR targets genes, and its depletion attenuates 1,25D-stimulated VDR DNA binding, transactivation, and cell cycle arrest. Thus, the VDR and FBW7 are mutual cofactors, which provides a molecular basis for the cancer-preventive actions of vitamin D through accelerated turnover of FBW7 target proteins.
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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) | 0.003 | 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".