Enhancing circadian clock function in cancer cells inhibits tumor growth
Bibliographic record
Abstract
BACKGROUND: Circadian clocks control cell cycle factors, and circadian disruption promotes cancer. To address whether enhancing circadian rhythmicity in tumor cells affects cell cycle progression and reduces proliferation, we compared growth and cell cycle events of B16 melanoma cells and tumors with either a functional or dysfunctional clock. RESULTS: We found that clock genes were suppressed in B16 cells and tumors, but treatments inducing circadian rhythmicity, such as dexamethasone, forskolin and heat shock, triggered rhythmic clock and cell cycle gene expression, which resulted in fewer cells in S phase and more in G1 phase. Accordingly, B16 proliferation in vitro and tumor growth in vivo was slowed down. Similar effects were observed in human colon carcinoma HCT-116 cells. Notably, the effects of dexamethasone were not due to an increase in apoptosis nor to an enhancement of immune cell recruitment to the tumor. Knocking down the essential clock gene Bmal1 in B16 tumors prevented the effects of dexamethasone on tumor growth and cell cycle events. CONCLUSIONS: Here we demonstrated that the effects of dexamethasone on cell cycle and tumor growth are mediated by the tumor-intrinsic circadian clock. Thus, our work reveals that enhancing circadian clock function might represent a novel strategy to control cancer progression.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".