p53 binding to the p21 promoter is dependent on the nature of DNA damage
Bibliographic record
Abstract
p53 Is a tumor suppressor that integrates signals from different stress induced signalling pathways, regulates cell cycle arrest, senescence, apoptosis and DNA repair. How p53 dictates cell fate is unclear. As a major transcriptional target of p53 in response to cellular stress, p21 is a key component in cell cycle control and apoptosis, directing an anti-apoptotic response following DNA damage. It is therefore likely that p53-dependent regulation of p21 contributes, at least in part, how p53 influences cellular outcome upon DNA damage. Here we compare the p53-dependent transcriptional regulation of p21 in response to DNA damage by ultraviolet (UV) radiation and ionizing radiation (IR). We demonstrate that despite comparable levels of p53 accumulation by both types of DNA damage, IR causes significant, early accumulation of p21 not seen in UV-damaged cells, with a substantially different cell cycle profile. Whereas UV and IR both target p21 protein for degradation immediately after DNA damage, differential post-damage p21 transcription is accountable for the disparity in p21 protein levels. Chromatin immunoprecipitation studies reveal that p53 displays a clear bias against the p21 promoter in UV-damaged cells compared to IR-damaged cells. We note differential post-translational modifications of nuclear p53 between UV and IR treatment. Furthermore we demonstrate that this disparity correlated with reduced histone acetylation on the TATA box within the p21 promoter following UV treatment. This suggests that the nature of DNA damage enables p53 to selectively discriminate between promoters in the induction of target genes, thereby regulating their expression and subsequent cellular outcome.
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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 | 0.000 |
| 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".