p53 Pre- and Post-Binding Event Theories Revisited: Stresses Reveal Specific and Dynamic p53-Binding Patterns on the <i>p21</i> Gene Promoter
Bibliographic record
Abstract
p53 is a master transcription factor that prevents neoplasia and genomic instability. It is an important target for anticancer drug design. Understanding the molecular mechanisms behind its transcriptional activities in normal cells is a prerequisite to further understand the deregulation effected by mutant p53 in cancerous cells. Currently, how p53 coordinates transcription programs in response to stress remains unclear. One theory proposes that stresses induce pre-binding events that direct p53 to bind to specific response elements, whereas a second posits that, in response to stress, p53 binds most response elements and post-binding events then regulate transcription initiation. It is critical to establish the relevance of both theories and investigate whether stresses induce specific p53-binding patterns correlated with effector gene induction. Using unique in cellulo genomic footprinting experiments, we studied p53 binding to the five response elements of p21 in response to stresses and monitored p21 mRNA variant transcription. We show clear footprints of p53 bound to response elements in living cells and reveal that the binding of p53 to response elements is transient, subject to dynamic changes during stress responses, and influenced by response element pentamer orientations. We show further that stresses lead to specific p53-binding patterns correlated with particular p21 mRNA variant transcription profiles and that p53 binding is necessary but not sufficient to induce p21 transcription. Our results indicate that pre- and post-binding events act together to regulate adapted stress responses; this paves the way to the unification of pre- and post-binding event theories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".