Pirh2, a Ubiquitin E3 Ligase, Inhibits p73 Transcriptional Activity by Promoting Its Ubiquitination
Bibliographic record
Abstract
p73, a homolog of the tumor suppressor p53, transactivates many p53 target genes, leading to apoptosis or cell-cycle arrest. p73 has recently been reported to play an important role in tumor suppression in a mouse model. Here, we show that Pirh2 physically interacted with p73 and downregulated p73 function through its E3 ligase activity. Pirh2 promoted p73 ubiquitination in vivo and in vitro. Intriguingly, Pirh2 primarily used K63-linked chains to ubiquitinate p73 in vitro, but in vivo, Pirh2 utilized K11-, K29-, K48-, and K63-linked chains to promote p73 ubiquitination. Depletion of Pirh2 by siRNA significantly reduced the ubiquitination of p73 in p53 null cells. Ectopic expression of Pirh2 repressed p73-dependent transcriptional activity, but the levels of p73 were not decreased. We consistently showed that ablation of endogenous Pirh2 restored p73-mediated transactivational activity. We found that Pirh2 repressed p73 transcriptional activity by directly inhibiting the p73 transcript, and p73 repression by Pirh2 was required for p73-dependent transcriptional activity and G(1) arrest but not for apoptosis. This study provides evidence that the ubiquitination of p73 mediated by Pirh2 represents an important pathway for controlling the suppressive function of p73. Furthermore, the data suggest a link between the transcriptional activity of p73 and its ubiquitination.
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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) | 0.001 | 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".