MDM2 mediates p73 ubiquitination: a new molecular mechanism for suppression of p73 function
Bibliographic record
Abstract
// Hong Wu 1 , Roger P. Leng 1 1 Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada Correspondence to: Hong Wu, e-mail: hwu8@ualberta.ca Roger P. Leng, e-mail: rleng@ualberta.ca Keywords: ubiquitin E3 ligase, ubiquitination, tumor suppressor, oncogene, protein degradation Received: March 11, 2015 Accepted: May 14, 2015 Published: May 26, 2015 ABSTRACT The protein p73, a homologue of the tumor suppressor protein p53, is capable of inducing apoptosis and cell cycle arrest. MDM2 is transcriptionally activated by p73 and represses the functions of p73, including p73-dependent transactivation and growth suppression. However, the molecular mechanism of this repression is unknown. In this study, we show that MDM2 mediates p73 ubiquitination. MDM2 mainly utilizes K11, K29 and K63-linked chains to mediate p73 ubiquitination in vivo and in vitro . However, MDM2 is unable to promote p73 degradation in most tested cell lines. Surprisingly, we observe that overexpression of Mdm2 promotes p73 degradation mainly through Itch in Mdm2-null MEFs. We further find that Itch interacts with the transfected Mdm2 in Mdm2-null cells. Moreover, our findings reveal that the E3 ligase activity of MDM2 is required to repress p73-dependent apoptosis and cell cycle arrest but not p73-dependent transcriptional activity. Furthermore, the data suggest a link between p73 ubiquitination/MDM2 E3 ligase activity and p73 biological functions.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".