SUMOylation of the lysine-less tumor suppressor p14ARF counters ubiquitylation-dependent degradation
Bibliographic record
Abstract
p14ARF is a lysine-less tumor suppressor that enhances SUMOylation of its interactors. Although p14ARF is known to interact with the E2 SUMO conjugating enzyme UBC9, the link between ARF and SUMOylation is poorly understood and the potential impact of SUMOylation on p14ARF is unknown. Here we show that SUMO2 conjugates to the N-terminus of p14ARF and stabilizes it. Either depleting UBC9 or pharmacologically inhibiting SUMOylation, induces p14ARF degradation. In contrast, blocking ubiquitination or NEDDylation, with TAK-243 or MLN4924/Pevonedistat respectively, increases p14ARF SUMOylation and restores p14ARF levels when SUMOylation is blocked. Treatment with MLN4924 also causes p14ARF-dependent mRNA upregulation of the SUMOylation components SUMO1, SUMO2, and UBC9, globally augmenting SUMOylation. Finally, p14ARF contributes to MLN4924-driven cytotoxicity of prostate cancer cells. Our results provide evidence that, despite lacking lysine, p14ARF is SUMOylated and this modification is critical to counter ubiquitin driven degradation and establishes a new link between inhibition of NEDDylation and SUMOylation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".