Phosphorylation of the tumor suppressor p33 <sup>ING1b</sup> at Ser‐126 influences its protein stability and proliferation of melanoma cells
Bibliographic record
Abstract
ABSTRACT ING (inhibitor of growth) tumor suppressors regulate cell‐cycle checkpoints, apoptosis, and ultimately tumor suppression. Among the ING family members, p33 ING1b is the most intensively studied and plays an important role in the cellular stress response to DNA damage. Here we demonstrate that there is basal phosphorylation of p33 ING1b at Ser‐126 in normal physiological conditions and that this phosphorylation is increased on DNA damage. The mutation of Ser‐126 to alanine dramatically shortened the half‐life of p33 ING1b . Furthermore, we found that both Chk1 and Cdk1 can phosphorylate this residue. Interestingly, while Cdk1 can phosphorylate p33 ING1b at Ser‐126 in nonstress conditions, Chk1 predominantly phosphory‐lates this residue on DNA damage, which suggests that p33 ING1b is a downstream target of the ATM/ATR response cascade to genotoxic stress. More importantly, our data indicate that the Ser‐126 residue plays a key role in regulating the expression of cyclin B1 and proliferation of melanoma cells.—Garate, M., Campos, E. I., Bush, J. A., Xiao, H., Li, G. Phosphorylation of the tumor suppressor p33ING1b at Ser‐126 influences its protein stability and proliferation of melanoma cells. FASEB J. 21, 3705–3716 (2007)
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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) | 0.002 | 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".