Regulation of E2F1 phosphorylation, subcellular distribution and stability in keratinocytes.
Bibliographic record
Abstract
101 E2F transcription factors play key roles in epidermal keratinocyte growth, differentiation and transformation. We have shown that E2F1 protein stability and subcellular localization are regulated by a Ca2+-regulated signaling cascade that triggers activation of protein kinase C δ and η, as well as p38β mitogen-activated protein kinase (MAPK). This pathway activates CRM1-mediated E2F1 nuclear export and degradation ( Oncogene 26: 1147, 2007). We further investigated the mechanism of p38β MAPK regulation of E2F1, and have determined that E2F1 forms a complex with p38β MAPK primarily in differentiated keratinocytes. In vitro kinase assays revealed that E2F1 is phosphorylated by p38β MAPK on Ser403 and Thr433. We next determined the role of E2F1 phosphorylation by assessing alterations in subcellular localization and protein stability in phosphorylation E2F1 mutants expressed in keratinocytes. Whereas wild type E2F1 exhibits a predominantly cytoplasmic distribution in differentiated keratinocytes, E2F1(S403A), E2F1(T433A) and E2F1(S403A;T433A) are retained in the nucleus. These mutants are also more stable in differentiating keratinocytes, relative to wild type E2F1. Phosphorylation of Ser403 and Thr433 may also be crucial for normal differentiation, as evidenced by the failure of differentiating keratinocytes exogenously expressing E2F1(S403A), E2F1(T433A) and E2F1(S403A;T433A) to express involucrin, a marker of differentiation in the epidermis. In conclusion, we have identified a previously unrecognized mode of E2F1 regulation involving phosphorylation of Ser403 and Thr433 by p38β MAPK during epidermal maturation. Mutation of these residues results in E2F1 nuclear retention and increased protein stability, which appears to interfere with proper keratinocyte differentiation.
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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) | 0.001 | 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".