ERK-associated changes in E2F4 phosphorylation, localization and transcriptional activity during mitogenic stimulation in human intestinal epithelial crypt cells
Bibliographic record
Abstract
BACKGROUND: The transcription factor E2F4 controls proliferation of normal and cancerous intestinal epithelial cells. E2F4 localization in normal human intestinal epithelial cells (HIEC) is cell cycle-dependent, being cytoplasmic in quiescent differentiated cells but nuclear in proliferative cells. However, the intracellular signaling mechanisms regulating such E2F4 localization remain unknown. RESULTS: Treatment of quiescent HIEC with serum induced ERK1/2 activation, E2F4 phosphorylation, E2F4 nuclear translocation and G1/S phase transition while inhibition of MEK/ERK signaling by U0126 prevented these events. Stimulation of HIEC with epidermal growth factor (EGF) also led to the activation of ERK1/2 but, in contrast to serum or lysophosphatidic acid (LPA), EGF failed to induce E2F4 phosphorylation, E2F4 nuclear translocation and G1/S phase transition. Furthermore, Akt and GSK3β phosphorylation levels were markedly enhanced in serum- or LPA-stimulated HIEC but not by EGF. Importantly, E2F4 phosphorylation, E2F4 nuclear translocation and G1/S phase transition were all observed in response to EGF when GSK3 activity was concomitantly inhibited by SB216763. Finally, E2F4 was found to be overexpressed, phosphorylated and nuclear localized in epithelial cells from human colorectal adenomas exhibiting mutations in APC and KRAS or BRAF genes, known to deregulate GSK3/β-catenin and MEK/ERK signaling, respectively. CONCLUSIONS: The present results indicate that MEK/ERK activation and GSK3 inhibition are both required for E2F4 phosphorylation as well as its nuclear translocation and S phase entry in HIEC. This finding suggests that dysregulated E2F4 nuclear localization may be an instigating event leading to hyperproliferation and hence, of tumor initiation and promotion in the colon and rectum.
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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".