PEA-15 Is Inhibited by Adenovirus E1A and Plays a Role in ERK Nuclear Export and Ras-induced Senescence
Bibliographic record
Abstract
Oncogenic ras activates multiple signaling pathways to enforce cell proliferation in tumor cells. The ERK1/2 mitogen-activated protein kinase pathway is required for the transforming effects of ras, and its activation is often sufficient to convey mitogenic stimulation. However, in some settings oncogenic ras triggers a permanent cell cycle arrest with features of cellular senescence. How the Ras/ERK1/2 pathway activates different cellular programs is not well understood. Here we show that ERK1/2 localize predominantly in the cytoplasm during ras-induced senescence. This cytoplasmic localization seems to be dependent on an active nuclear export mechanism and can be rescued by the viral oncoprotein E1A. Consistent with this hypothesis, we showed that E1A dramatically down-regulated the expression of the ERK1/2 nuclear export factor PEA-15. Also, RNA interference against PEA-15 restored the nuclear localization of phospho-ERK1/2 in Ras-expressing primary murine embryo fibroblasts and stimulated their escape from senescence. Because senescence prevents the transforming effect of oncogenic ras, our results suggest a tumor suppressor function for PEA-15 that operates by means of controlling the localization of phospho-ERK1/2.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".