Dual Function of Pancreatic Endoplasmic Reticulum Kinase in Tumor Cell Growth Arrest and Survival
Bibliographic record
Abstract
Pancreatic endoplasmic reticulum kinase (PERK)-eIF2 alpha signaling, a component of the endoplasmic reticulum (ER) stress response, has been proposed as a therapeutic target due to its importance to cell survival in hypoxic tumors. In this study, we show that in addition to promoting survival, PERK can also suppress tumor growth of advanced carcinomas. Our results show that in squamous carcinoma T-HEp3 cells, which display low PERK-eIF2 alpha signaling, inducible activation of an Fv2E-PERK fusion protein results in a strong G(0)-G(1) arrest in vitro. Most importantly, Fv2E-PERK activation, in addition to promoting survival in vitro, inhibits T-HEp3 and SW620 colon carcinoma growth in vivo. Increased PERK activation is linked to enhanced p-eIF2 alpha levels, translational repression, and a decrease in Ki67, pH 3, and cycD1/D3 levels, but not to changes in angiogenesis or apoptosis. Experimental reduction of PERK activity, or overexpression of GADD34 in a spontaneously arising in vivo quiescent variant of HEp3 cells that displays strong basal PERK-eIF2 alpha activation, reverts their quiescent phenotype. We conclude that the growth-inhibitory function of PERK is preserved in tumors and upon proper reactivation can severely inhibit tumor growth through induction of quiescence. This is an important consideration in the development of PERK-based therapies, as its inhibition may facilitate the proliferation of slow-cycling or dormant tumor cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".