Activation of the Integrated Stress Response Regulates Lovastatin-induced Apoptosis
Bibliographic record
Abstract
Lovastatin, a potent inhibitor of mevalonate synthesis, can readily induce apoptosis in a subset of human tumor types including head and neck squamous cell carcinomas (HNSCC). We recently identified activation of transcription factor (ATF) 4 as a lovastatin induced gene in HNSCC cells. ATF4 plays a significant role in regulating cellular responses to a wide variety of stress inducers known as the integrated stress response (ISR). These cell stresses lead to the phosphorylation of eukaryotic initiation factor (eIF) 2alpha shutting down global protein translation. However, the translation of ATF4 is enhanced. In this study, lovastatin treatment induced eIF2alpha phosphorylation and inhibited global protein translation. ATF4 expression was induced followed by increased ATF3 and CHOP expression, targets of ATF4 activity, in SCC25 HNSCC cells. In CHOP(-/-) murine embryonic fibroblasts (MEFs), lovastatin-induced apoptosis was attenuated indicating a role for CHOP in this response. Furthermore, the eIF2alpha kinase GCN2 mediates lovastatin induction of ATF4 and lovastatin-induced apoptosis was also attenuated in GCN2(-/-) MEFs. The pro-drug version of lovastatin has potential proteasome inhibitory activity and recently a variety of well established proteasome inhibitors were shown to activate the ISR. In this study, neither the pro-drug nor the active forms of lovastatin had any significant effect on proteasome activity. Therefore, lovastatin, by targeting mevalonate synthesis, is a potent inducer of the ISR through a novel and as yet unrecognized mechanism.
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 | 0.000 |
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".