Activating transcription factor 4 plays a major role in shaping the transcriptional response to isoginkgetin in HCT116 cells
Bibliographic record
Abstract
Activating transcription factor 4 (ATF4) plays a central role in the integrated stress response (ISR) and one overlapping branch of the unfolded protein response (UPR). We recently reported that the splicing inhibitor isoginkgetin (IGG) induced ATF4 protein along with several known ATF4-regulated transcripts in a response that resembled the ISR and UPR. However, the contribution of ATF4-dependent and -independent transcriptional responses to IGG exposure was not known. Here we used RNA-sequencing in HCT116 colon cancer cells and an isogenic subline lacking ATF4 to investigate the contribution of ATF4 to IGG-induced changes in gene expression. Approximately 85% of the IGG-responsive DEGs in HCT116 cells were also differentially expressed in response to the ER stressor thapsigargin (Tg) and these were enriched for genes associated with the UPR and ISR. Most of these were positively regulated by IGG with impaired responses in the ATF4-deficient cells. Nonetheless, there were DEGs that responded similarly in both cell lines. The ATF4-independent IGG-induced DEGs included several metal responsive transcripts encoding metallothionines and a zinc transporter. Taken together, the predominant IGG response was ATF4-dependent in these cells and resembled the UPR and ISR while a second less prominent response involved the ATF4-independent regulation of metal responsive mRNAs.
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 | 0.001 |
| 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".