IRF1 Downregulation by Ras/MEK Is Independent of Translational Control of IRF1 mRNA
Bibliographic record
Abstract
Oncogenic activation of Ras/MEK downregulates the expression of interferon regulatory factor 1 (IRF1), which is a prerequisite for oncolytic viruses to replicate in cancer cells [1]. Moreover, restoration of IRF1 expression is essential to induce apoptosis of cancer cells treated with a MEK inhibitor [2]. However, the molecular mechanisms that underlie IRF1 downregulation by Ras/MEK remain unclear. In this study, we determined whether Ras/MEK activation modulates IRF1 expression at its translational level. MEK inhibition increased the activity of IRF1 promoter construct in Ras transformed NIH3T3 cells and wild type MEF, but not in IRF1 deficient MEF, indicating that IRF1 protein is required for the transcriptional activation of IRF1. By conducting reporter analysis using IRF1 5'- and 3'- UTR constructs, we determined that cis elements on 5'- and 3'-UTR of IRF1 mRNA are not involved in the IRF1 regulation by Ras/MEK. We further compared the recruitment of ribosomes to IRF1 mRNA in RasV12 cells treated with or without the MEK inhibitor by conducting polysome analysis. No difference was observed in the polysomal distribution of IRF1 mRNA between RasV12 cells treated with and without the MEK inhibitor. These results suggest that regulation of IRF1 translation is independent of IRF1 downregulation by Ras/MEK.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".