Novel cis-trans interactions are involved in post-transcriptional regulation of cyclin-dependent kinase inhibitor p21<sup>WAF1/CIP1</sup> mRNA
Bibliographic record
Abstract
Background: A variety of pathways target CDKI p21WAF1/CIP1 expression at transcriptional, post-transcriptional as well as translational levels. We previously found that cell growth suppressing retinoid CD437 enhanced expression of p21WAF1/CIP1 and DNA damage inducible GADD45 proteins in part by elevating their mRNA stability.Results: Here, we investigated molecular mechanisms of CD437-dependent post-transcriptional regulation of p21WAF1/CIP1 expression. By utilizing MDA-MB-468 HBC cells expressing chimeric rabbit b-globin-p21WAF1/CIP1 transcripts we mapped multiple CD437-responsive sequences located within positions 1195 to 1795 of the 3′-untranslated region of p21WAF1/CIP1 mRNA. Several cytoplasmic proteins present in MDA-MB-468, MCF-7 HBC as well as HL-60R leukemia cells bound specifically, in vitro, with these CD437-responsive sequences. CD437 treatment of cells resulted in elevated binding of ~85 kD and ~55 kD cytoplasmic proteins with putative CD437-responsive sequences. A 12 nt RNA sequence (5′-UGUGGUGGCACA-3′) present within CD437-responsive region of p21WAF1/CIP1 mRNA displayed specific and elevated binding with the above noted proteins. Treatment of cells with ActD or CHX prior to CD437 exposure did not abrogate RNA-protein interactions. However, treatment of cytoplasmic protein extracts with proteinase K or alkaline phosphatase resulted in loss of RNA-protein interactions.Conclusions: CD437 regulates cell growth in part by regulating stability of p21WAF1/CIP1 mRNA that involves specific RNA-protein interactions that are phosphorylation-dependent, while not requiring nascent transcription or protein synthesis.
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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) | 0.005 | 0.002 |
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".