Activation of p53 by MEG3 Non-coding RNA
Bibliographic record
Abstract
MEG3 is a maternally expressed imprinted gene suggested to function as a non-coding RNA. Our previous studies suggest that MEG3 has a function of tumor suppression. The tumor suppressor p53 plays a central role in tumor suppression and mediates the functions of many other tumor suppressors. Therefore, we hypothesized that MEG3 functions through activation of p53. We found that transfection of expression constructs for MEG3 and its isoforms results in a significant increase in p53 protein levels and dramatically stimulates p53-dependent transcription from a p53-responsive promoter. Using this as the functional assay, we demonstrated that the open reading frames encoded by MEG3 transcripts are not required for MEG3 function, and the folding of MEG3 RNA is critical to its function, supporting the concept that MEG3 functions as a non-coding RNA. We further found that MEG3 stimulates expression of the growth differentiation factor 15 (GDF15) by enhancing p53 binding to the GDF15 gene promoter. Interestingly, MEG3 does not stimulate p21(CIP1) expression, suggesting that MEG3 can regulate the specificity of p53 transcriptional activation. p53 degradation is mainly mediated by the mouse double minute 2 homolog (MDM2). We found that MDM2 levels were down-regulated in cells transfected with MEG3, suggesting that MDM2 suppression contributes at least in part to p53 accumulation induced by MEG3. Finally, we found that MEG3 is able to inhibit cell proliferation in the absence of p53. These data suggest that MEG3 non-coding RNA may function as a tumor suppressor, whose action is mediated by both p53-dependent and p53-independent pathways.
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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) | 0.001 | 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".