ING1b-inducible microRNA203 inhibits cell proliferation
Bibliographic record
Abstract
BACKGROUND: The ING family of type II tumour suppressors serve as both epigenetic 'readers' and target histone acetyl transferase (HAT) and histone deacetylase (HDAC) 'writers' of the epigenetic histone code. The ING1 protein has also been implicated in regulating microRNA (miRNA) levels. In this study, we identify a link between ING1b and the miRNA epigenetic network. METHODS: Primary fibroblasts infected with adenoviruses expressing GFP control or GFP plus ING1b were examined for alterations in miRNA profiles using a miRNA PCR array. Additional experiments confirmed specificity and consequences of altered miRNA expression. RESULTS: MicroRNAs miR-203, miR-375, miR-449b and miR-200c were increased by ING1b overexpression. Ectopic expression of miR-203 inhibited U2OS and MDA-MB-231 cancer cell growth, and induced G1 cell cycle arrest in U2OS cells as estimated by flow cytometry. Transfection with miR-203 inhibitor reversed the proliferation inhibition induced by ING1b in U2OS cells. CHIP assays showed that ING1b bound to the promoter of miR-203. Western blot analyses showed that CDK6, c-Abl and Src were downregulated by the transfection of miR-203. CONCLUSION: These results indicate that ING1b epigenetically regulates several miRNAs including miR-203. The several-fold increase in miR-203 by ING1b might inhibit cancer cell proliferation through coordinate downregulation of CDK6, c-Abl and Src.
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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) | 0.003 | 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".