NFAT3 and TGF-β/SMAD3 regulate the expression of miR-140 in osteoarthritis
Bibliographic record
Abstract
INTRODUCTION: MicroRNAs (miRNAs) down-regulate their target genes. The intronic miR-140, present in the WW domain containing E3 ubiquitin protein ligase 2 (WWP2) gene, decreases the expression of genes that play detrimental roles in osteoarthritis (OA). As the expression level of miR-140 is significantly decreased in human OA chondrocytes, we investigated its regulation in those cells. METHODS: Gene expression in human chondrocytes was determined by quantitative polymerase chain reaction (qPCR) and gene silencing was done in OA chondrocytes by transient transfection with specific small interfering RNAs (siRNAs). Binding sites of the miR-140 regulatory sequence (rsmiR-140) were identified by mutagenesis and chromatin immunoprecipitation (ChIP) in OA chondrocytes. The effects of translocation on OA chondrocytes were determined by immunocytochemistry and qPCR. RESULTS: In contrast to miR-140, the expression of WWP2 was similar in both normal and OA cells, suggesting that miR-140 has an additional level of regulation. rsmiR-140 showed activity and predicted binding sites for nuclear matrix transcription factor 4 (NMP4), myc-associated zinc (MAZ), nuclear factor of activated T-cells (NFAT), and mothers against decapentaplegic homolog 3 (SMAD3). Silencing NFAT3 (P ≤0.01) and SMAD3 (P ≤0.05) differentially regulated miR-140 independently of WWP2. Silencing NFAT5 decreased both miR-140 and WWP2 (P ≤0.003 and P ≤0.05, respectively). NFAT3 activation increased and transforming growth factor-β (TGF-β) decreased rsmiR-140 activity. Mutagenesis of rsmiR-140 and ChIP assays identified binding sites at which NFAT3 (activator) and SMAD3 (repressor) directly regulated miR-140. TGF-β interfered with NFAT3 translocation, and subsequently with miR-140 expression. CONCLUSIONS: This is the first study to provide evidence of a regulatory mechanism of miR-140 independent of WWP2, and new and differential roles for NFAT3 and SMAD3 in the OA process in the regulation of miR-140 transcription. Such knowledge could advance therapeutic strategies targeting OA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".