Wilms Tumor Suppressor, WT1, Cooperates with MicroRNA-26a and MicroRNA-101 to Suppress Translation of the Polycomb Protein, EZH2, in Mesenchymal Stem Cells
Bibliographic record
Abstract
Hereditary forms of Wilms arise from developmentally arrested clones of renal progenitor cells with biallelic mutations of WT1; recently, it has been found that Wilms tumors may also be associated with biallelic mutations in DICER1 or DROSHA, crucial for miRNA biogenesis. We have previously shown that a critical role for WT1 during normal nephrogenesis is to suppress transcription of the Polycomb group protein, EZH2, thereby de-repressing genes in the differentiation cascade. Here we show that WT1 also suppresses translation of EZH2. All major WT1 isoforms induce an array of miRNAs, which target the 3' UTR of EZH2 and other Polycomb-associated transcripts. We show that the WT1(+KTS) isoform binds to the 5' UTR of EZH2 and interacts directly with the miRNA-containing RISC to enhance post-transcriptional inhibition. These observations suggest a novel mechanism through which WT1 regulates the transition from resting stem cell to activated progenitor cell during nephrogenesis. Our findings also offer a plausible explanation for the fact that Wilms tumors can arise either from loss of WT1 or loss of miRNA processing enzymes.
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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 | 0.000 |
| 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 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".