The NOTCH1/SNAIL1/MEF2C Pathway Regulates Growth and Self-Renewal in Embryonal Rhabdomyosarcoma
Bibliographic record
Abstract
Tumor-propagating cells (TPCs) share self-renewal properties with normal stem cells and drive continued tumor growth. However, mechanisms regulating TPC self-renewal are largely unknown, especially in embryonal rhabdomyosarcoma (ERMS)-a common pediatric cancer of muscle. Here, we used a zebrafish transgenic model of ERMS to identify a role for intracellular NOTCH1 (ICN1) in increasing TPCs by 23-fold. ICN1 expanded TPCs by enabling the de-differentiation of zebrafish ERMS cells into self-renewing myf5+ TPCs, breaking the rigid differentiation hierarchies reported in normal muscle. ICN1 also had conserved roles in regulating human ERMS self-renewal and growth. Mechanistically, ICN1 upregulated expression of SNAIL1, a transcriptional repressor, to increase TPC number in human ERMS and to block muscle differentiation through suppressing MEF2C, a myogenic differentiation transcription factor. Our data implicate the NOTCH1/SNAI1/MEF2C signaling axis as a major determinant of TPC self-renewal and differentiation in ERMS, raising hope of therapeutically targeting this pathway in the future.
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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".