Novel Roles for Staufen1 in Embryonal and Alveolar Rhabdomyosarcoma via c-myc-dependent and -independent events
Bibliographic record
Abstract
Rhabdomyosarcoma is the most common soft tissue sarcoma in children and young adults. Rhabdomyosarcomas are skeletal muscle-like tumours that typically arise in muscle beds, and express key myogenic regulatory factors. However, their developmental program remains blocked in the proliferative phase with cells unable to exit the cell cycle to fuse into myotubes. Recently, we uncovered a key role for the RNA-binding protein Staufen1 during myogenic differentiation through the regulation of c-myc translation. Given the known implication of c-myc in rhabdomyosarcoma, we hypothesized in the current work that Staufen1 controls rhabdomyosarcoma tumorigenesis. Here, we report for the first time the novel role of Staufen1 in cancer, specifically in rhabdomyosarcoma. We demonstrate that Staufen1 is markedly upregulated in human rhabdomyosarcoma tumours and cell lines as compared to normal skeletal muscle. Moreover, we show that Staufen1 promotes the tumorigenesis of embryonal and alveolar rhabdomyosarcoma subtypes both in cell culture and in animal models. Finally, our data demonstrate that Staufen1 has differential roles in embryonal versus alveolar rhabdomyosarcoma through the control of proliferative and apoptotic pathways, respectively. Together, these results provide the first evidence for Staufen1's direct implication in cancer biology. Accordingly, Staufen1 thus represents a novel target for the development of future therapeutic strategies for rhabdomyosarcoma.
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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".