Hyper-Activation of Notch3 Amplifies the Proliferative Potential of Rhabdomyosarcoma Cells
Bibliographic record
Abstract
Rhabdomyosarcoma (RMS) is a pediatric myogenic-derived soft tissue sarcoma that includes two major histopathological subtypes: embryonal and alveolar. The majority of alveolar RMS expresses PAX3-FOXO1 fusion oncoprotein, associated with the worst prognosis. RMS cells show myogenic markers expression but are unable to terminally differentiate. The Notch signaling pathway is a master player during myogenesis, with Notch1 activation sustaining myoblast expansion and Notch3 activation inhibiting myoblast fusion and differentiation. Accordingly, Notch1 signaling is up-regulated and activated in embryonal RMS samples and supports the proliferation of tumor cells. However, it is unable to control their differentiation properties. We previously reported that Notch3 is activated in RMS cell lines, of both alveolar and embryonal subtype, and acts by inhibiting differentiation. Moreover, Notch3 depletion reduces PAX3-FOXO1 alveolar RMS tumor growth in vivo. However, whether Notch3 activation also sustains the proliferation of RMS cells remained unclear. To address this question, we forced the expression of the activated form of Notch3, Notch3IC, in the RH30 and RH41 PAX3-FOXO1-positive alveolar and in the RD embryonal RMS cell lines and studied the proliferation of these cells. We show that, in all three cell lines tested, Notch3IC over-expression stimulates in vitro cell proliferation and prevents the effects of pharmacological Notch inhibition. Furthermore, Notch3IC further increases RH30 cell growth in vivo. Interestingly, knockdown of Notch canonical ligands JAG1 or DLL1 in RMS cell lines decreases Notch3 activity and reduces cell proliferation. Finally, the expression of Notch3IC and its target gene HES1 correlates with that of the proliferative marker Ki67 in a small cohort of primary PAX-FOXO1 alveolar RMS samples. These results strongly suggest that high levels of Notch3 activation increase the proliferative potential of RMS cells.
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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) | 0.002 | 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".