C.2 Dexamethasone induced p57-mediated quiescence contributes to chemotherapy resistance in sonic hedgehog medulloblastoma
Bibliographic record
Abstract
Background: Medulloblastoma (MB), the most common malignant pediatric brain tumor, is often incurable upon recurrence, largely driven by treatment-resistant quiescent cells. While quiescent SHH MB populations have been identified, the mechanisms driving their chemoresistance remain unclear. Here, we investigate the role of the cell cycle inhibitor p57 in inducing quiescence and show that dexamethasone, widely used in MB management, promotes p57-mediated quiescence, potentially reducing treatment efficacy. Methods: To assess p57’s role, we introduced a TMP-inducible p57 construct into Ptch1 +/- SHH MB cells and treated them with vincristine. We also treated Ptch1 +/- SHH MB cells with dexamethasone and quantified p57 levels and cell cycle states using high-throughput immunofluorescence imaging. Results: In culture, nuclear p57 was enriched in Sox2+ and Nestin+ stem-like SHH MB cells relative to rapidly-cycling Atoh1+ cells. Stabilizing p57 with TMP increased G 0 -phase cells six-fold, exhibiting survival to vincristine doses that caused complete cell death in controls. Dexamethasone treatment increased nuclear p57 by 40% and G 0 -phase cells by 15% in Ptch1 +/- cells, while doubling G 0 -phase cells in Ptch1 +/- ; Trp53 -/- cells. Conclusions: These findings suggest dexamethasone promotes p57-mediated quiescence, potentially contributing to chemoresistance in SHH MB. This raises critical concerns about the use of dexamethasone in MB treatment, as it may inadvertently enhance tumor recurrence.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".