MEDU-10. THERAPEUTIC TARGETING OF STEM CELL SELF-RENEWAL IN CHILDHOOD MEDULLOBLASTOMA: STRATEGIES FOR BLOCKING RECURRENCE
Bibliographic record
Abstract
Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Group 3 MB patients face the highest incidence of metastasis and poor overall survival. The early onset and aggressive nature of MB suggest a stem cell origin, where a highly self-renewing transformed cell of the postnatal cerebellum drives MB tumorigenesis. In this work, we explore the therapeutic value of activating WNT signaling and targeting other essential drivers of self-renewal, BMI1 and MSI1. A small molecule BMI1 inhibitor, PTC-028, induced a remarkable decrease in self-renewal, while reducing local and spinal metastatic disease in recurrent MB, which is striking as no prior drug has shown efficacy against recurrent Group 3 MB. Although mouse and human neural stem cells (NSCs) express BMI1 and are mildly sensitive to BMI1 inhibitors, no significant toxicity was observed in NSCs upon PTC-028 treatment, at doses that effectively kill MB cells. Another novel therapeutic paradigm includes activating Wnt signaling in otherwise non-Wnt MB, which abrogates self-renewal and tumorigenicity of these aggressive tumors. For safe and non-toxic activation of Wnt in preclinical models, we identified L807mts, a novel inhibitor that functions through a substrate-to-inhibitor conversion mechanism within the catalytic site of GSK. A final therapeutic strategy lies in the discovery of the targetable MB-specific interactome of the RNA binding protein (RBP) Musashi1. shRNA knockdown of Msi1 decreased the self-renewal capacity of MB stem cells, significantly decreased tumor burden and increased survival in our PDX model. Comparative eCLIP (enhanced cross-linking and immunoprecipitation) of MB stem cells and normal NSCs, combined with mass spectrometry and RNA-sequencing of shMSI1 MB cells has elucidated novel therapeutic targets in interactome of MSI1. Characterization and therapeutic targeting of self-renewal mechanisms may provide an opportunity to limit treatment-resistant stem cell populations from driving patient relapse in Group 3 MB, a disease currently lacking any targeted therapies.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".