TRTH-29. CONTEXT-SPECIFIC TUMOR SUPPRESSIVE FUNCTION OF THE CANONICAL WNT PATHWAY IN PEDIATRIC MEDULLOBLASTOMA HIGHLIGHTS A THERAPEUTIC STRATEGY FOR TREATMENT-REFRACTORY SUBGROUPS
Bibliographic record
Abstract
Current molecular subgroups of childhood medulloblastoma (MB) recognize distinct disease entities of which activated Wnt signaling is associated with a distinct subgroup and the best overall outcome. In contrast, non-Wnt MBs are characterized by metastatic disease, increased rate of recurrence, and poor overall survivorship. Given the excellent clinical outcome in Wnt-driven MB, we aimed to convert treatment-resistant MB subgroups 3 and 4 into an ostensibly benign tumor. Activated Wnt signaling by way of Wnt agonists decreased in vitro self-renewal of primary MB cells. Comparative RNA-sequencing of control and transgenic lines containing a stabilized beta-catenin mutant demonstrated a reduction in self-renewal genes following beta-catenin overexpression, including Sox2 and Bmi1. In order to validate the therapy-sensitive nature of Wnt-activated cells, we developed stable human Group 3 and 4 patient-derived lines containing a 7XTOPFlash reporter to determine the presence of endogenous Wnt signaling. Rare subclonal Wnt-active cells demonstrated a reduced self-renewal and tumor-initiating capacity through in vivo limiting dilution assays when compared to bulk Wnt-inactive cells from Group 3 and 4 MBs. The therapeutic relevance of these findings were demonstrated with an in vivo survival advantage in mice with orthotopic injections of cells containing stabilized beta-catenin overexpression or endogenous Wnt-active cells. Resulting xenograft tumors were smaller in size, maintained a lower rate of proliferation, and reduction in MB self-renewal genes. To develop a rationale clinical therapeutic, we used a novel substrate-competitive peptide inhibitor for GSK. Treatment with our peptide inhibitor showed a significant reduction in tumor burden and metastatic disease with a corresponding increase in survival of patient-derived Group 3 and 4 tumors that were otherwise treatment-resistant. Our work establishes activated Wnt signaling as a novel treatment paradigm in childhood MB, identifies a rationale therapeutic approach for recurrent MB, and provides evidence for the context-specific tumor suppressive function of the canonical Wnt pathway.
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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) | 0.002 | 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".