PS1 - 169 Discovering the Treatment Refractory BTIC Population in Group 3 Medulloblastoma through Therapy Adapted Patient-Derived Human Mouse Xenograft (PDX) Model
Bibliographic record
Abstract
Medulloblastoma (MB), the most common malignant pediatric brain tumor, is categorized into four molecular subgroups. Given the high rate of metastatic dissemination at diagnosis and recurrence in Group 3 MBs, these patients have the worst clinical outcome with a 5-year survivorship of approximately 50%. By adapting the existing COG (Children’s Oncology Group) Protocol for children with newly diagnosed high-risk MB, for treatment of immuno-deficient mice intracranially engrafted with human MB brain tumour initiating cells we aim to identify and characterize the treatment-refractory cell population in Group 3 MBs. Mice were sacrificed at multiple time points during the course of tumor development and therapy: (i) at engraftment; (ii) post-radiation; (iii) post-radiation and chemotherapy; and (iv) at MB recurrence. MB cell populations recovered separately from brains and spines were comprehensively profiled for gene expression analysis, stem cell and molecular features to generate a global, comparative profile of MB cells through therapy. We report a higher expression of CD133, Sox2 and Bmi1 in addition to increased self-renewal capacity following chemoradiotherapy treatment. The enrichment map constructed from global gene expression analysis showed an increase in pathways regulating self-renewal, DNA repair and chemoresistance post-therapy despite the apparent decrease in tumour size and vascularity. Additionally, from gene expression at MB recurrence, we identified a list of genes that negatively correlate with survival in patients diagnosed with Group 3 MB. A differential genomic profile of the “treatment-responsive” tumors against those that fail therapy may contribute to discovery of novel therapeutic approaches for the most aggressive subgroup of MB.
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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 | 0.000 |
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".