MDB-08. MYC AND TGFΒ PROMOTE GROUP 3 MEDULLOBLASTOMA TUMOR RESISTANCE THROUGH DEREGULATION OF POLYCOMB TARGETS
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is one of the most prevalent malignant brain tumors in children, with tremendous cognitive and neuroendocrine disability among survivors. Group 3 (G3) MBs have poor overall survival at <50%, higher frequency of metastasis, and no targeted therapies. Amplification of MYC and activation of TGFβ signaling are frequent in G3MB. Remarkably, some tumors have no reported mutations, suggesting roles for epigenetic mechanisms in driving disease. We have generated new humanized models for G3MB by transforming neuroepithelial stem cells (NESC) derived from human induced pluripotent stem cells with TGFβ effectors alone and/or in combination with MYC, prioritizing combinations observed in patients. Excitingly, both MYC and TGFβ effectors drove tumor formation in vivo with the combination of TGFβ effectors and MYC leading to more aggressive tumors. Moreover, NESC-derived tumors clustered with human G3/G4MB samples, indicating our models recapitulates human disease. We next found that NESCs expressing MYC with either TGFβR1 or TGFβ1 showed resistance to clinical TGFβR1 inhibitors, compared to cells driven by either TGFβR1 or TGFβ1 alone. To decipher mechanisms of resistance, we integrated CUT&RUN to probe for MYC genomic localization and relevant histone PTMs with RNA-seq analysis and discovered a subset of genes upregulated in MYC and TGFβ-driven lines that are targets of the histone demethylase KDM2B and Polycomb Repressive Complex 2 (PRC2) member SUZ12. Moreover, we found that MYC is bound to regions normally regulated by PRC interactors. We postulate that chromatin remodeling via MYC and recruitment of other MYC-interacting cofactors to PRC targets culminates in transcriptional changes that lead to aggressive disease. Work from others suggests that PRC-mediated chromatin regulation is critical in many adult and pediatric brain tumors, underscoring its significance in MB. Our studies provide important insight on identifying new therapeutic avenues with a focus on the epigenetic landscape for patients with MYC and TGFβ driven G3MB.
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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".