MB-02 * SONIC HEDGEHOG INDUCES YB-1 IN A YAP-DEPENDENT MANNER TO REGULATE Igf2 EXPRESSION AND PROLIFERATION IN CEREBELLAR GRANULE NEURON PROGENITORS AND MEDULLOBLASTOMA CELLS
Bibliographic record
Abstract
Interactions between the developmentally essential Sonic hedgehog (Shh) and Insulin-like Growth Factor (IGF) pathways play prominent roles in medulloblastoma (MB), the most common malignant pediatric brain tumor. MB patients undergo surgery, chemotherapy, and radiation, a regimen that carries devastating side effects, emphasizing the need for targeted therapies to improve survival and quality of life. Post-natal proliferation of cerebellar granule neuron precursors (CGNPs), proposed cells-of-origin for the SHH-associated subgroup of MB, is driven by Shh and IGF in the developing cerebellum. Shh induces the oncogene Yes-associated protein (YAP), which drives IGF2 expression in CGNPs and mouse Shh-associated medulloblastomas. To determine how IGF2 expression is regulated downstream of YAP, we carried out an unbiased screen for transcriptional regulators bound to IGF2 promoters. We report that Y-box binding protein-1 (YB-1), an onco-protein regulating transcription and translation, binds to IGF2 promoter P3 and is required for IGF2 expression in CGNPs. We show that YB-1 is induced by Shh in CGNPs in a YAP-dependent manner and is found in the germinal layer of the developing cerebellum. We observed that YB-1 is up-regulated across human medulloblastoma subclasses and is elevated in a mouse model for the Shh medulloblastoma subclass. Finally, shRNA-mediated knockdown experiments reveal that YB-1 activity is required for CGNP and medulloblastoma cell (MBC) proliferation in primary cultures and organotypic slice cultures. Collectively, our findings describe a novel role for YB-1 in driving proliferation in the developing cerebellum and medulloblastoma cells and they identify the SHH:YAP:YB1:IGF2 axis as a powerful target for therapeutic intervention in medulloblastomas.
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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 | 0.000 | 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 | 0.000 |
| 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; a candidate call from one teacher head, 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".