MB-18 * POST-TRANSLATIONAL REGULATION OF ATOH1: FROM CEREBELLAR DEVELOPMENT TO MEDULLOBLASTOMA FORMATION
Bibliographic record
Abstract
Medulloblastoma (MB), a tumor of the cerebellum, is the most common malignant pediatric tumor of the central nervous system. Human MBs have been classified by gene expression profiling into four subgroups. A subgroup of human MBs (∼25%) harbors constitutive activation of the Sonic Hedgehog (SHH) signaling pathway. Atoh1, a proneural basic helix-loop-helix transcription factor is essential for cerebellum development and collaborates with SHH signaling for the formation of SHH MB in vivo. Because Atoh1 acts as a lineage dependency transcription factor in SHH MB, mechanisms controlling Atoh1 expression are keen interest in the field. However, how this master transcription factor is regulated has remained poorly understood. Using a proteomic approach we recently described a functional interaction between Atoh1 and the E3 ubiquitin ligase Huwe1 during cerebellar development. We uncovered that SHH regulates Atoh1 degradation in a phospho- and E3-dependent manner in cerebellar granule neuron progenitors. In human SHH MB, low HUWE1 expression is associated with poor prognosis. These results led us to deepen the relationship between Huwe1 and Atoh1 in SHH MB formation. More specifically, we wish to explore whether Huwe1 could cooperate with the constitutive activation of the SHH pathway for the formation of SHH MB in vivo.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".