CNSS Chair’s Select Abstract Presentations
Bibliographic record
Abstract
Background: The hedgehog pathway (Hh) is an important developmental signaling pathway that is commonly dysregulated in brain tumors, most notably in medulloblastomas. To identify novel therapeutic targets within the Hh pathway, we performed the first quantitative proteome-wide evaluation of phosphorylation events resulting from in vitro SHH administration and occurring throughout Hh-driven cerebellar development in vivo. Methods: Multiplexed quantitative mass spectrometry was done using Tandem Mass Tags 10-plex reagents, TiO2 phosphopeptide enrichment and HPLC-MS/MS/MS. Results: Motif analysis of 2-fold changing phosphorylation events suggested casein kinase 2 (CK2) was responsible for mediating 45% of all changes in phosphorylation. Epistasis studies revealed that CK2 activity is necessary for hedgehog signaling and affects terminal signaling components, thereby circumventing challenges of emergence of resistance and a priori resistance that are commonly encountered with existing small molecule inhibitors in medulloblastoma. In vivo, mice harboring MB allografts resistant to current therapies showed near-complete cessation of tumor growth in response to a CK2 inhibitor. Conclusion: Our use of developmental phosphoproteomics revealed casein kinase 2 as a key regulator of hedgehog signaling and therapeutic target in medulloblastoma. Our success establishes a foundation for us, and others, to apply a similar approach in different tumor initiating pathways.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.688 | 0.419 |
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".