Hedgehog target genes regulate lipid metabolism to drive basal cell carcinoma and medulloblastoma
Bibliographic record
Abstract
Abstract Hedgehog (Hh) signaling is essential for development, homeostasis, and regeneration1. Misactivation of the Hh pathway underlies medulloblastoma, the most common malignant brain tumor in children, and basal cell carcinoma (BCC), the most common cancer in the United States2. Primary cilia regulate Hh signal transduction3, but target genes that drive cell fate decisions in response to ciliary ligands or oncogenic Hh signaling are incompletely understood. Here we define the Hh gene expression program using RNA sequencing of cultured cells treated with ciliary ligands, BCCs from humans, and Hh-associated medulloblastomas from humans and mice (Fig. 1a). To validate our results, we integrate lipidomic mass spectrometry and bacterial metabolite labeling of free sterols with genetic and pharmacologic approaches in cells and mice. Our results reveal novel Hh target genes such as the oxysterol synthase Hsd11β1 and the adipokine Retnla that regulate lipid metabolism to drive cell fate decisions in response to Hh pathway activation. These data provide insights into cellular mechanisms underlying ciliary and oncogenic Hh signaling and elucidate targets to treat Hh-associated cancers.
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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 | 0.001 |
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".