Data from A Novel Somatic Mouse Model to Survey Tumorigenic Potential Applied to the Hedgehog Pathway
Bibliographic record
Abstract
<div>Abstract<p>We report a novel mouse model for the generation of sporadic tumors and show the efficiency of this approach by surveying Hedgehog (Hh)–related tumors. Up-regulation of the Hh pathway is achieved by conditionally regulated expression of an activated allele of Smoothened (<i>R26-SmoM2</i>) using either sporadic leakage or global postnatal induction of a ubiquitously expressed inducible Cre transgene (<i>CAGGS-CreER</i>). Following postnatal tamoxifen induction, <i>CAGGS-CreER; R26-SmoM2</i> mice developed tumors with short latency and high penetrance. All mice exhibited rhabdomyosarcoma and basal cell carcinoma; 40% also developed medulloblastoma. In addition, mice showed a novel pancreatic lesion resembling low-grade mucinous cystic neoplasms in humans. In contrast, widespread activation of SmoM2 in the postnatal prostate epithelium results in no detectable morphologic outcome in 12-month-old mice. Comparison of gene expression profiles among diverse tumors identified several signature genes, including components of platelet-derived growth factor and insulin-like growth factor pathways, which may provide a common mechanistic link to the Hh-related malignancies. This experimental model provides a robust tool for exploring the process of Hh-dependent tumorigenesis and the treatment of such tumors. More generally, this approach provides a genetic platform for identifying tumorigenic potential in putative oncogenes and tumor suppressors and for more effective modeling of sporadic cancers in mice. (Cancer Res 2006; 66(20): 10171-7)</p></div>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".