Prkar1a is an osteosarcoma tumor suppressor that defines a molecular subclass in mice
Bibliographic record
Abstract
Some cancers have been stratified into subclasses based on their unique involvement of specific signaling pathways. The mapping of human cancer genomes is revealing a vast number of somatic alterations; however, the identification of clinically relevant molecular tumor subclasses and their respective driver genes presents challenges. This information is key to developing more targeted and personalized cancer therapies. Here, we generate a new mouse model of genomically unstable osteosarcoma (OSA) that phenocopies the human disease. Integrative oncogenomics pinpointed cAMP-dependent protein kinase type I, alpha regulatory subunit (Prkar1a) gene deletions at 11qE1 as a recurrent genetic trait for a molecularly distinct subclass of mouse OSA featuring RANKL overexpression. Using mouse genetics, we established that Prkar1a is a bone tumor suppressor gene capable of directing subclass development and driving RANKL overexpression during OSA tumorigenesis. Finally, we uncovered evidence for a PRKAR1A-low subset of human OSA with distinct clinical behavior. Thus, tumor subclasses develop in mice and can potentially provide information toward the molecular stratification of human 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".