Sleeping Beauty Mouse Models Identify Candidate Genes Involved in Gliomagenesis
Bibliographic record
Abstract
Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".