Preclinical Evaluation of Radiation and Perifosine in a Genetically and Histologically Accurate Model of Brainstem Glioma
Bibliographic record
Abstract
Brainstem gliomas (BSG) are a rare group of central nervous system tumors that arise mostly in children and usually portend a particularly poor prognosis. We report the development of a genetically engineered mouse model of BSG using the RCAS/tv-a system and its implementation in preclinical trials. Using immunohistochemistry, we found that platelet-derived growth factor (PDGF) receptor alpha is overexpressed in 67% of pediatric BSGs. Based on this observation, we induced low-grade BSGs by overexpressing PDGF-B in the posterior fossa of neonatal nestin tv-a mice. To generate high-grade BSGs, we overexpressed PDGF-B in combination with Ink4a-ARF loss, given that this locus is commonly lost in high-grade pediatric BSGs. We show that the likely cells of origin for these mouse BSGs exist on the floor of the fourth ventricle and cerebral aqueduct. Irradiation of these high-grade BSGs shows that although single doses of 2, 6, and 10 Gy significantly increased the percent of terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL)-positive nuclei, only 6 and 10 Gy significantly induce cell cycle arrest. Perifosine, an inhibitor of AKT signaling, significantly induced TUNEL-positive nuclei in this high-grade BSG model, but in combination with 10 Gy, it did not significantly increase the percent of TUNEL-positive nuclei relative to 10 Gy alone at 6, 24, and 72 hours. Survival analysis showed that a single dose of 10 Gy significantly prolonged survival by 27% (P = 0.0002) but perifosine did not (P = 0.92). Perifosine + 10 Gy did not result in a significantly increased survival relative to 10 Gy alone (P = 0.23). This PDGF-induced BSG model can serve as a preclinical tool for the testing of novel agents.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 0.000 |
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".