MODL-32. EGFRVIII OVEREXPRESSION AND LOSS OF MOUSE SPECIFIC CDKN2A IN GLIAL CELLS LEADS TO GLIOMAGENESIS IN A NOVEL MOUSE MODEL
Bibliographic record
Abstract
Abstract A new mouse model for the classical subtype of human glioblastoma has been generated using Cre-mediated EGFRvIII overexpression and homozygous p19-ARF deletion (the mouse homolog of human p14-ARF/CDKN2A) in GFAP expressing cells. Transgenic mice develop intraparchenymal and/or leptomeningeal brain lesions with some spinal cord invasion as early as 1 month old and 95% of mice die by 6 months due to hydrocephalus and/or paralysis. Mice with high grade tumors have worse survival and similar features to human classical glioblastoma such as necrosis, high levels of mitosis, and infiltration of tumor cells into normal brain. Immunohistochemical analysis confirms EGFRvIII overexpression and p19-ARF loss in tumor cells, along with patchy positive GFAP and positivity for Olig2, S100β and NeuN, suggesting that tumor cells arise from a progenitor glial cell type. Adherent and neurosphere primary culture of dissociated tumors indicate that tumor cells maintain EGFRvIII expression in culture and are able to generate xenograft tumors by 3 weeks after intracranial injections into NODSCID mice. Xenograft tumors are reminiscent of the primary tumor, with similar histopathological features and immunohistochemical staining. This novel mouse model can be used to study diffuse glioma with a leptomeningeal component.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".