TMOD-11. APPLICATION OF A NOVEL TRANSGENIC AND SYNGENEIC MOUSE MODELS OF HUMAN CLASSICAL GLIOBLASTOMA FOR DRUG SCREENING AND PRE-CLINICAL TRIALS
Bibliographic record
Abstract
Abstract Glioblastoma multiforme (GBM) is the most common malignant brain tumor in adults with 1 year median survival. The classical subtype of GBM occurs in about 10% of GBM cases and has the worst clinical outcome. The most frequent genetic alteration associated with classical GBM is amplification in the epidermal growth factor receptor (EGFR) and homozygous deletion in CDKN2A (Cyclin Dependent Kinase Inhibitor 2A). We generated a transgenic mouse harboring EGFRvIII, a constitutively active mutant of EGFR, knock in and homozygous deletion in p19 ARF, an alternative spliced form of the CDKN2a gene, restricted to glial cells. Transgenic mice develop tumors as early as 1 month and 73% of mice die by 6 months of age. MRIs reveal that mice develop infiltrative tumor cells throughout the brain and craniospinal junction with some infiltration within the leptomeninges that can result in hydrocephalus. Histology shows that 72% of tumors are high grade gliomas and some tumors demonstrate classical histological features of human GBM such as pseudopallisading necrosis, hyper vascularity and cellular atypia. We generated primary cell lines from transgenic mice that retained EGFRVIII expression and P19 ARF deletion and formed allografts in syngeneic mouse brains. Epigenetic modifications are considered a key mechanism in GBM development. We have therefore evaluated the efficacy of a panel of 42 compounds that target various epigenetic proteins including the readers, writers, and editors of several histone marks available from the Structural Genomics Consortium in primary cell lines derived from our mouse model. The primary cell lines were exposed to epigenetic drugs showing different responses to the same epigenetic modifiers. Key candidate drugs will further be tested pre-clinically in our syngeneic mouse model. In summary, we developed a novel transgenic and syngeneic mouse model for human classical GBM that can be used for drug screening and pre-clinical trials.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".