TMOD-21. MOUSE MODEL TO CONDITIONALLY EXPRESS A DIFFUSE MIDLINE GLIOMA DERIVED MUTATION IN THE ONCOGENIC PHOSPHATASE PPM1D
Bibliographic record
Abstract
Abstract Diffuse Midline Gliomas (DMGs) are incurable brain tumors of children and adults, and there is an urgent need for new therapeutic approaches. Their location within critical areas of the brain precludes complete surgical removal. While current treatment mainly relies on radiation therapy, its efficacy remains palliative. DMGs commonly harbor truncating mutations in the Mn2+/Mg2+-dependent protein phosphatase 1D (PPM1D), leading to a gain-of-function in PPM1D by enhancing protein stability and activity. Thus, investigating PPM1D protein expression and its regulatory mechanisms is crucial for understanding its oncogenic role and identifying therapeutic targets. To address this, we developed a Ppm1d-loxP-exon6-loxP-exon6-E518X-tag mouse allele (Ppm1d-FL). This allele allows conditional expression of DMG-derived truncating mutations from the endogenous Ppm1d locus when the loxP sites are recombined in the presence of Cre recombinase. Tosimulate primary gliomas, we utilized the RCAS/tv-a retrovirus system and Cre/loxP recombination platforms. Mouse pups were injected with RCAS retroviruses bearing oncogenic platelet-derived growth factor B, Cre recombinase, and luciferase reporter genes into the brainstem. We confirmed that Cre leads to expected recombination of Ppm1d-FL, leading to expression of DMG-derived truncated Ppm1d-E518X-Tag mRNA. We examined tumor-free survival data, which indicates accelerated tumor formation with Ppm1d-FL compared to littermate controls with wildtype Ppm1d. The tumors demonstrated expression of molecular biomarkers commonly found in DMGs. Single-cell RNA sequencing has identified pathways activated or inactivated upon Ppm1d mutation. These data shed light on the complex interplay between PPM1D mutations and glioma pathogenesis and may guide the design of therapies that target PPM1D molecular pathways.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".