DIPG-41. DISSECTING THE MECHANISTIC BASIS FOR <i>ACVR1</i> AND <i>PIK3CA</i> MUTATION CO-OCCURRENCE IN DIFFUSE MIDLINE GLIOMAS USING GENETICALLY ENGINEERED MOUSE MODELS
Bibliographic record
Abstract
Abstract Diffuse midline gliomas (DMGs) are aggressive childhood brain tumors with a dismal prognosis. Most of these tumors carry K27M mutations in histone H3-encoding genes, particularly H3F3A and HIST1H3B. In addition, activating mutations in ACVR1 and PIK3CA co-occur in a subset of DMGs. To understand how these lesions drive the development of DMGs, we generated genetically engineered mouse models in which Acvr1G328V, Hist1h3bK27M, and Pik3caH1047R are targeted to the OLIG2-expressing cell lineage. Animals carrying Acvr1G328V and Pik3caH1047R, with (“AHPO”) or without (“APO”) Hist1h3bK27M, developed high-grade diffuse gliomas involving midline and forebrain regions. Neither Acvr1G328V nor Pik3caH1047R drove tumorigenesis by themselves, but Acvr1G328V was sufficient to cause oligodendroglial differentiation arrest, pointing to a role in the earliest stages of gliomas formation. Transcriptomic analyses of AHPO and APO tumors indicated a predominantly proneural and oligodendrocyte precursor-like gene expression signature, consistent with the corresponding human pathology. Genes encoding transcription factors (TFs) with dual roles in controlling glial and neuronal differentiation were upregulated in tumors. Some of these genes were mildly induced by Acvr1G328V alone. Functional experiments using CRISPR/Cas9-mediated gene editing in patient-derived cell lines confirmed a role for some of these TFs in controlling DMG cell fitness. Overall, our results suggest that Pik3caH1047R consolidates Acvr1G328V-induced glial differentiation arrest to drive DMG development and progression.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".