Abstract 912: A novel genetically engineered H3.3G34R model reveals cooperation with ATRX loss in upregulation of PRC2 target genes
Bibliographic record
Abstract
Abstract Pediatric High Grade Glioma (pHGG) is a collection of molecularly distinct subtypes with different prognoses depending on the genetic drivers. One particularly aggressive subtype is H3.3G34R mutant gliomas, which are currently incurable and in need of improved therapies. Interestingly, H3.3G34R mutant gliomas commonly harbor TP53mutations, ATRX mutations, and alterations in PDGFRA signaling. The mechanism by which H3.3G34R promotes gliomagenesis is still somewhat unclear and additional models are needed to dissect its role in tumorigenesis. We used the RCAS Tv-a system to model H3.3G34R pHGG in mice. Nestin expressing progenitors in the frontal cortex of Nestin-Tva (Ntva); p53 fl/fl; ATRX fl/fl or Ntva; p53 fl/fl mice were infected with H3.3G34R or H3.3WT, PDGFA, and Cre, and monitored for signs and symptoms of tumor formation. RNAseq analysis and immunophenotype were used to characterize the tumors. We observed that H3.3G34R did not significantly impact tumor latency independent of ATRX status. ATRX loss significantly increased tumor latency independent of H3.3G34R (P < 0.01) from 90 days to 143 days. H&E analysis revealed that the majority of tumors in all groups were high grade and that mice with ATRX loss were more likely to develop low grade tumors though this trend did not reach significance (P = 0.075). Expression of Ki67, GFAP and Olig2 was present in all groups, as shown by Immunophenotypic analysis. RNAseq analysis of murine tumor tissue revealed that ATRX loss in the context of G34R led to significant differential expression of 113 genes (78 upregulated and 35 downregulated) including upregulation of PRC2 target genes including HoxA genes. These findings highlight the cooperation between ATRX loss and H3.3G34R in gliomagenesis. Citation Format: Aalaa Abdallah, Herminio J. Cardona, David J. Picketts, Daniel J. Brat, Xiao-Nan Li, Oren J. Becher. A novel genetically engineered H3.3G34R model reveals cooperation with ATRX loss in upregulation of PRC2 target genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 912.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".