Epigenetic activation of a RAS/MYC axis in H3.3K27M-driven cancer
Bibliographic record
Abstract
Histone H3 lysine 27 (H3K27M) mutations represent the canonical oncohistone, occurring frequently in midline gliomas but also identified in haematopoietic malignancies and carcinomas. H3K27M functions, at least in part, through widespread changes in H3K27 trimethylation but its role in tumour initiation remains obscure. To address this, we created a transgenic mouse expressing H3.3K27M in diverse progenitor cell populations. H3.3K27M expression drives tumorigenesis in multiple tissues, which is further enhanced by Trp53 deletion. We find that H3.3K27M epigenetically activates a transcriptome, enriched for PRC2 and SOX10 targets, that overrides developmental and tissue specificity and is conserved between H3.3K27M-mutant mouse and human tumours. A key feature of the H3K27M transcriptome is activation of a RAS/MYC axis, which we find can be targeted therapeutically in isogenic and primary DIPG cell lines with H3.3K27M mutations, providing an explanation for the common co-occurrence of alterations in these pathways in human H3.3K27M-driven cancer. Taken together, these results show how H3.3K27M-driven transcriptome remodelling promotes tumorigenesis and will be critical for targeting cancers with these mutations.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".