EPEN-52. METABOLIC REGULATION OF THE EPIGENOME DRIVES LETHAL INFANTILE EPENDYMOMA
Bibliographic record
Abstract
Abstract PFA ependymomas are a lethal glial malignancy of the hindbrain found in infants and toddlers. Lacking any highly recurrent somatic mutations, PFAs have been proposed to be a largely epigenetically driven entity, defined by hypomethylation at the histone 3 lysine 27 residue. Unfortunately, an almost complete lack of model systems has limited the discovery of novel PFA therapies. In this study, we have identified that the PFA hypoxic microenvironment controls the availability of specific metabolites, resulting in diminished H3K27 trimethylation and increased H3K27 acetylation in vitro and in vivo. Unique to PFA cells, transient exposure to ambient oxygen results in irreversible cellular toxicity. Furthermore, perturbation of key metabolic pathways is sufficient to inhibit growth of PFA primary cultures in vitro. Although PFA tumors exhibit a low basal level of H3K27me3, inhibition of H3K27 methylation paradoxically demonstrates significant and specific activity against PFA. Thus, we propose a “Goldilocks Model” of metabolic-epigenetic regulation in PFA ependymoma, whereby increased or decreased H3K27 trimethylation results in cell death. Mapping of PFA ependymoma tumours suggests a cell of origin arising in the first trimester of human development where there is a known hypoxic microenvironment. Therefore, targeting metabolism and/or the epigenome presents a unique opportunity for rational therapy for infants with PFA ependymoma.
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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) | 0.002 | 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".