Lowered H3K27me3 and DNA hypomethylation define poorly prognostic pediatric posterior fossa ependymomas
Bibliographic record
Abstract
Childhood posterior fossa (PF) ependymomas cause substantial morbidity and mortality. These tumors lack recurrent genetic mutations, but a subset of these ependymomas exhibits CpG island (CpGi) hypermethylation [PF group A (PFA)], implicating epigenetic alterations in their pathogenesis. Further, histological grade does not reliably predict prognosis, highlighting the importance of developing more robust prognostic markers. We discovered global H3K27me3 reduction in a subset of these tumors (PF-ve ependymomas) analogous to H3K27M mutant gliomas. PF-ve tumors exhibited many clinical and biological similarities with PFA ependymomas. Genomic H3K27me3 distribution showed an inverse relationship with CpGi methylation, suggesting that CpGi hypermethylation drives low H3K27me3 in PF-ve ependymomas. Despite CpGi hypermethylation and global H3K27me3 reduction, these tumors showed DNA hypomethylation in the rest of the genome and exhibited increased H3K27me3 genomic enrichment at limited genomic loci similar to H3K27M mutant gliomas. Combined integrative analysis of PF-ve ependymomas with H3K27M gliomas uncovered common epigenetic deregulation of select factors that control radial glial biology, and PF radial glia in early human development exhibited reduced H3K27me3. Finally, H3K27me3 immunostaining served as a biomarker of poor prognosis and delineated radiologically invasive tumors, suggesting that reduced H3K27me3 may be a prognostic indicator in PF ependymomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".