MPTH-26MOLECULAR REFINEMENT OF PEDIATRIC POSTERIOR FOSSA EPENDYMOMA
Bibliographic record
Abstract
We have recently identified nine distinct molecular subgroups of ependymoma across all age groups, three in each major anatomical compartment of the CNS: spinal (SP), posterior fossa (PF), and supratentorial (ST). These nine molecular subgroups are genetically, epigenetically, transcriptionally, demographically, and clinically distinct. Pediatric intracranial ependymomas were either affiliated with one of two supratentorial subgroups characterized by RELA (ST-EPN-RELA) or YAP1 (ST-EPN-YAP1) fusion genes, or with the PF-EPN-A subgroup in the hindbrain. Observing distinct outcomes among children with PF-EPN-A tumors, the largest molecular subgroup, we tested the hypothesis that further molecular diversity exists among these tumors. The genome-wide DNA methylation profiles of 575 pediatric PF ependymomas were analyzed by unsupervised consensus hierarchical clustering and principal component analysis, which identified three distinct molecular subtypes of PF-EPN-A tumors: PFA-1, PFA-2, and PFA-3. PFA-1 and PFA-2 showed different chromosomal copy number alterations and comprised tumors almost exclusively from infants, while PFA-3 ependymomas were generally from older children. The PFA-3 subtype was significantly enriched for gain of 1q. Distinct developmental gene expression profiles and radiological characteristics on pre-operative MR imaging suggested separate anatomic origins for the infant subtypes, PFA-1 and PFA-2. Survival analyses identified PFA-3 as having the poorest outcome. Multivariate analysis revealed molecular subgroup, grade of resection and gain of 1q as independent prognostic markers among PF-EPN-A tumors. We conclude that further molecular refinement of pediatric PF-EPN-A tumors, with their division into three distinct molecular subtypes, has clinical utility and the potential for enhanced risk assessment or therapeutic stratification.
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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 | 0.001 |
| 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".