EPEN-23. MOLECULAR HETEROGENEITY AMONG PEDIATRIC POSTERIOR FOSSA EPENDYMOMA
Bibliographic record
Abstract
Previously, we have identified nine distinct molecular groups of ependymoma across all age groups, three in each major anatomical compartment of the CNS: spinal, posterior fossa, and supratentorial. These groups are genetically, epigenetically, transcriptionally, and clinically distinct. The commonest pediatric intracranial ependymomas belong to the posterior fossa type-A (PFA) molecular group. Observing distinct outcomes among children with PFA ependymomas, we tested the hypothesis that further molecular diversity with clinical utility, including possible novel genetic alterations, may exist among these tumors. Genome-wide DNA methylation profiles of 675 pediatric PFA ependymomas were analyzed by unsupervised consensus hierarchical clustering and t-distributed stochastic neighbor embedding. These analyses revealed two major subgroups and nine subtypes of PFA ependymoma. Two major subgroups, PFA-1 and PFA-2, demonstrated distinct gene expression profiles suggesting an independent histogenesis, while nine subtypes were characterized by significant differences in age at diagnosis, gender ratio, pathologic grade, outcome, and frequency of genetic alterations, including chromosome 1q gain and H3 K27M mutations. Specifically, one subtype, PFA-1c, was enriched for 1q gain and had a very poor outcome, while PFA-2c tumors showed an overall survival at 5 years of >90% and elevated levels of OTX2 expression, a potential biomarker for this subtype. We conclude that further molecular refinement of pediatric PFA ependymomas has clinical utility and the potential for enhanced risk assessment or therapeutic stratification. In addition, identification of PFA subgroups and further molecular heterogeneity within these subgroups may help to identify the drivers of PFA ependymomas, which are currently unknown.
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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".