Embryonal tumor with abundant neuropil and true rosettes (ETANTR), ependymoblastoma, and medulloepithelioma share molecular similarity and comprise a single clinicopathological entity
Bibliographic record
Abstract
Three histological variants are known within the family of embryonal rosette-forming neuroepithelial brain tumors. These include embryonal tumor with abundant neuropil and true rosettes (ETANTR), ependymoblastoma (EBL), and medulloepithelioma (MEPL). In this study, we performed a comprehensive clinical, pathological, and molecular analysis of 97 cases of these rare brain neoplasms, including genome-wide DNA methylation and copy number profiling of 41 tumors. We identified uniform molecular signatures in all tumors irrespective of histological patterns, indicating that ETANTR, EBL, and MEPL comprise a single biological entity. As such, future WHO classification schemes should consider lumping these variants into a single diagnostic category, such as embryonal tumor with multilayered rosettes (ETMR). We recommend combined LIN28A immunohistochemistry and FISH analysis of the 19q13.42 locus for molecular diagnosis of this tumor category. Recognition of this distinct pediatric brain tumor entity based on the fact that the three histological variants are molecularly and clinically uniform will help to distinguish ETMR from other embryonal CNS tumors and to better understand the biology of these highly aggressive and therapy-resistant pediatric CNS malignancies, possibly leading to alternate treatment strategies.
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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 | 0.000 |
| 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".