PATH-24. MOLECULAR CLASSIFICATION OF HIGH RISK INFANT EMBRYONAL BRAIN TUMORS ENROLLED IN THE ACNS0334 TRIAL: A REPORT FROM THE CHILDREN’S ONCOLOGY GROUP
Bibliographic record
Abstract
Abstract Young children with embryonal brain tumors including medulloblastoma (MB), supratentorial primitive neuro-ectodermal tumor, or pineoblastoma have historically been considered high-risk patients with poor outcomes despite the use of intensive radiation-sparing treatment. In the ACNS0334 phase III trial, 91 consented children <36 months old with the above diagnoses were randomized to intensive induction chemotherapy with or without methotrexate followed by consolidation with stem cell rescue. Here we present the results of a centralized integrated molecular analysis including global methylation profiling (65/91), and whole exome sequencing of tumor (46/91) and germline (35/91) DNA. Unsupervised clustering analyses of methylation profiles using multiple orthogonal methods against a reference dataset of 1200 pediatric brain tumors, revealed known and new molecular entities. For tumors diagnosed as MB on central pathology review, 7.3% (3/41) had a non-MB molecular diagnosis (2 embryonal tumor with multiple rosettes/ETMR, 1 group MYC pineoblastoma), with the remainder as MB Group SHH (11/41), Group3 (25/41), and Group4 (2/41). Among histologic non-MBs, 3/24 (12.5%) were molecular entities not intended for trial inclusion (1 each for ATRT, pleomorphic xanthoastrocytoma, and high-grade glioma). ETMR, historically considered a rare entity, was molecularly identified in a significant proportion (14/65; 21.5%) of samples. Among MB-SHH, we detected deleterious PTCH1 mutations in 6/9 tumors but none among 5 germline samples tested; a germline SUFU frameshift mutation with tumor LOH was also observed in MB-SHH. Correlation of these and other molecular features to the parallel clinical analysis will yield important markers of risk stratification and predictors of treatment response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".