Relevance of Molecular Groups in Children with Newly Diagnosed Atypical Teratoid Rhabdoid Tumor: Results from Prospective St. Jude Multi-institutional Trials
Bibliographic record
Abstract
Abstract Purpose: Report relevance of molecular groups to clinicopathologic features, germline SMARCB1/SMARCA4 alterations (GLA), and survival of children with atypical teratoid rhabdoid tumor (ATRT) treated in two multi-institutional clinical trials. Materials and Methods: Seventy-four participants with newly diagnosed ATRT were treated in two trials: infants (SJYC07: age < 3 years; n = 52) and children (SJMB03: age 3–21 years; n = 22), using surgery, conventional chemotherapy (infants), or dose-dense chemotherapy with autologous stem cell rescue (children), and age- and risk-adapted radiotherapy [focal (infants) and craniospinal (CSI; children)]. Molecular groups ATRT-MYC (MYC), ATRT-SHH (SHH), and ATRT-TYR (TYR) were determined from tumor DNA methylation profiles. Results: Twenty-four participants (32%) were alive at time of analysis at a median follow-up of 8.4 years (range, 3.1–14.1 years). Methylation profiling classified 64 ATRTs as TYR (n = 21), SHH (n = 30), and MYC (n = 13), SHH group being associated with metastatic disease. Among infants, TYR group had the best overall survival (OS; P = 0.02). However, outcomes did not differ by molecular groups among infants with nonmetastatic (M0) disease. Children with M0 disease and <1.5 cm2 residual tumor had a 5-year progression-free survival (PFS) of 72.7 ± 12.7% and OS of 81.8 ± 11%. Infants with M0 disease had a 5-year PFS of 39.1 ± 11.5% and OS of 51.8 ± 12%. Those with metastases fared poorly [5-year OS 25 ± 12.5% (children) and 0% (infants)]. SMARCB1 GLAs were not associated with PFS. Conclusions: Among infants, those with ATRT-TYR had the best OS. ATRT-SHH was associated with metastases and consequently with inferior outcomes. Children with nonmetastatic ATRT benefit from postoperative CSI and adjuvant chemotherapy.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".