AT-11CRIBRIFORM NEUROEPITHELIAL TUMOR (CRINET): MOLECULAR CHARACTERIZATION OF A SMARCB1-DEFICIENT NON-RHABDOID TUMOR WITH FAVORABLE LONG-TERM OUTCOME
Bibliographic record
Abstract
Rhabdoid phenotype and SMARCB1/INI1 loss are characteristic features of atypical teratoid/rhabdoid tumors (AT/RT). Rare non-rhabdoid brain tumors showing cribriform growth pattern and loss of SMARCB1/INI1 expression have been designated as cribriform neuroepithelial tumors (CRINET). Small case series suggest that CRINET may have a relatively favorable prognosis. It remains uncertain, however, if CRINET represents a distinct molecular entity or a variant of AT/RT. Therefore, ten CRINET were clinically and molecularly characterized as compared to ten AT/RT of each of three molecular subgroups (i.e. TYR, MYC and SHH). Median age of the 6 boys and 4 girls harboring CRINET was 20 months (range 10-129 months). On histopathological examination, all CRINET demonstrated a cribriform growth pattern and distinct tyrosinase staining. On unsupervised cluster analysis of Illumina Infinium Human Methylation 450k data, all 8 CRINET examined clustered with the AT/RT-TYR subgroup. FISH and/or MLPA confirmed the presence of heterozygous SMARCB1 deletions (8/9 cases evaluable). In addition, truncating SMARCB1 mutations (c.367C > T, c.367C > T, c.492duplCCTT and c.986 + 1G > T) were identified, while two cases showed additional small SMARCB1 deletions on MLPA (delEx7,delEx7-Ex9). Furthermore, an exon 9 missense mutation (c.1142C > G) and an exon 6 duplication where encountered, both mutations also being present in the germline. Except for one child, all patients are alive and well with a mean overall survival of 125 months (95% confidence interval 100-151 months). In conclusion, CRINET represents a SMARCB1 deficient non-rhabdoid tumor clustering with the AT/RT-TYR subgroup. Molecular alterations responsible for the relatively favorable outcome of CRINET as compared to AT/RT remain to be determined.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".