Germline pathogenic <i>SMARCA4</i> variants in neuroblastoma
Bibliographic record
Abstract
Heterozygous germline pathogenic variants (GPVs) in SMARCA4 , the gene encoding the ATP-dependent chromatin remodelling protein SMARCA4 (previously known as BRG1), predispose to several rare tumour types, including small cell carcinoma of the ovary, hypercalcaemic type, atypical teratoid and malignant rhabdoid tumour, and uterine sarcoma. The increase in germline testing of SMARCA4 in recent years has revealed putative GPVs affecting SMARCA4 in patients with other cancer types. Here we describe 11 patients with neuroblastoma (NBL), including 4 previously unreported cases, all of whom were found to harbour heterozygous germline variants in SMARCA4 . Median age at diagnosis was 5 years (range 2 months–26 years); nine were male; and eight of nine cases had tumour location information in the adrenal gland. Eight of the germline variants were expected to result in loss of function of SMARCA4 (large deletion, truncating and canonical splice variants), while the remaining four were missense variants. Loss of heterozygosity of the wild-type SMARCA4 allele was found in all eight cases where somatic testing was performed, supporting the notion that SMARCA4 functions as a classic tumour suppressor. Altogether, these findings strongly suggest that NBL should be included in the spectrum of SMARCA4 -associated tumours.
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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 | 0.001 | 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".