Loss of BRG1 ( <i>SMARCA4</i> ) Immunoexpression in a Pediatric Non-Central Nervous System Tumor Cohort
Bibliographic record
Abstract
Malignant rhabdoid tumors and atypical teratoid/rhabdoid tumors of the central nervous system are primitive malignancies associated with a poor prognosis. These tumors have previously been characterized by inactivation of the switch/sucrose nonfermenting (SWI/SNF) chromatin remodeling complex protein integrase interactor 1 (INI1), encoded by the SMARCB1 gene. In the last decade, sporadic publications have shown that a different SWI/SNF protein, brahma-related gene 1 (BRG1), encoded by the SMARCA4 gene, is associated with a similar rhabdoid phenotype and possible germline mutation termed rhabdoid tumor predisposition syndrome type 2. We sought to determine the presence of BRG1 expression in pediatric embryonal tumors. Using a local tissue microarray consisting of 28 tumors diagnosed as having an undifferentiated, polyphenotypic, or rhabdoid morphology, expression of BRG1 by immunohistochemistry was performed. Four cases showed loss of INI1, while 3 of the remaining 24 cases demonstrated loss of BRG1. Two cases were diagnosed as soft tissue sarcomas, and 1 case was diagnosed as a small cell carcinoma of the ovary, hypercalcemic type. Survival ranged from less than 6 months after diagnosis to more than 5 years at the time of last follow-up. In conclusion, we demonstrate that BRG1 immunohistochemistry is a useful second-line immunostain for the workup of undifferentiated, polyphenotypic or rhabdoid pediatric tumors that demonstrate retained expression of INI1.
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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 | 0.000 |
| 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".