Loss of SMARCA4 (BRG1) protein expression as determined by immunohistochemistry in small‐cell carcinoma of the ovary, hypercalcaemic type distinguishes these tumours from their mimics
Bibliographic record
Abstract
AIMS: Molecular investigation of small-cell carcinoma of the ovary, hypercalcaemic type (SCCOHT) has revealed that it is a monogenetic tumour characterized by alteration of SMARCA4 (BRG1), encoding a member of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodelling complex. A large majority of cases show loss of expression of the corresponding SMARCA4/BRG1 protein. Furthermore, three cases of SCCOHT with retained SMARCA4 protein expression showed loss of SMARCB1/INI1 expression. The aim of this study was to assess the sensitivity and specificity of loss of SMARCA4 expression as a diagnostic test for SCCOHT. METHODS AND RESULTS: We performed SMARCA4 and SMARCB1 staining in 245 tumours, many of which were potentially in the differential diagnosis of SCCOHT. We also stained 56 cases of SCCOHT for SMARCA4 and 37 of these for SMARCB1. Fifty-four of the SCCOHT cases showed complete absence of SMARCA4 expression. The two cases with retained expression showed molecular alteration of SMARCA4. Of the 217 other neoplasms with interpretable staining, all retained SMARCA4 expression. Although the majority showed diffuse, strong nuclear expression, a heterogeneous, typically weak staining pattern was present in 13% of cases. All 37 cases of SCCOHT tested and all other neoplasms, apart from three malignant rhabdoid tumours, showed retained nuclear SMARCB1 expression. Loss of SMARCA4 expression had a sensitivity of 96.55% and specificity of 100%. CONCLUSIONS: Loss of SMARCA4 expression is sensitive and specific for SCCOHT. Although some mimics show heterogeneous expression, there is retention of nuclear staining in at least a part of the tumour; therefore, only complete loss of staining should be regarded as being supportive of SCCOHT.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".