<scp>SMARCA4</scp> ‐deficient rhabdoid tumours show intermediate molecular features between <scp>SMARCB1</scp> ‐deficient rhabdoid tumours and small cell carcinomas of the ovary, hypercalcaemic type
Bibliographic record
Abstract
Abstract Extracranial rhabdoid tumours (ECRTs) are an aggressive malignancy of infancy and early childhood. The vast majority of cases demonstrate inactivation of SMARCB1 (ECRT SMARCB1 ) on a background of a remarkably stable genome, a low mutational burden, and no other recurrent mutations. Rarely, ECRTs can harbour the alternative inactivation of SMARCA4 (ECRT SMARCA4 ) instead of SMARCB1. However, very few ECRT SMARCA4 cases have been published to date, and a systematic characterization of ECRT SMARCA4 is missing from the literature. In this study, we report the clinical, pathological, and genomic features of additional cases of ECRT SMARCA4 and show that they are comparable to those of ECRT SMARCB1. We also assess whether ECRT SMARCB1 , ECRT SMARCA4 , and small cell carcinomas of the ovary, hypercalcaemic type (SCCOHT) represent distinct or overlapping entities at a molecular level. Using DNA methylation and transcriptomics‐based tumour classification approaches, we demonstrate that ECRT SMARCA4 display molecular features intermediate between SCCOHT and ECRT SMARCB1 ; however, ECRT SMARCA4 appear to be more closely related to SCCOHT by DNA methylation. Conversely, both transcriptomics and DNA methylation show a larger gap between SCCOHT and ECRT SMARCB1 , potentially supporting their continuous separate classification. Lastly, we show that ECRT SMARCA4 display concomitant lack of SMARCA4 (BRG1) and SMARCA2 (BRM) expression at the protein level, similar to what is seen in SCCOHT. Overall, these results expand our knowledge on this rare tumour type and explore the similarities and differences among entities from the ‘rhabdoid tumour’ spectrum. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".