Immunophenotypic features of dedifferentiated endometrial carcinoma – insights from <scp>BRG</scp>1/<scp>INI</scp>1‐deficient tumours
Bibliographic record
Abstract
AIMS: Dedifferentiated endometrial carcinoma (DDEC) is defined by the presence of an undifferentiated carcinoma together with an endometrioid carcinoma. Inactivation of SMARCA4 (BRG1) and inactivation of SMARCB1 (INI1) were recently described as potential mechanisms underlying the histological dedifferentiation. The aim of this study was to characterize the immunophenotypic features of DDECs, particularly in cases with prototypical histological and molecular features (BRG1/INI1 deficiency). METHODS AND RESULTS: We evaluated PAX8, oestrogen receptor (ER) and p53 immunostaining in the endometrioid and the undifferentiated components of 20 BRG1/INI1-deficient DDECs and 15 BRG1/INI1-intact DDECs, and compared the results with those of 23 grade 3 endometrioid carcinomas. The differentiated endometrioid component was positive for PAX8 and/or ER in 19 of 20 BRG1/INI1-deficient DDECs, whereas the corresponding undifferentiated component of all 20 tumours showed a complete absence of PAX8 and ER staining. All except one of the BRG1/INI1-deficient tumours showed a wild-type p53 staining pattern. PAX8 and ER expression in the undifferentiated component was absent in 67% and 80% of BRG1/INI1-intact DDECs, respectively, whereas 47% of the BRG1/INI1-intact DDECs showed a mutated p53 staining pattern. In comparison, absent PAX8 expression and absent ER expression were each observed in the more solid area of 48% and 48% of grade 3 endometrioid carcinomas. CONCLUSIONS: The consistent absence of PAX8 and ER expression in molecularly defined (BRG1/INI1-deficient) DDECs suggests that the loss of PAX8 and ER expression is a fundamental feature of dedifferentiation. The frequent findings of a mutated p53 staining pattern in BRG1/INI1-intact DDECs indicate that BRG1/INI1-intact DDECs may be biologically different from BRG1/INI1-deficient 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 | 0.000 |
| 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".