Genomic profiling of dedifferentiated endometrial carcinomas arising in the background of high‐grade carcinoma: a targeted next‐generation sequencing study
Bibliographic record
Abstract
AIMS: Our understanding of dedifferentiated endometrial carcinoma (DEC), a rare and aggressive malignancy, mainly reflects undifferentiated carcinomas (UC) arising in the setting of low-grade endometrial cancer (DEC-LG). However, cases of UC arising in the setting of high-grade EC (DEC-HG) have been noted in the literature. Our knowledge of the genomics of DEC-HG is limited. To characterise the molecular landscape of DEC-HC, targeted genomic sequencing and immunohistochemical analysis was carried out on seven DEC-HG and four DEC-LG. METHODS AND RESULTS: DEC-HG and DEC-LG, including undifferentiated and differentiated components, both showed a similar frequency and spectrum of mutations. ARID1A mutations were identified in 6/7 (86%) DEC-HG and 4/4 (100%) DEC-LG, while SMARCA4 mutations were present in 4/7 (57%) DEC-HG and in 1/4 (25%) DEC-LG. Concurrent SMARCA4/BRG1 protein loss by immunohistochemistry was observed in 3/4 and 1/1 SMARCA4 mutated DEC-HG and DEC-LG, respectively. Neither genomic alterations nor protein loss in SMARCB1/INI1 were observed in any of our cases. TP53 mutations were detected in 4/7 (57%) DEC-HG and in 2/4 (50%) DEC-LG, while mutation-pattern p53 immunohistochemistry expression was observed in 2/7 (29%) DEC-HG and none of the DEC-LG. MLH1 mutations were observed in 1/7 (14%) DEC-HG and 1/4 (25%) DEC-LG. MSH2 and MSH6 mutations were each detected in 1/7 (14%) DEC-HG, but neither was associated with corresponding loss of protein expression. CONCLUSION: The findings support expanding the definition of DEC to include DEC-HG, a previously under-recognised phenomenon with genomic similarities to DEC-LG.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".