Targeted mutation analysis of endometrial clear cell carcinoma
Bibliographic record
Abstract
AIMS: Endometrial clear cell carcinomas (CCC) constitute fewer than 5% of all carcinomas of the endometrium. Currently, little is known regarding the genetic basis of endometrial CCC. METHODS AND RESULTS: We performed genomic and immunohistochemical analyses on 14 rigorously reviewed pure endometrial CCC. The genomic analysis consisted of sequencing the coding regions of 26 genes implicated previously in endometrial carcinoma. Twelve of 14 tumours displayed a prototypical CCC immunophenotype [napsin A+, hepatocyte nuclear factor-1β (HNF1β(+) ) and oestrogen receptor(-) ] and all showed intact mismatch repair protein expression. We detected mutations in 11 of 14 tumours, and there was a predominance of mutations involving genes that are mutated more frequently in endometrial serous carcinomas than in endometrioid carcinomas. Two tumours displayed a prototypical serous carcinoma mutation profile (concurrent TP53 and PPP2R1A mutations, without PTEN, CTNNB1 or ARID1A mutation). No mutations in PTEN, CTNNB1 or POLE were identified. CONCLUSIONS: The overall mutation profile of this cohort of endometrial CCC appears to be more serous-like than endometrioid-like, with a minor subset in the TP53-mutated CCC showing serous carcinoma profile. These findings provide new insights into the molecular features of morphologically prototypical endometrial CCC, and underscore the need for further investigations into the oncogenesis of endometrial CCC.
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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 | 0.001 | 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".