Immunohistochemical characterization of prototypical endometrial clear cell carcinoma—diagnostic utility of <scp>HNF</scp>‐1β and oestrogen receptor
Bibliographic record
Abstract
AIMS: The great majority of ovarian clear cell carcinomas have a hepatocyte nuclear factor 1 homeobox B (HNF-1β)-positive and oestrogen receptor (ER)-negative immunoprofile. However, the pattern of HNF-1β and ER immunostaining in clear cell carcinomas of the endometrium and the usefulness of this panel in distinguishing clear cell carcinoma from other histological types of endometrial carcinoma have yet to be well defined. METHODS AND RESULTS: We examined the immunostaining patterns of HNF-1β, ER and p53 in 15 morphologically classic pure endometrial clear cell carcinomas, and compared these patterns with 15 endometrioid and 15 serous carcinomas of the endometrium. We observed the presence of diffuse (>70%) moderate to strong nuclear HNF-1β staining and negative ER staining in 14 of 15 clear cell carcinomas, with the remaining case showing both diffuse strong nuclear HNF-1β staining and focal ER staining. In comparison, only one of 15 serous carcinomas and none of 15 endometrioid carcinomas showed a combination of diffuse moderate to strong HNF-1β nuclear staining and negative ER staining. Aberrant p53 immunostaining was observed in five of 15 (33%) clear cell carcinomas. CONCLUSIONS: Overall, our findings demonstrate that, similarly to the situation for the ovary, a diagnostic panel of HNF-1β and ER may be considered for separating clear cell carcinoma from endometrioid and serous carcinoma of the endometrium.
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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 | 0.001 | 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".