A Comparison of GATA3, TTF1, CD10, and Calretinin in Identifying Mesonephric and Mesonephric-like Carcinomas of the Gynecologic Tract
Bibliographic record
Abstract
Mesonephric carcinomas of the gynecologic tract are neoplasms that are often under-recognized due to their varied morphologic appearances. Recently, GATA3 and TTF1 have been reported to be useful immunohistochemical markers for distinguishing mesonephric carcinomas from its morphologic mimics. Herein, we compared the performance of GATA3 and TTF1 to the traditional markers used for mesonephric carcinomas, CD10 and calretinin. We studied 694 cases: 8 mesonephric carcinomas (7 cervical [includes 3 mesonephric carcinosarcomas], 1 vaginal), 5 mesonephric-like carcinomas (4 uterine corpus, 1 ovarian), 585 endometrial adenocarcinomas, and 96 cervical adenocarcinomas. Mesonephric-like carcinomas were defined as tumors exhibiting the classic morphologic features of mesonephric carcinoma, but occurring outside of the cervix and without convincing mesonephric remnants. GATA3 had the highest sensitivity and specificity (91% and 94%) compared with TTF1 (45% and 99%), CD10 (73% and 83%), and calretinin (36% and 89%). GATA3, however, also stained a substantial number of uterine carcinosarcomas (23/113, 20%). TTF1 was positive in 5/5 (100%) mesonephric-like carcinomas and only 1/8 (13%) mesonephric carcinomas. In 4/6 (67%) TTF1 positive cases, GATA3 exhibited an inverse staining pattern with TTF1. In summary, GATA3 was the best overall marker for mesonephric and mesonephric-like carcinomas, but cannot be used to distinguish mesonephric carcinosarcomas from Müllerian carcinosarcomas. The inverse staining pattern between GATA3 and TTF1, suggests that TTF1 may be useful when GATA3 is negative in small biopsies where mesonephric or mesonephric-like carcinoma is suspected. The greater TTF1 positivity in mesonephric-like carcinomas suggests they may be biologically different from prototypical mesonephric carcinomas.
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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 | 0.002 | 0.000 |
| 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 | 0.003 |
| 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".