Napsin-A Expression in Mesonephric and Mesonephric-like Adenocarcinomas: Implications for Distinction From Clear Cell Carcinoma
Bibliographic record
Abstract
Mesonephric adenocarcinoma (MA) and mesonephric-like adenocarcinoma (MLA) are rare gynecological neoplasms that sometimes exhibit morphologic overlap with clear cell carcinoma (CCC), which may lead to diagnostic challenges. Napsin-A is regarded as the most specific immunohistochemical marker of CCC, but its expression in MLA and MA has not been widely investigated. This study investigated the expression of Napsin-A in a series of MAs and MLAs to determine its utility in distinguishing these neoplasms from CCC. The cohort included 32 MLAs arising in the ovary, endometrium, abdominal wall, and sigmoid mesocolon, 13 cervical MLAs, 2 ovarian mesonephric-like carcinosarcomas, and 1 cervical mesonephric carcinosarcoma, with Napsin-A immunohistochemistry performed on whole-slide tissue sections. Napsin-A staining was positive in 17 of 48 cases (35.4%), with focal granular cytoplasmic expression ranging from 1% to 40%. In all, 13/32 (40.6%) MLAs, 2/13 (15.4%) MAs, and 2/3 (66.7%) mesonephric or mesonephric-like carcinosarcomas were positive. Our results demonstrate that Napsin-A is expressed in a significant subset of MLAs and MAs. Given the morphologic and immunohistochemical overlap, this may contribute to misclassification as CCC, especially in cases with ambiguous morphology. Pathologists should be aware of this diagnostic pitfall and employ a panel of markers rather than relying on a single marker.
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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 | 0.000 | 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".