Transitional Cell Carcinoma of the Ovary is Related to High-grade Serous Carcinoma and is Distinct From Malignant Brenner Tumor
Bibliographic record
Abstract
Transitional cell tumors of the ovary include benign, borderline (atypically proliferating), and malignant Brenner tumors (BT), as well as transitional cell carcinoma (TCC). Some TCCs could conceivably be examples of malignant BT where the benign component has been overgrown. Our objectives were: (A) compare the immunophenotypes of BT and TCC and (B) examine a large cohort of ovarian carcinomas for cases with the immunophenotype of BT and transitional features but lacking a benign BT component. Seven BTs (3 benign, 3 borderline/atypically proliferating, 1 malignant) and 7 TCCs were stained for WT1, ER, p53, and p16(INK4a). The BTs were negative for WT1, p53 overexpression, ER (except for weak positivity in 1), and negative or weakly positive for p16(INK4a). In contrast, the TCCs stained as follows: 4/6 positive for WT1, 5/7 positive for ER, 2/7 strongly positive for p16(INK4a), and 6/7 showed abnormal p53, an immunophenotype resembling that of high-grade serous carcinoma. A database of 500 cases of ovarian carcinoma was searched and 116 showed an immunoprofile characteristic of BT: WT1 negative, ER negative, p16(INK4a) or weak positive, p53 negative (77 clear cell carcinoma, 14 endometrioid carcinoma, 12 mucinous carcinoma, 8 high-grade serous carcinoma). None of these tumors showed transitional features on review, indicating that if examples of malignant BT where there has been overgrowth of benign BT components exist, they are rare. Our results suggest that BT and TCC are unrelated, and should not be combined for classification purposes.
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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) | 0.002 | 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".