Tubo-Ovarian Transitional Cell Carcinoma and High-grade Serous Carcinoma Show Subtly Different Immunohistochemistry Profiles
Bibliographic record
Abstract
Tubo-ovarian transitional cell carcinoma (TCC) is grouped with high-grade serous carcinoma (HGSC) in the current World Health Organization classification. TCC is associated with BRCA mutations and a better prognosis compared with HGSC. Previous papers examining the immunohistochemical features of TCC have studied limited numbers of samples. No marker reflecting the biological difference between TCC and HGSC is known. We collected a large cohort of TCC to determine whether TCC and HGSC could be distinguished by immunohistochemistry. A tissue microarray was built from 89 TCC and a control cohort of 232 conventional HGSC. Immunohistochemistry was performed, scored, and statistically analyzed for routine markers of HGSC and urothelial tumors: PAX8, WT1, p53, p16, ER, p63, and GATA3. Using scoring cutoffs commonly employed in clinical practice, the immunohistochemical profile of TCC was indistinguishable from HGSC for all markers. However, more detailed scoring criteria revealed statistically significant differences between the 2 groups of tumors with respect to ER, PAX8, and WT1. HGSC showed more diffuse and intense staining for PAX8 (P=0.004 and 0.001, respectively) and WT1 (P=0.002 and 0.002, respectively); conversely, TCC showed more intense staining for ER (P=0.007). TCC and HGSC therefore show subtle differences in their immunohistochemical profiles which might reflect underlying (epi)genetic differences. Further studies using proteomic analysis will focus on the identification of differentially expressed proteins that might serve as markers of TCC-like differentiation, which could help explain biologic differences between TCC and HGSC and might identify other cases of HGSC with a better prognosis.
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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) | 0.001 | 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 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".