Immunohistochemical Profiling of Endometrial Serous Carcinoma
Bibliographic record
Abstract
Endometrial serous carcinoma (ESC) is an aggressive neoplasm mainly seen in older women. The objective of this study was to refine immunohistochemical (IHC) panels for the differential diagnoses against endometrial endometrioid grade 3 (EC3), endometrial clear cell, and ovarian high-grade serous carcinoma as well as exploring the prognostic role of selected IHC markers. Fifty-two ESC from a single institution were assessed for 20 IHC markers, including ARID1A, CCNE1, CDKN2A, ERBB2, ESR1, HNF1B, FBXW7, IGF2BP3, MLH1, MSH2, MSH6, NAPSA, PAX8, PGR, PMS2, PTEN, TFF3, TP53, VIM, and WT1. ERBB2 chromogenic in situ hybridization was evaluated on tissue microarrays. Statistical analysis was performed. All ESC showed aberrant TP53, normal mismatch repair protein, and retained ARID1A and PTEN expression. ESR1 expression was present in 80% of ESC. A combination of TP53, PTEN, and CDKN2A had a sensitivity of 93.6% [95% confidence interval (CI), 84%-98%] and specificity of 87.8% (95% CI, 75%-95%) for ESC versus EC3. A combination of NAPSA and ESR1 had a sensitivity of 97.9% (95% CI, 89%-99%) and specificity of 72.2% (95% CI, 46%-90%) for ESC versus clear cell carcinoma. Absence of WT1 alone had a sensitivity of 66.0% (95% CI, 51%-79%) and specificity of 98.0% (95% CI, 94%-99%) for ESC versus ovarian high-grade serous carcinoma. Among all 52 ESCs, ERBB2 amplification was present in 23%, FBXW7 expression was absent in 10%, and CCNE1 was overexpressed in 59%, however, none were associated with prognosis. Our data support the value of IHC marker panels for histotyping of high-grade endometrial 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 | 0.000 | 0.004 |
| 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 | 0.000 |
| 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".