Utility of Methylthioadenosine Phosphorylase Compared With BAP1 Immunohistochemistry, and CDKN2A and NF2 Fluorescence In Situ Hybridization in Separating Reactive Mesothelial Proliferations From Epithelioid Malignant Mesotheliomas
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Bibliographic record
Abstract
CONTEXT.—: The separation of reactive from malignant mesothelial proliferations is often a difficult morphologic problem. There is contradictory information in the literature on whether methylthioadenosine phosphorylase (MTAP) immunohistochemistry can be used for this purpose. OBJECTIVE.—: To determine the utility of MTAP immunohistochemistry in distinguishing reactive from malignant mesothelial proliferations. DESIGN.—: We stained a tissue microarray containing 20 epithelioid malignant mesotheliomas and 17 reactive mesothelial proliferations. For the mesotheliomas, comparisons were made between MTAP staining and BRCA-associated nuclear protein 1 (BAP1) immunohistochemistry, cyclin-dependent kinase inhibitor 2A ( CDKN2A) fluorescence in situ hybridization, and neurofibromin 2 ( NF2) fluorescence in situ hybridization, which are established techniques for making this separation. RESULTS.—: Loss of MTAP was seen in 0 of 17 reactive mesothelial proliferations and 13/20 (65%) malignant mesotheliomas. Almost all cases with loss showed loss in 100% of mesothelial cells. Background inflammatory and stromal cells served as a positive internal control. CDKN2A fluorescence in situ hybridization on the mesotheliomas showed concordance with MTAP staining in 14 of 17 evaluable cases. BAP1 immunohistochemistry showed loss of nuclear staining in 11 of 20 mesotheliomas (55%). No cases showed loss of NF2. A total of 18 of 20 mesotheliomas (90%) showed loss of either MTAP or BAP1. CONCLUSIONS.—: In the context of a mesothelial proliferation, loss of MTAP staining is 100% specific for malignant mesothelioma. In this study the combination of MTAP and BAP1 immunohistochemical staining allowed separation of reactive from epithelial malignant mesothelial proliferations in 90% of cases.
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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 | 0.002 |
| 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 it