Utility of SOX6 and DAB2 for the Diagnosis of Malignant Mesothelioma
Bibliographic record
Abstract
The separation of malignant mesothelioma from non-small cell lung carcinomas can be a difficult problem. Sex-determining region Y box 6 (SOX6) and disabled homolog 2 (DAB2) have recently been proposed as sensitive/specific markers of mesothelial lineage, but have not yet been independently tested for utility in mesothelioma diagnosis. Using tissue microarrays containing mesotheliomas (epithelioid: n=40, sarcomatoid: n=23) and non-small cell lung carcinomas (adenocarcinoma: n=52, squamous cell carcinoma: n=57, large cell carcinoma: n=12) we evaluated the performance of SOX6 and DAB2 by themselves, in conjunction with other established mesothelioma markers (calretinin, WT1, D2-40, CK5/6, HEG1) and combined with 3 broad-spectrum established carcinoma markers: claudin-4, MOC31, and BerEP4. For epithelioid mesothelioma, SOX6 and DAB2 had sensitivities of 85% and 98%, respectively. For sarcomatoid mesothelioma, SOX6 had a sensitivity of 13% and DAB2 could not be assessed due to background stromal staining. For SOX6 alone, specificity for mesothelioma versus adenocarcinoma, squamous cell carcinoma, and large cell carcinoma was 94%, 79%, and 92%, respectively, while for DAB2 specificity was 77%, 86%, and 67%. Combinations of SOX6 and established mesothelioma markers produced sensitivities of 95% or greater. A combination of SOX6 positive/claudin-4 negative staining was 95% to 100% specific for mesothelioma versus carcinoma with a sensitivity of 85%. SOX6 is a promising marker for the diagnosis of mesothelioma and potentially could be combined with other mesothelial markers or a broad-spectrum carcinoma marker to reach an accurate diagnosis with relatively few immunostains, The relatively low specificity and difficulty of interpreting DAB2 staining limits its utility for mesothelioma diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".