Sox10 and S100 in the Diagnosis of Soft-tissue Neoplasms
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Bibliographic record
Abstract
Despite a well-characterized lack of specificity, pathologists routinely employ S100 in the diagnosis of neural crest-derived tumors. Recent studies have shown that Sox10 is a reliable marker of neural crest differentiation that is consistently expressed in schwannian and melanocytic tumors. We sought to validate these results in a larger series of soft tissue neoplasms of both neural crest and non-neural crest origin, and to further characterize the sensitivity and specificity of Sox10 for use in clinical diagnosis. We evaluated Sox10 and S100 mRNA levels in 122 cases of peripheral nerve sheath tumors and synovial sarcoma and used immunohistochemistry for Sox10 and S100 protein expression in 1012 tissue specimens. This study includes 174 tissue microarray cases previously reported by Nonaka and colleagues, which include cases of melanoma, dermatofibrosarcoma protuberans, neurofibroma, synovial sarcoma, clear-cell sarcoma, malignant peripheral nerve sheath tumor (MPNST), perineurioma, and schwannoma. Synovial sarcomas expressed significantly higher levels of S100B than Sox10 (P=7.9×10), and no significant Sox10 mRNA expression was identified in synovial sarcoma (n=40), whereas 18/40 cases showed comparatively increased levels of S100 mRNA. The majority of schwannomas (n=26) and neurofibromas (n=28) showed relatively an increased expression of both Sox10 and S100 mRNA. MPNSTs (n=28) showed variable levels of Sox10 and S100 mRNA expression, and these expression levels were highly correlated (Pearson correlation coefficient r=0.79). In contrast, immunohistochemistry performed on a larger and more varied number of cases highlighted significant differences between the 2 proteins. We identified 5 non-neural, nonmelanocytic sarcoma types in which a subset of cases showed S100 protein expression: synovial sarcoma (12/79, 15%), Ewing sarcoma (3/14, 21%), rhabdomyosarcoma (4/17, 24%), chondrosarcoma (3/4, 75%), and extraskeletal myxoid chondrosarcoma (5/11, 45%). For each of these entities, we identified cases with strong and diffuse S100 staining. Of these cases, only 1 case of rhabdomyosarcoma showed focal Sox10 positivity. In 78 cases of MPNST, S100 increased the sensitivity (31/78, 40%) as compared with Sox10 (21/78, 27%), but the majority of these cases were negative for both Sox10 and S100 (44/78, 56%). Sox10 proved superior to S100 in the detection of desmoplastic melanoma (7/9, 78%) and clear-cell sarcoma (4/7, 57%). We also report for the first time Sox10 expression in 26 cases of granular cell tumor, further supporting the neural crest derivation of this tumor. Excluding MPNST, S100 and Sox10 showed similar sensitivity in tumors of neural crest origin (140/148, 95% and 137/148, 93%, respectively). In summary, Sox10 shows an increased specificity for tumors of neural crest origin compared with S100: Sox10 was positive in only 5 of 668 cases (99% specificity) in nonschwannian, nonmelanocytic tumors, whereas S100 was positive in 53 of 668 cases (91% specificity). Sox10 should be used in the place of or along with S100 in soft tissue tumor diagnosis.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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