<scp>CD99</scp> expression in Merkel cell carcinoma: a case series with an unusual paranuclear dot‐like staining pattern
Bibliographic record
Abstract
BACKGROUND: Merkel cell carcinoma (MCC) is a rare neuroendocrine cancer of the skin. The utility of CD99 (MIC-2) in the diagnosis of MCC has been previously studied, with reported rates of expression ranging from 13 to 55%. When specified, a membranous or cytoplasmic staining pattern was considered significant. Recent studies of CD99 have identified a paranuclear dot-like expression pattern in certain non-neuroendocrine pancreatic and colonic lesions. We recently noted paranuclear dot-like staining in several cases of MCC, including cases lacking cytokeratin 20 (CK20) expression. METHODS: Fourteen cases of MCC were stained with CK20 and CD99 antibody, and the pattern and intensity of staining were recorded. Seven cases of pulmonary small cell carcinoma (PSCC) and one case of primitive neuroectodermal tumor (PNET) were used for comparison. RESULTS: All 14 cases of MCC showed at least focal CD99 staining, with both membranous and paranuclear dot-like staining patterns identified. CK20 staining was present in 12/14 cases, with the characteristic dot-like pattern identified. Four of seven cases of PSCC showed CD99 staining, with two showing a finely granular dot-like staining pattern. CONCLUSIONS: We report an unusual pattern of paranuclear dot-like expression of CD99 in 14 cases of MCC, two of which did not express CK20. This previously unrecognized expression pattern may be of use in differentiating MCC from other cutaneous malignancies, especially when CK20 expression is limited or absent.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".