Significant overexpression of the Merkel cell polyomavirus (MCPyV) large T antigen in Merkel cell carcinoma
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to determine the expression pattern of the Merkel cell polyomavirus (MCPyV) large T-protein antigen in patients with Merkel cell carcinoma. METHODS: A tissue microarray (TMA) containing 30 specimens was constructed and stained for the MCPyV large T protein. Immunohistochemical expression was determined semiquantitively and was compared to patients' outcome. RESULTS: Nuclear expression of MCPyV large T protein was detected in 29 of 30 specimens (97%). In particular, 60% to 100%, 30% to 60%, and 10% to 30% of tumor cells were positive in 27 specimens (90%), 1 (3%), and 1 (3%), respectively. There was no difference in positivity between primary and metastatic lesions. Clinical data could not be correlated to MCPyV large T-protein expression. CONCLUSION: MCPyV large T protein was significantly overexpressed in 97% of all specimens. Although we could not demonstrate a predictive effect, MCPyV large T protein may represent a molecular marker with utility in pathological diagnosis as well as a potential new therapeutic target in patients with Merkel cell carcinoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".