Global PD-L1 Signals and Tumor-Infiltrating Lymphocytes: Markers of Immunogenicity in Different Subsets of Merkel Cell Carcinoma and Potential Therapeutic Implications
Bibliographic record
Abstract
We previously studied the genetic and immunohistochemical profiles of subsets of Merkel cell carcinoma (MCC) stratified by morphology and Merkel cell polyomavirus (MCPyV) status. Recent advances in the immunotherapy of this disease prompted us to examine markers of immunogenicity [PD-L1 expression and tumor-infiltrating lymphocytes (TILS) in these subsets]. The observed clinical responses to checkpoint inhibition of the PD-1/PD-L1 pathway have not correlated with PD-L1 expression by MCC cells, and recent evidence suggests that functions of this pathway within the immune tumor microenvironment may be relevant. We conducted a semiquantitative (high, moderate, and minimal) immunohistochemical evaluation of the global PD-L1 signal in 52 cases of MCC, segregated in 3 subsets [pure MCPyV-positive (n = 28), pure MCPyV-negative (n = 9), and combined MCPyV-negative (n = 15)]. TILS were categorized as brisk, nonbrisk, or absent. Intersubset comparisons revealed that high global PD-L1 signals were exclusively associated with pure MCPyV-positive MCCs contrasted with virus-negative cases (P = 0.0003). Moderate signals were seen across all 3 groups. Brisk TILS were significantly associated with MCPyV-positive MCCs compared with MCPyV-negative cases (P = 0.029). Neither parameter (PD-L1 or TILS) was significantly different between the MCPyV-negative groups. Of potential clinical relevance, MCPyV seems to convey greater immunogenicity to MCCs than the high mutational burden/greater neoantigen load of MCPyV-negative cases. Interesting too is the fact that subset-related profiles of these markers mirrored those noted at genetic and immunohistochemical levels, separating pure MCPyV-positive MCCs from the virus-negative subsets.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".