Assessment Of Tumour Infiltrating Lymphocytes And Pd-l1 Expression In Adenoid Cystic Carcinoma Of The Salivary Gland
Bibliographic record
Abstract
PURPOSE: Early phase clinical studies are ongoing to evaluate the role of immune checkpoint inhibitors in adenoid cystic carcinoma (ACC) despite a paucity of information on the immune microenvironment. This study aims to better characterize the immune microenvironment of ACC tumours and evaluate survival outcomes based on tumour infiltrating lymphocyte (TIL) and programmed death-ligand 1 (PD-L1) expression. METHODS: Patient characteristics, treatment and outcome data were collected for 24 ACC patients. The CD8+(cluster of differentiation 8) TIL and PD-L1 expression were quantified by immunohistochemistry. Marker expression and survival outcomes were evaluated by Kaplan-Meier analysis. RESULTS: All cases were negative for PD-L1 expression; four cases had focal high, eight cases had focal moderate and 12 cases had low TIL expression. Based on TIL expression, there was no difference in disease-free or overall survival. CONCLUSION: Adenoid cystic carcinoma tumours were found to be associated with a poor immunogenic microenvironment, with absent PD-L1 expression and low CD8+ TILs. There was no association between TIL expression and survival. These data suggest that PD-L1 and TIL expression are unlikely to be useful as predictive biomarkers for response to immunotherapy.
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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 | 0.001 | 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".