Negative prognostic behaviour of PD-L1 expression in tongue and larynx squamous cell carcinoma and its significant predictive power in combination with PD-1 expression on TILs
Bibliographic record
Abstract
BACKGROUND: Biomarkers that can predict outcome will improve the efficacy of treatment for HNSCC patients. In this regard, we retrospectively evaluated the prognostic effect of PD1, PD-L1, and CD45RO in tongue and larynx squamous cell carcinomas. METHODS: FFPE tissue blocks of 63 larynx and 40 tongue squamous cell carcinoma samples were selected, cut into 3 µm sections, and immunohistochemically stained for PD1, PD-L1, and CD45RO. The slides were evaluated by an expert pathologist, and results were analysed using Chi-square, univariate, and multivariable Cox regression methods. RESULTS: TC-PD-L1 expression (P = 0.001) and its expression intensity (P = 0.002) were significantly correlated with a higher percentage of PD-1 + tumor infiltrating lymphocytes. In univariate survival analysis, TC-PD-L1 and its expression intensity had a significant impact on both DFS (HR: 0.203; P = 0.003 and HR: 0.320; P = 0.005) and OS (HR: 0.147; P = 0.002 and HR: 0.322; P = 0.005). Based on the multivariate analysis, PD1 (DFS: HR: 3.202; P = 0.011, OS: HR: 2.671; P = 0.027) and TC-PD-L1 (DFS: HR: 0.174; P = 0.006, OS: HR: 0.189; P = 0.009) were found to be independent prognostic markers. In the second part, scoring systems were defined based on the expression status of PD1 and PD-L1. Patients with higher scores were expected to have longer DFS and OS. In multivariate analysis, the PD1/TC-PD-L1 (DFS: P = 0.001, OS: P = 0.003) scoring systems showed superior prognostic effects. Interestingly, at the highest levels of this score, none of the patients experienced recurrence or cancer-caused death. CONCLUSION: Collectively, this study suggests negative prognostic behaviour for TC-PD-L1 protein and introduces the PD-1/TC-PD-L1 scoring system as a strong prognostic marker in OS and DFS prediction of tongue and larynx HNSCC patients.
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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) | 0.000 | 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 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".