Objective: Programmed death ligand 1 (PD-L1) expression affects tumor evasion of immune surveillance. The prognostic value and relationship of PD-L1 expression to T-cell-inflamed immune signatures in ovarian cancer are unclear. The purpose of this study is to evaluate the impact of PD-L1 on overall survival and its correlation with an immune-mediated gene expression profile in patients with advanced ovarian cancer.
Methods: PD-L1 expression in tumor and immune cells was assessed by immunohistochemistry, and PD-L1-positive expression was defined as a combined positive score ≥1; a T-cell-inflamed gene expression profile containing interferon γ response genes was evaluated using extracted RNA from surgical samples. Associations between PD-L1 expression, gene expression profile status, and overall survival were analyzed using the Kaplan-Meier method, log-rank test, and multivariate Cox proportional hazards regression models.
Results: A total of 376 patients with advanced epithelial ovarian, primary peritoneal, or fallopian tube cancer treated by cytoreductive surgery and platinum-based therapy were included. PD-L1-positive expression was observed in 50.5% of patients and associated with more advanced stage (p=0.047), more aggressive histologic subtype (p=0.001), and platinum sensitivity defined by increasing treatment-free interval from first platinum-based chemotherapy to next systemic treatment (p=0.027). PD-L1-positive expression was associated with longer overall survival in multivariate analyses (adjusted HR 0.72, 95% CI 0.56 to 0.93). In subgroup analyses, this association was most pronounced in patients with partially platinum-sensitive disease (treatment-free interval ≥6 to <12 months). T-cell-inflamed gene expression profile status correlated with PD-L1 expression (Spearman, ρ=0.712) but was not an independent predictor of overall survival.
Conclusion: PD-L1 expression is associated with longer overall survival among advanced ovarian cancer patients. PD-L1 expression may be an independent prognostic biomarker.
Keywords: medical oncology.
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