Prognostic Value of PD-L1, BAP-1 and ILK in Pleural Mesothelioma

Background: Pleural mesothelioma (PM) is a rare type of cancer with poor prognosis. Prognostic and predictive biomarkers could improve treatment strategies in these patients. Programmed death ligand 1 (PD-L1), integrin-linked kinase (ILK) and breast cancer gene 1-associated protein (BAP-1) have been proposed to predict outcomes in PM, but existing data are limited and controversial. Design and Methods: This single-center, retrospective study analyzed data on expression patterns and the prognostic role of PD-L1, ILK and BAP-1 in consecutive patients diagnosed with PM. Results: Of all patients (n = 52) included, more than half showed a positive PD-L1 expression (52% TPS ≥ 1%, 65% CPS ≥ 1), 69% showed a BAP-1 loss and 80% an ILK ≥ 50%. Positive PD-L1 expression was more frequent in the non-epithelioid subtype (p = 0.045). ILK intensity (p = 0.032) and positive PD-L1 (p = 0.034) were associated with more advanced tumor stages. The median overall survival (OS) was 16.9 (95% CI 13.1-25.2) months. Multimodality therapy (MMT) including surgery and early stage were independent prognostic factors for longer OS (MMT: HR 0.347, 95% CI 0.13-0.90, p = 0.029; advanced stage: HR 4.989; 95% CI 1.64-15.13, p = 0.005). Patients with an expression of PD-L1 TPS ≥ 1% or BAP-1 positivity showed numerically worse survival with a median OS of 15.3 (11.5; 24.4) vs. 20.0 (11.2; 34.9) and 11.3 (5.6; 31.0) vs. 20.0 (15.2; 28.1) months, respectively. Furthermore, PD-L1 was associated with worse survival in patients receiving MMT (PD-L1 TPS ≥ 1%: 15.8 (12.1-25.4) vs. 31.3 (17.4-95.4) p = 0.053). ILK expression ≥50% did not influence survival. The combinations of CPS ≥ 1% with BAP-1 positivity or ILK expression ≥50% were associated with worse survival (p = 0.045, p = 0.019). Conclusions: In this real-world analysis, expressions of PD-L1 and BAP-1 were associated with worse survival in patients with PM. ILK showed no prognostic value. Further studies with larger cohorts are needed to identify prognostic and predictive biomarkers facilitating optimized individual treatment decision in this rare type of cancer.