Evaluation of PD-L1 expression and Associated Tumor-Infiltrating Lymphocytes in Laryngeal Squamous Cell Carcinoma
A partir d'échantillons tumoraux prélevés sur une cohorte initiale de 260 patients atteints d'un carcinome épidermoïde du larynx, puis validée sur une cohorte complémentaire de 89 patients, cette étude met en évidence une association entre le niveau d'expression de PD-L1, la densité des lymphocytes infiltrant les tumeurs et la survie des patients
Purpose: Programmed death-ligand 1 (PD-L1; also known as CD274 or B7-H1), expression represents a mechanism of immune escape for cancer. Our purpose was to characterize tumor PD-L1 expression and associated T cell infiltration in primary laryngeal squamous cell carcinomas (SCC).
Experimental Design: A well annotated cohort of 260 operable primary laryngeal SCCs (formalin-fixed paraffin embedded [FFPE] specimens) was morphologically characterized for stromal tumor infiltrating lymphocytes (TILs), on hematoxylin/eosin-stained whole sections and for PD-L1 mRNA expression by qRT-PCR in formalin-fixed paraffin embedded (FFPE) specimens. For PD-L1 protein expression automated quantitative protein analysis (AQUA) was applied on tissue microarrays consisting of two cores from these tumors. In addition, PD-L1 mRNA expression in fresh frozen tumors and normal adjacent tissue specimens was assessed in a second independent cohort of 89 patients with primary laryngeal SCC.
Results: PD-L1 mRNA levels were upregulated in tumors compared to surrounding normal tissue (p=0.009). TILs density correlated with tumor PD-L1 AQUA levels (p=0.021). Both high TILs density and high PD-L1 AQUA levels were significantly associated with superior disease-free survival (DFS) (TILs: p=0.009 and PD-L1: p=0.044) and overall survival (OS) (TILs: p=0.015 and PD-L1: p=0.059) of the patients and retained significance in multivariate analysis.
Conclusions: Increased TILs density and PD-L1 levels are associated with better outcome in laryngeal squamous cell cancer. Assessment of TILs and PD-L1 expression could be useful to predict response to immune checkpoint inhibitors.
Clinical Cancer Research , résumé, 2015