POLE Score: a comprehensive profiling of programmed death 1 ligand 1 expression in pancreatic ductal adenocarcinoma.
Oncotarget
; 10(16): 1572-1588, 2019 Feb 22.
Article
em En
| MEDLINE
| ID: mdl-30899426
ABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) being characterized by a pronounced stromal compartment is commonly diagnosed at an advanced stage limiting curative treatment options. Although therapeutical targeting of immune checkpoint regulators like programmed death 1 ligand 1 (PD-L1) represent a promising approach that substantially improved survival of several highly aggressive malignancies, convincing indicators for response prediction are still lacking for PDAC which might be attributed to the insufficient characterization of PD-L1 status. Therefore, we investigated PD-L1 expression by immunohistochemistry in a well characterized cohort of 59 PDAC and 18 peritumoral tissues. Despite the histopathological homogeneity within our cohort, tumor tissues exhibited a great heterogeneity regarding PD-L1 expression. Considering distinct PD-L1 expression patterns, we established the novel POLE Score that incorporates overall PD-L1 expression (P), cellular Origin of PD-L1 (O), PD-L1 level in tumor-associated Lymph follicles (L) and Enumerated local PD-L1 distribution (E). We show that tumoral PD-L1 expression is higher compared to peritumoral areas. Furthermore, POLE Score parameters correlated with overall survival, tumor grade, Ki67 status, local proximity of tumor cells and particular stroma composition. For the first time, we demonstrate that PD-L1 is mostly expressed by stroma and rarely by tumor cells in PDAC. Moreover, our in situ analyses on serial tissue sections and in vitro data suggest that PD-L1 is prominently expressed by tumor-associated macrophages. In conclusion, POLE Score represents a comprehensive characterization of PD-L1 expression in tumor and stroma compartment and might provide the basis for improved patient stratification in future clinical trials on PD-1/PD-L1 targeting therapies in PDAC.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article