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The local immune landscape determines tumor PD-L1 heterogeneity and sensitivity to therapy
Yuan Wei, … , Limin Zheng, Dong-Ming Kuang
Yuan Wei, … , Limin Zheng, Dong-Ming Kuang
Published August 1, 2019; First published May 21, 2019
Citation Information: J Clin Invest. 2019;129(8):3347-3360. https://doi.org/10.1172/JCI127726.
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Categories: Research Article Immunology Inflammation

The local immune landscape determines tumor PD-L1 heterogeneity and sensitivity to therapy

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Abstract

Programmed death-1 receptor ligand 1 (PD-L1) is a promising therapeutic target in aggressive cancers. However, immune landscapes and cancer hallmarks of human PD-L1+ tumors as well as their roles in determining therapeutic efficacies are unknown. Here, we showed, in detailed studies of gene data regarding 9769 patients of 32 types of human cancers, that PD-L1 could not exclusively represent the IFN-γ signature and potentially signified proinflammatory myeloid responses in a tumor. PD-L1 heterogeneity endowed by local immune landscapes controlled cancer hallmarks and clinical outcomes of patients. Mechanically, NF-κB signal elicited by macrophage inflammatory responses generated PD-L1+ cancer cells exhibiting capabilities to aggressively survive, support angiogenesis, and metastasize, whereas STAT1 signal triggered by activated T cells induced PD-L1+ cancer cells susceptive to apoptosis. Importantly, PD-L1+ cancer cells generated by macrophages established great resistance to conventional chemotherapy, cytotoxicity of tumor-specific effector T cells, and therapy of immune-checkpoint blockade. Therapeutic strategy combining immune-checkpoint blockade with macrophage depletion or NF-κB inhibition in vivo effectively and successfully elicited cancer regression. Our results provide insight into the functional features of PD-L1+ tumors and suggest that strategies to influence functional activities of inflammatory cells may benefit immune-checkpoint blockade therapy.

Authors

Yuan Wei, Qiyi Zhao, Zhiliang Gao, Xiang-Ming Lao, Wei-Ming Lin, Dong-Ping Chen, Ming Mu, Chun-Xiang Huang, Zheng-Yu Liu, Bo Li, Limin Zheng, Dong-Ming Kuang

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ISSN: 0021-9738 (print), 1558-8238 (online)

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