Background: Immunotherapy targeting PD-1 provides a limited survival benefit in patients with unresectable advanced or recurrent gastric cancer (GC). Beside PD-L1, the expression of inhibitory ligands such as CEACAM-1 and LSECtin on GC cells account for this limitation. Here we assessed their expression and immune suppressive effect in GC patients. Methods: Using multiplexed immunohistochemistry staining, we evaluated the distribution of different inhibitory ligands, including PD-L1, CEACAM-1, LSECtin, and MHC class II, in 365 GC patients. We analyzed their correlations and overall survival (OS) based on the expression of each inhibitory ligand and the independent prognostic factors that affect OS. Subsequently, we evaluated the additive effect of anti-PD-1 mAb or anti-PD-L1 mAb with/without anti-Lag-3 mAb with/without anti-Tim-3 mAb in cytotoxic assay using tumor-antigen specific CTL clones against GC cell lines. Results: Co-expression of the inhibitory ligands for PD-1, Tim-3, and Lag-3 was observed in the largest proportion (34.7%). CEACAM-1, LSECtin, and MHC class II expression showed significant correlation with PD-L1 expression and OS. Multivariable analysis demonstrated that CEACAM-1 low is an independent prognostic factor. Furthermore, combining dual and triple ICIs yielded additive effect on cytotoxicity of CTL clones against each immune inhibitory ligand positive GC cell lines. Conclusions: Our findings suggested that the expression of inhibitory ligands for Tim-3 and Lag-3 on GC cells serve as potential biomarkers to predict the response to anti-PD-1 therapy and the combinatorial immunotherapy with ICIs targeting for PD-1, Tim-3, and Lag-3 has a therapeutic potential for GC patients.
CITATION STYLE
Mimura, K., Kua, L. F., Xiao, J. F., Asuncion, B. R., Nakayama, Y., Syn, N., … Yong, W. P. (2021). Combined inhibition of PD-1/PD-L1, Lag-3, and Tim-3 axes augments antitumor immunity in gastric cancer–T cell coculture models. Gastric Cancer, 24(3), 611–623. https://doi.org/10.1007/s10120-020-01151-8
Mendeley helps you to discover research relevant for your work.