Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment.

Chen, Yang; Jia, Keren; Sun, Yu; Zhang, Cheng; Li, Yilin; Zhang, Li; Chen, Zifan; Zhang, Jiangdong et al. · Nat Commun · 2022

basic_science · Level V

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Abstract

A single biomarker is not adequate to identify patients with gastric cancer (GC) who have the potential to benefit from anti-PD-1/PD-L1 therapy, presumably owing to the complexity of the tumour microenvironment. The predictive value of tumour-infiltrating immune cells (TIICs) has not been definitively established with regard to their density and spatial organisation. Here, multiplex immunohistochemistry is used to quantify in situ biomarkers at sub-cellular resolution in 80 patients with GC. To predict the response to immunotherapy, we establish a multi-dimensional TIIC signature by considering the density of CD4+FoxP3-PD-L1+, CD8+PD-1-LAG3-, and CD68+STING+ cells and the spatial organisation of CD8+PD-1+LAG3- T cells. The TIIC signature enables prediction of the response of patients with GC to anti-PD-1/PD-L1 immunotherapy and patient survival. Our findings demonstrate that a multi-dimensional TIIC signature may be relevant for the selection of patients who could benefit the most from anti-PD-1/PD-L1 immunotherapy.

Medical subject headings