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

Yang Chen, Keren Jia, Yu Sun, Cheng Zhang, Yilin Li, Li Zhang, Zifan Chen, Jiangdong Zhang, Yajie Hu, Jiajia Yuan, Xingwang Zhao, Yanyan Li, Jifang Gong, Bin Dong, Xiaotian Zhang, Jian Li and Lin Shen ()
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Yang Chen: Peking University Cancer Hospital and Institute
Keren Jia: Peking University Cancer Hospital and Institute
Yu Sun: Peking University Cancer Hospital and Institute
Cheng Zhang: Peking University Cancer Hospital and Institute
Yilin Li: Peking University Cancer Hospital and Institute
Li Zhang: Peking University
Zifan Chen: Peking University
Jiangdong Zhang: Peking University
Yajie Hu: Peking University
Jiajia Yuan: Peking University Cancer Hospital and Institute
Xingwang Zhao: Peking University Cancer Hospital and Institute
Yanyan Li: Peking University Cancer Hospital and Institute
Jifang Gong: Peking University Cancer Hospital and Institute
Bin Dong: Peking University
Xiaotian Zhang: Peking University Cancer Hospital and Institute
Jian Li: Peking University Cancer Hospital and Institute
Lin Shen: Peking University Cancer Hospital and Institute

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-32570-z

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