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

Yang ChenKeren JiaYu SunCheng ZhangYilin LiLi ZhangZifan ChenJiangdong ZhangYajie HuJiajia YuanXingwang ZhaoYanyan LiJifang GongBin DongXiaotian ZhangJian LiLin Shen
Published in: Nature communications (2022)
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.
Keyphrases
  • stem cells
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  • immune response
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  • mass spectrometry
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  • mesenchymal stem cells
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  • cell cycle arrest
  • smoking cessation
  • climate change
  • pi k akt