T-bet+CD8+ T cells govern anti-PD-1 responses in microsatellite-stable gastric cancers
Shiying Tang, Xiaofang Che, Jinyan Wang, Ce Li, Xin He, Kezuo Hou, Xiaojie Zhang, Jia Guo, Bowen Yang, Danni Li, Lili Cao, Xiujuan Qu, Zhenning Wang, Yunpeng Liu
Abstract
More than 90% of advanced gastric cancers (GC) are microsatellite-stable (MSS). Compared to the high response rate of immune checkpoint inhibitors (ICI) in microsatellite-instability-high (MSI-H) GCs, only 10% of unstratified MSS GCs respond to ICIs. In this study, we apply semi-supervised learning to stratify potential ICI responders in MSS GCs, achieving high accuracy, quantified by an area under the curve of 0.924. Spatial analysis of the tumor microenvironment of ICI-sensitive GCs reveals a high level of T-bet+ CD8 + T cell infiltration in their tumor compartments. T-bet+ CD8 + T cells exhibit superior anti-tumor activity due to their increased ability to infiltrate tumors and secrete cytotoxic molecules. Adoptive transfer of T-bet+ CD8 + T cells boosts anti-tumor immunity and confers susceptibility to ICIs in immune-ignorant MSS GCs in a humanized mouse model. Spatial RNA sequencing suggests a positive-feedback loop between T-bet+ T cells and PD-L1+ tumor cells, which eventually drives T cell exhaustion and can therefore be leveraged for ICI therapy. In summary, our research provides insights into the underlying mechanism of anti-tumor immunity and deepens our understanding of varied ICI responses in MSS GCs. Microsatellite-instability-high gastric cancers typically respond to immune checkpoint inhibitors, but only a small proportion of patients in the microsatellite-stable group responds. Here authors stratify these patients via a semi-supervised learning approach using multi-omics input data and functionally validate T-bet+ CD8 + T cells as crucial factor in the immunotherapy response.