bioRxivCancer BiologyPreprint
CEACAM5/6+ Tumor Cells and IL-1β+ Macrophages Drive Resistance to Chemo-immunotherapy in Gastric Cancer
Jian Chen, Liudeng ZhangiD, Yikai LuoiD, Xu HaniD, Muxing KangiD, Jing Chen, Wei LiuiD, Zhenzhen XuniD, Guofeng CheniD, Ke CheniD, Shenbin XuiD, Yu ZhangiD, Zhiwei WuiD, Wenxuan Wu, Z. R. Hao, Yaxuan HaniD, Qiaowei Lin, Yewei XuiD, Lie WangiD, Han LiangiD
Abstract
Chemo-immunotherapy is a first-line treatment for advanced gastric cancer, yet response rates remain limited and resistance mechanisms are poorly defined. Here we generate a single-cell atlas of 542,121 cells from 35 patients treated with anti-PD-1 plus chemotherapy, profiling pre- and post-treatment tumors linked to clinical response. Integrating spatial transcriptomics, immunohistochemistry, and bulk RNA sequencing, we identify two temporally distinct resistance programs. Intrinsic resistance in pre-treatment non-responders is marked by enrichment of CEACAM5/6 tumor cells that form immune-excluded spatial niches characterized by macrophage recruitment and CD8 T-cell exhaustion. Acquired resistance in post-treatment non-responders is driven by expansion of IL-1{beta} macrophages, which induces coordinated NF-{kappa}B activation across tumor and stromal compartments, promoting PD-L1 upregulation, epithelial-mesenchymal transition, and chronic inflammation. These findings delineate an evolutionary trajectory of resistance and nominate CEACAM5/6 and IL-1{beta} as predictive biomarkers and therapeutic targets to improve anti-PD-1-based combination strategies.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
- Citations
- 0
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