Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment

平行单细胞和批量转录组分析揭示胃肿瘤微环境的关键特征

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作者:Boxi Kang #, Jordi Camps #, Biao Fan #, Hongpeng Jiang #, Mahmoud M Ibrahim, Xueda Hu, Shishang Qin, Dennis Kirchhoff, Derek Y Chiang, Shan Wang, Yingjiang Ye, Zhanlong Shen, Zhaode Bu, Zemin Zhang, Helge G Roider7

Background

The tumor microenvironment (TME) has been shown to strongly influence treatment outcome for cancer patients in various indications and to influence the overall survival. However, the cells forming the TME in gastric cancer have not been extensively characterized.

Conclusions

Our gastric cancer single-cell TME compendium together with the matched bulk transcriptome data provides a unique resource for the identification of new potential biomarkers for patient stratification. This study helps further to elucidate the mechanism of gastric cancer and provides insights for therapy.

Results

We combine bulk and single-cell RNA sequencing from tumors and matched normal tissue of 24 treatment-naïve GC patients to better understand which cell types and transcriptional programs are associated with malignant transformation of the stomach. Clustering 96,623 cells of non-epithelial origin reveals 81 well-defined TME cell types. We find that activated fibroblasts and endothelial cells are most prominently overrepresented in tumors. Intercellular network reconstruction and survival analysis of an independent cohort imply the importance of these cell types together with immunosuppressive myeloid cell subsets and regulatory T cells in establishing an immunosuppressive microenvironment that correlates with worsened prognosis and lack of response in anti-PD1-treated patients. In contrast, we find a subset of IFNγ activated T cells and HLA-II expressing macrophages that are linked to treatment response and increased overall survival. Conclusions: Our gastric cancer single-cell TME compendium together with the matched bulk transcriptome data provides a unique resource for the identification of new potential biomarkers for patient stratification. This study helps further to elucidate the mechanism of gastric cancer and provides insights for therapy.

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