Cancer immunotherapies have shown sustained clinical responses in treating non-small-cell lung cancer1,2,3, but efficacy varies and depends in part on the amount and properties of tumor infiltrating lymphocytes4,5,6. To depict the baseline landscape of the composition, lineage and functional states of tumor infiltrating lymphocytes, here we performed deep single-cell RNA sequencing for 12,346 T cells from 14 treatment-naïve non-small-cell lung cancer patients. Combined expression and T cell antigen receptor based lineage tracking revealed a significant proportion of inter-tissue effector T cells with a highly migratory nature. As well as tumor-infiltrating CD8+ T cells undergoing exhaustion, we observed two clusters of cells exhibiting states preceding exhaustion, and a high ratio of “pre-exhausted” to exhausted T cells was associated with better prognosis of lung adenocarcinoma. Additionally, we observed further heterogeneity within the tumor regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of those activated tumor Tregs, which included IL1R2, correlated with poor prognosis in lung adenocarcinoma. Our study provides a new approach for patient stratification and will help further understand the functional states and dynamics of T cells in lung cancer.
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We thank S. Geng for discussions and members of the BIOPIC high-throughput sequencing facility and the Computing Platform of the Centre for Life Science. We also thank the National Centre for Protein Sciences Beijing (Peking University) and F. Wang, X. Zhang, S. Wang and Z. Fu for assistance with FACS. This project was supported by grants from the Beijing Advanced Innovation Centre for Genomics at Peking University, Key Technologies R&D Program (2016YFC0900100), the National Natural Science Foundation of China (81573022, 31530036, 91742203) and Bayer AG (Germany). C. Zheng and L. Zhang were supported by the Postdoctoral Foundation of Centre for Life Sciences at Peking University–Tsinghua University.
The authors declare no competing interests.
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Supplementary Figures 1–10
Patient information and sequencing statistics
TCR typing of single T cells
List of signature genes of each T cell cluster
List of genes specifically expressed in exhausted tumor T cells
Differentially expressed genes of suppressive tumor Treg cells in CD4–C9–CTLA4
Differentially expressed genes of activated tumor Treg cells in CD4–C9–CTLA4
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Guo, X., Zhang, Y., Zheng, L. et al. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing. Nat Med 24, 978–985 (2018). https://doi.org/10.1038/s41591-018-0045-3
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