Which dataset
would you like to
analyze in BBrowser?

Species: human
Number of cells: 9055
Study size: 750MB

Immunology 
Immunotherapy 
lung 
lung cancer 

Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing

Xinyi Guo, Yuanyuan Zhang, Liangtao Zheng, Chunhong Zheng, Jintao Song, Qiming Zhang, Boxi Kang, Zhouzerui Liu, Liang Jin, Rui Xing, Ranran Gao, Lei Zhang, Minghui Dong, Xueda Hu, Xianwen Ren, Dennis Kirchhoff, Helge Gottfried Roider, Tiansheng Yan, Zemin Zhang

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.

Download bbrowser to analyze now

About 1 datasets