Transcriptomics

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T cell landscape of non-small cell lung cancer revealed by deep single-cell RNA sequencing


ABSTRACT: Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but the clinical outcome is not uniform among patients, with complex tumour-immune interactions playing key roles. To depict and dissect the baseline landscape of the composition, lineage and functional states of tumor-infiltrating lymphocytes (TILs) in lung cancer, here we generated deep single-cell RNA sequencing data for 12346 T cells from the tumour, adjacent normal tissues and peripheral blood from 14 treatment-naïve NSCLC patients. Based on expression and TCR-based lineage tracking, we found a significant proportion of effector memory T cells with the same origin and similar functional states across peripheral blood and tumours, indicating the existence of systemic T cell immunity. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion in tumours, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of “pre-exhausted” to exhausted T cells was associated with better prognosis of lung adenocarcinoma. In addition, we observed a specific cluster of tumour-specific regulatory T cells (Tregs), characterized by a set of immunosuppressive genes, and high expression of their signature genes, including IL1R2, correlated with poor prognosis of lung adenocarcinoma. These findings and the accompanying compendium of single cell data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE99254 | GEO | 2018/06/25

REPOSITORIES: GEO

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