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Genome medicine, 2020-02, Vol.12 (1), p.22-22, Article 22
2020
Details
- Autor(en) / Beteiligte
- Titel
- Single-cell transcriptome analysis reveals TOX as a promoting factor for T cell exhaustion and a predictor for anti-PD-1 responses in human cancer
- Ist Teil von
- Genome medicine, 2020-02, Vol.12 (1), p.22-22, Article 22
- Ort / Verlag
- England: BioMed Central Ltd
- Erscheinungsjahr
- 2020
- Link zum Volltext
- Quelle
- Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
- Beschreibungen/Notizen
- T cells exhibit heterogeneous functional states in the tumor microenvironment. Immune checkpoint inhibitors (ICIs) can reinvigorate only the stem cell-like progenitor exhausted T cells, which suggests that inhibiting the exhaustion progress will improve the efficacy of immunotherapy. Thus, regulatory factors promoting T cell exhaustion could serve as potential targets for delaying the process and improving ICI efficacy. We analyzed the single-cell transcriptome data derived from human melanoma and non-small cell lung cancer (NSCLC) samples and classified the tumor-infiltrating (TI) CD8 T cell population based on PDCD1 (PD-1) levels, i.e., PDCD1-high and PDCD1-low cells. Additionally, we identified differentially expressed genes as candidate factors regulating intra-tumoral T cell exhaustion. The co-expression of candidate genes with immune checkpoint (IC) molecules in the TI CD8 T cells was confirmed by single-cell trajectory and flow cytometry analyses. The loss-of-function effect of the candidate regulator was examined by a cell-based knockdown assay. The clinical effect of the candidate regulator was evaluated based on the overall survival and anti-PD-1 responses. We retrieved many known factors for regulating T cell exhaustion among the differentially expressed genes between PDCD1-high and PDCD1-low subsets of the TI CD8 T cells in human melanoma and NSCLC. TOX was the only transcription factor (TF) predicted in both tumor types. TOX levels tend to increase as CD8 T cells become more exhausted. Flow cytometry analysis revealed a correlation between TOX expression and severity of intra-tumoral T cell exhaustion. TOX knockdown in the human TI CD8 T cells resulted in downregulation of PD-1, TIM-3, TIGIT, and CTLA-4, which suggests that TOX promotes intra-tumoral T cell exhaustion by upregulating IC proteins in cancer. Finally, the TOX level in the TI T cells was found to be highly predictive of overall survival and anti-PD-1 efficacy in melanoma and NSCLC. We predicted the regulatory factors involved in T cell exhaustion using single-cell transcriptome profiles of human TI lymphocytes. TOX promoted intra-tumoral CD8 T cell exhaustion via upregulation of IC molecules. This suggested that TOX inhibition can potentially impede T cell exhaustion and improve ICI efficacy. Additionally, TOX expression in the TI T cells can be used for patient stratification during anti-tumor treatments, including anti-PD-1 immunotherapy.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1756-994XeISSN: 1756-994XDOI: 10.1186/s13073-020-00722-9Titel-ID: cdi_doaj_primary_oai_doaj_org_article_11c908938c9c467ab68b4fdabbbf93d8
- Format
- –
- Schlagworte
- Analysis, Animals, Annotations, Anti-PD-1 immunotherapy, Cancer, Carcinoma, Non-Small-Cell Lung - drug therapy, Carcinoma, Non-Small-Cell Lung - genetics, Data analysis, Datasets, Fatigue, Female, Gene expression, Genes, High Mobility Group Proteins - genetics, High Mobility Group Proteins - metabolism, Humans, Immune checkpoint, Immune Checkpoint Inhibitors - therapeutic use, Immunotherapy, Intra-tumoral T cell exhaustion, Lung cancer, Lung cancer, Non-small cell, Lung Neoplasms - drug therapy, Lung Neoplasms - genetics, Lymphocytes, Lymphocytes T, Lymphocytes, Tumor-Infiltrating - immunology, Melanoma, Melanoma - drug therapy, Melanoma - genetics, Mice, Mice, Inbred C57BL, Non-small cell lung cancer, Patients, PD-1 protein, Programmed Cell Death 1 Receptor - antagonists & inhibitors, Programmed Cell Death 1 Receptor - genetics, Programmed Cell Death 1 Receptor - metabolism, Proteins, RNA sequencing, RNA-Seq, Scientific equipment and supplies industry, Scientific equipment industry, Single-Cell Analysis, Single-cell RNA sequencing, Small cell lung cancer, Software, Stem cells, T cells, Transcriptome, Tumor Cells, Cultured, Tumors