Pan-cancer single-cell landscape of tumor-infiltrating T cells
Abstract
An atlas of cancer-associated T cells The tumor microenvironment contains many different kinds of immune cells, the composition, function, and roles of which are unclear. Using single-cell RNA sequencing of T cells in 21 cancer types from more than 300 patients, Zheng et al . identified differences in transcript composition that could be used to catalog different T cell types (see the Perspective by van der Leun and Schumacher). These annotations identified the different roles of specific types of CD4 + and CD8 + T cells among the different tumor types. Some of these clusters revealed evidence for two developmental paths for T cells, one of which shows a trajectory toward the “exhausted” T cell state, knowledge of which may be useful in developing future cancer immunotherapies. —LMZ
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Heavyweight studies on tumor-infiltrating lymphocytes have exhibited T cell and TCR clonotype diversity, constructing the landscape of T cell heterogeneity and dynamics in the tumor microenvironment.
“A series of heavyweight studies on the TILs have exhibited the T cell and TCR clonotype diversity, constructing the landscape of T cell heterogeneity and dynamics in the TME [135–137].”
From Single-cell sequencing to multi-omics: technologies and applications (2024) · cites this paper as [137]
Zhang's group pioneered development of multiple indicators such as STARTRAC, Ro/e, and OR to assess the status of TCR.
“From the excellent work of Zhang’s group, they pioneered the development of multiple indicators such as single T cell analysis by RNA sequencing and TCR tracking (STARTRAC) (for clonal expansion, tissue migration, and state transition), Ro/e, and OR (for tissue distribution) to assess the status of TCR [135–137].”
From Single-cell sequencing to multi-omics: technologies and applications (2024) · cites this paper as [137]
Single-cell sequencing revealed a standard developmental trajectory of Tregs in cancer, moving from a resting state (TNFRSF9− Tregs) to an activated state with increased suppressive capacity (TNFRSF9+ Tregs).
“Single-cell sequencing has revealed a standard developmental trajectory of Tregs in cancer, moving from a resting state (TNFRSF9− Tregs) to an activated state with increased suppressive capacity (TNFRSF9+ Tregs) [149] (Fig. 3C).”
From Potential anti-tumor effects of regulatory T cells in the tumor microenvironment: a review (2024) · cites this paper as [149]
CD8+ T cells showing high expression levels of KIRs are reported in peripheral blood of cancer patients.
“CD8+ T cells showing high expression levels of KIRs are also reported in peripheral blood of cancer patients”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [34]
A broader analysis revealed two subsets of GZMK+ Tem cells with transcriptional features similar to cTem cells and limited TCR sharing with tTex cells in various treatment-naive cancers.
“A broader analysis revealed two subsets of GZMK+ Tem cells with transcriptional features similar to cTem cells and limited TCR sharing with tTex cells in various treatment-naive cancers.34”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [34]
TCF7+ PDCD1+ Tpex cells are at low levels in HCC compared to other cancers such as head and neck squamous cell carcinoma (HNSCC) and melanoma.
“Given the low levels of TCF7+ PDCD1+ Tpex cells in HCC compared to other cancers such as head and neck squamous cell carcinoma (HNSCC) and melanoma,34”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [34]
Diffusion map based on TOSICA attention embedding recapitulates the previous observation that CD4+ T cells develop from naïve T cells to Temra cells, TFH/TH1 cells, or TNFRSF9+ Treg cells, separately.
“Diffusion map based on TOSICA attention embedding recapitulates the previous observation49 that CD4+ T cells develop from naïve T cells to Temra cells, TFH/TH1 cells, or TNFRSF9+ Treg cells, separately (Supplementary Fig. 14a–c).”
From Transformer for one stop interpretable cell type annotation (2023) · cites this paper as [49]
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- Authors
- Zheng, L., Qin, S., Si, W., Wang, A., Xing, B., Gao, R., Ren, X., Wang, L., Wu, X., Zhang, J., Wu, N., Zhang, N., Zheng, H., Ouyang, H., Chen, K., Bu, Z., Hu, X., Ji, J., & Zhang, Z.
- Affiliations
- Peking University (CN)
- Peking University Cancer Hospital (CN)
- Peking University Third Hospital (CN)
- Corresponding author
- Zheng, Liangtao
- Qin, Shishang
- Si, Wen
- Bu, Zhaode
- Hu, Xueda
- Ji, Jiafu
- Zhang, Zemin
- ORCID
- Venue
- Science
- Published
- 2021-12-17
- Volume
- 374
- Issue
- 6574
- Pages
- abe6474-abe6474
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4200468913
- Cited by
- 1,402
- References
- 18
- Citations by year
- 2026: 276 · 2025: 362 · 2024: 388 · 2023: 262 · 2022: 113 · 2021: 1
- FWCI
- 72.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- tumor-infiltrating T cells, tumor microenvironment, pan-cancer analysis, T cell exhaustion, CD4+ T cells, CD8+ T cells, T cell transcriptome, cancer immunotherapy, single-cell RNA sequencing
- MeSH terms
- RNA-Seq, Memory T Cells, Cell Differentiation, Humans, Neoplasms, Receptors, Antigen, T-Cell, Transcription Factors, CD4-Positive T-Lymphocytes, Gene Expression Regulation, Neoplastic, T-Lymphocyte Subsets, Lymphocytes, Tumor-Infiltrating, CD8-Positive T-Lymphocytes, Single-Cell Analysis, Tumor Microenvironment, Transcriptome
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