The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance
Open accessAbstract
A single-cell analysis of tumor-infiltrating T cells from 16 cancer types identifies new T cell subsets and a stress response cell state enriched in tumors resistant to immunotherapy. Tumor-infiltrating T cells offer a promising avenue for cancer treatment, yet their states remain to be fully characterized. Here we present a single-cell atlas of T cells from 308,048 transcriptomes across 16 cancer types, uncovering previously undescribed T cell states and heterogeneous subpopulations of follicular helper, regulatory and proliferative T cells. We identified a unique stress response state, T_STR, characterized by heat shock gene expression. T_STR cells are detectable in situ in the tumor microenvironment across various cancer types, mostly within lymphocyte aggregates or potential tertiary lymphoid structures in tumor beds or surrounding tumor edges. T cell states/compositions correlated with genomic, pathological and clinical features in 375 patients from 23 cohorts, including 171 patients who received immune checkpoint blockade therapy. We also found significantly upregulated heat shock gene expression in intratumoral CD4/CD8^+ cells following immune checkpoint blockade treatment, particularly in nonresponsive tumors, suggesting a potential role of T_STR cells in immunotherapy resistance. Our well-annotated T cell reference maps, web portal and automatic alignment/annotation tool could provide valuable resources for T cell therapy optimization and biomarker discovery.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Integrated analysis of multimodal single-cell data
Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zagar, M., et al. (2020) · doi:10.1101/2020.10.12.335331 · Cited by 15,508
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
The Immune Landscape of Cancer
Thorsson, V., Gibbs, D. L., Brown, S. D., Wolf, D., Bortone, D. S., Ou Yang, T.-H., Porta-Pardo, E., Gao, G. F., Plaisier, C. L., Eddy, J. A., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.03.023 · Cited by 5,870
Self-citationTGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells
Mariathasan, S., Turley, S. J., Nickles, D., Castiglioni, A., Yuen, K., Wang, Y., Kadel III, E. E., Koeppen, H., Astarita, J. L., Cubas, R., et al. (2018) · Nature · doi:10.1038/nature25501 · Cited by 5,400
Self-citationDimensionality reduction for visualizing single-cell data using UMAP
Becht, E., McInnes, L., Healy, J., Dutertre, C.-A., Kwok, I. W. H., Ng, L. G., Ginhoux, F., & Newell, E. W. (2019) · Nature Biotechnology · doi:10.1038/nbt.4314 · Cited by 5,358
Reversed graph embedding resolves complex single-cell trajectories
Qiu, X., Mao, Q., Tang, Y., Wang, L., Chawla, R., Pliner, H. A., & Trapnell, C. (2017) · Nature Methods · doi:10.1038/nmeth.4402 · Cited by 5,070
Self-citationAran, D., Looney, A. P., Liu, L., Wu, E., Fong, V., Hsu, A., Chak, S., Naikawadi, R. P., Wolters, P. J., Abate, A. R., et al. (2019) · Nature Immunology · doi:10.1038/s41590-018-0276-y · Cited by 4,984
The immune contexture in human tumours: impact on clinical outcome
Fridman, W. H., Pagès, F., Sautès-Fridman, C., & Galon, J. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3245 · Cited by 4,981
Cited by
SPP1 + macrophages cause exhaustion of tumor-specific T cells in liver metastases
Trehan, R., Huang, P., Zhu, X. B., Wang, X., Soliman, M., Strepay, D., Nur, A., Kedei, N., Arhin, M., Ghabra, S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59529-0 · Cited by 74
Proteotoxic stress response drives T cell exhaustion and immune evasion
Wang, Y., Ma, A., Song, N.-J., Shannon, A. E., Amankwah, Y. S., Chen, X., Wu, W., Wang, Z., Saadey, A. A., Yousif, A., et al. (2025) · Nature · doi:10.1038/s41586-025-09539-1 · Cited by 68
Self-citationConcurrent loss of the Y chromosome in cancer and T cells impacts outcome
Chen, X., Shen, Y., Choi, S., Abdel-Hafiz, H. A., Basu, M., Hoelzen, L., Tufano, M., Kailasam Mani, S. K., Ranjpour, M., Zhu, J., et al. (2025) · Nature · doi:10.1038/s41586-025-09071-2 · Cited by 50
He, S., Tan, Y., Ye, Q., M Gubin, M., Dede, M., Rafei, H., Peng, W., Rezvani, K., Mohanty, V., & Chen, K. (2026) · npj Artificial Intelligence · doi:10.1038/s44387-025-00060-4 · Cited by 3
Metadata
- Authors
- Chu, Y., Dai, E., Li, Y., Han, G., Pei, G., Ingram, D. R., Thakkar, K., Qin, J.-J., Dang, M., Le, X., Hu, C., Deng, Q., Sinjab, A., Gupta, P., Wang, R., Hao, D., Peng, F., Yan, X., Liu, Y., Song, S., Zhang, S., Heymach, J. V., Reuben, A., Elamin, Y. Y., Pizzi, M. P., Lu, Y., Lazcano, R., Hu, J., Li, M., Curran, M., Futreal, A., Maitra, A., Jazaeri, A. A., Ajani, J. A., Swanton, C., Cheng, X.-D., Abbas, H. A., Gillison, M., Bhat, K., Lazar, A. J., Green, M., Litchfield, K., Kadara, H., Yee, C., & Wang, L.
- Venue
- Nature Medicine
- Published
- 2023-05-29
- Volume
- 29
- Issue
- 6
- Pages
- 1550-1562
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4378648463
- Cited by
- 478
- References
- 83
- FWCI
- 50.52
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance. https://app.cochat.ai/papers/10.1038/s41591-023-02371-y
- The paper
- Chu, Y., Dai, E., Li, Y., Han, G., Pei, G., Ingram, D. R., Thakkar, K., Qin, J.-J., Dang, M., Le, X., Hu, C., Deng, Q., Sinjab, A., Gupta, P., Wang, R., Hao, D., Peng, F., Yan, X., Liu, Y., . . . Wang, L. (2023). Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance. Nature Medicine. https://doi.org/10.1038/s41591-023-02371-y
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
