Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer
Open accessAbstract
In triple-negative breast cancer (TNBC), the benefit of combining chemotherapy with checkpoint inhibitors is still not very clear. We utilize single-cell RNA- and ATAC-sequencing to examine the immune cell dynamics in 22 patients with advanced TNBC treated with paclitaxel or its combination with the anti-PD-L1 atezolizumab. We demonstrate that high levels of baseline CXCL13 + T cells are linked to the proinflammatory features of macrophages and can predict effective responses to the combination therapy. In responsive patients, lymphoid tissue inducer (LTi) cells, follicular B (Bfoc) cells, CXCL13 + T cells, and conventional type 1 dendritic cells (cDC1) concertedly increase following the combination therapy, but instead decrease after paclitaxel monotherapy. Our data highlight the importance of CXCL13 + T cells in effective responses to anti-PD-L1 therapies and suggest that their reduction by paclitaxel regimen may compromise the clinical outcomes of accompanying atezolizumab for TNBC treatment.
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These CD8+ T cell subsets show different responses to anti-PD(L)-1 therapies, with TCF7+ Tpex cells demonstrated critical for ICB response in mouse tumor models and cancers.
“These cell subsets show different responses to anti-PD(L)-1 therapies,”
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 [19]
The Results report different changes in T-cell subsets after paclitaxel versus paclitaxel plus atezolizumab, supporting the claim that subsets respond differently to treatment. They also link CD8-CXCL13 cells to PD-L1 blockade response, but the cited passages do not demonstrate that TCF7+ Tpex cells are critical for ICB response in mouse tumor models and cancers. (LLM, conf=0.86)
Experimental — accuracy not yet measuredApplying ICB and combination therapies as neoadjuvant treatments provides an opportunity to observe immune cell dynamics in the tumor microenvironment with temporal samples.
“Applying ICB and combination therapies as neoadjuvant treatments provides an opportunity to observe immune cell dynamics in tumor microenvironment (TME) with temporal samples.”
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 [19]
The Methods describe tumor biopsies collected before treatment and four weeks after treatment began, supporting the use of temporal samples to observe immune-cell dynamics. But the paper says only some locally advanced patients received neoadjuvant therapy; all tumor samples in the PD-L1-blockade combination group came from metastatic sites after breast surgery. It therefore does not establish the claimed opportunity specifically for neoadjuvant ICB combination treatment. (LLM, conf=0.88)
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Self-citationGao, S., Liu, S., Wang, G., & Zhou, G. (2021) · Life · doi:10.3390/life11121282 · Cited by 65 · see citing works
Wang, X., Collet, L., Rediti, M., Debien, V., Caluwé, A. D., Venet, D., Romano, E., Rothé, F., Sotiriou, C., & Buisseret, L. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12030953 · Cited by 64 · see citing works
Han, P.-Z., Ye, W.-D., Yu, P., Tan, L.-C., Xiao Hua, S. H. I., Chen, X.-F., He, C., Hu, J., Wei, W., Lu, Z., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.173712 · Cited by 63 · see citing works
Self-citationA T cell resilience model associated with response to immunotherapy in multiple tumor types
Zhang, Y., Vu, T., Palmer, D. C., Kishton, R. J., Gong, L., Huang, J., Nguyen, T., Chen, Z., Smith, C., Livák, F., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01799-y · Cited by 63 · see citing works
Self-citation
- Authors
- Zhang, Y., Chen, H., Mo, H., Hu, X., Gao, R., Zhao, Y., Liu, B., Niu, L., Sun, X., Yu, X., Wang, Y., Chang, Q., Gong, T., Guan, X., Hu, T., Qian, T., Xu, B., Ma, F., Zhang, Z., & Liu, Z.
- Affiliations
- Peking University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Cancer Hospital of Huanxing Chaoyang District Beijing (CN)
- Corresponding author
- Xu, Binghe
- Ma, Fei
- Zhang, Zemin
- Liu, Zhihua
- ORCID
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 39
- Issue
- 12
- Pages
- 1578-1593.e8
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W3205385275
- Cited by
- 783
- References
- 77
- Citations by year
- 2026: 135 · 2025: 206 · 2024: 183 · 2023: 158 · 2022: 93 · 2021: 8
- FWCI
- 41.16
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (31991171, 81988101, 82030089, 91942307)
- Chinese Academy of Meteorological Sciences (2016-I2M-1-001, 2017-I2M-3-004, 2019-I2M-1-003)
- Peking University
- Beijing Municipal Science and Technology Commission (Z201100005320014)
- National Key Research and Development Program of China (2018YFC1312101, 2020YFA0803300)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Keywords
- triple-negative breast cancer, PD-L1 blockade, atezolizumab, paclitaxel, immune cell dynamics, lymphoid tissue inducer cells, follicular B cells, conventional type 1 dendritic cells, single-cell RNA sequencing, single-cell ATAC-seq
- MeSH terms
- Immune Checkpoint Inhibitors, Female, Humans, Single-Cell Analysis, Triple Negative Breast Neoplasms
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 ›
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