A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer
Open accessAbstract
Immune-checkpoint blockade (ICB) combined with neoadjuvant chemotherapy improves pathological complete response in breast cancer. To understand why only a subset of tumors respond to ICB, patients with hormone receptor-positive or triple-negative breast cancer were treated with anti-PD1 before surgery. Paired pre- versus on-treatment biopsies from treatment-naive patients receiving anti-PD1 (n = 29) or patients receiving neoadjuvant chemotherapy before anti-PD1 (n = 11) were subjected to single-cell transcriptome, T cell receptor and proteome profiling. One-third of tumors contained PD1-expressing T cells, which clonally expanded upon anti-PD1 treatment, irrespective of tumor subtype. Expansion mainly involved CD8+ T cells with pronounced expression of cytotoxic-activity (PRF1, GZMB), immune-cell homing (CXCL13) and exhaustion markers (HAVCR2, LAG3), and CD4+ T cells characterized by expression of T-helper-1 (IFNG) and follicular-helper (BCL6, CXCR5) markers. In pre-treatment biopsies, the relative frequency of immunoregulatory dendritic cells (PD-L1+), specific macrophage phenotypes (CCR2+ or MMP9+) and cancer cells exhibiting major histocompatibility complex class I/II expression correlated positively with T cell expansion. Conversely, undifferentiated pre-effector/memory T cells (TCF7+, GZMK+) or inhibitory macrophages (CX3CR1+, C3+) were inversely correlated with T cell expansion. Collectively, our data identify various immunophenotypes and associated gene sets that are positively or negatively correlated with T cell expansion following anti-PD1 treatment. We shed light on the heterogeneity in treatment response to anti-PD1 in breast cancer.
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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 [17]
The section ‘T-cells expressing PD1 proliferate after anti-PD1 treatment’ reports that CD8+ T-cell phenotypes differed in expansion following treatment, supporting the citing sentence’s general point. But the paper does not demonstrate that TCF7+ Tpex cells are critical for ICB response in mouse tumor models or cancers; its ‘Immune environment associated with T-cell expansion’ section instead reports an inverse correlation between pretreatment TCF7 expression and T-cell expansion in the breast-cancer patients studied. Page numbers are unavailable in our copy. (LLM, conf=0.87)
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 [17]
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“In recent years, multiple studies have thoroughly characterized the immune and stromal microenvironment in breast cancer (27, 64–66), but these studies have focused on the primary tumor site.”
Transcriptomic profiles of neoantigen-reactive T cells in human gastrointestinal cancers
Zheng, C., Fass, J. N., Shih, Y.-P., Gunderson, A. J., Silva, N. S., Huang, H., Bernard, B. M., Rajamanickam, V., Slagel, J., Bifulco, C. B., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.03.005 · Cited by 143 · see citing works
Browaeys, R., Gilis, J., Sang-aram, C., Bleser, P. D., Hoste, L., Tavernier, S. J., Lambrechts, D., Seurinck, R., & Saeys, Y. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.13.544751 · Cited by 126 · see citing works
“Figure 3 MultiNicheNet prioritizes differences in therapy-induced intercellular communication changes between and within response groups. a) MultiNicheNet was applied to scRNA-seq from Bassez et al. to compare on-therapy versus pre-therapy differences in cell-cell communication between breast cancer patients with T ce…”
MethodInfluentialSelf-citationHigh-throughput single-сell sequencing in cancer research
Jia, Q., Chu, H., Jin, Z., Long, H., & Zhu, B. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00990-4 · Cited by 152 · see citing works
“used scTCR-Seq technology to confirm the presence of clonotype expansion in patients after PD-1 inhibitor treatment, indicating a continuous antitumor immune response; tumor cells from patients with clonotype expansion are enriched in pathways such as cell death, proteolysis, and immune signal transduction.(104)”
MethodHigh endothelial venules in cancer: Regulation, function, and therapeutic implication.
Vella, G., Hua, Y.-C., & Bergers, G. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.02.002 · Cited by 119 · see citing works
Chen, W., Teo, J., Yau, S.-W., Wong, M., Lok, C.-N., Che, C., Javed, A., Huang, Y.-H., Ma, S., & Ling, G.-S. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111647 · Cited by 117 · see citing works
Franken, A., Bila, M., Mechels, A., Kint, S., Dessel, J. V., Pomella, V., Vanuytven, S., Philips, G., Bricard, O., Xiong, J., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.02.007 · Cited by 117 · see citing works
Self-citationPD-1 blockade therapy promotes infiltration of tumor-attacking exhausted T cell clonotypes
Nagasaki, J., Inozume, T., Sax, N., Ariyasu, R., Ishikawa, M., Yamashita, K., Kawazu, M., Ueno, T., Irie, T., Tanji, E., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110331 · Cited by 123 · see citing works
Reshaping the tumor immune microenvironment to improve CAR-T cell-based cancer immunotherapy
Xia, X., Yang, Z., Lu, Q., Liu, Z., Wang, L., Du, J., Li, Y., Yang, D., & Wu, S. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02079-8 · Cited by 109 · see citing works
Wang, L., Guo, W., Zhikun, G., Yu, J., Tan, J., Simons, D. L., Hu, K., Liu, X., Zhou, Q., Zheng, Y.-Z., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101420 · Cited by 114 · see citing works
Li, Z., Pai, R., Gupta, S., Currenti, J., Guo, W., Bartolomeo, A. D., Feng, H., Zhang, Z., Li, Z., Liu, L., et al. (2024) · Nature Cancer · doi:10.1038/s43018-023-00672-2 · Cited by 104 · see citing works
“The presence of onco-fetal reprogramming could provide promising opportunities for stratification in early stage HCCs to anticipate relapse and has implications for therapeutically targeting the TME with combined immunotherapy.”
InfluentialPichler, A., Carrié, N., Cuisinier, M., Ghazali, S., Voisin, A., Axisa, P., Tosolini, M., Mazzotti, C., Golec, D. P., Mahéo, S., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.06.007 · Cited by 118 · see citing works
“Analysis of public datasets of CD8 + TIL scRNA-seq from human melanoma 47 and breast cancer 48 confirmed the higher expression of TNFRSF9 on Tex cell clusters (Figures S1K and S1N).”
BackgroundLe, J., Dian, Y., Zhao, D., Guo, Z., Luo, Z., Chen, X., Zeng, F., & Deng, G. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02426-3 · Cited by 109 · see citing works
“…genomics, transcriptomics, epigenomics, proteomics, and spatial transcriptomics [2–5]—researchers can now construct high-resolution cellular atlases of tumors [6, 7] delineate tumor evolutionary trajectories [8, 9] and unravel the intricate regulatory networks within the TME [10, 11].”
Guo, X., Nie, H., Zhang, W., Li, J., Ge, J., Xie, B., Hu, W., Zhu, Y., Zhong, N., Zhang, X., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.01.001 · Cited by 100 · see citing works
Xu, L., Saunders, K., Huang, S.-P., Knútsdóttir, H., Martinez-Algarin, K., Terrazas, I., Chen, K., McArthur, H., Maués, J., Hodgdon, C., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101511 · Cited by 79 · see citing works
Supervised discovery of interpretable gene programs from single-cell data
Kunes, R., Walle, T., Land, M., Nawy, T., & Pe’er, D. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01940-3 · Cited by 96 · see citing works
Cappuyns, S., Philips, G., Vandecaveye, V., Boeckx, B., Schepers, R., Brussel, T. V., Arijs, I., Mechels, A., Bassez, A., Lodi, F., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43381-1 · Cited by 92 · see citing works
Self-citationLi, J., Zhou, J., Huang, H., Jiang, J., Zhang, T., & Ni, C. (2023) · Clinical and Translational Medicine · doi:10.1002/ctm2.1199 · Cited by 96 · see citing works
Impaired function of dendritic cells within the tumor microenvironment
Xiao, Z., Wang, R., Wang, X., Yang, H., Dong, J.-M., He, X., Yang, Y., Guo, J., Cui, J., & Zhou, Z. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1213629 · Cited by 101 · see citing works
“MregDCs have also been described in various human cancers, including hepatocellular carcinoma (23), breast cancer (24), colon cancer (25), and gastric cancer (26).”
BackgroundSheng, J., Zhang, J., Wang, L., Tano, V., Tang, J., Wang, X., Wu, J., Song, J., Zhao, Y., Rong, J., et al. (2021) · Gut · doi:10.1136/gutjnl-2021-324339 · Cited by 107 · see citing works
Exploiting temporal aspects of cancer immunotherapy
Zemek, R. M., Anagnostou, V., da Silva, I. P., Long, G. V., & Lesterhuis, W. (2024) · Nature Reviews. Cancer · doi:10.1038/s41568-024-00699-2 · Cited by 90 · see citing works
“On the basis of the accumulating data on beneficial immunological effects early after start of chemotherapy, the TONIC study has explored a short induction approach in patients with TNBC involving 2 weeks of radiotherapy, cyclophosphamide, cisplatin, doxorubicin or no induction, followed by anti-PD1 treatment 52 .”
InfluentialImmune-mediated tubule atrophy promotes acute kidney injury to chronic kidney disease transition
Xu, L., Guo, J., Moledina, D., & Cantley, L. (2022) · Nature Communications · doi:10.1038/s41467-022-32634-0 · Cited by 90 · see citing works
Kim, M. J., Kim, K., Park, H. J., Kim, G.-R., Hong, K. H., Oh, J. H., Son, J., Park, D. J., Kim, D., Choi, J.-M., et al. (2023) · Nature Immunology · doi:10.1038/s41590-022-01373-1 · Cited by 90 · see citing works
Kang, J., Lee, J. H., Cha, H., An, J., Kwon, J., Lee, S., Kim, S., Baykan, M. Y., Kim, S. Y., An, D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48310-4 · Cited by 86 · see citing works
“S3, 4).”
Tumor-associated NK cells drive MDSC-mediated tumor immune tolerance through the IL-6/STAT3 axis
Neo, S.-Y., Tong, L., Chong, J., Liu, Y., Jing, X., Oliveira, M. M. S., Chen, Y., Chen, Z.-Q., Lee, K., Burduli, N., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adi2952 · Cited by 87 · see citing works
“Following up on our previous study, the present work reports a subset of CD69 + and perforin low/neg NK sub-set that correlated with myeloid cell abundance in patients who are considered nonresponders to anti–PD-1 therapy from a published dataset ( 30 ).”
MethodNederlof, I., Isaeva, O. I., de Graaf, M., Gielen, R., Bakker, N. A. M., Rolfes, A. L., Garner, H., Boeckx, B., Traets, J. J. H., Mandjes, I. A. M., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03249-3 · Cited by 80 · see citing works
Self-citationTumor microenvironment and immunotherapy for triple-negative breast cancer
Guo, Z.-J., Zhu, Z.-Y., Lin, X.-X., Wang, S., Wen, Y.-H., Wang, L.-B., Zhi, L.-L., & Zhou, J.-C. (2024) · Biomarker Research · doi:10.1186/s40364-024-00714-6 · Cited by 84 · see citing works
Distinct CD8+ T cell dynamics associate with response to neoadjuvant cancer immunotherapies
Li, H., Zandberg, D. P., Kulkarni, A., Chiosea, S. I., Santos, P. M., Isett, B. R., Joy, M., Sica, G., Contrera, K. J., Tatsuoka, C. M., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.02.026 · Cited by 83 · see citing works
Schalck, A., Sakellariou-Thompson, D., Forget, M.-A., Sei, E., Hughes, T. G., Reuben, A., Bai, S., Hu, M., Kumar, T., Hurd, M. W., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-1248 · Cited by 85 · see citing works
Clark, A. J., & Lillard, J. W. (2024) · Genes · doi:10.3390/genes15081036 · Cited by 107 · see citing works
“These technologies allow for high-resolution analysis of gene expression at the individual cell level, investigating the diversity of cell types and interactions within the microenvironment [89].”
BackgroundYang, Z., Liu, X.-P., Zhu, J., Chai, Y.-Y., Cong, B., Li, B., Gao, W.-F., Hu, Y., Wen, M., Liu, Y., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.11.008 · Cited by 81 · see citing works
Zhao, L.-P., Zheng, R.-R., Rao, X., Huang, C.-Y., Zhou, H., Yu, X.-Y., Jiang, X.-Y., & Li, S.-Y. (2024) · Advancement of science · doi:10.1002/advs.202309204 · Cited by 80 · see citing works
Chen, C.-J., Zhao, F.-C., Peng, J.-L., Zhao, D., Xu, L.-Y., Li, H., Ma, S.-Y., Peng, X., Sheng, X., Sun, Y., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101686 · Cited by 79 · see citing works
Zheng, S., Zou, Y., Tang, Y., Yang, A., Liang, J.-Y., Wu, L., Tian, W., Xiao, W., Xie, X., Yang, L., et al. (2022) · OncoImmunology · doi:10.1080/2162402x.2021.2020984 · Cited by 91 · see citing works
Lee, C. Y. C., Kennedy, B. C., Richoz, N., Dean, I., Tuong, Z. K., Gaspal, F., Li, Z., Willis, C., Hasegawa, T., Whiteside, S. K., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44787-1 · Cited by 78 · see citing works
“1d, 11h) 24 , CCR7_DCs from tumours that successfully underwent clonal T cell expansion following treatment with anti-PD-1 antibodies were enriched in transcripts associated with our ICB-induced Ccr7_DC.2 cluster, versus non-responders (Fig.”
BackgroundGuimarães, G. R., Maklouf, G. R., Teixeira, C. E., Santos, L. D. O., Tessarollo, N. G., de Toledo, N. E., Serain, A. F., de Lanna, C. A., Pretti, M. A. M., da Cruz, J. G. V., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49916-4 · Cited by 85 · see citing works
Liu, T., Zhou, Z.-H., Zhang, M.-X., Lang, P., Li, J., Liu, Z.-M., Zhang, Z., Li, L., & Zhang, L. (2023) · Journal of Controlled Release · doi:10.1016/j.jconrel.2023.08.055 · Cited by 74 · see citing works
Beziaud, L., Young, C. M., Alonso, A. M., Norkin, M., Minafra, A. R., & Huelsken, J. (2023) · Cell stem cell · doi:10.1016/j.stem.2023.05.007 · Cited by 76 · see citing works
Potential Role of CXCL13/CXCR5 Signaling in Immune Checkpoint Inhibitor Treatment in Cancer
Hsieh, C.-H., Jian, C.-Z., Lin, L., Low, G.-S., Ou, P.-Y., Hsu, C., & Ou, D. (2022) · Cancers · doi:10.3390/cancers14020294 · Cited by 69 · see citing works
“identified several genes that were able to predict a better immune response to anti-PD-1 treatment associated with CXCL13 [126].”
BackgroundMapping cellular interactions from spatially resolved transcriptomics data
Zhu, J. J., Wang, Y., Chang, W. Y., Malewska, A., Napolitano, F., Gahan, J. C., Unni, N. G., Zhao, M., Yuan, R., Wu, F., et al. (2024) · Nature Methods · doi:10.1038/s41592-024-02408-1 · Cited by 72 · see citing works
“As we will show later in this work, this is also to be expected as they all participate in inducing the epithelial–mesenchymal transition (EMT) in”
Cappuyns, S., Piqué-Gili, M., Esteban-Fabró, R., Philips, G., Balaseviciute, U., Pinyol, R., Gris-Oliver, A., Vandecaveye, V., Abril-Fornaguera, J., Montironi, C., et al. (2024) · Journal of Hepatology · doi:10.1016/j.jhep.2024.12.016 · Cited by 69 · see citing works
“Finally, patients were categorized accordingly into molecular subsets predictive of clinical bene fi t or resistance to atezo+bev.”
Self-citationShen, W., Shi, P., Dong, Q., Zhou, X., Chen, C.-X., Sui, X., Tian, W.-T., Zhu, X., Wang, X., Jin, S., et al. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-007068 · Cited by 68 · see citing works
Borràs, D. M., Verbandt, S., Ausserhofer, M., Sturm, G., Lim, J., Verge, G. A., Vanmeerbeek, I., Laureano, R. S., Govaerts, J., Sprooten, J., et al. (2023) · Cell Discovery · doi:10.1038/s41421-023-00605-4 · Cited by 67 · see citing works
“Indeed these genes together enriched for various pathways relevant for tumor-reactive exhaustion or multi-factorial tumoral in fl ammation 7,31,42,43 including nuclear factor of activated T cells (NFAT) signaling, IFNG signaling, various IL-based pathways including IL2/IL15, TGF β signaling, and…”
Self-citationWang, Y., Tong, C., Lu, Y.-T., Wu, Z.-Q., Guo, Y.-L., Liu, Y., Wei, J.-S., Wang, C.-M., Yang, Q.-M., & Han, W.-D. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01659-2 · Cited by 67 · see citing works
Cheng, S.-L., Lee, H.-M., Li, C.-P., Lin, M.-W., Chou, M.-Y., Yen, Y.-T., Wu, T.-H., Lian, Y.-C., Shih, Y., Chiang, C.-S., et al. (2024) · ACS Nano · doi:10.1021/acsnano.3c12337 · Cited by 65
Semi-supervised integration of single-cell transcriptomics data
Andreatta, M., Hérault, L., Gueguen, P., Gfeller, D., Berenstein, A. J., & Carmona, S. (2023) · bioRxiv · doi:10.1038/s41467-024-45240-z · Cited by 65 · see citing works
“These samples amounted to 11,021 cells covering 7 different tumor types from multiple studies 24 – 32 .”
Ren, X., Hui, Z., Zhang, J., Ren, Y., LI, X., Yan, C., Wang, T., Yu, W., Wang, T., Xiao, S., et al. (2022) · Cell Death and Disease · doi:10.1038/s41419-022-05057-4 · Cited by 71 · see citing works
“Consistent with our findings, Bassez and colleagues [44] performed single-cell sequencing and proteomic analysis of tumor tissue from breast cancer patients before and after anti-PD-1 therapy and demonstrated that CD4 T cells characterized by expression of T helper 1 (IFNG) and Tfh (BCL6, CXCR5) markers clonally expan…”
ResultHe, J., Zhou, Y. L., & Sun, L. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-023-01438-0 · Cited by 69 · see citing works
“…[16], T-cell immunoreceptor with Ig and ITIM domains (TIGIT) [17], CD160 [18], TNF receptor superfamily member 9 (TNFRSF9) [19], and hepatitis A virus cellular receptor 2 (HAVCR2) [20]; and (2) decreased proliferation, viability, and the loss of cytotoxic activity against tumours in vitro [21].”
BackgroundObesity-associated changes in molecular biology of primary breast cancer
Nguyen, H.-L., Geukens, T., Maetens, M., Aparicio, S. A. J. R., Bassez, A., Borg, Å., Brock, J. E., Broeks, A., Caldas, C., Cardoso, F., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-39996-z · Cited by 71 · see citing works
Self-citationWang, 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
Palakurthi, B., Fross, S., Guldner, I. H., Aleksandrovic, E., Liu, X.-Y., Martino, A. K., Wang, Q.-F., Neff, R. A., Golomb, S. M., Lewis, C. M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37727-y · Cited by 63 · see citing works
“To strengthen the clinical relevance of our fi ndings by which the emergence of trajectory Path 1 myeloid cells (cluster 0 cells) after chemo treatment contribute to breast cancer immune microenvironment in human breast cancer context, we performed in silico analysis using Bassez et al. dataset 23 .”
- Authors
- Bassez, A., Vos, H., Van Dyck, L., Floris, G., Arijs, I., Desmedt, C., Boeckx, B., Vanden Bempt, M., Nevelsteen, I., Lambein, K., Punie, K., Neven, P., Garg, A. D., Wildiers, H., Qian, J., Smeets, A., & Lambrechts, D.
- Affiliations
- VIB-KU Leuven Center for Cancer Biology (BE)
- KU Leuven (BE)
- Universitair Ziekenhuis Leuven (BE)
- Women's Hospital, School of Medicine, Zhejiang University (CN)
- Corresponding author
- Qian, Junbin
- Smeets, Ann
- Lambrechts, Diether
- ORCID
- Venue
- Nature Medicine
- Published
- 2021-05
- Volume
- 27
- Issue
- 5
- Pages
- 820-832
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3157384750
- Cited by
- 867
- References
- 74
- Citations by year
- 2026: 156 · 2025: 168 · 2024: 234 · 2023: 159 · 2022: 116 · 2021: 33
- FWCI
- 52.64
- Type
- journal article
- Language
- en
- Open access
- green
- lirias.kuleuven.be
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- Funders
- Vlaams Supercomputer Centrum
- European Commission (847912)
- Fonds Wetenschappelijk Onderzoek (KOTK/2018/11509/1, C14/18/092, POR/16/040, G0B4620N, C14/19/098, 30837538, G0B6120N)
- KU Leuven (C14/19/098, C14/18/092, POR/16/040, C14/19, 30837538, KOTK/2018/11509/1)
- Kom op tegen Kanker (C14/19/098, 30837538, POR/16/040, KOTK/2018/11509/1)
- Vlaamse regering (VR 2016 2312 Doc.1521/4, 30837538, C14/19/098)
- 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 › T-cell and B-cell Immunology
- Keywords
- breast cancer, anti-PD-1 therapy, immune checkpoint blockade, neoadjuvant chemotherapy, tumor immune microenvironment, T cell clonal expansion, CD8+ T cells, CD4+ T cells, T cell exhaustion, tumor-infiltrating macrophages, treatment response heterogeneity, triple-negative breast cancer, hormone receptor-positive breast cancer, single-cell transcriptomics, proteomics
- MeSH terms
- Immune Checkpoint Inhibitors, Dendritic Cells, Female, Humans, Macrophages, Receptors, Antigen, T-Cell, CD4-Positive T-Lymphocytes, CD8-Positive T-Lymphocytes, Neoadjuvant Therapy, Single-Cell Analysis, Programmed Cell Death 1 Receptor, Antibodies, Monoclonal, Humanized, Triple Negative Breast Neoplasms
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