Cited by 867Cancer Immunotherapy and BiomarkersBreast Cancer Treatment StudiesT-cell and B-cell Immunology

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A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer

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Bassez, Ayse, Vos, Hanne, Van Dyck, Laurien, Floris, Giuseppe, Arijs, Ingrid, Desmedt, Christine, Boeckx, Bram, Vanden Bempt, Marlies, Nevelsteen, Ines, Lambein, Kathleen, Punie, Kevin, Neven, Patrick, Garg, Abhishek D., Wildiers, Hans, Qian, Junbin, Smeets, Ann, Lambrechts, Diether·2021·Nature Medicine

DOI 10.1038/s41591-021-01323-8

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Abstract

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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Chen, S., Elhessewi, G. M. S., Cai, H., Alawad, W. M., Mishra, M. K., & Sayed, U. (2026) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.71235 · Cited by 2
Targeting VEGF signaling and stromal remodeling enhances chemoimmunotherapy efficacy in esophageal cancer
Yu, Z., Li, W., Xu, S., Xu, M. M., Lin, Q., Liu, L., Zhang, J., Zhong, X., Jin, C., Zuo, L., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-014249 · Cited by 3
“ST analyses confirmed the close proximity of RGCC+ ECs, MMP11+ CAFs and TNFRSF4+ Tregs, forming a tightly integrated immuno-suppressive network.”
Immunotherapy innovations in triple-negative breast cancer: targeting checkpoints, combinations, and biomarkers
Wang, Z., Chu, J.-H., Wang, Y., Huang, L., & Qian, M. (2026) · Oncology Reviews · doi:10.3389/or.2026.1802090 · Cited by 2
“This benefit was linked to Atezolizumab’s modulation of the tumor microenvironment, including increased CD8 + T-cell activation and dendritic cell maturation (18).”
Single-Cell Multi-Tissue T Cell Clonal Dynamics Reveal Distinct Immune Coercion Landscapes in MSI and MSS Colorectal Cancer
Zhan, Q., Zhang, S.-W., Cao, B., Chen, L.-M., & Xie, L. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27062689 · Cited by 2
“This limitation hampers a systematic understanding of the dynamic mechanisms underlying responses to immunotherapy [22].”
Systemic immune profiling uncovers divergent mechanisms and predictive biomarkers of response to combination immunotherapies in hepatocellular carcinoma
Nishio, A., Kodama, T., Daiku, K., Maesaka, K., Tanaka, S., Nozaki, Y., Kurahashi, T., Matsumoto, K., Nawa, T., Tawara, S., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-013648 · Cited by 2
The role of programmed cell death 1 in autoimmune diseases: mechanisms and therapeutic implications
Liu, Z.-Y., Hu, Z.-P., Lao, H.-L., Chen, L., Wen, Y., Liang, Y.-Q., Zhang, C., Wu, J., & Hou, X.-L. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1707084 · Cited by 2
“In malignancies such as NSCLC (58), breast cancer (59), and melanoma (60), tumor cell upregulation of PD-L1 directly drives immunosuppression.”
ABCA8-positive lipid-metabolic CAFs mediate immunotherapy resistance in TNBC
Qin, W., Li, D., Zhang, J., Wang, S., Hou, L., Zhang, C., Wang, D., & Zhang, J. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2025.1729275 · Cited by 2
Decoding the tumor microenvironment remodeling orchestrated by CLEC3B+ inflammatory cancer-associated fibroblasts in lung adenocarcinoma immunotherapy: elucidation from pan-cancer spatially single-cell transcriptomics landscape
Li, S., Weng, K., Yan, L., Lu, Y., Zhou, R., Fan, Z., Yang, Z., Yue, J., & Li, W. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07677-2 · Cited by 1
“(BRCA, Bassez 2021 [23]), carcinoma of colon and rectum (CRC, GSE205506 [24] and GSE236581 [25]), non-small cell lung carcinoma (NSCLC, GSE207422 [26]) and basal cell carcinoma (BCC, GSE123813 [27]).”
AugGCL: Multimodal graph learning for spatial transcriptomics analysis with enhanced gene and morphological data
Ji, T., Yang, B., Wang, M., Ji, H. G., Yang, H., & Liu, Y. T. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013912 · Cited by 2
“In this study, AugGCL was applied to the spatial transcriptomics analysis of the human breast cancer dataset [35–38], assessing its performance in spatial domain recognition and clustering accuracy.”
The interplay between cytokines and immune checkpoints in breast cancer therapy
Wu, Y., Zhu, Y. F., Cang, Q., Shaibu, Z., Kong, L., Zhou, Q., Li, X., & Yin, L. (2026) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2026.189539 · Cited by 1
Progression-free survival for unresectable non-metastatic locally advanced pancreatic cancer after surgical microwave ablation plus durvalumab and tremelimumab: phase-2 non-randomized prospective clinical trial
Topal, H., Venken, T., Bassez, A., Chiritescu, G., Cutsem, E. V., van der Merwe, S., Lambrechts, D., & Topal, B. (2025) · Communications Medicine · doi:10.1038/s43856-025-01186-x · Cited by 2
Self-citation
Combination of a novel TCR Vβ chain-directed selective T cell activator with standard of care therapy for head and neck cancer improves antitumor responses and promotes regression of checkpoint-refractory tumor models
Rosato, F., Santiago-Sánchez, G. S., Fabian, K. P., Padget, M., Lee, J. K., Allen, C., Su, Z., Katragadda, M., Moisan, J., Bayliffe, A., et al. (2025) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-013158 · Cited by 2
“32–34 In the present study, we evaluated the therapeutic efficacy of a dual T cell activator (mSTAR1302) in combination with the current SOC treatment for recurrent or metastatic HPV − HNSCC in a syngeneic murine tumor model.”
Tumor-specific major histocompatibility-II expression predicts pathological complete response to atezolizumab combined to chemotherapy in triple-negative breast cancer
Balko, J. M., Licata, L., Wang, X. Q., Dugo, M., Huang, C., Egle, D., Bermejo, B., Zamagni, C., Thill, M., Antón, A., et al. (2025) · npj Breast Cancer · doi:10.1038/s41523-025-00828-6 · Cited by 2
Tumor microenvironment response to neoadjuvant therapy in breast cancer: insights from single-cell and spatial omics
Wu, Q., Yang, J., Zhang, D., Xu, H., Yu, Y., & Zheng, Y. (2025) · Medical Oncology · doi:10.1007/s12032-025-03028-1 · Cited by 2
“Takada et al. attempted to assess tumor-infiltrating lymph nodes (TILNs) before neoadjuvant chemotherapy to investigate the necessity of axillary lymph node dissection (ALND) after neoadjuvant chemotherapy.”
The role of the 3′-UTR of the chemokine receptor CCR2 and hnRNPA0 in regulating mRNA stability and subcellular distribution in human CD4+ T cells
Yükselten, Y., Wishah, H., Wang, L., & Sutton, R. E. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1655273 · Cited by 4
Immature monocytic cells within tumors differentiate into immunosuppressive cells in resistant tumors to immunotherapy
Levin, S., Benguigui, M., Manobla, B., Buxbaum, C., Raviv, Z., Yizhak, K., & Shaked, Y. (2025) · iScience · doi:10.1016/j.isci.2025.113141 · Cited by 3
LaGrACE: estimating gene program dysregulation with latent regulatory network
Jia, M., Mao, H., Zhou, M., Chen, Y.-C., & Benos, P. (2025) · Molecular Systems Biology · doi:10.1038/s44320-025-00115-3 · Cited by 2
Semaphorin7A and PD-L1 cooperatively drive immunosuppression during mammary involution and breast cancer
Elder, A. M., Fairchild, H., Kines, K. T., Cozzens, L. M., Becks, A. R., Slansky, J. E., Anderson, S. M., & Lyons, T. R. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115676 · Cited by 2
Senescence-related cytokine levels are associated with HIV-1 serostatus and persistence
Li, Y.-J., Soto-Ramirez, Z. N., Roscher, J., Medvec, T., Alaoui-El-Azher, M., Piazza, P., Chen, Y., Sluis-Cremer, N., Rinaldo, C., & Macatangay, B. (2025) · medRxiv · doi:10.1101/2025.02.05.25321757 · Cited by 2
“…of long-lived CD4+ T cells that harbor intact HIV-1 provirus: although it has not been reported in HIV-1 infection, MMP-9-expressing macrophages in the breast cancer microenvironment positively correlate with T cell expansion after anti-programmed cell death protein-1 (PD-1) treatment [16].”
Single-cell transcriptomes of dissecting the intra-tumoral heterogeneity of breast cancer microenvironment
Chen, P., Liang, K.-F., Mao, X., Wu, Q., Chen, Z.-Y., Jin, Y., Lin, K.-R., He, T., Yang, S.-Q., Huang, H., et al. (2024) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-024-06015-7 · Cited by 2
“However, as with most tumor types, not all breast cancer patients benefited from PD-1/PD-L1 and CTLA-4 therapies(Zhou and Zhong 2004; Bassez et al. 2021).”
The mechanism of PDE7B inhibiting the development of hepatocellular carcinoma through oxidative stress
Luo, Y.-F., Gao, H., Zhao, J., Chen, L., Shao, J., & Ju, L.-L. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1469740 · Cited by 2
“Moreover, abnormal expression of PDCD1 has been observed in several cancers, including esophageal cancer (51), breast cancer (52), lung cancer (53), and thyroid cancer (54).”
Prognostic and therapeutic potential of gene profiles related to tertiary lymphoid structures in colorectal cancer
Yu, J., Gong, Y., Huang, X., & Bao, Y. (2024) · PeerJ · doi:10.7717/peerj.18401 · Cited by 2
“GZMB stood out as a primary indicator of cytotoxic T-cell activity, with GZMB + T-cells being pivotal in antitumor immunity ( Bassez et al., 2021 ).”
Background
Study on the mechanism of heterogeneous tumor-associated macrophages in three subtypes of breast cancer through the integration of single-cell RNA sequencing and in vitro experiments
Yuan, Y., Zhang, S., & Huang, J. (2024) · Molecular Biology Reports · doi:10.1007/s11033-024-09665-5 · Cited by 2
“However, due to the vast heterogeneity among the subtypes of BRCA, treating patients at the same clinical stage with the same treatment strategies could result in different prognoses [ 3].”
Single-cell transcriptomics reveals that tumor-infiltrating natural killer cells are activated by localized ablative immunotherapy and share anti-tumor signatures induced by immune checkpoint inhibitorsPreprint
Liu, K., Sadeghipour, N., Hoover, A. R., Valero, T. I., Furrer, C., Adams, J. P., Naqash, A. R., Zhao, M., Papin, J., & Chen, W. R. (2023) · bioRxiv · doi:10.1101/2023.05.02.539163 · Cited by 2
GITR and TIGIT immunotherapy provokes divergent multi-cellular responses in the tumor microenvironment of gastrointestinal cancersPreprint
Sathe, A., Ayala, C., Bai, X.-Q., Grimes, S., Lee, B., Kin, C., Shelton, A., Poultsides, G., & Ji, H. P. (2023) · bioRxiv · doi:10.1101/2023.03.13.532299 · Cited by 2
“Single cell genomic methods have provided valuable information about how specific cell types respond to PD-1 blockade using longitudinal pre and on treatment patient biopsies (13, 14).”
Background
EstroGene database reveals diverse temporal, context-dependent and directional estrogen receptor regulomes in breast cancer
Li, Z.-Q., Li, T.-Q., Yates, M. E., Wu, Y., Ferber, A., Chen, L., Brown, D., Carroll, J., Sikora, M., Tseng, G., et al. (2023) · bioRxiv · doi:10.1101/2023.01.30.526388 · Cited by 2
“To test this hypothesis, we examined the BIOKEY cohort of single cell 534 RNA-seq profiling in 15 intra-patient paired treatment naïve or anti-PD1 treatment ER+ 535 breast cancer biopsies (43).”
Method
Efficacy of digital breast tomosynthesis combined with magnetic resonance imaging in the diagnosis of early breast cancer
Ren, Y.-Q., Zhang, J., Zhang, J.-D., & Xu, J. (2022) · World Journal of Clinical Cases · doi:10.12998/wjcc.v10.i28.10042 · Cited by 2
Machine learning-based screening of an epithelial-mesenchymal transition-related long non-coding RNA signature reveals lower-grade glioma prognosis and the tumor microenvironment and predicts antitumor therapy response
Wang, N., Gao, X., Ji, H., Ma, S., Wu, J., Dong, J., Wang, F., Zhao, H., Liu, Z., Yan, X., et al. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.942966 · Cited by 3
“The increased expression of HAVCR2 (Bassez et al., 2021), LGALS9 (Wang et al., 2020), and LAIR1 (Peng DH et al., 2020) promoted the depletion and functional decline of T cells.”
BackgroundInfluential
Tumor immune microenvironment remodeling predicts response to checkpoint inhibitor therapy.
Lin, Z., Chandra, M., Srinivas, N., Ugurel, S., Becker, J. C., & Aran, D. (2026) · Cancer Cell · doi:10.1016/j.ccell.2026.08.007 · Cited by 1
CX3CR1⁺ CD8⁺ cytotoxic T cells drive tumor killing in esophageal squamous cell carcinoma during neoadjuvant therapy
Zhao, Y.-H., Zhang, R., Li, Y., Liu, S., Liu, C., Wang, Y.-H., Wang, T., Xiao, M., Huang, J., Zhang, B., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-76959-6 · Cited by 1
“Through pre-viousstudies,acompellingpatternhasemerged,indicatingthattumor clearance in several cancer types, including basal cell carcinomas (BCC) 14 , breast tumors 15,16 , and non-small-cell lung cancer (NSCLC) 17 , is predominantly mediated by CXCL13 + CD8 + T cells.”
Migration of immune cells in tumors and inflammation: molecular mechanisms and therapeutic targets
Lu, Y., Shao, D., Xiao, Y., Jiang, Y., & Shao, Z. (2026) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-026-02851-w · Cited by 3
“137,138 Within the TME and TDLNs, IL-21 secreted by Tfh cells restores CD8 + T cell-dependent antitumor immunity by enhancing the expression of IFN-γ and granzyme B. 139 Notably, CD8 + TAs further recruit IL-12-producing Tfh cells via CXCL13-CXCR5 axis, thereby sustaining their effector functions.”
Silica-based nanoplatforms for nucleic acid delivery: Emerging strategies and biomedical applications
Li, X., Bai, Y., Zhang, D., & Li, Y. (2026) · Nano Today · doi:10.1016/j.nantod.2026.103090 · Cited by 1
Engineered Bacterial Membranes as Next‐Generation Platforms for Cancer Immunotherapy
Malik, H. A., Virk, U. Y., Attia, M. S., Wilson, J., & Wei, M. Q. (2026) · Small Science · doi:10.1002/smsc.70351 · Cited by 1
“I signatures [90], T - cell receptor (TCR) clonality [91], and intratumoral CD8 + /NK infiltration [52] are likely to guide rational combination strategies and patient selec‐ tion.”
Single-cell transcriptomic analysis reveals the immunosuppressive status of NK cell subpopulations in TNBC
Liu, Y., Cao, W., Jin, Y., & Xu, W. (2026) · PLoS ONE · doi:10.1371/journal.pone.0354524 · Cited by 1
“ScRNA-seq is an effective method to study the heterogeneity of NK cell clusters in breast cancer, particularly in terms of infiltration ratios and functions [8–10].”
Influential
Spatial organization of the TNBC tumor microenvironment: multicellular niches, T-cell bottlenecks, and therapeutic opportunities
Wu, J., Fan, J., Sha, T., & Li, H. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-08602-3 · Cited by 2
“DC abundance and activation status are tightly linked to T-cell infiltration and the overall immune landscape: for example, an increased proportion of activated PD-L1^+ DCs in tumors is frequently accompanied by greater CD8^+ T-cell infiltration or clonal expansion [80].”
Upregulation of macrophage UPP1 promotes lung adenocarcinoma metastasis through an mtROS-cGAS-NLRP3 inflammasome axis
Feng, M.-T., Gao, C., Yang, Y.-F., Li, D.-H., Zhou, C.-S., Chen, L., Su, Y.-X., Cao, Y.-Q., Li, L.-D., & Gao, Y. (2026) · Cell Death Discovery · doi:10.1038/s41420-026-03226-4 · Cited by 1
Anti-PD1-IL18 immunoconjugate promotes effector T cell-mediated antitumor immunity
Oelgarth, N., Martin, K., Junker, F., Serger, C., Herr, C., Buchi, M., Gremlich, L., Fusi, I., Fürst, J. D., Herzig, P., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2026-015090 · Cited by 1
“38 This finding was corroborated in human PBMC assays, where IFN-γ release following aPD1-IL18 mut challenge occurred at substantially lower concentrations compared with wild-type IL-18 alone or Isotype-IL18 mut .”
Influential
Smart responsive hydrogels for postoperative pancreatic ductal adenocarcinoma therapy: From residual cancer eradication to tissue regeneration
Li, H.-J., Li, Y., Mi, Y., & Fan, D.-D. (2026) · Chemical Engineering Journal · doi:10.1016/j.cej.2026.178979 · Cited by 1
Knowledge-guided contextual gene set analysis with large language models
Wang, Z.-Z., Day, C.-P., Wei, C.-H., Jin, Q., Leaman, R., Yang, Y.-F., Tian, S., Qiu, A., Fang, Y., Zhu, Q.-Q., et al. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag214 · Cited by 1
“These DEGs were derived from single-cell RNA-sequencing data from 31 breast cancer patients treated with anti–PD-1 therapy (Bassez et al. 2021).”
Driving tumor-associated macrophages to a CXCL9Hi/SPP1Low phenotype eliminates pancreatic cancer
Nguyen, Y. T. M., Pfefferlé, M., Oh, J., Simpson, G. G., Walker, S. A., Noguchi, S., Garris, C. S., Deutsch-Williams, R. J., Wirapati, P., Stefano, F. D., et al. (2026) · Cell Reports Medicine · doi:10.1016/j.xcrm.2026.102938 · Cited by 1
When effective anticancer therapies are, in fact, destabilizing the tumor’s Group Phenotypic Composition
Thomas, F., Dujon, A., Marusyk, A., DeGregori, J., Fontanella, A., Bieuville, M., Campone, M., Pujol, P., Alix-Panabières, C., Cam, L. L., et al. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01536-5 · Cited by 1
“At the functional level, recent studies using single-cell transcriptomics have shown that therapy can alter ligand – receptor interaction networks between tumor and immune cells 107,108 , illustrating the disruption of cooperative interactions thatarecentraltotheGPCframework.”
Translating lineage-resolved single-cell programs to bulk clinical prognosis: Adversarial generative learning reveals lineage-informed immune – stromal – epithelial risk signatures
Le, B., Nguyen, D. P. Q., Binh, D. H. N., Vo, B. L., Anh, L. D., & Ta, H. D. K. (2026) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2026.109154
GPAT4 regulates antitumor immune response through activating the mtDNA-cGAS axis in cancer cells
Ruan, Z., Liang, W., Gong, Y.-T., Guan, W., Zhou, X.-A., Jiang, K., Yang, Q., & Hu, M.-M. (2026) · Cell Insight · doi:10.1016/j.cellin.2026.100343 · Cited by 1
“The single-cell analysis was based on the pretreatment breast cancer anti-PD-1 scRNA-seq cohort reported by Bassez et al. (Bassez et al., 2021), which profiled paired pre-and on-treatment biopsies from treatment-naive patients receiving pem-brolizumab before surgery.”
JAK-STAT pathway heterogeneity governs immunotherapy response in breast cancer
Zhou, J.-B., Zhang, H., Tang, H.-L., Yu, L., & Peng, F. (2026) · bioRxiv · doi:10.64898/2026.02.03.703506 · Cited by 1
“Med, pembrolizumab, 29 patients: 2 ER-/HER2 + , 15 ER + /HER2±, 12 TNBC) was available in the reported literature 26 .”
Explainable machine learning-guided integrated multiomics analysis reveals macrophage-driven immune suppression in breast cancer
Azimzade, Y., Haugen, M., Kristensen, V., Frigessi, A., & Köhn-Luque, A. (2026) · Nature Communications · doi:10.1038/s41467-026-73617-9 · Cited by 1
“32.”
Recent advances in dissolving microneedles for breast cancer immunotherapy: local delivery and tumor microenvironment remodeling
Chen, Y., Song, L., Zhu, Y., Zhang, Z., Lu, Y., Wang, X., & Pang, H. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1831221 · Cited by 1
CLEC2B-KLRB1 axis acts as an immune checkpoint, governing the exhaustion of CD8 + T cells and their resistance to immune checkpoint blockade
Cheng, J., Lu, J., Gao, Z., Xiao, Y., Chen, P. J., Zhou, M., Huang, D. J. Y., Zhao, Z., Zhang, X., Zhao, Y., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-013637 · Cited by 1
Identify CCL20 as the key immune microenvironment regulator in APC-mutation colon cancer by sc-RNA data analysis
Shi, X., Chen, H., Li, R., Zhong, Z., Lu, X., Kong, X., Li, J., Wang, S., Guo, W., & Zhang, R.-M. (2026) · Biochemical Pharmacology · doi:10.1016/j.bcp.2026.117992 · Cited by 1
Single-cell spatial analysis stratifies lung adenocarcinoma with rare actionable mutations and reveals immune-modulatory cellular crosstalk
Ma, J., Li, X., Qian, N., Li, S., Li, L., Zhang, X., Su, L., Yang, Y., Luo, H., Yin, M., et al. (2026) · Cell Reports Medicine · doi:10.1016/j.xcrm.2026.102760 · Cited by 1
“16 Therefore, leveraging single-cell spatial transcriptomics to investigate the TME in patients with LUAD harboring rare driver mutations is essential for uncovering actionable insights into the treatment response and optimizing patient stratification in clinical practice.”
Single-cell dissection of persistent tumor antigens in non-responders reveals opportunities for TAA-targeted vaccination after neoadjuvant therapy in esophageal squamous cell carcinoma
Zhang, R., Qi, S., Zhou, Y., Hu, Y., Li, Y., Li, Y., Qin, J., Yang, A., Zhang, H., Liu, Z. H., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-014562 · Cited by 1
Decoding Human T Cell Immunity with Artificial Intelligence and Single-Cell Genomics.
Dratva, L., Teichmann, S. A., & Kretschmer, L. (2026) · Annual Review of Immunology · doi:10.17863/cam.130879 · Cited by 1
Pan-Cancer Proteomic and Transcriptomic Meta-Analysis of PD-1/PD-L1 Signaling Reveals Predictive Biomarkers for Anti-PD-1 Therapy in Lung Cancer
Suo, Y., Song, Y., Zhou, H., & Liu, Q. (2026) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5c01238 · Cited by 1
The roles and heterogeneity of CD8 + T cells in inflammatory bowel disease: A narrative review of insights from single‑cell transcriptomics (Review)
Zhong, R., Guo, J., Ye, W., Deng, Z., Wu, H., Qi, Q., Li, G., Zhu, L., Huang, Y., & Wu, L. (2026) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2026.5801 · Cited by 1
“…of CD8 + T cell infiltration in numerous human diseases, including malignancies such as non‑small cell lung cancer (49), breast cancer (50), head and neck cancer (51), liver cancer (52), melanoma (53), bladder cancer (54) and colorectal cancer (55), as well as immune‑ related diseases…”
Decoding drug-responsive cell subpopulations in triple-negative breast cancer using single-cell multiomics
Wang, Y., Haase, S., Whitman, A., Beltran, A., Spanheimer, P., & Brunk, E. C. (2026) · iScience · doi:10.1016/j.isci.2026.115445 · Cited by 1
“57 These findings, together with other studies that have characterized TME remodeling in response to therapy 61–63 in TNBC, provide an important biological context for our observations.”
Single-cell profiling of PBMCS reveals an immune signature of irAEs in anti-PD-1-treated acral melanoma patients
Bao, Q., Pan, J., & Wang, Z. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1758205 · Cited by 1
A machine learning model integrating circulating Temra cell transcriptional profiles to predict immunotherapy efficacy.
Dong, Y.-C., Xu, X., Si, H.-J., Li, Y., Yang, D.-L., Chen, J.-Y., Wang, Y.-Z., Zhang, H.-M., Yang, L., Xie, H.-K., et al. (2026) · i Medicina · doi:10.1016/j.medj.2026.101027 · Cited by 1
T-cell receptor clonotypic diversity and specialization in digestive system cancers
Li, L., Li, J., Wang, F., Jiang, R., Wang, H., Li, X., & Zhen, Y. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01294-4 · Cited by 1
Novel pan-cancer T cell exhaustion signature forecasts immunotherapy response and unveils BCAP31 in macrophages as a therapeutic target in neuroblastoma
Li, S., Zhu, J., Huang, X., Ji, F., Li, J., Yao, Z., Tang, H., Liu, L., Yan, B., & Zhanghuang, C. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1709225 · Cited by 2
“…SCP1288 (17)), urothelial carcinoma (UC, GSE145281 (18)), triple negative breast cancer (TNBC, GSE169246 (19)), breast invasive carcinoma (BRCA, Bassez 2021 (20)), carcinoma of colon and rectum (CRC, GSE205506 (21) and GSE236581 (22)), non-small cell lung carcinoma (NSCLC, GSE207422 (23) and…”
ProjectSVR: mapping single-cell RNA-seq data to reference atlases by supported vector regression
Gao, J., Fang, J., Zhu, Q., Li, G., Bi, Z., Hu, Y., Hong, B., Zhang, Y., Guo, S., & Wang, H. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf586 · Cited by 6
“Consistent with the original findings [23], we observed an enrichment of T follicular helper (Tfh), T helper 1 (Th1), and regulatory T (Treg) cells in pre-treatment tumors from responders (Fig.”
Enhanced prediction of breast cancer patient response to chemotherapy by integrating deconvolved expression patterns of immune, stromal and tumor cells
Dhruba, S. R., Sahni, S., Wang, B., Wu, D., Rajagopal, P. S., Gurevich, Y., Shulman, E. D., Sinha, S., Sammut, S., Caldas, C., et al. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.218101 · Cited by 4
Differential T cell clonal dynamics underlie outcomes to frontline chemoimmunotherapy in advanced gastric cancer
Wright, S., Kang, S., An, M., Heo, Y., Parikh, M., Bi, L., Lee, H., Moorehead, G., Haradhvala, N., Lim, S., et al. (2025) · medRxiv · doi:10.1101/2025.08.26.25334455 · Cited by 1
“We applied a gene signature associated with CD8+ T cell tumor-reactivity derived through supervised factorization of a scRNA-seq dataset from an anti-PDL1 treated cohort with non-metastatic breast cancer 12,31 .”
Pan-cancer single cell transcriptomic clustering reveals heterogeneous CD8 + exhausted T cell populations with different immune checkpoint inhibitor responses
Mu, R., Barakat, R., & Gutmann, D. H. (2025) · OncoImmunology · doi:10.1080/2162402x.2025.2540504 · Cited by 1
“33 Collectively, these findings suggest that one mechanism by which anti-PD1 antibody therapy eradicates tumors could involve an expansion of cluster C1 containing CD8 + exhausted T cells with cytotoxic activity.”
DALE-Eval: A comprehensive cell type-specific expression deconvolution benchmark for transcriptomics dataPreprint
Hu, M., Zhang, M. J., & Chikina, M. D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.31.667984
Multi-omics analysis of zinc finger protein 683 as a prognostic biomarker for immune infiltration in clear cell renal cell carcinoma
Guo, Y.-C., Wang, Y., Ding, G.-X., Wang, T., Sun, F.-Z., Ma, X., & Wu, J.-T. (2025) · BMC Cancer · doi:10.1186/s12885-025-14643-6 · Cited by 1
“Notably, in patients with progressive disease, ZNF683 showed a positive correlation with HAVCR2, a known immune checkpoint associated with immune exhaustion [46].”
Benchmarking and optimizing organism wide single-cell RNA alignment methods
Díaz-Mejía, J. J., Williams, E., Focsa, O., Mendonca, D., Singh, S., Innes, B., & Cooper, S. (2025) · arXiv.org · doi:10.48550/arxiv.2503.20730 · Cited by 1
“To create this more realistic example we took a 30,000 cell sample from one high-quality scRNA dataset Bassez et al. (2021) and embedded it into a 5-dimensional space S ∈ R 5 using a basic implementation of a Variational Autoencoder with Mean Squared Error loss function Kingma & Welling (2013),…”
Single-cell and transcriptome analyses revealed CTHRC1 a potential therapeutic target mediating invasion and tumor microenvironment in TNBC: experimental validation
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Single-cell RNA sequencing of bone marrow reveals the immune response mechanisms of lymphocytes under avian leukosis virus subgroup J infection
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“In HIV infection, HIV exhibits unique susceptibility to CD4 + T cells, as CD4 is the receptor for HIV (Bassez et al., 2021).”
Influential
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“Building on these findings, we expanded our analysis to multiple patient samples 58 ( Extended Data Fig.5,6 and Supplementary Table 7 ) to determine whether global trends in identity shifts could be identified.”
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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: Bassez, Ayse
Vos, Hanne
Floris, Giuseppe
Arijs, Ingrid
Desmedt, Christine
Boeckx, Bram
Vanden Bempt, Marlies
Nevelsteen, Ines
Punie, Kevin
Neven, Patrick
Garg, Abhishek D.
Wildiers, Hans
Qian, Junbin
Smeets, Ann
Lambrechts, Diether
Venue: Nature Medicine
Publisher: Springer Science and Business Media LLC
Published: 2021-05
Volume: 27
Issue: 5
Pages: 820-832
ISSN: 1078-8956 (ISSN-L)
1546-170X
DOI: 10.1038/s41591-021-01323-8
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: other-oa
www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
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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A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer

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