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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Yuan, Z., Liu, Z., Zhou, M., Wen, H., & Li, B. (2026) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2025.105111 · Cited by 6
Immunotherapy-driven remodeling of the tumor immune microenvironment: Spatiotemporal heterogeneity and multidimensional dynamics
Pan, J., Chen, S., Jin, L., Chen, K., Ye, Z., & Li, B. (2026) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2026.189544 · Cited by 6
Intelligent responsive degradation nanoplatform with aggregation-induced emission for hypoxic tumors multimodal phototheranostics and overcoming PD-L1 resistance
Yan, X.-K., Shang, W.-Z., Ren, H., Cai, Y., Gong, Y., Wang, L.-R., Tang, B. Z., & Su, H.-F. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.171050 · Cited by 6
Cellular reprogramming during anti-PD-1 and chemotherapy treatment in early-stage primary hormone receptor-positive breast cancer
Fu, J., Waks, A. G., Pimenta, E. M., Titchen, B. M., Bi, K., Camp, S. Y., Pappa, T., Keenan, T. E., Shannon, E. E., Vigneau, S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66659-y · Cited by 4
“Multiomic single-nucleus sequencing, which couples single-nucleus transcriptome and chromatin accessibility pro ﬁ ling, offers opportunities to study the microenvironment of tumors and uncover molecular programs underlying response or resistance to therapy in breast cancer 7,8 .”
NK cell adaptation in the tumor microenvironment: Insights for NK cell-based immunotherapy
Li, Y., Gao, Y., Wang, L., & Si, J. (2025) · Cytokine & Growth Factor Reviews · doi:10.1016/j.cytogfr.2025.10.003 · Cited by 6
m6A-modified circZNF548 regulates exosomal miR-7108-3p to activate CD3+CD8+ T cells and suppress NSCLC growth by JMY
Zhao, Y.-L., Li, Y.-J., Wu, C.-X., Xie, N., Li, X.-Y., Cao, D.-C., Guo, Y., Liang, Y., Li, Y.-M., Xue, J.-N., et al. (2025) · BMC Biology · doi:10.1186/s12915-025-02355-z · Cited by 6
“The antitumor activity of CD8 + T cells is linked to the upregulation of CD107, IFN-γ, PRF1, and Gzmb [45, 46].”
A spatial transcriptomics study of MES-like and mono/macro cells in gliomas
Zhao, B., Wu, J., Zhang, T.-H., Han, M., Zhang, C., Rong, X., Zhang, R., Chen, X., Peng, F., Jin, J., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-95277-3 · Cited by 6
Arsenene-Vanadene Nanodots Co-Activate Apoptosis/Ferroptosis for Enhanced Chemo-Immunotherapy.
He, L., Ren, W., Cheng, W., Chen, J.-Q., Lai, J.-J., Wu, Y.-J., Wu, Z.-B., Bao, D., Wei, Y., & Piao, J.-G. (2025) · Acta Biomaterialia · doi:10.1016/j.actbio.2025.02.059 · Cited by 6
Development of a prognostic model for NSCLC based on differential genes in tumour stem cells
Ma, Y.-Q., Li, J., Xiong, C., Sun, X., & Shen, T. (2024) · Scientific Reports · doi:10.1038/s41598-024-71317-2 · Cited by 6
Disulfidptosis-related gene SLC7A11 predicts prognosis and indicates tumor immune infiltration in lung adenocarcinoma
Zhu, J., Ge, H.-T., Chen, Y., Zhang, S., Wu, J., Nai, W., & Min, L. (2024) · Translational Cancer Research · doi:10.21037/tcr-24-1182 · Cited by 6
“Single-cell sequencing data from patients treated with programmed cell death protein 1 (PD1) therapy were curated from a breast cancer study (15).”
Method
Single‐cell RNA sequencing of cystic fibrosis liver disease explants reveals endothelial complement activation
Declercq, M., Treps, L., Geldhof, V., Conchinha, N. V., de Rooij, L. P. M. H., Subramanian, A., Feyeux, M., Cotinat, M., Boeckx, B., Vinckier, S., et al. (2024) · Liver International · doi:10.1111/liv.15963 · Cited by 7
Self-citation
Comprehensive pan‐cancer analysis of mitochondrial outer membrane permeabilisation activity reveals positive immunomodulation and assists in identifying potential therapeutic targets for immunotherapy resistance
Chen, Q., Gao, F., Wu, J., Zhang, K.-M., Du, T., Chen, Y., Cai, R., Zhao, D., Deng, R., & Tang, J. (2024) · Clinical and Translational Medicine · doi:10.1002/ctm2.1735 · Cited by 5
Single-cell data revealed exhaustion of characteristic NK cell subpopulations and T cell subpopulations in hepatocellular carcinoma
Cui, Z.-N., Li, H.-Z., Liu, C., Wang, J., Chen, C., Hu, S., Zhao, X., & Li, G.-M. (2024) · Aging · doi:10.18632/aging.205723 · Cited by 6
“TCF7 was a biomarker for naïve or undifferentiated cells [29].”
Background
Single-cell RNA-seq reveals the metabolic status of immune cells response to immunotherapy in triple-negative breast cancer
Liu, P.-W., Lin, J., Hou, R., Cai, Z., Gong, Y., He, P., & Yang, J. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.107926 · Cited by 7
ProjectSVR: Mapping single-cell RNA-seq data to reference atlases by supported vector regressionPreprint
Gao, J., Guo, S., & Zhang, Y.-W. (2023) · bioRxiv · doi:10.1101/2023.07.31.551202 · Cited by 6
“Consistent with the original study 24 , we observed that T helper (Tfh) cells, T helper 1 (Th1) cells (referred to “experienced T cells” in the original study) and regulatory T cells (Treg) were enriched in the pretreatment tumors of responders (Fig.”
Result
Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer
Li, H.-M., Liu, H., Hao, Q., Liu, X., Yao, Y.-Z., & Cao, M. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.891175 · Cited by 6
Integration of Genomic Profiling and Organoid Development in Precision Oncology
Yoon, H., & Lee, S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms23010216 · Cited by 9
Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers
Shi, T., Guo, Y., Tang, X., Liu, Z., Guo, Q., Fang, T., Xu, S., & Zhuang, Z. (2026) · Neoplasia · doi:10.1016/j.neo.2026.101348 · Cited by 9
“In breast cancer patients receiving anti-PD-1 treatment, single-cell profiling of intratumoral changes revealed therapy-associated remodeling of T-cell and other immune compartments [117].”
Influential
TROP2/claudin program mediates immune exclusion to impede checkpoint blockade in breast cancer
Wu, B., Thant, W., Bitman, E., Liu, T., Liu, J., Paschalis, E. I., Patel, B. K., Nawrocki, C., Xu, K. H., Nieman, L. T., et al. (2026) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-012265 · Cited by 12
“30 31 We examined the impact of TROP2 expression on treatment effect through bulk/pseudo-bulk RNA analysis, plotting the OR for effect as a function of TROP2.”
Molecular remodeling of cancer-associated fibroblasts in breast cancer patients receiving anti–PD-1 immunotherapy
Do, K. V., Tran, A. V., Pham, A. D., Mac, T. T., Pham, T. L., & Do, H. N. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1754311 · Cited by 5
Activated CD38+ mast cells promote gastric cancer progression by suppressing CD8+ T cell cytotoxic activity through adenosine metabolism
Zhao, J., Feng, D., Zhang, F., Cai, S., Xiong, Y., Pan, G., Ma, J., Tan, J., Zhong, M., Lin, Z., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2025.116863 · Cited by 6
A pan-immunotherapy signature to predict intratumoral CD8+ T cell expansions
Takahashi, M., Tsunoda, M., Aoki, H., Kurosu, M., Ogiwara, H., Shichino, S., Bending, D., Ishikawa, S., Thaventhiran, J., Matsushima, K., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64107-5 · Cited by 5
“dif ﬁ cult to determine whether any observed changes re ﬂ ect true biology, or are an artifact of the limited sampling 12 .”
Influential
Why combine and why neoadjuvant? Tumor immunological perspectives on chemoimmunotherapy in triple-negative breast cancer
Kakimi, K., & Sugie, T. (2025) · Breast Cancer · doi:10.1007/s12282-025-01707-5 · Cited by 7
“Bassez et al. conducted comprehensive single-cell transcriptome, TCR repertoire, and proteome analysis in tumor samples pre/post-neoadjuvant anti-PD-1 therapy (ER-positive or TNBC) [65].”
Single-cell profiling in ovarian germ cell and sex cord-stromal tumours
Laga, T., Rompuy, A. V., Busschaert, P., Marquina, G., Loverix, L., Olbrecht, S., Ottenbourgs, T., Baert, T., Gorp, T. V., Vergote, I. B., et al. (2025) · British Journal of Cancer · doi:10.1038/s41416-025-03012-6 · Cited by 5
Self-citation
Single-cell and multi-omics integration reveals cholesterol biosynthesis as a synergistic target with HER2 in aggressive breast cancer
Tseng, T.-Y., Hsieh, C.-H., Liu, J., Huang, H., & Juan, H. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.04.030 · Cited by 6
“To uncover the mechanisms underlying malignant breast cancer cells and inform prognosis-guided therapeutic approaches, we analyzed the scRNA-seq profiles of tumor tissues from 31 treatment-naïve breast cancer patients [16].”
Cancer-cell derived S100A11 promotes macrophage recruitment in ER+ breast cancer
Lee, S., Cho, Y., Li, Y., Li, R., Lau, A. W., Laird, M. S., Brown, D. D., McAuliffe, P. F., Lee, A. V., Oesterreich, S., et al. (2024) · OncoImmunology · doi:10.1080/2162402x.2024.2429186 · Cited by 10
Effect of acute exercise on gene expression in peripheral blood mononuclear cells of puberty children
Du, L., Song, Y.-H., & Tang, L.-X. (2024) · Scientific Reports · doi:10.1038/s41598-024-77242-8 · Cited by 5
“GZMB pronounced in the expression of cytotoxic activity 23 .”
NK cell exhaustion in Wilson’s disease revealed by single-cell RNA sequencing predicts the prognosis of cholecystitis
Jin, Y., Xing, J., Dai, C., Jin, L., Zhang, W., Tao, Q., Hou, M., Li, Z.-Y., Yang, W., Feng, Q.-Y., et al. (2024) · bioRxiv · doi:10.1101/2024.05.02.592210 · Cited by 5
Endoplasmic reticulum stress-related features predict the prognosis of osteosarcoma and reveal STC2 as a novel risk indicator for disease progression
Yu, Y., Duan, P., Chen, H., Cheng, Y., Zhang, H., Zheng, L., Yu, J., Yu, Z., Ye, X., Xu, J., et al. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1453173 · Cited by 4
scPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets
Xie, Y., Yang, J., Ouyang, J. F., & Petretto, E. G. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae482 · Cited by 5
“For example, in anti-PD1 treatment, only specific macrophage phenotypes (CCR2 + or MMP9 + ) are correlated with T cell expansion, an indicator of anti-PD1 treatment response, in pre-treatment tissues [49].”
Integrative analysis identifies cancer cell-intrinsic RARRES1 as a predictor of prognosis and immune response in triple-negative breast cancer
Yu, Z.-H., Liu, H., Ye, J., Liu, Y., Xin, L., Liu, Q., Cheng, Y., Lu, Y., & Xu, L. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1360507 · Cited by 5
“…in single-cell RNA sequencing (scRNA-seq) have made it possible to analyze the heterogeneity, functional status, interactions, and evolving trajectories of cells in the TME at single-cell resolution (Bassez et al., 2021; Huang and Zhang, 2021b; Wu et al., 2021; Yan et al., 2021; Zhao et al., 2022).”
BackgroundMethod
Gas-Phase Fractionation Data-Independent Acquisition Analysis of 3D Cocultured Spheroid Tumor Model Reveals Altered Translational Processes and Signaling Using Proteomics
Shannon, A. E., Boos, C. E., Searle, B. C., & Hummon, A. B. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00786 · Cited by 4
Multifactor assessment of ovarian cancer reveals immunologically interpretable molecular subtypes with distinct prognoses
Guo, Y., Li, S., Li, C., Wang, L., & Ning, W. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1326018 · Cited by 6
“By contrast, CX3CR1 was highly expressed in S-III, which represented inhibitory (CX3CR1 + ) macrophages (36).”
Background
CILP is a potential pan-cancer marker: combined silico study and in vitro analyses
Guo, B.-J., Zhao, F., & Zhang, S. (2023) · Cancer Gene Therapy · doi:10.1038/s41417-023-00688-x · Cited by 5
“…cells (KRT19 [16, 17], EPCAM [16, 17]), Endothelial cells (VWF [16]), Fibroblasts (ACTA2 [18], FGF7 [19]), NK cells (KLRB1 [20]), Dendritic cells (CD1E [17]), Monocytes (S100A9 [21]), Macrophages (C1QA [22]), Mast cells (TPSAB1 [23]), B cells (MZB1 [23], CD79A [16, 17]), T cells (CD3D [24]).”
Combination of local radiotherapy and anti-glucocorticoid-induced tumor necrosis factor receptor (GITR) therapy augments PD-L1 blockade-mediated anti-tumor effects in murine breast cancer model
Song, J. Y., Han, M. G., Kim, Y., Kim, M. J., Kang, M. H., Jeon, S. H., & Kim, I. A. (2023) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2023.109981 · Cited by 5
Immunology of cell death in cancer and infection
Garg, A. (2022) · Genes and Immunity · doi:10.1038/s41435-022-00184-6 · Cited by 5
Self-citation
Dissecting the cellular architecture of breast cancer brain metastases reveals prognostically distinct immune landscapes
Jassowicz, L., Feng, F., Warta, R., Heinicke, F., Wöllner, A., Briesch, H., Sor, F., Soller, J., Lotsch, C., Wong, J. K. L., et al. (2026) · Cancer Cell · doi:10.1016/j.ccell.2026.03.016 · Cited by 6
Obesity- and tumor-derived signals drive cancer-associated state transitions in breast mesenchymal stromal/stem cells reprogrammed by IL1RA or JAK inhibition
Ritter, A., Hoock, S., Kreis, N.-N., Roth, S., Colin, R. C. T., Friemel, A., Wildner, J. M., Scherr, I., Louwen, F., Solbach, C., et al. (2026) · Experimental Hematology & Oncology · doi:10.1186/s40164-026-00747-7 · Cited by 4
“Raw gene expression matrices and cell clustering analyses were initially performed by Bassez and Vos et al. using the Seurat v3 R package [36].”
Influential
Evaluating deconvolution methods using real bulk RNA-expression data for robust prognostic insights across cancer types
Li, M., Su, Y., Tang, Y., Lee, Y., & Tian, W. (2026) · Genome biology · doi:10.1186/s13059-026-03942-1 · Cited by 5
“The cancer types included were breast cancer (BRCA) [39], colon adenocarcinoma (COAD) [40], esophageal carcinoma (ESCA) [41], head and neck squamous cell carcinoma (HNSC) [42], kidney renal clear cell carcinoma (KIRC) [43], liver hepatocellular carcinoma (LIHC) [44], non-small cell lung cancer…”
Immune Predictors of Radiotherapy Outcomes in Cervical Cancer
Wang, L., Zhu, J., Ding, Z., Xie, Z., Liu, X., Zhang, F., Liu, X., Zhang, Y., & Chen, H. (2026) · Advanced Science · doi:10.1002/advs.202509784 · Cited by 3
“MMP9 was associated with extracellular matrix remodeling(Figure 3E ) [ 25 ].”
Host-derived interleukin-1α drives tumor immunosuppression by reprogramming tumor-associated myeloid cells
Raja, M. R. K., Gupta, G., Atkinson, G., Kathrein, K. L., Armstrong, A. R., Gower, R. M., Roninson, I. B., Broude, E. V., Chen, M., Ji, H., et al. (2026) · npj Breast Cancer · doi:10.1038/s41523-026-00890-8 · Cited by 6
Pharmacological perturbation of splicing elicits SMG1 reduction: Implications for cancer therapy
Barainka, M., Zheleva, A., Pérez-Cervera, Á., Villanueva, H., Meraviglia-Crivelli, D., Moreno, B., & Pastor, F. (2026) · iScience · doi:10.1016/j.isci.2025.114597 · Cited by 4
“To explore this possibility, we analyzed single-cell RNA sequencing (scRNAseq) data from tumor cells of a cohort of 31 breast cancer patients, 30 focusing on the expression of SMG1 and different splicing factors. scRNAseq data from Bassez et al. 30 were reanalyzed using the SCTransform normalization method, 31 which c…”
Monitoring systemic immune responses to checkpoint inhibition in breast cancer reveals host responses and mechanisms of resistance
Hanna, A., Sun, X., Sheng, Q., Ericsson, P. I. G., Wescott, E. C., Taylor, B. C., Marshall, J. L., Opalenik, S. R., Toren, A. L., Sanchez, V. M., et al. (2025) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-012606 · Cited by 5
Efficacy, safety, and predictive biomarkers of neoadjuvant nab-paclitaxel and pembrolizumab in hormone receptor-positive breast cancer: A randomized pilot trial
Waks, A. G., Fu, J., Chu, X., Kurt, B. B., Li, T., Kuntz, T. M., Shen, Y., Yang, D. D., Meli, K., Reardon, B. M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66667-y · Cited by 6
“Neoadjuvant ICI has been shown to induce expansion of PD1 -expressing T cells in HER2-negative breast cancer (both triple-negative and HR +), and this effect appears consistent whether tumors are treatment-naïve or chemotherapy-exposed atthe time of ICI initiation 14 .”
Novel nanoparticle-combined therapy through EGFR and PD-L1 blockade: PFPR-siRNA-mediated suppressing NSCLC proliferation via PDT and enhanced antitumor immunity.
Zhang, M., Xie, N., Wu, D.-Y., Wu, C.-X., Guo, Y., Wang, N.-N., Li, X.-Y., Liang, Y., Xie, X., Wang, T., et al. (2025) · Colloids and Surfaces B: Biointerfaces · doi:10.1016/j.colsurfb.2025.115284 · Cited by 4
Single-cell mapping of alternative splicing linked to checkpoint immunotherapy response
Xiong, J., Bricard, O., Arijs, I., Demeulemeester, J., Gu, C., Thienpont, B., Daaboul, D., Bassez, A., Bechter, O. E., Poźniak, J., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1171 · Cited by 4
“6 D), while TMB did not differ [ 23 ].”
InfluentialSelf-citation
Peripheral blood gene expression signatures of systemic immunity predict tumor microenvironment biology and therapeutic response in breast cancerPreprint
Balko, J. M., Sun, X., Hanna, A., Ocampo, A. A., Taylor, B. C., Marshall, J., Steele, J., Axelrod, M. L., Wescott, E. C., Opalenik, S. R., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-6926989/v1 · Cited by 2
“Tissue based biomarkers, like tumor-specic MHC-II expression, have been validated retrospectively in a large number of studies across multiple groups 5–10 .”
The interplay between the immune response and neoadjuvant therapy in breast cancer
Thomas, N., Foukakis, T., & Willard-Gallo, K. E. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1469982 · Cited by 5
CD103+CD56+ ILCs Are Associated with an Altered CD8+ T-cell Profile within the Tumor Microenvironment
Chung, D. C., Shakfa, N. E., Vakharia, J., Warner, K., Jacquelot, N., Sayad, A., Han, S., Ghaedi, M., Garcia-Batres, C. R., Sotty, J., et al. (2025) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-24-0151 · Cited by 5
Unveiling the role of MDH1 in breast cancer drug resistance through single-cell sequencing and schottenol intervention.
Lu, J.-F., Ding, F., Sun, Y.-J., Zhao, Y., Ma, W., Zhang, H., & Shi, B. (2025) · Cellular Signalling · doi:10.1016/j.cellsig.2025.111608 · Cited by 4
GSDMD is associated with survival in human breast cancer but does not impact anti-tumor immunity in a mouse breast cancer model
Boersma, B., Puddinu, V., Huard, A., Fauteux‐Daniel, S., Wirapati, P., Guedri, S., Tille, J., McKee, T., Pittet, M. J., Palmer, G., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1396777 · Cited by 6
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions
Li, M., Su, Y., Gao, Y., & Tian, W. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae422 · Cited by 3
“Four TNBC scRNA-seq datasets, which are from the studies of Wu et al. (GSE176078) [28], Pal et al. (GSE161529) [29], Xu et al. (GSE180286) [35], and Bassez et al (http://biokey.lambrechtslab.org) [30] were integrated as the reference set.”
Method
Bibliometric Analysis of TREM2 (2001-2022): Trends, Hotspots and Prospects in Human Disease
Qian, M., Zhong, J., Lu, Z., Zhang, W., Weng, M., Zhang, K., & Jin, Y. (2024) · International Journal of Medical Sciences · doi:10.7150/ijms.96851 · Cited by 4
“In breast cancer patients treated with anti-PD-1 therapy, TREM2 + TAMs are inversely correlated with T cell clonal expansion [69].”
Background
Prognostic and therapeutic insights into colorectal carcinoma through immunogenic cell death gene profiling
Yu, J.-L., Gong, Y., Xu, Z., Chen, L., Li, S., & Cui, Y. (2024) · PeerJ · doi:10.7717/peerj.17629 · Cited by 4
“Additionally, examining single-cell changes during anti-PD1 treatment could provide insights into treatment response heterogeneity in colorectal cancer ( Bassez et al., 2021 ).”
Background
Decoding changes in tumor‐infiltrating leukocytes through dynamic experimental models and single‐cell technologies
Lee, C. Y. C., Clatworthy, M. R., & Withers, D. R. (2024) · Immunology and Cell Biology · doi:10.1111/imcb.12787 · Cited by 3
“20,47 A challenge in time-series data is that scRNA-seq experiments are cell-destructive and only represent a fraction of the proﬁled tissues.”
AAnet resolves a continuum of spatially-localized cell states to unveil tumor complexityPreprint
Venkat, A., Youlten, S. E., Juan, B. P. S., Purcell, C., Amodio, M., Burkhardt, D. B., Benz, A., Holst, J., McCool, C. S., Mollbrink, A., et al. (2024) · bioRxiv · doi:10.1101/2024.05.11.593705 · Cited by 4
“To examine the clinical relevance of the identified archetypes, we analyzed single-cell transcriptomes from human breast cancer cells across four distinct studies, corresponding to 34 samples from three major breast cancer subtypes (ER+, HER2+, TNBC) (Figure 7c) [6,35,51].”
BackgroundMethod
Regulatory T‐cells activated in metastatic draining lymph nodes possibly suppress cancer immunity in cancer tissues of head and neck squamous cell cancer
Suzuki, S., Tsuzuki, T., Saito, M., Ishii, T., Takahara, T., Satou, A., Inukai, D., Yamanaka, S., Yoshikawa, K., Ueda, R., et al. (2024) · Pathology international (Print) · doi:10.1111/pin.13430 · Cited by 4
Identification of MIR600HG/hsa-miR-342-3p/ANLN network as a potential prognosis biomarker associated with lmmune infiltrates in pancreatic cancer
Qian, B.-L., Liu, Q., Wang, C., Lu, S., Ke, S., Yin, B., Li, X., Yu, H., Wu, Y.-H., & Ma, Y. (2023) · Scientific Reports · doi:10.1038/s41598-023-43174-y · Cited by 4
Resistance of MMTV-NeuT/ATTAC mice to anti-PD-1 immune checkpoint therapy is associated with macrophage infiltration and Wnt pathway expression
Yuan, H., Jin, L., Xiang, H., Bhattacharya, A., Brandish, P. E., Baltus, G. A., Tong, A., Zhou, C., & Glazer, R. I. (2022) · Oncotarget · doi:10.18632/oncotarget.28330 · Cited by 3
scMARK an ‘MNIST’ like benchmark to evaluate and optimize models for unifying scRNA dataPreprint
Swechha, Mendonca, D., Focsa, O., Díaz-Mejía, J. J., & Cooper, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.08.471773 · Cited by 1
Tumor organoid-immune cell co-culture systems for precision oncology
Cai, L., Xiao, Y., Xie, F., & Yang, Z. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1865487 · Cited by 3
The PLAU-ITGB1-TGF-β axis orchestrates spatiotemporal reprogramming of fibroblasts at the invasive front to drive dual immunosuppressive niche and immunotherapy resistance in oral squamous cell carcinoma
Xiong, Y.-L., Liu, S.-P., Zhao, L.-Y., Liu, X.-Z., Zhang, H.-Z., Wang, H.-R., Zhang, D.-S., Wang, C.-L., & Wu, H.-W. (2026) · Cell Death and Disease · doi:10.1038/s41419-026-09110-4 · Cited by 3
TNF-α drives pancreatic microcirculatory dysfunction via CD8+ T cell-mediated endothelial injury in severe acute pancreatitis
Shi, L., Li, W.-Q., Chen, D., Liu, B., Huang, Z., Jin, C.-Q., Ma, L.-F., Liu, Q., Dong, B.-Z., Pan, Z., et al. (2026) · Gut · doi:10.1136/gutjnl-2025-337183 · Cited by 3
“33 34 Interestingly, CD8 + Temra lineage (Lineage 3) emerged as the predominant trajectory in SAP samples (p 0.01), suggesting a pivotal role for Temra cells in disease progression (figure 3K).”
InfluentialSelf-citation
T cell exhaustion landscapes and therapeutic modulation in cancer immunity
Bautista, J., & López‐Cortés, A. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1827716 · Cited by 5
“Most human studies remain constrained by limited temporal resolution, making directionality difficult to infer and increasing the risk of over-interpreting embeddings or trajectory models in the absence of orthogonal validation (Bassez et al., 2021; Bergen et al., 2020).”
Regorafenib and R837 nanoparticle-stabilized Pickering emulsions overcome the angiogenesis-immune tolerance axis in transarterial chemoembolization.
Peng, Y., Liu, H., Yang, L.-J., Wu, X.-Y., Fan, J., Liang, X.-L., Cao, L., Miao, M., Chen, H., Teng, M.-L., et al. (2026) · Biomaterials · doi:10.1016/j.biomaterials.2026.124317 · Cited by 3
Peripheral blood transcriptional profiling predicts tumor subtype and neoadjuvant chemoimmunotherapy outcomes in human breast cancer
Sun, X., Ocampo, A. A., Hanna, A., Taylor, B. C., Marshall, J. L., Steele, J. A., Axelrod, M. L., Wescott, E. C., Opalenik, S. R., DeMichele, A. M., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.aec2358 · Cited by 3
Pharmacological activation of WASp potentiates macrophage phagocytosis and enhances ibrutinib efficacy against mouse models of brain tumors.
Cheng, Y., Li, T., Wang, M.-R., Lan, C., Fan, H.-Z., He, Z.-C., Liu, Q., Li, F., Wang, L.-J., Wang, W.-Y., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.aed1155 · Cited by 3

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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