Abstract
Gemcitabine plus cisplatin (GP) chemotherapy is the standard of care for nasopharyngeal carcinoma (NPC). However, the mechanisms underpinning its clinical activity are unclear. Here, using single-cell RNA sequencing and T cell and B cell receptor sequencing of matched, treatment-naive and post-GP chemotherapy NPC samples (n = 15 pairs), we show that GP chemotherapy activated an innate-like B cell (ILB)-dominant antitumor immune response. DNA fragments induced by chemotherapy activated the STING type-I-interferon-dependent pathway to increase major histocompatibility complex class I expression in cancer cells, and simultaneously induced ILB via Toll-like receptor 9 signaling. ILB further expanded follicular helper and helper type 1 T cells via the ICOSL–ICOS axis and subsequently enhanced cytotoxic T cells in tertiary lymphoid organ-like structures after chemotherapy that were deficient for germinal centers. ILB frequency was positively associated with overall and disease-free survival in a phase 3 trial of patients with NPC receiving GP chemotherapy (NCT01872962, n = 139). It also served as a predictor for favorable outcomes in patients with NPC treated with GP and immunotherapy combined treatment (n = 380). Collectively, our study provides a high-resolution map of the tumor immune microenvironment after GP chemotherapy and uncovers a role for B cell-centered antitumor immunity. We also identify and validate ILB as a potential biomarker for GP-based treatment in NPC, which could improve patient management.
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Data availability
The scRNA-seq and TCR/BCR sequencing data generated by this study were deposited at the CNGB Sequence Archive (https://db.cngb.org/cnsa/) under accession nos. CNP0001341 for the scRNA-seq raw data and CNP0001503 for the scRNA-seq processed data. Raw FASTQ data are publicly available as of the date of publication. The study-level clinical data used in this study are shown in Extended Data Tables 1–4. Deidentifed patient-level data will be made available upon reasonable request after approval by the corresponding author and Sun Yat-sen University Cancer Center. A detailed research protocol and data access agreement will be required to evaluate the reasonableness of the data request and to avoid any confidentiality obligations. The corresponding author and Sun Yat-sen University Cancer Center reserve the right to decide whether to share the data or not based on the materials provided by researchers. Requests for access to the patient-level data from this study can be submitted via email to the corresponding author J.M. (majun@sysucc.org.cn). The microarray profiles of Cohort_2 (EGAS00001004542) can be downloaded from the European Genome-phenome Archive dataset (https://ega-archive.org/). GSE164522 and GSE148673 can be downloaded from the Gene Expression Omnibus dataset (https://www.ncbi.nlm.nih.gov/geo/). The public databases MSigDB and CancerSEA, which provide a resource of annotated gene sets for use, are available at https://www.gsea-msigdb.org and http://biocc.hrbmu.edu.cn/CancerSEA/, respectively. All raw western blot images are provided as Source data files associated with each figure. The authenticity of this manuscript was validated by uploading the key raw data to the Research Data Deposit public platform (RDDB2023502087) (www.researchdata.org.cn). Source data are provided with this paper.
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Acknowledgements
This work was supported by grants from the National Natural Science Foundation of China (award nos. 82172870 and 81930072 to J.M.; award nos. 82025016 and 31830025 to D.-M.K.; award no. 92259202 to Y.S.; and award no. 82203049 to J.L.), the National Postdoctoral Program for Innovative Talents (award no. BX2021386 to J.L.), the Overseas Expertise Introduction Project for Discipline Innovation, 111 Project (award no. B14035 to J.M.), the Fundamental Research Funds for the Central Universities (award no. 23yxqntd001 to D.-M.K.), the Natural Science Foundation of Guangdong Province (award no. 2021B1515020010 to Y.-P.C.), and the National Key R&D Program of China (award no. 2022YFC3400400 to G.-B.L.).
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J.M., Y.S., D.-M.K. and J.L. designed the study. J.M., Y.S., D.-M.K. and J.L. procured financial support. J.L., Y.W., J.-L.G., G.-Q.Z., W.-F.L., L.-L.T., R.G., R.S., Y.-P.M., Y.S. and J.M. collected and prepared the samples. J.L., Y.W., J.-H.Y., C.W. and C.-J.Z. collected the data and performed the methodology. J.L., Y.W., J.-H.Y., C.W. and C.-J.Z. performed the statistical analyses. J.L., Y.W., J.-H.Y., Y.-P.C., C.W., X.-Y.L., D.-M.K., Y.S. and J.M. interpreted the data. J.L., Y.W. and D.-M.K. wrote the original draft. All other authors contributed to the data discussion and interpretation processes. All authors revised and reviewed the manuscript and approved the final version.
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Extended data
Extended Data Fig. 1 Single-cell clustering census.
a, Workflow diagram and study design. b, Flowchart showing patient inclusion criteria and recruitment process of Cohort_1. c, Identification of major cell clusters based on scRNA-seq data. Left: UMAP plot showing major cell clusters of the representative sample. Middle: Heatmap showing copy-number variations (CNVs) of the representative sample. Individual cells (rows) and chromosomal regions (columns) were shown. Right: UMAP plot showing expression of representative genes. d, UMAP plot showing tumor and immune cell subclusters.
Extended Data Fig. 2 Chemotherapy activates STING-IFN-I pathway to enhance antigen presentation capacity of cancer cells.
a, In situ CD20+ B cell density in matched NPC tumors before and after chemotherapy. b, UMAP plot showing 13 clusters of tumor cells colored by patient identity (left) and treatment status (right). c, Expression of MHC classI and antigen presentation genes of individual tumor cells from each patient in the single-cell dataset. Matched samples with > 20 malignant cells were included in the analysis (n = 8 pairs). P values for samples with significantly increased antigen presentation molecules after chemotherapy were shown. d, Kaplan–Meier curves for DFS in NPC patients stratified by high versus low expression of signature scores for trajectory_I (Cluster_12) in Cohort_2. Patients were dichotomously divided based on median expression values. HRs and 95% CIs were calculated using a Cox regression model (two-sided P value by log-rank test). e, Changes of phospho-STAT1 after chemotherapy in NPC samples from Fig. 1d. f,g, IFN-β level (f), phospho-STAT1 (g) in HONE1 treated with GEM, DDP, or GP (48 h; n = 3). h-k, Expression of MHC classI and antigen presentation genes in HK1 (h,k) and HONE1 (i,j) treated with GEM, DDP, or GP (48 h; n = 3). l, Changes in tumor cell STING expression after chemotherapy in the single-cell dataset. Samples with increased MHC classI in c were included in the analysis (n = 5 pairs). The bottom and top of the boxes were 25th and 75th percentiles, respectively (interquartile range). Whiskers encompassed 1.5 times the interquartile range. m, Phospho-STING, STING, phospho-TBK1, TBK1, phospho-IRF3, and IRF3 in HONE1 treated with GEM, DDP, or GP (48 h, n = 3). n, MHC classI and antigen presentation gene expressions in STING knock-out HK1 treated with or without GP chemotherapy (48 h; n = 3). o-q, STING expression (o,p), IFN-β level (p), phospho-STING, phospho-STAT1 (p), MHC classI and antigen presentation gene expression (q) in STING knock-down HONE1 treated with or without GP chemotherapy (48 h; n = 3). Data are the mean ± s.d. A two-sided Wilcoxon test was computed for (c,l), a two-sided one-way ANOVA followed by LSD test for multiple-comparison was computed for (f,h-j,n,o-q).
Extended Data Fig. 3 Chemotherapy triggers effector CD4+ and CD8+ T cell responses.
a, In situ mIF analysis of exhausted CD8+ T cells in matched NPC tumors before and after chemotherapy. Representative images (left) and quantification of changes in CD8+ T cell density, exhausted CD8+ T density and frequency after chemotherapy in responders and nonresponders (right) were shown. b, Expression of TCF7, LAG3, and HAVCR2 in exhausted CD8+ T (Cluster_5) before and after chemotherapy from samples in the single-cell dataset (n = 15 pairs). The bottom and top of the boxes were 25th and 75th percentiles, respectively (interquartile range). Whiskers encompassed 1.5 times the interquartile range. c, Degree of changes in b between responders and nonresponders (n = 15). The boxplot indicated median (center), 25th and 75th percentiles (bounds of box), and minimum and maximum (whiskers). d, Absolute numbers of preexisting and newly-emerged CD8+ and CD4+ T cell clones after chemotherapy in samples with scTCR-seq data (n = 3 pairs). e,f, FACS analysis of IFN-γ+ TH1 (e) and TFH (f) in NPC tumors before and after chemotherapy. Representative plot (left) and quantification of changes in TH1 and TFH after chemotherapy in responders and nonresponders (right) were shown. g,h, In situ mIF analysis of TH1-like cells (g) and TFH (h) in matched NPC tumors before and after chemotherapy. Representative images (upper) and quantification of changes in CD4+ T cell density, TH1-like density and frequency, TFH density and frequency after chemotherapy in responders and nonresponders (bottom) were shown. i, Correlations between TH1-like (x axis, left), TFH signature expression (x axis, right) and CTL signature expression (y axis) in Cohort_2. The correlation coefficient and two-sided P value were calculated by Spearman correlation analysis. j, Kaplan–Meier curves for DFS in NPC patients stratified by high versus low expression of TH1-like (left) and TFH (right) signatures in Cohort_2. Patients were dichotomously divided by median expression value. HRs and 95% CIs were calculated using a Cox regression model (two-sided P value by log-rank test). Data are the mean ± s.d. A two-sided paired-sample t-test was computed for (a,e-h), a two-sided Wilcoxon test for (b), a two-sided student’s t-test for (c).
Extended Data Fig. 4 CD27+IgD+IgM+ ILB frequency increases after chemotherapy.
a, Single-cell clustering of 18,208 myeloid cells from 30 matched NPC samples before and after chemotherapy in the single-cell dataset. UMAP plot displaying myeloid cell clusters (left) and treatment status (right) were shown. b, Changes in cellular interaction scores between myeloid APC subsets and CD4+ Th cells upon chemotherapy. c, Cell-cell interactome between TH1-TFH cells and DC2, TAMs, B cells. d, Correlations between the frequency of B cells and CD4+ T cell subsets in the single-cell dataset. The correlation coefficient and two-sided P value were calculated by Spearman correlation analysis. e, Frequency of ILBs in matched tumor samples before and after chemotherapy from the single-cell dataset (n = 15 pairs). f, Representative flow cytometry plot showing IgM-positive cells in CD45+CD19+CD27+IgD+ B cell subset. g, FACS analysis of CD45+CD19+CD27+IgD+ ILBs in matched NPC tumors before and after chemotherapy. Representative plot (left) and quantification of changes in ILBs after chemotherapy in responders and nonresponders (right) were shown. h, FACS analysis of CD45+CD19+CD27+IgD+ ILBs in peripheral blood of matched NPC patients before and after chemotherapy. Representative plots (left) and quantification of changes in peripheral ILBs after chemotherapy in responders and nonresponders (right) were shown. i, ICOSL expression on ILB in matched samples from the single-cell dataset (n = 15 pairs). j, ICOS expression on TH1-like and TFH cells in matched samples before and after chemotherapy from the single-cell dataset (n = 15 pairs). The bottom and top of the boxes were 25th and 75th percentiles, respectively (interquartile range). Whiskers encompassed 1.5 times the interquartile range. k, FACS analysis of ICOS expression on TH1 and TFH in matched NPC tumors before and after chemotherapy. Data are the mean ± s.d. A two-sided paired-sample t-test was computed for (e,g,h,k), a two-sided Wilcoxon test for (i,j).
Extended Data Fig. 5 ICOSL-elicited mTOR activation is crucial for ILB-mediated effector Th expansion.
a, In situ mIF staining of the typical markers of TLOs (CD3, CD20, CD21, MECA-79) in the chemotherapy-induced TLO-like structures (n = 5). Representative image showed The serial slices from Fig. 4a,c,f. b, Representative in situ mIF images showing the existence of GCs at 1 week, 2-3 weeks, 4-5 weeks upon chemotherapy (n = 5). GC B cells were stained with CD20 plus BCL6. c, Trace plot showing B cell activation signature expression along the second components of diffusion map in Fig. 5a. Cells were projected along the component (x axis), the lines indicated the moving average of signature expression, and the shaded area displayed the standard error. d, Absolute cell numbers of TH1 and TFH cells in Fig. 5g,h. e, Representative FACS plots (left) and quantification of absolute cell numbers of TH1 (right) in Fig. 5j. f, Representative FACS plots (left) and quantification of absolute cell numbers of TFH (right) in Fig. 5j. Data are the mean ± s.d. A two-sided one-way ANOVA followed by LSD test for multiple-comparison was computed for (d), a two-sided paired-sample t-test for (e,f).
Extended Data Fig. 6 ILB predicts favorable survival outcomes in NPC cohorts.
a, Kaplan–Meier curves for OS, distant metastasis-free survival (DMFS), and locoregional recurrence-free survival (LRFS) in NPC patients receiving GP chemotherapy stratified by high (≥50%) versus low (<50%) tumor-infiltrating ILBs in Cohort_3 (n = 139). ILB was measured by in situ mIF analysis. Multivariable analysis was shown in Supplementary Table 7. b, Kaplan–Meier curves for OS in all and subgroups of NPC patients stratified by high versus low expression of ILB signature in Cohort_2 (n = 150). Patients were dichotomously divided by median expression values. Multivariable analysis was shown in Supplementary Table 9. HRs and 95% CIs in a,b were calculated using a Cox regression model (two-sided P value by log-rank test).
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Supplementary Methods, Figs. 1–14, Approval for off-label use of immunotherapy combinations in Cohort_4.
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Lv, J., Wei, Y., Yin, JH. et al. The tumor immune microenvironment of nasopharyngeal carcinoma after gemcitabine plus cisplatin treatment. Nat Med 29, 1424–1436 (2023). https://doi.org/10.1038/s41591-023-02369-6
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DOI: https://doi.org/10.1038/s41591-023-02369-6
