Journal: Cancer Communications
Article Title: The Ly6g high Neutrophil Subset Dictates Breast Cancer Lung Metastasis via CD8 + T Cell Death
doi: 10.34133/cancomm.0003
Figure Lengend Snippet: Il-1β induces Ly6g high neutrophil NETosis in the lung metastatic niche. (A) Heatmap of the scRNA-seq data showing the expression of cytokine genes at different time points during lung metastasis. (B and C) Representative immunofluorescence micrographs (B) showing NET formation by FACS-sorted Ly6g high and Ly6g low neutrophils ( n = 6) after treatment with Il-1β, Cxcl2, and Ccl6 for 6 h in vitro. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The statistical data are presented in (C). (D) Representative immunofluorescence micrographs showing NET formation at the MACRO stages of lung tissue with PBS, rIl-1β, anti-IgG, and anti-Il-1β antibody treatment, respectively [4T1-LM3 (BALB/c) model, n = 5]. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The bar graph on the right quantifies NET formation. (E) Representative bioluminescence imaging and hematoxylin and eosin (H&E) staining images at the MACRO lungs from mice treated with PBS, rIl-1β, IgG, or anti-Il-1β antibody [4T1-LM3 (BALB/c) model, n = 5]. The bar graph on the right shows the quantitative data of lung metastasis burden. (F) Violin plots showing the expression of Il1b in different cell clusters in the lung tissues based on scRNA-seq data from Fig. D. (G) Representative immunofluorescence micrographs demonstrate NET formation in sorted Ly6g high neutrophils ( n = 6). Neutrophils were treated with CM-MΦ or CM-MΦ that had been neutralized with an anti-Il-1β antibody. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). (H and I) Mice were treated with anti-IgG control, anti-F4/80 antibody, or anti-F4/80 antibody combined with rIl-1β until the macrometastatic stage [4T1-LM3 (BALB/c) model, n = 6]. (H) Il-1β levels in the lungs were detected by ELISA. (I) Representative immunofluorescence images show NET formation. NETs were stained for Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The bar graph on the right quantifies NET formation (I). (J) Macrophages were treated with CM-Neu, NETs (5 μg/ml), NETs (10 μg/ml), or NETs (10 μg/ml) combined with deoxyribonuclease (DNase) I ( n = 3). The expression of Il1b was determined by qPCR. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C) and 1-way ANOVA test (D, E, and G to J). 4T1-LM3, 4T1-lung metastasis 3; ANOVA, analysis of variance; Ccl11 , c-c motif chemokine ligand 11; Ccl12 , c-c motif chemokine ligand 12; Ccl17 , c-c motif chemokine ligand 17; Ccl2 , c-c motif chemokine ligand 2; Ccl22 , c-c motif chemokine ligand 22; Ccl3 , c-c motif chemokine ligand 3; Ccl4 , c-c motif chemokine ligand 4; Ccl5 , c-c motif chemokine ligand 5; Ccl6 , c-c motif chemokine ligand 6; CCL6; c-c motif ligand 6; Ccl9 , c-c motif chemokine ligand 9; CM-MΦ, macrophage-derived conditioned medium; CM-Neu, neutrophil-derived conditioned medium; Cxcl12 , c-x-c motif chemokine ligand 12; Cxcl14 , c-x-c motif chemokine ligand 14; Cxcl16 , c-x-c motif chemokine ligand 16; CXCL2, c-x-c motif chemokine ligand 2; Cxcl2 , c-x-c motif chemokine ligand 2; Cxcl3 , c-x-c motif chemokine ligand 3; Cxcl9 , c-x-c motif chemokine ligand 9; DAPI, 4’,6-diamidino-2-phenylindole; ELISA, enzyme linked immunosorbent assay; FACS, fluorescence-activated cell sorting; H3cit; citrullinated histone H3; Il12a , interleukin 12a; Il13 , interleukin 13; Il18 , interleukin, 18; Il1a , interleukin 1α; Il1b , interleukin 1β; Il-1β, interleukin-1β; Il2 ,interleukin 2; Il33 , interleukin 33; Il4 , interleukin 4; Il6 , interleukin 6; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; MPO, myeloperoxidase; NETs, neutrophil extracellular trap; NK, natural killer; NL, normal lung; Ppbp , pro-platelet basic protein; Neu, neutrophil; PRE, premetastatic lung; qRT-PCR, quantitative real-time polymerase chain reaction; rIl-1β, recombinant interleukin-1β; scRNA-seq: single-cell RNA sequencing; SD, standard deviation.
Article Snippet: To induce NET formation, primary tumors were resected on day 21 after the orthotopic injection of 4T1-LM3 cells, followed by daily intraperitoneal injections of recombinant Il-1β (rIl-1β; 8 ng per mouse, HY-P7073, MedChemExpress) until the macrometastatic stage.
Techniques: Expressing, Immunofluorescence, In Vitro, Staining, Imaging, Control, Enzyme-linked Immunosorbent Assay, Derivative Assay, Fluorescence, FACS, Quantitative RT-PCR, Real-time Polymerase Chain Reaction, Recombinant, RNA Sequencing, Standard Deviation
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![<t>Il-1β</t> <t>induces</t> Ly6g high neutrophil NETosis in the lung metastatic niche. (A) Heatmap of the scRNA-seq data showing the expression of cytokine genes at different time points during lung metastasis. (B and C) Representative immunofluorescence micrographs (B) showing NET formation by FACS-sorted Ly6g high and Ly6g low neutrophils ( n = 6) after treatment with Il-1β, Cxcl2, and Ccl6 for 6 h in vitro. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The statistical data are presented in (C). (D) Representative immunofluorescence micrographs showing NET formation at the MACRO stages of lung tissue with PBS, rIl-1β, anti-IgG, and anti-Il-1β antibody treatment, respectively [4T1-LM3 (BALB/c) model, n = 5]. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The bar graph on the right quantifies NET formation. (E) Representative bioluminescence imaging and hematoxylin and eosin (H&E) staining images at the MACRO lungs from mice treated with PBS, rIl-1β, IgG, or anti-Il-1β antibody [4T1-LM3 (BALB/c) model, n = 5]. The bar graph on the right shows the quantitative data of lung metastasis burden. (F) Violin plots showing the expression of Il1b in different cell clusters in the lung tissues based on scRNA-seq data from Fig. D. (G) Representative immunofluorescence micrographs demonstrate NET formation in sorted Ly6g high neutrophils ( n = 6). Neutrophils were treated with CM-MΦ or CM-MΦ that had been neutralized with an anti-Il-1β antibody. NETs were stained with antibodies against Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). (H and I) Mice were treated with anti-IgG control, anti-F4/80 antibody, or anti-F4/80 antibody combined with rIl-1β until the macrometastatic stage [4T1-LM3 (BALB/c) model, n = 6]. (H) Il-1β levels in the lungs were detected by ELISA. (I) Representative immunofluorescence images show NET formation. NETs were stained for Mpo (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The bar graph on the right quantifies NET formation (I). (J) Macrophages were treated with CM-Neu, NETs (5 μg/ml), NETs (10 μg/ml), or NETs (10 μg/ml) combined with deoxyribonuclease (DNase) I ( n = 3). The expression of Il1b was determined by qPCR. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C) and 1-way ANOVA test (D, E, and G to J). 4T1-LM3, 4T1-lung metastasis 3; ANOVA, analysis of variance; Ccl11 , c-c motif chemokine ligand 11; Ccl12 , c-c motif chemokine ligand 12; Ccl17 , c-c motif chemokine ligand 17; Ccl2 , c-c motif chemokine ligand 2; Ccl22 , c-c motif chemokine ligand 22; Ccl3 , c-c motif chemokine ligand 3; Ccl4 , c-c motif chemokine ligand 4; Ccl5 , c-c motif chemokine ligand 5; Ccl6 , c-c motif chemokine ligand 6; CCL6; c-c motif ligand 6; Ccl9 , c-c motif chemokine ligand 9; CM-MΦ, macrophage-derived conditioned medium; CM-Neu, neutrophil-derived conditioned medium; Cxcl12 , c-x-c motif chemokine ligand 12; Cxcl14 , c-x-c motif chemokine ligand 14; Cxcl16 , c-x-c motif chemokine ligand 16; CXCL2, c-x-c motif chemokine ligand 2; Cxcl2 , c-x-c motif chemokine ligand 2; Cxcl3 , c-x-c motif chemokine ligand 3; Cxcl9 , c-x-c motif chemokine ligand 9; DAPI, 4’,6-diamidino-2-phenylindole; ELISA, enzyme linked immunosorbent assay; FACS, fluorescence-activated cell sorting; H3cit; citrullinated histone H3; Il12a , interleukin 12a; Il13 , interleukin 13; Il18 , interleukin, 18; Il1a , interleukin 1α; Il1b , interleukin 1β; Il-1β, interleukin-1β; Il2 ,interleukin 2; Il33 , interleukin 33; Il4 , interleukin 4; Il6 , interleukin 6; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; MPO, myeloperoxidase; NETs, neutrophil extracellular trap; NK, natural killer; NL, normal lung; Ppbp , pro-platelet basic protein; Neu, neutrophil; PRE, premetastatic lung; qRT-PCR, quantitative real-time polymerase chain reaction; rIl-1β, recombinant interleukin-1β; scRNA-seq: single-cell RNA sequencing; SD, standard deviation.](https://pub-med-central-images-cdn.bioz.com/pub_med_central_ids_ending_with_7760/pmc12857760/pmc12857760__cancomm.0003.fig.004.jpg)
![Prognostic significance of NETs in human BC. (A) Representative FACS plot showing the ratio of human CD84 high and CD84 low neutrophils in healthy individuals ( n = 50) and patients with BC at different stages [stages I/II ( n = 80), stages III/IV ( n = 80)]. To define the CD84 high and CD84 low subsets in humans, we first established the positive gating threshold using FMO controls. Subsequently, the boundary between “high” and “low” subsets was determined based on a clear inflection point observed in the fluorescence intensity histogram. Statistical significance was determined by comparing with the healthy group. The bar graph on the right quantifies the ratio of human CD84 high and CD84 low neutrophils. (B) Representative immunofluorescence micrographs showing NET formation of CD84 high and CD84 low neutrophils, which were sorted by FACS after treatment with PMA for 2 h ( n = 6). NETs were stained with antibodies against MPO (red) and H3cit (green), and nuclei were counterstained with DAPI (blue). The bar graph on the right quantifies the formation of NETs. (C) Plasma NET levels in healthy individuals ( n = 50) and BC patients at different stages [stages I/II ( n = 80), stages III/IV ( n = 80)]. (D) Kaplan–Meier survival curves showing the overall survival (OS) of BC patients with low (NETs < 344.91 pg/ml; n = 83) or high (NETs ≥ 344.91 pg/ml; n = 77) concentrations of plasma NETs. BC patients were stratified into high and low NET groups using the mean plasma NET level of the entire cohort as the cutoff. (E) Receiver operator characteristic (ROC) curve analysis of plasma NET levels for predicting BC patients’ lung metastases ( n = 160). The area under the curve (AUC) value reflects the model’s power to distinguish between BC patients with and without lung metastasis within 6 years after diagnosis. Higher AUC values (approaching 1) denote superior differentiation accuracy at this time point. (F) Correlation between plasma NET levels and CD8 + T cell proportion in healthy individuals and patients with BC ( n = 210). (G) Kaplan–Meier analysis showing the recurrence-free survival of BC patients with high or low levels of LL37 ( n = 4,929). Data were obtained from the Kaplan–Meier plotter database, which does not provide detailed numerical thresholds for LL37 level classification. (H) Mechanism scheme of Ly6g high and Ly6g low neutrophils in promoting pulmonary metastasis of BC. Briefly, Ly6g high neutrophils accumulated in the premetastatic stage and induced CD8 + T cell apoptosis through NETosis. The NET-derived cathelicidin directly bound with Ant1, an mPTP protein in CD8 + T cells, leading to conformational changes in the Ant1 and subsequent Ant1–Vdac1 complex formation, which resulted in mPTP opening, loss of ΔΨm, and uncoupling of mitochondrial electron transport chain in CD8 + T cells. Ly6g low neutrophils bearing MDSC-like transcriptional signatures exhibit a superior capacity to inhibit the proliferation and effector functions of CD8 + T cells. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (A), Student’s t test (B), 1-way ANOVA test (C), and 2-sided log-rank test (D and G). 4T1-LM3, 4T1-lung metastasis 3; ANOVA, analysis of variance; APC, allophycocyanin; BC, breast cancer; CD8, cluster of differentiation 8; CD84, cluster of differentiation 84; CI, confidence interval; DAPI, 4',6-diamidino-2-phenylindole; E0771-LM3, E0771-lung metastasis 3; FACS, fluorescence-activated cell sorting; FMO, fluorescence-minus-one; H3cit, citrullinated histone H3; HR, hazard ratio; Interferon-γ, IFN-γ; Il-1β, interleukin-1β; Ly6g, lymphocyte antigen 6 complex locus g; MDSC, myeloid-derived suppressor cell; MPO, myeloperoxidase; mPTP, mitochondrial permeability transition pore; NETs, neutrophil extracellular traps; PADI4, peptidyl arginine deiminase 4; PE, phycoerythrin; PMA, phorbol 12-myristate 13-acetate; RFS, recurrence-free survival; ROS, reactive oxygen species; Vdac1, voltage-dependent anion channel 1; SD, standard deviation; ΔΨm, mitochondrial membrane potential.](https://pub-med-central-images-cdn.bioz.com/pub_med_central_ids_ending_with_7760/pmc12857760/pmc12857760__cancomm.0003.fig.007.jpg)