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anti il 1β  (Bio X Cell)


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    Bio X Cell anti il 1β
    Anti Il 1β, supplied by Bio X Cell, used in various techniques. Bioz Stars score: 96/100, based on 164 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    anti il 1β - by Bioz Stars, 2026-06
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    Bio X Cell interleukin 1β il 1β antibody
    Dynamic changes in Ly6g high and Ly6g low neutrophil subsets in the lung metastatic microenvironment. (A and B) UMAP plots showing Ly6g expression of neutrophil subsets derived from integrated data of lung tissue (A) and lung tissues at different stages of BC metastasis (B) [4T1-LM3 (BALB/c) model]. The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (C and D) Representative fluorescence-activated cell sorting (FACS) plot of Ly6g high and Ly6g low neutrophils in normal lung tissue and lung tumor tissue at different metastatic stages in breast tumor-bearing mice [4T1-LM3 (BALB/c) model: NL ( n = 6), PRE ( n = 6), MICRO ( n = 6), MACRO ( n = 7), (C); E0771-LM3 (C57BL/6) model: NL ( n = 6), PRE ( n = 5), MICRO ( n = 5), MACRO ( n = 6), (D)]. The bar graph on the right shows the quantification of the proportions of Ly6g high and Ly6g low neutrophil subsets in lung tissues during BC pulmonary metastasis. Statistical significance was determined by comparison with NL. (E) UMAP plots of neutrophils, color-coded for the expression level of genes encoding CD11b ( Itgam ), Ly6c ( Ly6c2 ), and cell surface glycoprotein F4/80 ( Adgre1 ). The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (F) Expression levels of myeloid markers in Ly6g high (top) and Ly6g low (bottom) neutrophils, including CD11b ( n = 8), Ly6c ( n = 6), and F4/80 ( n = 11). (G) Heatmap displaying the expression level of the genes related to immunosuppression based on the RNA-seq data. (H to J) As depicted in the schematic, Ly6g high and Ly6g low neutrophils were separated from the macrometastatic lung tissues [4T1-LM3 (BALB/c) model] and were respectively cocultured with naïve splenic CD8 + T cells at a ratio of 1:1 in the presence of plate-bound anti-CD3 antibody and soluble anti-CD28 antibody to facilitate T cell activation (H). T cell proliferation was quantified by flow cytometry [ n = 4, (I)]; IFN-γ was determined using intracellular staining by flow cytometry [ n = 4, (J)]. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C and D), Student’s t test (F), and 1-way ANOVA test (I and J). 4T1-LM3, 4T1-lung metastasis 3; △MFI, the difference of mean fluorescence intensity; Adgre1 , adhesion g protein-coupled receptor e1; ANOVA, analysis of variance; Arg2 , arginase 2; BC, breast cancer; CD3, cluster of differentiation 3; Cd11b , integrin subunit α m; CD11b, integrin α-m; Cd274 , cluster of differentiation cd274; CD28, cluster of differentiation 28; Cd84 , cluster of differentiation 84; Clec4d , c-type lectin domain family 4 member d; Clec4e , c-type lectin domain family 4 member e; Csf1 , colony-stimulating factor 1; Ctsd , cathepsin d, E0771-LM3, E0771-lung metastasis 3; Exp, expression; FITC, fluorescein isothiocyanate; IFN-γ, interferon-γ; Il1b , interleukin 1β; Il1f9, interleukin 1 family member 9; FPKM ,fragments per kilobase million; Itgam, integrin subunit α M; Junb , junb proto-oncogene; Ly6c, lymphocyte antigen c2; Ly6c2 , lymphocyte antigen c2; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; Neu, neutrophils; NL, normal lung; PE, phycoerythrin; Pla2g7 , phospholipase a2 group vii; PRE, premetastatic lung; Ptgs2 , prostaglandin-endoperoxide synthase 2; RNA-seq, RNA sequencing; SD, standard deviation; Stat3 , signal transducer and activator of transcription 3; UMAP, uniform manifold approximation and projection.
    Interleukin 1β Il 1β Antibody, supplied by Bio X Cell, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Santa Cruz Biotechnology resource source identifier antibodies anti il1β antibody invivolab be0246
    Dynamic changes in Ly6g high and Ly6g low neutrophil subsets in the lung metastatic microenvironment. (A and B) UMAP plots showing Ly6g expression of neutrophil subsets derived from integrated data of lung tissue (A) and lung tissues at different stages of BC metastasis (B) [4T1-LM3 (BALB/c) model]. The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (C and D) Representative fluorescence-activated cell sorting (FACS) plot of Ly6g high and Ly6g low neutrophils in normal lung tissue and lung tumor tissue at different metastatic stages in breast tumor-bearing mice [4T1-LM3 (BALB/c) model: NL ( n = 6), PRE ( n = 6), MICRO ( n = 6), MACRO ( n = 7), (C); E0771-LM3 (C57BL/6) model: NL ( n = 6), PRE ( n = 5), MICRO ( n = 5), MACRO ( n = 6), (D)]. The bar graph on the right shows the quantification of the proportions of Ly6g high and Ly6g low neutrophil subsets in lung tissues during BC pulmonary metastasis. Statistical significance was determined by comparison with NL. (E) UMAP plots of neutrophils, color-coded for the expression level of genes encoding CD11b ( Itgam ), Ly6c ( Ly6c2 ), and cell surface glycoprotein F4/80 ( Adgre1 ). The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (F) Expression levels of myeloid markers in Ly6g high (top) and Ly6g low (bottom) neutrophils, including CD11b ( n = 8), Ly6c ( n = 6), and F4/80 ( n = 11). (G) Heatmap displaying the expression level of the genes related to immunosuppression based on the RNA-seq data. (H to J) As depicted in the schematic, Ly6g high and Ly6g low neutrophils were separated from the macrometastatic lung tissues [4T1-LM3 (BALB/c) model] and were respectively cocultured with naïve splenic CD8 + T cells at a ratio of 1:1 in the presence of plate-bound anti-CD3 antibody and soluble anti-CD28 antibody to facilitate T cell activation (H). T cell proliferation was quantified by flow cytometry [ n = 4, (I)]; IFN-γ was determined using intracellular staining by flow cytometry [ n = 4, (J)]. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C and D), Student’s t test (F), and 1-way ANOVA test (I and J). 4T1-LM3, 4T1-lung metastasis 3; △MFI, the difference of mean fluorescence intensity; Adgre1 , adhesion g protein-coupled receptor e1; ANOVA, analysis of variance; Arg2 , arginase 2; BC, breast cancer; CD3, cluster of differentiation 3; Cd11b , integrin subunit α m; CD11b, integrin α-m; Cd274 , cluster of differentiation cd274; CD28, cluster of differentiation 28; Cd84 , cluster of differentiation 84; Clec4d , c-type lectin domain family 4 member d; Clec4e , c-type lectin domain family 4 member e; Csf1 , colony-stimulating factor 1; Ctsd , cathepsin d, E0771-LM3, E0771-lung metastasis 3; Exp, expression; FITC, fluorescein isothiocyanate; IFN-γ, interferon-γ; Il1b , interleukin 1β; Il1f9, interleukin 1 family member 9; FPKM ,fragments per kilobase million; Itgam, integrin subunit α M; Junb , junb proto-oncogene; Ly6c, lymphocyte antigen c2; Ly6c2 , lymphocyte antigen c2; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; Neu, neutrophils; NL, normal lung; PE, phycoerythrin; Pla2g7 , phospholipase a2 group vii; PRE, premetastatic lung; Ptgs2 , prostaglandin-endoperoxide synthase 2; RNA-seq, RNA sequencing; SD, standard deviation; Stat3 , signal transducer and activator of transcription 3; UMAP, uniform manifold approximation and projection.
    Resource Source Identifier Antibodies Anti Il1β Antibody Invivolab Be0246, supplied by Santa Cruz Biotechnology, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Bio X Cell il 1β neutralizing antibody
    <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.
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    Dynamic changes in Ly6g high and Ly6g low neutrophil subsets in the lung metastatic microenvironment. (A and B) UMAP plots showing Ly6g expression of neutrophil subsets derived from integrated data of lung tissue (A) and lung tissues at different stages of BC metastasis (B) [4T1-LM3 (BALB/c) model]. The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (C and D) Representative fluorescence-activated cell sorting (FACS) plot of Ly6g high and Ly6g low neutrophils in normal lung tissue and lung tumor tissue at different metastatic stages in breast tumor-bearing mice [4T1-LM3 (BALB/c) model: NL ( n = 6), PRE ( n = 6), MICRO ( n = 6), MACRO ( n = 7), (C); E0771-LM3 (C57BL/6) model: NL ( n = 6), PRE ( n = 5), MICRO ( n = 5), MACRO ( n = 6), (D)]. The bar graph on the right shows the quantification of the proportions of Ly6g high and Ly6g low neutrophil subsets in lung tissues during BC pulmonary metastasis. Statistical significance was determined by comparison with NL. (E) UMAP plots of neutrophils, color-coded for the expression level of genes encoding CD11b ( Itgam ), Ly6c ( Ly6c2 ), and cell surface glycoprotein F4/80 ( Adgre1 ). The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (F) Expression levels of myeloid markers in Ly6g high (top) and Ly6g low (bottom) neutrophils, including CD11b ( n = 8), Ly6c ( n = 6), and F4/80 ( n = 11). (G) Heatmap displaying the expression level of the genes related to immunosuppression based on the RNA-seq data. (H to J) As depicted in the schematic, Ly6g high and Ly6g low neutrophils were separated from the macrometastatic lung tissues [4T1-LM3 (BALB/c) model] and were respectively cocultured with naïve splenic CD8 + T cells at a ratio of 1:1 in the presence of plate-bound anti-CD3 antibody and soluble anti-CD28 antibody to facilitate T cell activation (H). T cell proliferation was quantified by flow cytometry [ n = 4, (I)]; IFN-γ was determined using intracellular staining by flow cytometry [ n = 4, (J)]. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C and D), Student’s t test (F), and 1-way ANOVA test (I and J). 4T1-LM3, 4T1-lung metastasis 3; △MFI, the difference of mean fluorescence intensity; Adgre1 , adhesion g protein-coupled receptor e1; ANOVA, analysis of variance; Arg2 , arginase 2; BC, breast cancer; CD3, cluster of differentiation 3; Cd11b , integrin subunit α m; CD11b, integrin α-m; Cd274 , cluster of differentiation cd274; CD28, cluster of differentiation 28; Cd84 , cluster of differentiation 84; Clec4d , c-type lectin domain family 4 member d; Clec4e , c-type lectin domain family 4 member e; Csf1 , colony-stimulating factor 1; Ctsd , cathepsin d, E0771-LM3, E0771-lung metastasis 3; Exp, expression; FITC, fluorescein isothiocyanate; IFN-γ, interferon-γ; Il1b , interleukin 1β; Il1f9, interleukin 1 family member 9; FPKM ,fragments per kilobase million; Itgam, integrin subunit α M; Junb , junb proto-oncogene; Ly6c, lymphocyte antigen c2; Ly6c2 , lymphocyte antigen c2; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; Neu, neutrophils; NL, normal lung; PE, phycoerythrin; Pla2g7 , phospholipase a2 group vii; PRE, premetastatic lung; Ptgs2 , prostaglandin-endoperoxide synthase 2; RNA-seq, RNA sequencing; SD, standard deviation; Stat3 , signal transducer and activator of transcription 3; UMAP, uniform manifold approximation and projection.

    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: Dynamic changes in Ly6g high and Ly6g low neutrophil subsets in the lung metastatic microenvironment. (A and B) UMAP plots showing Ly6g expression of neutrophil subsets derived from integrated data of lung tissue (A) and lung tissues at different stages of BC metastasis (B) [4T1-LM3 (BALB/c) model]. The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (C and D) Representative fluorescence-activated cell sorting (FACS) plot of Ly6g high and Ly6g low neutrophils in normal lung tissue and lung tumor tissue at different metastatic stages in breast tumor-bearing mice [4T1-LM3 (BALB/c) model: NL ( n = 6), PRE ( n = 6), MICRO ( n = 6), MACRO ( n = 7), (C); E0771-LM3 (C57BL/6) model: NL ( n = 6), PRE ( n = 5), MICRO ( n = 5), MACRO ( n = 6), (D)]. The bar graph on the right shows the quantification of the proportions of Ly6g high and Ly6g low neutrophil subsets in lung tissues during BC pulmonary metastasis. Statistical significance was determined by comparison with NL. (E) UMAP plots of neutrophils, color-coded for the expression level of genes encoding CD11b ( Itgam ), Ly6c ( Ly6c2 ), and cell surface glycoprotein F4/80 ( Adgre1 ). The dashed line separates the Ly6g low (above) and Ly6g high (below) neutrophil subsets. (F) Expression levels of myeloid markers in Ly6g high (top) and Ly6g low (bottom) neutrophils, including CD11b ( n = 8), Ly6c ( n = 6), and F4/80 ( n = 11). (G) Heatmap displaying the expression level of the genes related to immunosuppression based on the RNA-seq data. (H to J) As depicted in the schematic, Ly6g high and Ly6g low neutrophils were separated from the macrometastatic lung tissues [4T1-LM3 (BALB/c) model] and were respectively cocultured with naïve splenic CD8 + T cells at a ratio of 1:1 in the presence of plate-bound anti-CD3 antibody and soluble anti-CD28 antibody to facilitate T cell activation (H). T cell proliferation was quantified by flow cytometry [ n = 4, (I)]; IFN-γ was determined using intracellular staining by flow cytometry [ n = 4, (J)]. The data with error bars are presented as the mean ± SD; statistical significance was determined by 2-way ANOVA (C and D), Student’s t test (F), and 1-way ANOVA test (I and J). 4T1-LM3, 4T1-lung metastasis 3; △MFI, the difference of mean fluorescence intensity; Adgre1 , adhesion g protein-coupled receptor e1; ANOVA, analysis of variance; Arg2 , arginase 2; BC, breast cancer; CD3, cluster of differentiation 3; Cd11b , integrin subunit α m; CD11b, integrin α-m; Cd274 , cluster of differentiation cd274; CD28, cluster of differentiation 28; Cd84 , cluster of differentiation 84; Clec4d , c-type lectin domain family 4 member d; Clec4e , c-type lectin domain family 4 member e; Csf1 , colony-stimulating factor 1; Ctsd , cathepsin d, E0771-LM3, E0771-lung metastasis 3; Exp, expression; FITC, fluorescein isothiocyanate; IFN-γ, interferon-γ; Il1b , interleukin 1β; Il1f9, interleukin 1 family member 9; FPKM ,fragments per kilobase million; Itgam, integrin subunit α M; Junb , junb proto-oncogene; Ly6c, lymphocyte antigen c2; Ly6c2 , lymphocyte antigen c2; Ly6g, lymphocyte antigen 6 complex locus g; MACRO, macrometastatic lung; MICRO, micrometastatic lung; Neu, neutrophils; NL, normal lung; PE, phycoerythrin; Pla2g7 , phospholipase a2 group vii; PRE, premetastatic lung; Ptgs2 , prostaglandin-endoperoxide synthase 2; RNA-seq, RNA sequencing; SD, standard deviation; Stat3 , signal transducer and activator of transcription 3; UMAP, uniform manifold approximation and projection.

    Article Snippet: Primary tumors were surgically resected at week 3 post-inoculation, followed by intraperitoneal injection of either interleukin-1β (Il-1β) antibody (200 μg per mouse, BE0246, BioXCell, West Lebanon, NH, USA) or immunoglobulin G (IgG) isotype control antibody (200 μg per mouse; BE0091, BioXCell) 3 times weekly until the macrometastatic stage.

    Techniques: Expressing, Derivative Assay, Fluorescence, FACS, Comparison, RNA Sequencing, Activation Assay, Flow Cytometry, Staining, Standard Deviation

    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.

    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: Primary tumors were surgically resected at week 3 post-inoculation, followed by intraperitoneal injection of either interleukin-1β (Il-1β) antibody (200 μg per mouse, BE0246, BioXCell, West Lebanon, NH, USA) or immunoglobulin G (IgG) isotype control antibody (200 μg per mouse; BE0091, BioXCell) 3 times weekly 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

    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.

    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: 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.

    Article Snippet: Primary tumors were surgically resected at week 3 post-inoculation, followed by intraperitoneal injection of either interleukin-1β (Il-1β) antibody (200 μg per mouse, BE0246, BioXCell, West Lebanon, NH, USA) or immunoglobulin G (IgG) isotype control antibody (200 μg per mouse; BE0091, BioXCell) 3 times weekly until the macrometastatic stage.

    Techniques: Fluorescence, Immunofluorescence, Staining, Clinical Proteomics, Biomarker Discovery, Derivative Assay, FACS, Permeability, Standard Deviation, Membrane

    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.

    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: We then treated Ly6g high and Ly6g low neutrophils with this CM-MΦ, in the presence or absence of an Il-1β neutralizing antibody (5 μg/ml, BE0246, BioXCell), for 24 h. After treatment, the cells were incubated with the ROS-sensitive probe 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA; 10 μM, 50101ES01, Yeasen) at 37 °C for 20 min, washed twice with PBS, and analyzed immediately using a BD FACSCanto Plus flow cytometer.

    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

    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.

    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: 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.

    Article Snippet: We then treated Ly6g high and Ly6g low neutrophils with this CM-MΦ, in the presence or absence of an Il-1β neutralizing antibody (5 μg/ml, BE0246, BioXCell), for 24 h. After treatment, the cells were incubated with the ROS-sensitive probe 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA; 10 μM, 50101ES01, Yeasen) at 37 °C for 20 min, washed twice with PBS, and analyzed immediately using a BD FACSCanto Plus flow cytometer.

    Techniques: Fluorescence, Immunofluorescence, Staining, Clinical Proteomics, Biomarker Discovery, Derivative Assay, FACS, Permeability, Standard Deviation, Membrane