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R&D Systems cxcl9
Cxcl9, supplied by R&D Systems, used in various techniques. Bioz Stars score: 93/100, based on 15 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/recombinant+mouse+cxcl9+protein/Recombinant+Mouse+CXCL9%2FMIG+Protein/bio_rxiv__2025__11__11__687837-250-7-9
Average 93 stars, based on 15 article reviews

cxcl9 - by Bioz Stars, 2026-09

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Article Title: Cyclin G2 in macrophages triggers CTL-mediated antitumor immunity and antiangiogenesis via interferon-gamma.
Article Snippet: Cell chemotaxis assays were performed in 24-well plates using a 5-μm chamber (Corning, NY, USA). .. A total of 10 × 104 cells/well were suspended in RPMI 1640 containing 0.2% FBS in the upper chamber, and the lower chamber was filled with the conditioned medium of BMDMs from C57BL/6 mice with or without recombinant mouse CXCL9 protein (492-MM-010/CF, R&D Systems). .. The cells were cultured for 12 h in a humidified incubator at 37 °C with 5% CO2, and cells that invaded the lower surface were stained with 5 nM eBioscienceTM Calcein AM Viability Dye (Invitrogen, USA) for 15 min and detected by fluorescence microscopy.

Article Title: An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging
Article Snippet: .. Following normalization, vessels were incubated with either PBS or different concentrations of recombinant mouse CXCL9 protein (R&D systems, catalog no. 492-MM) for 3–4 h. A concentration-dependent contraction curve was created by the cumulative application of the prostaglandin agonist U46619. ..

Article Title: An Inflammatory Clock Predicts Multi-morbidity, Immunosenescence and Cardiovascular Aging in Humans
Article Snippet: .. Following normalization, the vessels were incubated with either PBS or different concentrations of recombinant mouse CXCL9 protein (R&D systems, catalog number 492-MM) for 3-4 hrs. ..

Article Title: Cyclin G2 in macrophages triggers CTL-mediated antitumor immunity and antiangiogenesis via interferon-gamma
Article Snippet: Cell chemotaxis assays were performed in 24-well plates using a 5-μm chamber (Corning, NY, USA). .. A total of 10 × 10 4 cells/well were suspended in RPMI 1640 containing 0.2% FBS in the upper chamber, and the lower chamber was filled with the conditioned medium of BMDMs from C57BL/6 mice with or without recombinant mouse CXCL9 protein (492-MM-010/CF, R&D Systems). .. The cells were cultured for 12 h in a humidified incubator at 37 °C with 5% CO 2 , and cells that invaded the lower surface were stained with 5 nM eBioscienceTM Calcein AM Viability Dye (Invitrogen, USA) for 15 min and detected by fluorescence microscopy.

Incubation:

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PD-L1 mediates the regulation of chemokine biosynthesis in M1-polarized macrophages, as determined by RNA-seq. ( A ) PD-L1 NC /THP-1-M and PD-L1 HI /THP-1-M cells were treated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 6 h and subjected to RNA sequencing analysis. The KEGG database was used to identify enriched signaling pathways whose activation significantly differed (up). Single-gene GSEA was conducted using the GSE57065 , GSE65682 , and GSE95233 datasets to identify the relationship between PD-L1 and chemokine signaling pathways (down). ( B ) Intersection analysis of upregulated genes between the PD-L1 HI /THP-1-M + LPS + IFN-γ group and PD-L1 NC /THP-1-M + LPS + IFN-γ group and between the PD-L1 NC /THP-1-M + LPS + IFN-γ group and PD-L1 NC /THP-1-M + PBS group via a Venn diagram, followed by further intersection with chemokine datasets, revealed three highly expressed PD-L1-mediated chemokines (CCL8, CXCL9, and CXCL10) under LPS + IFN-γ stimulation. ( C ) RNA sequencing analysis revealed the expression of CCL8, CXCL9 and CXCL10 upon PD-L1 overexpression. ( D ) PD-L1 NC /THP-1-M and PD-L1 HI /THP-1-M cells were treated with LPS + IFN-γ for 12 h, after which CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). ( E ) Human monocytes were induced into macrophages, transfected with scramble siRNA and PD-L1 siRNA, and then treated with LPS + IFN-γ for 12 h. CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). ( F ) PD-L1 NC /THP-1-M and PD-L1 KO /THP-1-M cells were treated with LPS + IFN-γ for 12 h, after which CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for D, E and F was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Journal: Inflammation

Article Title: Programmed death-ligand 1 (PD-L1) Modulates Chemokine Production Via the TLR4/TRAF6 Signaling Axis During LPS + IFN-γ-Induced Endotoxemia-mimicked Sepsis

doi: 10.1007/s10753-025-02394-2

Figure Lengend Snippet: PD-L1 mediates the regulation of chemokine biosynthesis in M1-polarized macrophages, as determined by RNA-seq. ( A ) PD-L1 NC /THP-1-M and PD-L1 HI /THP-1-M cells were treated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 6 h and subjected to RNA sequencing analysis. The KEGG database was used to identify enriched signaling pathways whose activation significantly differed (up). Single-gene GSEA was conducted using the GSE57065 , GSE65682 , and GSE95233 datasets to identify the relationship between PD-L1 and chemokine signaling pathways (down). ( B ) Intersection analysis of upregulated genes between the PD-L1 HI /THP-1-M + LPS + IFN-γ group and PD-L1 NC /THP-1-M + LPS + IFN-γ group and between the PD-L1 NC /THP-1-M + LPS + IFN-γ group and PD-L1 NC /THP-1-M + PBS group via a Venn diagram, followed by further intersection with chemokine datasets, revealed three highly expressed PD-L1-mediated chemokines (CCL8, CXCL9, and CXCL10) under LPS + IFN-γ stimulation. ( C ) RNA sequencing analysis revealed the expression of CCL8, CXCL9 and CXCL10 upon PD-L1 overexpression. ( D ) PD-L1 NC /THP-1-M and PD-L1 HI /THP-1-M cells were treated with LPS + IFN-γ for 12 h, after which CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). ( E ) Human monocytes were induced into macrophages, transfected with scramble siRNA and PD-L1 siRNA, and then treated with LPS + IFN-γ for 12 h. CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). ( F ) PD-L1 NC /THP-1-M and PD-L1 KO /THP-1-M cells were treated with LPS + IFN-γ for 12 h, after which CCL8 and CXCL9 mRNA and protein levels were quantified ( n = 3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for D, E and F was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Article Snippet: CCL8 and CXCL9 concentrations in cell supernatants or plasma were quantified using ELISA kits (Boster Biological Technology; Wuhan, China) with absorbance measurements at 450 nm, following the manufacturer’s protocols.

Techniques: RNA Sequencing, Protein-Protein interactions, Activation Assay, Expressing, Over Expression, Transfection

TLR4 acts as a critical upstream regulator of PD-L1 in modulating CCL8 and CXCL9 expression. ( A ) GSEA of RNA-seq data to investigate the relationship between PD-L1 expression and Toll-like receptor signaling pathway activation. ( B ) PD-L1 HI /THP-1-M and PD-L1 NC /THP-1-M cells were transfected with scramble siRNA or TLR4 siRNA, respectively, followed by 12 h of stimulation with LPS (100 ng/mL) + IFN-γ (20 ng/mL). The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for B was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Journal: Inflammation

Article Title: Programmed death-ligand 1 (PD-L1) Modulates Chemokine Production Via the TLR4/TRAF6 Signaling Axis During LPS + IFN-γ-Induced Endotoxemia-mimicked Sepsis

doi: 10.1007/s10753-025-02394-2

Figure Lengend Snippet: TLR4 acts as a critical upstream regulator of PD-L1 in modulating CCL8 and CXCL9 expression. ( A ) GSEA of RNA-seq data to investigate the relationship between PD-L1 expression and Toll-like receptor signaling pathway activation. ( B ) PD-L1 HI /THP-1-M and PD-L1 NC /THP-1-M cells were transfected with scramble siRNA or TLR4 siRNA, respectively, followed by 12 h of stimulation with LPS (100 ng/mL) + IFN-γ (20 ng/mL). The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for B was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Techniques: Expressing, RNA Sequencing, Activation Assay, Transfection

PD-L1 binds to the TLR4 downstream molecule TRAF6 to regulate CCL8 and CXCL9 expression. ( A ) Venn diagram analysis of proteins coimmunoprecipitated with PD-L1 in THP-1-M cells stimulated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 6 h via IP‒MS. After excluding proteins bound to the IgG control group, 289 PD-L1-specific interacting proteins were identified (up). Representative MS/MS spectrum showing peptide fragments of the TRAF6 protein identified in the immunoprecipitation complex (down). ( B ) THP-1-M (up) and human monocyte-derived (down) macrophages were treated with or without LPS+IFN-γ for 6 h and then harvested for Co-IP. TRAF6 protein levels were measured via Western blotting. ( C ) PD-L1 HI /THP-1-M and PD-L1 NC /THP-1-M cells were transfected with scramble siRNA or TRAF6 siRNA, respectively, followed by 12 hours of stimulation with LPS+IFN-γ. The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). ( D ) Structural models of full-length PD-L1 and TRAF6 predicted by AlphaFold (PAE plots were obtained from AlphaFold). ( E ) Molecular docking generic matching information. ( F ) A protein‒protein interaction cartoon model generated by PyMOL (left). Predicted binding sites between PD-L1 and TRAF6 (right). ( G ) PD-L1 NC /THP-1-M, PD-L1 HI /THP-1-M and PD-L1 Δ62-139 /THP-1-M cells were treated with LPS+IFN-γ for 12 h. The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for C and G was performed by one-way ANOVA with LSD test for post hoc analyses. * p <0.05.

Journal: Inflammation

Article Title: Programmed death-ligand 1 (PD-L1) Modulates Chemokine Production Via the TLR4/TRAF6 Signaling Axis During LPS + IFN-γ-Induced Endotoxemia-mimicked Sepsis

doi: 10.1007/s10753-025-02394-2

Figure Lengend Snippet: PD-L1 binds to the TLR4 downstream molecule TRAF6 to regulate CCL8 and CXCL9 expression. ( A ) Venn diagram analysis of proteins coimmunoprecipitated with PD-L1 in THP-1-M cells stimulated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 6 h via IP‒MS. After excluding proteins bound to the IgG control group, 289 PD-L1-specific interacting proteins were identified (up). Representative MS/MS spectrum showing peptide fragments of the TRAF6 protein identified in the immunoprecipitation complex (down). ( B ) THP-1-M (up) and human monocyte-derived (down) macrophages were treated with or without LPS+IFN-γ for 6 h and then harvested for Co-IP. TRAF6 protein levels were measured via Western blotting. ( C ) PD-L1 HI /THP-1-M and PD-L1 NC /THP-1-M cells were transfected with scramble siRNA or TRAF6 siRNA, respectively, followed by 12 hours of stimulation with LPS+IFN-γ. The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). ( D ) Structural models of full-length PD-L1 and TRAF6 predicted by AlphaFold (PAE plots were obtained from AlphaFold). ( E ) Molecular docking generic matching information. ( F ) A protein‒protein interaction cartoon model generated by PyMOL (left). Predicted binding sites between PD-L1 and TRAF6 (right). ( G ) PD-L1 NC /THP-1-M, PD-L1 HI /THP-1-M and PD-L1 Δ62-139 /THP-1-M cells were treated with LPS+IFN-γ for 12 h. The supernatants and cells were harvested for concurrent measurements of CCL8 and CXCL9 protein and mRNA levels via ELISAs and qRT‒PCR ( n =3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for C and G was performed by one-way ANOVA with LSD test for post hoc analyses. * p <0.05.

Techniques: Expressing, Control, Tandem Mass Spectroscopy, Immunoprecipitation, Derivative Assay, Co-Immunoprecipitation Assay, Western Blot, Transfection, Generated, Binding Assay

PD-L1 knockout attenuates septic mouse mortality and suppresses CCL8 and CXCL9 expression. ( A – C ) PD-L1 WT /mice and PD-L1 KO /mice were intraperitoneally injected with LPS (15 mg/kg) and IFN-γ (10 µg/kg) to induce endotoxemia-induced sepsis. ( B ) The survival rate was determined over a 60-hour observation period and is presented as a Kaplan‒Meier survival curve ( n = 15 mice per group). The results are presented as Kaplan–Meier survival curves. The results of the statistical analysis were analyzed with the log-rank test. * p < 0.05. ( C ) Peripheral blood was collected 12 h posttreatment for serum isolation and PBMC separation. CCL8 and CXCL9 protein levels in serum and their corresponding mRNA levels in PBMCs were subsequently analyzed ( n = 3 independent biological replicates). ( D ) Peritoneal macrophages (PMs) were extracted from PD-L1 wild-type and knockout mice and then treated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 12 h. The cells were harvested for CCL8 and CXCL9 mRNA and protein detection by qRT‒PCR and ELISAs ( n = 3 independent biological replicates). (E) Peripheral blood monocytes were extracted from PD-L1 wild-type and knockout mice and then treated with LPS + IFN-γ for 12 h. The cells were harvested for CCL8 and CXCL9 mRNA and protein detection by qRT‒PCR and ELISAs ( n = 3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for C was performed by Student’s t test, and that for D and E was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Journal: Inflammation

Article Title: Programmed death-ligand 1 (PD-L1) Modulates Chemokine Production Via the TLR4/TRAF6 Signaling Axis During LPS + IFN-γ-Induced Endotoxemia-mimicked Sepsis

doi: 10.1007/s10753-025-02394-2

Figure Lengend Snippet: PD-L1 knockout attenuates septic mouse mortality and suppresses CCL8 and CXCL9 expression. ( A – C ) PD-L1 WT /mice and PD-L1 KO /mice were intraperitoneally injected with LPS (15 mg/kg) and IFN-γ (10 µg/kg) to induce endotoxemia-induced sepsis. ( B ) The survival rate was determined over a 60-hour observation period and is presented as a Kaplan‒Meier survival curve ( n = 15 mice per group). The results are presented as Kaplan–Meier survival curves. The results of the statistical analysis were analyzed with the log-rank test. * p < 0.05. ( C ) Peripheral blood was collected 12 h posttreatment for serum isolation and PBMC separation. CCL8 and CXCL9 protein levels in serum and their corresponding mRNA levels in PBMCs were subsequently analyzed ( n = 3 independent biological replicates). ( D ) Peritoneal macrophages (PMs) were extracted from PD-L1 wild-type and knockout mice and then treated with LPS (100 ng/mL) + IFN-γ (20 ng/mL) for 12 h. The cells were harvested for CCL8 and CXCL9 mRNA and protein detection by qRT‒PCR and ELISAs ( n = 3 independent biological replicates). (E) Peripheral blood monocytes were extracted from PD-L1 wild-type and knockout mice and then treated with LPS + IFN-γ for 12 h. The cells were harvested for CCL8 and CXCL9 mRNA and protein detection by qRT‒PCR and ELISAs ( n = 3 independent biological replicates). The data are presented as the mean ± SEM. Statistical analysis for C was performed by Student’s t test, and that for D and E was performed by one-way ANOVA with LSD test for post hoc analyses. * p < 0.05

Techniques: Knock-Out, Expressing, Injection, Isolation

Representative flow cytometry contour plots of PD-1 x CXCR5 expression within CD25-CD4+ T cells isolated from NCD (left) and HFD (right) mouse spleen (top) and liver (bottom) ( A ). Blue gates represent PD-1 HI CXCR5+ cells, yellow gates represent PD-1 HI CXCR5-cells, and black gates represent PD-1-cells ( A ). Frequency and absolute number of PD-1 HI CXCR5+ T FH cells ( B , blue), or PD-1 HI CXCR5-T PH cells ( C , yellow) within the CD25-CD4+ T cell compartments of spleen (top) and liver (bottom) of NCD (grey) and HFD (blue/yellow) mice. Quantification of Bcl-6 ( D ), ICOS ( E ), and T-bet ( F ) protein expression (gMFI) in splenic (left) or hepatic (right) CD25-CD4+ T cell subsets. Representative flow cytometry contour plots depicting relative expression of IL-21 and IFNg by PD-1 HI CXCR5+ T FH cells or PD-1 HI CXCR5-T PH cells from spleen (top) or liver (bottom) that are also CXCR3+ (blue/red) or CXCR3-(black) ( G ). Summary of frequency of IL-21 ( H,J; left) or IFNg ( I,K ; right) producing CD4+ PD-1 HI CXCR5+ T FH (blue) or PD-1 HI CXCR5-T PH (red) cells categorized by CXCR3+ expression as noted in spleen ( H, I ) or liver ( J,K ) from HFD-fed mice. Data pooled from 2 independent experiments with 4 female mice/group, Bar ± SEM; [ Student’s t-test (two-tailed) (B,C); one-way ANOVA (D-F; H-K)]; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Journal: bioRxiv

Article Title: CD11c+ Tbet+ B cells constrain obesity- and vaccination-induced germinal center B cells and T helper cells

doi: 10.1101/2025.09.01.673552

Figure Lengend Snippet: Representative flow cytometry contour plots of PD-1 x CXCR5 expression within CD25-CD4+ T cells isolated from NCD (left) and HFD (right) mouse spleen (top) and liver (bottom) ( A ). Blue gates represent PD-1 HI CXCR5+ cells, yellow gates represent PD-1 HI CXCR5-cells, and black gates represent PD-1-cells ( A ). Frequency and absolute number of PD-1 HI CXCR5+ T FH cells ( B , blue), or PD-1 HI CXCR5-T PH cells ( C , yellow) within the CD25-CD4+ T cell compartments of spleen (top) and liver (bottom) of NCD (grey) and HFD (blue/yellow) mice. Quantification of Bcl-6 ( D ), ICOS ( E ), and T-bet ( F ) protein expression (gMFI) in splenic (left) or hepatic (right) CD25-CD4+ T cell subsets. Representative flow cytometry contour plots depicting relative expression of IL-21 and IFNg by PD-1 HI CXCR5+ T FH cells or PD-1 HI CXCR5-T PH cells from spleen (top) or liver (bottom) that are also CXCR3+ (blue/red) or CXCR3-(black) ( G ). Summary of frequency of IL-21 ( H,J; left) or IFNg ( I,K ; right) producing CD4+ PD-1 HI CXCR5+ T FH (blue) or PD-1 HI CXCR5-T PH (red) cells categorized by CXCR3+ expression as noted in spleen ( H, I ) or liver ( J,K ) from HFD-fed mice. Data pooled from 2 independent experiments with 4 female mice/group, Bar ± SEM; [ Student’s t-test (two-tailed) (B,C); one-way ANOVA (D-F; H-K)]; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Article Snippet: C57BL/6J WT female mice were injected IP with 0.25 mg of anti-mouse CXCR3 (CD183) and anti-mouse CXCL9 (MIG) or hamster IgG (BioXCell) every other day for 14 days after completing 12 weeks on HFD.

Techniques: Flow Cytometry, Expressing, Isolation, Two Tailed Test

CXCL9- and CXCR3-neutralizing antibodies abolish the anti-tumor effect of DB by reducing TILs . ( A ) Growth curves of B16-OVA melanoma treated with DB or vehicle (every 2 days) in combination with neutralizing antibodies for CXCL9 (αCXCL9, every 3 days), CXCR3 (αCXCR3, every 4 days), control IgG (every 4 days). ( B ) Relative frequencies of immune cells (CD45 + ), CD4 or CD8 T cells (CD45 + /CD3 + , CD4 + or CD8 + ), and NK cells (CD45 + /CD3 − /NK1.1 + ). Macrophages (CD45 + /CD11b + /F4/80 + ) were included for comparison. ( C , D ) Immunohistochemical staining of CD8 and Granzyme B (GrzB) in tumors using the specified treatments. Tumor tissues were stained with CD8 − and GrzB-specific antibodies, followed by incubation with HRP-conjugated secondary antibodies. HRP signals were detected using the DAB substrate kit, as described in Materials and Methods. The corresponding quantification data are presented in the right panels of ( C , D ); CD8 immunohistochemistry (IHC) is quantified as cells per field of view (cells/FOV), and Granzyme B (GrzB) IHC is quantified by the optical density of DAB staining. Statistical significance was assessed using a one-way ANOVA followed by Tukey’s multiple comparisons test. p < 0.05. Sample sizes: n = 5–6 for panel ( A ); n = 3–4 for other panels.

Journal: Cancers

Article Title: Inhibition of the Transcription Factor PU.1 Suppresses Tumor Growth in Mice by Promoting the Recruitment of Cytotoxic Lymphocytes Through the CXCL9-CXCR3 Axis

doi: 10.3390/cancers17162684

Figure Lengend Snippet: CXCL9- and CXCR3-neutralizing antibodies abolish the anti-tumor effect of DB by reducing TILs . ( A ) Growth curves of B16-OVA melanoma treated with DB or vehicle (every 2 days) in combination with neutralizing antibodies for CXCL9 (αCXCL9, every 3 days), CXCR3 (αCXCR3, every 4 days), control IgG (every 4 days). ( B ) Relative frequencies of immune cells (CD45 + ), CD4 or CD8 T cells (CD45 + /CD3 + , CD4 + or CD8 + ), and NK cells (CD45 + /CD3 − /NK1.1 + ). Macrophages (CD45 + /CD11b + /F4/80 + ) were included for comparison. ( C , D ) Immunohistochemical staining of CD8 and Granzyme B (GrzB) in tumors using the specified treatments. Tumor tissues were stained with CD8 − and GrzB-specific antibodies, followed by incubation with HRP-conjugated secondary antibodies. HRP signals were detected using the DAB substrate kit, as described in Materials and Methods. The corresponding quantification data are presented in the right panels of ( C , D ); CD8 immunohistochemistry (IHC) is quantified as cells per field of view (cells/FOV), and Granzyme B (GrzB) IHC is quantified by the optical density of DAB staining. Statistical significance was assessed using a one-way ANOVA followed by Tukey’s multiple comparisons test. p < 0.05. Sample sizes: n = 5–6 for panel ( A ); n = 3–4 for other panels.

Article Snippet: InVivoMAb, rat IgG2a isotype control, anti-mouse CXCR3 (CD183), anti-mouse CXCL9 (MIG), and polyclonal Armenian hamster IgG isotype control antibodies were purchased from Bio X Cell (Lebanon, NH, USA).

Techniques: Control, Comparison, Immunohistochemical staining, Staining, Incubation, Immunohistochemistry

The CXCL9-CXCR3 axis is responsible for DB-induced transcriptional changes in tumors. B16−OVA tumors under the same treatments described in A were harvested on day 13 for mRNA sequencing. Transcript counts were analyzed by GSEA and were visualized using the Cytoscape program. Enriched GO nodes (dots) and leading edge (grouped in circles with key functional annotation) are presented in pair-wise comparisons (up-regulation in red, down-regulation in blue), including DB + IgG vs. Vehicle + IgG ( A ), Vehicle + αCXCR3 vs. Vehicle + IgG ( B ), DB + αCXCR3 vs. DB + IgG ( C ), DB + αCXCR3 vs. Vehicle + IgG ( D ).

Journal: Cancers

Article Title: Inhibition of the Transcription Factor PU.1 Suppresses Tumor Growth in Mice by Promoting the Recruitment of Cytotoxic Lymphocytes Through the CXCL9-CXCR3 Axis

doi: 10.3390/cancers17162684

Figure Lengend Snippet: The CXCL9-CXCR3 axis is responsible for DB-induced transcriptional changes in tumors. B16−OVA tumors under the same treatments described in A were harvested on day 13 for mRNA sequencing. Transcript counts were analyzed by GSEA and were visualized using the Cytoscape program. Enriched GO nodes (dots) and leading edge (grouped in circles with key functional annotation) are presented in pair-wise comparisons (up-regulation in red, down-regulation in blue), including DB + IgG vs. Vehicle + IgG ( A ), Vehicle + αCXCR3 vs. Vehicle + IgG ( B ), DB + αCXCR3 vs. DB + IgG ( C ), DB + αCXCR3 vs. Vehicle + IgG ( D ).

Techniques: Sequencing, Functional Assay

Macrophage enrichment by CXCL9 enhances fibrosis and portal hypertension after pIVCL. ( A ) RNA ish reveals increased expression of CXCL9 in LSECs 6 weeks after pIVCL ( right ). The zoomed-in inset shows CXCL9 expression in a LSEC after pIVCL. In contrast, CXCL9 is absent in LSECs 6 weeks after the sham operation ( left ). Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the panel to the right of the images. CXCL9 is shown in red , the endothelial marker Lyve-1 is shown in green , and blue represents DAPI nuclear counterstain. The scale bar represents 20 microns. A t -test was used to obtain the P value; n = 6–7 ( P < .001). ( B ) Circulating CXCL9 levels are significantly increased in mice 6 weeks after pIVCL compared with 6 weeks after sham surgeries ( P < .05). A paired t -test was used to obtain the P value; n = 7. ( C ) Mice treated with AMG487 have significantly decreased portal pressures 6 weeks after pIVCL and sham surgeries when compared with DMSO-treated mice (n = 5–7 per group; ANOVA P < .05). ( D ) Sirius red staining and quantification of liver tissue after sham and IVC ligation procedures. Images are 10× magnification. Scale bar represents 200 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels). ( E ) IHC staining for CD68 of liver tissue after sham and IVC ligation procedures. Images are 20× magnification. Scale bar represents 50 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels).

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: Macrophage enrichment by CXCL9 enhances fibrosis and portal hypertension after pIVCL. ( A ) RNA ish reveals increased expression of CXCL9 in LSECs 6 weeks after pIVCL ( right ). The zoomed-in inset shows CXCL9 expression in a LSEC after pIVCL. In contrast, CXCL9 is absent in LSECs 6 weeks after the sham operation ( left ). Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the panel to the right of the images. CXCL9 is shown in red , the endothelial marker Lyve-1 is shown in green , and blue represents DAPI nuclear counterstain. The scale bar represents 20 microns. A t -test was used to obtain the P value; n = 6–7 ( P < .001). ( B ) Circulating CXCL9 levels are significantly increased in mice 6 weeks after pIVCL compared with 6 weeks after sham surgeries ( P < .05). A paired t -test was used to obtain the P value; n = 7. ( C ) Mice treated with AMG487 have significantly decreased portal pressures 6 weeks after pIVCL and sham surgeries when compared with DMSO-treated mice (n = 5–7 per group; ANOVA P < .05). ( D ) Sirius red staining and quantification of liver tissue after sham and IVC ligation procedures. Images are 10× magnification. Scale bar represents 200 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels). ( E ) IHC staining for CD68 of liver tissue after sham and IVC ligation procedures. Images are 20× magnification. Scale bar represents 50 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels).

Article Snippet: We therefore treated mice with a neutralizing antibody to CXCL9 (BioXCell) to confirm the role of CXCL9-recruited macrophages in the pathophysiology of congestive fibrosis and PHTN.

Techniques: Expressing, Fluorescence, Marker, Staining, Ligation, Immunohistochemistry

Hepatic congestion leads to increased CXCL9 expression in peri-central LSECs. ( A ) RNA ish was performed on liver biopsies obtained from patients with FALD ( right ) and HCs ( left ). LSECs express CXCL9 in patients with FALD but not in HCs. Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the panel to the right of the images. CXCL9 is shown in red , the endothelial marker Lyve-1 is shown in green , and blue represents DAPI nuclear counterstain. The scale bar represents 50 microns. A t -test was used to obtain the P value; n = 7. ( B ) Circulating CXCL9 levels are significantly increased in patients with FALD compared with age- and gender-matched healthy controls ( P < .05). A paired t -test was used to obtain the P value; n = 7.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: Hepatic congestion leads to increased CXCL9 expression in peri-central LSECs. ( A ) RNA ish was performed on liver biopsies obtained from patients with FALD ( right ) and HCs ( left ). LSECs express CXCL9 in patients with FALD but not in HCs. Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the panel to the right of the images. CXCL9 is shown in red , the endothelial marker Lyve-1 is shown in green , and blue represents DAPI nuclear counterstain. The scale bar represents 50 microns. A t -test was used to obtain the P value; n = 7. ( B ) Circulating CXCL9 levels are significantly increased in patients with FALD compared with age- and gender-matched healthy controls ( P < .05). A paired t -test was used to obtain the P value; n = 7.

Techniques: Expressing, Fluorescence, Marker

CXCL9-recruited macrophages contribute to fibrosis and portal hypertension after pIVCL. ( A ) Mice treated with a neutralizing antibody to CXCL9 have significantly decreased portal pressures 6 weeks after pIVCL and sham surgeries when compared with control-treated mice (n = 5–8 per group; ANOVA P < .05). ( B ) qPCR from whole-liver mRNA shows lower mRNA levels of α-SMA after pIVCL in mice treated with a neutralizing antibody to CXCL9 compared with mice treated with control (ANOVA P < .05). ( C ) Sirius red staining and quantification of liver tissue after sham and IVC ligation procedures. Images are 10× magnification. Scale bar represents 200 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels). ( D ) IHC staining for CD68 of liver tissue after sham and IVC ligation procedures. Images are 20× magnification. Scale bar represents 50 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels).

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: CXCL9-recruited macrophages contribute to fibrosis and portal hypertension after pIVCL. ( A ) Mice treated with a neutralizing antibody to CXCL9 have significantly decreased portal pressures 6 weeks after pIVCL and sham surgeries when compared with control-treated mice (n = 5–8 per group; ANOVA P < .05). ( B ) qPCR from whole-liver mRNA shows lower mRNA levels of α-SMA after pIVCL in mice treated with a neutralizing antibody to CXCL9 compared with mice treated with control (ANOVA P < .05). ( C ) Sirius red staining and quantification of liver tissue after sham and IVC ligation procedures. Images are 10× magnification. Scale bar represents 200 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels). ( D ) IHC staining for CD68 of liver tissue after sham and IVC ligation procedures. Images are 20× magnification. Scale bar represents 50 microns. Quantification was performed with ImageJ (National Institutes of Health) and displayed in the adjacent graph (n = 5–7; ∗ P ≤ .05 for all panels).

Techniques: Control, Staining, Ligation, Immunohistochemistry

Pathways regulating the inflammatory response are upregulated in peri-central LSECs after pIVCL. ( A ) Enrichr analysis reveals upregulation of cells and molecules involved in the local acute inflammatory response in peri-central LSECs. Pathways are sorted by P -value ranking. ( B ) Expression of CXCL9 is highest in peri-central LSECs compared with other LSEC subpopulations in our scRNA sequencing dataset. ( C ) Feature plot demonstrating that LSECs are the primary source of CXCL9 within the liver. ( D ) RNAish reveals increased CXCL9 in biopsies collected from patients with FALD ( bottom row ) compared with HCs ( top row ). CXCL9 colocalizes with Cd117, which is a marker of peri-central LSECs. CXCL9 also colocalizes with β-catenin. Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the bottom left panel . Colocalization of CXCL9 and Cd117 fluorescence was quantified by ImageJ and compared via Pearson’s coefficient ( bottom right panel ). Cd117 is shown in green , CXCL9 is shown in red , and β-catenin is shown in teal . A DAPI nuclear counterstain was performed. The scale bar represents 50 microns. A paired t -test was used to obtain the P value; n = 6–7; ∗ P < .05.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: Pathways regulating the inflammatory response are upregulated in peri-central LSECs after pIVCL. ( A ) Enrichr analysis reveals upregulation of cells and molecules involved in the local acute inflammatory response in peri-central LSECs. Pathways are sorted by P -value ranking. ( B ) Expression of CXCL9 is highest in peri-central LSECs compared with other LSEC subpopulations in our scRNA sequencing dataset. ( C ) Feature plot demonstrating that LSECs are the primary source of CXCL9 within the liver. ( D ) RNAish reveals increased CXCL9 in biopsies collected from patients with FALD ( bottom row ) compared with HCs ( top row ). CXCL9 colocalizes with Cd117, which is a marker of peri-central LSECs. CXCL9 also colocalizes with β-catenin. Intensity of CXCL9 fluorescence was quantified by ImageJ (National Institutes of Health) and displayed in the bottom left panel . Colocalization of CXCL9 and Cd117 fluorescence was quantified by ImageJ and compared via Pearson’s coefficient ( bottom right panel ). Cd117 is shown in green , CXCL9 is shown in red , and β-catenin is shown in teal . A DAPI nuclear counterstain was performed. The scale bar represents 50 microns. A paired t -test was used to obtain the P value; n = 6–7; ∗ P < .05.

Techniques: Expressing, Sequencing, Marker, Fluorescence

Expression of CXCL9 and CXCR3 after pIVCL. ( A ) Violin plot demonstrating differential expression of CXCL9 in LSECs (clusters 1 and 6) after pIVCL. ( B ) Violin plot demonstrating expression of CXCR3 after pIVCL. CXCR3 expression is mainly localized to clusters 5 (T cells) and 17 (dendritic cells) in this scRNA-seq dataset. These data corroborate other publicly available datasets, which demonstrates robust expression of CXCR3 protein with low CXCR3 mRNA expression in macrophages. This is likely due to low mRNA expression of surface marker proteins.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: Expression of CXCL9 and CXCR3 after pIVCL. ( A ) Violin plot demonstrating differential expression of CXCL9 in LSECs (clusters 1 and 6) after pIVCL. ( B ) Violin plot demonstrating expression of CXCR3 after pIVCL. CXCR3 expression is mainly localized to clusters 5 (T cells) and 17 (dendritic cells) in this scRNA-seq dataset. These data corroborate other publicly available datasets, which demonstrates robust expression of CXCR3 protein with low CXCR3 mRNA expression in macrophages. This is likely due to low mRNA expression of surface marker proteins.

Techniques: Expressing, Quantitative Proteomics, Marker

HIF-1 α and β-catenin drive LSEC zonation in CH. ( A ) Ingenuity Pathway Analysis of upstream transcriptional regulators of CXCL9 with an activation Z-score >2.0 suggests that β-catenin and HIF-1 α regulate CXCL9 transcription. ( B ) Treatment of LSECs with the hypoxia-mimetic agent DMOG increases CXCL9 mRNA levels. A t -test was used to obtain the P value; n = 3. ( C ) Transfection of LSECs with the pcDNA3-S33Y β-catenin mutant plasmid (Addgene plasmid #19286) leads to upregulation of CXCL9 mRNA levels at varying concentrations (ANOVA P < .05). ( D ) pcDNA3-S33Y-transfected LSECs that were treated with DMOG demonstrated further increases in CXCL9 mRNA expression compared with pcDNA-S33Y-transfected LSECs treated with a vehicle agent (Veh) (ANOVA P < .05). n = 3–4.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: HIF-1 α and β-catenin drive LSEC zonation in CH. ( A ) Ingenuity Pathway Analysis of upstream transcriptional regulators of CXCL9 with an activation Z-score >2.0 suggests that β-catenin and HIF-1 α regulate CXCL9 transcription. ( B ) Treatment of LSECs with the hypoxia-mimetic agent DMOG increases CXCL9 mRNA levels. A t -test was used to obtain the P value; n = 3. ( C ) Transfection of LSECs with the pcDNA3-S33Y β-catenin mutant plasmid (Addgene plasmid #19286) leads to upregulation of CXCL9 mRNA levels at varying concentrations (ANOVA P < .05). ( D ) pcDNA3-S33Y-transfected LSECs that were treated with DMOG demonstrated further increases in CXCL9 mRNA expression compared with pcDNA-S33Y-transfected LSECs treated with a vehicle agent (Veh) (ANOVA P < .05). n = 3–4.

Techniques: Activation Assay, Transfection, Mutagenesis, Plasmid Preparation, Expressing

HIF1- α regulates CXCL9 transcription. Transfection of LSECs with siRNA to HIF1- α decreases CXCL9 mRNA levels after 48 hours. A t -test was used to obtain the P value; n = 3; ∗ P < .05.

Journal: Cellular and Molecular Gastroenterology and Hepatology

Article Title: Congestion Enriches Intra-hepatic Macrophages Through Reverse Zonation of CXCL9 in Liver Sinusoidal Endothelial Cells

doi: 10.1016/j.jcmgh.2025.101475

Figure Lengend Snippet: HIF1- α regulates CXCL9 transcription. Transfection of LSECs with siRNA to HIF1- α decreases CXCL9 mRNA levels after 48 hours. A t -test was used to obtain the P value; n = 3; ∗ P < .05.

Techniques: Transfection

Myeloid cells communicate with IrColitis-enriched T cells via the CXCL9/CXCL10-CXCR3 Axis. (A) Cell communication between CD4 + T cell subpopulations and other major cell types. (B) Strength of incoming cell communication signals received by CD4 + T cell subpopulations and other major cell types. (C, D) Interaction of CD4 + T cell subpopulations with other major cell types via CXCL signaling and the roles of each cell type in CXCL signaling. (E) Receptor-ligand pairs contributing to CXCL signaling. (F) CXCL9/10-CXCR3 signaling communication between CD4 + T cell subsets and other major cell types. (G, H) CXCL9/10-CXCR3 signaling communication between CD4 + T cell subsets ( G ) or CD8 + T cell subsets ( H ) and other major cell types in the no-irColitis (left) and irColitis (right) groups. (I) Dot plot showing the expression levels of CXCL9 and CXCL10 in myeloid cells across groups. (J) Dot plot showing the expression levels of CXCR3 in CD4 + T cells (left) and CD8 + T cells (right) across groups. (K) Dot plot showing CXCR3 expression levels in CD4 + (left) and CD8 + (right) T cell subsets. (L, M) Single-cell spatial transcriptomics data from 10 x Visium ( L ) or NanoString CosMx ( M ) showing CXCL9, CXCL10, and CXCR3 positive cells in the no-irColitis and irColitis groups. (N–P) Expression levels of Cxcl9 ( N ), Cxcl10 ( O ), and Cxcr3 ( P ) in intestinal tissue from control and irColitis mice. (Q) Flow cytometry analysis of CXCR3 expression in CD4 + T cells from intestinal tissue of control and irColitis mice. (R) Flow cytometry analysis of CXCR3 expression in IFN-γ + IL-17 + CD4 + T cells and other T cells in the intestinal tissue of irColitis mice. (group 1: B cell, group 2: CD8 + T cell, group 3: Epithelial cell, group 4: IFNG + IL17 + effector, group 5: Memory, group 6: Myeloid cell, group 7: Naïve/Stemness, group 8: Resident memory, group 9: TCF7+Exhausted, group 10: Th1 like effector, group 11: Treg, group 12: IL7R + Resident Memory, group 13: GZMK + Effector, group 14: GZMB + GZMK + Effector, group 15: Exhausted, group 16: Central Memory, group 17: CD160 + Memory, group 18: NK). *p<0.05; **p<0.01; ***p<0.001. irColitis, immune-related colitis; UC, ulcerative colitis.

Journal: Journal for Immunotherapy of Cancer

Article Title: Single-cell multiomics reveals macrophage-derived IL-23 and CXCL9/10 drive pathogenic IFNG+IL17+ T cells in immunotherapy-related colitis

doi: 10.1136/jitc-2025-011959

Figure Lengend Snippet: Myeloid cells communicate with IrColitis-enriched T cells via the CXCL9/CXCL10-CXCR3 Axis. (A) Cell communication between CD4 + T cell subpopulations and other major cell types. (B) Strength of incoming cell communication signals received by CD4 + T cell subpopulations and other major cell types. (C, D) Interaction of CD4 + T cell subpopulations with other major cell types via CXCL signaling and the roles of each cell type in CXCL signaling. (E) Receptor-ligand pairs contributing to CXCL signaling. (F) CXCL9/10-CXCR3 signaling communication between CD4 + T cell subsets and other major cell types. (G, H) CXCL9/10-CXCR3 signaling communication between CD4 + T cell subsets ( G ) or CD8 + T cell subsets ( H ) and other major cell types in the no-irColitis (left) and irColitis (right) groups. (I) Dot plot showing the expression levels of CXCL9 and CXCL10 in myeloid cells across groups. (J) Dot plot showing the expression levels of CXCR3 in CD4 + T cells (left) and CD8 + T cells (right) across groups. (K) Dot plot showing CXCR3 expression levels in CD4 + (left) and CD8 + (right) T cell subsets. (L, M) Single-cell spatial transcriptomics data from 10 x Visium ( L ) or NanoString CosMx ( M ) showing CXCL9, CXCL10, and CXCR3 positive cells in the no-irColitis and irColitis groups. (N–P) Expression levels of Cxcl9 ( N ), Cxcl10 ( O ), and Cxcr3 ( P ) in intestinal tissue from control and irColitis mice. (Q) Flow cytometry analysis of CXCR3 expression in CD4 + T cells from intestinal tissue of control and irColitis mice. (R) Flow cytometry analysis of CXCR3 expression in IFN-γ + IL-17 + CD4 + T cells and other T cells in the intestinal tissue of irColitis mice. (group 1: B cell, group 2: CD8 + T cell, group 3: Epithelial cell, group 4: IFNG + IL17 + effector, group 5: Memory, group 6: Myeloid cell, group 7: Naïve/Stemness, group 8: Resident memory, group 9: TCF7+Exhausted, group 10: Th1 like effector, group 11: Treg, group 12: IL7R + Resident Memory, group 13: GZMK + Effector, group 14: GZMB + GZMK + Effector, group 15: Exhausted, group 16: Central Memory, group 17: CD160 + Memory, group 18: NK). *p<0.05; **p<0.01; ***p<0.001. irColitis, immune-related colitis; UC, ulcerative colitis.

Article Snippet: Mice were treated i.p. with 100 μg/mouse of anti-mouse CXCR3 mAb (clone CXCR3-173, BioXCell) or a combination of anti-mouse CXCL9 (clone MIG-2F5.5, BioXCell) and anti-mouse CXCL10 (clone 134013, Invitrogen) mAbs, administered on day 3 and day 9.

Techniques: Expressing, Control, Flow Cytometry

IL-23 synergizes with CXCL9/10 to promote IFNG + IL17 + CD4 + T cells and immune-related colitis. (A) Schematic diagram of CXCL9/10 or CXCR3 neutralizing antibody treatment in mouse irColitis. (B) Disease Activity Index (DAI) of mouse irColitis. (C) Representative colonoscopy images of mice in different treatment groups. (D) Flow cytometry analysis of the proportion of CD3ε + T cells in intestinal tissues across treatment groups. (E) Flow cytometry analysis of the proportion of IFN-γ + IL-17 + T cells within CD4 + T cells in intestinal tissues. (F, G) Quantification of the proportion of IFN-γ + T cells ( F ) and IL-17 + T cells ( G ) within CD4 + T cells across treatment groups. (H) Quantification of the proportion of Ki67 + T cells within IL-17 + CD4 + T cells across treatment groups. (I) Quantification of IL-17 + T cells within CD4 + T cells in different treatment groups. (J) Quantification of Ki67 + T cells within IL-17 + CD4 + T cells across treatment groups. (K) Flow cytometry analysis of the proportion and number of IL-17 + T cells within Th17 cells. (L) CFSE staining analysis of Th17 cells across treatment groups. (M) Quantification of Ki67 + T cells within Th17 cells across treatment groups. (N) Flow cytometry analysis of the proportion and number of IFN-γ + IL-17 + T cells within the Th17 cells. (O) Quantification of IFN-γ + T cells within CD4 + T cells across treatment groups. (P) Schematic diagram of combination treatment with anti-CXCR3 and anti-IL-23 antibodies in mouse irColitis. (Q, R) Quantification of IFN-γ + IL-17 + T cells ( Q ) and IL-17 + T cells ( R ) within CD4 + T cells across treatment groups. (S) Disease Activity Index (DAI) in irColitis mice. (T) Schematic diagram illustrating the synergistic induction of IFN-γ + IL-17 + T cells by IL-23 and CXCL9/10. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. ICB, immune checkpoint blockade; irColitis, immune-related colitis.

Journal: Journal for Immunotherapy of Cancer

Article Title: Single-cell multiomics reveals macrophage-derived IL-23 and CXCL9/10 drive pathogenic IFNG+IL17+ T cells in immunotherapy-related colitis

doi: 10.1136/jitc-2025-011959

Figure Lengend Snippet: IL-23 synergizes with CXCL9/10 to promote IFNG + IL17 + CD4 + T cells and immune-related colitis. (A) Schematic diagram of CXCL9/10 or CXCR3 neutralizing antibody treatment in mouse irColitis. (B) Disease Activity Index (DAI) of mouse irColitis. (C) Representative colonoscopy images of mice in different treatment groups. (D) Flow cytometry analysis of the proportion of CD3ε + T cells in intestinal tissues across treatment groups. (E) Flow cytometry analysis of the proportion of IFN-γ + IL-17 + T cells within CD4 + T cells in intestinal tissues. (F, G) Quantification of the proportion of IFN-γ + T cells ( F ) and IL-17 + T cells ( G ) within CD4 + T cells across treatment groups. (H) Quantification of the proportion of Ki67 + T cells within IL-17 + CD4 + T cells across treatment groups. (I) Quantification of IL-17 + T cells within CD4 + T cells in different treatment groups. (J) Quantification of Ki67 + T cells within IL-17 + CD4 + T cells across treatment groups. (K) Flow cytometry analysis of the proportion and number of IL-17 + T cells within Th17 cells. (L) CFSE staining analysis of Th17 cells across treatment groups. (M) Quantification of Ki67 + T cells within Th17 cells across treatment groups. (N) Flow cytometry analysis of the proportion and number of IFN-γ + IL-17 + T cells within the Th17 cells. (O) Quantification of IFN-γ + T cells within CD4 + T cells across treatment groups. (P) Schematic diagram of combination treatment with anti-CXCR3 and anti-IL-23 antibodies in mouse irColitis. (Q, R) Quantification of IFN-γ + IL-17 + T cells ( Q ) and IL-17 + T cells ( R ) within CD4 + T cells across treatment groups. (S) Disease Activity Index (DAI) in irColitis mice. (T) Schematic diagram illustrating the synergistic induction of IFN-γ + IL-17 + T cells by IL-23 and CXCL9/10. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. ICB, immune checkpoint blockade; irColitis, immune-related colitis.

Techniques: Activity Assay, Flow Cytometry, Staining

Reprogrammed macrophages promote IFNG + IL17 + CD4 + T cells and IrColitis. (A) UMAP visualization of myeloid cell subpopulations. (B) Communication of CXCL9/10-CXCR3 signaling between CD4 + T cell subpopulations and myeloid cell subpopulations as well as other major cell types. (group 1: B cell, group 2: CD8 + T cell, group 3: DC, group 4: Epithelial cell, group 5: IFNG + IL17 + effector, group 6: Macrophage, group 7: Memory, group 8: Monocyte, group 9: Naïve/Stemness, group 10: Resident memory, group 11: TCF7 + Exhausted, group 12: Th1 like effector, group 13: Treg). (C) Dot plot showing the expression of CXCL9 and CXCL10 in myeloid cells across different groups (left) and in different myeloid cell subpopulations (right). (D) Dot plot illustrating marker gene annotations for myeloid cell subpopulations. (E) Stacked bar plot showing the percentage (left) and the cell count (right) of different myeloid cell subpopulations across different groups. (F) Box plot depicting the differences in the proportions of myeloid cell subpopulations between the Normal and IrColitis groups. (G) CytoTRACE showing the differentiation levels of macrophage 1 and macrophage 2. (H) Comparison of metabolic levels in macrophages between the No-Colitis and IrColitis groups, and between macrophage 1 and macrophage 2. (I) Schematic diagram of Clodronate treatment in mouse irColitis. (J) Disease Activity Index (DAI) of mouse irColitis. (K) qPCR analysis of Cxcl9 and Cxcl10 expression in intestinal tissues of different treatment groups. (L) Flow cytometry analysis of the proportion of IFN-γ + IL-17 + T cells in CD4 + T cells in intestinal tissues of different treatment groups. (M) qPCR analysis of Il23a expression in intestinal tissues of different treatment groups. (N) Dot plot showing the expression of IL23A and IL23R in different cell types. (O) NanoString CosMx Single-cell spatial transcriptomics data showing CD3D, IL23A, and CD14 positive cells in the irColitis. (P, Q) Flow cytometry analysis of the proportion of IL-23 + cells in different cell types on day 5 and day 15. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. FMT, fecal microbiota transplantation; ICB, immune checkpoint blockade; irColitis, immune-related colitis; UMAP, uniform manifold approximation and projection.

Journal: Journal for Immunotherapy of Cancer

Article Title: Single-cell multiomics reveals macrophage-derived IL-23 and CXCL9/10 drive pathogenic IFNG+IL17+ T cells in immunotherapy-related colitis

doi: 10.1136/jitc-2025-011959

Figure Lengend Snippet: Reprogrammed macrophages promote IFNG + IL17 + CD4 + T cells and IrColitis. (A) UMAP visualization of myeloid cell subpopulations. (B) Communication of CXCL9/10-CXCR3 signaling between CD4 + T cell subpopulations and myeloid cell subpopulations as well as other major cell types. (group 1: B cell, group 2: CD8 + T cell, group 3: DC, group 4: Epithelial cell, group 5: IFNG + IL17 + effector, group 6: Macrophage, group 7: Memory, group 8: Monocyte, group 9: Naïve/Stemness, group 10: Resident memory, group 11: TCF7 + Exhausted, group 12: Th1 like effector, group 13: Treg). (C) Dot plot showing the expression of CXCL9 and CXCL10 in myeloid cells across different groups (left) and in different myeloid cell subpopulations (right). (D) Dot plot illustrating marker gene annotations for myeloid cell subpopulations. (E) Stacked bar plot showing the percentage (left) and the cell count (right) of different myeloid cell subpopulations across different groups. (F) Box plot depicting the differences in the proportions of myeloid cell subpopulations between the Normal and IrColitis groups. (G) CytoTRACE showing the differentiation levels of macrophage 1 and macrophage 2. (H) Comparison of metabolic levels in macrophages between the No-Colitis and IrColitis groups, and between macrophage 1 and macrophage 2. (I) Schematic diagram of Clodronate treatment in mouse irColitis. (J) Disease Activity Index (DAI) of mouse irColitis. (K) qPCR analysis of Cxcl9 and Cxcl10 expression in intestinal tissues of different treatment groups. (L) Flow cytometry analysis of the proportion of IFN-γ + IL-17 + T cells in CD4 + T cells in intestinal tissues of different treatment groups. (M) qPCR analysis of Il23a expression in intestinal tissues of different treatment groups. (N) Dot plot showing the expression of IL23A and IL23R in different cell types. (O) NanoString CosMx Single-cell spatial transcriptomics data showing CD3D, IL23A, and CD14 positive cells in the irColitis. (P, Q) Flow cytometry analysis of the proportion of IL-23 + cells in different cell types on day 5 and day 15. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. FMT, fecal microbiota transplantation; ICB, immune checkpoint blockade; irColitis, immune-related colitis; UMAP, uniform manifold approximation and projection.

Techniques: Expressing, Marker, Cell Counting, Comparison, Activity Assay, Flow Cytometry, Transplantation Assay

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