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Cell Signaling Technology Inc phospho stat5
Phospho Stat5, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 335 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/anti+rabbit+stat5/Phospho-Stat5+(Tyr694)+XP+Rabbit+mAb/pmc13049607-338-59-61
Average 96 stars, based on 335 article reviews

phospho stat5 - by Bioz Stars, 2026-10

96/100 stars

Images

Ubiquitin Proteomics:

Article Title: Discovery of a dual-acting inhibitor of interleukin-1β and STATs for the treatment of inflammatory bowel disease.
Article Snippet: The proteins were transferred to the PVDF membrane, blocked with 5% non-fat milk in TBST for 1 h, incubated with primary antibodies overnight at 4 °C and with secondary antibodies for 1 h, and finally developed with the ECL western blot detection reagent (ThermoFisher Scientific, USA). .. The primary antibodies mentioned above were anti-mouse IL-1β (AF-401-NA, R&D Systems), anti-mouse caspase-1 (AG-20B0042, Adipogen), antirabbit NLRP3 (15100S, Cell Signaling Technology), antimouse ASC (67824S, Cell Signaling Technology), anti-mouse β-actin (P30002, Abmart, China), anti-mouse ubiquitin (3936T, Cell Signaling Technology), anti-mouse Stat3 (9139, Cell Signaling Technology), anti-rabbit pStat3 (9145, Cell Signaling Technology), anti-rabbit Stat1 (14994, Cell Signaling Technology), anti-rabbit pStat1 (9167, Cell Signaling Technology), anti-rabbit Stat5 (25656, Cell Signaling Technology), and anti-rabbit pStat5 (4322, Cell Signaling Technology). .. The secondary HRP-conjugated antibodies used were HRP conjugated anti-rabbit lgG (W4011, Promega), HRP-conjugated anti-mouse lgG (W4021, Promega), and conjugated donkey anti goat IgG (V8051, Promega).

SDS Page:

Article Title: HSP27 is a partner of JAK2-STAT5 and a potential therapeutic target in myelofibrosis
Article Snippet: .. After boiling, the immunoprecipitates were resolved in 8-12% SDS-PAGE and immunoblots were performed using an anti-rabbit STAT5 (#9363, Cell Signalling technologies). ..

Article Title: HSP27 is a partner of JAK2-STAT5 and a potential therapeutic target in myelofibrosis
Article Snippet: .. After boiling, the immunoprecipitates were resolved in 10% SDS-PAGE and immunoblots were performed using an anti-rabbit STAT5, JAK2 (clone D2O6Y, #9363 and clone D2E12, #3230, Cell Signalling technologies) or HSP27 antibody (polyclonal, SPA-803, Enzo Life Sciences). ..

Western Blot:

Article Title: HSP27 is a partner of JAK2-STAT5 and a potential therapeutic target in myelofibrosis
Article Snippet: .. After boiling, the immunoprecipitates were resolved in 10% SDS-PAGE and immunoblots were performed using an anti-rabbit STAT5, JAK2 (clone D2O6Y, #9363 and clone D2E12, #3230, Cell Signalling technologies) or HSP27 antibody (polyclonal, SPA-803, Enzo Life Sciences). ..

Article Title: HSP27 is a partner of JAK2-STAT5 and a potential therapeutic target in myelofibrosis.
Article Snippet: .. After boiling, the immunoprecipitates were resolved in 8-12% SDSPAGE and immunoblots were performed using an anti-rabbit STAT5 (#9363, Cell Signalling technologies). ..

Incubation:

Article Title: Dynamic Regulation of GH–IGF1 Signaling in Injury and Recovery in Hyperoxia-Induced Neonatal Lung Injury
Article Snippet: .. Blots were incubated with the following antibodies: anti-rabbit pSTAT5 (#4322, 1:1000, Cell Signaling, Danvers, MA, USA), anti-rabbit STAT5 (#94205, 1:2000, Cell Signaling, Danvers, MA, USA), anti-rabbit pAKT (#4058, 1:1000, Cell Signaling, Danvers, MA, USA), anti-rabbit AKT (#9272, 1:2000, Cell Signaling, Danvers, MA, USA), anti-rabbit growth hormone receptor (GH-R) (#NBP1-95983, 1:1000, Novus Biologicals, Littleton, CO, USA), anti-rabbit insulin-like growth factor receptor 1 (IGF1-R) (#3027, 1:1000, Cell Signaling, Danvers, MA, USA), anti-mouse proliferating cell nuclear antigen (PCNA) (#M0879, Aligent Dako, Santa Clara, CA, USA), anti-mouse aquaporin 5 (AQP5) (#A4979, 1:2000, Sigma-Aldrich, St. Louis, MO, USA), and anti-mouse surfactant protein C (SFTPC) (#AP3786, 1:2000, Millipore, Burlington, MA, USA), with anti-mouse β-actin (#3700, 1:5000, Cell Signaling, Danvers, MA, USA) serving as the loading control. .. Anti-mouse IgG, HRP-linked (#7076, Cell Signaling, Danvers, MA, USA) and anti-rabbit IgG, HRP-linked (#7074, Cell Signaling, Danvers, MA, USA) were used as secondary antibodies.

Control:

Image Search Results

Attenuated IL-2/STAT5 signaling and an enhanced exhaustion phenotype in CD8 + T cells within SMARCA4-deficient tumors (A) Schematic of the workflow for transcriptomic profiling of CD8 + T cells. (B) Volcano plot displaying differentially expressed genes in CD8 + T cells from SMARCA4-KD versus WT tumors. (C–E) Pathway enrichment analyses of genes downregulated in CD8 + T cells from SMARCA4-KD tumors, including Gene Ontology (GO) terms, KEGG pathways, and Reactome pathways. (F) The gene set enrichment analysis (GSEA) plot. (G) Correlation matrix (pie chart) showing the association between IL-2 receptor subunits expression and key T cell exhaustion marker genes in tumor-infiltrating CD8 + T cells. (H) Radar plot comparing the normalized expression levels of genes encoding IL-2 receptor subunits and exhaustion markers in CD8 + T cells. (I) Quantification by flow cytometry of the expression frequencies of PD-1, TIGIT, and TIM-3 on tumor-infiltrating CD8 + T cells. (J and K) Representative multiplex immunofluorescence (mIF) images of SMARCA4-WT and -KD tumor sections stained for PanCK (cyan), CD8 (green), GZMB (white), PD-1 (red), TIGIT (orange), and TIM-3 (yellow). Scale bars, 20 μm. Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Journal: Cell Reports Medicine

Article Title: Dual PD-1/IL-2Rα targeting restores CD8 + T cell fitness via STAT5/CD47 axis in SMARCA4-deficient NSCLC

doi: 10.1016/j.xcrm.2026.102633

Figure Lengend Snippet: Attenuated IL-2/STAT5 signaling and an enhanced exhaustion phenotype in CD8 + T cells within SMARCA4-deficient tumors (A) Schematic of the workflow for transcriptomic profiling of CD8 + T cells. (B) Volcano plot displaying differentially expressed genes in CD8 + T cells from SMARCA4-KD versus WT tumors. (C–E) Pathway enrichment analyses of genes downregulated in CD8 + T cells from SMARCA4-KD tumors, including Gene Ontology (GO) terms, KEGG pathways, and Reactome pathways. (F) The gene set enrichment analysis (GSEA) plot. (G) Correlation matrix (pie chart) showing the association between IL-2 receptor subunits expression and key T cell exhaustion marker genes in tumor-infiltrating CD8 + T cells. (H) Radar plot comparing the normalized expression levels of genes encoding IL-2 receptor subunits and exhaustion markers in CD8 + T cells. (I) Quantification by flow cytometry of the expression frequencies of PD-1, TIGIT, and TIM-3 on tumor-infiltrating CD8 + T cells. (J and K) Representative multiplex immunofluorescence (mIF) images of SMARCA4-WT and -KD tumor sections stained for PanCK (cyan), CD8 (green), GZMB (white), PD-1 (red), TIGIT (orange), and TIM-3 (yellow). Scale bars, 20 μm. Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Article Snippet: Stat5 (D2O6Y) Rabbit mAb , Cell Signaling Technology , Cat#94205; RRID: AB_2737403.

Techniques: Expressing, Marker, Flow Cytometry, Multiplex Assay, Immunofluorescence, Staining

SMARCA4 loss in tumor cells attenuates CD8 + T cell function via NF-κB-mediated suppression of ICAM1 (A) Flow cytometry analysis of surface expression of the exhaustion markers PD-1, TIGIT, and TIM-3 on human CD8 + T cells following co-culture. (B and C) Representative flow cytometry plots showing the production of IFN-γ and TNF-α and the surface expression of IL-2Rα (CD25) by CD8 + T cells following co-culture. (D) Quantification of the frequencies of IFN-γ + , TNF-α + , and IL-2Rα + cells among co-cultured CD8 + T cells. (E) Integrated single-nucleus RNA sequencing (snRNA-seq) analysis comparing IL2-STAT5 signaling activity. y axis: IL2-STAT5 signaling score. (F and G) Incoming and outgoing signaling patterns between major cell types in the TME, as inferred from snRNA-seq. (H) Specific cell-cell communication network illustrating the ICAM signaling pathway from tumor cells to CD8 + T cells in patients with SMARCA4-WT NSCLC. (I) Correlation analysis between SMARCA4 and ICAM1 mRNA expression in TCGA cohorts. (J) Immunohistochemistry staining and quantification of ICAM1 protein expression in tumor tissues from SMARCA4-WT ( n = 10) and -deficient ( n = 10) NSCLC patients. (K) Schematic illustrating the proposed link between SMARCA4 deficiency and impaired NF-κB activation. (L) Immunoblot analysis of ICAM1 and p65 protein levels in SMARCA4-WT H2122 cells treated with the NF-κB inhibitor PTDC or vehicle control. (M) ChIP-qPCR analysis showing NF-κB (p65) binding to a specific site within the ICAM1 promoter in SMARCA4-WT H2122 cells ( n = 3). (N) Dual-luciferase reporter assay in SMARCA4-WT H2122 cells ( n = 3). Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Journal: Cell Reports Medicine

Article Title: Dual PD-1/IL-2Rα targeting restores CD8 + T cell fitness via STAT5/CD47 axis in SMARCA4-deficient NSCLC

doi: 10.1016/j.xcrm.2026.102633

Figure Lengend Snippet: SMARCA4 loss in tumor cells attenuates CD8 + T cell function via NF-κB-mediated suppression of ICAM1 (A) Flow cytometry analysis of surface expression of the exhaustion markers PD-1, TIGIT, and TIM-3 on human CD8 + T cells following co-culture. (B and C) Representative flow cytometry plots showing the production of IFN-γ and TNF-α and the surface expression of IL-2Rα (CD25) by CD8 + T cells following co-culture. (D) Quantification of the frequencies of IFN-γ + , TNF-α + , and IL-2Rα + cells among co-cultured CD8 + T cells. (E) Integrated single-nucleus RNA sequencing (snRNA-seq) analysis comparing IL2-STAT5 signaling activity. y axis: IL2-STAT5 signaling score. (F and G) Incoming and outgoing signaling patterns between major cell types in the TME, as inferred from snRNA-seq. (H) Specific cell-cell communication network illustrating the ICAM signaling pathway from tumor cells to CD8 + T cells in patients with SMARCA4-WT NSCLC. (I) Correlation analysis between SMARCA4 and ICAM1 mRNA expression in TCGA cohorts. (J) Immunohistochemistry staining and quantification of ICAM1 protein expression in tumor tissues from SMARCA4-WT ( n = 10) and -deficient ( n = 10) NSCLC patients. (K) Schematic illustrating the proposed link between SMARCA4 deficiency and impaired NF-κB activation. (L) Immunoblot analysis of ICAM1 and p65 protein levels in SMARCA4-WT H2122 cells treated with the NF-κB inhibitor PTDC or vehicle control. (M) ChIP-qPCR analysis showing NF-κB (p65) binding to a specific site within the ICAM1 promoter in SMARCA4-WT H2122 cells ( n = 3). (N) Dual-luciferase reporter assay in SMARCA4-WT H2122 cells ( n = 3). Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Article Snippet: Stat5 (D2O6Y) Rabbit mAb , Cell Signaling Technology , Cat#94205; RRID: AB_2737403.

Techniques: Cell Function Assay, Flow Cytometry, Expressing, Co-Culture Assay, Cell Culture, RNA Sequencing, Activity Assay, Immunohistochemistry, Staining, Activation Assay, Western Blot, Control, ChIP-qPCR, Binding Assay, Luciferase, Reporter Assay

STAT5 activation mediates the therapeutic effect of the PD-1/IL-2 bsAb in SMARCA4-deficient NSCLC (A) Representative flow cytometry plots showing the expression of the exhaustion markers PD-1, TIGIT, and TIM-3 on activated human CD8 + T cells. (B) Quantification of the mean fluorescence intensity (MFI) of the exhaustion markers PD-1, TIGIT, and TIM-3 on CD8 + T cells from the experiment in (A) ( n = 3). (C) Representative flow cytometry plots showing the production of IFN-γ and TNF-α by CD8 + T cells under the conditions described in (A). (D) Quantification of the frequencies of IFN-γ + and TNF-α + cells among CD8 + T cells ( n = 3). (E) Schematic of the adoptive T cell transfer experiment ( n = 8/group). (F) Representative in vivo bioluminescence images of mice from the indicated groups at different time points. (G) Tumor growth curves, as measured by bioluminescence, for mice in each treatment group. (H) Kaplan-Meier survival curves of mice from the four treatment groups. (I) Quantification of the frequency of donor-derived CD45.2 + CD8 + T cells among total tumor-infiltrating lymphocytes. (J) Flow analysis of donor-derived CD45.2 + CD8 + T cells expressing PD-1, TIGIT, and TIM-3. (K–M) Frequency of IFN-γ + (K–L) and TNF-α + (M) cells among donor-derived CD45.2 + CD8 + T cells. Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA or two-way ANOVA where appropriate.

Journal: Cell Reports Medicine

Article Title: Dual PD-1/IL-2Rα targeting restores CD8 + T cell fitness via STAT5/CD47 axis in SMARCA4-deficient NSCLC

doi: 10.1016/j.xcrm.2026.102633

Figure Lengend Snippet: STAT5 activation mediates the therapeutic effect of the PD-1/IL-2 bsAb in SMARCA4-deficient NSCLC (A) Representative flow cytometry plots showing the expression of the exhaustion markers PD-1, TIGIT, and TIM-3 on activated human CD8 + T cells. (B) Quantification of the mean fluorescence intensity (MFI) of the exhaustion markers PD-1, TIGIT, and TIM-3 on CD8 + T cells from the experiment in (A) ( n = 3). (C) Representative flow cytometry plots showing the production of IFN-γ and TNF-α by CD8 + T cells under the conditions described in (A). (D) Quantification of the frequencies of IFN-γ + and TNF-α + cells among CD8 + T cells ( n = 3). (E) Schematic of the adoptive T cell transfer experiment ( n = 8/group). (F) Representative in vivo bioluminescence images of mice from the indicated groups at different time points. (G) Tumor growth curves, as measured by bioluminescence, for mice in each treatment group. (H) Kaplan-Meier survival curves of mice from the four treatment groups. (I) Quantification of the frequency of donor-derived CD45.2 + CD8 + T cells among total tumor-infiltrating lymphocytes. (J) Flow analysis of donor-derived CD45.2 + CD8 + T cells expressing PD-1, TIGIT, and TIM-3. (K–M) Frequency of IFN-γ + (K–L) and TNF-α + (M) cells among donor-derived CD45.2 + CD8 + T cells. Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA or two-way ANOVA where appropriate.

Article Snippet: Stat5 (D2O6Y) Rabbit mAb , Cell Signaling Technology , Cat#94205; RRID: AB_2737403.

Techniques: Activation Assay, Flow Cytometry, Expressing, Fluorescence, In Vivo, Derivative Assay

PD-1/IL-2 bsAb protects CD8 + T cells from macrophage phagocytosis via STAT5-mediated upregulation of CD47 (A) Schematic of the Cleavage Under Targets and Tagmentation (CUT&Tag) assays workflow. (B) Distribution of STAT5 binding signals relative to transcription start sites (TSS) in CD8 + T cells treated with or without the PD-1/IL-2 bsAb. (C) Genomic annotation of differentially enriched STAT5 binding peaks in the bsAb-treated group. (D) KEGG pathway enrichment analysis of genes associated with STAT5 binding peaks. (E and F) Strategy and Venn diagram for identifying potential STAT5 downstream genes. (G) ChIP-qPCR analysis of STAT5 binding to the promoter regions of selected candidate genes ( n = 3). (H) Genome browser tracks showing STAT5 binding signals at the CD47 locus in control and PD-1/IL-2 bsAb-treated CD8 + T cells. (I) Schematic of the macrophage phagocytosis assay. (J) Representative confocal microscopy images showing macrophages (red) engulfing CD8 + T cells (green). Scale bars, 20 μm. (K) Flow cytometry quantification of the percentage of macrophages that had phagocytosed CD8 + T cells under the indicated conditions ( n = 3). Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Journal: Cell Reports Medicine

Article Title: Dual PD-1/IL-2Rα targeting restores CD8 + T cell fitness via STAT5/CD47 axis in SMARCA4-deficient NSCLC

doi: 10.1016/j.xcrm.2026.102633

Figure Lengend Snippet: PD-1/IL-2 bsAb protects CD8 + T cells from macrophage phagocytosis via STAT5-mediated upregulation of CD47 (A) Schematic of the Cleavage Under Targets and Tagmentation (CUT&Tag) assays workflow. (B) Distribution of STAT5 binding signals relative to transcription start sites (TSS) in CD8 + T cells treated with or without the PD-1/IL-2 bsAb. (C) Genomic annotation of differentially enriched STAT5 binding peaks in the bsAb-treated group. (D) KEGG pathway enrichment analysis of genes associated with STAT5 binding peaks. (E and F) Strategy and Venn diagram for identifying potential STAT5 downstream genes. (G) ChIP-qPCR analysis of STAT5 binding to the promoter regions of selected candidate genes ( n = 3). (H) Genome browser tracks showing STAT5 binding signals at the CD47 locus in control and PD-1/IL-2 bsAb-treated CD8 + T cells. (I) Schematic of the macrophage phagocytosis assay. (J) Representative confocal microscopy images showing macrophages (red) engulfing CD8 + T cells (green). Scale bars, 20 μm. (K) Flow cytometry quantification of the percentage of macrophages that had phagocytosed CD8 + T cells under the indicated conditions ( n = 3). Data are represented as mean ± SD (error bars) from biological replicates. Statistical analyses, n.s., no significance. Statistical significance was determined by unpaired Student’s t test or one-way ANOVA where appropriate.

Article Snippet: Stat5 (D2O6Y) Rabbit mAb , Cell Signaling Technology , Cat#94205; RRID: AB_2737403.

Techniques: Binding Assay, ChIP-qPCR, Control, Phagocytosis Assay, Confocal Microscopy, Flow Cytometry

Efficacy of IQDMA in the C57BL/6 intradermal T-cell lymphoma model. (A) Treatment schema and tumor response in C57BL/6 mice treated with IQDMA. Mice were prepared and injected with EL4 cells, followed by daily IQDMA or vehicle injections. Tumor growth was tracked over time, revealing a lower growth rate in the IQDMA group than in the control, as depicted in the inset plot. (B) The plot shows tumor volume over time, with the blue line representing the control group and the red line depicting the IQDMA-treated group. Error bars indicate mean ± SEM (Vehicle n = 7 ; IQDMA n = 8 ), demonstrating the variability within each group and the therapeutic effect of IQDMA on tumor growth suppression. (C) Body weight changes in mice throughout the study. The graph compares the average body weight of mice in the control group (blue line)to those in the IQDMA-treated group (red line). (D) H&E staining visualizes the overall tumor architecture. (E) CD3 staining highlights T-cell infiltration. (F) Ki67 staining marks proliferative cells. (G–I) Expression of STAT3, STAT5, and phosphorylated STAT5 (pY-STAT5) (black arrowheads). (J–L) Correlation analyses between Ki67 + , STAT3 + , and STAT5 + cells/mm 2 (Two-tailed Spearman correlation analysis with 95% confidence interval, P > 0.05). Scale bars: 500 μ m (D, H&E overview), 50 μ m (E–I, IHC panels).

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: Efficacy of IQDMA in the C57BL/6 intradermal T-cell lymphoma model. (A) Treatment schema and tumor response in C57BL/6 mice treated with IQDMA. Mice were prepared and injected with EL4 cells, followed by daily IQDMA or vehicle injections. Tumor growth was tracked over time, revealing a lower growth rate in the IQDMA group than in the control, as depicted in the inset plot. (B) The plot shows tumor volume over time, with the blue line representing the control group and the red line depicting the IQDMA-treated group. Error bars indicate mean ± SEM (Vehicle n = 7 ; IQDMA n = 8 ), demonstrating the variability within each group and the therapeutic effect of IQDMA on tumor growth suppression. (C) Body weight changes in mice throughout the study. The graph compares the average body weight of mice in the control group (blue line)to those in the IQDMA-treated group (red line). (D) H&E staining visualizes the overall tumor architecture. (E) CD3 staining highlights T-cell infiltration. (F) Ki67 staining marks proliferative cells. (G–I) Expression of STAT3, STAT5, and phosphorylated STAT5 (pY-STAT5) (black arrowheads). (J–L) Correlation analyses between Ki67 + , STAT3 + , and STAT5 + cells/mm 2 (Two-tailed Spearman correlation analysis with 95% confidence interval, P > 0.05). Scale bars: 500 μ m (D, H&E overview), 50 μ m (E–I, IHC panels).

Article Snippet: The following primary antibodies were used: CD3 (Rabbit monoclonal; #RM9107-S0, Thermo Fisher Scientific, USA), a marker for T-cell infiltration; Ki67 (#KI67-MM1-L-CE, Leica Biosystems), a marker for cell proliferation; STAT3 (Clone 9D8; #MA1-13042, Thermo Fisher Scientific), which plays a role in tumor-associated inflammation and proliferation; STAT5A (Clone E289; #ab32043, Abcam, UK) and STAT5B (#ab235934, Abcam), markers involved in JAK-STAT signaling associated with immune response and cell survival; and pY-STAT5 (Phospho-Tyr694/699; #9359, Cell Signaling Technology, USA), a phosphorylated form of STAT5 indicative of activation.

Techniques: Injection, Control, Staining, Expressing, Two Tailed Test

Immunohistochemical analysis of STAT3 and STAT5 in tumor tissues from the vehicle and IQDMA-treated groups. (A, B) Representative images of vehicle and IQDMA-treated tumors. H&E staining shows differences in tumor cell infiltration and density. (C) Quantification of tumor cell infiltration area with a significant reduction observed in the IQDMA group. (D, E) Representative images of Ki67 staining of the vehicle and IQDMA-treated tumors. (F) Quantification of Ki67 + cells. (G, H) Representative images of STAT3 expression in vehicle and IQDMA-treated tumors. (I) Quantification of STAT3 + cells/mm 2 , showing a significant decrease post-IQDMA treatment ( P = 0.01). (J, K) Representative images of total STAT5 expression in vehicle and IQDMA-treated tumors. (L) Quantification of total number of STAT5 + cells/mm 2 indicates a trend toward decreased expression with IQDMA treatment. Scale bars: 500 μ m ( (A, B) , H&E overview), 50 μ m [ (D, E, G, H, J, K) , IHC panels]. *P < 0.05 vs. vehicle control (unpaired t-test).

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: Immunohistochemical analysis of STAT3 and STAT5 in tumor tissues from the vehicle and IQDMA-treated groups. (A, B) Representative images of vehicle and IQDMA-treated tumors. H&E staining shows differences in tumor cell infiltration and density. (C) Quantification of tumor cell infiltration area with a significant reduction observed in the IQDMA group. (D, E) Representative images of Ki67 staining of the vehicle and IQDMA-treated tumors. (F) Quantification of Ki67 + cells. (G, H) Representative images of STAT3 expression in vehicle and IQDMA-treated tumors. (I) Quantification of STAT3 + cells/mm 2 , showing a significant decrease post-IQDMA treatment ( P = 0.01). (J, K) Representative images of total STAT5 expression in vehicle and IQDMA-treated tumors. (L) Quantification of total number of STAT5 + cells/mm 2 indicates a trend toward decreased expression with IQDMA treatment. Scale bars: 500 μ m ( (A, B) , H&E overview), 50 μ m [ (D, E, G, H, J, K) , IHC panels]. *P < 0.05 vs. vehicle control (unpaired t-test).

Techniques: Immunohistochemical staining, Staining, Expressing, Control

Localization and quantification of phosphorylated STAT5 (pY-STAT5) in vehicle vs. IQDMA-treated cells. (A, B) Immunohistochemical staining of pY-STAT5, showing nuclear and cytoplasmic ( A , black arrowheads) and only cytoplasmic localization ( B , black arrowheads). (C, D) Correlation between total number of STAT5 + and pY-STAT5 + cells/mm 2 , with the vehicle group showing positive correlation ( r = +0.57, P = 0.15) and IQDMA group showing negative correlation ( r = − 0.74, P = 0.046). (E, F) The negative correlation between the number of Ki67 + cells/mm 2 and pY-STAT5 + cells/mm 2 is more pronounced in the IQDMA group ( r = − 0.71, P = 0.058) (Two-tailed Spearman correlation analysis with 95% confidence interval). Scale bars: 20 μ m [ (A, B) , high-magnification pY-STAT5 panels].

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: Localization and quantification of phosphorylated STAT5 (pY-STAT5) in vehicle vs. IQDMA-treated cells. (A, B) Immunohistochemical staining of pY-STAT5, showing nuclear and cytoplasmic ( A , black arrowheads) and only cytoplasmic localization ( B , black arrowheads). (C, D) Correlation between total number of STAT5 + and pY-STAT5 + cells/mm 2 , with the vehicle group showing positive correlation ( r = +0.57, P = 0.15) and IQDMA group showing negative correlation ( r = − 0.74, P = 0.046). (E, F) The negative correlation between the number of Ki67 + cells/mm 2 and pY-STAT5 + cells/mm 2 is more pronounced in the IQDMA group ( r = − 0.71, P = 0.058) (Two-tailed Spearman correlation analysis with 95% confidence interval). Scale bars: 20 μ m [ (A, B) , high-magnification pY-STAT5 panels].

Techniques: Immunohistochemical staining, Staining, Two Tailed Test

IQDMA-induced pathway response heatmaps and GSEA analysis. Pathway-specific protein expression changes following IQDMA treatment. (A) JAK/STAT Pathway Response to IQDMA showing z-score normalized expression of JAK/STAT pathway proteins across treatment conditions. (B) PAK/Rho Pathway Response to IQDMA displaying expression changes in PAK family members and associated Rho-GTPase signaling components. (C) Apoptosis Pathway Response to IQDMA showing expression of pro-apoptotic and anti-apoptotic regulators. (D) Cell Cycle Pathway Response to IQDMA (Complete Pathway Panel) displaying expression changes in cyclins, CDKs, and cell cycle inhibitors. Notable finding: CCND2 (Cyclin D2), a known STAT3/STAT5 target gene, shows strong dose-dependent downregulation (log2FC = − 2.86 at 10 μ M). (E) GSEA: Hallmark Gene Sets (IQDMA 10 μ M vs Vehicle) showing enrichment of Hallmark pathways with normalized enrichment scores (NES). Significant pathways highlighted. (F) Leading Edge Analysis: Key Pathway Genes showing the top contributing genes from leading edge analysis for JAK/STAT, Cell Cycle, Apoptosis, and Ribosome pathways (4 sub-panels).

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: IQDMA-induced pathway response heatmaps and GSEA analysis. Pathway-specific protein expression changes following IQDMA treatment. (A) JAK/STAT Pathway Response to IQDMA showing z-score normalized expression of JAK/STAT pathway proteins across treatment conditions. (B) PAK/Rho Pathway Response to IQDMA displaying expression changes in PAK family members and associated Rho-GTPase signaling components. (C) Apoptosis Pathway Response to IQDMA showing expression of pro-apoptotic and anti-apoptotic regulators. (D) Cell Cycle Pathway Response to IQDMA (Complete Pathway Panel) displaying expression changes in cyclins, CDKs, and cell cycle inhibitors. Notable finding: CCND2 (Cyclin D2), a known STAT3/STAT5 target gene, shows strong dose-dependent downregulation (log2FC = − 2.86 at 10 μ M). (E) GSEA: Hallmark Gene Sets (IQDMA 10 μ M vs Vehicle) showing enrichment of Hallmark pathways with normalized enrichment scores (NES). Significant pathways highlighted. (F) Leading Edge Analysis: Key Pathway Genes showing the top contributing genes from leading edge analysis for JAK/STAT, Cell Cycle, Apoptosis, and Ribosome pathways (4 sub-panels).

Techniques: Expressing

STAT and pathway target gene expression analysis. Expression profiling of transcription factor targets and pathway-associated proteins. (A) STAT3 Target Gene Expression showing dose-response of established STAT3 transcriptional targets across IQDMA concentrations. (B) STAT5 Target Gene Expression showing dose-response of established STAT5A/B transcriptional targets. (C) PAK Pathway Expression (Expression-based, No Phosphoproteomics) displaying proteins associated with PAK signaling. (D) CTCL-Associated Protein Expression showing expression changes in proteins with established roles in CTCL pathogenesis. (E) Transcription Factor Expression Changes (* = FDR< 0.05) displaying effect sizes for key transcription factors. (F) Kinase Expression Levels (Expression-based, * = FDR< 0.05, Orange = Priority) showing kinase protein expression with priority kinases highlighted. (G) Apoptosis Regulator Expression Changes showing effect sizes for pro-apoptotic, anti-apoptotic, and caspase proteins, color-coded by functional category. (H) Cell Cycle Regulator Expression (CCND2 = Key Target) displaying effect sizes for cyclins, CDKs, and inhibitors with key targets annotated.

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: STAT and pathway target gene expression analysis. Expression profiling of transcription factor targets and pathway-associated proteins. (A) STAT3 Target Gene Expression showing dose-response of established STAT3 transcriptional targets across IQDMA concentrations. (B) STAT5 Target Gene Expression showing dose-response of established STAT5A/B transcriptional targets. (C) PAK Pathway Expression (Expression-based, No Phosphoproteomics) displaying proteins associated with PAK signaling. (D) CTCL-Associated Protein Expression showing expression changes in proteins with established roles in CTCL pathogenesis. (E) Transcription Factor Expression Changes (* = FDR< 0.05) displaying effect sizes for key transcription factors. (F) Kinase Expression Levels (Expression-based, * = FDR< 0.05, Orange = Priority) showing kinase protein expression with priority kinases highlighted. (G) Apoptosis Regulator Expression Changes showing effect sizes for pro-apoptotic, anti-apoptotic, and caspase proteins, color-coded by functional category. (H) Cell Cycle Regulator Expression (CCND2 = Key Target) displaying effect sizes for cyclins, CDKs, and inhibitors with key targets annotated.

Techniques: Targeted Gene Expression, Expressing, Phospho-proteomics, Functional Assay

STAT signaling and nuclear transport machinery analysis. Integration of STAT transcriptional outputs with nuclear transport mechanisms. (A) STAT3/5 Transcriptional Target Response showing effect sizes for established STAT3 and STAT5 target genes (* p< 0.05, ** p< 0.01, *** p< 0.001). (B) Nuclear Transport Machinery Changes displaying expression alterations in importins, exportins, and nuclear pore components that may affect STAT nuclear shuttling (* p< 0.05, ** p< 0.01, *** p< 0.001). (C) PAK-Rho-CDC42 Pathway Response (* = FDR< 0.05 at 10 μ M) showing heatmap of log2 fold change values for pathway members, highlighting the coordinate regulation of this signaling axis.

Journal: Frontiers in Immunology

Article Title: IQDMA disrupts STAT5 nuclear transport through CDC42-PAK2 axis collapse in cutaneous T-cell lymphoma

doi: 10.3389/fimmu.2026.1674527

Figure Lengend Snippet: STAT signaling and nuclear transport machinery analysis. Integration of STAT transcriptional outputs with nuclear transport mechanisms. (A) STAT3/5 Transcriptional Target Response showing effect sizes for established STAT3 and STAT5 target genes (* p< 0.05, ** p< 0.01, *** p< 0.001). (B) Nuclear Transport Machinery Changes displaying expression alterations in importins, exportins, and nuclear pore components that may affect STAT nuclear shuttling (* p< 0.05, ** p< 0.01, *** p< 0.001). (C) PAK-Rho-CDC42 Pathway Response (* = FDR< 0.05 at 10 μ M) showing heatmap of log2 fold change values for pathway members, highlighting the coordinate regulation of this signaling axis.

Techniques: Expressing

( A ) Immunoblot for Stat5, Stat3, p-Stat5, and p-Stat3 with their respective loading control (Tubulin or β-actin) on endpoint mammary tumor lysates of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. ( B – E ) Quantification of immunoblot for Stat5, Stat3, p-Stat5, and p-Stat3 normalized to their loading control, respectively. ( F ) Fluorescent IHC for ERα, p-Stat5, p-Stat3, PanCK, and DAPI on endpoint mammary tumors of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. ( G – I ) Quantification of p-Stat5 + cells, ERα + p-Stat5 + PanCK + cells, and p-Stat3 + cells, respectively. ( J ) Stat5 enrichment on Il1b and Il17a promoter sites detected by ChIP-qPCR in endpoint mammary tumors of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. Scale bars: 100 μm. Mean ± SEM for data calculated using 1-way ANOVA with Tukey’s multiple-comparison test.

Journal: JCI Insight

Article Title: Activating mutations in ESR1 contribute to an immunosuppressive breast tumor microenvironment by dampening cytokine secretion

doi: 10.1172/jci.insight.199927

Figure Lengend Snippet: ( A ) Immunoblot for Stat5, Stat3, p-Stat5, and p-Stat3 with their respective loading control (Tubulin or β-actin) on endpoint mammary tumor lysates of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. ( B – E ) Quantification of immunoblot for Stat5, Stat3, p-Stat5, and p-Stat3 normalized to their loading control, respectively. ( F ) Fluorescent IHC for ERα, p-Stat5, p-Stat3, PanCK, and DAPI on endpoint mammary tumors of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. ( G – I ) Quantification of p-Stat5 + cells, ERα + p-Stat5 + PanCK + cells, and p-Stat3 + cells, respectively. ( J ) Stat5 enrichment on Il1b and Il17a promoter sites detected by ChIP-qPCR in endpoint mammary tumors of MIC WT, MIC ESR1-Y541S homo , and MIC ESR1-D542G homo mice. Scale bars: 100 μm. Mean ± SEM for data calculated using 1-way ANOVA with Tukey’s multiple-comparison test.

Article Snippet: The following antibodies were used for immunoblots: β-actin (Sigma, A5441, 1:2000), tubulin (Cell Signaling Technology (CST), 2148, 1:1000), Cyclin D1 (CST, 2922, 1:500), FOXA1 (Abcam, ab23738, 1:1000), Stat3 (CST, 9139, 1:1000), Stat5 (CST, 94205, 1:1000), p-Stat3 (CST, 9145, 1:1000), and p-Stat5 (CST, 4322, 1:500).

Techniques: Western Blot, Control, ChIP-qPCR, Comparison

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