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anti phospho stat4 tyr693  (Cell Signaling Technology Inc)


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    Structured Review

    Cell Signaling Technology Inc anti phospho stat4 tyr693
    Anti Phospho Stat4 Tyr693, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 94/100, based on 39 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/phospho+stat4+tyr693/Phospho-Stat4+(Tyr693)+Rabbit+mAb/pm41826817-101-69-74
    Average 94 stars, based on 39 article reviews
    anti phospho stat4 tyr693 - by Bioz Stars, 2026-09
    94/100 stars

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    Related Articles

    Western Blot:

    Article Title: Therapeutic Efficacy of Suppressing the JAK/STAT Pathway in Multiple Models of EAE
    Article Snippet: Abs against phospho-STAT1 (Tyr701) and phospho-STAT3 (Tyr705) used for flow cytometry are from Cell Signaling Technology, and phospho-STAT4 (Tyr693) Ab is from BD Biosciences. .. Abs against phospho-STAT1 (Tyr701), phospho-STAT3 (Tyr705), phospho-STAT4 (Tyr693), phospho-STAT5 (Tyr694), phospho-STAT6 (Tyr641), phospho-p65 (Ser536), phospho-JAK2 (Tyr221), STAT1, STAT3, STAT4, STAT5, STAT6, p65 and JAK2 used for immunoblotting are from Cell Signaling Technology. .. Ab against GAPDH is from Abcam, and Abs against Ly-6C, CD11c, MHC class II, CD40, CD80, CD86, CD11b and CD45 are from BD Pharmingen.

    Article Title: Aldh2 Attenuates Stem Cell Factor/Kit-Dependent Signaling and Activation in Mast Cells
    Article Snippet: Antibodies and reagents were purchased from the following sources: antibodies against ALDH2 (sc-48838) and Kit (sc-13508) were from Santa Cruz Biotechnology (Dallas, TX, USA) and used at a dilution of 1:1000 for Western blotting. .. Anti-phospho-Syk (Tyr525/526) (#2711), -phospho-LAT (Tyr191) (#3584), -phospho-PLCγ1 (Y783) (#2821), -phospho-Stat4 (Tyr693) (#5267), -phospho-Akt (Thr308) (#9275), -phospho-SAPK/Jnk (Thr183/Tyr185) (#9251), and -phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) (#9101) antibodies were from Cell Signaling Technology (Beverly, MA, USA) and diluted to 1:2000 for Western blotting. .. Anti-β-actin (#A5316), used as a loading control at 1:5000 dilution, was purchased from Sigma-Aldrich (St Louis, MO, USA).

    Blocking Assay:

    Article Title: MiR‐363‐5p modulates regulatory T cells through STAT4‐HSPB1‐Notch1 axis and is associated with the immunological abnormality in Graves' disease
    Article Snippet: Total protein was electrophoresed on 10% SDS–PAGE and electrically transferred to PVDF membranes (Bio‐Rad). .. After blocking, the membranes were incubated with anti‐β‐actin (Santa Cruz Biotechnology), anti‐phospho‐Stat4 (Tyr693) and anti‐Notch1 mAb (Cell Signaling Technology) overnight at 4°C. .. After washing, the membranes were incubated with the peroxidase‐conjugated secondary antibody (Proteintech Group) for 2 h. Protein bands were detected using ECL kit.

    Incubation:

    Article Title: MiR‐363‐5p modulates regulatory T cells through STAT4‐HSPB1‐Notch1 axis and is associated with the immunological abnormality in Graves' disease
    Article Snippet: Total protein was electrophoresed on 10% SDS–PAGE and electrically transferred to PVDF membranes (Bio‐Rad). .. After blocking, the membranes were incubated with anti‐β‐actin (Santa Cruz Biotechnology), anti‐phospho‐Stat4 (Tyr693) and anti‐Notch1 mAb (Cell Signaling Technology) overnight at 4°C. .. After washing, the membranes were incubated with the peroxidase‐conjugated secondary antibody (Proteintech Group) for 2 h. Protein bands were detected using ECL kit.



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    (A) Linear regression plot depicting the relationship between <t>STAT4</t> expression and patient poverty burden in the VA dataset. (B) STAT4 expression relative to patient poverty burden in the CBCS validation cohort, where the horizontal dotted line indicates average STAT4 expression. (C) tSNE plots from the Single Cell Portal for STAT4 expression depicting highest expression levels in immune T-cell subsets. (D) Representative immunohistochemistry images for phospho-STAT4 protein expression in patient tumor sections from the VA-dataset across two separate patient tumors from high- and low-poverty burden with accompanying quantification represented as stacked columns. (E-F) Kaplan Meier survival curves comparing patient tumors with high and low STAT4 RNA expression for women with estrogen receptor positive/human epidermal growth factor receptor 2 negative breast cancer from Metabric (E, left) and TCGA (E, right & F), with (F) or without race stratification (E). (G) Working model schematic highlighting the interplay between patient-intrinsic and -extrinsic factors in the modulation of tumor biology that contributes to poor patient outcomes in Black breast cancer patients. Scale bar is 290um (D). Linear regression coefficients were used to determine p-values using a T-test (A). Fisher’s exact test was used for determining the p-values in (B and D). Survival analysis was performed using the Mantel-Haenszel method to determine hazard ratios (HR) and a log-rank Mantel-Cox test was used to determine p-values (E-F). Abbreviations: TMM (Trimmed Mean of M values), TPM (Transcripts per million), VA-cohort (Veterans Affairs cohort), CBCS-cohort (Carolina Breast Cancer Study cohort), CD8 (cluster of differentiation 8), CD4 (cluster of differentiation 4), Treg (Regulatory T cells), POV (poverty burden), HR (hazard ratio), n (number).
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    (A) Linear regression plot depicting the relationship between <t>STAT4</t> expression and patient poverty burden in the VA dataset. (B) STAT4 expression relative to patient poverty burden in the CBCS validation cohort, where the horizontal dotted line indicates average STAT4 expression. (C) tSNE plots from the Single Cell Portal for STAT4 expression depicting highest expression levels in immune T-cell subsets. (D) Representative immunohistochemistry images for phospho-STAT4 protein expression in patient tumor sections from the VA-dataset across two separate patient tumors from high- and low-poverty burden with accompanying quantification represented as stacked columns. (E-F) Kaplan Meier survival curves comparing patient tumors with high and low STAT4 RNA expression for women with estrogen receptor positive/human epidermal growth factor receptor 2 negative breast cancer from Metabric (E, left) and TCGA (E, right & F), with (F) or without race stratification (E). (G) Working model schematic highlighting the interplay between patient-intrinsic and -extrinsic factors in the modulation of tumor biology that contributes to poor patient outcomes in Black breast cancer patients. Scale bar is 290um (D). Linear regression coefficients were used to determine p-values using a T-test (A). Fisher’s exact test was used for determining the p-values in (B and D). Survival analysis was performed using the Mantel-Haenszel method to determine hazard ratios (HR) and a log-rank Mantel-Cox test was used to determine p-values (E-F). Abbreviations: TMM (Trimmed Mean of M values), TPM (Transcripts per million), VA-cohort (Veterans Affairs cohort), CBCS-cohort (Carolina Breast Cancer Study cohort), CD8 (cluster of differentiation 8), CD4 (cluster of differentiation 4), Treg (Regulatory T cells), POV (poverty burden), HR (hazard ratio), n (number).
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    (A) Linear regression plot depicting the relationship between <t>STAT4</t> expression and patient poverty burden in the VA dataset. (B) STAT4 expression relative to patient poverty burden in the CBCS validation cohort, where the horizontal dotted line indicates average STAT4 expression. (C) tSNE plots from the Single Cell Portal for STAT4 expression depicting highest expression levels in immune T-cell subsets. (D) Representative immunohistochemistry images for phospho-STAT4 protein expression in patient tumor sections from the VA-dataset across two separate patient tumors from high- and low-poverty burden with accompanying quantification represented as stacked columns. (E-F) Kaplan Meier survival curves comparing patient tumors with high and low STAT4 RNA expression for women with estrogen receptor positive/human epidermal growth factor receptor 2 negative breast cancer from Metabric (E, left) and TCGA (E, right & F), with (F) or without race stratification (E). (G) Working model schematic highlighting the interplay between patient-intrinsic and -extrinsic factors in the modulation of tumor biology that contributes to poor patient outcomes in Black breast cancer patients. Scale bar is 290um (D). Linear regression coefficients were used to determine p-values using a T-test (A). Fisher’s exact test was used for determining the p-values in (B and D). Survival analysis was performed using the Mantel-Haenszel method to determine hazard ratios (HR) and a log-rank Mantel-Cox test was used to determine p-values (E-F). Abbreviations: TMM (Trimmed Mean of M values), TPM (Transcripts per million), VA-cohort (Veterans Affairs cohort), CBCS-cohort (Carolina Breast Cancer Study cohort), CD8 (cluster of differentiation 8), CD4 (cluster of differentiation 4), Treg (Regulatory T cells), POV (poverty burden), HR (hazard ratio), n (number).
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    IL-12 EVs enhance the function of CAR-T cells. ( A ) CAR-T cells were treated with control EVs or IL-12 EVs for 30 min, and the phosphorylation of <t>STAT4</t> was analyzed by western blotting. Experiments are representative of 3 independent repeats with similar results. (B-G) CAR-T cells (cell density: 1*10 6 /mL) were mixed with 5 × 10 4 Raji cells at an effector-to-target ratio of 1:1 and treated with PBS, control EVs, rhIL-12, and IL-12 EVs repectively. Protein concentration of EVs is 167 µg/mL, and rhIL-12 concentration is 667 pg/mL. ( B , C ) Cytokine secretion by CAR-T cells was detected by ELISA after 24 h of coculture ( n = 3 donors). ( D ) The proportion of CAR-T cells was analyzed by flow cytometry after 72 h of coculture ( n = 3 donors). ( E ) CD107a expression in CD8 + CAR-T cells was detected by flow cytometry ( n = 3 donors). ( F ) Raji cell death was determined using PI (BD Pharmingen) and analyzed by using flow cytometry after 24 h ( n = 5 donors). ( G ) Subsets were detected via flow cytometry in CAR-T cells after 7 days of treatment ( n = 3 donors). Data are presented as mean ± SEM. Statistical analysis was performed using one-way or two-way ANOVA. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001
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    IL-12 EVs enhance the function of CAR-T cells. ( A ) CAR-T cells were treated with control EVs or IL-12 EVs for 30 min, and the phosphorylation of <t>STAT4</t> was analyzed by western blotting. Experiments are representative of 3 independent repeats with similar results. (B-G) CAR-T cells (cell density: 1*10 6 /mL) were mixed with 5 × 10 4 Raji cells at an effector-to-target ratio of 1:1 and treated with PBS, control EVs, rhIL-12, and IL-12 EVs repectively. Protein concentration of EVs is 167 µg/mL, and rhIL-12 concentration is 667 pg/mL. ( B , C ) Cytokine secretion by CAR-T cells was detected by ELISA after 24 h of coculture ( n = 3 donors). ( D ) The proportion of CAR-T cells was analyzed by flow cytometry after 72 h of coculture ( n = 3 donors). ( E ) CD107a expression in CD8 + CAR-T cells was detected by flow cytometry ( n = 3 donors). ( F ) Raji cell death was determined using PI (BD Pharmingen) and analyzed by using flow cytometry after 24 h ( n = 5 donors). ( G ) Subsets were detected via flow cytometry in CAR-T cells after 7 days of treatment ( n = 3 donors). Data are presented as mean ± SEM. Statistical analysis was performed using one-way or two-way ANOVA. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001
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    Image Search Results


    (A) Linear regression plot depicting the relationship between STAT4 expression and patient poverty burden in the VA dataset. (B) STAT4 expression relative to patient poverty burden in the CBCS validation cohort, where the horizontal dotted line indicates average STAT4 expression. (C) tSNE plots from the Single Cell Portal for STAT4 expression depicting highest expression levels in immune T-cell subsets. (D) Representative immunohistochemistry images for phospho-STAT4 protein expression in patient tumor sections from the VA-dataset across two separate patient tumors from high- and low-poverty burden with accompanying quantification represented as stacked columns. (E-F) Kaplan Meier survival curves comparing patient tumors with high and low STAT4 RNA expression for women with estrogen receptor positive/human epidermal growth factor receptor 2 negative breast cancer from Metabric (E, left) and TCGA (E, right & F), with (F) or without race stratification (E). (G) Working model schematic highlighting the interplay between patient-intrinsic and -extrinsic factors in the modulation of tumor biology that contributes to poor patient outcomes in Black breast cancer patients. Scale bar is 290um (D). Linear regression coefficients were used to determine p-values using a T-test (A). Fisher’s exact test was used for determining the p-values in (B and D). Survival analysis was performed using the Mantel-Haenszel method to determine hazard ratios (HR) and a log-rank Mantel-Cox test was used to determine p-values (E-F). Abbreviations: TMM (Trimmed Mean of M values), TPM (Transcripts per million), VA-cohort (Veterans Affairs cohort), CBCS-cohort (Carolina Breast Cancer Study cohort), CD8 (cluster of differentiation 8), CD4 (cluster of differentiation 4), Treg (Regulatory T cells), POV (poverty burden), HR (hazard ratio), n (number).

    Journal: bioRxiv

    Article Title: The impact of patient biology on racial disparities in breast cancer outcome

    doi: 10.1101/2025.11.05.685148

    Figure Lengend Snippet: (A) Linear regression plot depicting the relationship between STAT4 expression and patient poverty burden in the VA dataset. (B) STAT4 expression relative to patient poverty burden in the CBCS validation cohort, where the horizontal dotted line indicates average STAT4 expression. (C) tSNE plots from the Single Cell Portal for STAT4 expression depicting highest expression levels in immune T-cell subsets. (D) Representative immunohistochemistry images for phospho-STAT4 protein expression in patient tumor sections from the VA-dataset across two separate patient tumors from high- and low-poverty burden with accompanying quantification represented as stacked columns. (E-F) Kaplan Meier survival curves comparing patient tumors with high and low STAT4 RNA expression for women with estrogen receptor positive/human epidermal growth factor receptor 2 negative breast cancer from Metabric (E, left) and TCGA (E, right & F), with (F) or without race stratification (E). (G) Working model schematic highlighting the interplay between patient-intrinsic and -extrinsic factors in the modulation of tumor biology that contributes to poor patient outcomes in Black breast cancer patients. Scale bar is 290um (D). Linear regression coefficients were used to determine p-values using a T-test (A). Fisher’s exact test was used for determining the p-values in (B and D). Survival analysis was performed using the Mantel-Haenszel method to determine hazard ratios (HR) and a log-rank Mantel-Cox test was used to determine p-values (E-F). Abbreviations: TMM (Trimmed Mean of M values), TPM (Transcripts per million), VA-cohort (Veterans Affairs cohort), CBCS-cohort (Carolina Breast Cancer Study cohort), CD8 (cluster of differentiation 8), CD4 (cluster of differentiation 4), Treg (Regulatory T cells), POV (poverty burden), HR (hazard ratio), n (number).

    Article Snippet: Antibodies used were STAT4 (Cell Signaling Technology, catalog no. #4134), and Histone H3 (Cell Signaling Technology, catalog no. #9701).

    Techniques: Expressing, Biomarker Discovery, Immunohistochemistry, RNA Expression

    IL-12 EVs enhance the function of CAR-T cells. ( A ) CAR-T cells were treated with control EVs or IL-12 EVs for 30 min, and the phosphorylation of STAT4 was analyzed by western blotting. Experiments are representative of 3 independent repeats with similar results. (B-G) CAR-T cells (cell density: 1*10 6 /mL) were mixed with 5 × 10 4 Raji cells at an effector-to-target ratio of 1:1 and treated with PBS, control EVs, rhIL-12, and IL-12 EVs repectively. Protein concentration of EVs is 167 µg/mL, and rhIL-12 concentration is 667 pg/mL. ( B , C ) Cytokine secretion by CAR-T cells was detected by ELISA after 24 h of coculture ( n = 3 donors). ( D ) The proportion of CAR-T cells was analyzed by flow cytometry after 72 h of coculture ( n = 3 donors). ( E ) CD107a expression in CD8 + CAR-T cells was detected by flow cytometry ( n = 3 donors). ( F ) Raji cell death was determined using PI (BD Pharmingen) and analyzed by using flow cytometry after 24 h ( n = 5 donors). ( G ) Subsets were detected via flow cytometry in CAR-T cells after 7 days of treatment ( n = 3 donors). Data are presented as mean ± SEM. Statistical analysis was performed using one-way or two-way ANOVA. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001

    Journal: Experimental Hematology & Oncology

    Article Title: Improving CAR-T cell function through a targeted cytokine delivery system utilizing car target-modified extracellular vesicles

    doi: 10.1186/s40164-025-00701-z

    Figure Lengend Snippet: IL-12 EVs enhance the function of CAR-T cells. ( A ) CAR-T cells were treated with control EVs or IL-12 EVs for 30 min, and the phosphorylation of STAT4 was analyzed by western blotting. Experiments are representative of 3 independent repeats with similar results. (B-G) CAR-T cells (cell density: 1*10 6 /mL) were mixed with 5 × 10 4 Raji cells at an effector-to-target ratio of 1:1 and treated with PBS, control EVs, rhIL-12, and IL-12 EVs repectively. Protein concentration of EVs is 167 µg/mL, and rhIL-12 concentration is 667 pg/mL. ( B , C ) Cytokine secretion by CAR-T cells was detected by ELISA after 24 h of coculture ( n = 3 donors). ( D ) The proportion of CAR-T cells was analyzed by flow cytometry after 72 h of coculture ( n = 3 donors). ( E ) CD107a expression in CD8 + CAR-T cells was detected by flow cytometry ( n = 3 donors). ( F ) Raji cell death was determined using PI (BD Pharmingen) and analyzed by using flow cytometry after 24 h ( n = 5 donors). ( G ) Subsets were detected via flow cytometry in CAR-T cells after 7 days of treatment ( n = 3 donors). Data are presented as mean ± SEM. Statistical analysis was performed using one-way or two-way ANOVA. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001

    Article Snippet: Total STAT4 and phosphorylated STAT4 in T cells were detected using an anti-Stat4 (C46B10) antibody (CST, 2653 S, 1:1000) and an anti-phospho-Stat4 (Tyr693) antibody (CST, 5267 S, 1:1000).

    Techniques: Control, Phospho-proteomics, Western Blot, Protein Concentration, Concentration Assay, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Expressing