fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgfr1
    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between <t>FGFR1/2/3/4</t> expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Fgfr1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts"

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    Journal: Theranostics

    doi: 10.7150/thno.68972

    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Figure Legend Snippet: FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Techniques Used: Expressing, Immunohistochemistry

    FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).
    Figure Legend Snippet: FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Techniques Used: Migration, Transwell Migration Assay, Staining, Expressing

    FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.
    Figure Legend Snippet: FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Techniques Used: RNA Sequencing Assay

    fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgfr1
    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between <t>FGFR1/2/3/4</t> expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Fgfr1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts"

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    Journal: Theranostics

    doi: 10.7150/thno.68972

    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Figure Legend Snippet: FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Techniques Used: Expressing, Immunohistochemistry

    FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).
    Figure Legend Snippet: FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Techniques Used: Migration, Transwell Migration Assay, Staining, Expressing

    FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.
    Figure Legend Snippet: FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Techniques Used: RNA Sequencing Assay

    anti fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc anti fgfr1
    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between <t>FGFR1/2/3/4</t> expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Anti Fgfr1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 96 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    anti fgfr1 - by Bioz Stars, 2023-02
    96/100 stars

    Images

    1) Product Images from "FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts"

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    Journal: Theranostics

    doi: 10.7150/thno.68972

    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
    Figure Legend Snippet: FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Techniques Used: Expressing, Immunohistochemistry

    FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).
    Figure Legend Snippet: FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Techniques Used: Migration, Transwell Migration Assay, Staining, Expressing

    FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.
    Figure Legend Snippet: FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Techniques Used: RNA Sequencing Assay

    fgf receptor 1 fgfr 1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgf receptor 1 fgfr 1
    Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and <t>FGFR-1.</t> (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.
    Fgf Receptor 1 Fgfr 1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/fgf receptor 1 fgfr 1/product/Cell Signaling Technology Inc
    Average 96 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    fgf receptor 1 fgfr 1 - by Bioz Stars, 2023-02
    96/100 stars

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    1) Product Images from "Combination of Ligusticum Chuanxiong and Radix Paeonia Promotes Angiogenesis in Ischemic Myocardium through Notch Signalling and Mobilization of Stem Cells"

    Article Title: Combination of Ligusticum Chuanxiong and Radix Paeonia Promotes Angiogenesis in Ischemic Myocardium through Notch Signalling and Mobilization of Stem Cells

    Journal: Evidence-based Complementary and Alternative Medicine : eCAM

    doi: 10.1155/2019/7912402

    Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and FGFR-1. (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.
    Figure Legend Snippet: Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and FGFR-1. (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.

    Techniques Used: Expressing

    fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgfr1
    A Heatmap showing genes up-regulated (red) or down-regulated (blue) in 22RV1 ARHGEF2 downregulated cells obtained by RNA-seq analysis. B , C KEGG pathway enrichment ( B ) and GSEA ( C ) analysis showing the MAPK pathway enriched in the 22RV1-siARHGEF2 group relative to control. D , E Immunoblot analysis for protein levels in SOX2 and <t>FGFR1/MAPK</t> pathway in ARHGEF2-silenced (shARHGEF2) and control (shSCR) LNCaP-AI (left) and 22RV1 (right) cells. F Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway in ARHGEF2-overexpressed (oeARHGEF2) and control (oeVector) LNCaP cells. G Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway using the same cells as F treated with AZD4547. AZD4547, a selective FGFR inhibitor . H , I Immunoblot analysis for protein levels in ARHGEF2 using the LNCaP-AI and 22RV1 cells treated with Vehicle and AZD4547. J Illustration showing AR-repressed ARHGEF2 regulate SOX2 via FGFR1/MAPK pathway in prostate cancer. AR, androgen receptor; ARHGEF2, Rho guanine nucleotide exchange factor 2; FGFR1, fibroblast growth factor receptor 1; SOX2 SRY-Box transcription factor 2; NE neuroendocrine.
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    Images

    1) Product Images from "Androgen deprivation restores ARHGEF2 to promote neuroendocrine differentiation of prostate cancer"

    Article Title: Androgen deprivation restores ARHGEF2 to promote neuroendocrine differentiation of prostate cancer

    Journal: Cell Death & Disease

    doi: 10.1038/s41419-022-05366-8

    A Heatmap showing genes up-regulated (red) or down-regulated (blue) in 22RV1 ARHGEF2 downregulated cells obtained by RNA-seq analysis. B , C KEGG pathway enrichment ( B ) and GSEA ( C ) analysis showing the MAPK pathway enriched in the 22RV1-siARHGEF2 group relative to control. D , E Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway in ARHGEF2-silenced (shARHGEF2) and control (shSCR) LNCaP-AI (left) and 22RV1 (right) cells. F Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway in ARHGEF2-overexpressed (oeARHGEF2) and control (oeVector) LNCaP cells. G Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway using the same cells as F treated with AZD4547. AZD4547, a selective FGFR inhibitor . H , I Immunoblot analysis for protein levels in ARHGEF2 using the LNCaP-AI and 22RV1 cells treated with Vehicle and AZD4547. J Illustration showing AR-repressed ARHGEF2 regulate SOX2 via FGFR1/MAPK pathway in prostate cancer. AR, androgen receptor; ARHGEF2, Rho guanine nucleotide exchange factor 2; FGFR1, fibroblast growth factor receptor 1; SOX2 SRY-Box transcription factor 2; NE neuroendocrine.
    Figure Legend Snippet: A Heatmap showing genes up-regulated (red) or down-regulated (blue) in 22RV1 ARHGEF2 downregulated cells obtained by RNA-seq analysis. B , C KEGG pathway enrichment ( B ) and GSEA ( C ) analysis showing the MAPK pathway enriched in the 22RV1-siARHGEF2 group relative to control. D , E Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway in ARHGEF2-silenced (shARHGEF2) and control (shSCR) LNCaP-AI (left) and 22RV1 (right) cells. F Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway in ARHGEF2-overexpressed (oeARHGEF2) and control (oeVector) LNCaP cells. G Immunoblot analysis for protein levels in SOX2 and FGFR1/MAPK pathway using the same cells as F treated with AZD4547. AZD4547, a selective FGFR inhibitor . H , I Immunoblot analysis for protein levels in ARHGEF2 using the LNCaP-AI and 22RV1 cells treated with Vehicle and AZD4547. J Illustration showing AR-repressed ARHGEF2 regulate SOX2 via FGFR1/MAPK pathway in prostate cancer. AR, androgen receptor; ARHGEF2, Rho guanine nucleotide exchange factor 2; FGFR1, fibroblast growth factor receptor 1; SOX2 SRY-Box transcription factor 2; NE neuroendocrine.

    Techniques Used: RNA Sequencing Assay, Western Blot

    A . Transwell migration assay in LNCaP-AI cells infected with lentiviruses carrying shARHGEF2. The left panel shows the representative microphotographs (scale bar = 100 µm). B . MTT assays in LNCaP-AI cells infected with lentiviruses carrying shARHGEF2. Cell growth assessed daily for 6 days using an MTT assay in LNCaP-AI cells. Data were obtained from three independent experiments with samples in triplicate. C . Transwell migration assay in 22RV1 cells infected with lentiviruses carrying shARHGEF2. The left panel shows the representative microphotographs (scale bar = 100 µm). D MTT assays in 22RV1 cells infected with lentiviruses carrying shARHGEF2. Cell growth assessed daily for 6 days using an MTT assay in 22RV1 cells. Data were obtained from three independent experiments with samples in triplicate. E , F . Transwell migration assay E and MTT assays F in LNCaP cells infected with lentiviruses carrying overexpressed ARHGEF2 (oeARHGEF2). G Representative image of the dissected tumors was shown. H Growth curves of xenografts of 22RV1 cells infected with shSCR or shARHGEF2. Data are representative of mean ± SD of n = 5 tumors per group. I Representative image of the dissected tumors was shown. Representative images showing immunostaining (×100 and ×200 magnification) for ARHGEF2, FGFR1, p-ERK, SOX2, CHGA, SYN and Ki-67 in tumor specimens obtained from xenografts. For panels A , C , E two-tailed unpaired Student’s t-test; For panels B , D , F , and H , two-way ANOVA, Sidak’s multiple-comparisons test was applied. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, and **** P < 0.0001.
    Figure Legend Snippet: A . Transwell migration assay in LNCaP-AI cells infected with lentiviruses carrying shARHGEF2. The left panel shows the representative microphotographs (scale bar = 100 µm). B . MTT assays in LNCaP-AI cells infected with lentiviruses carrying shARHGEF2. Cell growth assessed daily for 6 days using an MTT assay in LNCaP-AI cells. Data were obtained from three independent experiments with samples in triplicate. C . Transwell migration assay in 22RV1 cells infected with lentiviruses carrying shARHGEF2. The left panel shows the representative microphotographs (scale bar = 100 µm). D MTT assays in 22RV1 cells infected with lentiviruses carrying shARHGEF2. Cell growth assessed daily for 6 days using an MTT assay in 22RV1 cells. Data were obtained from three independent experiments with samples in triplicate. E , F . Transwell migration assay E and MTT assays F in LNCaP cells infected with lentiviruses carrying overexpressed ARHGEF2 (oeARHGEF2). G Representative image of the dissected tumors was shown. H Growth curves of xenografts of 22RV1 cells infected with shSCR or shARHGEF2. Data are representative of mean ± SD of n = 5 tumors per group. I Representative image of the dissected tumors was shown. Representative images showing immunostaining (×100 and ×200 magnification) for ARHGEF2, FGFR1, p-ERK, SOX2, CHGA, SYN and Ki-67 in tumor specimens obtained from xenografts. For panels A , C , E two-tailed unpaired Student’s t-test; For panels B , D , F , and H , two-way ANOVA, Sidak’s multiple-comparisons test was applied. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, and **** P < 0.0001.

    Techniques Used: Transwell Migration Assay, Infection, MTT Assay, Immunostaining, Two Tailed Test

    fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgfr1
    (A) RT-qPCR determination of changes of <t>FGFR1</t> and FGFR2 mRNA expression during the initial 3d after intrahippocampal injection of KA (1 nmol). One-way ANOVA for FGFR1 and Kruskal Wallis for FGFR2. Bars show mean ± SEM. Dots show individual data. n=3. (B) WB of hippocampi dissected at different time points after KA (1 nmol) showing no changes in FGFR1 expression. (C) Confocal microscopy images after immunostaining for FGFR1 in the SGZ of Nestin-GFP mice 24 h after KA. Scale bar is 10 μm. (D) Immunofluorescence images of cultured hippocampal NSPCs stimulated with EGF and FGF showing EGFR staining. Scale bar is 10 μm.
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    1) Product Images from "HB-EGF and zinc activate EGFR to induce reactive neural stem cells in the mouse hippocampus after seizures"

    Article Title: HB-EGF and zinc activate EGFR to induce reactive neural stem cells in the mouse hippocampus after seizures

    Journal: bioRxiv

    doi: 10.1101/2022.11.02.514820

    (A) RT-qPCR determination of changes of FGFR1 and FGFR2 mRNA expression during the initial 3d after intrahippocampal injection of KA (1 nmol). One-way ANOVA for FGFR1 and Kruskal Wallis for FGFR2. Bars show mean ± SEM. Dots show individual data. n=3. (B) WB of hippocampi dissected at different time points after KA (1 nmol) showing no changes in FGFR1 expression. (C) Confocal microscopy images after immunostaining for FGFR1 in the SGZ of Nestin-GFP mice 24 h after KA. Scale bar is 10 μm. (D) Immunofluorescence images of cultured hippocampal NSPCs stimulated with EGF and FGF showing EGFR staining. Scale bar is 10 μm.
    Figure Legend Snippet: (A) RT-qPCR determination of changes of FGFR1 and FGFR2 mRNA expression during the initial 3d after intrahippocampal injection of KA (1 nmol). One-way ANOVA for FGFR1 and Kruskal Wallis for FGFR2. Bars show mean ± SEM. Dots show individual data. n=3. (B) WB of hippocampi dissected at different time points after KA (1 nmol) showing no changes in FGFR1 expression. (C) Confocal microscopy images after immunostaining for FGFR1 in the SGZ of Nestin-GFP mice 24 h after KA. Scale bar is 10 μm. (D) Immunofluorescence images of cultured hippocampal NSPCs stimulated with EGF and FGF showing EGFR staining. Scale bar is 10 μm.

    Techniques Used: Quantitative RT-PCR, Expressing, Injection, Confocal Microscopy, Immunostaining, Immunofluorescence, Cell Culture, Staining

    fgfr  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgfr
    Fgfr, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    fgf receptor 1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc fgf receptor 1
    The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of <t>Fgfr1</t> in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm
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    1) Product Images from "Disrupted tenogenesis in masseter as a potential cause of micrognathia"

    Article Title: Disrupted tenogenesis in masseter as a potential cause of micrognathia

    Journal: International Journal of Oral Science

    doi: 10.1038/s41368-022-00196-y

    The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of Fgfr1 in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm
    Figure Legend Snippet: The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of Fgfr1 in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm

    Techniques Used: Immunostaining, Staining

    anti fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc anti fgfr1
    A. The morphology of prostate in WT and TRAMP mice dissected at the age of 12 and 22 week is observed in a light microscope. Below is the analysis of prostate/tumor weight. (n = 4 mice for each group) B. Representative image of H&E staining. Scale bars: 50μm. C. Immunohistochemistry staining showing the expression of <t>FGFR1</t> (brown). Hematoxylin for the counterstaining of nuclear. Scale bars: 50μm. D. Representative image of Perl’s staining enhanced with DAB. Scale bars: 50μm. E. Immunohistochemistry staining showed the expression of TFR1 (brown). Scale bars: 50μm. F. Representative Perl’s staining enhanced with DAB of well differentiated and poor differentiated human PCa tissues. Scale bars: 50μm. Data information: In A, data are presented as mean ± SD. 12W, mice at the age of 12 week. 22W, mice at the age of 12 week. WT, wildtype mice. TRAMP, TRAMP mice. *, P < 0.05.
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    Images

    1) Product Images from "FGFR1 governs iron metabolism via regulating post-translational modification of IRP2 in prostate cancer cells"

    Article Title: FGFR1 governs iron metabolism via regulating post-translational modification of IRP2 in prostate cancer cells

    Journal: bioRxiv

    doi: 10.1101/2022.10.17.512481

    A. The morphology of prostate in WT and TRAMP mice dissected at the age of 12 and 22 week is observed in a light microscope. Below is the analysis of prostate/tumor weight. (n = 4 mice for each group) B. Representative image of H&E staining. Scale bars: 50μm. C. Immunohistochemistry staining showing the expression of FGFR1 (brown). Hematoxylin for the counterstaining of nuclear. Scale bars: 50μm. D. Representative image of Perl’s staining enhanced with DAB. Scale bars: 50μm. E. Immunohistochemistry staining showed the expression of TFR1 (brown). Scale bars: 50μm. F. Representative Perl’s staining enhanced with DAB of well differentiated and poor differentiated human PCa tissues. Scale bars: 50μm. Data information: In A, data are presented as mean ± SD. 12W, mice at the age of 12 week. 22W, mice at the age of 12 week. WT, wildtype mice. TRAMP, TRAMP mice. *, P < 0.05.
    Figure Legend Snippet: A. The morphology of prostate in WT and TRAMP mice dissected at the age of 12 and 22 week is observed in a light microscope. Below is the analysis of prostate/tumor weight. (n = 4 mice for each group) B. Representative image of H&E staining. Scale bars: 50μm. C. Immunohistochemistry staining showing the expression of FGFR1 (brown). Hematoxylin for the counterstaining of nuclear. Scale bars: 50μm. D. Representative image of Perl’s staining enhanced with DAB. Scale bars: 50μm. E. Immunohistochemistry staining showed the expression of TFR1 (brown). Scale bars: 50μm. F. Representative Perl’s staining enhanced with DAB of well differentiated and poor differentiated human PCa tissues. Scale bars: 50μm. Data information: In A, data are presented as mean ± SD. 12W, mice at the age of 12 week. 22W, mice at the age of 12 week. WT, wildtype mice. TRAMP, TRAMP mice. *, P < 0.05.

    Techniques Used: Light Microscopy, Staining, Immunohistochemistry, Expressing

    A. Relationship between Gleason score and the mRNA level of TFR1 of prostate cancer in TCGA database. B. Correlation analysis between the mRNA level of TFR1 and FGFR1 of prostate cancer in TCGA database. C. HE staining and double immunofluorescence staining with FGFR1 (green) and TFR1 (red) between well and poorly differentiated human PCa tissues. Right panel is the quantitative analysis by Image J. Scale bars: 30μm. D. Double immunofluorescence staining with FGFR1 (green) and TFR1 (red) in DU145 and DU145 ΔR1 cells. Scale bars: 30μm. E. Western blotting analysis of the indicated proteins and the quantitative analyses of TFR1 with Image J. β-actin was used as a loading control. F. Calcein AM was used to detect the labile iron pool of DU145 and DU145 ΔR1 cells. G. Western blot showed the protein expression of FGFR1 and TFR1 in different PCa cell lines and the quantitative analyses of TFR1 in indicated PCa cells with Image J. β-actin was used as a loading control. H. Labile iron pool were detected with Calcein AM. Data information: In (E-H), data are presented as mean ± SD. Ctrl, DU145; R1KO, DU145 ΔR1 ; DU145 ΔR1OE , FGFR1 overexpressed in DU145 ΔR1 ; LNCaP R1OE /C4-2 R1OE , FGFR1 overexpressed in LNCaP/C4-2. ***, P < 0.001. *, P < 0.05.
    Figure Legend Snippet: A. Relationship between Gleason score and the mRNA level of TFR1 of prostate cancer in TCGA database. B. Correlation analysis between the mRNA level of TFR1 and FGFR1 of prostate cancer in TCGA database. C. HE staining and double immunofluorescence staining with FGFR1 (green) and TFR1 (red) between well and poorly differentiated human PCa tissues. Right panel is the quantitative analysis by Image J. Scale bars: 30μm. D. Double immunofluorescence staining with FGFR1 (green) and TFR1 (red) in DU145 and DU145 ΔR1 cells. Scale bars: 30μm. E. Western blotting analysis of the indicated proteins and the quantitative analyses of TFR1 with Image J. β-actin was used as a loading control. F. Calcein AM was used to detect the labile iron pool of DU145 and DU145 ΔR1 cells. G. Western blot showed the protein expression of FGFR1 and TFR1 in different PCa cell lines and the quantitative analyses of TFR1 in indicated PCa cells with Image J. β-actin was used as a loading control. H. Labile iron pool were detected with Calcein AM. Data information: In (E-H), data are presented as mean ± SD. Ctrl, DU145; R1KO, DU145 ΔR1 ; DU145 ΔR1OE , FGFR1 overexpressed in DU145 ΔR1 ; LNCaP R1OE /C4-2 R1OE , FGFR1 overexpressed in LNCaP/C4-2. ***, P < 0.001. *, P < 0.05.

    Techniques Used: Staining, Double Immunofluorescence Staining, Western Blot, Expressing

    anti fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc anti fgfr1
    Anti Fgfr1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    rabbit anti fgfr1  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc rabbit anti fgfr1
    Cellular expression of <t>FGFR1</t> during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).
    Rabbit Anti Fgfr1, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    1) Product Images from "FGF8–FGFR1 signaling regulates human GnRH neuron differentiation in a time- and dose-dependent manner"

    Article Title: FGF8–FGFR1 signaling regulates human GnRH neuron differentiation in a time- and dose-dependent manner

    Journal: Disease Models & Mechanisms

    doi: 10.1242/dmm.049436

    Cellular expression of FGFR1 during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).
    Figure Legend Snippet: Cellular expression of FGFR1 during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).

    Techniques Used: Expressing, Fluorescence, Immunostaining

    Effect of FGFR1 inhibition on the relative gene expression of GNRH1 . (A) Schematic of the differentiation protocol when cells were treated with 100 ng/ml FGF8 alone or with FGF8 and 10 µM of the FGFR1 inhibitor PD166866 (PD); black asterisk, cell splitting; red asterisk, end of differentiation. (B) Bar graphs show the relative levels of GNRH1 RNA obtained from cells at day 25 of the differentiation protocol, after treatment with FGF8 alone or FGF8+PD compared to undifferentiated hPS control cells. ( n =4, * P <0.05; error bars indicate the +standard error of the mean (+s.e.m.).
    Figure Legend Snippet: Effect of FGFR1 inhibition on the relative gene expression of GNRH1 . (A) Schematic of the differentiation protocol when cells were treated with 100 ng/ml FGF8 alone or with FGF8 and 10 µM of the FGFR1 inhibitor PD166866 (PD); black asterisk, cell splitting; red asterisk, end of differentiation. (B) Bar graphs show the relative levels of GNRH1 RNA obtained from cells at day 25 of the differentiation protocol, after treatment with FGF8 alone or FGF8+PD compared to undifferentiated hPS control cells. ( n =4, * P <0.05; error bars indicate the +standard error of the mean (+s.e.m.).

    Techniques Used: Inhibition, Expressing

    Analysis of the FGF8–FGFR1 mechanistic network. (A) Venn diagram indicating the 461 differentially expressed genes (DEGs; encircled in red) on day 13 that belong to FGF8–FGFR1 mechanistic networks as identified by IPA. (B) Venn diagram indicating the DEGs (red circle) across all FGF8 treatment time points that belong to FGF8–FGFR1 mechanistic networks as identified by IPA.
    Figure Legend Snippet: Analysis of the FGF8–FGFR1 mechanistic network. (A) Venn diagram indicating the 461 differentially expressed genes (DEGs; encircled in red) on day 13 that belong to FGF8–FGFR1 mechanistic networks as identified by IPA. (B) Venn diagram indicating the DEGs (red circle) across all FGF8 treatment time points that belong to FGF8–FGFR1 mechanistic networks as identified by IPA.

    Techniques Used:

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    Cell Signaling Technology Inc fgfr1
    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between <t>FGFR1/2/3/4</t> expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
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    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between <t>FGFR1/2/3/4</t> expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.
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    Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and <t>FGFR-1.</t> (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.
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    Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and <t>FGFR-1.</t> (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.
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    The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of <t>Fgfr1</t> in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm
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    Cellular expression of <t>FGFR1</t> during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).
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    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Article Snippet: Tumor specimens were stained using antibodies against α-SMA (Abcam, ab7817), CD3 (Abcam, ab5690) or FGFR1 (Cell Signaling Technology, #9740).

    Techniques: Expressing, Immunohistochemistry

    FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Article Snippet: Tumor specimens were stained using antibodies against α-SMA (Abcam, ab7817), CD3 (Abcam, ab5690) or FGFR1 (Cell Signaling Technology, #9740).

    Techniques: Migration, Transwell Migration Assay, Staining, Expressing

    FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Article Snippet: Tumor specimens were stained using antibodies against α-SMA (Abcam, ab7817), CD3 (Abcam, ab5690) or FGFR1 (Cell Signaling Technology, #9740).

    Techniques: RNA Sequencing Assay

    FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR signaling pathways were enriched in immune-excluded type triple-negative breast cancer (TNBC). A) The gene signature in immune-inflamed and immune-excluded TNBC samples from TCGA dataset. B) The correlation between FGFR score and 23 types of stromal cells in TME based on TCGA BRCA dataset. “Pos.” represents immune cells positively correlated with FGFR score; “Neg.” represents immune cells negatively correlated with FGFR score; “No correlation” represents immune cells that do not correlate with FGFR score. Immune subtypes (C1-C6) were characterized by differences in the nature of the overall immune response .C) The correlation between FGFR1/2/3/4 expression and cytotoxic T lymphocytes (CTL) infiltration in indicated cancer types from GEO database based on Tumor Immune Dysfunction and Exclusion (TIDE) system. D) T cell exclusion score in BRCA of TCGA based on FGFRs expression. E) Immune phenotypes of TNBC defined by IHC staining of CD3. F) The expression of FGFR1 in immune-inflamed and immune-excluded TNBC samples based on IHC staining (inflamed, n=33; excluded, n=118, t test). G) Kaplan-Meier survival analysis of low FGFR1 (blue, n=51) versus high FGFR1 (red, n=68) expression in TNBC.

    Article Snippet: The primary antibodies used for IF staining includes anti-CD3 antibody (Abcam, ab5690), anti-SMA antibody (Abcam, ab7817) anti-FGFR1 (Cell Signaling Technology, #9740) and anti-VCAM-1 antibody (Abcam, ab134047).

    Techniques: Expressing, Immunohistochemistry

    FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR blockade induced T cell infiltration by modulating fibroblasts. A) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration was detected by transwell migration assay (n=5 biological replicates, one-way ANOVA). B) Representative staining and IHC score of α-SMA in immune-inflamed and immune-excluded TNBC samples. C) Representative IF staining of α-SMA and CD3 in immune-inflamed and immune-excluded TNBC samples. D) FGFR1 expression in tumor microenvironment of breast cancer (GSE114727). E-F) Cell population in TME of breast cancer based on FGFR1 expression. G) Representative IF staining of FGFR1 and α-SMA in TNBC samples. H) The effect of FGFRi Erdafitinib on CD4 + and CD8 + T cell migration in presence of CAFs was detected by transwell migration assay (n=3 biological replicates, one-way ANOVA).

    Article Snippet: The primary antibodies used for IF staining includes anti-CD3 antibody (Abcam, ab5690), anti-SMA antibody (Abcam, ab7817) anti-FGFR1 (Cell Signaling Technology, #9740) and anti-VCAM-1 antibody (Abcam, ab134047).

    Techniques: Migration, Transwell Migration Assay, Staining, Expressing

    FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Journal: Theranostics

    Article Title: FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts

    doi: 10.7150/thno.68972

    Figure Lengend Snippet: FGFR blockade synergizes with immune checkpoint blockade therapy. A) Overall survival of melanoma patients who had high FGFR1 vs. low FGFR1 expressed in the tumors before anti-PD-1 treatment (GSE78220). B and C) EMT6 (B) and 4T1 (C) tumor growth in mice treated with vehicle, anti-PD-1, FGFRi (Erdafitinib) or combination of anti-PD-1 and FGFRi (n=7 mice/group, two-way ANOVA). D) Survival analysis of 4T1 tumor-bearing mice treated with indicated therapy (n=8 mice/group, log-rank test). E) The t-SNE plot of TILs and CD8 + T cell population in 4T1 tumors from mice treated with indicated therapies (n=6, one-way ANOVA). F) Percentage of IFN-γ + CD8 + T-cells in indicated therapy-treated 4T1 tumors (n=6, one-way ANOVA). G) Gene ontology (GO) analysis by RNA-seq of 4T1 tumors in indicated groups (n=3/group). Heatmap shows the DEGs and associated signatures. COM, anti-PD-1+FGFRi. H) Heatmap shows the percentage of tumor infiltrating immune cells and fibroblasts in indicated therapy-treated 4T1 tumors.

    Article Snippet: The primary antibodies used for IF staining includes anti-CD3 antibody (Abcam, ab5690), anti-SMA antibody (Abcam, ab7817) anti-FGFR1 (Cell Signaling Technology, #9740) and anti-VCAM-1 antibody (Abcam, ab134047).

    Techniques: RNA Sequencing Assay

    Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and FGFR-1. (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.

    Journal: Evidence-based Complementary and Alternative Medicine : eCAM

    Article Title: Combination of Ligusticum Chuanxiong and Radix Paeonia Promotes Angiogenesis in Ischemic Myocardium through Notch Signalling and Mobilization of Stem Cells

    doi: 10.1155/2019/7912402

    Figure Lengend Snippet: Expression of angiogenesis and stem cell mobilization proteins. (a) Protein levels of HIF-1 α and FGFR-1. (b) Protein levels of SDF-1, CXCR-4, and cardiotrophin1. (c) Protein levels of Notch1 and NICD. ∗ P <0.05, ∗∗ P <0.01, and ∗∗∗ P <0.001 vs. sham group; $ P <0.05, $$ P <0.01 vs. model group; && P <0.01 vs. CX-CS group. n=3.

    Article Snippet: After incubation with primary antibodies against GAPDH (5174, CST, USA), hypoxia-inducible factor 1-alpha (HIF-1 α ) (36169, CST, USA), FGF Receptor 1 (FGFR-1) (9740, CST, USA), Notch1 (3608, CST, USA), cleaved Notch1 (also named NICD) (4147s, CST), stromal cell-derived factor-1 (SDF-1) (3740, CST, USA), C-X-C chemokine receptor 4 (CXCR-4) (60042-1-1g, Proteintech, USA), and cardiotrophin1 (YT0638, ImmunoWay, USA) at 4°C, the membranes were incubated with a secondary antibody (115-035-003, Jackson, USA) at room temperature for two hours.

    Techniques: Expressing

    The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of Fgfr1 in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm

    Journal: International Journal of Oral Science

    Article Title: Disrupted tenogenesis in masseter as a potential cause of micrognathia

    doi: 10.1038/s41368-022-00196-y

    Figure Lengend Snippet: The immunostaining of FGF signaling and chondrogenic markers in Osr2-cre; Rosa26R-Fgf8 mandibles. a – d The immunostaining of Fgfr1 in the cross sections of E13.5 WT deep ( a ) and superficial masseter levels ( b ), and the Osr2-cre; Rosa26R-Fgf8 deep ( c ) and superficial masseter levels ( d ). e – h The immunostaining of p-Erk1/2 in the cross sections of E13.5 WT deep ( e ) and superficial masseter levels ( f ), and the Osr2-cre; Rosa26R-Fgf8 deep ( g ) and superficial masseter levels ( h ). i – l The immunostaining of Sox9 in the cross sections of E13.5 WT deep ( i ) and superficial masseter levels ( j ), and the Osr2-cre;Rosa26R-Fgf8 deep ( k ) and superficial masseter levels ( l ). m – p The immunostaining of Col II in the cross sections of E16.5 WT deep ( m ) and superficial masseter levels ( o ), and the Osr2-cre; Rosa26R-Fgf8 deep ( n ) and superficial masseter levels ( p ). q – t The immunostaining of Aggrecan in the cross sections of E16.5 WT deep ( q ) and superficial masseter levels ( s ), and the Osr2-cre; Rosa26R-Fgf8 deep ( r ) and superficial masseter levels ( t ). The red dotted lines encircled the masseter tenogenic mesenchyme; the red arrowheads in a – l indicated the positive signals in periosteum of mandibular bones, while the yellow arrowheads pointed to the staining of chondrogenic markers in masseter tendons; the yellow asterisks indicated the positive signals in the mesenchyme adjacent to Meckel’s cartile; Scale bars: 200 μm

    Article Snippet: The sections were blocked in 3% H 2 O 2 and methanol mixture for 20 min, and then, with 10% goat serum (Maixin Ltd., Fuzhou, China) and 0.3% Triton X-100 in PBS for 1 h at room temperature, and incubated overnight at 4 °C with the primary antibodies against p-Erk1/2 (Abcam, Catlog NO. Ab50011, in the dilution of 1:200), phosphorylated-Smad1/5/8 (p-Smad1/5/8, Cell Signaling Technology, Catlog NO. 13820S, in the dilution of 1:200), Sox9 (Abcam, Catlog NO. Ab185966, in the dilution of 1:1 000), Myosin (Zhongshan Golden Bridge, Catlog NO. ZM0196, in the dilution of 1:50), FGF Receptor 1 (Fgfr1, Cell Signaling Technology, Catlog NO. 9740S, in the dilution of 1:400), YAP (Cell Signaling Technology, Catlog NO. 14074T, in the dilution of 1:400), Collagen Type II (Col II, Proteintech, Catlog NO. 28459-1-AP, in the dilution of 1:800), Osterix (OSX, Abcam, Catlog NO. Ab209484, in the dilution of 1:100) and Aggrecan (Proteintech, Catlog NO. 13880-1-AP, in the dilution of 1:1 000), respectively.

    Techniques: Immunostaining, Staining

    Cellular expression of FGFR1 during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).

    Journal: Disease Models & Mechanisms

    Article Title: FGF8–FGFR1 signaling regulates human GnRH neuron differentiation in a time- and dose-dependent manner

    doi: 10.1242/dmm.049436

    Figure Lengend Snippet: Cellular expression of FGFR1 during differentiation to GnRH neurons. (A) Localization of FGFR1 in an FGFR1 - GFP reporter cell line on day 11 of the differentiation protocol. Green, FGFR1-GFP fluorescence; blue, NucBlue™ Live ReadyProbes ™ cell-permeant dye used to counterstain nuclei. Scale bars: 100 μm. (B) Immunostaining of FGFR1 (green) on day 17 (6 days after treatment with FGF8 at 100 ng/ml) of the differentiation experiment, indicating its localization to the cell membrane. Nuclei are shown in blue (DAPI). Scale bars: 20 μm. (C,D) Immunostaining for FGFR1 (red) on day 25 of the differentiation, showing its nuclear localization in neurons, including GnRH neurons (green) is shown C. The boxed area is shown magnified in D, demonstrating the nuclear localization of FGFR1 in a GNRH1 -expressing neuron. Nuclei are shown in blue (DAPI). Scale bars: 10 μm (C), 2 μm (D).

    Article Snippet: Primary antibodies were: rabbit anti-FGFR1 (Cell Signaling Technology, #9740, 1:200), sheep anti-GnRH1 [a gift from Erik Hrabovszky (Laboratory of Reproductive Neurobiology, Institute of Experimental Medicine, Budapest, Hungary), 1:4000] rabbit anti-GnRH1 (Immunostar, #20075, 1:1000), anti-NRP1 (Abcam, #ab81321, rabbit, 1:250), anti-SPRY2 (Santa Cruz, #sc-100862, mouse, 1:150), anti-GSX2 (Merck, #ABN162, rabbit, 1:500), anti-ASCL1 (Santa Cruz, #sc-28688, rabbit, 1:100), anti-FOXG1 (Abcam, #ab182659, rabbit, 1:1000), anti-LHX2 (Thermo Scientific, #MA5-15834, mouse, 1:200), anti-DLX5 (Abcam, #ab109737, rabbit, 1:500) and anti-DCX (Abcam, #ab18723, rabbit, 1:200).

    Techniques: Expressing, Fluorescence, Immunostaining

    Effect of FGFR1 inhibition on the relative gene expression of GNRH1 . (A) Schematic of the differentiation protocol when cells were treated with 100 ng/ml FGF8 alone or with FGF8 and 10 µM of the FGFR1 inhibitor PD166866 (PD); black asterisk, cell splitting; red asterisk, end of differentiation. (B) Bar graphs show the relative levels of GNRH1 RNA obtained from cells at day 25 of the differentiation protocol, after treatment with FGF8 alone or FGF8+PD compared to undifferentiated hPS control cells. ( n =4, * P <0.05; error bars indicate the +standard error of the mean (+s.e.m.).

    Journal: Disease Models & Mechanisms

    Article Title: FGF8–FGFR1 signaling regulates human GnRH neuron differentiation in a time- and dose-dependent manner

    doi: 10.1242/dmm.049436

    Figure Lengend Snippet: Effect of FGFR1 inhibition on the relative gene expression of GNRH1 . (A) Schematic of the differentiation protocol when cells were treated with 100 ng/ml FGF8 alone or with FGF8 and 10 µM of the FGFR1 inhibitor PD166866 (PD); black asterisk, cell splitting; red asterisk, end of differentiation. (B) Bar graphs show the relative levels of GNRH1 RNA obtained from cells at day 25 of the differentiation protocol, after treatment with FGF8 alone or FGF8+PD compared to undifferentiated hPS control cells. ( n =4, * P <0.05; error bars indicate the +standard error of the mean (+s.e.m.).

    Article Snippet: Primary antibodies were: rabbit anti-FGFR1 (Cell Signaling Technology, #9740, 1:200), sheep anti-GnRH1 [a gift from Erik Hrabovszky (Laboratory of Reproductive Neurobiology, Institute of Experimental Medicine, Budapest, Hungary), 1:4000] rabbit anti-GnRH1 (Immunostar, #20075, 1:1000), anti-NRP1 (Abcam, #ab81321, rabbit, 1:250), anti-SPRY2 (Santa Cruz, #sc-100862, mouse, 1:150), anti-GSX2 (Merck, #ABN162, rabbit, 1:500), anti-ASCL1 (Santa Cruz, #sc-28688, rabbit, 1:100), anti-FOXG1 (Abcam, #ab182659, rabbit, 1:1000), anti-LHX2 (Thermo Scientific, #MA5-15834, mouse, 1:200), anti-DLX5 (Abcam, #ab109737, rabbit, 1:500) and anti-DCX (Abcam, #ab18723, rabbit, 1:200).

    Techniques: Inhibition, Expressing

    Analysis of the FGF8–FGFR1 mechanistic network. (A) Venn diagram indicating the 461 differentially expressed genes (DEGs; encircled in red) on day 13 that belong to FGF8–FGFR1 mechanistic networks as identified by IPA. (B) Venn diagram indicating the DEGs (red circle) across all FGF8 treatment time points that belong to FGF8–FGFR1 mechanistic networks as identified by IPA.

    Journal: Disease Models & Mechanisms

    Article Title: FGF8–FGFR1 signaling regulates human GnRH neuron differentiation in a time- and dose-dependent manner

    doi: 10.1242/dmm.049436

    Figure Lengend Snippet: Analysis of the FGF8–FGFR1 mechanistic network. (A) Venn diagram indicating the 461 differentially expressed genes (DEGs; encircled in red) on day 13 that belong to FGF8–FGFR1 mechanistic networks as identified by IPA. (B) Venn diagram indicating the DEGs (red circle) across all FGF8 treatment time points that belong to FGF8–FGFR1 mechanistic networks as identified by IPA.

    Article Snippet: Primary antibodies were: rabbit anti-FGFR1 (Cell Signaling Technology, #9740, 1:200), sheep anti-GnRH1 [a gift from Erik Hrabovszky (Laboratory of Reproductive Neurobiology, Institute of Experimental Medicine, Budapest, Hungary), 1:4000] rabbit anti-GnRH1 (Immunostar, #20075, 1:1000), anti-NRP1 (Abcam, #ab81321, rabbit, 1:250), anti-SPRY2 (Santa Cruz, #sc-100862, mouse, 1:150), anti-GSX2 (Merck, #ABN162, rabbit, 1:500), anti-ASCL1 (Santa Cruz, #sc-28688, rabbit, 1:100), anti-FOXG1 (Abcam, #ab182659, rabbit, 1:1000), anti-LHX2 (Thermo Scientific, #MA5-15834, mouse, 1:200), anti-DLX5 (Abcam, #ab109737, rabbit, 1:500) and anti-DCX (Abcam, #ab18723, rabbit, 1:200).

    Techniques: