antibodies against foxc2 (Bioss)
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Bioss
antibodies against foxc2
Antibodies Against Foxc2, supplied by Bioss, used in various techniques. Bioz Stars score: 93/100, based on 3 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/antibodies+against+foxc2/pmc13067797-123-15-19?v=Bioss
Average 93 stars, based on 3 article reviews
Antibodies Against Foxc2, supplied by Bioss, used in various techniques. Bioz Stars score: 93/100, based on 3 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/antibodies+against+foxc2/pmc13067797-123-15-19?v=Bioss
Average 93 stars, based on 3 article reviews
antibodies against foxc2 - by Bioz Stars,
2026-08
93/100 stars
Images
1) Product Images from "The FOXC2‐LAMA4 Axis Orchestrates Vasculogenic Mimicry and Immunosuppressive Niche Formation to Drive Metastatic Cascade in Renal Cell Carcinoma"
Article Title: The FOXC2‐LAMA4 Axis Orchestrates Vasculogenic Mimicry and Immunosuppressive Niche Formation to Drive Metastatic Cascade in Renal Cell Carcinoma
Journal: Advanced Science
doi: 10.1002/advs.202516382
Figure Legend Snippet: Spatial transcriptomics reveals the significant association of the Epithelial_s4 subpopulation with VM in renal cell carcinoma. (A),(B) Single‐cell data analysis demonstrates marked activation of VM pathways in the Epithelial_s4 subpopulation, significantly higher than in other subpopulations. (C) Gene Set Enrichment Analysis (GSEA) indicates significant enrichment of tube formation‐related pathways in the Epithelial_s4 subpopulation. (D) Spatial mapping and region‐specific analysis for 10 ccRCC patients. For each patient, the spatial analysis is comprised of four panels: the upper left section displays the dimensionality reduction and clustering results of spatial spots (Seurat_clusters), the identification of Tumor_region and Normal_region (Spatial_region), and the spatial enrichment patterns of FOXC2_Regulon, EMT, VM, and Epithelial_s4; the lower left panel includes a DotPlot showing the expression of key ccRCC marker genes (EPCAM, SLC17A3, NDUFA4L2, PAX8) across different spatial spot clusters, alongside violin plots depicting the distribution of Epithelial_s4 and Epithelial_other scores from RCTD deconvolution within these clusters; the right section visualizes the correlation matrices of pathway scores among spatial spots within the defined Tumor_region and Normal_region. (E) A heatmap demonstrating that the enrichment scores for FOXC2_Regulon, EMT, VM, and Epithelial_s4 are significantly higher in the Tumor_region compared to the Normal_region. (F) Correlation analysis of FOXC2_Regulon, EMT, VM, Epithelial_s4, and Epithelial_other was performed separately in the Tumor_region and Normal_region after merging spatial spots data from all 10 patients. (G)–(I) Patient‐level analysis of pathway co‐activation. The average activation scores for FOXC2_Regulon, EMT, and VM were calculated per patient within the Tumor_region and Normal_region, respectively. Their associations are displayed as Pearson correlation scatter plots. The correlation strength for each pair of pathways is markedly higher in the Tumor_region than in the Normal_region.
Techniques Used: Spatial Transcriptomics, Single Cell, Activation Assay, Expressing, Marker
Figure Legend Snippet: Multi‐dimensional analyses identify FOXC2 as the key transcription factor in the Epithelial_s4 subpopulation. (A) Integration of scRNA‐seq data into pseudobulk metacells via neighboring cell clustering to mitigate sparsity in the single‐cell matrix. Clustering results align with those from the original single‐cell data. (B),(C) scWGCNA analysis identifies 14 gene modules, with the salmon module showing significant correlation with the Epithelial_s4 subpopulation (cor = 0.67, p < 0.001). (D) GO and KEGG analyses reveal that the salmon module is enriched in biological processes such as tube formation and epithelial‐mesenchymal transition (EMT). (E) Co‐expression network of the salmon gene module. (F) Volcano plot of differentially expressed genes between Epithelial_s4 and other tumor subpopulations, highlighting FOXC2 as significantly upregulated in Epithelial_s4. (G) pySCENIC heatmap of highly activated transcription factors across tumor subpopulations, with FOXC2 being the most activated in Epithelial_s4. (H) pySCENIC analysis demonstrates specific activation of the transcription factor FOXC2 in the Epithelial_s4 subpopulation. (I) Transcription factor activity and gene expression levels of FOXC2 are significantly elevated in Epithelial_s4. (J) TCGA data confirm higher FOXC2 expression levels in renal carcinoma.
Techniques Used: Single Cell, Expressing, Activation Assay, Activity Assay, Gene Expression
Figure Legend Snippet: Experimental evidence elucidates the role of FOXC2 in regulating EMT and VM processes in ccRCC. (A) IHC analysis and quantitative comparison of FOXC2 protein expression in primary (n=16) vs. metastatic (n=15) ccRCC tissues ( ** p < 0.01; original magnification ×200). (B) Establishment of FOXC2 knockdown models in 786‐O and OSCR‐2 cell lines, with Western blot validation of knockdown efficiency (sh‐Ctrl vs. sh‐FOXC2). (C) qPCR analysis of FOXC2 knockout effects on mRNA levels of EMT‐related genes (FOXC2, E‐cadherin, N‐cadherin, Vimentin, FN1, Slug, and α‐SMA) (n=3; ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001). (D) Western blot analysis of core EMT markers (FOXC2, E‐cadherin, N‐cadherin, Vimentin) in wild‐type (WT), control (sh‐Ctrl), and FOXC2‐knockdown (sh‐FOXC2) groups. (E),(F) Transwell invasion assays showing suppressed invasive capacity of ccRCC cells upon sh‐FOXC2 group (n=3; *** p < 0.001). (G),(H) Wound healing assays confirming significantly reduced migration ability in sh‐FOXC2 group (n=3; ** p < 0.001). (I) Representative images of tube formation assays performed with 786‐O cells embedded in Matrigel. Cells were transfected with control shRNA (sh‐Ctrl), FOXC2‐targeting shRNA (sh‐FOXC2), or subjected to a rescue treatment with FOXC2 overexpression in the knockdown background (sh‐FOXC2 OE‐FOXC2). The number of tubes was quantified (ns: not significant, ** p < 0.01, *** p < 0.001). (J) Western blot analysis of FOXC2 and VE‐cadherin across three groups. (K) Serial section staining of metastatic vs. primary ccRCC tissues: FOXC2 IHC and CD31/PAS double staining illustrating vasculogenic mimicry distribution (original magnification ×200).
Techniques Used: Comparison, Expressing, Knockdown, Western Blot, Biomarker Discovery, Knock-Out, Control, Migration, Transfection, shRNA, Over Expression, Staining, Double Staining
Figure Legend Snippet: Multi‐omics sequencing identifies LAMA4 as a key downstream effector of FOXC2. (A) Genome‐wide binding signal heatmap of FOXC2 CUT&Tag sequencing in 786‐O cells (FOXC2 vs. IgG). (B) Distribution of FOXC2 binding peaks across the genome and motif analysis of its promoter‐bound sequences in 786‐O cells. (C) Venn diagram intersecting differentially expressed genes (log2FC > 1) upon FOXC2 knockdown, FOXC2‐bound downstream genes, and Epithelial_s4 subpopulation‐enriched genes, identifying LAMA4 and VAV3 as potential FOXC2 transcriptional targets. (D) GO/KEGG functional enrichment analysis of genes with FOXC2 binding peaks from CUT&Tag sequencing. (E) GO/KEGG functional enrichment analysis of RNA‐seq differentially expressed genes in FOXC2 knockdown vs. control groups. (F) CUT&Tag sequencing reveals a specific FOXC2 binding site (highlighted in dark yellow) within the upstream promoter region of the LAMA4 gene. (G) RNA‐seq data from 786‐O cells validate LAMA4 as a FOXC2‐regulated differentially expressed gene. (H) TCGA‐KIRC dataset analysis demonstrates a significant positive correlation between FOXC2 and LAMA4 mRNA expression (R = 0.527, ** p < 0.01). (I)–(K) scRNA data show significant co‐expression of FOXC2 and LAMA4 in the Epithelial_s4 subpopulation. (L) scRNA data from 12 ccRCC patients confirm a robust expression correlation between tumor cell‐derived FOXC2 and LAMA4 (R = 0.630, * p < 0.05). (M) Western blot analysis of FOXC2 and LAMA4 protein levels in paired tumor and adjacent normal tissues from ccRCC patients. (N) Positive correlation between FOXC2 and LAMA4 protein expression. Protein levels were quantified by western blot (n=9; * p < 0.05, ** p < 0.01). A significant correlation was found by Spearman analysis (R = 0.717, p = 0.037).
Techniques Used: Biomarker Discovery, Sequencing, Genome Wide, Binding Assay, Knockdown, Functional Assay, RNA Sequencing, Control, Expressing, Derivative Assay, Western Blot
Figure Legend Snippet: FOXC2 promotes VM in ccRCC cells by transcriptionally regulating LAMA4. (A) Western blot analysis of LAMA4 protein expression upon FOXC2 knockdown. (B) qPCR detection of LAMA4 mRNA levels following FOXC2 knockdown (n=3; ** p < 0.01, *** p < 0.001). (C) Western blot analysis of FOXC2, LAMA4, VE‑cadherin, and the EMT markers E‑cadherin, N‑cadherin, and Vimentin in FOXC2‑overexpressing (OE‐ FOXC2) and LAMA4‑knockdown (sh‐LAMA4) cell models. (D) Tube formation assays demonstrate that FOXC2 overexpression significantly enhances VM capacity in renal cancer cells, while LAMA4 knockdown partially reverses this effect (n=3; *** p < 0.001). (E) Transwell invasion assays reveal that FOXC2 overexpression promotes cancer cell invasion, which is suppressed by LAMA4 knockdown (n=3; ** p < 0.01, *** p < 0.001). (F) Wound healing assays confirm that FOXC2 overexpression increases cell migration, an effect attenuated by LAMA4 knockdown (n=3; *** p < 0.001). 0.001). (G) Statistical analysis was performed on the following metrics: tube formation (number of tubes, branches, junctions, meshes, and total length), wound healing (wound healing percentage), and Transwell (number of migrated cells). ns: not significant, * p < 0.05, ** p < 0.01, *** p < 0.001. (H) Luciferase reporter assays using LAMA4 promoter truncations transfected into renal cancer cells. FOXC2 regulates promoter activity across distinct LAMA4 promoter regions (n=3; ns p > 0.05, *** p < 0.001). (I) ChIP with FOXC2 antibody followed by qPCR amplification of LAMA4 promoter fragments (site1–site4) (n=3; ns p > 0.05, ** p < 0.01). (J) Luciferase assays comparing wild‐type and site2‐mutated LAMA4 promoter activity in renal cancer cells. FOXC2 selectively regulates wild‐type promoter activity (n=3; ns p > 0.05, *** p < 0.001).
Techniques Used: Western Blot, Expressing, Knockdown, Over Expression, Migration, Luciferase, Transfection, Activity Assay, Amplification
Figure Legend Snippet: FOXC2‐LAMA4 remodels the metastatic microenvironment by promoting TREM2 + CD206 + MAM polarization in pulmonary metastases. (A) Experimental design and grouping for orthotopic renal carcinoma xenografts. (B) In vivo imaging system dynamically monitors renal orthotopic tumor growth (days 7, 14, 21, 28) and lung metastasis formation (terminal imaging at day 28) across groups. (C) Comparison of renal tumor volumes at the experimental endpoint among groups. (D) Lung metastasis imaging and H&E staining validation in the Foxc2 overexpression group (Foxc2 OE Lama4 NC ) vs. Foxc2 overexpression + LAMA4 knockdown group (Foxc2 OE Lama4 KD ). (E) Dimensionality reduction and cell type annotation of scRNA data from lung tissues of Foxc2 OE Lama4 NC and Foxc2 OE Lama4 KD mice. (F) Heatmap of MAMs signature genes showing upregulated immunosuppressive markers (e.g., Trem2, Arg1) (log2FC >1, * p < 0.05). (G) Tissue preference analysis (R/oe score) highlights significant enrichment of MAMs (red arrow) in the Foxc2 OE Lama4 NC group. (H),(I) Flow cytometry analysis of the effect of LAMA4 on inducing immunosuppressive polarization. Shown is the MFI of CD206 (H) within the CD68 + population for human THP1‑derived macrophages and (I) within the CD11b + F4/80 + population for mouse BMDMs following treatment with LAMA4. Untreated cells and IL‑4‑treated cells served as negative and positive controls, respectively (n = 3, **** p < 0.0001). (J) scRNA data from ccRCC lung metastases show high LAMA4 expression and elevated Trem2 + macrophage markers (TREM2, C1QC, APOE, CD163) in GPNMB‐Hi and FOLR2‐Hi macrophages. (K) scRNA of murine lung metastases: Macrophages in the oeFoxc2 ncLama4 group exhibit higher M2 markers, while T cells display pronounced exhaustion markers. (L),(M) Flow cytometry analysis of immune cell phenotypes in lung metastases from the orthotopic kidney cancer model. (L) Proportion of exhausted (CD8a + PD‑1 + ) CD8 + T cells. (M) MFI of TREM2 on macrophages. Comparisons are between the FOXC2 OE LAMA4 NC and FOXC2 OE LAMA4 KD groups (n = 5). ( ** p < 0.01, *** p < 0.001).
Techniques Used: In Vivo Imaging, Imaging, Comparison, Staining, Biomarker Discovery, Over Expression, Knockdown, Flow Cytometry, Expressing
Figure Legend Snippet: LAMA4‐ITGA6 binding activates STAT6 phosphorylation to drive GATA3‐dependent TREM2 + CD206 + MAM polarization, promoting metastatic outgrowth. (A) Schematic representation of the experimental setup to investigate the role of LAMA4 in macrophage polarization. THP‐1 cells were treated with PMA to differentiate into macrophages, followed by stimulation with LAMA4 (5 ng/mL). (B) Volcano plot comparing gene expression profiles between control and LAMA4‐treated THP‐1 macrophages. Red dots indicate upregulated genes; blue dots indicate downregulated genes. GATA3 was highly expressed in the LAMA4 treatment group. (C) Heatmap showing DEGs between control and LAMA4‐treated THP‐1 macrophages. Upregulated and downregulated genes are represented in red and blue, respectively. CXCL2, CXCL1, and TNF (inflammatory factors) exhibited elevated expression in controls, whereas ARG1, GATA3, and HES3 (immunosuppressive markers) showed significant upregulation in LAMA4‐treated macrophages. (D) GSEA demonstrating LAMA4‐mediated upregulation of the Fatty Acid Metabolic signaling pathway and downregulation of the TNF/NF‐κB signaling signaling pathway. (E) Pseudotime trajectory constructed by Monocle revealed that MAMs are derived from monocytes/macrophages (Mono/Mac) in mouse lung metastatic niches. (F) SCENIC analysis revealed heightened Gata3 regulon activity score (Gata3 RAS) enriched in MAMs, with concurrent elevation of Gata3 activity in Mono/Mac from oeFOXC2_ncLama4 mice group. (G) Cell‐cell communication analysis indicated that tumor cells in the oeFOXC2_ncLama4 group release enhanced LAMININ signals, which significantly activate downstream pathways in monocytes/macrophages (Mono/Mac), suggesting LAMA4‐mediated LAMININ signaling drives Mono/Mac differentiation into MAMs via specific receptor engagement. (H) Western blot analysis confirmed significant downregulation of GATA3 protein following siRNA‐mediated silencing, with concomitant reduction in TREM2 and CD206 expression. (I) Western blot analysis demonstrated that escalating LAMA4 concentrations (0, 1, 5, 25 ng/mL) induced progressive upregulation of immunosuppressive markers CD206 and TREM2 in macrophages. (J) Molecular docking of human and murine LAMA4 with ITGA6 reveals conserved binding capacity. Structures depict ITGA6 (cyan cartoon; extracellular domain in yellow) and LAMA4 (blue cartoon). (K) Comparative analysis of Itga6 expression in Mono/Mac and MAM populations within lung metastases revealed significantly elevated levels in oeFoxc2_ncLama4 vs. oeFoxc2_kdLama4 cohorts, suggesting enhanced responsiveness to LAMA4‐mediated signaling. (L) Validation of the interaction between LAMA4 and ITGA6. Lysates from co‐cultures of 786‐O renal carcinoma cells and THP‐1 macrophages were subjected to Co‐IP using an anti‐LAMA4 antibody, followed by immunoblotting with an anti‐ITGA6 antibody to confirm their direct binding.(M) FOXC2 knockdown attenuates the LAMA4‐ITGA6 interaction. Co‐IP was performed on lysates from co‐cultures of THP‐1 macrophages with 786‐O cells stably expressing either sh‐Ctrl or sh‐FOXC2, using an anti‐LAMA4 antibody. Western blot analysis for ITGA6 shows reduced complex formation upon FOXC2 knockdown. (N) STAT6‐neutralizing antibody (anti‐ ITGA6 Ab, 5 µg/mL) treatment significantly blocked LAMA4 (25 ng/mL)‐induced upregulation of p‐STAT6, GATA3, TREM2, and CD206 proteins in Western blot analysis. (O) In vivo imaging of orthotopic Renca‐luciferase Foxc2‐overexpressing (Renca‐luc Foxc2 oe ) renal tumors in BALB/c mice treated with ITGA6‐neutralizing antibody (10 mg/kg, i.v., weekly) vs. Rat‐IgG control, showing differential tumor progression and metastatic burden at days 7, 14, and 28 post‐implantations.
Techniques Used: Binding Assay, Phospho-proteomics, Gene Expression, Control, Expressing, Construct, Derivative Assay, Activity Assay, Western Blot, Biomarker Discovery, Co-Immunoprecipitation Assay, Knockdown, Stable Transfection, In Vivo Imaging, Luciferase
