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mouse ccn4 quantikine elisa development kit (R&D Systems)

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R&D Systems mouse ccn4 quantikine elisa development kit

<t>CCN4</t> concentration as quantified by ELISA in media conditioned for 48 hours by WT Py230 and Py8119 cells and two independent CCN4 KO variants for each parental cell line. Cell-free media was used as a negative control and media conditioned by B16F0 cells was used as a positive control. Individual data points represent technical replicates and values reported below quantification threshold are indicated as n.d.

Mouse Ccn4 Quantikine Elisa Development Kit, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 10 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 94 stars, based on 10 article reviews

mouse ccn4 quantikine elisa development kit - by Bioz Stars, 2026-05

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1) Product Images from "Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer"

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

Journal: bioRxiv

doi: 10.64898/2026.01.07.698253

CCN4 concentration as quantified by ELISA in media conditioned for 48 hours by WT Py230 and Py8119 cells and two independent CCN4 KO variants for each parental cell line. Cell-free media was used as a negative control and media conditioned by B16F0 cells was used as a positive control. Individual data points represent technical replicates and values reported below quantification threshold are indicated as n.d.

Figure Legend Snippet: CCN4 concentration as quantified by ELISA in media conditioned for 48 hours by WT Py230 and Py8119 cells and two independent CCN4 KO variants for each parental cell line. Cell-free media was used as a negative control and media conditioned by B16F0 cells was used as a positive control. Individual data points represent technical replicates and values reported below quantification threshold are indicated as n.d.

Techniques Used: Concentration Assay, Enzyme-linked Immunosorbent Assay, Negative Control, Positive Control

Kaplan-Meier time-to-event survival curves for immunocompetent C57BL/6 mice (B and D) and severely immunocompromised NSG mice (A and C) challenged subcutaneously with wild-type (black curves) and two CCN4 KO variants (KO1 in blue and KO2 in dotted red curves) derived from Py8119 (A and B) and Py230 (C and D) cell lines. The tumor size exceeding 100 mm 3 was considered the triggering event. The number of animals that experienced a triggering event among the total number of animals challenged with tumor cells is indicated in the legend. Statistical difference among the three curves was assessed using a Peto & Peto Modification the Gehan-Wilcoxon test with the resulting Chi-squared, degrees of freedom and resulting P-values are indicated. As this was an exploratory study, the p-values indicate the extent to which these three Kaplan-Meier survival curves are different.

Figure Legend Snippet: Kaplan-Meier time-to-event survival curves for immunocompetent C57BL/6 mice (B and D) and severely immunocompromised NSG mice (A and C) challenged subcutaneously with wild-type (black curves) and two CCN4 KO variants (KO1 in blue and KO2 in dotted red curves) derived from Py8119 (A and B) and Py230 (C and D) cell lines. The tumor size exceeding 100 mm 3 was considered the triggering event. The number of animals that experienced a triggering event among the total number of animals challenged with tumor cells is indicated in the legend. Statistical difference among the three curves was assessed using a Peto & Peto Modification the Gehan-Wilcoxon test with the resulting Chi-squared, degrees of freedom and resulting P-values are indicated. As this was an exploratory study, the p-values indicate the extent to which these three Kaplan-Meier survival curves are different.

Techniques Used: Derivative Assay, Modification

(A) Box-and-whisker plots for spleen weights obtained from C57BL/6 mice challenged with WT Py230 cells and CCN4 KO variants In a time-matched experimental design with the end point at 69 days (n = 5 for each group). (B) Spleen weights and corresponding excised tumor weights obtained from C57BL/6 mice challenged with WT Py8119 cells and CCN4 KO variants in a size-matched experimental design (n = 5 for each group). As there was no statistical difference between CCN4 KO variants, results were combined for analysis. A homoscedastic two-sided Student’s t-test was used to assess statistical significance.

Figure Legend Snippet: (A) Box-and-whisker plots for spleen weights obtained from C57BL/6 mice challenged with WT Py230 cells and CCN4 KO variants In a time-matched experimental design with the end point at 69 days (n = 5 for each group). (B) Spleen weights and corresponding excised tumor weights obtained from C57BL/6 mice challenged with WT Py8119 cells and CCN4 KO variants in a size-matched experimental design (n = 5 for each group). As there was no statistical difference between CCN4 KO variants, results were combined for analysis. A homoscedastic two-sided Student’s t-test was used to assess statistical significance.

Techniques Used: Whisker Assay

Following enzymatic dissociation of tumor tissues, the immune cell compartment was quantified by full spectrum flow cytometry. A self-organizing map shows the distribution of negative Live/Dead violet and positive CD45 cells in size-matched WT (left) and CCN4 KO1 (center) tumors (n = 5 for both WT and CCN4 KO1 Py230). Right panel shows the percentage of events associated with each cluster that relate to cells identified by manual gating.

Figure Legend Snippet: Following enzymatic dissociation of tumor tissues, the immune cell compartment was quantified by full spectrum flow cytometry. A self-organizing map shows the distribution of negative Live/Dead violet and positive CD45 cells in size-matched WT (left) and CCN4 KO1 (center) tumors (n = 5 for both WT and CCN4 KO1 Py230). Right panel shows the percentage of events associated with each cluster that relate to cells identified by manual gating.

Techniques Used: Flow Cytometry

$In a size-matched experimental design, the tumor-infiltrating lymphocytes were quantified by flow cytometry using antibody panels focused on the T cell (A, B, and C) and the myeloid (D, E, and F) compartments. Mice received either WT Py8119 cells (black circles) or one of two independently generated CCN4 KO variants (red + and blue x, n = 5 for all groups). Results highlight the CD45+ fraction among total Live events measured using the T cell (A) and myeloid (D) panels. The proportion of infiltrating CD4+ T cells within the live CD45+ compartment (B) was not different but the CD25+ fraction of live CD4+ T cells (C) was increased in CCN4 KO tumors. The MDSC compartment was shifted from PMN-MDSC (E, Live CD45+ CD11b+ Ly6G+ Ly6C int events) to Mo-MDSC (F, Live CD45+ CD11b+ Ly6G-Ly6C+ events) upon CCN4 KO. p-values calculated between WT and pooled CCN4 KOs using two-sided Student’s t test.$
Figure Legend Snippet: In a size-matched experimental design, the tumor-infiltrating lymphocytes were quantified by flow cytometry using antibody panels focused on the T cell (A, B, and C) and the myeloid (D, E, and F) compartments. Mice received either WT Py8119 cells (black circles) or one of two independently generated CCN4 KO variants (red + and blue x, n = 5 for all groups). Results highlight the CD45+ fraction among total Live events measured using the T cell (A) and myeloid (D) panels. The proportion of infiltrating CD4+ T cells within the live CD45+ compartment (B) was not different but the CD25+ fraction of live CD4+ T cells (C) was increased in CCN4 KO tumors. The MDSC compartment was shifted from PMN-MDSC (E, Live CD45+ CD11b+ Ly6G+ Ly6C int events) to Mo-MDSC (F, Live CD45+ CD11b+ Ly6G-Ly6C+ events) upon CCN4 KO. p-values calculated between WT and pooled CCN4 KOs using two-sided Student’s t test.

Techniques Used: Flow Cytometry, Generated

Results from R&D Systems’ Mouse XL Cytokine Array Kit of cytokine, chemokine, and growth factor expression by WT versus CCN4 KO cells derived from Py8119 (A) and Py230 (B) lines in vitro . (C) Compares the WT profiles between the Py8119 and Py230 cell lines. In presenting the combined results for assaying each cell line’s secretome using a single biological replicate, open circles represent results for specific cytokine probes, which are spotted in duplicate on the array, and filled circles represent positive and negative controls. Dotted red lines indicate Z-scores of 3 and −3. Particular secreted factors that are differentially expressed are annotated with their respective names.

Figure Legend Snippet: Results from R&D Systems’ Mouse XL Cytokine Array Kit of cytokine, chemokine, and growth factor expression by WT versus CCN4 KO cells derived from Py8119 (A) and Py230 (B) lines in vitro . (C) Compares the WT profiles between the Py8119 and Py230 cell lines. In presenting the combined results for assaying each cell line’s secretome using a single biological replicate, open circles represent results for specific cytokine probes, which are spotted in duplicate on the array, and filled circles represent positive and negative controls. Dotted red lines indicate Z-scores of 3 and −3. Particular secreted factors that are differentially expressed are annotated with their respective names.

Techniques Used: Expressing, Derivative Assay, In Vitro

(A) Projections of WT versus CCN4 KO variants along PC1 and PC2 axes for B16F0, YUMM1.7, Py230, and Py8119 cell lines. The location of duplicates of each cell line label correspond to technical replicates on the array. The percentage of variance explained by each principal component is indicated in the axis label. (B) Projection of the measured proteins based on the loading scores associated with PC1 (y-axis) listed from left to right in alphabetical order. The curves on the right represent the density distribution of the PC1 loading scores (black) and a normal distribution centered at −0.091 with a standard deviation of 0.00074 (red).

Figure Legend Snippet: (A) Projections of WT versus CCN4 KO variants along PC1 and PC2 axes for B16F0, YUMM1.7, Py230, and Py8119 cell lines. The location of duplicates of each cell line label correspond to technical replicates on the array. The percentage of variance explained by each principal component is indicated in the axis label. (B) Projection of the measured proteins based on the loading scores associated with PC1 (y-axis) listed from left to right in alphabetical order. The curves on the right represent the density distribution of the PC1 loading scores (black) and a normal distribution centered at −0.091 with a standard deviation of 0.00074 (red).

Techniques Used: Standard Deviation

(A) Schematic diagram of the network topology associated with the adherens pathway activity of beta-catenin. Adherens junctions are formed by homotypic interactions between the extracellular cadherin domains of a single pass transmembrane protein E-cadherin (E-cad: blue double oval). The cytoplasmic tail of E-cadherin provides a scaffold for a multi-protein complex that includes beta-catenin ( β -cat: red oval). (B) Upon the proteolytic cleavage of adherens junctions, a cytoplasmic fragment of E-cadherin and associated catenins (tBE) are transported to the cytoplasm. In the cytoplasm, the cytoplasmic fragment of E-cadherin and associated catenins can either enter the nucleus or undergo proteasomal degradation. In the nucleus, this multi-protein complex promotes the transcription and translation of CCN4, beta-catenin, and E-cadherin, among other factors. mRNA is represented by light green parallelogram. Once synthesized, CCN4 (light blue circle) is secreted. Newly synthesized beta-catenin and E-cadherin reform the multi-protein complex and are transported to the cell membrane to re-establish adherens junctions. If no E-cadherin binding sites are present, the multi-protein complex is internalized and degraded. (C) Graphical summary of mutations that include both changes in single nucleotides and in copy numbers for breast invasive carcinoma (TCGA, Cell 2015) samples. Of the 816 samples contained in the dataset obtained through cBioPortal (retrieved 11/10/2025), the queried genes are altered in 336 (41%) of the samples.

Figure Legend Snippet: (A) Schematic diagram of the network topology associated with the adherens pathway activity of beta-catenin. Adherens junctions are formed by homotypic interactions between the extracellular cadherin domains of a single pass transmembrane protein E-cadherin (E-cad: blue double oval). The cytoplasmic tail of E-cadherin provides a scaffold for a multi-protein complex that includes beta-catenin ( β -cat: red oval). (B) Upon the proteolytic cleavage of adherens junctions, a cytoplasmic fragment of E-cadherin and associated catenins (tBE) are transported to the cytoplasm. In the cytoplasm, the cytoplasmic fragment of E-cadherin and associated catenins can either enter the nucleus or undergo proteasomal degradation. In the nucleus, this multi-protein complex promotes the transcription and translation of CCN4, beta-catenin, and E-cadherin, among other factors. mRNA is represented by light green parallelogram. Once synthesized, CCN4 (light blue circle) is secreted. Newly synthesized beta-catenin and E-cadherin reform the multi-protein complex and are transported to the cell membrane to re-establish adherens junctions. If no E-cadherin binding sites are present, the multi-protein complex is internalized and degraded. (C) Graphical summary of mutations that include both changes in single nucleotides and in copy numbers for breast invasive carcinoma (TCGA, Cell 2015) samples. Of the 816 samples contained in the dataset obtained through cBioPortal (retrieved 11/10/2025), the queried genes are altered in 336 (41%) of the samples.

Techniques Used: Activity Assay, Synthesized, Membrane, Binding Assay

Image Search Results

Differential expression of WISP1 in normal and tumor tissue samples. (A) Expression of WISP1 in pan-cancer tissues and adjacent normal tissues via TIMER2.0. (B) Expression levels of WISP1 in ESCA from GEPIA2 (|Log2FC|> 1, P < 0.01, log scale: log2 (TPM + 1), Jitter Size: 0.4; T: Tumor, N: Normal). (C) Expression of WISP1 mRNA in the ESCC dataset. (D–G) Results of IHC and WB analyses using 12 paired ESCC tissues and adjacent control samples (T: Tumor, N: Normal; scale bars = 100μm). (H) ROC curves predicting the prognostic ability of high WISP1 expression for 1-year, 3-year, and 5-year patient survival. *p < 0.05; **p < 0.01; ***p < 0.001,;****P < 0.0001.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Differential expression of WISP1 in normal and tumor tissue samples. (A) Expression of WISP1 in pan-cancer tissues and adjacent normal tissues via TIMER2.0. (B) Expression levels of WISP1 in ESCA from GEPIA2 (|Log2FC|> 1, P < 0.01, log scale: log2 (TPM + 1), Jitter Size: 0.4; T: Tumor, N: Normal). (C) Expression of WISP1 mRNA in the ESCC dataset. (D–G) Results of IHC and WB analyses using 12 paired ESCC tissues and adjacent control samples (T: Tumor, N: Normal; scale bars = 100μm). (H) ROC curves predicting the prognostic ability of high WISP1 expression for 1-year, 3-year, and 5-year patient survival. *p < 0.05; **p < 0.01; ***p < 0.001,;****P < 0.0001.

Article Snippet: Primary fibroblasts were infected with shWISP1 lentivirus or treated with recombinant human WISP1 (rhWISP1) protein( NP_003873.1 , Sino Biological, China; endotoxin level <0.1 EU/μg, as determined by Limulus Amebocyte Lysate assay), followed by three washes with PBS.

Techniques: Quantitative Proteomics, Expressing, Control

The impact of WISP1 expression on the survival of ESCC patients. (A–C) Kaplan-Meier analysis of overall survival for high-expression versus low-expression groups in the datasets GSE53624 , GSE53625 , and TCGA. (D–F) Time-dependent ROC analysis for patients in the datasets.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: The impact of WISP1 expression on the survival of ESCC patients. (A–C) Kaplan-Meier analysis of overall survival for high-expression versus low-expression groups in the datasets GSE53624 , GSE53625 , and TCGA. (D–F) Time-dependent ROC analysis for patients in the datasets.

Techniques: Expressing

Identification of DEGs in ESCC, functional enrichment analysis, and functional annotation of WISP1. (A) Volcano plot shows the DEGs from four datasets. (B) A Venn diagram shows genes that are differentially expressed across all four datasets. (C) GO and KEGG analyses reveal the potential biological mechanisms of DEGs in the four datasets. (D, E) GeneMANIA and STRING databases identify target proteins and genes associated with WISP1, followed by enrichment analysis of the functions of these proteins and genes. (F) Visualization of enrichment analysis results.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Identification of DEGs in ESCC, functional enrichment analysis, and functional annotation of WISP1. (A) Volcano plot shows the DEGs from four datasets. (B) A Venn diagram shows genes that are differentially expressed across all four datasets. (C) GO and KEGG analyses reveal the potential biological mechanisms of DEGs in the four datasets. (D, E) GeneMANIA and STRING databases identify target proteins and genes associated with WISP1, followed by enrichment analysis of the functions of these proteins and genes. (F) Visualization of enrichment analysis results.

Techniques: Functional Assay

Tumor microenvironment and immune cell infiltration analysis in the GSE53624 dataset. (A) Differences in the abundance of infiltrating immune cells between high-expression and low-expression groups. (B–D) Differences in stromal scores, immune scores, and estimate scores between high-expression and low-expression groups. (E) Evaluation of the expression of immune checkpoint molecules (CD274, PDCD1, TIGIT, CD276, CTLA4, LAG3) between high-risk and low-risk groups. (F) Correlation between WISP1 expression and immune checkpoint molecules (CD274, PDCD1, TIGIT, CD276, CTLA4, LAG3). Blue indicates positive correlation, red indicates negative correlation, and the numbers inside the boxes represent the magnitude of the correlation. *p < 0.05; **p < 0.01; ***p < 0.001; ****P < 0.0001.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Tumor microenvironment and immune cell infiltration analysis in the GSE53624 dataset. (A) Differences in the abundance of infiltrating immune cells between high-expression and low-expression groups. (B–D) Differences in stromal scores, immune scores, and estimate scores between high-expression and low-expression groups. (E) Evaluation of the expression of immune checkpoint molecules (CD274, PDCD1, TIGIT, CD276, CTLA4, LAG3) between high-risk and low-risk groups. (F) Correlation between WISP1 expression and immune checkpoint molecules (CD274, PDCD1, TIGIT, CD276, CTLA4, LAG3). Blue indicates positive correlation, red indicates negative correlation, and the numbers inside the boxes represent the magnitude of the correlation. *p < 0.05; **p < 0.01; ***p < 0.001; ****P < 0.0001.

Techniques: Expressing

Gene set enrichment analysis (GSEA) of hallmark pathways for esophageal squamous cell carcinoma (ESCC) patients stratified by WISP1 expression levels. (A–C) Enrichment patterns of associated pathways in the GSE53624 , GSE53625 , and TCGA datasets. The analyses were evaluated using a significance threshold corrected for the False Discovery Rate (FDR).

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Gene set enrichment analysis (GSEA) of hallmark pathways for esophageal squamous cell carcinoma (ESCC) patients stratified by WISP1 expression levels. (A–C) Enrichment patterns of associated pathways in the GSE53624 , GSE53625 , and TCGA datasets. The analyses were evaluated using a significance threshold corrected for the False Discovery Rate (FDR).

Techniques: Expressing

Computational prediction of drug sensitivity for ESCC patients stratified by WISP1 expression levels. Using WISP1 expression grouping derived from the GSE53624 dataset, the “oncoPredict” R package was employed to evaluate the drug response spectrum. **** indicates statistical significance at p < 0.0001.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Computational prediction of drug sensitivity for ESCC patients stratified by WISP1 expression levels. Using WISP1 expression grouping derived from the GSE53624 dataset, the “oncoPredict” R package was employed to evaluate the drug response spectrum. **** indicates statistical significance at p < 0.0001.

Techniques: Expressing, Derivative Assay

Functional characterization of WISP1 in a subpopulation of fibroblasts. (A) Gene Set Enrichment Analysis (GSEA) shows enrichment results of differentially expressed genes between WISP1_Fib_Negative and WISP1_Fib_Positive clusters within the c5.all.v2024.1.Hs.symbols gene set; (B, C) display the enrichment results of DEGs in the h.all.v7.1.symbols gene set. (D) Proportional distribution of WISP1_Fib_Negative and WISP1_Fib_Positive clusters in normal esophageal tissues and ESCC samples. (E, F) Comparative analysis of intercellular communication signal intensity among fibroblast subpopulations. (G, H) Molecular stratification of fibroblasts using lineage-specific markers (DCN/Decorin, IGFBP6/Insulin Like Growth Factor Binding Protein 6, MFAP5/Microfibril Associated Protein 5, ACTA2/Actin Alpha 2 Smooth Muscle, TAGLN/Transgelin, CTHRC1/Collagen Triple Helix Repeat Containing 1)into NFs and CAFs subtypes. (I) Validation of CAF-specific markers (FAP, COL1A1, COL3A1, COL4A1, COL10A1, MMP1, MMP11, MMP14) and expression patterns of WISP1 in CAFs via single-cell RNA sequencing.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: Functional characterization of WISP1 in a subpopulation of fibroblasts. (A) Gene Set Enrichment Analysis (GSEA) shows enrichment results of differentially expressed genes between WISP1_Fib_Negative and WISP1_Fib_Positive clusters within the c5.all.v2024.1.Hs.symbols gene set; (B, C) display the enrichment results of DEGs in the h.all.v7.1.symbols gene set. (D) Proportional distribution of WISP1_Fib_Negative and WISP1_Fib_Positive clusters in normal esophageal tissues and ESCC samples. (E, F) Comparative analysis of intercellular communication signal intensity among fibroblast subpopulations. (G, H) Molecular stratification of fibroblasts using lineage-specific markers (DCN/Decorin, IGFBP6/Insulin Like Growth Factor Binding Protein 6, MFAP5/Microfibril Associated Protein 5, ACTA2/Actin Alpha 2 Smooth Muscle, TAGLN/Transgelin, CTHRC1/Collagen Triple Helix Repeat Containing 1)into NFs and CAFs subtypes. (I) Validation of CAF-specific markers (FAP, COL1A1, COL3A1, COL4A1, COL10A1, MMP1, MMP11, MMP14) and expression patterns of WISP1 in CAFs via single-cell RNA sequencing.

Techniques: Functional Assay, Binding Assay, Biomarker Discovery, Expressing, RNA Sequencing

WISP1 regulates cancer-associated fibroblast function and extracellular matrix remodeling. (A, B) Immunofluorescence multiplex staining of α-smooth muscle actin (αSMA) and fibroblast activation protein (FAP) in paired cancer-associated fibroblasts (CAFs, tumor-derived) and normal fibroblasts (NFs, adjacent non-tumor tissues) (scale bars = 50μm). (C) Western blot (WB) analysis of WISP1, αSMA, and FAP expression in CAFs versus NFs. (D, E) Lentiviral short hairpin RNA (shRNA)-mediated WISP1 knockdown in CAFs, validated by quantitative reverse transcription PCR (qRT-PCR) and WB. (F–K) Functional characterization of CAF proliferation (CCK-8/EdU), migration, and invasion (Transwell) post-WISP1 silencing (scale bars = 50μm). (M) ELISA quantification of secreted WISP1 in supernatants from untransfected CAFs, CAFs-shVector, and CAFs-shWISP1 at 0 h, 24 h, and 48 h (N) Schematic of indirect co-culture system for CAF-ESCC interaction analysis. (L, P) WB assessment of extracellular matrix (ECM)-remodeling markers (COL1A1, MMP14) in WISP1-depleted CAFs and rescue via recombinant human WISP1 (rhWISP1). (O, Q) Transwell assay comparing the migration and invasion capacities of KYSE150 (left) and Eca109 (right) cells co-cultured with untransfected CAFs, CAFs-shVector, or CAFs-shWISP1(scale bars = 50μm). (R, S) Transwell assay assessing the migration and invasion capacities of KYSE150 (left) and Eca109 (right) cells in the CAFs-shWISP1 co-culture system following rescue experiments with rhWISP1 supplementation (scale bar = 50μm).Data are presented as mean ± standard deviation from three independent experiments. Statistical significance was analyzed by two-tailed Student’s t-tests. ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: WISP1 regulates cancer-associated fibroblast function and extracellular matrix remodeling. (A, B) Immunofluorescence multiplex staining of α-smooth muscle actin (αSMA) and fibroblast activation protein (FAP) in paired cancer-associated fibroblasts (CAFs, tumor-derived) and normal fibroblasts (NFs, adjacent non-tumor tissues) (scale bars = 50μm). (C) Western blot (WB) analysis of WISP1, αSMA, and FAP expression in CAFs versus NFs. (D, E) Lentiviral short hairpin RNA (shRNA)-mediated WISP1 knockdown in CAFs, validated by quantitative reverse transcription PCR (qRT-PCR) and WB. (F–K) Functional characterization of CAF proliferation (CCK-8/EdU), migration, and invasion (Transwell) post-WISP1 silencing (scale bars = 50μm). (M) ELISA quantification of secreted WISP1 in supernatants from untransfected CAFs, CAFs-shVector, and CAFs-shWISP1 at 0 h, 24 h, and 48 h (N) Schematic of indirect co-culture system for CAF-ESCC interaction analysis. (L, P) WB assessment of extracellular matrix (ECM)-remodeling markers (COL1A1, MMP14) in WISP1-depleted CAFs and rescue via recombinant human WISP1 (rhWISP1). (O, Q) Transwell assay comparing the migration and invasion capacities of KYSE150 (left) and Eca109 (right) cells co-cultured with untransfected CAFs, CAFs-shVector, or CAFs-shWISP1(scale bars = 50μm). (R, S) Transwell assay assessing the migration and invasion capacities of KYSE150 (left) and Eca109 (right) cells in the CAFs-shWISP1 co-culture system following rescue experiments with rhWISP1 supplementation (scale bar = 50μm).Data are presented as mean ± standard deviation from three independent experiments. Statistical significance was analyzed by two-tailed Student’s t-tests. ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Techniques: Immunofluorescence, Multiplex Assay, Staining, Activation Assay, Derivative Assay, Western Blot, Expressing, shRNA, Knockdown, Reverse Transcription, Quantitative RT-PCR, Functional Assay, CCK-8 Assay, Migration, Enzyme-linked Immunosorbent Assay, Co-Culture Assay, Recombinant, Transwell Assay, Cell Culture, Standard Deviation, Two Tailed Test

WISP1 regulates ECM remodeling in CAFs through STAT3 signaling. (A, B) Representative phospho-kinase antibody array membrane comparing CAFs-shVector and CAFs-shWISP1. Red boxes highlight phosphorylated STAT3 (Y705) signals. (C) Dose-response curve of STAT3 inhibitor Stattic in CAFs. (D) Western blot analysis of phosphorylated STAT3 (Y705), total STAT3, and GAPDH (loading control) in: CAFs-shVector, CAFs-shWISP1, CAFs-shWISP1 + rhWISP1 (0.8 μg/mL), and CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) + Stattic (7 μM). (E) Western blot analysis of COL1A1, MMP14, and GAPDH in CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) and CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) + Stattic (7 μM).

Journal: Frontiers in Immunology

Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment

doi: 10.3389/fimmu.2025.1586790

Figure Lengend Snippet: WISP1 regulates ECM remodeling in CAFs through STAT3 signaling. (A, B) Representative phospho-kinase antibody array membrane comparing CAFs-shVector and CAFs-shWISP1. Red boxes highlight phosphorylated STAT3 (Y705) signals. (C) Dose-response curve of STAT3 inhibitor Stattic in CAFs. (D) Western blot analysis of phosphorylated STAT3 (Y705), total STAT3, and GAPDH (loading control) in: CAFs-shVector, CAFs-shWISP1, CAFs-shWISP1 + rhWISP1 (0.8 μg/mL), and CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) + Stattic (7 μM). (E) Western blot analysis of COL1A1, MMP14, and GAPDH in CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) and CAFs-shWISP1 + rhWISP1 (0.8 μg/mL) + Stattic (7 μM).

Techniques: Ab Array, Membrane, Western Blot, Control

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: CCN4 concentration as quantified by ELISA in media conditioned for 48 hours by WT Py230 and Py8119 cells and two independent CCN4 KO variants for each parental cell line. Cell-free media was used as a negative control and media conditioned by B16F0 cells was used as a positive control. Individual data points represent technical replicates and values reported below quantification threshold are indicated as n.d.

Article Snippet: To measure CCN4 secretion from each WT cell line and KO variant, cells were grown for 48 hours to reach about 80% confluence and the media was filtered for ELISA (enzyme-linked immunosorbent assay) analysis using a Mouse CCN4 Quantikine ELISA Development Kit (R&D Systems, Minneapolis, MN).

Techniques: Concentration Assay, Enzyme-linked Immunosorbent Assay, Negative Control, Positive Control

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: Kaplan-Meier time-to-event survival curves for immunocompetent C57BL/6 mice (B and D) and severely immunocompromised NSG mice (A and C) challenged subcutaneously with wild-type (black curves) and two CCN4 KO variants (KO1 in blue and KO2 in dotted red curves) derived from Py8119 (A and B) and Py230 (C and D) cell lines. The tumor size exceeding 100 mm 3 was considered the triggering event. The number of animals that experienced a triggering event among the total number of animals challenged with tumor cells is indicated in the legend. Statistical difference among the three curves was assessed using a Peto & Peto Modification the Gehan-Wilcoxon test with the resulting Chi-squared, degrees of freedom and resulting P-values are indicated. As this was an exploratory study, the p-values indicate the extent to which these three Kaplan-Meier survival curves are different.

Techniques: Derivative Assay, Modification

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: (A) Box-and-whisker plots for spleen weights obtained from C57BL/6 mice challenged with WT Py230 cells and CCN4 KO variants In a time-matched experimental design with the end point at 69 days (n = 5 for each group). (B) Spleen weights and corresponding excised tumor weights obtained from C57BL/6 mice challenged with WT Py8119 cells and CCN4 KO variants in a size-matched experimental design (n = 5 for each group). As there was no statistical difference between CCN4 KO variants, results were combined for analysis. A homoscedastic two-sided Student’s t-test was used to assess statistical significance.

Techniques: Whisker Assay

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: Following enzymatic dissociation of tumor tissues, the immune cell compartment was quantified by full spectrum flow cytometry. A self-organizing map shows the distribution of negative Live/Dead violet and positive CD45 cells in size-matched WT (left) and CCN4 KO1 (center) tumors (n = 5 for both WT and CCN4 KO1 Py230). Right panel shows the percentage of events associated with each cluster that relate to cells identified by manual gating.

Techniques: Flow Cytometry

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: In a size-matched experimental design, the tumor-infiltrating lymphocytes were quantified by flow cytometry using antibody panels focused on the T cell (A, B, and C) and the myeloid (D, E, and F) compartments. Mice received either WT Py8119 cells (black circles) or one of two independently generated CCN4 KO variants (red + and blue x, n = 5 for all groups). Results highlight the CD45+ fraction among total Live events measured using the T cell (A) and myeloid (D) panels. The proportion of infiltrating CD4+ T cells within the live CD45+ compartment (B) was not different but the CD25+ fraction of live CD4+ T cells (C) was increased in CCN4 KO tumors. The MDSC compartment was shifted from PMN-MDSC (E, Live CD45+ CD11b+ Ly6G+ Ly6C int events) to Mo-MDSC (F, Live CD45+ CD11b+ Ly6G-Ly6C+ events) upon CCN4 KO. p-values calculated between WT and pooled CCN4 KOs using two-sided Student’s t test.

Techniques: Flow Cytometry, Generated

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: Results from R&D Systems’ Mouse XL Cytokine Array Kit of cytokine, chemokine, and growth factor expression by WT versus CCN4 KO cells derived from Py8119 (A) and Py230 (B) lines in vitro . (C) Compares the WT profiles between the Py8119 and Py230 cell lines. In presenting the combined results for assaying each cell line’s secretome using a single biological replicate, open circles represent results for specific cytokine probes, which are spotted in duplicate on the array, and filled circles represent positive and negative controls. Dotted red lines indicate Z-scores of 3 and −3. Particular secreted factors that are differentially expressed are annotated with their respective names.

Techniques: Expressing, Derivative Assay, In Vitro

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: (A) Projections of WT versus CCN4 KO variants along PC1 and PC2 axes for B16F0, YUMM1.7, Py230, and Py8119 cell lines. The location of duplicates of each cell line label correspond to technical replicates on the array. The percentage of variance explained by each principal component is indicated in the axis label. (B) Projection of the measured proteins based on the loading scores associated with PC1 (y-axis) listed from left to right in alphabetical order. The curves on the right represent the density distribution of the PC1 loading scores (black) and a normal distribution centered at −0.091 with a standard deviation of 0.00074 (red).

Techniques: Standard Deviation

Journal: bioRxiv

Article Title: Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer

doi: 10.64898/2026.01.07.698253

Figure Lengend Snippet: (A) Schematic diagram of the network topology associated with the adherens pathway activity of beta-catenin. Adherens junctions are formed by homotypic interactions between the extracellular cadherin domains of a single pass transmembrane protein E-cadherin (E-cad: blue double oval). The cytoplasmic tail of E-cadherin provides a scaffold for a multi-protein complex that includes beta-catenin ( β -cat: red oval). (B) Upon the proteolytic cleavage of adherens junctions, a cytoplasmic fragment of E-cadherin and associated catenins (tBE) are transported to the cytoplasm. In the cytoplasm, the cytoplasmic fragment of E-cadherin and associated catenins can either enter the nucleus or undergo proteasomal degradation. In the nucleus, this multi-protein complex promotes the transcription and translation of CCN4, beta-catenin, and E-cadherin, among other factors. mRNA is represented by light green parallelogram. Once synthesized, CCN4 (light blue circle) is secreted. Newly synthesized beta-catenin and E-cadherin reform the multi-protein complex and are transported to the cell membrane to re-establish adherens junctions. If no E-cadherin binding sites are present, the multi-protein complex is internalized and degraded. (C) Graphical summary of mutations that include both changes in single nucleotides and in copy numbers for breast invasive carcinoma (TCGA, Cell 2015) samples. Of the 816 samples contained in the dataset obtained through cBioPortal (retrieved 11/10/2025), the queried genes are altered in 336 (41%) of the samples.

Techniques: Activity Assay, Synthesized, Membrane, Binding Assay

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