human wisp1 rhwisp1 (Sino Biological)
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Human Wisp1 Rhwisp1, supplied by Sino Biological, used in various techniques. Bioz Stars score: 90/100, based on 2 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/human+wisp1+rhwisp1/Human+CCN4+WISP1+Protein/pmc12325208-106-11-17
Average 90 stars, based on 2 article reviews
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1) Product Images from "WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment"
Article Title: WISP1 drives esophageal squamous cell carcinoma progression via modulation of cancer-associated fibroblasts and immune microenvironment
Journal: Frontiers in Immunology
doi: 10.3389/fimmu.2025.1586790
Figure Legend 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.
Techniques Used: Quantitative Proteomics, Expressing, Control
Figure Legend 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 Used: Expressing
Figure Legend 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 Used: Functional Assay
Figure Legend 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 Used: Expressing
Figure Legend 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 Used: Expressing
Figure Legend 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 Used: Expressing, Derivative Assay
Figure Legend 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 Used: Functional Assay, Binding Assay, Biomarker Discovery, Expressing, RNA Sequencing
Figure Legend 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 Used: 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
Figure Legend 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 Used: Ab Array, Membrane, Western Blot, Control
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