Journal: Bone & Joint Research

Article Title: Piezo1 drives fibroblast activation in epidural fibrotic remodelling via the ET-1/HIF-1α pathway

doi: 10.1302/2046-3758.158.BJR-2025-0662.R1

Figure Lengend Snippet: Ca² + and endothelin-1 (ET-1) contribute to Piezo1-dependent activation of hypoxia-inducible factor 1-alpha (HIF-1α). a) and b) Gene set enrichment analysis (GSEA) of epidural scar tissue from mice after laminectomy. c) Ca² + influx measured by Fluo-4 AM in the blank, type I rat tail collagen-encapsulated, and collagen-encapsulated with GsMTX4 groups. d) Western blot analysis of NIH/3T3 fibroblasts treated with type I rat tail collagen and the calcium influx blocker Nimodipine (n = 3). e) Western blot analysis of NIH/3T3 fibroblasts treated with Yoda1 and Nimodipine (n = 3). f) Quantitative analysis of relative Edn1 messenger RNA (mRNA) expression in blank and collagen-encapsulated NIH/3T3 fibroblasts. g) and h) Western blot analysis of NIH/3T3 fibroblasts treated with type I rat tail collagen and the ET-1 inhibitor Bosentan (n = 3). *p < 0.05, **p < 0.01, ***p < 0.001, independent-samples t -test (two groups) or analysis of variance (multiple groups).

Article Snippet: Alternatively, the following drugs were used to stimulate NIH/3T3 cells: Yoda1 (25 μM; HY-P1410), a chemical activator of Piezo1; BAY 87-2243 (1 μM; HY-15836), an inhibitor of hypoxia-inducible factor 1-alpha (HIF-1α); SB-431542 (10 μM; HY-10431), an inhibitor of TGF-β1; SIS 3 (10 μM; HY-13013), an inhibitor of Smad3; GsMTX4 (2.5 μM; HY-P1410); Nimodipine (60 μM; HY-B0265), a calcium channel blocker; and Bosentan (1 μM; HY-A0013, all MedChemExpress), an endothelin-1 (ET-1) receptor antagonist.

Techniques: Activation Assay, Western Blot, Expressing

Journal: Aging Cell

Article Title: Characterizing the SASP ‐Dependent Paracrine Spreading of Senescence Between Human Brain Cell Types

doi: 10.1111/acel.70673

Figure Lengend Snippet: Analysis of ligands and receptors in senescent and receiving cells. (A) Schematic depicting BulkSignalR pipeline which uses known ligand‐receptor interactions and affected downstream pathways to analyze their activation based on our bulk RNAseq data from DMSO and BrdU treated human cell lines (created with BioRender). (B) Venn diagram showing the number of receptors inferred from BulkSignalR to be activated across each of the five human cell types. Three receptors were identified in common between astrocytes (purple), endothelial cells (pink), and microglia (yellow) which were the cell types shown (Figure ) to be capable of receiving senescence signals and becoming SA β‐gal positive: CXCR7, KREMEN2, and GIPR. Only CXCR7 was expressed in the cell types capable of entering secondary senescence (astrocytes, endothelial cells, microglia) (Figure , Figure ). (C) TPM expression values of CXCR7 , its ligand CXCL12 , and DPP4 which cleaves and inactivates CXCL12 in DMSO (gray) and BrdU (red) treated cell lines ( n = 3 replicates). (D) Schematic of the four selected SASP inhibitors mechanisms of action: Bindarit is a CCL2 synthesis inhibitor which prevents p65 activation of the CCL2 gene at the promoter region, ISO‐1 is a MIF antagonist, ACT‐1004‐1239 is a CXCR7 antagonist, and Sitagliptin inhibits DPP4 preventing its action of cleaving and inactivating CXCL12 (created with BioRender). Data were analyzed by two‐way ANOVA with Tukey's multiple comparisons test (C). All graphs show mean with error bars depicting standard deviation (ns, p > 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Treatment with migration inhibitor factor (MIF) antagonist ISO‐1 (MedChemExpress, Catalog No. HY‐16692) (Kok et al. ) was utilized to prevent MIF‐associated communication between senescence inducers and receiving cells.

Techniques: Activation Assay, RNA sequencing, Expressing, Standard Deviation

Journal: Aging Cell

Article Title: Characterizing the SASP ‐Dependent Paracrine Spreading of Senescence Between Human Brain Cell Types

doi: 10.1111/acel.70673

Figure Lengend Snippet: Targeting SASP ligands and receptors to prevent the spreading of senescence. (A) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with 100 μM BrdU (red) along with 200 μM Bindarit (pink), 50 μM ISO‐1 (blue), 200 μM ACT‐1004‐1239 (orange), or 2 μM Sitagliptin (green) ( n = 6 replicates). (B) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with 100 μM BrdU (red) along with 200 μM Bindarit (pink), 50 μM ISO‐1 (blue), 200 μM ACT‐1004‐1239 (orange), or 2 μM Sitagliptin (green) ( n = 6 replicates). (C) Timeline showing treatment with DMSO + Bindarit CM or BrdU + Bindarit CM for 7 days. Timeline showing treatment with DMSO or 100 μM BrdU along with SASP inhibitors (ISO‐1, ACT‐1004‐1239, or Sitagliptin) for 7 days. Features of senescence were analyzed 8 days after the initial plating of cells (created with BioRender). (D) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO + Bindarit CM from astrocytes (gray), BrdU + Bindarit CM from astrocytes (red), DMSO CM from astrocytes + SASP inhibitor (gray), or BrdU CM from astrocytes + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from astrocytes + Bindarit (gray) or BrdU CM from astrocytes + Bindarit (red) ( n = 4 replicates). (E) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO + Bindarit CM from microglia (gray), BrdU + Bindarit CM from microglia (red), DMSO CM from microglia + SASP inhibitor (gray), or BrdU CM from microglia + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from microglia + Bindarit (gray) or BrdU CM from microglia + Bindarit (red) ( n = 4 replicates). (F) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with DMSO + Bindarit CM from microglia (gray), BrdU + Bindarit CM from microglia (red), DMSO CM from microglia + SASP inhibitor (gray), or BrdU CM from microglia + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from microglia + Bindarit (gray) or BrdU CM from microglia + Bindarit (red) ( n = 4 replicates). (G) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with DMSO + Bindarit CM from astrocytes (gray), BrdU + Bindarit CM from astrocytes (red), DMSO CM from astrocytes + SASP inhibitor (gray), or BrdU CM from astrocytes + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from astrocytes + Bindarit (gray) or BrdU CM from astrocytes + Bindarit (red) ( n = 4 replicates). Data analyzed by unpaired t ‐test (A, B) and two‐way ANOVA with Tukey's or Šídák's multiple comparisons test (D–G). All graphs show mean with error bars depicting standard deviation (ns, p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Treatment with migration inhibitor factor (MIF) antagonist ISO‐1 (MedChemExpress, Catalog No. HY‐16692) (Kok et al. ) was utilized to prevent MIF‐associated communication between senescence inducers and receiving cells.

Techniques: Standard Deviation

Journal: Aging Cell

Article Title: Characterizing the SASP ‐Dependent Paracrine Spreading of Senescence Between Human Brain Cell Types

doi: 10.1111/acel.70673

Figure Lengend Snippet: Analysis of ligands and receptors in senescent and receiving cells. (A) Schematic depicting BulkSignalR pipeline which uses known ligand‐receptor interactions and affected downstream pathways to analyze their activation based on our bulk RNAseq data from DMSO and BrdU treated human cell lines (created with BioRender). (B) Venn diagram showing the number of receptors inferred from BulkSignalR to be activated across each of the five human cell types. Three receptors were identified in common between astrocytes (purple), endothelial cells (pink), and microglia (yellow) which were the cell types shown (Figure ) to be capable of receiving senescence signals and becoming SA β‐gal positive: CXCR7, KREMEN2, and GIPR. Only CXCR7 was expressed in the cell types capable of entering secondary senescence (astrocytes, endothelial cells, microglia) (Figure , Figure ). (C) TPM expression values of CXCR7 , its ligand CXCL12 , and DPP4 which cleaves and inactivates CXCL12 in DMSO (gray) and BrdU (red) treated cell lines ( n = 3 replicates). (D) Schematic of the four selected SASP inhibitors mechanisms of action: Bindarit is a CCL2 synthesis inhibitor which prevents p65 activation of the CCL2 gene at the promoter region, ISO‐1 is a MIF antagonist, ACT‐1004‐1239 is a CXCR7 antagonist, and Sitagliptin inhibits DPP4 preventing its action of cleaving and inactivating CXCL12 (created with BioRender). Data were analyzed by two‐way ANOVA with Tukey's multiple comparisons test (C). All graphs show mean with error bars depicting standard deviation (ns, p > 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Treatment with CXCR7 antagonist ACT‐1004‐1239 (MedChemExpress, Catalog No. HY‐142617) was utilized to prevent CXCR7‐associated communication between senescence inducers and receiving cells.

Techniques: Activation Assay, RNA sequencing, Expressing, Standard Deviation

Journal: Aging Cell

Article Title: Characterizing the SASP ‐Dependent Paracrine Spreading of Senescence Between Human Brain Cell Types

doi: 10.1111/acel.70673

Figure Lengend Snippet: Targeting SASP ligands and receptors to prevent the spreading of senescence. (A) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with 100 μM BrdU (red) along with 200 μM Bindarit (pink), 50 μM ISO‐1 (blue), 200 μM ACT‐1004‐1239 (orange), or 2 μM Sitagliptin (green) ( n = 6 replicates). (B) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with 100 μM BrdU (red) along with 200 μM Bindarit (pink), 50 μM ISO‐1 (blue), 200 μM ACT‐1004‐1239 (orange), or 2 μM Sitagliptin (green) ( n = 6 replicates). (C) Timeline showing treatment with DMSO + Bindarit CM or BrdU + Bindarit CM for 7 days. Timeline showing treatment with DMSO or 100 μM BrdU along with SASP inhibitors (ISO‐1, ACT‐1004‐1239, or Sitagliptin) for 7 days. Features of senescence were analyzed 8 days after the initial plating of cells (created with BioRender). (D) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO + Bindarit CM from astrocytes (gray), BrdU + Bindarit CM from astrocytes (red), DMSO CM from astrocytes + SASP inhibitor (gray), or BrdU CM from astrocytes + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from astrocytes + Bindarit (gray) or BrdU CM from astrocytes + Bindarit (red) ( n = 4 replicates). (E) Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO + Bindarit CM from microglia (gray), BrdU + Bindarit CM from microglia (red), DMSO CM from microglia + SASP inhibitor (gray), or BrdU CM from microglia + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from microglia + Bindarit (gray) or BrdU CM from microglia + Bindarit (red) ( n = 4 replicates). (F) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with DMSO + Bindarit CM from microglia (gray), BrdU + Bindarit CM from microglia (red), DMSO CM from microglia + SASP inhibitor (gray), or BrdU CM from microglia + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from microglia + Bindarit (gray) or BrdU CM from microglia + Bindarit (red) ( n = 4 replicates). (G) Quantification of percentage of SA β‐gal positive microglia following 7‐day treatment with DMSO + Bindarit CM from astrocytes (gray), BrdU + Bindarit CM from astrocytes (red), DMSO CM from astrocytes + SASP inhibitor (gray), or BrdU CM from astrocytes + SASP inhibitor (red) ( n = 4 replicates). Quantification of percentage of SA β‐gal positive astrocytes following 7‐day treatment with DMSO CM from astrocytes + Bindarit (gray) or BrdU CM from astrocytes + Bindarit (red) ( n = 4 replicates). Data analyzed by unpaired t ‐test (A, B) and two‐way ANOVA with Tukey's or Šídák's multiple comparisons test (D–G). All graphs show mean with error bars depicting standard deviation (ns, p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Treatment with CXCR7 antagonist ACT‐1004‐1239 (MedChemExpress, Catalog No. HY‐142617) was utilized to prevent CXCR7‐associated communication between senescence inducers and receiving cells.

Techniques: Standard Deviation

Journal: Oncology Letters

Article Title: A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response

doi: 10.3892/ol.2026.15719

Figure Lengend Snippet: HRH1 is associated with prognosis, chemotherapy resistance and immunotherapy resistance in PDAC. (A) Venn analysis identified GPCR-related genes that are highly expressed and associated with prognosis in PDAC. (B) Kaplan-Meier analysis indicated the prognostic value of HRH1. (C) Online analysis using the GEPIA2 database showed HRH1 expression in pancreatic cancer and normal tissue (one-way ANOVA; *P<0.05). (D) HRH1 expression in tumor tissues and matched adjacent normal tissues. Data were obtained from 266 patients across seven cohorts (Wilcoxon rank-sum test; ***P<0.001). (E) Sequencing data from GSE26088 revealed that HRH1 expression was higher in 19 pancreatic cancer cell lines when compared with the normal pancreatic cell line (HPDE). (F) Reverse transcription quantitative-PCR analysis of HRH1 expression. Each of the 7 PDAC cell lines was compared with the control HPNE cell line. Statistical significance was assessed by one-way ANOVA followed by Dunnett's post hoc test (****P<0.0001; ***P<0.001). (G) Relationship between HRH1 expression and tumor mutation burden (Wilcoxon rank-sum test; **P<0.01). (H) In the CRA001160 dataset, HRH1 expression across different cell types, displayed using UMAP plot, feature plot and bar plot reflecting mean UMI count. (I) Relationship between HRH1 expression and TIDE score (Wilcoxon rank-sum test, **P<0.01). Association between HRH1 expression and resistance to (J) Gemcitabine, (K) Fluorouracil, (L) SN-38 and (M) Oxaliplatin. Statistical comparisons were performed using the Wilcoxon rank-sum test. GPCRs, G protein-coupled receptors; PDAC, pancreatic ductal adenocarcinoma; UMAP, Uniform Manifold Approximation and Projection.

Article Snippet: Fexofenadine (cat. no. HY-B0801; MedChemExpress) was employed as a selective HRH1 antagonist, while histamine (cat. no. HY-B1204; MedChemExpress) served as the HRH1 agonist.

Techniques: Expressing, Sequencing, Reverse Transcription, Real-time Polymerase Chain Reaction, Control, Mutagenesis

Journal: Oncology Letters

Article Title: A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response

doi: 10.3892/ol.2026.15719

Figure Lengend Snippet: Targeting and inhibiting HRH1 is a potential therapeutic strategy for PDAC. (A) Scatter plot of the causal association between fexofenadine treatment and PDAC. (B) Leave-one-out sensitivity analysis using the IVW method. CCK-8 proliferation assay was used to detect the proliferation of (C) PANC1 cells and (D) SW1990 cells after HRH1 knockdown. The knockdown groups were compared with the non-targeting control in PANC-1 and SW1990 cells. Statistical significance was assessed by one-way ANOVA followed by Dunnett's post hoc test (****P<0.0001). Experiments were performed in triplicate. The reverse transcription-quantitative PCR validation data for HRH1 knockdown efficiency is provided in . Dose-response curves of (E) PANC1 and (F) SW1990 cells transfected with siControl, siHRH1#1 or siHRH1#2 and treated with increasing concentrations of gemcitabine for 48 h. Cell viability was assessed by CCK-8 assay and normalized to the untreated control. PDAC, pancreatic ductal adenocarcinoma; CCK-8, Cell Counting Kit-8; si, small interfering; IVW, inverse variance-weighted.

Article Snippet: Fexofenadine (cat. no. HY-B0801; MedChemExpress) was employed as a selective HRH1 antagonist, while histamine (cat. no. HY-B1204; MedChemExpress) served as the HRH1 agonist.

Techniques: CCK-8 Assay, Proliferation Assay, Knockdown, Control, Reverse Transcription, Real-time Polymerase Chain Reaction, Biomarker Discovery, Transfection, Cell Counting

Journal: Oncology Letters

Article Title: A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response

doi: 10.3892/ol.2026.15719

Figure Lengend Snippet: HRH1 is associated with YAP1 signaling. (A) Metascape enrichment analysis revealed that HRH1 is functionally associated with YAP1 signaling. The gene set was derived from differentially upregulated genes in the HRH1-high expression group within TCGA-PAAD cohort. Gene Set Enrichment Analysis further indicated a significant correlation between HRH1 and both the (B) ‘Cordenosi YAP conserved signature’ and the (D) ‘YAP1 up signature’. (C) A heatmap illustrated HRH1 expression and the expression of multiple YAP1 pathway target genes. Based on HRH1 expression levels, TCGA PDAC groups were categorized into two groups to compare the expression of YAP1-targeted genes (***P<0.001). Expression changes of HRH1, CTGF, CYR61, ANKRD1 and YAP1 were assessed following knockdown of HRH1 and YAP1. The knockdown groups were compared with the non-targeting control in (E) PANC-1 and (F) SW1990 cells. Statistical significance was assessed by one-way ANOVA followed by Dunnett's post hoc test ( ***P <0.001, **P<0.01; ns, Not Significant). si, small interfering; NC, negative control.

Article Snippet: Fexofenadine (cat. no. HY-B0801; MedChemExpress) was employed as a selective HRH1 antagonist, while histamine (cat. no. HY-B1204; MedChemExpress) served as the HRH1 agonist.

Techniques: Derivative Assay, Expressing, Knockdown, Control, Negative Control

Journal: Oncology Letters

Article Title: A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response

doi: 10.3892/ol.2026.15719

Figure Lengend Snippet: The reciprocal regulation between YAP1 and HRH1. (A) YAP1 binds to the promoter region of HRH1. The ChIP-seq data for H3K4me3, H3K27ac and YAP1, as well as ATAC-seq data, were obtained from the ChIP-Atlas database. (B) In PA-TU-8902 and PCa3 cells, knockdown of YAP1 and TAZ resulted in reduced chromatin accessibility at the HRH1 promoter region. ATAC-seq data for PA-TU-8902 and PCa3 were obtained from the ChIP-Atlas database. Knockdown of HRH1 and YAP1 led to a marked reduction in YAP1 protein levels in (C) SW199 and (D) PANC10 cells. The observed molecular weights of β-actin and YAP1 were ~42 and 75 kDa, respectively. Relative YAP1 expression levels, normalized to β-actin and the NC, are provided in . Treatment of (E) SW1990 and (F) PANC1 cells with fexofenadine and histamine resulted in altered expression of YAP1. Relative YAP1 expression levels, normalized to β-actin and the Control group, are provided in . si, small interfering; NC, negative control.

Article Snippet: Fexofenadine (cat. no. HY-B0801; MedChemExpress) was employed as a selective HRH1 antagonist, while histamine (cat. no. HY-B1204; MedChemExpress) served as the HRH1 agonist.

Techniques: ChIP-sequencing, Knockdown, Expressing, Control, Negative Control

Journal: Oncology Letters

Article Title: A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response

doi: 10.3892/ol.2026.15719

Figure Lengend Snippet: Prognostic value of the HRH1/YAP1 signaling axis-derived signature in TCGA, ICGC and GEO cohorts. (A) Risk score distribution plots demonstrating the correlation between elevated risk scores and mortality events. (B) Kaplan-Meier curves stratified by risk groups. (C) Time-dependent receiver operating characteristic curves assessing the model's predictive accuracy for 1-, 2-, 3- and 4-year survival. (D) Expression heatmaps of the eight signature genes incorporated in the risk model. (E) PCA visualizing the separation between high- and low-risk groups. PCA, principal component analysis; KM, Kaplan-Meier. TCGA, The Cancer Genome Atlas; ICGC, International Cancer Genome Consortium; GEO, Gene Expression Omnibus.

Article Snippet: Fexofenadine (cat. no. HY-B0801; MedChemExpress) was employed as a selective HRH1 antagonist, while histamine (cat. no. HY-B1204; MedChemExpress) served as the HRH1 agonist.

Techniques: Derivative Assay, Expressing, Gene Expression