human dpp4 cd26 antibody  (R&D Systems)

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: The flow chart, differential expression analysis, ceRNA network construction, and PPI network construction. (A) The flow chart of our analysis. (B) Expression of DPP4 in 33 tumor types between normal tissues and tumor tissues. DPP4 expression was down-regulated in BRCA ( p < 0.001), CESC ( p < 0.05), CHOL ( p < 0.001), COAD ( p < 0.05), KICH ( p < 0.001), LUSC ( p < 0.001), PCPG ( p < 0.05), READ ( p < 0.01) and UCEC ( p < 0.01), while it was up-regulated in GBM ( p < 0.01), KIRC ( p < 0.001), KIRP ( p < 0.001), LIHC ( p < 0.001), LUAD ( p < 0.001), STAD ( p < 0.05) and THCA ( p < 0.001). (C) The ceRNA network of DPP4. There were three key miRNAs correlated with DPP4 and there were eight lncRNAs correlated with the key miRNAs. (D) The PPI network of DPP4. At the proteomic level, DPP4 was closely associated with FN1, CXCR4, CAV1, ITGB1, PTPRC, ADA, GCG, GIP, ACE2, and PRCP. ceRNA, competing endogenous RNA; lncRNA, long non-coding RNA; PPI, Protein-Protein Interaction. * p < 0.05, ** p < 0.01, *** p < 0.001.

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Quantitative Proteomics, Expressing

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: Survival analysis and univariate Cox regression analysis in pan-cancer. (A) Survival analysis of DPP4 in pan-cancer. K-M survival curves indicated DPP4 was positively correlated with OS in KIRC ( p < 0.001), with DSS in KIRC ( p < 0.001), and with DFS in PRAD ( p < 0.001). (B) Univariate Cox model of OS. DPP4 expression was a risk factor in DLBC (HR = 2.757, 95%CI = 1.066-7.127, p = 0.036), LAML (HR = 2.757, 95%CI = 1.066-7.127, p = 0.036), LGG (HR = 3.474, 95%CI = 2.617-4.611, p < 0.001), and LUSC (HR = 1.118, 95%CI = 1.000-2.014, p < 0.049), and it was a protective factor in KIRC (HR = 0.787, 95%CI = 0.716-0.865, p < 0.001), KIRP (HR = 0.789, 95%CI = 0.675-0.921, p = 0.003), LUAD (HR = 0.911, 95%CI = 0.837-0.992, p = 0.031), THCA (HR = 0.701, 95%CI = 0.553-0.887, p = 0.003), and THYM (HR = 0.440, 95%CI = 0.233-0.830, p = 0.011). (C) Univariate Cox model of DFS. DPP4 expression was a risk factor in LGG (HR = 4.698, 95%CI = 1.068-20.654, p = 0.041) and UCS (HR = 1.542, 95%CI = 1.004-2.370, p = 0.048), while it was a protective factor in PRAD (HR = 0.727, 95%CI = 0.567-0.931, p = 0.012). (D) Univariate Cox model in DSS. DPP4 expression was a risk factor in LGG (HR = 3.573, 95%CI = 2.672-4.778, p < 0.001), BRCA (HR = 1.383, 95%CI = 1.133-1.689, p = 0.001), DLBC (HR = 7.111, 95%CI = 1.469-34.432, p = 0.015), and ACC (HR = 1.343, 95%CI = 1.036-1.742, p = 0.026), while it was a protective factor in KIRC (HR = 0.703, 95%CI = 0.630-0.784, p < 0.001), KIRP (HR = 0.706, 95%CI = 0.595-0.838, p < 0.001), THCA (HR = 0.593, 95%CI = 0.419-0.839, p = 0.003), and LUAD (HR = 0.872, 95%CI = 0.782-0.971, p = 0.013). (E) Univariate Cox model in PFS. DPP4 expression was a risk factor in LGG (HR = 2.442, 95%CI = 1.884-3.163, p < 0.001), PCPG (HR = 1.832, 95%CI = 1.041-3.226, p = 0.036), and LUSC (HR = 1.137, 95%CI = 1.005-1.285, p = 0.041), while it was a protective factor in KIRC (HR = 0.787, 95%CI = 0.717-0.864, p < 0.001), PRAD (HR = 0.736, 95%CI = 0.638-0.850, p < 0.001), KIRP (HR = 0.818, 95%CI = 0.711-0.942, p = 0.005), PAAD (HR = 0.794, 95%CI = 0.659-0.956, p = 0.015), and MESO (HR = 0.836, 95%CI = 0.716-0.976, p = 0.023). OS, Overall Survival; DFS, Disease-Free Survival; DSS, Disease-Specific Survival; PFS, Progression-Free Survival. *p < 0.05, **p < 0.01, ***p < 0.001 .

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Expressing

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: Relationship of DPP4 expression with TME in pan-cancer. (A) Correlation of DPP4 expression with MSI. It was positively correlated with MSI in COAD ( p < 0.001), ESCA ( p < 0.05), and KIRC ( p < 0.01), while it was negatively related in DLBC ( p < 0.001), HNSC ( p < 0.05), LUSC ( p < 0.001), PRAD ( p < 0.01), SKCM ( p < 0.001), and UCS ( p < 0.05). (B) Correlation of DPP4 expression with TMB. It was positively correlated with TMB in LAML ( p < 0.01), SARC ( p < 0.05), ESCA ( p < 0.001), KIRP ( p < 0.001), COAD ( p < 0.01), UCEC ( p < 0.05), GBM ( p < 0.05), LIHC ( p < 0.05), and OV ( p < 0.05), while it was negatively correlated in THYM ( p < 0.001), LUSC ( p < 0.001), CESC ( p < 0.05), PRAD ( p < 0.001), BRCA ( p < 0.001), and LUAD ( p < 0.05). (C) The relationship between DPP4 expression and immune-related genes. There is a significant association between DPP4 expression and immune-related genes across various cancers, particularly with NRP1 and HHLA2. Additionally, the majority of immune genes showed a positive correlation with DPP4 expression in BLCA, BRCA, LGG, SKCM, and THCA. (D) In PRAD, DPP4 expression was positively correlated with T cells CD4 memory resting (R = 0.18, p < 0.001), while it was negatively correlated with T cells CD8 (R = -0.19, p < 0.001), and T cells regulatory (R = -0.19, p < 0.001). MSI, Microsatellite Instability; TMB, Tumor Mutation Burden; TME, Tumor Microenvironment. *p < 0.05, **p < 0.01, ***p < 0.001 .

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Expressing, Mutagenesis

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: Drug sensitivity prediction for DPP4 in (A) CellMiner, (B) CTRP and (C) GDSC databases. The expression of DPP4 was negatively related with drug sensitivity of most drugs. However, several drugs were positively related with DPP4 expression, including perifosine and adavosertib from CellMiner, dasatinib and saracatinib from CTRP, and cetuximab and crizotinib from GDSC. (D) The molecular docking analysis of DPP4 and dasatinib. (E) The molecular docking analysis of DPP4 and midostaurin. (F) The molecular docking analysis of DPP4 and saracatinib. (G) The molecular docking analysis of DPP4 and selumetinib. The possible binding sites were illustrated. (H) RMSD values of the protein-ligand complexes over time. The DPP4-Saracatinib complex reached equilibrium after 20 ns, with its RMSD fluctuating around 2.2 Å. The DPP4-Selumetinib complex reached equilibrium after 20 ns, fluctuating around 4.1 Å. The DPP4-Dasatinib complex reached equilibrium after 20 ns, fluctuating around 2.0 Å. The DPP4-Midostaurin complex reached equilibrium after 30 ns, fluctuating around 2.2 Å. (I) Rg of the protein-ligand complexes over time. All complex systems exhibited only minor fluctuations throughout the simulation. (J) SASA of the protein-ligand complexes over time. The results indicate that the SASA of the complexes did not change significantly after ligand binding to DPP4. (K) RMSF of the protein-ligand complexes. The RMSF values for all complexes were relatively low, with most residues fluctuating below 3 Å. RMSD, Root Mean Square Deviation; RMSF, Root-Mean-Square Fluctuation; Rg, Radius of gyration; SASA, Solvent-Accessible Surface Area.

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Expressing, Binding Assay, Ligand Binding Assay, Solvent

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: A single-cell transcriptomic atlas of DPP4 in prostate cancer. (A) UMAP dimension reduction plot exhibiting 386,664 single-cell transcriptomes across nine major cell lineages (B cell, DC, endothelial cell, epithelial cell, fibroblast, mast cell, mono_macro, NK cell, and T cell) and 18 minor subtypes (luminal, basal, NE, NK cell, CD4+ T cell, CD8+ T cell, B cell, plasma cell, monocyte, macrophage, cDC1, cDC2, pDC, mast cell, fibroblast, SMC, pericyte, and endothelial cell). (B) Bubble plots depicting the feature expression of different marker genes in nine major cell subtypes. (C) UMAP dimension reduction plots by Grade1-5. (D) Bar plot demonstrating that the proportion of epithelial cells varied greatly in different grades of prostate cancer. (E) Stacked bar plots highlighting the enrichment of upregulated DEGs in epithelial cells within non-metastatic prostate cancer. (F, G) DPP4 expression was exclusively expressed in luminal cells. (H) Violin plots comparing DPP4 expression levels across ISUP grades, showing significantly higher expression in low-grade groups (p < 0.001). (I) Violin plots showing DPP4 expression across clinical T stages, indicating a significant downregulation in advanced stages (p < 0.001). (J) The interaction network illustrating the cellular communications of DPP4+ epithelial cells. (K) Heatmap summarizing the total interaction numbers, highlighting that DPP4+ epithelial cells exhibit significant communication with fibroblasts. (L) Volcano plot showing genes significantly perturbed by virtual DPP4 knockout in epithelial cells. (M) Functional enrichment analysis of the significantly perturbed genes following virtual KO of DPP4. UMAP, Uniform Manifold Approximation and Projection; AJCC, American Joint Committee on Cancer; DEG, Differential Expressed Genes; KO, Knockout.

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Single Cell, Clinical Proteomics, Expressing, Marker, Knock-Out, Functional Assay

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: Higher DPP4 expression was correlated with better prognosis in prostate cancer. (A) The inclusion and exclusion criteria of the cohort. (B) IHC scores revealed that normal tissue exhibited significantly higher DPP4 expression compared to tumor tissues ( p < 0.001). (C) Representative IHC images of both prostate cancer and normal tissues from the cohort demonstrated this difference visually. (D) The Chi square test showed that DPP4 expression was associated with WHO/ISUP grade ( p = 0.03). (E) The K-M survival curve indicated that higher DPP4 expression was not significantly correlated with OS and PFS ( p > 0.05). However, DPP4 expression tended to be a protective factor. (F) Multivariate Cox regression analysis indicated that high DPP4 expression was an independent protective factor for OS in prostate cancer patients (HR = 0.052, 95%CI = 0.0041 - 0.65, p = 0.02). IHC, Immunohistochemical; OS, Overall Survival; PFS, Progression-Free Survival.

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Expressing, Immunohistochemical staining

Journal: Frontiers in Immunology

Article Title: Integrative pan-cancer analysis of dipeptidyl peptidase 4 with clinical and in vitro validation in prostate cancer

doi: 10.3389/fimmu.2026.1616889

Figure Lengend Snippet: Dasatinib and midostaurin regulated DPP4 expression. (A) IC50 of 22Rv1 and C4–2 treated with dasatinib tested by CCK-8 assays. (B) IC50 of 22Rv1 and C4–2 treated with midostarin tested by CCK-8 assays. (C) Dasatinib treatment significantly increased DPP4 expression in C4–2 cells ( p = 0.0042, primer 1; p = 0.0029, primer 2). In contrast, midostaurin treatment reduced DPP4 expression in both cell lines (C4-2: p = 0.0218, primer 1; 22Rv1: p = 0.0172, primer 1; p = 0.0002, primer 2). IC50, Half maximal inhibitory concentration; CCK-8, Cell Counting Kit-8.

Article Snippet: Primary antibodies against human DPP4 (1:200; Affinity Biosciences Cat# DF12387, RRID: AB_2845192) were then introduced, followed by secondary antibodies conjugated with horseradish peroxidase (HRP).

Techniques: Expressing, CCK-8 Assay, Concentration Assay, Cell Counting

Journal: Investigative Ophthalmology & Visual Science

Article Title: Dipeptidyl Peptidase 4, a Novel Adipokine, Impairs Retinal Microcirculation in Patients With Type 2 Diabetes Mellitus

doi: 10.1167/iovs.66.14.4

Figure Lengend Snippet: Effect of DPP4 intraluminal incubation on the BK-induced vasodilation of the retinal arterioles ( A ). The dose-dependent effect of DPP4 in response to BK is examined before (control, n = 16), and after intraluminal incubation with 100 ng/mL ( n = 4), 400 ng/mL ( n = 4), or 1 µg/mL ( n = 8) DPP4 for 3 hours ( B ). The time-course effect of DPP4 in response to BK is examined before (control), and after intraluminal incubation with 1 µg/mL DPP4 for 1, 2, and 3 hours ( n = 8). * P < 0.05 versus control.

Article Snippet: Human recombinant DPP4 was purchased from R&D Systems, and DPP4 inhibitor teneligliptin was obtained from Mitsubishi Tanabe Pharma Co., Ltd. (Osaka, Japan).

Techniques: Incubation, Control

Journal: Investigative Ophthalmology & Visual Science

Article Title: Dipeptidyl Peptidase 4, a Novel Adipokine, Impairs Retinal Microcirculation in Patients With Type 2 Diabetes Mellitus

doi: 10.1167/iovs.66.14.4

Figure Lengend Snippet: Effect of coadministration of DPP4 with superoxide scavenger, NADPH oxidase inhibitor, xanthine oxidase inhibitor, or DPP4 inhibitor ( A ). The dilation of the retinal arterioles to BK is examined before (control, n = 14) and after intraluminal incubation with 1 µg/mL DPP4 plus the superoxide anion scavenger TEMPOL (1 mM; n = 5), the NADPH oxidase inhibitor apocynin (100 µM; n = 4), or the xanthine oxidase inhibitor allopurinol (10 µM; n = 5) ( B ). Dilation of the retinal arterioles in response to BK is examined before (control, n = 5) and after intraluminal incubation with 1 µM plus the DPP4 inhibitor teneligliptin (0.5 µM; n = 5). * P < 0.05 versus control. † P < 0.05 versus DPP4 alone.

Article Snippet: Human recombinant DPP4 was purchased from R&D Systems, and DPP4 inhibitor teneligliptin was obtained from Mitsubishi Tanabe Pharma Co., Ltd. (Osaka, Japan).

Techniques: Control, Incubation