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: JID Innovations

Article Title: Human keratinocytes exhibit limited potential for SARS-CoV-2 infection despite ACE2 and mature cathepsin L expression

doi: 10.1016/j.xjidi.2025.100447

Figure Lengend Snippet: Differential ACE2, TMPRSS2, NRP1, CTSL, CD147, AXL, and DPP4 protein expression. Whole-cell lysates of the indicated cells were analyzed by western blot using the following antibodies: ACE2 (mAb clone AC384), TMPRSS2 (mAb clone S20014A), NRP1 (mAb clone 14H4), CTSL (mAb clone 33/1), CD147 (mAb clone HIM6), AXL (polyclonal goat IgG, AF154), and DPP4 (polyclonal goat IgG, AF1180). ( a ) Representative immunoblots from 2 to 4 independent experiments. ( b ) Densitometric quantification normalized to actin, expressed as mean ± SEM from 2 to 4 independent experiments. CTSL, cathepsin L.

Article Snippet: Primary antibodies included anti-ACE2, clone AC384 (AdipoGen Life Science/Coger, Paris, France); anti-TMPRSS2, clone S20014A; anti-NRP1, clone 14H4; anti-CD147, clone HIM6; anti–keratin 10, rabbit polyclonal Poly19054 (BioLegend); anti-CTSL, clone 33/1 (eBioscience, Thermo Fisher Scientific); anti-AXL, polyclonal goat IgG AF154; and anti-DPP4, polyclonal goat IgG AF1180 (R&D Systems, Bio-Techne SAS, Noyal Châtillon, France).

Techniques: Expressing, Western Blot

Journal: Nature Communications

Article Title: Circadian fluctuation of soluble CD26 dictates the impact of the timing of cord blood transplantation on acute graft-versus-host disease

doi: 10.1038/s41467-026-68958-4

Figure Lengend Snippet: a Experimental design. Blood samples were collected at 7:00 am ± 15 min ( n = 10) or 11:30 am ± 15 min ( n = 10) from recipients with malignant hematological diseases in complete remission prior to cord blood infusion. b , c Serum concentrations of cytokines before cord blood infusion. Normalized z score ( b ) and absolute concentrations ( c ) of cytokines between 7:00 am and 11:30 am. The P values are two-sided and reported as exact values. d Absolute concentrations of soluble CD26/DPPIV in serum post-MAC. Blood samples were collected from recipients at 7:00 am ± 15 min ( n = 19), 11:30 am ± 15 min ( n = 19), or 4:00 pm ± 15 min ( n = 29). e – i Associations between serum soluble CD26/DPPIV (sCD26/DPPIV) levels and inflammatory cytokines before cord blood infusion on day 0. Pearson’s correlation coefficient ( r ) was calculated for the relationships between serum DPPIV levels and IL-1Ra ( e ) ( r = 0.476, P = 0.034), IL-1β ( f ) ( r = 0.450, P = 0.046), LIF ( g ) ( r = 0.517, P = 0.020), IL-18 ( h ) ( r = −0.811, P < 0.001) and IL-1α ( i ) ( r = 0.006, P = 0.741) concentrations. The P values are two-sided and reported as exact values.The data are presented as the means ± SEMs and were analyzed by unpaired t test followed by Bonferroni-Dunn correction ( c ), one-way ANOVA with Bonferroni multiple comparisons ( d ) and Pearson’s correlation ( e – i ). Source data are provided as a Source Data file.

Article Snippet: In the experimental groups, recombinant human CD26/DPPIV protein (1000 ng/mL, 11244-SE, R&D Systems) or Sitagliptin phosphate monohydrate (DPPIV inhibitor, 200 μg/mL, S4002, Selleck) was added to the respective groups.

Techniques:

Journal: Nature Communications

Article Title: Circadian fluctuation of soluble CD26 dictates the impact of the timing of cord blood transplantation on acute graft-versus-host disease

doi: 10.1038/s41467-026-68958-4

Figure Lengend Snippet: a , b Representative immunofluorescence images ( a ) and quantification ( b ) of CD26/DPPIV levels in intestinal epithelial cells from a healthy population at different times ( n = 3 patients per group) ( P < 0.001). Intestinal samples were collected at 10 am (CT10), 2 pm (CT14), and 6 pm (CT18). Scale bars, 50 μm. c Bmal1 and DPP4 expression in primary mouse epidermal cells postsynchronization in vitro ( n = 3 biological replicates, each from an independent primary culture prepared and synchronized on separate days). The Gapdh gene was used as an internal control. The relative expression levels were computed via the 2 −ΔΔCT method. CT6 is double plotted. d The concentration of CD26/DPPIV in the supernatant of primary mouse epidermal cells postsynchronization in vitro ( n = 3 biological replicates, each from an independent primary culture prepared and synchronized on separate days) ( P < 0.001). CT6 is double plotted. e Diurnal mRNA expression of DPP4 in mouse epidermal cells. Bmal1 ΔEC , epithelium cell-specific Bmal1 knockout mice. Statistics were obtained from a publicly available dataset ( GSE190035 ), with values representing the log2-transformed mean RPKM from 4 biological replicates per time point. ZT0 is double plotted.The data are presented as the means ± SEMs and were analyzed by one-way ANOVA with Bonferroni multiple comparisons ( b , d ) and JTK_Cycle ( c , e ). Source data are provided as a Source Data file.

Article Snippet: In the experimental groups, recombinant human CD26/DPPIV protein (1000 ng/mL, 11244-SE, R&D Systems) or Sitagliptin phosphate monohydrate (DPPIV inhibitor, 200 μg/mL, S4002, Selleck) was added to the respective groups.

Techniques: Immunofluorescence, Expressing, In Vitro, Control, Concentration Assay, Knock-Out, Transformation Assay

Journal: Nature Communications

Article Title: Circadian fluctuation of soluble CD26 dictates the impact of the timing of cord blood transplantation on acute graft-versus-host disease

doi: 10.1038/s41467-026-68958-4

Figure Lengend Snippet: PBMCs from healthy donors were cultured with PHA-L (control group), PHA-L plus CD26/DPPIV (sCD26 group), or PHA-L plus Sitagliptin (DPPIV inhibitor, DPPIVi group) for 72 h. a Experimental design. PBMCs from healthy donors were cultured with PHA-L (control group), PHA-L plus CD26/DPPIV (sCD26 group), or PHA-L plus Sitagliptin (DPPIV inhibitor, DPPIVi group) for 72 h. b , c Representative plots (left) and quantified percentages (right) of CD86 + ( b ) and CD80 + ( c ) CD14 + cells after 72 h of PBMCs coculture in different groups (pooled data from 8 healthy donors across four independent experiments). d – i Representative plots (left) and quantified percentages (right) of Ki-67 + , IFNγ + , and CD38 + cells among CD4 + T cells ( d , f , h ) and CD8 + T cells ( e , g , i ) after 72 h of PBMCs coculture in different groups (pooled data from 6 healthy donors across three independent experiments).The data are presented as the means ± SEMs and were analyzed by one-way ANOVA with the Bonferroni correction for multiple comparisons ( b – i ). All P values are two-sided and reported as exact values unless <0.001. Source data are provided as a Source Data file.

Article Snippet: In the experimental groups, recombinant human CD26/DPPIV protein (1000 ng/mL, 11244-SE, R&D Systems) or Sitagliptin phosphate monohydrate (DPPIV inhibitor, 200 μg/mL, S4002, Selleck) was added to the respective groups.

Techniques: Cell Culture, Control