HBD3 Induces PD-L1 Expression on Head and Neck Squamous Cell Carcinoma Cell Lines.

Human ß-defensin 3 (HBD3) is an antimicrobial peptide up-regulated in the oral tissues of individuals with head and neck squamous cell carcinomas (HNSCC) and oral squamous cell carcinomas (SCC) and present in high concentrations in their saliva. In this study, we determined if HBD3 contributes to HNSCC pathogenesis by inducing programmed death-ligand 1 (PD-L1) expression on HNSCC cell lines. For this, SCC cell lines SCC4, SCC15, SCC19, SCC25, and SCC99 (5.0 × 104 viable cells) were used. Cells were incubated with IFNγ (0.6 µM) and HBD3 (0.2, 2.0, or 20.0 µM) for 24 h. Cells alone served as controls. Cells were then treated with anti-human APC-CD274 (PD-L1) and Live/Dead Fixable Green Dead Cell Stain. Cells treated with an isotype antibody and cells alone served as controls. All cell suspensions were analyzed in a LSR II Violet Flow Cytometer. Cytometric data was analyzed using FlowJo software. Treatment with IFNγ (0.6 µM) increased the number of cells expressing PD-L1 (p < 0.05) with respect to controls. Treatment with HBD3 (20.0 µM) also increased the number of cells expressing PD-L1 (p < 0.05) with respect to controls. However, treatment with IFNγ (0.6 µM) was not significantly different from treatment with HBD3 (20.0 µM) and the numbers of cells expressing PD-L1 were similar (p = 1). Thus, HBD3 increases the number of cells expressing PD-L1. This is a novel concept, but the role HBD3 contributes to HNSCC pathogenesis by inducing PD-L1 expression in tumors will have to be determined.

Computational Models Accurately Predict Multi-Cell Biomarker Profiles in Inflammation and Cancer.

Individual computational models of single myeloid, lymphoid, epithelial, and cancer cells were created and combined into multi-cell computational models and used to predict the collective chemokine, cytokine, and cellular biomarker profiles often seen in inflamed or cancerous tissues. Predicted chemokine and cytokine output profiles from multi-cell computational models of gingival epithelial keratinocytes (GE KER), dendritic cells (DC), and helper T lymphocytes (HTL) exposed to lipopolysaccharide (LPS) or synthetic triacylated lipopeptide (Pam3CSK4) as well as multi-cell computational models of multiple myeloma (MM) and DC were validated using the observed chemokine and cytokine responses from the same cell type combinations grown in laboratory multi-cell cultures with accuracy. Predicted and observed chemokine and cytokine responses of GE KER + DC + HTL exposed to LPS and Pam3CSK4 matched 75% (15/20, p = 0.02069) and 80% (16/20, P = 0.005909), respectively. Multi-cell computational models became 'personalized' when cell line-specific genomic data were included into simulations, again validated with the same cell lines grown in laboratory multi-cell cultures. Here, predicted and observed chemokine and cytokine responses of MM cells lines MM.1S and U266B1 matched 75% (3/4) and MM.1S and U266B1 inhibition of DC marker expression in co-culture matched 100% (6/6). Multi-cell computational models have the potential to identify approaches altering the predicted disease-associated output profiles, particularly as high throughput screening tools for anti-inflammatory or immuno-oncology treatments of inflamed multi-cellular tissues and the tumor microenvironment.

Matrix metalloproteinase (MMP) and immunosuppressive biomarker profiles of seven head and neck squamous cell carcinoma (HNSCC) cell lines.

BACKGROUND: Biomarkers like programmed death ligand-1 (PDL1) have become a focal point for immunotherapeutic checkpoint inhibition in head and neck squamous cell carcinoma (HNSCC). However, it's only part of the total immunosuppressive biomarker profile of HNSCC cells. Matrix metalloproteinases (MMPs) are enzymes that break down the basement membrane allowing cancer cells to metastasize and play an important role in the tumor microenvironment. MMPs can also activate certain cytokines, growth factors, and chemokines post-translationally. The objective of this study was to determine MMP and biomarker profiles of seven different HNSCC cell lines. METHODS: Authenticated cell lines were grown in minimal media at 1×106 viable cells/mL and incubated at 37 °C. After 24 hrs supernatants were collected, and adhering cells were lysed. Multiplex immunoassays were used to determine MMP1, MMP7, MMP9, IL-6, VEGFA, IL-1α, TNF-α, GM-CSF, IL-1RA, and IL-8 concentrations in supernatants. ELISAs were used to determine PDL1, CD47, FASL, and IDO concentrations in cell lysates. A one-way ANOVA was fit to examine log-transformed concentrations of biomarkers between seven HNSCC cell lines, and pairwise group comparisons were conducted using post- hoc Tukey's honest significance test (α=0.05). RESULTS: Significant differences (P<0.05) in MMP and biomarker concentrations were found between the seven HNSCC cell lines. For example, MMP9 was highest in SCC25 and UM-SCC99, MMP7 was highest in SCC25 and UM-SCC19, and MMP1 was highest in SCC25. CONCLUSIONS: These results suggest different patients' HNSCC cells can express distinct profiles of select biomarkers and MMPs, which could be due to metastatic stage of the cancer, primary tumor site, type of tissue the tumor originated from, or genomic differences between patients. MMP and biomarker expression profiles should be considered when choosing cell lines for future studies. The results support the reason for personalized medicine and the need to further investigate how it can be used to treat HNSCC.

Correction to: Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

It has been highlighted that in the original manuscript [1] Table S3 'An example of the predictive computational modeling process. Specific details on an annexure section of the PD-L1 pathway show the step-by-step reactions, mechanisms, and reaction equations that occur. Such reactions also occurred in all of the other pathways' was omitted and did not appear in the Additional files and that the Additional files were miss-numbered thereafter. This Correction shows the correct and incorrect Additional files. The original article has been updated.

Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

BACKGROUND: Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. METHODS: We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. RESULTS: Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. CONCLUSIONS: Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.

Cell genomics and immunosuppressive biomarker expression influence PD-L1 immunotherapy treatment responses in HNSCC-a computational study.

OBJECTIVES: Programmed death-ligand 1 (PD-L1) expression is correlated with objective response rates to PD-1 and PD-L1 immunotherapies. However, both immunotherapies have only demonstrated 12%-24.8% objective response rates in patients with head and neck squamous cell carcinoma (HNSCC), demonstrating a need for a more accurate method to identify those who will respond before their therapy. Immunohistochemistry to detect PD-L1 reactivity in tumors can be challenging, and additional methods are needed to predict and confirm PD-L1 expression. Here, we hypothesized that HNSCC tumor cell genomics influences cell signaling and downstream effects on immunosuppressive biomarkers and that these profiles can predict patient clinical responses. STUDY DESIGN: We identified deleterious gene mutations in SCC4, SCC15, and SCC25 and created cell line-specific predictive computational simulation models. The expression of 24 immunosuppressive biomarkers were then predicted and used to sort cell lines into those that would respond to PD-L1 immunotherapy and those that would not. RESULTS: SCC15 and SCC25 were identified as cell lines that would respond to PD-L1 immunotherapy treatment and SCC4 was identified as a cell line that would not likely respond to PD-L1 immunotherapy treatment. CONCLUSIONS: This approach, when applied to HNSCC cells, has the ability to predict PD-L1 expression and predict PD-1- or PD-L1-targeted treatment responses in these patients.

Mouse-adapted MERS coronavirus causes lethal lung disease in human DPP4 knockin mice.

The Middle East respiratory syndrome (MERS) emerged in Saudi Arabia in 2012, caused by a zoonotically transmitted coronavirus (CoV). Over 1,900 cases have been reported to date, with ∼36% fatality rate. Lack of autopsies from MERS cases has hindered understanding of MERS-CoV pathogenesis. A small animal model that develops progressive pulmonary manifestations when infected with MERS-CoV would advance the field. As mice are restricted to infection at the level of DPP4, the MERS-CoV receptor, we generated mice with humanized exons 10-12 of the mouse Dpp4 locus. Upon inoculation with MERS-CoV, human DPP4 knockin (KI) mice supported virus replication in the lungs, but developed no illness. After 30 serial passages through the lungs of KI mice, a mouse-adapted virus emerged (MERSMA) that grew in lungs to over 100 times higher titers than the starting virus. A plaque-purified MERSMA clone caused weight loss and fatal infection. Virus antigen was observed in airway epithelia, pneumocytes, and macrophages. Pathologic findings included diffuse alveolar damage with pulmonary edema and hyaline membrane formation associated with accumulation of activated inflammatory monocyte-macrophages and neutrophils in the lungs. Relative to the parental MERS-CoV, MERSMA viruses contained 13-22 mutations, including several within the spike (S) glycoprotein gene. S-protein mutations sensitized viruses to entry-activating serine proteases and conferred more rapid entry kinetics. Recombinant MERSMA bearing mutant S proteins were more virulent than the parental virus in hDPP4 KI mice. The hDPP4 KI mouse and the MERSMA provide tools to investigate disease causes and develop new therapies.

Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models.

PURPOSE: Interaction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity. METHODS: Multiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture. RESULT: The observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression. CONCLUSION: This concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.

Expression of Membrane-Bound Mucins and p63 in Distinguishing Mucoepidermoid Carcinoma from Papillary Cystadenoma.

The aim of this study was to compare the immunoexpression of epithelial mucins (MUCs) in salivary duct cysts, papillary cystadenomas, and mucoepidermoid carcinomas and to evaluate if any of these markers could be useful for differentiating between mucoepidermoid carcinoma and papillary cystadenoma. We also sought to validate the p63 expression pattern found to differentiate between mucoepidermoid carcinoma and papillary cystadenoma. Immunoexpression of MUC1, MUC2, MUC4, MUC7, and p63 was studied and quantified in 22 mucoepidermoid carcinomas, 12 papillary cystadenomas, and 3 salivary duct cysts. The immunohistochemical evaluation was collectively performed by 3 oral pathologists. Scores and trends in proportions were assessed using the nonparametric Wilcoxon-Mann-Whitney rank sum test. Mucoepidermoid carcinomas, papillary cystadenomas, and salivary duct cysts demonstrated variable MUC expression patterns. All tumors were positive for p63 immunoexpression with p63 labeling in salivary duct cysts and papillary cystadenomas (15/15) limited to the basal layers of the cystic spaces, whereas in mucoepidermoid carcinomas (22/22) the p63 labeling extended throughout the suprabasal layers (p < 0.001). This study adds more confirmatory data to validate that the reactivity pattern of p63 protein can be used in distinguishing between papillary cystadenoma and low-grade mucoepidermoid carcinoma. Although positive reactivity in a tumor with MUC1 and MUC4 was inconclusive, negative reactivity suggests the diagnosis of a benign PC or SDC.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells.

Long-chain bases, found in the oral cavity, have potent antimicrobial activity against oral pathogens. In an article associated with this dataset, Poulson and colleagues determined the cytotoxicities of long-chain bases (sphingosine, dihydrosphingosine, and phytosphingosine) for human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), dendritic cells (DC), and squamous cell carcinoma (SCC) cell lines [1]. Poulson and colleagues found that GE keratinocytes were more resistant to long-chain bases as compared to GF, DC, and SCC cell lines [1]. In this study, we assess the susceptibility of DC to lower concentrations of long chain bases. 0.2-10.0 µM long-chain bases and GML were not cytotoxic to DC; 40.0-80.0 µM long-chain bases, but not GML, were cytotoxic for DC; and 80.0 µM long-chain bases were cytotoxic to DC and induced cellular damage and death in less than 20 mins. Overall, the LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections.

Cytotoxicity of HBD3 for dendritic cells, normal human epidermal keratinocytes, hTERT keratinocytes, and primary oral gingival epithelial keratinocytes in cell culture conditions.

Human ß-defensin 3 (HBD3) is a prominent host defense peptide. In our recent work, we observed that HBD3 modulates pro-inflammatory agonist-induced chemokine and cytokine responses in human myeloid dendritic cells (DCs), often at 20.0 µM concentrations. Since HBD3 can be cytotoxic in some circumstances, it is necessary to assess its cytotoxicity for DCs, normal human epidermal keratinocytes (NHEKs), human telomerase reverse transcriptase (hTERT) keratinocytes, and primary oral gingival epithelial (GE) keratinocytes in different cell culture conditions. Cells, in serum free media with resazurin and in complete media with 10% fetal bovine serum and resazurin, were incubated with 5, 10, 20, and 40 µM HBD3. Cytotoxicity was determined by measuring metabolic conversion of resazurin to resorufin. The lethal dose 50 (LD50, mean µM±Std Err) values were determined from the median fluorescent intensities of test concentrations compared to live and killed cell controls. The LD50 value range of HBD3 was 18.2-35.9 µM in serum-free media for DCs, NHEKs, hTERT keratinocytes, and GE keratinocytes, and >40.0 µM in complete media. Thus, HBD3 was cytotoxic at higher concentrations, which must be considered in future studies of HBD3-modulated chemokine and cytokine responses in vitro.

Novel biomarkers of periodontitis and/or obesity in saliva-An exploratory analysis.

OBJECTIVE: Recent studies point to the clinical and research utility of saliva as a valuable diagnostic aid for monitoring periodontal health. The objectives of this study were to detect novel biomarkers attributed to chronic inflammation in saliva and to determine if the levels of these markers correlate with severity of periodontitis and with standard obesity measures in participants in a periodontal maintenance program. DESIGN: In this cross-sectional assessment of 63 participants, unstimulated whole saliva was collected after recording anthropometric and clinical parameters of obesity and periodontitis, respectively. The levels of interleukin-1 receptor antagonist (IL-1ra), sCD40L, granzyme B and alpha-fetoprotein (AFP) in saliva were determined using multiplex proteomic immunoassays. The correlation between the four tested biomarker concentrations and obesity/periodontal measures was determined. RESULTS: Positive correlation between fat% and granzyme B levels (r=0.292; p=0.020) and negative correlation between BMI and sCD40L (r=0.256; p=0.043) was observed. In addition, positive correlation between severity of periodontal disease and levels of IL1-ra (r=0.253; p=0.046) and negative correlation between periodontitis severity and sCD40L salivary levels (r=0.272; p=0.031) was noted. None of the above correlations remained statistically significant after multiple comparisons adjustment. After adjustment for clinical covariates, the relationship between sCD40L and periodontal severity remained suggestive (p=0.081). CONCLUSIONS: Levels of four novel biomarkers of periodontitis were detectable in saliva of subjects enrolled in a periodontal maintenance program. Prospective studies with larger sample sizes and other populations are warranted to explore the diagnostic applicability of these markers.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells.

Long-chain bases are present in the oral cavity. Previously we determined that sphingosine, dihydrosphingosine, and phytosphingosine have potent antimicrobial activity against oral pathogens. Here, we determined the cytotoxicities of long-chain bases for oral cells, an important step in considering their potential as antimicrobial agents for oral infections. This information would clearly help in establishing prophylactic or therapeutic doses. To assess this, human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), and dendritic cells (DC) were exposed to 10.0-640.0 µM long-chain bases and glycerol monolaurate (GML). The effects of long-chain bases on cell metabolism (conversion of resazurin to resorufin), membrane permeability (uptake of propidium iodide or SYTOX-Green), release of cellular contents (LDH), and cell morphology (confocal microscopy) were all determined. GE keratinocytes were more resistant to long-chain bases as compared to GF and DC, which were more susceptible. For DC, 0.2-10.0 µM long-chain bases and GML were not cytotoxic; 40.0-80.0 µM long-chain bases, but not GML, were cytotoxic; and 80.0 µM long-chain bases induced cellular damage and death in less than 20 min. The LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections.

A cross-sectional assessment of biomarker levels around implants versus natural teeth in periodontal maintenance patients.

BACKGROUND: Recent studies point to the clinical utility of using peri-implant sulcular fluid (PISF) as a valuable diagnostic aid for monitoring peri-implant tissue health. The objectives of this study are to determine the levels of key biomarkers in PISF in periodontal maintenance participants and compare them with their corresponding levels in gingival crevicular fluid (GCF) obtained from the same participants. METHODS: PISF and GCF were collected from an implant and a contralateral natural tooth after the clinical examination of 73 participants. The levels of interleukin (IL)-1α, IL-1ß, IL-6, IL-8, IL-10, IL-12, IL-17A, tumor necrosis factor (TNF)-α, C-reactive protein, osteoprotegerin, leptin, and adiponectin were determined using multiplex proteomic immunoassays. The correlation of biomarker concentrations between GCF versus PISF, within GCF or PISF, and with several covariates (age, brushing frequency, days since professional cleaning, probing depth [PD], and plaque index) were also determined. RESULTS: Significantly higher levels of IL-17A (P = 0.02) and TNF-α (P = 0.03) were noted in PISF when compared with their levels in GCF. Significant positive correlations were noted between the concentrations of cytokines in PISF versus their levels in GCF. Among the covariates, a significant positive correlation was noted between mean PDs around implants and levels of IL-1ß (P <0.05) and IL-8 (P <0.05) in PISF. CONCLUSION: The results of this study point to the differential expression of specific biomarkers in GCF versus their levels in PISF in periodontal maintenance patients, which is critical information before establishing PISF as a diagnostic fluid to monitor peri-implant health.

Body fat indices and biomarkers of inflammation: a cross-sectional study with implications for obesity and peri-implant oral health.

PURPOSE: To examine the relationships between three measures of body fat-body mass index (BMI), waist circumference (WC), and total body fat percent-and markers of inflammation around dental implants in stable periodontal maintenance patients. MATERIALS AND METHODS: Seventy-three subjects were enrolled in this cross-sectional assessment. The study visit consisted of a physical examination that included anthropologic measurements of body composition (BMI, WC, body fat %); intraoral assessments were performed (full-mouth plaque index, periodontal and peri-implant comprehensive examinations) and peri-implant sulcular fluid (PISF) was collected on the study implants. Levels of interleukin (IL)-1α, IL-1ß, IL-6, IL-8, IL-10, IL-12, IL-17, tumor necrosis factor-α, C-reactive protein, osteoprotegerin, leptin, and adiponectin in the PISF were measured using multiplex proteomic immunoassays. Correlation analysis with body fat measures was then performed using appropriate statistical methods. RESULTS: After adjustments for covariates, regression analyses revealed statistically significant correlation between IL-1ß in PISF and WC (R = 0.33; P = .0047). CONCLUSION: In this study in stable periodontal maintenance patients, a modest but statistically significant positive correlation was observed between the levels of IL-1ß, a major proinflammatory cytokine in PISF, and WC, a reliable measure of central obesity.

Inflammasome-independent IL-1ß mediates autoinflammatory disease in Pstpip2-deficient mice.

Chronic recurrent multifocal osteomyelitis (CRMO) is a human autoinflammatory disorder that primarily affects bone. Missense mutation (L98P) of proline-serine-threonine phosphatase-interacting protein 2 (Pstpip2) in mice leads to a disease that is phenotypically similar to CRMO called chronic multifocal osteomyelitis (cmo). Here we show that deficiency of IL-1RI in cmo mice resulted in a significant reduction in the time to onset of disease as well as the degree of bone pathology. Additionally, the proinflammatory cytokine IL-1ß, but not IL-1α, played a critical role in the pathology observed in cmo mice. In contrast, disease in cmo mice was found to be independent of the nucleotide-binding domain, leucine-rich repeat-containing family, pyrin domain-containing 3 (NLRP3) inflammasome as well as caspase-1. Neutrophils, but not bone marrow-derived macrophages, from cmo mice secreted increased IL-1ß in response to ATP, silica, and Pseudomonas aeruginosa compared with neutrophils from WT mice. This aberrant neutrophil response was sensitive to inhibition by serine protease inhibitors. These results demonstrate an inflammasome-independent role for IL-1ß in disease progression of cmo and implicate neutrophils and neutrophil serine proteases in disease pathogenesis. These data provide a rationale for directly targeting IL-1RI or IL-1ß as a therapeutic strategy in CRMO.

Oral inflammation, a role for antimicrobial peptide modulation of cytokine and chemokine responses.

Acute and chronic inflammation commonly occurs throughout the oral cavity. The most common causes are physical damage and microbial infections, and less frequently immune reactions and malignant changes. All of these processes result in the induction of antimicrobial peptides, chemokines and cytokines that lead to cellular infiltrates, a vascular response, tissue destruction and cellular proliferation. A fascinating concept developing in the current literature suggests that antimicrobial peptides modulate the production of chemokines, cytokines and other cellular mediators and that this may have a larger ramification as an underlying mechanism mediating inflammation. Here, we propose that the ability of antimicrobial peptides to induce chemokines and anti-inflammatory or proinflammatory cytokines plays an important role in the early events of oral inflammation and may be a target for the prevention or treatment of oral inflammatory conditions.

Defensin DEFB103 bidirectionally regulates chemokine and cytokine responses to a pro-inflammatory stimulus.

Human ß defensin DEFB103 acts as both a stimulant and an attenuator of chemokine and cytokine responses: a dichotomy that is not entirely understood. Our predicted results using an in silico simulation model of dendritic cells and our observed results in human myeloid dendritic cells, show that DEFB103 significantly (p < 0.05) enhanced 6 responses, attenuated 7 responses, and both enhanced/attenuated the CXCL1 and TNF responses to Porphyromonas gingivalis hemagglutinin B (HagB). In murine JAWSII dendritic cells, DEFB103 significantly attenuated, yet rarely enhanced, the Cxcl2, Il6, and Csf3 responses to HagB; and in C57/BL6 mice, DEFB103 significantly enhanced, yet rarely attenuated, the Cxcl1, Csf1, and Csf3 responses. Thus, DEFB103 influences pro-inflammatory activities with the concentration of DEFB103 and order of timing of DEFB103 exposure to dendritic cells, with respect to microbial antigen exposure to cells, being paramount in orchestrating the onset, magnitude, and composition of the chemokine and cytokine response.

Quantitation of SPLUNC1 in saliva with an xMAP particle-based antibody capture and detection immunoassay.

The short palate lung and nasal epithelial clone 1 (SPLUNC1) protein may be differentially expressed in oral infections, oral inflammatory disorders, or oral malignancies and may be involved in innate immune responses in the oral cavity. However, the actual concentration of SPLUNC1 in saliva has not previously been determined. In this study, we determined the concentrations of SPLUNC1 in saliva using a particle-based antibody capture and detection immunoassay. A commercial goat anti-rhSPLUNC1 polyclonal antibody (AF1897) was linked to fluorescent polystyrene microspheres and used as the capture antibody. A commercial mouse IgG2b anti-rhSPLUNC1 monoclonal antibody (MAB1897) was biotinylated and used as the detection antibody. Western blot and 2-dimensional fluorescence difference gel electrophoresis (2-D DIGE) analysis of immunoprecipitated rhSPLUNC1 and SPLUNC1 from saliva were used to show that the capture AF1897 and detection MAB1897 antibodies both recognized SPLUNC1. Protein concentrations in saliva from 20 subjects ranged from 0.9 to 23.9mg/ml; SPLUNC1 concentrations ranged from 34.7ng/ml to 13.8µg/ml; and SPLUNC concentrations normalized per mg of total salivary protein ranged from 4.7ng/ml to 5.3µg/ml. These results show that SPLUNC1 is detected in saliva in a variety of concentrations. This immunoassay may prove to be useful in determining the concentration of SPLUNC1 in saliva for assessing its role in the pathogenesis of oral infections, oral inflammatory disorders, or oral malignancies.