Anti-Pepsinogen I monoclonal antibody, clone 9004 (00/23)

Gastroesophageal reflux is a common gastrointestinal issue that can lead to aspiration and contribute to respiratory problems. Little is known about how reflux can alter the respiratory microenvironment. We aimed to determine if the presence of gastric pepsinogen in the trachea was associated with changes in the microbial and inflammatory microenvironment. A pediatric cohort at high risk of reflux aspiration was prospectively recruited, and the tracheal microenvironment was examined. Pepsinogen A3 (PGA3) and cytokines were measured. The microbiome (bacterial and fungal) was profiled using 16S rRNA and internal transcribed spacer 2 (ITS2) amplicon sequencing. Increased bacterial richness and an altered composition driven by an enrichment of Prevotella correlated with high PGA3 levels. Fungal richness increased with PGA3, with higher Candida relative abundances observed in a subset of samples with high PGA3 levels. Source tracking of tracheal microbial taxa against taxa from matched oral and gastric samples revealed a significantly greater contribution of oral than of gastric taxa with higher PGA3 levels. Tracheal cytokines were differentially produced when stratified according to PGA3, with higher levels of interleukin-1 (IL-1)-related cytokines and IL-8 being associated with high PGA3 levels. Network analysis across cytokine and microbiome measures identified relationships between IL-1-related proteins and microbial taxa, with the presence of respiratory issues associated with higher levels of IL-1 beta, IP-10, and Prevotella. In conclusion, PGA3 levels in the trachea are correlated with increases in specific microbial taxa and inflammatory molecules, with an increase in oral microbes with increasing PGA3.

Background: The objective of this study was to discover and to validate novel noninvasive biomarkers that distinguish between benign prostate hyperplasia (BPH) and localized prostate cancer (PCa), thereby helping to solve the diagnostic dilemma confronting clinicians who treat these patients. Methods: Quantitative iTRAQ LC/LC/MS/MS analysis was used to identify proteins that are differentially expressed in the urine of men with BPH compared with those who have localized PCa. These proteins were validated in 173 urine samples from patients diagnosed with BPH (N = 83) and PCa (N = 90). Multivariate logistic regression analysis was used to identify the predictive biomarkers. Results: Three proteins, beta 2M, PGA3, and MUC3 were identified by iTRAQ and validated by immunoblot analyses. Univariate analysis demonstrated significant elevations in urinary beta 2M (P < 0.001), PGA3 (P = 0.006), and MUC3 (P = 0.018) levels found in the urine of PCa patients. Multivariate logistic regression analysis revealed AUC values ranging from 0.618 for MUC3 (P = 0.009), 0.625 for PGA3 (P < 0.008), and 0.668 for beta 2M (P < 0.001). The combination of all three demonstrated an AUC of 0.710 (95% CI: 0.631 - 0.788, P < 0.001); diagnostic accuracy improved even more when these data were combined with PSA categories (AUC = 0.812, (95% CI: 0.740 - 0.885, P < 0.001). Conclusions: Urinary beta 2M, PGA3, and MUC3, when analyzed alone or when multiplexed with clinically defined categories of PSA, may be clinically useful in noninvasively resolving the dilemma of effectively discriminating between BPH and localized PCa.