Mouse Anti-Human Pepsinogen I monoclonal antibody, clone 9110

Mutations impacting specific stages of cell growth and division have provided a foundation for dissecting mechanisms that underlie cell cycle progression. We have undertaken an objective examination of the yeast cell cycle through flow cytometric analysis of DNA content in TetO(7) promoter mutant strains representing 75% of all essential yeast genes. More than 65% of the strains displayed specific alterations in DNA content, suggesting that reduced function of an essential gene in most cases impairs progression through a specific stage of the cell cycle. Because of the large number of essential genes required for protein biosynthesis, G1 accumulation was the most common phenotype observed in our analysis. In contrast, relatively few mutants displayed S-phase delay, and most of these were defective in genes required for DNA replication or nucleotide metabolism. G2 accumulation appeared to arise from a variety of defects. In addition to providing a global view of the diversity of essential cellular processes that influence cell cycle progression, these data also provided predictions regarding the functions of individual genes: we identified four new genes involved in protein trafficking (NUS1, PHS1, PGA2, PGA3), and we found that CSE1 and SMC4 are important for DNA replication.

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.