RNA Binding Protein CUGBP2/CELF2 Mediates Curcumin-Induced Mitotic Catastrophe of Pancreatic Cancer Cells

Curcumin inhibits the growth of pancreatic cancer tumor xenografts in nude mice; however, the mechanism of action is not well understood. It is becoming increasingly clear that RNA binding proteins regulate posttranscriptional gene expression and play a critical role in RNA stability and translation. Here, we have determined that curcumin modulates the expression of RNA binding protein CUGBP2 to inhibit pancreatic cancer growth.In this study, we show that curcumin treated tumor xenografts have a significant reduction in tumor volume and angiogenesis. Curcumin inhibited the proliferation, while inducing G2-M arrest and apoptosis resulting in mitotic catastrophe of various pancreatic cancer cells. This was further confirmed by increased phosphorylation of checkpoint kinase 2 (Chk2) protein coupled with higher levels of nuclear cyclin B1 and Cdc-2. Curcumin increased the expression of cyclooxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) mRNA, but protein levels were lower. Furthermore, curcumin increased the expression of RNA binding proteins CUGBP2/CELF2 and TIA-1. CUGBP2 binding to COX-2 and VEGF mRNA was also enhanced, thereby increasing mRNA stability, the half-life changing from 30 min to 8 h. On the other hand, silencer-mediated knockdown of CUGBP2 partially restored the expression of COX-2 and VEGF even with curcumin treatment. COX-2 and VEGF mRNA levels were reduced to control levels, while proteins levels were higher.Curcumin inhibits pancreatic tumor growth through mitotic catastrophe by increasing the expression of RNA binding protein CUGBP2, thereby inhibiting the translation of COX-2 and VEGF mRNA. These data suggest that translation inhibition is a novel mechanism of action for curcumin during the therapeutic intervention of pancreatic cancers

Leveraging structure determination with fragment screening for infectious disease drug targets: MECP synthase from Burkholderia pseudomallei

As part of the Seattle Structural Genomics Center for Infectious Disease, we seek to enhance structural genomics with ligand-bound structure data which can serve as a blueprint for structure-based drug design. We have adapted fragment-based screening methods to our structural genomics pipeline to generate multiple ligand-bound structures of high priority drug targets from pathogenic organisms. In this study, we report fragment screening methods and structure determination results for 2C-methyl-D-erythritol-2,4-cyclo-diphosphate (MECP) synthase from Burkholderia pseudomallei, the gram-negative bacterium which causes melioidosis. Screening by nuclear magnetic resonance spectroscopy as well as crystal soaking followed by X-ray diffraction led to the identification of several small molecules which bind this enzyme in a critical metabolic pathway. A series of complex structures obtained with screening hits reveal distinct binding pockets and a range of small molecules which form complexes with the target. Additional soaks with these compounds further demonstrate a subset of fragments to only bind the protein when present in specific combinations. This ensemble of fragment-bound complexes illuminates several characteristics of MECP synthase, including a previously unknown binding surface external to the catalytic active site. These ligand-bound structures now serve to guide medicinal chemists and structural biologists in rational design of novel inhibitors for this enzyme

Medical Errors: Physician and Institutional Responsibilities

When it comes to medical errors, honesty is always the best practice for your practice

Host factors are associated with vaginal microbiome structure in pregnancy in the ECHO Cohort Consortium

Using pooled vaginal microbiota data from pregnancy cohorts (N = 683 participants) in the Environmental influences on Child Health Outcomes (ECHO) Program, we analyzed 16S rRNA gene amplicon sequences to identify clinical and demographic host factors that associate with vaginal microbiota structure in pregnancy both within and across diverse cohorts. Using PERMANOVA models, we assessed factors associated with vaginal community structure in pregnancy, examined whether host factors were conserved across populations, and tested the independent and combined effects of host factors on vaginal community state types (CSTs) using multinomial logistic regression models. Demographic and social factors explained a larger amount of variation in the vaginal microbiome in pregnancy than clinical factors. After adjustment, lower education, rather than self-identified race, remained a robust predictor of L. iners dominant (CST III) and diverse (CST IV) (OR = 8.44, 95% CI = 4.06–17.6 and OR = 4.18, 95% CI = 1.88–9.26, respectively). In random forest models, we identified specific taxonomic features of host factors, particularly urogenital pathogens associated with pregnancy complications (Aerococcus christensenii and Gardnerella spp.) among other facultative anaerobes and key markers of community instability (L. iners). Sociodemographic factors were robustly associated with vaginal microbiota structure in pregnancy and should be considered as sources of variation in human microbiome studies