The molecular basis of genistein-induced mitotic arrest and exit of self-renewal in embryonal carcinoma and primary cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Genistein is an isoflavonoid present in soybeans that exhibits anti-carcinogenic properties. The issue of genistein as a potential anti-cancer drug has been addressed in some papers, but comprehensive genomic analysis to elucidate the molecular mechanisms underlying the effect elicited by genistein on cancer cells have not been performed on primary cancer cells, but rather on transformed cell lines. In the present study, we treated primary glioblastoma, rhabdomyosarcoma, hepatocellular carcinoma and human embryonic carcinoma cells (NCCIT) with μ-molar concentrations of genistein and assessed mitotic index, cell morphology, global gene expression, and specific cell-cycle regulating genes. We compared the expression profiles of NCCIT cells with that of the cancer cell lines in order to identify common genistein-dependent transcriptional changes and accompanying signaling cascades.</p> <p>Methods</p> <p>We treated primary cancer cells and NCCIT cells with 50 μM genistein for 48 h. Thereafter, we compared the mitotic index of treated versus untreated cells and investigated the protein expression of key regulatory self renewal factors as OCT4, SOX2 and NANOG. We then used gene expression arrays (Illumina) for genome-wide expression analysis and validated the results for genes of interest by means of Real-Time PCR. Functional annotations were then performed using the DAVID and KEGG online tools.</p> <p>Results</p> <p>We found that cancer cells treated with genistein undergo cell-cycle arrest at different checkpoints. This arrest was associated with a decrease in the mRNA levels of core regulatory genes, <it>PBK</it>, <it>BUB1</it>, and <it>CDC20 </it>as determined by microarray-analysis and verified by Real-Time PCR. In contrast, human NCCIT cells showed over-expression of <it>GADD45 A </it>and <it>G </it>(growth arrest- and DNA-damage-inducible proteins 45A and G), as well as down-regulation of OCT4, and NANOG protein. Furthermore, genistein induced the expression of apoptotic and anti-migratory proteins p53 and p38 in all cell lines. Genistein also up-regulated steady-state levels of both <it>CYCLIN A </it>and <it>B</it>.</p> <p>Conclusion</p> <p>The results of the present study, together with the results of earlier studies show that genistein targets genes involved in the progression of the M-phase of the cell cycle. In this respect it is of particular interest that this conclusion cannot be drawn from comparison of the individual genes found differentially regulated in the datasets, but by the rather global view of the pathways influenced by genistein treatment.</p

Fishery-Independent Data Reveal Negative Effect of Human Population Density on Caribbean Predatory Fish Communities

BACKGROUND: Understanding the current status of predatory fish communities, and the effects fishing has on them, is vitally important information for management. However, data are often insufficient at region-wide scales to assess the effects of extraction in coral reef ecosystems of developing nations. METHODOLOGY/PRINCIPAL FINDINGS: Here, I overcome this difficulty by using a publicly accessible, fisheries-independent database to provide a broad scale, comprehensive analysis of human impacts on predatory reef fish communities across the greater Caribbean region. Specifically, this study analyzed presence and diversity of predatory reef fishes over a gradient of human population density. Across the region, as human population density increases, presence of large-bodied fishes declines, and fish communities become dominated by a few smaller-bodied species. CONCLUSIONS/SIGNIFICANCE: Complete disappearance of several large-bodied fishes indicates ecological and local extinctions have occurred in some densely populated areas. These findings fill a fundamentally important gap in our knowledge of the ecosystem effects of artisanal fisheries in developing nations, and provide support for multiple approaches to data collection where they are commonly unavailable

Prediction of Morphine Clearance in the Paediatric Population

The pharmacokinetics of morphine in paediatrics have been widely studied using different approaches and modelling techniques. In this review, we explore advantages and disadvantages of the different data analysis techniques that have been applied, with specific focus on the accuracy of morphine clearance predictions by reported paediatric pharmacokinetic models. Twenty paediatric studies reported a wide range in morphine clearance values using traditional, rather descriptive methods. Clearance values were expressed per kilogram bodyweight, while maturation in clearance was described by comparing mean clearance per kilogram bodyweight between age-stratified subgroups. Population modelling allows for the analysis of sparse data, thereby limiting the burden to individual patients. Using this technique, continuous maturation profiles can be obtained on the basis of either fixed allometric scaling or comprehensive covariate analysis. While the models based on fixed allometric scaling resulted in complex maturation functions, all three paediatric population models for morphine yielded quite similar clearance predictions. The largest difference in clearance predictions between these three population models occurred in the first months of life, particularly in preterm neonates. Morphine clearance predictions by a physiologically based pharmacokinetic model were based on many continuous equations describing changes in underlying physiological processes across the full paediatric age range, and resulted in similar clearance predictions as well. However, preterm neonates could not be integrated in this model. In conclusion, the value of paediatric pharmacokinetic models is mostly dependent on clearance predictions and population concentration predictions, rather than on the individual description of data. For most pharmacokinetic models, however, the assessment of model performance was very limited and the accuracy of morphine clearance predictions as well as population concentration predictions was confirmed by formal evaluation and validation procedures for only one model