Display of probability densities for data from a continuous distribution

Based on cumulative distribution functions, Fourier series expansion and Kolmogorov tests, we present a simple method to display probability densities for data drawn from a continuous distribution. It is often more efficient than using histograms.Comment: 5 pages, 4 figures, presented at Computer Simulation Studies XXIV, Athens, GA, 201

WNT signalling in prostate cancer

Genome sequencing and gene expression analyses of prostate tumours have highlighted the potential importance of genetic and epigenetic changes observed in WNT signalling pathway components in prostate tumours-particularly in the development of castration-resistant prostate cancer. WNT signalling is also important in the prostate tumour microenvironment, in which WNT proteins secreted by the tumour stroma promote resistance to therapy, and in prostate cancer stem or progenitor cells, in which WNT-β-catenin signals promote self-renewal or expansion. Preclinical studies have demonstrated the potential of inhibitors that target WNT receptor complexes at the cell membrane or that block the interaction of β-catenin with lymphoid enhancer-binding factor 1 and the androgen receptor, in preventing prostate cancer progression. Some WNT signalling inhibitors are in phase I trials, but they have yet to be tested in patients with prostate cancer

Sphingomyelin Functions as a Novel Receptor for Helicobacter pylori VacA

The vacuolating cytotoxin (VacA) of the gastric pathogen Helicobacter pylori binds and enters epithelial cells, ultimately resulting in cellular vacuolation. Several host factors have been reported to be important for VacA function, but none of these have been demonstrated to be essential for toxin binding to the plasma membrane. Thus, the identity of cell surface receptors critical for both toxin binding and function has remained elusive. Here, we identify VacA as the first bacterial virulence factor that exploits the important plasma membrane sphingolipid, sphingomyelin (SM), as a cellular receptor. Depletion of plasma membrane SM with sphingomyelinase inhibited VacA-mediated vacuolation and significantly reduced the sensitivity of HeLa cells, as well as several other cell lines, to VacA. Further analysis revealed that SM is critical for VacA interactions with the plasma membrane. Restoring plasma membrane SM in cells previously depleted of SM was sufficient to rescue both toxin vacuolation activity and plasma membrane binding. VacA association with detergent-resistant membranes was inhibited in cells pretreated with SMase C, indicating the importance of SM for VacA association with lipid raft microdomains. Finally, VacA bound to SM in an in vitro ELISA assay in a manner competitively inhibited by lysenin, a known SM-binding protein. Our results suggest a model where VacA may exploit the capacity of SM to preferentially partition into lipid rafts in order to access the raft-associated cellular machinery previously shown to be required for toxin entry into host cells

Monitoring the Long-Term Molecular Epidemiology of the Pneumococcus and Detection of Potential ‘Vaccine Escape’ Strains

While the pneumococcal protein conjugate vaccines reduce the incidence in invasive pneumococcal disease (IPD), serotype replacement remains a major concern. Thus, serotype-independent protection with vaccines targeting virulence genes, such as PspA, have been pursued. PspA is comprised of diverse clades that arose through recombination. Therefore, multi-locus sequence typing (MLST)-defined clones could conceivably include strains from multiple PspA clades. As a result, a method is needed which can both monitor the long-term epidemiology of the pneumococcus among a large number of isolates, and analyze vaccine-candidate genes, such as pspA, for mutations and recombination events that could result in 'vaccine escape' strains.We developed a resequencing array consisting of five conserved and six variable genes to characterize 72 pneumococcal strains. The phylogenetic analysis of the 11 concatenated genes was performed with the MrBayes program, the single nucleotide polymorphism (SNP) analysis with the DNA Sequence Polymorphism program (DnaSP), and the recombination event analysis with the recombination detection package (RDP).The phylogenetic analysis correlated with MLST, and identified clonal strains with unique PspA clades. The DnaSP analysis correlated with the serotype-specific diversity detected using MLST. Serotypes associated with more than one ST complex had a larger degree of sequence polymorphism than a serotype associated with one ST complex. The RDP analysis confirmed the high frequency of recombination events in the pspA gene.The phylogenetic tree correlated with MLST, and detected multiple PspA clades among clonal strains. The genetic diversity of the strains and the frequency of recombination events in the mosaic gene, pspA were accurately assessed using the DnaSP and RDP programs, respectively. These data provide proof-of-concept that resequencing arrays could play an important role within research and clinical laboratories in both monitoring the molecular epidemiology of the pneumococcus and detecting 'vaccine escape' strains among vaccine-candidate genes

The alpha-kinase family: an exceptional branch on the protein kinase tree

The alpha-kinase family represents a class of atypical protein kinases that display little sequence similarity to conventional protein kinases. Early studies on myosin heavy chain kinases in Dictyostelium discoideum revealed their unusual propensity to phosphorylate serine and threonine residues in the context of an alpha-helix. Although recent studies show that some members of this family can also phosphorylate residues in non-helical regions, the name alpha-kinase has remained. During evolution, the alpha-kinase domains combined with many different functional subdomains such as von Willebrand factor-like motifs (vWKa) and even cation channels (TRPM6 and TRPM7). As a result, these kinases are implicated in a large variety of cellular processes such as protein translation, Mg2+ homeostasis, intracellular transport, cell migration, adhesion, and proliferation. Here, we review the current state of knowledge on different members of this kinase family and discuss the potential use of alpha-kinases as drug targets in diseases such as cancer

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases