Complex Patterns of Chromosome 11 Aberrations in Myeloid Malignancies Target CBL,MLL, DDB1 and LMO2

Exome sequencing of primary tumors identifies complex somatic mutation patterns. Assignment of relevance of individual somatic mutations is difficult and poses the next challenge for interpretation of next generation sequencing data. Here we present an approach how exome sequencing in combination with SNP microarray data may identify targets of chromosomal aberrations in myeloid malignancies. The rationale of this approach is that hotspots of chromosomal aberrations might also harbor point mutations in the target genes of deletions, gains or uniparental disomies (UPDs). Chromosome 11 is a frequent target of lesions in myeloid malignancies. Therefore, we studied chromosome 11 in a total of 813 samples from 773 individual patients with different myeloid malignancies by SNP microarrays and complemented the data with exome sequencing in selected cases exhibiting chromosome 11 defects. We found gains, losses and UPDs of chromosome 11 in 52 of the 813 samples (6.4%). Chromosome 11q UPDs frequently associated with mutations of CBL. In one patient the 11qUPD amplified somatic mutations in both CBL and the DNA repair gene DDB1. A duplication within MLL exon 3 was detected in another patient with 11qUPD. We identified several common deleted regions (CDR) on chromosome 11. One of the CDRs associated with de novo acute myeloid leukemia (P=0.013). One patient with a deletion at the LMO2 locus harbored an additional point mutation on the other allele indicating that LMO2 might be a tumor suppressor frequently targeted by 11p deletions. Our chromosome-centered analysis indicates that chromosome 11 contains a number of tumor suppressor genes and that the role of this chromosome in myeloid malignancies is more complex than previously recognized.     

EV20, a Novel Anti-ErbB-3 Humanized Antibody,Promotes ErbB-3 Down-Regulation and Inhibits Tumor Growth In Vivo

ErbB-3 (HER-3) receptor is involved in tumor progression and resistance to therapy. Development of specific inhibitors impairing the activity of ErbB-3 is an attractive tool for cancer therapeutics. MP-RM-1, a murine monoclonal antibody targeting human ErbB-3, has shown anticancer activity in preclinical models. With the aim to provide novel candidates for clinical use, we have successfully generated a humanized version of MP-RM-1. The humanized antibody, named EV20, abrogates both ligand-dependent and ligand-independent receptor signaling of several tumor cell types, strongly promotes ErbB-3 down-regulation, and efficiently and rapidly internalizes into tumor cells. Furthermore, treatment with EV20 significantly inhibits growth of xenografts originating from prostatic, ovarian, and pancreatic cancers as well as melanoma in nude mice. In conclusion, we provide a novel candidate for ErbB-3-targeted cancer therapy.     

Barriers to interspecific hybridization between Juglans nigra L. and J. regia L species

Juglans nigra and Juglans regia are phylogenetically divergent species. Despite the economic interest in Juglans?×?intermedia (J. nigra?×? J. regia), walnut hybridization is rare under natural conditions and still difficult using controlled pollination. Here, we evaluated some reproductive mechanisms that may prevent successful natural hybridization. The study of flowering phenology of 11 J. nigra and 50 J. regia trees growing in a plantation provided information regarding the opportunity for interspecific crosses. Variation in flower size, pollen quality of putative donors, and variation in seed yield and rate of hybrid production among putative maternal trees were examined. DNA fingerprinting and parentage analyses based on nine microsatellites permitted the identification of hybrids and hybridogenic parent. Our data indicated that overlap occurred between the staminate flowering of protogynous J. regia and the beginning of pistillate flowering of protogynous J. nigra. Differences in floral size were computed between walnut species. Only three hybrids among 422 offspring of eleven J. nigra progenies were identified. Interspecific hybridization involving pollination of one early-flowering-protogynous J. nigra by three protogynous J. regia trees was detected. The correct development of J. regia male gametophytes, high pollen viability (86.5 %), and germination (57.6 %) ruled out the possibility that low pollen quality contributed to depressed hybrid production. Our findings indicated that these two species tended to remain reproductively isolated. The substantial disjunction in flowering time and additional prezygotic barriers such as differences in floral size and conspecific pollen advance may affect interspecific gene flow between J. regia and J. nigra.     

Approximate Bayesian Computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

This is a “Topic Page” article for PLOS Computational Biology.

     

Durable Resistance to Crop Pathogens: An Epidemiological Framework to Predict Risk under Uncertainty

Increasing the durability of crop resistance to plant pathogens is one of the key goals of virulence management. Despite the recognition of the importance of demographic and environmental stochasticity on the dynamics of an epidemic, their effects on the evolution of the pathogen and durability of resistance has not received attention. We formulated a stochastic epidemiological model, based on the Kramer-Moyal expansion of the Master Equation, to investigate how random fluctuations affect the dynamics of an epidemic and how these effects feed through to the evolution of the pathogen and durability of resistance. We focused on two hypotheses: firstly, a previous deterministic model has suggested that the effect of cropping ratio (the proportion of land area occupied by the resistant crop) on the durability of crop resistance is negligible. Increasing the cropping ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur when we take account of demographic stochasticity, but found that the durability does depend on the cropping ratio. Secondly, we tested whether a superimposed external source of stochasticity (for example due to environmental variation or to intermittent fungicide application) interacts with the intrinsic demographic fluctuations and how such interaction affects the durability of resistance. We show that in the pathosystem considered here, in general large stochastic fluctuations in epidemics enhance extinction of the pathogen. This is more likely to occur at large cropping ratios and for particular frequencies of the periodic external perturbation (stochastic resonance). The results suggest possible disease control practises by exploiting the natural sources of stochasticity.     

Single Cell Analysis of Lymph Node Tissue from HIV-1 Infected Patients Reveals that the Majority of CD4+ T-cells Contain One HIV-1 DNA Molecule

Genetic recombination contributes to the diversity of human immunodeficiency virus (HIV-1). Productive HIV-1 recombination is, however, dependent on both the number of HIV-1 genomes per infected cell and the genetic relationship between these viral genomes. A detailed analysis of the number of proviruses and their genetic relationship in infected cells isolated from peripheral blood and tissue compartments is therefore important for understanding HIV-1 recombination, genetic diversity and the dynamics of HIV-1 infection. To address these issues, we used a previously developed single-cell sequencing technique to quantify and genetically characterize individual HIV-1 DNA molecules from single cells in lymph node tissue and peripheral blood. Analysis of memory and naïve CD4⁺ T cells from paired lymph node and peripheral blood samples from five untreated chronically infected patients revealed that the majority of these HIV-1-infected cells (>90%) contain only one copy of HIV-1 DNA, implying a limited potential for productive recombination in virus produced by these cells in these two compartments. Phylogenetic analysis revealed genetic similarity of HIV-1 DNA in memory and naïve CD4⁺ T-cells from lymph node, peripheral blood and HIV-1 RNA from plasma, implying exchange of virus and/or infected cells between these compartments in untreated chronic infection.     

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait''s genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.     

Euphorbia characias Latex Amine Oxidase and Peroxidase: Interacting Enzymes?

This minireview deals the enzymatic transformation of some amino acids as arginine and ornithine, amines as tyramine, putrescine, spermine and spermidine, and other substances as nitric oxide and thiocyanate. These reactions, catalyzed by two proteins purified from the latex of Euphorbia characias, a copper/quinone containing amine oxidase and a cationic peroxidase, show enzymatic activity interactions probably occurring between these proteins in Euphorbia latex.     

Electronic evaluation for video commercials by impression index

How to evaluate the effect of commercials is significantly important in neuromarketing. In this paper, we proposed an electronic way to evaluate the influence of video commercials on consumers by impression index. The impression index combines both the memorization and attention index during consumers observing video commercials by tracking the EEG activity. It extracts features from scalp EEG to evaluate the effectiveness of video commercials in terms of time–frequency-space domain. And, the general global field power was used as an impression index for evaluation of video commercial scenes as time series. Results of experiment demonstrate that the proposed approach is able to track variations of the cerebral activity related to cognitive task such as observing video commercials, and help to judge whether the scene in video commercials is impressive or not by EEG signals.