Clinical Implication of Targeting of Cancer Stem Cells

The existence of cancer stem cells (CSCs) is receiving increasing interest particularly due to its potential ability to enter clinical routine. Rapid advances in the CSC field have provided evidence for the development of more reliable anticancer therapies in the future. CSCs typically only constitute a small fraction of the total tumor burden; however, they harbor self-renewal capacity and appear to be relatively resistant to conventional therapies. Recent therapeutic approaches aim to eliminate or differentiate CSCs or to disrupt the niches in which they reside. Better understanding of the biological characteristics of CSCs as well as improved preclinical and clinical trials targeting CSCs may revolutionize the treatment of many cancers. Copyright (c) 2012 S. Karger AG, Base

Identification of Candida glabrata genes involved in pH modulation and modification of the phagosomal environment in macrophages

notes: PMCID: PMC4006850types: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov'tCandida glabrata currently ranks as the second most frequent cause of invasive candidiasis. Our previous work has shown that C. glabrata is adapted to intracellular survival in macrophages and replicates within non-acidified late endosomal-stage phagosomes. In contrast, heat killed yeasts are found in acidified matured phagosomes. In the present study, we aimed at elucidating the processes leading to inhibition of phagosome acidification and maturation. We show that phagosomes containing viable C. glabrata cells do not fuse with pre-labeled lysosomes and possess low phagosomal hydrolase activity. Inhibition of acidification occurs independent of macrophage type (human/murine), differentiation (M1-/M2-type) or activation status (vitamin D3 stimulation). We observed no differential activation of macrophage MAPK or NFκB signaling cascades downstream of pattern recognition receptors after internalization of viable compared to heat killed yeasts, but Syk activation decayed faster in macrophages containing viable yeasts. Thus, delivery of viable yeasts to non-matured phagosomes is likely not triggered by initial recognition events via MAPK or NFκB signaling, but Syk activation may be involved. Although V-ATPase is abundant in C. glabrata phagosomes, the influence of this proton pump on intracellular survival is low since blocking V-ATPase activity with bafilomycin A1 has no influence on fungal viability. Active pH modulation is one possible fungal strategy to change phagosome pH. In fact, C. glabrata is able to alkalinize its extracellular environment, when growing on amino acids as the sole carbon source in vitro. By screening a C. glabrata mutant library we identified genes important for environmental alkalinization that were further tested for their impact on phagosome pH. We found that the lack of fungal mannosyltransferases resulted in severely reduced alkalinization in vitro and in the delivery of C. glabrata to acidified phagosomes. Therefore, protein mannosylation may play a key role in alterations of phagosomal properties caused by C. glabrata.Deutsche ForschungsgemeinschaftNational Institutes for HealthWellcome TrustBBSR

Differential Modulation of Beta-Adrenergic Receptor Signaling by Trace Amine-Associated Receptor 1 Agonists

Trace amine-associated receptors (TAAR) are rhodopsin-like G-protein-coupled receptors (GPCR). TAAR are involved in modulation of neuronal, cardiac and vascular functions and they are potentially linked with neurological disorders like schizophrenia and Parkinson's disease. Subtype TAAR1, the best characterized TAAR so far, is promiscuous for a wide set of ligands and is activated by trace amines tyramine (TYR), phenylethylamine (PEA), octopamine (OA), but also by thyronamines, dopamine, and psycho-active drugs. Unfortunately, effects of trace amines on signaling of the two homologous β-adrenergic receptors 1 (ADRB1) and 2 (ADRB2) have not been clarified yet in detail. We, therefore, tested TAAR1 agonists TYR, PEA and OA regarding their effects on ADRB1/2 signaling by co-stimulation studies. Surprisingly, trace amines TYR and PEA are partial allosteric antagonists at ADRB1/2, whereas OA is a partial orthosteric ADRB2-antagonist and ADRB1-agonist. To specify molecular reasons for TAAR1 ligand promiscuity and for observed differences in signaling effects on particular aminergic receptors we compared TAAR, tyramine (TAR) octopamine (OAR), ADRB1/2 and dopamine receptors at the structural level. We found especially for TAAR1 that the remarkable ligand promiscuity is likely based on high amino acid similarity in the ligand-binding region compared with further aminergic receptors. On the other hand few TAAR specific properties in the ligand-binding site might determine differences in ligand-induced effects compared to ADRB1/2. Taken together, this study points to molecular details of TAAR1-ligand promiscuity and identified specific trace amines as allosteric or orthosteric ligands of particular β-adrenergic receptor subtypes

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesOver the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15).We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls).We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P = 9 × 10(-6)). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23.This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4.National Institutes of Mental Health (NIMH, USA) ACE Network Autism Genetic Resource Exchange (AGRE) is a program of Autism Speaks (USA) The Autism Genome Project (AGP) from Autism Speaks (USA) Canadian Institutes of Health Research (CIHR), Genome Canada Health Research Board (Ireland) Hilibrand Foundation (USA) Medical Research Council (UK) National Institutes of Health (USA) Ontario Genomics Institute University of Toronto McLaughlin Centre Simons Foundation Johns Hopkins Autism Consortium of Boston NLM Family foundation National Institute of Health grants National Health Medical Research Council Scottish Rite Spunk Fund, Inc. Rebecca and Solomon Baker Fund APEX Foundation National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) endowment fund of the Nancy Pritzker Laboratory (Stanford) Autism Society of America Janet M. Grace Pervasive Developmental Disorders Fund The Lundbeck Foundation universities and university hospitals of Aarhus and Copenhagen Stanley Foundation Centers for Disease Control and Prevention (CDC) Netherlands Scientific Organization Dutch Brain Foundation VU University Amsterdam Trinity Centre for High Performance Computing through Science Foundation Ireland Autism Genome Project (AGP) from Autism Speak

Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways

What determines cell size?

AbstractFirst paragraph (this article has no abstract) For well over 100 years, cell biologists have been wondering what determines the size of cells. In modern times, we know all of the molecules that control the cell cycle and cell division, but we still do not understand how cell size is determined. To check whether modern cell biology has made any inroads on this age-old question, BMC Biology asked several heavyweights in the field to tell us how they think cell size is controlled, drawing on a range of different cell types. The essays in this collection address two related questions - why does cell size matter, and how do cells control it

Genomewide linkage scan of schizophrenia in a large multicenter pedigree sample using single nucleotide polymorphisms

A genomewide linkage scan was carried out in eight clinical samples of informative schizophrenia families. After all quality control checks, the analysis of 707 European-ancestry families included 1615 affected and 1602 unaffected genotyped individuals, and the analysis of all 807 families included 1900 affected and 1839 unaffected individuals. Multipoint linkage analysis with correction for marker–marker linkage disequilibrium was carried out with 5861 single nucleotide polymorphisms (SNPs; Illumina version 4.0 linkage map). Suggestive evidence for linkage (European families) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in nonparametric and/or parametric analyses. In a logistic regression allele-sharing analysis of linkage allowing for intersite heterogeneity, genomewide significant evidence for linkage was observed on chromosome 10p12. Significant heterogeneity was also observed on chromosome 22q11.1. Evidence for linkage across family sets and analyses was most consistent on chromosome 8p21, with a one-LOD support interval that does not include the candidate gene NRG1, suggesting that one or more other susceptibility loci might exist in the region. In this era of genomewide association and deep resequencing studies, consensus linkage regions deserve continued attention, given that linkage signals can be produced by many types of genomic variation, including any combination of multiple common or rare SNPs or copy number variants in a region