DLX1 acts as a crucial target of FOXM1 to promote ovarian cancer aggressiveness by enhancing TGF-β/SMAD4 signaling

Recent evidence from a comprehensive genome analysis and functional studies have revealed that FOXM1 is a crucial metastatic regulator that drives cancer progression. However, the regulatory mechanism by which FOXM1 exerts its metastatic functions in cancer cells remains obscure. Here, we report that DLX1 acts as a FOXM1 downstream target, exerting pro-metastatic function in ovarian cancers. Both FOXM1 isoforms (FOXM1B or FOXM1C) could transcriptionally upregulate DLX1 through two conserved binding sites, located at +61 to +69bp downstream (TFBS1) and -675 to -667bp upstream (TFBS2) of the DLX1 promoter, respectively. This regulation was further accentuated by the significant correlation between the nuclear expression of FOXM1 and DLX1 in high-grade serous ovarian cancers. Functionally, the ectopic expression of DLX1 promoted ovarian cancer cell growth, cell migration/invasion and intraperitoneal dissemination of ovarian cancer in mice, whereas small interfering RNA-mediated DLX1 knockdown in FOXM1-overexpressing ovarian cancer cells abrogated these oncogenic capacities. In contrast, depletion of FOXM1 by shRNAi only partially attenuated tumor growth and exerted almost no effect on cell migration/invasion and the intraperitoneal dissemination of DLX1-overexpressing ovarian cancer cells. Furthermore, the mechanistic studies showed that DLX1 positively modulates TGF- signaling by upregulating PAI-1 and JUNB through direct interaction with SMAD4 in the nucleus upon TGF-1 induction. Taken together, these data strongly suggest that DLX1 plays a pivotal role in FOXM1 signaling to promote cancer aggressiveness through intensifying TGF-/SMAD4 signaling in high-grade serous ovarian cancer cells.published_or_final_versio

Asymmetric localization of DLC1 defines avian trunk neural crest polarity for directional delamination and migration

Following epithelial-mesenchymal transition, acquisition of avian trunk neural crest cell (NCC) polarity is prerequisite for directional delamination and migration, which in turn is essential for peripheral nervous system development. However, how this cell polarization is established and regulated remains unknown. Here we demonstrate that, using the RHOA biosensor in vivo and in vitro, the initiation of NCC polarization is accompanied by highly activated RHOA in the cytoplasm at the cell rear and its fluctuating activity at the front edge. This differential RHOA activity determines polarized NC morphology and motility, and is regulated by the asymmetrically localized RhoGAP Deleted in liver cancer (DLC1) in the cytoplasm at the cell front. Importantly, the association of DLC1 with NEDD9 is crucial for its asymmetric localization and differential RHOA activity. Moreover, NC specifiers, SOX9 and SOX10, regulate NEDD9 and DLC1 expression, respectively. These results present a SOX9/SOX10-NEDD9/DLC1-RHOA regulatory axis to govern NCC migratory polarization.published_or_final_versio

Infection of Differentiated Porcine Airway Epithelial Cells by Influenza Virus: Differential Susceptibility to Infection by Porcine and Avian Viruses

BACKGROUND: Swine are important hosts for influenza A viruses playing a crucial role in the epidemiology and interspecies transmission of these viruses. Respiratory epithelial cells are the primary target cells for influenza viruses. METHODOLOGY/PRINCIPAL FINDINGS: To analyze the infection of porcine airway epithelial cells by influenza viruses, we established precision-cut lung slices as a culture system for differentiated respiratory epithelial cells. Both ciliated and mucus-producing cells were found to be susceptible to infection by swine influenza A virus (H3N2 subtype) with high titers of infectious virus released into the supernatant already one day after infection. By comparison, growth of two avian influenza viruses (subtypes H9N2 and H7N7) was delayed by about 24 h. The two avian viruses differed both in the spectrum of susceptible cells and in the efficiency of replication. As the H9N2 virus grew to titers that were only tenfold lower than that of a porcine H3N2 virus this avian virus is an interesting candidate for interspecies transmission. Lectin staining indicated the presence of both α-2,3- and α-2,6-linked sialic acids on airway epithelial cells. However, their distribution did not correlate with pattern of virus infection indicating that staining by plant lectins is not a reliable indicator for the presence of cellular receptors for influenza viruses. CONCLUSIONS/SIGNIFICANCE: Differentiated respiratory epithelial cells significantly differ in their susceptibility to infection by avian influenza viruses. We expect that the newly described precision-cut lung slices from the swine lung are an interesting culture system to analyze the infection of differentiated respiratory epithelial cells by different pathogens (viral, bacterial and parasitic ones) of swine

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Working Memory Impairment in Fibromyalgia Patients Associated with Altered Frontoparietal Memory Network

BACKGROUND: Fibromyalgia (FM) is a disorder characterized by chronic widespread pain and frequently associated with other symptoms. Patients with FM commonly report cognitive complaints, including memory problem. The objective of this study was to investigate the differences in neural correlates of working memory between FM patients and healthy subjects, using functional magnetic resonance imaging (MRI). METHODOLOGY/PRINCIPAL FINDINGS: Nineteen FM patients and 22 healthy subjects performed an n-back memory task during MRI scan. Functional MRI data were analyzed using within- and between-group analysis. Both activated and deactivated brain regions during n-back task were evaluated. In addition, to investigate the possible effect of depression and anxiety, group analysis was also performed with depression and anxiety level in terms of Beck depression inventory (BDI) and Beck anxiety inventory (BAI) as a covariate. Between-group analyses, after controlling for depression and anxiety level, revealed that within the working memory network, inferior parietal cortex was strongly associated with the mild (r = 0.309, P = 0.049) and moderate (r = 0.331, P = 0.034) pain ratings. In addition, between-group comparison revealed that within the working memory network, the left DLPFC, right VLPFC, and right inferior parietal cortex were associated with the rating of depression and anxiety? CONCLUSIONS/SIGNIFICANCE: Our results suggest that the working memory deficit found in FM patients may be attributable to differences in neural activation of the frontoparietal memory network and may result from both pain itself and depression and anxiety associated with pain

High dose fluconazole in salvage therapy for HIV-uninfected cryptococcal meningitis.

BACKGROUND: The 2010 Infectious Diseases Society of America (IDSA) guidelines for management of cryptococcal diseases recommend high dose fluconazole (≥ 800 mg/day), either alone or with other antifungal drugs, as alternative anticryptococcal choices. But evidence for its use in the treatment of HIV-uninfected cryptococcal meningitis (CM) remains sparse. METHODS: A retrospective analysis of HIV-uninfected CM patients who received fluconazole 800 mg/day for salvage therapy from January 2011 to December 2016 at Huashan Hospital, Shanghai, China was performed. Efficacy and safety were assessed, and mortality and prognostic factors evaluated. RESULTS: A total of 44 patients were studied including 19 refractory to amphotericin B induction therapy, 8 refractory to fluconazole consolidation therapy (400 mg/d), and 17 intolerant of antifungal drugs. For salvage, 11 patients received triple therapy of high dose fluconazole, amphotericin B and flucytosine, 20 received dual therapy of high dose fluconazole and flucytosine, 13 received monotherapy of high dose fluconazole. Median duration of high dose fluconazole in salvage regimens was 136.5 days (range, 1-667 days). Clinical response rates were 72.1% (31/43) and 83.7% (36/43) when assessed at 2 weeks and the end of salvage therapy, respectively. Adverse events possibly related to high dose fluconazole occurred in 54.5% (24/44) of the patients, and all were mild or moderate. From the initiation of salvage therapy, 1-year all-cause mortality was 13.6% (6 of 44 patients) among the study population with no significant difference in refractory or intolerant patients. CONCLUSIONS: Adherence to guideline recommendations of high dose fluconazole, alone or in combination with other antifungals, was safe and often effective for salvage therapy of HIV-uninfected CM patients

From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes

Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays

Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls.

Determining whether potential causal variants for related diseases are shared can identify overlapping etiologies of multifactorial disorders. Colocalization methods disentangle shared and distinct causal variants. However, existing approaches require independent data sets. Here we extend two colocalization methods to allow for the shared-control design commonly used in comparison of genome-wide association study results across diseases. Our analysis of four autoimmune diseases--type 1 diabetes (T1D), rheumatoid arthritis, celiac disease and multiple sclerosis--identified 90 regions that were associated with at least one disease, 33 (37%) of which were associated with 2 or more disorders. Nevertheless, for 14 of these 33 shared regions, there was evidence that the causal variants differed. We identified new disease associations in 11 regions previously associated with one or more of the other 3 disorders. Four of eight T1D-specific regions contained known type 2 diabetes (T2D) candidate genes (COBL, GLIS3, RNLS and BCAR1), suggesting a shared cellular etiology.MF is funded by the Wellcome Trust (099772). CW and HG are funded by the Wellcome Trust (089989). This work was funded by the JDRF (9–2011–253), the Wellcome Trust (091157) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140). ImmunoBase.org is supported by Eli Lilly and Company. We thank the UK Medical Research Council and Wellcome Trust for funding the collection of DNA for the British 1958 Birth Cohort (MRC grant G0000934, WT grant 068545/Z/02). DNA control samples were prepared and provided by S. Ring, R. Jones, M. Pembrey, W. McArdle, D. Strachan and P. Burton. Biotec Cluster M4, the Fidelity Biosciences Research Initiative, Research Foundation Flanders, Research Fund KU Leuven, the Belgian Charcot Foundation, Gemeinntzige Hertie Stiftung, University Zurich, the Danish MS Society, the Danish Council for Strategic Research, the Academy of Finland, the Sigrid Juselius Foundation, Helsinki University, the Italian MS Foundation, Fondazione Cariplo, the Italian Ministry of University and Research, the Torino Savings Bank Foundation, the Italian Ministry of Health, the Italian Institute of Experimental Neurology, the MS Association of Oslo, the Norwegian Research Council, the South–Eastern Norwegian Health Authorities, the Australian National Health and Medical Research Council, the Dutch MS Foundation and Kaiser Permanente. Marina Evangelou is thanked for motivating the investigation of the FASLG association.This is the author accepted manuscript. The final version is available at http://www.nature.com/ng/journal/v47/n7/full/ng.3330.html