250 research outputs found

    Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines

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    <p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is the most common primary intracranial tumor and despite recent advances in treatment regimens, prognosis for affected patients remains poor. Active cell migration and invasion of GBM cells ultimately lead to ubiquitous tumor recurrence and patient death.</p> <p>To further understand the genetic mechanisms underlying the ability of glioma cells to migrate, we compared the matched transcriptional profiles of migratory and stationary populations of human glioma cells. Using a monolayer radial migration assay, motile and stationary cell populations from seven human long term glioma cell lines and three primary GBM cultures were isolated and prepared for expression analysis.</p> <p>Results</p> <p>Gene expression signatures of stationary and migratory populations across all cell lines were identified using a pattern recognition approach that integrates <it>a priori </it>knowledge with expression data. Principal component analysis (PCA) revealed two discriminating patterns between migrating and stationary glioma cells: i) global down-regulation and ii) global up-regulation profiles that were used in a proband-based rule function implemented in GABRIEL to find subsets of genes having similar expression patterns. Genes with up-regulation pattern in migrating glioma cells were found to be overexpressed in 75% of human GBM biopsy specimens compared to normal brain. A 22 gene signature capable of classifying glioma cultures based on their migration rate was developed. Fidelity of this discovery algorithm was assessed by validation of the invasion candidate gene, connective tissue growth factor (CTGF). siRNA mediated knockdown yielded reduced <it>in vitro </it>migration and <it>ex vivo </it>invasion; immunohistochemistry on glioma invasion tissue microarray confirmed up-regulation of CTGF in invasive glioma cells.</p> <p>Conclusion</p> <p>Gene expression profiling of migratory glioma cells induced to disperse <it>in vitro </it>affords discovery of genomic signatures; selected candidates were validated clinically at the transcriptional and translational levels as well as through functional assays thereby underscoring the fidelity of the discovery algorithm.</p

    Primary skin fibroblasts as a model of Parkinson's disease

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    Parkinson's disease is the second most frequent neurodegenerative disorder. While most cases occur sporadic mutations in a growing number of genes including Parkin (PARK2) and PINK1 (PARK6) have been associated with the disease. Different animal models and cell models like patient skin fibroblasts and recombinant cell lines can be used as model systems for Parkinson's disease. Skin fibroblasts present a system with defined mutations and the cumulative cellular damage of the patients. PINK1 and Parkin genes show relevant expression levels in human fibroblasts and since both genes participate in stress response pathways, we believe fibroblasts advantageous in order to assess, e.g. the effect of stressors. Furthermore, since a bioenergetic deficit underlies early stage Parkinson's disease, while atrophy underlies later stages, the use of primary cells seems preferable over the use of tumor cell lines. The new option to use fibroblast-derived induced pluripotent stem cells redifferentiated into dopaminergic neurons is an additional benefit. However, the use of fibroblast has also some drawbacks. We have investigated PARK6 fibroblasts and they mirror closely the respiratory alterations, the expression profiles, the mitochondrial dynamics pathology and the vulnerability to proteasomal stress that has been documented in other model systems. Fibroblasts from patients with PARK2, PARK6, idiopathic Parkinson's disease, Alzheimer's disease, and spinocerebellar ataxia type 2 demonstrated a distinct and unique mRNA expression pattern of key genes in neurodegeneration. Thus, primary skin fibroblasts are a useful Parkinson's disease model, able to serve as a complement to animal mutants, transformed cell lines and patient tissues

    Defective formation of IgA memory B cells, Th1 and Th17 cells in symptomatic patients with selective IgA deficiency

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    Objective: Selective IgA deficiency (sIgAD) is the most common primary immunodeficiency in Western countries. Patients can suffer from recurrent infections and autoimmune diseases because of a largely unknown aetiology. To increase insights into the pathophysiology of the disease, we studied memory B and T cells and cytokine concentrations in peripheral blood. Methods: We analysed 30 sIgAD patients (12 children, 18 adults) through detailed phenotyping of peripheral B-cell, CD8+ T-cell and CD4+ T-cell subsets, sequence analysis of IGA and IGG transcripts, in vitro B-cell activation and blood cytokine measurements. Results: All patients had significantly decreased numbers of T-cell-dependent (TD; CD27+) and T-cell-independent (TI; CD27−) IgA memory B cells and increased CD21low B-cell numbers. IgM+IgD− memory B cells were decreased in children and normal in adult patients. IGA and IGG transcripts contained normal SHM levels. In sIgAD children, IGA transcripts more frequently used IGA2 than controls (58.5% vs. 25.1%), but not in adult patients. B-cell activation after in vitro stimulation was normal. However, adult sIgAD patients exhibited increased blood levels of TGF-β1, BAFF and APRIL, whereas they had decreased Th1 and Th17 cell numbers. Conclusion: Impaired IgA memory formation in sIgAD patients is not due to a B-cell activation defect. Instead, decreased Th1 and Th17 cell numbers and high blood levels of BAFF, APRIL and TGF-β1 might reflect disturbed regulation of IgA responses in vivo. These insights into B-cell extrinsic immune defects suggest the need for a broader immunological focus on genomics and functional analyses to unravel the pathogenesis of sIgAD

    The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

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    The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

    The interior of Mars as seen by InSight (Invited)

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    InSight is the first planetary mission dedicated to exploring the whole interior of a planet using geophysical methods, specifically seismology and geodesy. To this end, we observed seismic waves of distant marsquakes and inverted for interior models using differential travel times of phases reflected at the surface (PP, SS...) or the core mantle-boundary (ScS), as well as those converted at crustal interfaces. Compared to previous orbital observations1-3, the seismic data added decisive new insights with consequences for the formation of Mars: The global average crustal thickness of 24-75 km is at the low end of pre-mission estimates5. Together with the the thick lithosphere of 450-600 km5, this requires an enrichment of heat-producing elements in the crust by a factor of 13-20, compared to the primitive mantle. The iron-rich liquid core is 1790-1870 km in radius6, which rules out the existence of an insulating bridgmanite-dominated lower mantle on Mars. The large, and therefore low-density core needs a high amount of light elements. Given the geochemical boundary conditions, Sulfur alone cannot explain the estimated density of ~6 g/cm3 and volatile elements, such as oxygen, carbon or hydrogen are needed in significant amounts. This observation is difficult to reconcile with classical models of late formation from the same material as Earth. We also give an overview of open questions after three years of InSight operation on the surface of Mars, such as the potential existence of an inner core or compositional layers above the CM

    Association of urinary phthalate metabolite concentrations with body mass index and waist circumference: a cross-sectional study of NHANES data, 1999–2002

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    BACKGROUND: Although diet and activity are key factors in the obesity epidemic, laboratory studies suggest that endocrine disrupting chemicals may also affect obesity. METHODS: We analyzed associations between six phthalate metabolites measured in urine and body mass index (BMI) and waist circumference (WC) in National Health and Nutrition Examination Survey (NHANES) participants aged 6–80. We included 4369 participants from NHANES 1999–2002, with data on mono-ethyl (MEP), mono-2-ethylhexyl (MEHP), mono-n-butyl (MBP), and mono-benzyl (MBzP) phthalate; 2286 also had data on mono-2-ethyl-5-hydroxyhexyl (MEHHP) and mono-2-ethyl-5-oxohexyl (MEOHP) phthalate (2001–2002). Using multiple regression, we computed mean BMI and WC within phthalate quartiles in eight age/gender specific models. RESULTS: The most consistent associations were in males aged 20–59; BMI and WC increased across quartiles of MBzP (adjusted mean BMI = 26.7, 27.2, 28.4, 29.0, p-trend = 0.0002), and positive associations were also found for MEOHP, MEHHP, MEP, and MBP. In females, BMI and WC increased with MEP quartile in adolescent girls (adjusted mean BMI = 22.9, 23.8, 24.1, 24.7, p-trend = 0.03), and a similar but less strong pattern was seen in 20–59 year olds. In contrast, MEHP was inversely related to BMI in adolescent girls (adjusted mean BMI = 25.4, 23.8, 23.4, 22.9, p-trend = 0.02) and females aged 20–59 (adjusted mean BMI = 29.9, 29.9, 27.9, 27.6, p-trend = 0.02). There were no important associations among children, but several inverse associations among 60–80 year olds. CONCLUSION: This exploratory, cross-sectional analysis revealed a number of interesting associations with different phthalate metabolites and obesity outcomes, including notable differences by gender and age subgroups. Effects of endocrine disruptors, such as phthalates, may depend upon endogenous hormone levels, which vary dramatically by age and gender. Individual phthalates also have different biologic and hormonal effects. Although our study has limitations, both of these factors could explain some of the variation in the observed associations. These preliminary data support the need for prospective studies in populations at risk for obesity.National Institutes of Environmental Health Sciences (R21ES013724

    Physician Experiences and Understanding of Genomic Sequencing in Oncology

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    The amount of information produced by genomic sequencing is vast, technically complicated, and can be difficult to interpret. Appropriately tailoring genomic information for nonâ geneticists is an essential next step in the clinical use of genomic sequencing. To initiate development of a framework for genomic results communication, we conducted eighteen qualitative interviews with oncologists who had referred adult cancer patients to a matched tumorâ normal tissue genomic sequencing study. In our qualitative analysis, we found varied levels of clinician knowledge relating to sequencing technology, the scope of the tumor genomic sequencing study, and incidental germline findings. Clinicians expressed a perceived need for more genetics education. Additionally, they had a variety of suggestions for improving results reports and possible resources to aid in results interpretation. Most clinicians felt genetic counselors were needed when incidental germline findings were identified. Our research suggests that more consistent genetics education is imperative in ensuring the proper utilization of genomic sequencing in cancer care. Clinician suggestions for results interpretation resources and results report modifications could be used to improve communication. Cliniciansâ perceived need to involve genetic counselors when incidental germline findings were found suggests genetic specialists could play a critical role in ensuring patients receive appropriate followâ up.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147187/1/jgc40187.pd

    Depression, anxiety, and the risk of cancer:An individual participant data meta-analysis

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    Background: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. Methods: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). Results: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06–1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04–1.23). Conclusions: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. Preregistration number: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.</p
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