18 research outputs found

    Mouse tumor susceptibility genes identify drug combinations for multiple myeloma

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    Long-term genetic studies utilizing backcross and congenic strain analyses coupled with positional cloning strategies and functional studies identified Cdkn2a, Mtor, and Mndal as mouse plasmacytoma susceptibility/resistance genes. Tumor incidence data in congenic strains carrying the resistance alleles of Cdkn2a and Mtor led us to hypothesize that drug combinations affecting these pathways are likely to have an additive, if not synergistic effect in inhibiting tumor cell growth. Traditional and novel systems-level genomic approaches were used to assess combination activity, disease specificity, and clinical potential of a drug combination involving rapamycin/everolimus, an Mtor inhibitor, with entinostat, an histone deacetylase inhibitor. The combination synergistically repressed oncogenic MYC and activated the Cdkn2a tumor suppressor. The identification of MYC as a primary upstream regulator led to the identification of small molecule binders of the G-quadruplex structure that forms in the NHEIII region of the MYC promoter. These studies highlight the importance of identifying drug combinations which simultaneously upregulate tumor suppressors and downregulate oncogenes

    ISCB-Student Council narratives : strategical development of the ISCB-Regional Student Groups in 2016

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    Regional Student Groups are groups established and managed by the ISCB-Student Council in different regions of the world. The article highlights some of the initiatives and management lessons from our 'top-performing' Spotlight Regional Student Groups (RSGs), RSG-Argentina and RSG-UK, for the current year (2016). In addition, it details some of the operational hurdles faced by RSGs and possible solutions

    ISCB-Student Council Narratives: Strategical development of the ISCB-Regional Student Groups in 2016

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    Regional Student Groups are groups established and managed by the ISCB-Student Council in different regions of the world. The article highlights some of the initiatives and management lessons from our 'top-performing' Spotlight Regional Student Groups (RSGs), RSG-Argentina and RSG-UK, for the current year (2016). In addition, it details some of the operational hurdles faced by RSGs and possible solutions.Fil: Shome, Sayane. Iowa State University; Estados UnidosFil: Meysman, Pieter. Universiteit Antwerp; BélgicaFil: Parra, Rodrigo Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Max Planck Institute for Biophysical Chemistry; AlemaniaFil: Monzón, Alexander. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Palopoli, Nicolás. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: White, Benjamen. Earlham Institute; Reino UnidoFil: Rahman, Farzana. University of South Wales; Reino UnidoFil: Hassan, Mehedi. University of South Wales; Reino UnidoFil: Özkeserli, Zeynep. Acibadem University; TurquíaFil: Ashano, Efejiro. National Biotechnology Development Agency; Nigeria. Covenant University; NigeriaFil: Hughitt, V. Keith. University of Maryland; Estados UnidosFil: Uzair Khan, Muhammad. CECOS University of Information Technology and Emerging Sciences; PakistánFil: Murphy, Denis J.. University of South Wales; Reino Unid

    Meta-transcriptome Profiling of the Human-Leishmania braziliensis Cutaneous Lesion

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    Carvalho Filho, E. M. Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil. “Documento produzido em parceria ou por autor vinculado à Fiocruz, mas não consta à informação no documento”.Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2017-04-11T12:53:23Z No. of bitstreams: 2 Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5) Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2017-04-11T13:21:02Z (GMT) No. of bitstreams: 2 Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5) Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5)Made available in DSpace on 2017-04-11T13:21:02Z (GMT). No. of bitstreams: 2 Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5) Christensen SM Meta-transctriptome....pdf: 3015587 bytes, checksum: 2c9fc203fcd3c0ae5f0719a7413a68b5 (MD5) Previous issue date: 2016National Institutes of Health NIAID (AI094773) and NIGMS (GM102589), and na International Collaboration for Infectious Disease Research (ICIDR) grant (U01-AUI088650).University of Maryland. Department of Cell Biology and Molecular Genetics. Maryland, USAUniversity of Maryland. Department of Cell Biology and Molecular Genetics. Maryland, USA / University of Maryland. Center for Bioinformatics and Computational Biology. Maryland, USAUniversidade Federal da Bahia. Salvador, BA, BrasilUniversidade Federal da Bahia. Salvador, BA, BrasilThe University of Pennsylvania. School of Veterinary Medicine. Department of Pathobiology. Philadelphia, Pennsylvania, USAUniversity of Maryland. Department of Cell Biology and Molecular Genetics. Maryland, USA / University of Maryland. Center for Bioinformatics and Computational Biology. Maryland, USAThe University of Pennsylvania. School of Veterinary Medicine. Department of Pathobiology. Philadelphia, Pennsylvania, USAUniversidade Federal da Bahia. Salvador, BA, BrasilThe University of Pennsylvania. School of Veterinary Medicine. Department of Pathobiology. Philadelphia, Pennsylvania, USAUniversity of Maryland. Department of Cell Biology and Molecular Genetics. Maryland, USA / University of Maryland. Center for Bioinformatics and Computational Biology. Maryland, USAUniversity of Maryland. Department of Cell Biology and Molecular Genetics. Maryland, USAHost and parasite gene expression in skin biopsies from Leishmania braziliensis-infected patients were simultaneously analyzed using high throughput RNA-sequencing. Biopsies were taken from 8 patients with early cutaneous leishmaniasis and 17 patients with late cutaneous leishmaniasis. Although parasite DNA was found in all patient lesions at the time of biopsy, the patients could be stratified into two groups: one lacking detectable parasite transcripts (PTNeg) in lesions, and another in which parasite transcripts were readily detected (PTPos). These groups exhibited substantial differences in host responses to infection. PTPos biopsies contained an unexpected increase in B lymphocyte-specific and immunoglobulin transcripts in the lesions, and an upregulation of immune inhibitory molecules. Biopsies without detectable parasite transcripts showed decreased evidence for B cell activation, but increased expression of antimicrobial genes and genes encoding skin barrier functions. The composition and abundance of L. braziliensis transcripts in PTPos lesions were surprisingly conserved among all six patients, with minimal meaningful differences between lesions from patients with early and late cutaneous leishmaniasis. The most abundant parasite transcripts expressed in lesions were distinct from transcripts expressed in vitro in human macrophage cultures infected with L. amazonensis or L. major. Therefore in vitro gene expression in macrophage monolayers may not be a strong predictor of gene expression in lesions. Some of the most highly expressed in vivo transcripts encoded amastin-like proteins, hypothetical genes, putative parasite virulence factors, as well as histones and tubulin. In summary, RNA sequencing allowed us to simultaneously analyze human and L. braziliensis transcriptomes in lesions of infected patients, and identify unexpected differences in host immune responses which correlated with active transcription of parasite genes

    Immune response signatures in parasite transcript positive (PT<sup>Pos</sup>) and negative (PT<sup>Neg</sup>) lesions.

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    <p><b>(3A)</b> Bars represent the fold change of RNA expression of cell-specific markers in PT<sup>Neg</sup> (blue), PT<sup>Int</sup> (yellow), and PT<sup>Pos</sup> (orange) samples, each compared to healthy controls (mean plus SEM). Statistically significant differentially expressed genes, when comparing PT<sup>Pos</sup> to PT<sup>Neg</sup> are identified with a # symbol (p<0.05) <b>(3B)</b> Bars depict fold changes of transcripts encoding inflammatory cytokines (<i>ifnγ</i>, <i>tnf</i>, <i>IL12p40</i>, <i>IL-10</i>, <i>faslg</i>), anti-inflammatory and inhibitory signals (<i>il10</i>, <i>ctla4</i>, <i>pdcd1</i>, <i>cd274</i>, <i>lag3</i>), and activation markers (<i>cd80</i>, <i>cd38</i>) in lesions of all three classifications compared to healthy controls (mean plus SEM). Statistically significant differentially expressed genes when comparing PT<sup>Pos</sup> to PT<sup>Neg</sup> are identified with a # symbol (p<0.05). <b>(3C)</b> Shown is the top module (by p-value, see * in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0004992#pntd.0004992.s003" target="_blank">S3A Fig</a>) and representative genes from within the module correlated to percent parasite reads using WGCNA analysis. The left plot demonstrates correlation to the module eigengene versus correlation to parasite percent reads for each gene. On the right, plots demonstrate normalized expression (rpkm) versus parasite percent reads for selected genes from within the module (highlighted in red in the left plot).</p
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