Datgan, a Reusable Software System for Facile Interrogation and Visualization of Complex Transcription Profiling Data Howell Et Al
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Downloaded the Normalized Gene Expression Profile from the GEO (Package Geoquery (5))
1 SUPPLEMENTARY MATERIALS 2 Supplementary Methods 3 Study design 4 The workflow to identify and validate the TME risk score and TME subtypes in gastric cancer is 5 depicted in Fig. S1. We first estimated the absolute abundance levels of the major stromal and 6 immune cell types in the TME using bulk gene expression data, and assessed the prognostic 7 effect of these cells in a discovery cohort. Next, we constructed a TME risk score and validated it 8 in two independent gene expression validation cohorts and three immunohistochemistry 9 validation cohorts. Finally, we stratified patients into four TME subtypes and examined their 10 genomic and molecular features and relation to established molecular subtypes. 11 Gene expression data 12 To explore the prognostic landscape of the TME, we used four gene expression profile (GEP) 13 datasets of resected gastric cancer patients with publicly available clinical information, namely, 14 ACRG (GSE62254) (1), GSE15459 (2), GSE84437 (3), and TCGA stomach adenocarcinoma 15 (STAD). Specifically, the raw microarray data in the ACRG cohort and GSE15459 were retrieved 16 from the Gene Expression Omnibus (GEO), and normalized by the RMA algorithm (package affy) 17 using custom chip definition files (Brainarray version 23 (4)) that convert Affymetrix probesets to 18 Entrez gene IDs. For GSE84437 dataset, which was measured by the Illumina platform, we 19 downloaded the normalized gene expression profile from the GEO (package GEOquery (5)). The 20 Illumina probes were also mapped to Entrez genes. For multiple probes mapping to the same 21 Entrez gene, we selected the one with the maximum mean expression level as the surrogate for 22 the Entrez gene using the function of collapseRows (6) (package WGCNA). -
Transcriptional Regulation of RKIP in Prostate Cancer Progression
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr. -
Laboratory Mouse Models for the Human Genome-Wide Associations
Laboratory Mouse Models for the Human Genome-Wide Associations The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Kitsios, Georgios D., Navdeep Tangri, Peter J. Castaldi, and John P. A. Ioannidis. 2010. Laboratory mouse models for the human genome-wide associations. PLoS ONE 5(11): e13782. Published Version doi:10.1371/journal.pone.0013782 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:8592157 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Laboratory Mouse Models for the Human Genome-Wide Associations Georgios D. Kitsios1,4, Navdeep Tangri1,6, Peter J. Castaldi1,2,4,5, John P. A. Ioannidis1,2,3,4,5,7,8* 1 Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, United States of America, 2 Tufts University School of Medicine, Boston, Massachusetts, United States of America, 3 Department of Hygiene and Epidemiology, University of Ioannina School of Medicine and Biomedical Research Institute, Foundation for Research and Technology-Hellas, Ioannina, Greece, 4 Tufts Clinical and Translational Science Institute, Tufts Medical Center, Boston, Massachusetts, United States of America, 5 Department of Medicine, Center for Genetic Epidemiology and Modeling, Tufts Medical Center, Tufts University -
Systems Analysis Implicates WAVE2&Nbsp
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL.5,NO.4,2020 ª 2020 THE AUTHORS. PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION. THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY-NC-ND LICENSE (http://creativecommons.org/licenses/by-nc-nd/4.0/). PRECLINICAL RESEARCH Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects a b b b Jonathan J. Edwards, MD, Andrew D. Rouillard, PHD, Nicolas F. Fernandez, PHD, Zichen Wang, PHD, b c d d Alexander Lachmann, PHD, Sunita S. Shankaran, PHD, Brent W. Bisgrove, PHD, Bradley Demarest, MS, e f g h Nahid Turan, PHD, Deepak Srivastava, MD, Daniel Bernstein, MD, John Deanfield, MD, h i j k Alessandro Giardini, MD, PHD, George Porter, MD, PHD, Richard Kim, MD, Amy E. Roberts, MD, k l m m,n Jane W. Newburger, MD, MPH, Elizabeth Goldmuntz, MD, Martina Brueckner, MD, Richard P. Lifton, MD, PHD, o,p,q r,s t d Christine E. Seidman, MD, Wendy K. Chung, MD, PHD, Martin Tristani-Firouzi, MD, H. Joseph Yost, PHD, b u,v Avi Ma’ayan, PHD, Bruce D. Gelb, MD VISUAL ABSTRACT Edwards, J.J. et al. J Am Coll Cardiol Basic Trans Science. 2020;5(4):376–86. ISSN 2452-302X https://doi.org/10.1016/j.jacbts.2020.01.012 JACC: BASIC TO TRANSLATIONALSCIENCEVOL.5,NO.4,2020 Edwards et al. 377 APRIL 2020:376– 86 WAVE2 Complex in LVOTO HIGHLIGHTS ABBREVIATIONS AND ACRONYMS Combining CHD phenotype–driven gene set enrichment and CRISPR knockdown screening in zebrafish is an effective approach to identifying novel CHD genes. -
Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol
Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol Danie¨lle M. P. H. J. Boesten1*., Alvin Berger2.¤, Peter de Cock3, Hua Dong4, Bruce D. Hammock4, Gertjan J. M. den Hartog1, Aalt Bast1 1 Department of Toxicology, Maastricht University, Maastricht, The Netherlands, 2 Global Food Research, Cargill, Wayzata, Minnesota, United States of America, 3 Cargill RandD Center Europe, Vilvoorde, Belgium, 4 Department of Entomology and UCD Comprehensive Cancer Center, University of California Davis, Davis, California, United States of America Abstract Diabetes is characterized by hyperglycemia and development of vascular pathology. Endothelial cell dysfunction is a starting point for pathogenesis of vascular complications in diabetes. We previously showed the polyol erythritol to be a hydroxyl radical scavenger preventing endothelial cell dysfunction onset in diabetic rats. To unravel mechanisms, other than scavenging of radicals, by which erythritol mediates this protective effect, we evaluated effects of erythritol in endothelial cells exposed to normal (7 mM) and high glucose (30 mM) or diabetic stressors (e.g. SIN-1) using targeted and transcriptomic approaches. This study demonstrates that erythritol (i.e. under non-diabetic conditions) has minimal effects on endothelial cells. However, under hyperglycemic conditions erythritol protected endothelial cells against cell death induced by diabetic stressors (i.e. high glucose and peroxynitrite). Also a number of harmful effects caused by high glucose, e.g. increased nitric oxide release, are reversed. Additionally, total transcriptome analysis indicated that biological processes which are differentially regulated due to high glucose are corrected by erythritol. We conclude that erythritol protects endothelial cells during high glucose conditions via effects on multiple targets. -
Tumor Necrosis Factor‑Α‑Induced Protein‑8 Like 2 Regulates
6346 MOLECULAR MEDICINE REPORTS 16: 6346-6353, 2017 Tumor necrosis factor‑α‑induced protein‑8 like 2 regulates lipopolysaccharide‑induced rat rheumatoid arthritis immune responses and is associated with Rac activation and interferon regulatory factor 3 phosphorylation CHUNYAN SHI1,2*, YUE WANG1*, GUOHONG ZHUANG1*, ZHONGQUAN QI1, YANPING LI1 and PING YIN3 1Organ Transplantation Institute, Anti‑Cancer Research Center, Medical College, Xiamen University, Xiamen, Fujian 361100; 2The Department of Oncology, Jiujiang People's Hospital, Jiujiang, Jiangxi 332000; 3Department of Pathology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, Fujian 361100, P.R. China Received October 28, 2016; Accepted June 19, 2017 DOI: 10.3892/mmr.2017.7311 Abstract. The endogenously activated rheumatoid arthritis Introduction (R A) synovial fibroblasts (RSFs) a re li kely to be the key to cur ing the disease. RSFs express Toll‑like receptors (TLRs) rendering Rheumatoid arthritis (RA) is a chronic inflammatory disease them prone to activation by exogenous and endogenous TLR characterized by articular inflammation and leads to joint ligands, resulting in the production of chemokines and cyto- destruction (1,2). RA pathogenesis involves a complex kines Germline deletion of tumor necrosis factor‑α-induced humoral and cellular immune response, including the infiltra- protein‑8 like 2 (TIPE2, also known as TNFAIP8L2) results tion of lymphocytes and monocytes into the synovium. These in fatal inflammation and hypersensitivity to TLR and T cell infiltrating cells and synoviocytes release numerous proin- receptor stimulation. The present study demonstrates an flammatory cytokine and chemokines, including interleukin inverse association between TIPE2 and cytokine gene expres- IL‑6, IL‑1 and tumor necrosis factor‑α (TNF‑α), which may sion in RSFs following lipopolysaccharide (LPS) stimulation. -
Nutrient Health and EROEN Compounds Resegsterixsteextics: Production * Gets Cartrai, Agairaxxxix
US 2011 O153221A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2011/0153221 A1 Stefanon et al. (43) Pub. Date: Jun. 23, 2011 (54) DIAGNOSTIC SYSTEM FOR SELECTING (52) U.S. Cl. .......................................................... 702/19 NUTRITION AND PHARMACOLOGICAL PRODUCTS FOR ANIMALS (57) ABSTRACT (76) Inventors: Bruno Stefanon, Martignacco (IT): W.Year Jean Dodds.Odds, Santa Monica,IVIon1ca, CA An analysis of the profile of a non-human animal comprises: a) providing a genotypic database to the species of the non (21) Appl. No.: 12/927,769 human animal Subject or a selected group of the species; b obtaining animal data; c) correlating the database of a) with (22) Filed:1-1. Nov. 19, 2010 the data ofb) to determinea relationshipp between the database of a) and the data of b); c) determining the profile of the Related U.S. Application Data animal based on the correlating step; and d) determining a (63)63) ContinuationConti offaroplication application No. 12/316.824,:4'. filed'O geneticmolecular profile dietary based signature on the being molecular a variation dietary of signature, expression the of Dec. 16, 2008, now Pat. No. 7,873,482. a set of genes which may differ for the genotype of each O O animal or a group of animals Nutrition and pharmalogical Publication Classification assessments are made. Reporting the determination is by the (51) Int. Cl. Internet, and payment for the report is obtained through the G06F 9/00 (2011.01) Internet. 38s. 4 gas registics, $88's *.icisixxxiiserscies: 8 texrigixi exsix * processire statisy • Essex: 88& goEffect onXXXXWWYYX Nutrient health and EROEN Compounds resegsterixsteextics: production * gets cartrai, agairaxxxix. -
Protein Interactions in the Cancer Proteome† Cite This: Mol
Molecular BioSystems View Article Online PAPER View Journal | View Issue Small-molecule binding sites to explore protein– protein interactions in the cancer proteome† Cite this: Mol. BioSyst., 2016, 12,3067 David Xu,ab Shadia I. Jalal,c George W. Sledge Jr.d and Samy O. Meroueh*aef The Cancer Genome Atlas (TCGA) offers an unprecedented opportunity to identify small-molecule binding sites on proteins with overexpressed mRNA levels that correlate with poor survival. Here, we analyze RNA-seq and clinical data for 10 tumor types to identify genes that are both overexpressed and correlate with patient survival. Protein products of these genes were scanned for binding sites that possess shape and physicochemical properties that can accommodate small-molecule probes or therapeutic agents (druggable). These binding sites were classified as enzyme active sites (ENZ), protein–protein interaction sites (PPI), or other sites whose function is unknown (OTH). Interestingly, the overwhelming majority of binding sites were classified as OTH. We find that ENZ, PPI, and OTH binding sites often occurred on the same structure suggesting that many of these OTH cavities can be used for allosteric modulation of Creative Commons Attribution 3.0 Unported Licence. enzyme activity or protein–protein interactions with small molecules. We discovered several ENZ (PYCR1, QPRT,andHSPA6)andPPI(CASC5, ZBTB32,andCSAD) binding sites on proteins that have been seldom explored in cancer. We also found proteins that have been extensively studied in cancer that have not been previously explored with small molecules that harbor ENZ (PKMYT1, STEAP3,andNNMT) and PPI (HNF4A, MEF2B,andCBX2) binding sites. All binding sites were classified by the signaling pathways to Received 29th March 2016, which the protein that harbors them belongs using KEGG. -
Mouse Steap4 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Steap4 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Steap4 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Steap4 gene (NCBI Reference Sequence: NM_054098 ; Ensembl: ENSMUSG00000012428 ) is located on Mouse chromosome 5. 5 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 5 (Transcript: ENSMUST00000115421). Exon 2~3 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Steap4 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-212F6 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a knock-out allele exhibit adipose accumulation, oxidative stress, increased liver weight, lower metabolic rate, hypoactivity, insulin resistance, glucose intolerance, mild hyperglycemia and dyslipidemia. Exon 2 starts from about 100% of the coding region. The knockout of Exon 2~3 will result in frameshift of the gene. The size of intron 1 for 5'-loxP site insertion: 14897 bp, and the size of intron 3 for 3'-loxP site insertion: 1385 bp. The size of effective cKO region: ~2082 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 4 5 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Steap4 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
The UBE2L3 Ubiquitin Conjugating Enzyme: Interplay with Inflammasome Signalling and Bacterial Ubiquitin Ligases
The UBE2L3 ubiquitin conjugating enzyme: interplay with inflammasome signalling and bacterial ubiquitin ligases Matthew James George Eldridge 2018 Imperial College London Department of Medicine Submitted to Imperial College London for the degree of Doctor of Philosophy 1 Abstract Inflammasome-controlled immune responses such as IL-1β release and pyroptosis play key roles in antimicrobial immunity and are heavily implicated in multiple hereditary autoimmune diseases. Despite extensive knowledge of the mechanisms regulating inflammasome activation, many downstream responses remain poorly understood or uncharacterised. The cysteine protease caspase-1 is the executor of inflammasome responses, therefore identifying and characterising its substrates is vital for better understanding of inflammasome-mediated effector mechanisms. Using unbiased proteomics, the Shenoy grouped identified the ubiquitin conjugating enzyme UBE2L3 as a target of caspase-1. In this work, I have confirmed UBE2L3 as an indirect target of caspase-1 and characterised its role in inflammasomes-mediated immune responses. I show that UBE2L3 functions in the negative regulation of cellular pro-IL-1 via the ubiquitin- proteasome system. Following inflammatory stimuli, UBE2L3 assists in the ubiquitylation and degradation of newly produced pro-IL-1. However, in response to caspase-1 activation, UBE2L3 is itself targeted for degradation by the proteasome in a caspase-1-dependent manner, thereby liberating an additional pool of IL-1 which may be processed and released. UBE2L3 therefore acts a molecular rheostat, conferring caspase-1 an additional level of control over this potent cytokine, ensuring that it is efficiently secreted only in appropriate circumstances. These findings on UBE2L3 have implications for IL-1- driven pathology in hereditary fever syndromes, and autoinflammatory conditions associated with UBE2L3 polymorphisms. -
Tumor Necrosis Factor-Α-Induced Protein 8-Like-2 Is Involved in the Activation of Macrophages by Astragalus Polysaccharides in Vitro
7428 MOLECULAR MEDICINE REPORTS 17: 7428-7434, 2018 Tumor necrosis factor-α-induced protein 8-like-2 is involved in the activation of macrophages by Astragalus polysaccharides in vitro JIE ZHU1, YUANYUAN ZHANG2, FANGHUA FAN1, GUOYOU WU1, ZHEN XIAO1 and HUANQIN ZHOU1 1Department of Clinical Laboratory, Zhejiang Hospital, Hangzhou, Zhejiang 310013; 2Department of Pulmonology, The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310052, P.R. China Received April 6, 2017; Accepted September 11, 2017 DOI: 10.3892/mmr.2018.8730 Abstract. In previous years, studies have shown that Introduction Astragalus polysaccharides (APS) can improve cellular immu- nity and humoral immune function, which has become a focus Macrophages are important immune cells, which are involved of investigations. Tumor necrosis factor-α-induced protein in the stimulation of the innate immune system, including the 8-like 2 (TIPE2) is a negative regulator of immune reactions. release of inflammatory cytokines and inflammatory molecules, However, the effect and underlying mechanisms of TIPE2 on including tumor necrosis-factor (TNF)-α, interleukin (IL)-1β, the APS-induced immune response remains to be fully eluci- IL-6 and nitric oxide (NO) (1,2). These cytokines and inflam- dated. The present study aimed to examine the role of TIPE2 matory molecules are often regulated by the mitogen-activated and its underlying mechanisms in the APS-induced immune protein kinase (MAPK) signaling pathway (3,4). response. The production of nitric oxide (NO) was detected TNF-α-induced protein-8 like 2 (TNFAIP8L2, also known in macrophages in vitro following APS stimulation. In addi- as TIPE2), is a novel member of the TNFAIP8 (TIPE) family. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine