Loss of the E3 Ubiquitin Ligase MKRN1 Represses Diet-Induced Metabolic Syndrome Through AMPK Activation
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DEPs in osteosarcoma cells comparing to osteoblastic cells Biological Process Protein Percentage of Hits metabolic process (GO:0008152) 29.3 29.3% cellular process (GO:0009987) 20.2 20.2% localization (GO:0051179) 9.4 9.4% biological regulation (GO:0065007) 8 8.0% developmental process (GO:0032502) 7.8 7.8% response to stimulus (GO:0050896) 5.6 5.6% cellular component organization (GO:0071840) 5.6 5.6% multicellular organismal process (GO:0032501) 4.4 4.4% immune system process (GO:0002376) 4.2 4.2% biological adhesion (GO:0022610) 2.7 2.7% apoptotic process (GO:0006915) 1.6 1.6% reproduction (GO:0000003) 0.8 0.8% locomotion (GO:0040011) 0.4 0.4% cell killing (GO:0001906) 0.1 0.1% 100.1% Genes 2179Hits 3870 biological adhesion apoptotic process … reproduction (GO:0000003) , 0.8% (GO:0022610) , 2.7% locomotion (GO:0040011) ,… immune system process cell killing (GO:0001906) , 0.1% (GO:0002376) , 4.2% multicellular organismal process (GO:0032501) , metabolic process 4.4% (GO:0008152) , 29.3% cellular component organization (GO:0071840) , 5.6% response to stimulus (GO:0050896), 5.6% developmental process (GO:0032502) , 7.8% biological regulation (GO:0065007) , 8.0% cellular process (GO:0009987) , 20.2% localization (GO:0051179) , 9. -
Supplemental Information to Mammadova-Bach Et Al., “Laminin Α1 Orchestrates VEGFA Functions in the Ecosystem of Colorectal Carcinogenesis”
Supplemental information to Mammadova-Bach et al., “Laminin α1 orchestrates VEGFA functions in the ecosystem of colorectal carcinogenesis” Supplemental material and methods Cloning of the villin-LMα1 vector The plasmid pBS-villin-promoter containing the 3.5 Kb of the murine villin promoter, the first non coding exon, 5.5 kb of the first intron and 15 nucleotides of the second villin exon, was generated by S. Robine (Institut Curie, Paris, France). The EcoRI site in the multi cloning site was destroyed by fill in ligation with T4 polymerase according to the manufacturer`s instructions (New England Biolabs, Ozyme, Saint Quentin en Yvelines, France). Site directed mutagenesis (GeneEditor in vitro Site-Directed Mutagenesis system, Promega, Charbonnières-les-Bains, France) was then used to introduce a BsiWI site before the start codon of the villin coding sequence using the 5’ phosphorylated primer: 5’CCTTCTCCTCTAGGCTCGCGTACGATGACGTCGGACTTGCGG3’. A double strand annealed oligonucleotide, 5’GGCCGGACGCGTGAATTCGTCGACGC3’ and 5’GGCCGCGTCGACGAATTCACGC GTCC3’ containing restriction site for MluI, EcoRI and SalI were inserted in the NotI site (present in the multi cloning site), generating the plasmid pBS-villin-promoter-MES. The SV40 polyA region of the pEGFP plasmid (Clontech, Ozyme, Saint Quentin Yvelines, France) was amplified by PCR using primers 5’GGCGCCTCTAGATCATAATCAGCCATA3’ and 5’GGCGCCCTTAAGATACATTGATGAGTT3’ before subcloning into the pGEMTeasy vector (Promega, Charbonnières-les-Bains, France). After EcoRI digestion, the SV40 polyA fragment was purified with the NucleoSpin Extract II kit (Machery-Nagel, Hoerdt, France) and then subcloned into the EcoRI site of the plasmid pBS-villin-promoter-MES. Site directed mutagenesis was used to introduce a BsiWI site (5’ phosphorylated AGCGCAGGGAGCGGCGGCCGTACGATGCGCGGCAGCGGCACG3’) before the initiation codon and a MluI site (5’ phosphorylated 1 CCCGGGCCTGAGCCCTAAACGCGTGCCAGCCTCTGCCCTTGG3’) after the stop codon in the full length cDNA coding for the mouse LMα1 in the pCIS vector (kindly provided by P. -
Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer Kumardeep Chaudhary1, Olivier B
Published OnlineFirst October 5, 2017; DOI: 10.1158/1078-0432.CCR-17-0853 Statistics in CCR Clinical Cancer Research Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer Kumardeep Chaudhary1, Olivier B. Poirion1, Liangqun Lu1,2, and Lana X. Garmire1,2 Abstract Identifying robust survival subgroups of hepatocellular car- index (C-index) ¼ 0.68]. More aggressive subtype is associated cinoma (HCC) will significantly improve patient care. Current- with frequent TP53 inactivation mutations, higher expression ly, endeavor of integrating multi-omicsdatatoexplicitlypredict of stemness markers (KRT19 and EPCAM)andtumormarker HCC survival from multiple patient cohorts is lacking. To fill BIRC5, and activated Wnt and Akt signaling pathways. We this gap, we present a deep learning (DL)–based model on HCC validated this multi-omics model on five external datasets of that robustly differentiates survival subpopulations of patients various omics types: LIRI-JP cohort (n ¼ 230, C-index ¼ 0.75), in six cohorts. We built the DL-based, survival-sensitive model NCI cohort (n ¼ 221, C-index ¼ 0.67), Chinese cohort (n ¼ on 360 HCC patients' data using RNA sequencing (RNA-Seq), 166, C-index ¼ 0.69), E-TABM-36 cohort (n ¼ 40, C-index ¼ miRNA sequencing (miRNA-Seq), and methylation data from 0.77), and Hawaiian cohort (n ¼ 27, C-index ¼ 0.82). This TheCancerGenomeAtlas(TCGA),whichpredictsprognosis is the first study to employ DL to identify multi-omics features as good as an alternative model where genomics and clinical linked to the differential survival of patients with HCC. Given data are both considered. This DL-based model provides two its robustness over multiple cohorts, we expect this workflow to optimal subgroups of patients with significant survival differ- be useful at predicting HCC prognosis prediction. -
Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer
Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer By Josiah Ewing Hutton, III. Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biochemistry December 2016 Nashville, Tennessee Approved: Daniel C. Liebler, Ph.D. Robert J. Coffey, M.D. Bruce D. Carter, Ph.D. Nicholas J. Reiter, Ph.D. Jamey D. Young, Ph.D. Charles R. Sanders, Ph.D. Acknowledgements I would like to acknowledge my mentor, Dr. Daniel Liebler, for his constant guidance throughout my graduate career. Dan allowed me the freedom to develop as a scientist, and tactfully provided the tutelage and discussion I needed at exactly the right time and not a moment earlier. I will be grateful for his mentorship, insight, and his wit for the rest of my career. I would also like to acknowledge all current and former laboratory members for not only providing insight and guidance with my dissertation, but also for making every single day in lab enjoyable. I wish to acknowledge my committee members, Dr. Bruce Carter, Dr. Robert Coffey, Dr. Nicholas Reiter, Dr. Charles Sanders, and Dr. Jamey Young. Our meetings throughout the years have helped to guide my research to the work that it is today. I am grateful to my friends, who have always been there for me and would quietly, and sometimes not so quietly, listen to me rehearse my dissertation while we were climbing, so long as I would then push them to climb harder. Lastly, I am grateful to my family, who have always supported me and driven me to work harder. -
Small-Molecule Inhibition of 6-Phosphofructo-2-Kinase Activity Suppresses Glycolytic Flux and Tumor Growth
110 Small-molecule inhibition of 6-phosphofructo-2-kinase activity suppresses glycolytic flux and tumor growth Brian Clem,1,3 Sucheta Telang,1,3 Amy Clem,1,3 reduces the intracellular concentration of Fru-2,6-BP, Abdullah Yalcin,1,2,3 Jason Meier,2 glucose uptake, and growth of established tumors in vivo. Alan Simmons,1,3 Mary Ann Rasku,1,3 Taken together, these data support the clinical development Sengodagounder Arumugam,1,3 of 3PO and other PFKFB3 inhibitors as chemotherapeutic William L. Dean,2,3 John Eaton,1,3 Andrew Lane,1,3 agents. [Mol Cancer Ther 2008;7(1):110–20] John O. Trent,1,2,3 and Jason Chesney1,2,3 Departments of 1Medicine and 2Biochemistry and Molecular Introduction Biology and 3Molecular Targets Group, James Graham Brown Neoplastic transformation causes a marked increase in Cancer Center, University of Louisville, Louisville, Kentucky glucose uptake and catabolic conversion to lactate, which forms the basis for the most specific cancer diagnostic 18 Abstract examination—positron emission tomography of 2- F- fluoro-2-deoxyglucose (18F-2-DG) uptake (1). The protein 6-Phosphofructo-1-kinase, a rate-limiting enzyme of products of several oncogenes directly increase glycolytic glycolysis, is activated in neoplastic cells by fructose-2,6- flux even under normoxic conditions, a phenomenon bisphosphate (Fru-2,6-BP), a product of four 6-phospho- originally termed the Warburg effect (2, 3). For example, fructo-2-kinase/fructose-2,6-bisphosphatase isozymes c-myc is a transcription factor that promotes the expression (PFKFB1-4). The inducible PFKFB3 isozyme is constitu- of glycolytic enzyme mRNAs, and its expression is increased tively expressed by neoplastic cells and required for the in several human cancers regardless of the oxygen pressure high glycolytic rate and anchorage-independent growth of (4, 5). -
Toolboxes for a Standardised and Systematic Study of Glycans
Campbell et al. BMC Bioinformatics 2014, 15(Suppl 1):S9 http://www.biomedcentral.com/1471-2105/15/S1/S9 RESEARCH Open Access Toolboxes for a standardised and systematic study of glycans Matthew P Campbell1, René Ranzinger2, Thomas Lütteke3, Julien Mariethoz4, Catherine A Hayes5, Jingyu Zhang1, Yukie Akune6, Kiyoko F Aoki-Kinoshita6, David Damerell7,11, Giorgio Carta8, Will S York2, Stuart M Haslam7, Hisashi Narimatsu9, Pauline M Rudd8, Niclas G Karlsson4, Nicolle H Packer1, Frédérique Lisacek4,10* From Integrated Bio-Search: 12th International Workshop on Network Tools and Applications in Biology (NETTAB 2012) Como, Italy. 14-16 November 2012 Abstract Background: Recent progress in method development for characterising the branched structures of complex carbohydrates has now enabled higher throughput technology. Automation of structure analysis then calls for software development since adding meaning to large data collections in reasonable time requires corresponding bioinformatics methods and tools. Current glycobioinformatics resources do cover information on the structure and function of glycans, their interaction with proteins or their enzymatic synthesis. However, this information is partial, scattered and often difficult to find to for non-glycobiologists. Methods: Following our diagnosis of the causes of the slow development of glycobioinformatics, we review the “objective” difficulties encountered in defining adequate formats for representing complex entities and developing efficient analysis software. Results: Various solutions already implemented and strategies defined to bridge glycobiology with different fields and integrate the heterogeneous glyco-related information are presented. Conclusions: Despite the initial stage of our integrative efforts, this paper highlights the rapid expansion of glycomics, the validity of existing resources and the bright future of glycobioinformatics. -
Anti-IDH3A Antibody (ARG42205)
Product datasheet [email protected] ARG42205 Package: 100 μl anti-IDH3A antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes IDH3A Tested Reactivity Hu, Ms, Rat Tested Application ICC/IF, IHC-P, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name IDH3A Antigen Species Human Immunogen Recombinant fusion protein corresponding to aa. 28-366 of Human IDH3A (NP_005521.1). Conjugation Un-conjugated Alternate Names Isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial; EC 1.1.1.41; NAD; Isocitric dehydrogenase subunit alpha; + Application Instructions Application table Application Dilution ICC/IF 1:50 - 1:200 IHC-P 1:50 - 1:200 WB 1:500 - 1:2000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control Raji Calculated Mw 40 kDa Observed Size ~ 40 kDa Properties Form Liquid Purification Affinity purified. Buffer PBS (pH 7.3), 0.02% Sodium azide and 50% Glycerol. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw www.arigobio.com 1/3 cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol IDH3A Gene Full Name isocitrate dehydrogenase 3 (NAD+) alpha Background Isocitrate dehydrogenases catalyze the oxidative decarboxylation of isocitrate to 2-oxoglutarate. -
Life with 6000 Genes Author(S): A. Goffeau, B. G. Barrell, H. Bussey, R
Life with 6000 Genes Author(s): A. Goffeau, B. G. Barrell, H. Bussey, R. W. Davis, B. Dujon, H. Feldmann, F. Galibert, J. D. Hoheisel, C. Jacq, M. Johnston, E. J. Louis, H. W. Mewes, Y. Murakami, P. Philippsen, H. Tettelin and S. G. Oliver Source: Science, Vol. 274, No. 5287, Genome Issue (Oct. 25, 1996), pp. 546+563-567 Published by: American Association for the Advancement of Science Stable URL: https://www.jstor.org/stable/2899628 Accessed: 28-08-2019 13:31 UTC REFERENCES Linked references are available on JSTOR for this article: https://www.jstor.org/stable/2899628?seq=1&cid=pdf-reference#references_tab_contents You may need to log in to JSTOR to access the linked references. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at https://about.jstor.org/terms American Association for the Advancement of Science is collaborating with JSTOR to digitize, preserve and extend access to Science This content downloaded from 152.3.43.41 on Wed, 28 Aug 2019 13:31:29 UTC All use subject to https://about.jstor.org/terms by FISH across the whole genome. A subset of the 37. G. D. Billingsleyet al., Am. J. Hum. Genet. 52, 343 (1994); L. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Genome-Wide Transcriptional Sequencing Identifies Novel Mutations in Metabolic Genes in Human Hepatocellular Carcinoma DAOUD M
CANCER GENOMICS & PROTEOMICS 11 : 1-12 (2014) Genome-wide Transcriptional Sequencing Identifies Novel Mutations in Metabolic Genes in Human Hepatocellular Carcinoma DAOUD M. MEERZAMAN 1,2 , CHUNHUA YAN 1, QING-RONG CHEN 1, MICHAEL N. EDMONSON 1, CARL F. SCHAEFER 1, ROBERT J. CLIFFORD 2, BARBARA K. DUNN 3, LI DONG 2, RICHARD P. FINNEY 1, CONSTANCE M. CULTRARO 2, YING HU1, ZHIHUI YANG 2, CU V. NGUYEN 1, JENNY M. KELLEY 2, SHUANG CAI 2, HONGEN ZHANG 2, JINGHUI ZHANG 1,4 , REBECCA WILSON 2, LAUREN MESSMER 2, YOUNG-HWA CHUNG 5, JEONG A. KIM 5, NEUNG HWA PARK 6, MYUNG-SOO LYU 6, IL HAN SONG 7, GEORGE KOMATSOULIS 1 and KENNETH H. BUETOW 1,2 1Center for Bioinformatics and Information Technology, National Cancer Institute, Rockville, MD, U.S.A.; 2Laboratory of Population Genetics, National Cancer Institute, National Cancer Institute, Bethesda, MD, U.S.A.; 3Basic Prevention Science Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, U.S.A; 4Department of Biotechnology/Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, U.S.A.; 5Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea; 6Department of Internal Medicine, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Korea; 7Department of Internal Medicine, College of Medicine, Dankook University, Cheon-An, Korea Abstract . We report on next-generation transcriptome Worldwide, liver cancer is the fifth most common cancer and sequencing results of three human hepatocellular carcinoma the third most common cause of cancer-related mortality (1). tumor/tumor-adjacent pairs. -
Lipid Deposition and Metabolism in Local and Modern Pig Breeds: a Review
animals Review Lipid Deposition and Metabolism in Local and Modern Pig Breeds: A Review Klavdija Poklukar 1 , Marjeta Candek-Potokarˇ 1,2 , Nina Batorek Lukaˇc 1 , Urška Tomažin 1 and Martin Škrlep 1,* 1 Agricultural Institute of Slovenia, Ljubljana SI-1000, Slovenia; [email protected] (K.P.); [email protected] (M.C.-P.);ˇ [email protected] (N.B.L.); [email protected] (U.T.) 2 University of Maribor, Faculty of Agriculture and Life Sciences, HoˇceSI-2311, Slovenia * Correspondence: [email protected]; Tel.: +386-(0)1-280-52-34 Received: 17 February 2020; Accepted: 29 February 2020; Published: 3 March 2020 Simple Summary: Intensive selective breeding and genetic improvement of relatively few pig breeds led to the abandonment of many low productive local pig breeds. However, local pig breeds are more highly adapted to their specific environmental conditions and feeding resources, and therefore present a valuable genetic resource. They are able to deposit more fat and have a distinct lipogenic capacity, along with a better fatty acid composition than modern breeds. Physiological, biochemical and genetic mechanisms responsible for the differences between fatty and lean breeds are still not fully clarified. The present paper highlights important associations to better understand the underlying mechanisms of lipid deposition in subcutaneous and intramuscular fat between fatty and lean breeds. Abstract: Modern pig breeds, which have been genetically improved to achieve fast growth and a lean meat deposition, differ from local pig breeds with respect to fat deposition, fat specific metabolic characteristics and various other properties. The present review aimed to elucidate the mechanisms underlying the differences between fatty local and modern lean pig breeds in adipose tissue deposition and lipid metabolism, taking into consideration morphological, cellular, biochemical, transcriptomic and proteomic perspectives. -
S41467-020-19704-X.Pdf
ARTICLE https://doi.org/10.1038/s41467-020-19704-x OPEN EZH2-mediated PP2A inactivation confers resistance to HER2-targeted breast cancer therapy Yi Bao1,2, Gokce Oguz2, Wee Chyan Lee2, Puay Leng Lee2, Kakaly Ghosh2, Jiayao Li3, Panpan Wang3, ✉ Peter E. Lobie1,4, Sidse Ehmsen 5, Henrik J. Ditzel 5,6, Andrea Wong7, Ern Yu Tan8, Soo Chin Lee1,7 & ✉ Qiang Yu 2,9,10 HER2-targeted therapy has yielded a significant clinical benefit in patients with HER2+ breast 1234567890():,; cancer, yet disease relapse due to intrinsic or acquired resistance remains a significant challenge in the clinic. Here, we show that the protein phosphatase 2A (PP2A) regulatory subunit PPP2R2B is a crucial determinant of anti-HER2 response. PPP2R2B is downregulated in a substantial subset of HER2+ breast cancers, which correlates with poor clinical outcome and resistance to HER2-targeted therapies. EZH2-mediated histone modification accounts for the PPP2R2B downregulation, resulting in sustained phosphorylation of PP2A targets p70S6K and 4EBP1 which leads to resistance to inhibition by anti-HER2 treatments. Genetic depletion or inhibition of EZH2 by a clinically-available EZH2 inhibitor restores PPP2R2B expression, abolishes the residual phosphorylation of p70S6K and 4EBP1, and resensitizes HER2+ breast cancer cells to anti-HER2 treatments both in vitro and in vivo. Furthermore, the same epi- genetic mechanism also contributes to the development of acquired resistance through clonal selection. These findings identify EZH2-dependent PPP2R2B suppression as an epigenetic control of anti-HER2 resistance, potentially providing an opportunity to mitigate anti-HER2 resistance with EZH2 inhibitors. 1 Cancer Science Institute of Singapore, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.