Quantitative PCR Tissue Expression Profiling of the Human SGLT2 Gene and Related Family Members
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The Title of the Article
Mechanism-Anchored Profiling Derived from Epigenetic Networks Predicts Outcome in Acute Lymphoblastic Leukemia Xinan Yang, PhD1, Yong Huang, MD1, James L Chen, MD1, Jianming Xie, MSc2, Xiao Sun, PhD2, Yves A Lussier, MD1,3,4§ 1Center for Biomedical Informatics and Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637 USA 2State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, P.R.China 3The University of Chicago Cancer Research Center, and The Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL 60637 USA 4The Institute for Genomics and Systems Biology, and the Computational Institute, The University of Chicago, Chicago, IL 60637 USA §Corresponding author Email addresses: XY: [email protected] YH: [email protected] JC: [email protected] JX: [email protected] XS: [email protected] YL: [email protected] - 1 - Abstract Background Current outcome predictors based on “molecular profiling” rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate “mechanism-anchored profiling”. We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype. -
Supplementary Information Integrative Analyses of Splicing in the Aging Brain: Role in Susceptibility to Alzheimer’S Disease
Supplementary Information Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease Contents 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project 1.2. Mount Sinai Brain Bank Alzheimer’s Disease 1.3. CommonMind Consortium 1.4. Data Availability 2. Supplementary Tables 3. Supplementary Figures Note: Supplementary Tables are provided as separate Excel files. 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project Gene expression data1. Gene expression data were generated using RNA- sequencing from Dorsolateral Prefrontal Cortex (DLPFC) of 540 individuals, at an average sequence depth of 90M reads. Detailed description of data generation and processing was previously described2 (Mostafavi, Gaiteri et al., under review). Samples were submitted to the Broad Institute’s Genomics Platform for transcriptome analysis following the dUTP protocol with Poly(A) selection developed by Levin and colleagues3. All samples were chosen to pass two initial quality filters: RNA integrity (RIN) score >5 and quantity threshold of 5 ug (and were selected from a larger set of 724 samples). Sequencing was performed on the Illumina HiSeq with 101bp paired-end reads and achieved coverage of 150M reads of the first 12 samples. These 12 samples will serve as a deep coverage reference and included 2 males and 2 females of nonimpaired, mild cognitive impaired, and Alzheimer's cases. The remaining samples were sequenced with target coverage of 50M reads; the mean coverage for the samples passing QC is 95 million reads (median 90 million reads). The libraries were constructed and pooled according to the RIN scores such that similar RIN scores would be pooled together. -
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception. -
Curcumin Alters Gene Expression-Associated DNA Damage, Cell Cycle, Cell Survival and Cell Migration and Invasion in NCI-H460 Human Lung Cancer Cells in Vitro
ONCOLOGY REPORTS 34: 1853-1874, 2015 Curcumin alters gene expression-associated DNA damage, cell cycle, cell survival and cell migration and invasion in NCI-H460 human lung cancer cells in vitro I-TSANG CHIANG1,2, WEI-SHU WANG3, HSIN-CHUNG LIU4, SU-TSO YANG5, NOU-YING TANG6 and JING-GUNG CHUNG4,7 1Department of Radiation Oncology, National Yang‑Ming University Hospital, Yilan 260; 2Department of Radiological Technology, Central Taiwan University of Science and Technology, Taichung 40601; 3Department of Internal Medicine, National Yang‑Ming University Hospital, Yilan 260; 4Department of Biological Science and Technology, China Medical University, Taichung 404; 5Department of Radiology, China Medical University Hospital, Taichung 404; 6Graduate Institute of Chinese Medicine, China Medical University, Taichung 404; 7Department of Biotechnology, Asia University, Taichung 404, Taiwan, R.O.C. Received March 31, 2015; Accepted June 26, 2015 DOI: 10.3892/or.2015.4159 Abstract. Lung cancer is the most common cause of cancer CARD6, ID1 and ID2 genes, associated with cell survival and mortality and new cases are on the increase worldwide. the BRMS1L, associated with cell migration and invasion. However, the treatment of lung cancer remains unsatisfactory. Additionally, 59 downregulated genes exhibited a >4-fold Curcumin has been shown to induce cell death in many human change, including the DDIT3 gene, associated with DNA cancer cells, including human lung cancer cells. However, the damage; while 97 genes had a >3- to 4-fold change including the effects of curcumin on genetic mechanisms associated with DDIT4 gene, associated with DNA damage; the CCPG1 gene, these actions remain unclear. Curcumin (2 µM) was added associated with cell cycle and 321 genes with a >2- to 3-fold to NCI-H460 human lung cancer cells and the cells were including the GADD45A and CGREF1 genes, associated with incubated for 24 h. -
Disease-Related Cellular Protein Networks Differentially Affected
www.nature.com/scientificreports OPEN Disease‑related cellular protein networks diferentially afected under diferent EGFR mutations in lung adenocarcinoma Toshihide Nishimura1,8*, Haruhiko Nakamura1,2,8, Ayako Yachie3,8, Takeshi Hase3,8, Kiyonaga Fujii1,8, Hirotaka Koizumi4, Saeko Naruki4, Masayuki Takagi4, Yukiko Matsuoka3, Naoki Furuya5, Harubumi Kato6,7 & Hisashi Saji2 It is unclear how epidermal growth factor receptor EGFR major driver mutations (L858R or Ex19del) afect downstream molecular networks and pathways. This study aimed to provide information on the infuences of these mutations. The study assessed 36 protein expression profles of lung adenocarcinoma (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Weighted gene co-expression network analysis together with analysis of variance-based screening identifed 13 co-expressed modules and their eigen proteins. Pathway enrichment analysis for the Ex19del mutation demonstrated involvement of SUMOylation, epithelial and mesenchymal transition, ERK/mitogen- activated protein kinase signalling via phosphorylation and Hippo signalling. Additionally, analysis for the L858R mutation identifed various pathways related to cancer cell survival and death. With regard to the Ex19del mutation, ROCK, RPS6KA1, ARF1, IL2RA and several ErbB pathways were upregulated, whereas AURK and GSKIP were downregulated. With regard to the L858R mutation, RB1, TSC22D3 and DOCK1 were downregulated, whereas various networks, including VEGFA, were moderately upregulated. In all mutation types, CD80/CD86 (B7), MHC, CIITA and IFGN were activated, whereas CD37 and SAFB were inhibited. Costimulatory immune-checkpoint pathways by B7/CD28 were mainly activated, whereas those by PD-1/PD-L1 were inhibited. Our fndings may help identify potential therapeutic targets and develop therapeutic strategies to improve patient outcomes. -
Supplementary Table 1: List of the 316 Genes Regulated During Hyperglycemic Euinsulinemic Clamp in Skeletal Muscle
Supplementary Table 1: List of the 316 genes regulated during hyperglycemic euinsulinemic clamp in skeletal muscle. UGCluster Name Symbol Fold Change Cytoband Response to stress Hs.517581 Heme oxygenase (decycling) 1 HMOX1 3.80 22q12 Hs.374950 Metallothionein 1X MT1X 2.20 16q13 Hs.460867 Metallothionein 1B (functional) MT1B 1.70 16q13 Hs.148778 Oxidation resistance 1 OXR1 1.60 8q23 Hs.513626 Metallothionein 1F (functional) MT1F 1.47 16q13 Hs.534330 Metallothionein 2A MT2A 1.45 16q13 Hs.438462 Metallothionein 1H MT1H 1.42 16q13 Hs.523836 Glutathione S-transferase pi GSTP1 -1.74 11q13 Hs.459952 Stannin SNN -1.92 16p13 Immune response, cytokines & related Hs.478275 TNF (ligand) superfamily, member 10 (TRAIL) TNFSF10 1.58 3q26 Hs.278573 CD59 antigen p18-20 (protectin) CD59 1.49 11p13 Hs.534847 Complement component 4B, telomeric C4A 1.47 6p21.3 Hs.535668 Immunoglobulin lambda variable 6-57 IGLV6-57 1.40 22q11.2 Hs.529846 Calcium modulating ligand CAMLG -1.40 5q23 Hs.193516 B-cell CLL/lymphoma 10 BCL10 -1.40 1p22 Hs.840 Indoleamine-pyrrole 2,3 dioxygenase INDO -1.40 8p12-p11 Hs.201083 Mal, T-cell differentiation protein 2 MAL2 -1.44 Hs.522805 CD99 antigen-like 2 CD99L2 -1.45 Xq28 Hs.50002 Chemokine (C-C motif) ligand 19 CCL19 -1.45 9p13 Hs.350268 Interferon regulatory factor 2 binding protein 2 IRF2BP2 -1.47 1q42.3 Hs.567249 Contactin 1 CNTN1 -1.47 12q11-q12 Hs.132807 MHC class I mRNA fragment 3.8-1 3.8-1 -1.48 6p21.3 Hs.416925 Carcinoembryonic antigen-related cell adhesion molecule 19 CEACAM19 -1.49 19q13.31 Hs.89546 Selectin E (endothelial -
Human Induced Pluripotent Stem Cell–Derived Podocytes Mature Into Vascularized Glomeruli Upon Experimental Transplantation
BASIC RESEARCH www.jasn.org Human Induced Pluripotent Stem Cell–Derived Podocytes Mature into Vascularized Glomeruli upon Experimental Transplantation † Sazia Sharmin,* Atsuhiro Taguchi,* Yusuke Kaku,* Yasuhiro Yoshimura,* Tomoko Ohmori,* ‡ † ‡ Tetsushi Sakuma, Masashi Mukoyama, Takashi Yamamoto, Hidetake Kurihara,§ and | Ryuichi Nishinakamura* *Department of Kidney Development, Institute of Molecular Embryology and Genetics, and †Department of Nephrology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan; ‡Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Hiroshima, Japan; §Division of Anatomy, Juntendo University School of Medicine, Tokyo, Japan; and |Japan Science and Technology Agency, CREST, Kumamoto, Japan ABSTRACT Glomerular podocytes express proteins, such as nephrin, that constitute the slit diaphragm, thereby contributing to the filtration process in the kidney. Glomerular development has been analyzed mainly in mice, whereas analysis of human kidney development has been minimal because of limited access to embryonic kidneys. We previously reported the induction of three-dimensional primordial glomeruli from human induced pluripotent stem (iPS) cells. Here, using transcription activator–like effector nuclease-mediated homologous recombination, we generated human iPS cell lines that express green fluorescent protein (GFP) in the NPHS1 locus, which encodes nephrin, and we show that GFP expression facilitated accurate visualization of nephrin-positive podocyte formation in -
(12) Patent Application Publication (10) Pub. No.: US 2016/0250307 A1 Weinschenk Et Al
US 2016O250307A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2016/0250307 A1 Weinschenk et al. (43) Pub. Date: Sep. 1, 2016 (54) NOVEL PEPTIDES AND COMBINATION OF A 6LX35/7 (2006.01) PEPTDES FOR USE IN IMMUNOTHERAPY CI2N5/0783 (2006.01) AGAINST HEPATOCELLULAR CARCINOMA (HCC) AND OTHER CANCERS (52) U.S. Cl. CPC ............. A61K 39/00II (2013.01); A61 K35/17 (71) Applicant: Immatics Biotechnologies GmbH, (2013.01); C12N5/0636 (2013.01); G0IN Tuebingen (DE) 33/6803 (2013.01); C07K 16/18 (2013.01); (72) Inventors: Toni Weinschenk, Aichwald (DE); CI2N 15/115 (2013.01); C12N 2501/998 Andrea Mahr, Tuebingen (DE); Jens (2013.01); C07K 2317/70 (2013.01); C12N Fritsche, Dusslingen (DE); Phillip 2310/16 (2013.01); A6 IK 2035/124 (2013.01) Mueller, Tuebingen (DE); Anita Wiebe, Pliezhausen (DE); Sara Kutscher, (57) ABSTRACT Tuebingen (DE) The present invention relates to peptides, proteins, nucleic (21) Appl. No.: 14/975,952 acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy (22) Filed: Dec. 21, 2015 of cancer. The present invention furthermore relates to tumor Related U.S. Application Data associated T-cell peptide epitopes, alone or in combination (60) Provisional application No. 62/096,165, filed on Dec. with other tumor-associated peptides that can for example 23, 2014. serve as active pharmaceutical ingredients of vaccine com positions that stimulate anti-tumor immune responses, or to (30) Foreign Application Priority Data stimulate T cells ex vivo and transfer into patients. Peptides Dec. 23, 2014 (GB) ................................... 1423016.3 bound to molecules of the major histocompatibility complex Jan. -
The Kinesin Spindle Protein Inhibitor Filanesib Enhances the Activity of Pomalidomide and Dexamethasone in Multiple Myeloma
Plasma Cell Disorders SUPPLEMENTARY APPENDIX The kinesin spindle protein inhibitor filanesib enhances the activity of pomalidomide and dexamethasone in multiple myeloma Susana Hernández-García, 1 Laura San-Segundo, 1 Lorena González-Méndez, 1 Luis A. Corchete, 1 Irena Misiewicz- Krzeminska, 1,2 Montserrat Martín-Sánchez, 1 Ana-Alicia López-Iglesias, 1 Esperanza Macarena Algarín, 1 Pedro Mogollón, 1 Andrea Díaz-Tejedor, 1 Teresa Paíno, 1 Brian Tunquist, 3 María-Victoria Mateos, 1 Norma C Gutiérrez, 1 Elena Díaz- Rodriguez, 1 Mercedes Garayoa 1* and Enrique M Ocio 1* 1Centro Investigación del Cáncer-IBMCC (CSIC-USAL) and Hospital Universitario-IBSAL, Salamanca, Spain; 2National Medicines Insti - tute, Warsaw, Poland and 3Array BioPharma, Boulder, Colorado, USA *MG and EMO contributed equally to this work ©2017 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2017.168666 Received: March 13, 2017. Accepted: August 29, 2017. Pre-published: August 31, 2017. Correspondence: [email protected] MATERIAL AND METHODS Reagents and drugs. Filanesib (F) was provided by Array BioPharma Inc. (Boulder, CO, USA). Thalidomide (T), lenalidomide (L) and pomalidomide (P) were purchased from Selleckchem (Houston, TX, USA), dexamethasone (D) from Sigma-Aldrich (St Louis, MO, USA) and bortezomib from LC Laboratories (Woburn, MA, USA). Generic chemicals were acquired from Sigma Chemical Co., Roche Biochemicals (Mannheim, Germany), Merck & Co., Inc. (Darmstadt, Germany). MM cell lines, patient samples and cultures. Origin, authentication and in vitro growth conditions of human MM cell lines have already been characterized (17, 18). The study of drug activity in the presence of IL-6, IGF-1 or in co-culture with primary bone marrow mesenchymal stromal cells (BMSCs) or the human mesenchymal stromal cell line (hMSC–TERT) was performed as described previously (19, 20). -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Behind Melanocortin Antagonist Overexpression in the Zebrafish Brain: a Behavioral and Transcriptomic Approach
Behind melanocortin antagonist overexpression in the zebrafish brain: a behavioral and transcriptomic approach 1 1 1 1 1 Raúl Guillot , Raúl Cortés , Sandra Navarro , Morena Mischitelli , Víctor García-Herranz , Elisa 2 3 4 5 6 Sánchez 1, Laura Cal , Juan Carlos Navarro , Jesús Míguez , Sergey Afanasyev , Aleksei Krasnov , 2 1 Roger D Cone 7, Josep Rotllant *, Jose Miguel Cerdá-Reverter * 1 Control of Food Intake Group, Department of Fish Physiolgy and Biotechnology, Instituto de 2 Acuicultura de Torre de la Sal (IATS-CSIC). Castellón, Spain, 12595. Aquatic Molecular Pathobiology Group, Instituto de Investigaciones Marinas, Consejo Superior de Investigaciones 3 Científicas (CSIC). Vigo, Spain. Lipid Group, Department of Biology, Culture and Pathology of Marine Species, Instituto de Acuicultura de Torre de la Sal (IATS-CSIC). Castellón, Spain, 12595. 4 Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, 5 Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain, 36310. Sechenov Institute of Evolutionary Physiology and Biochemistry, M. Toreza Av. 44, Saint Petersburg 194223, Russia 6 Nofima Marine, Norwegian Institutes of Food, Fisheries & Aquaculture Research, 5010 1432 Ås 7 Norway. Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, 702 Light Hall (0165), Nashville, Tennessee 37232–0165. *Corresponding authors and reprint requests: José Miguel Cerdá-Reverter, Instituto de Acuicultura de Torre de la Sal, CSIC. Torre la Sal s/n, 12595, Ribera de Cabanes, Castellón, Spain. Tel. (+34) 964319500 Fax (+34) 964319509. E-mail: [email protected] Josep Rotllant, Instituto de Investigaciones Marinas, CSIC. Eduardo Cabello, 36208, Vigo (Pontevedra), Spain. Tel. (+34) 986-231930 Fax (+34) 986 292 762. -
A Second Generation Human Haplotype Map of Over 3.1 Million Snps the International Hapmap Consortium1
doi: 10.1038/nature06258 SUPPLEMENTARY INFORMATION A second generation human haplotype map of over 3.1 million SNPs The International HapMap Consortium1 Supplementary material S1 The density of common SNPs in the Phase II HapMap and the assembled human genome S2 Analysis of data quality S2.1 Analysis of amplicon structure to genotyping error S2.2 Analysis of genotype discordance from overlap with Seattle SNPs S2.3 Analysis of genotype discordance from fosmid end sequences S2.4 Analysis of monomorphism/polymorphism discrepancies S2.5 Interchromosomal LD S3. Analysis of population stratification S4. Analysis of relatedness S5. Segmental analysis of relatedness S6. Analysis of homozygosity S7. Perlegen genotyping protocols Supplementary tables Legends to supplementary figures 1 See end of manuscript for Consortium details www.nature.com/nature 1 doi: 10.1038/nature06258 SUPPLEMENTARY INFORMATION Supplementary text 1. The density of common SNPs in the Phase II HapMap and the assembled human genome. To estimate the fraction of all common variants on the autosomes that have been successfully genotyped in the consensus Phase II HapMap we note that in YRI (release 21) there are 2,334,980 SNPs with MAF≥0.05. Across the autosomes, the completed reference sequence assembled in contigs is 2.68 billion bp. Assuming that the allele frequency distribution in the YRI is well approximated by that of a simple coalescent model and using an estimate of the population mutation rate of θ = 1.2 per kb for African populations1,2 the expected number of variants with MAF≥0.05 in a sample of 120 chromosomes is 114 = θ E(S MAF≥5% ) L ∑ /1 i i=6 where L is the total length of the sequence3.