Histology and Histopathology
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Age-Dependent Myocardial Transcriptomic Changes in the Rat
Revista Română de Medicină de Laborator Vol. 22, Nr. 1, Martie, 2014 9 Research article DOI: 10.2478/rrlm-2014-0001 Age-dependent myocardial transcriptomic changes in the rat. Novel insights into atrial and ventricular arrhythmias pathogenesis Modificări transcriptomice dependente de vârstă în miocardul de șobolan. Noi aspecte referitoare la patogeneza aritmiilor atriale și ventriculare Alina Scridon1,2, Emmanuelle Fouilloux-Meugnier3, Emmanuelle Loizon3, Marcel Perian1, Sophie Rome3, Claude Julien2, Christian Barrès2, Philippe Chevalier2,4 1.Physiology Department, University of Medicine and Pharmacy of Tîrgu Mureș, 540139, Tîrgu Mureș, Romania 2. Unité de Neurocardiologie, EA4612, Université Lyon 1, F-69008, Lyon, France 3. Unité 1060 INSERM CarMen, Université Lyon 1, F-69008, Lyon, France 4. Hospices Civils de Lyon, Hôpital Louis Pradel, Service de Rythmologie, 69500, Bron, France Abstract Background: Aging is associated with significantly increased prevalence of cardiac arrhythmias, but tran- scriptional events that underlie this process remain to be established. To gain deeper insight into molecular mech- anisms of aging-related cardiac arrhythmias, we performed mRNA expression analysis comparing atrial and ven- tricular myocardium from Wistar-Kyoto (WKY) rats of different ages. Methods: Atrial and ventricular sampling was performed in 3 groups (n=4 each) of young (14-week-old), adult (25-week-old), and aging (47-week-old) WKY rats. mRNA expressions of 89 genes involved in cardiac arrhythmogenicity were investigated using TaqMan Low Density Array analysis. Results: Of the 89 studied genes, 40 and 64 genes presented steady atrial and ventricu- lar expressions, respectively. All genes differentially expressed within the atria of WKY rats were up-regulated with advancing age, mainly the genes encoding for various K+, Ca2+, Na+ channels, and type 6 collagen. -
The Mineralocorticoid Receptor Leads to Increased Expression of EGFR
www.nature.com/scientificreports OPEN The mineralocorticoid receptor leads to increased expression of EGFR and T‑type calcium channels that support HL‑1 cell hypertrophy Katharina Stroedecke1,2, Sandra Meinel1,2, Fritz Markwardt1, Udo Kloeckner1, Nicole Straetz1, Katja Quarch1, Barbara Schreier1, Michael Kopf1, Michael Gekle1 & Claudia Grossmann1* The EGF receptor (EGFR) has been extensively studied in tumor biology and recently a role in cardiovascular pathophysiology was suggested. The mineralocorticoid receptor (MR) is an important efector of the renin–angiotensin–aldosterone‑system and elicits pathophysiological efects in the cardiovascular system; however, the underlying molecular mechanisms are unclear. Our aim was to investigate the importance of EGFR for MR‑mediated cardiovascular pathophysiology because MR is known to induce EGFR expression. We identifed a SNP within the EGFR promoter that modulates MR‑induced EGFR expression. In RNA‑sequencing and qPCR experiments in heart tissue of EGFR KO and WT mice, changes in EGFR abundance led to diferential expression of cardiac ion channels, especially of the T‑type calcium channel CACNA1H. Accordingly, CACNA1H expression was increased in WT mice after in vivo MR activation by aldosterone but not in respective EGFR KO mice. Aldosterone‑ and EGF‑responsiveness of CACNA1H expression was confrmed in HL‑1 cells by Western blot and by measuring peak current density of T‑type calcium channels. Aldosterone‑induced CACNA1H protein expression could be abrogated by the EGFR inhibitor AG1478. Furthermore, inhibition of T‑type calcium channels with mibefradil or ML218 reduced diameter, volume and BNP levels in HL‑1 cells. In conclusion the MR regulates EGFR and CACNA1H expression, which has an efect on HL‑1 cell diameter, and the extent of this regulation seems to depend on the SNP‑216 (G/T) genotype. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. -
Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation -
Cdk15 Igfals Lingo4 Gjb3 Tpbg Lrrc38 Serpinf1 Apod Trp73 Lama4 Chrnd Col9a1col11a1col5a2 Fgl2 Pitx2 Col2a1 Col3a1 Lamb3 Col24a1
Bnc2 Wdr72 Ptchd1 Abtb2 Spag5 Zfp385a Trim17 Ier2 Il1rapl1 Tpd52l1 Fam20a Car8 Syt5 Plxnc1 Sema3e Ndrg4 Snph St6galnac5 Mcpt2 B3galt2 Sphkap Arhgap24 Prss34 Lhfpl2 Ermap Rnf165 Shroom1 Grm4 Mobp Dock2 Tmem9b Slc35d3 Otud7b Serpinb3a Sh3d19 Syt6 Zan Trim67 Clec18a Mcoln1 Tob1 Slc45a2 Pcdhb9 Pcdh17 Plscr1 Gpr143 Cela1 Frem1 Sema3f Lgi2 Igsf9 Fjx1 Cpne4 Adgb Depdc7 Gzmm C1qtnf5 Capn11 Sema3c H2-T22 Unc5c Sytl4 Galnt5 Sytl2 Arhgap11a Pcdha1 Cdh20 Slc35f2 Trim29 B3gnt5 Dock5 Trim9 Padi4 Pcdh19 Abi2 Cldn11 Slitrk1 Fam13a Nrgn Cpa4 Clmp Il1rap Trpm1 Fat4 Nexn Pmel Mmp15 Fat3 H2-M5 Prss38 Wdr41 Prtg Mlana Mettl22 Tnrc6b Cdh6 Sema3b Ptgfrn Cldn1 Cntn4 Bcl2a1b Capn6 Capn5 Pcdhb19 Tcf15 Bmf Rgs8 Tecrl Tyrp1 Rhot1 Rnf123 Cldn6 Adam9 Hlx Rilpl1 Disp1 Atcay Vwc2 Fat2 Srpx2 Cldn3 Unc13c Creb3l1 Rab39b Robo3 Gpnmb Bves Orai2 Slc22a2 Prss8 Cdh10 Scg3 Adam33 Nyx Dchs1 Chmp4c Syt9 Ap1m2 Megf10 Cthrc1 Penk Igsf9b Akap2 Ltbp3 Dnmbp Tff2 Pnoc Vldlr Cpa3 Snx18 Capn3 Btla Htr1b Gm17231 Pcdh9Rab27a Grm8 Cnih2 Scube2 Id2 Reep1 Cpeb3 Mmp16 Slc18b1 Snx33 Clcn5 Cckbr Pkp2 Drp2 Mapk8ip1 Lrrc3b Cxcl14 Zfhx3 Esrp1 Prx Dock3 Sec14l1 Prokr1 Pstpip2 Usp2 Cpvl Syn2 Ntn1 Ptger1 Rxfp3 Tyr Snap91 Htr1d Mtnr1a Gadd45g Mlph Drd4 Foxc2 Cldn4 Birc7 Cdh17 Twist2 Scnn1b Abcc4 Pkp1 Dlk2 Rab3b Amph Mreg Il33 Slit2 Hpse Micu1 Creb3l2 Dsp Lifr S1pr5 Krt15 Svep1 Ahnak Kcnh1 Sphk1 Vwce Clcf1 Ptch2 Pmp22 Sfrp1 Sema6a Lfng Hs3st5 Efcab1 Tlr5 Muc5acKalrn Vwa2 Fzd8 Lpar6 Bmp5 Slc16a9 Cacng4 Arvcf Igfbp2 Mrvi1 Dusp15 Krt5 Atp13a5 Dsg1a Kcnj14 Edn3Memo1 Ngef Prickle2 Cma1 Alx4 Bmp3 Blnk GastAgtr2 -
Implication of Potassium Channels in the Pathophysiology of Pulmonary Arterial Hypertension
biomolecules Review Implication of Potassium Channels in the Pathophysiology of Pulmonary Arterial Hypertension Hélène Le Ribeuz 1,2,3,Véronique Capuano 1,2,3, Barbara Girerd 1,2,3, Marc Humbert 1,2,3, 1,2,3, 1,2,3, , David Montani y and Fabrice Antigny * y 1 Faculté de Médecine, Université Paris-Saclay, 94270 Le Kremlin-Bicêtre, France; [email protected] (H.L.R.); [email protected] (V.C.); [email protected] (B.G.); [email protected] (M.H.); [email protected] (D.M.) 2 INSERM UMR_S 999, Hypertension pulmonaire, Physiopathologie et Innovation Thérapeutique, Hôpital Marie Lannelongue, 92350 Le Plessis-Robinson, France 3 Assistance Publique—Hôpitaux de Paris (AP-HP), Service de Pneumologie et Soins Intensifs Respiratoires, Centre de Référence de l’Hypertension Pulmonaire, Hôpital Bicêtre, 94270 Le Kremlin-Bicêtre, France * Correspondence: [email protected] or [email protected]; Tel.: +33-1-40-94-22-99 These authors contributed equally to the work. y Received: 30 June 2020; Accepted: 27 August 2020; Published: 1 September 2020 Abstract: Pulmonary arterial hypertension (PAH) is a rare and severe cardiopulmonary disease without curative treatments. PAH is a multifactorial disease that involves genetic predisposition, epigenetic factors, and environmental factors (drugs, toxins, viruses, hypoxia, and inflammation), which contribute to the initiation or development of irreversible remodeling of the pulmonary vessels. The recent identification of loss-of-function mutations in KCNK3 (KCNK3 or TASK-1) and ABCC8 (SUR1), or gain-of-function mutations in ABCC9 (SUR2), as well as polymorphisms in KCNA5 (Kv1.5), which encode two potassium (K+) channels and two K+ channel regulatory subunits, has revived the interest of ion channels in PAH. -
Identification of Key Genes and Pathways Involved in Response To
Deng et al. Biol Res (2018) 51:25 https://doi.org/10.1186/s40659-018-0174-7 Biological Research RESEARCH ARTICLE Open Access Identifcation of key genes and pathways involved in response to pain in goat and sheep by transcriptome sequencing Xiuling Deng1,2†, Dong Wang3†, Shenyuan Wang1, Haisheng Wang2 and Huanmin Zhou1* Abstract Purpose: This aim of this study was to investigate the key genes and pathways involved in the response to pain in goat and sheep by transcriptome sequencing. Methods: Chronic pain was induced with the injection of the complete Freund’s adjuvant (CFA) in sheep and goats. The animals were divided into four groups: CFA-treated sheep, control sheep, CFA-treated goat, and control goat groups (n 3 in each group). The dorsal root ganglions of these animals were isolated and used for the construction of a cDNA= library and transcriptome sequencing. Diferentially expressed genes (DEGs) were identifed in CFA-induced sheep and goats and gene ontology (GO) enrichment analysis was performed. Results: In total, 1748 and 2441 DEGs were identifed in CFA-treated goat and sheep, respectively. The DEGs identi- fed in CFA-treated goats, such as C-C motif chemokine ligand 27 (CCL27), glutamate receptor 2 (GRIA2), and sodium voltage-gated channel alpha subunit 3 (SCN3A), were mainly enriched in GO functions associated with N-methyl- D-aspartate (NMDA) receptor, infammatory response, and immune response. The DEGs identifed in CFA-treated sheep, such as gamma-aminobutyric acid (GABA)-related DEGs (gamma-aminobutyric acid type A receptor gamma 3 subunit [GABRG3], GABRB2, and GABRB1), SCN9A, and transient receptor potential cation channel subfamily V member 1 (TRPV1), were mainly enriched in GO functions related to neuroactive ligand-receptor interaction, NMDA receptor, and defense response. -
Ion Channels 3 1
r r r Cell Signalling Biology Michael J. Berridge Module 3 Ion Channels 3 1 Module 3 Ion Channels Synopsis Ion channels have two main signalling functions: either they can generate second messengers or they can function as effectors by responding to such messengers. Their role in signal generation is mainly centred on the Ca2 + signalling pathway, which has a large number of Ca2+ entry channels and internal Ca2+ release channels, both of which contribute to the generation of Ca2 + signals. Ion channels are also important effectors in that they mediate the action of different intracellular signalling pathways. There are a large number of K+ channels and many of these function in different + aspects of cell signalling. The voltage-dependent K (KV) channels regulate membrane potential and + excitability. The inward rectifier K (Kir) channel family has a number of important groups of channels + + such as the G protein-gated inward rectifier K (GIRK) channels and the ATP-sensitive K (KATP) + + channels. The two-pore domain K (K2P) channels are responsible for the large background K current. Some of the actions of Ca2 + are carried out by Ca2+-sensitive K+ channels and Ca2+-sensitive Cl − channels. The latter are members of a large group of chloride channels and transporters with multiple functions. There is a large family of ATP-binding cassette (ABC) transporters some of which have a signalling role in that they extrude signalling components from the cell. One of the ABC transporters is the cystic − − fibrosis transmembrane conductance regulator (CFTR) that conducts anions (Cl and HCO3 )and contributes to the osmotic gradient for the parallel flow of water in various transporting epithelia. -
Spatial Distribution of Leading Pacemaker Sites in the Normal, Intact Rat Sinoa
Supplementary Material Supplementary Figure 1: Spatial distribution of leading pacemaker sites in the normal, intact rat sinoatrial 5 nodes (SAN) plotted along a normalized y-axis between the superior vena cava (SVC) and inferior vena 6 cava (IVC) and a scaled x-axis in millimeters (n = 8). Colors correspond to treatment condition (black: 7 baseline, blue: 100 µM Acetylcholine (ACh), red: 500 nM Isoproterenol (ISO)). 1 Supplementary Figure 2: Spatial distribution of leading pacemaker sites before and after surgical 3 separation of the rat SAN (n = 5). Top: Intact SAN preparations with leading pacemaker sites plotted during 4 baseline conditions. Bottom: Surgically cut SAN preparations with leading pacemaker sites plotted during 5 baseline conditions (black) and exposure to pharmacological stimulation (blue: 100 µM ACh, red: 500 nM 6 ISO). 2 a &DUGLDFIoQChDQQHOV .FQM FOXVWHU &DFQDG &DFQDK *MD &DFQJ .FQLS .FQG .FQK .FQM &DFQDF &DFQE .FQM í $WSD .FQD .FQM í .FQN &DVT 5\U .FQM &DFQJ &DFQDG ,WSU 6FQD &DFQDG .FQQ &DFQDJ &DFQDG .FQD .FQT 6FQD 3OQ 6FQD +FQ *MD ,WSU 6FQE +FQ *MG .FQN .FQQ .FQN .FQD .FQE .FQQ +FQ &DFQDD &DFQE &DOP .FQM .FQD .FQN .FQG .FQN &DOP 6FQD .FQD 6FQE 6FQD 6FQD ,WSU +FQ 6FQD 5\U 6FQD 6FQE 6FQD .FQQ .FQH 6FQD &DFQE 6FQE .FQM FOXVWHU V6$1 L6$1 5$ /$ 3 b &DUGLDFReFHSWRUV $GUDF FOXVWHU $GUDD &DY &KUQE &KUP &KJD 0\O 3GHG &KUQD $GUE $GUDG &KUQE 5JV í 9LS $GUDE 7SP í 5JV 7QQF 3GHE 0\K $GUE *QDL $QN $GUDD $QN $QN &KUP $GUDE $NDS $WSE 5DPS &KUP 0\O &KUQD 6UF &KUQH $GUE &KUQD FOXVWHU V6$1 L6$1 5$ /$ 4 c 1HXURQDOPURWHLQV -
Ion Channels
UC Davis UC Davis Previously Published Works Title THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels. Permalink https://escholarship.org/uc/item/1442g5hg Journal British journal of pharmacology, 176 Suppl 1(S1) ISSN 0007-1188 Authors Alexander, Stephen PH Mathie, Alistair Peters, John A et al. Publication Date 2019-12-01 DOI 10.1111/bph.14749 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: Ion channels. British Journal of Pharmacology (2019) 176, S142–S228 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels Stephen PH Alexander1 , Alistair Mathie2 ,JohnAPeters3 , Emma L Veale2 , Jörg Striessnig4 , Eamonn Kelly5, Jane F Armstrong6 , Elena Faccenda6 ,SimonDHarding6 ,AdamJPawson6 , Joanna L Sharman6 , Christopher Southan6 , Jamie A Davies6 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 3Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 4Pharmacology and Toxicology, Institute of Pharmacy, University of Innsbruck, A-6020 Innsbruck, Austria 5School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 6Centre for Discovery Brain Science, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. -
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Supplemental Information Biological and Pharmaceutical Bulletin Promoter Methylation Profiles between Human Lung Adenocarcinoma Multidrug Resistant A549/Cisplatin (A549/DDP) Cells and Its Progenitor A549 Cells Ruiling Guo, Guoming Wu, Haidong Li, Pin Qian, Juan Han, Feng Pan, Wenbi Li, Jin Li, and Fuyun Ji © 2013 The Pharmaceutical Society of Japan Table S1. Gene categories involved in biological functions with hypomethylated promoter identified by MeDIP-ChIP analysis in lung adenocarcinoma MDR A549/DDP cells compared with its progenitor A549 cells Different biological Genes functions transcription factor MYOD1, CDX2, HMX1, THRB, ARNT2, ZNF639, HOXD13, RORA, FOXO3, HOXD10, CITED1, GATA1, activity HOXC6, ZGPAT, HOXC8, ATOH1, FLI1, GATA5, HOXC4, HOXC5, PHTF1, RARB, MYST2, RARG, SIX3, FOXN1, ZHX3, HMG20A, SIX4, NR0B1, SIX6, TRERF1, DDIT3, ASCL1, MSX1, HIF1A, BAZ1B, MLLT10, FOXG1, DPRX, SHOX, ST18, CCRN4L, TFE3, ZNF131, SOX5, TFEB, MYEF2, VENTX, MYBL2, SOX8, ARNT, VDR, DBX2, FOXQ1, MEIS3, HOXA6, LHX2, NKX2-1, TFDP3, LHX6, EWSR1, KLF5, SMAD7, MAFB, SMAD5, NEUROG1, NR4A1, NEUROG3, GSC2, EN2, ESX1, SMAD1, KLF15, ZSCAN1, VAV1, GAS7, USF2, MSL3, SHOX2, DLX2, ZNF215, HOXB2, LASS3, HOXB5, ETS2, LASS2, DLX5, TCF12, BACH2, ZNF18, TBX21, E2F8, PRRX1, ZNF154, CTCF, PAX3, PRRX2, CBFA2T2, FEV, FOS, BARX1, PCGF2, SOX15, NFIL3, RBPJL, FOSL1, ALX1, EGR3, SOX14, FOXJ1, ZNF92, OTX1, ESR1, ZNF142, FOSB, MIXL1, PURA, ZFP37, ZBTB25, ZNF135, HOXC13, KCNH8, ZNF483, IRX4, ZNF367, NFIX, NFYB, ZBTB16, TCF7L1, HIC1, TSC22D1, TSC22D2, REXO4, POU3F2, MYOG, NFATC2, ENO1,