Expression of Regulator of G Protei
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RGS12 Is a Novel Tumor-Suppressor Gene in African American Prostate
Published OnlineFirst June 13, 2017; DOI: 10.1158/0008-5472.CAN-17-0669 Cancer Molecular and Cellular Pathobiology Research RGS12 Is a Novel Tumor-Suppressor Gene in African American Prostate Cancer That Represses AKT and MNX1 Expression Yongquan Wang1,2, Jianghua Wang2, Li Zhang2,3, Omer Faruk Karatas2, Longjiang Shao2, Yiqun Zhang4, Patricia Castro2, Chad J. Creighton4,5,and Michael Ittmann2 Abstract African American (AA) men exhibit a relatively high incidence epithelial cells. Notably, RGS12 exhibited potent tumor-suppres- and mortality due to prostate cancer even after adjustment for sor activity in prostate cancer and prostate epithelial cell lines in socioeconomic factors, but the biological basis for this disparity is vitro and in vivo. We found that RGS12 expression correlated unclear. Here, we identify a novel region on chromosome 4p16.3 negatively with the oncogene MNX1 and regulated its expression that is lost selectively in AA prostate cancer. The negative regulator in vitro and in vivo. Further, MNX1 was regulated by AKT activity, of G-protein signaling RGS12 was defined as the target of 4p16.3 and RGS12 expression decreased total and activated AKT levels. deletions, although it has not been implicated previously as a Our findings identify RGS12 as a candidate tumor-suppressor tumor-suppressor gene. RGS12 transcript levels were relatively gene in AA prostate cancer, which acts by decreasing expression of reduced in AA prostate cancer, and prostate cancer cell lines AKT and MNX1, establishing a novel oncogenic axis in this showed decreased RGS12 expression relative to benign prostate disparate disease setting. Cancer Res; 77(16); 1–11. -
Supplemental Material
Supplemental Table B ARGs in alphabetical order Symbol Title 3 months 6 months 9 months 12 months 23 months ANOVA Direction Category 38597 septin 2 1557 ± 44 1555 ± 44 1579 ± 56 1655 ± 26 1691 ± 31 0.05219 up Intermediate 0610031j06rik kidney predominant protein NCU-G1 491 ± 6 504 ± 14 503 ± 11 527 ± 13 534 ± 12 0.04747 up Early Adult 1G5 vesicle-associated calmodulin-binding protein 662 ± 23 675 ± 17 629 ± 16 617 ± 20 583 ± 26 0.03129 down Intermediate A2m alpha-2-macroglobulin 262 ± 7 272 ± 8 244 ± 6 290 ± 7 353 ± 16 0.00000 up Midlife Aadat aminoadipate aminotransferase (synonym Kat2) 180 ± 5 201 ± 12 223 ± 7 244 ± 14 275 ± 7 0.00000 up Early Adult Abca2 ATP-binding cassette, sub-family A (ABC1), member 2 958 ± 28 1052 ± 58 1086 ± 36 1071 ± 44 1141 ± 41 0.05371 up Early Adult Abcb1a ATP-binding cassette, sub-family B (MDR/TAP), member 1A 136 ± 8 147 ± 6 147 ± 13 155 ± 9 185 ± 13 0.01272 up Midlife Acadl acetyl-Coenzyme A dehydrogenase, long-chain 423 ± 7 456 ± 11 478 ± 14 486 ± 13 512 ± 11 0.00003 up Early Adult Acadvl acyl-Coenzyme A dehydrogenase, very long chain 426 ± 14 414 ± 10 404 ± 13 411 ± 15 461 ± 10 0.01017 up Late Accn1 amiloride-sensitive cation channel 1, neuronal (degenerin) 242 ± 10 250 ± 9 237 ± 11 247 ± 14 212 ± 8 0.04972 down Late Actb actin, beta 12965 ± 310 13382 ± 170 13145 ± 273 13739 ± 303 14187 ± 269 0.01195 up Midlife Acvrinp1 activin receptor interacting protein 1 304 ± 18 285 ± 21 274 ± 13 297 ± 21 341 ± 14 0.03610 up Late Adk adenosine kinase 1828 ± 43 1920 ± 38 1922 ± 22 2048 ± 30 1949 ± 44 0.00797 up Early -
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. -
Predicting Coupling Probabilities of G-Protein Coupled Receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J
Published online 30 May 2019 Nucleic Acids Research, 2019, Vol. 47, Web Server issue W395–W401 doi: 10.1093/nar/gkz392 PRECOG: PREdicting COupling probabilities of G-protein coupled receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J. Silvio Gutkind4, Robert B. Russell1,2,* and Francesco Raimondi1,2,* 1CellNetworks, Bioquant, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, 2Biochemie Zentrum Heidelberg (BZH), Heidelberg University, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany, 3Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan and 4Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA Received February 10, 2019; Revised April 13, 2019; Editorial Decision April 24, 2019; Accepted May 01, 2019 ABSTRACT great use in tinkering with signalling pathways in living sys- tems (5). G-protein coupled receptors (GPCRs) control multi- Ligand binding to GPCRs induces conformational ple physiological states by transducing a multitude changes that lead to binding and activation of G-proteins of extracellular stimuli into the cell via coupling to situated on the inner cell membrane. Most of mammalian intra-cellular heterotrimeric G-proteins. Deciphering GPCRs couple with more than one G-protein giving each which G-proteins couple to each of the hundreds receptor a distinct coupling profile (6) and thus specific of GPCRs present in a typical eukaryotic organism downstream cellular responses. Determining these coupling is therefore critical to understand signalling. Here, profiles is critical to understand GPCR biology and phar- we present PRECOG (precog.russelllab.org): a web- macology. Despite decades of research and hundreds of ob- server for predicting GPCR coupling, which allows served interactions, coupling information is still missing for users to: (i) predict coupling probabilities for GPCRs many receptors and sequence determinants of coupling- specificity are still largely unknown. -
Quantification of Cardiovascular Disease Biomarkers in Human
proteomes Article Quantification of Cardiovascular Disease Biomarkers in Human Platelets by Targeted Mass Spectrometry Sebastian Malchow ID , Christina Loosse, Albert Sickmann and Christin Lorenz * Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44139 Dortmund, Germany; [email protected] (S.M.); [email protected] (C.L.); [email protected] (A.S.) * Correspondence: [email protected]; Tel.: +49-231-1392-289 Received: 3 October 2017; Accepted: 13 November 2017; Published: 15 November 2017 Abstract: Platelets are known to be key players in thrombosis and hemostasis, contributing to the genesis and progression of cardiovascular diseases. Due to their pivotal role in human physiology and pathology, platelet function is regulated tightly by numerous factors which have either stimulatory or inhibitory effects. A variety of factors, e.g., collagen, fibrinogen, ADP, vWF, thrombin, and thromboxane promote platelet adhesion and aggregation by utilizing multiple intracellular signal cascades. To quantify platelet proteins for this work, a targeted proteomics workflow was applied. In detail, platelets are isolated and lyzed, followed by a tryptic protein digest. Subsequently, a mix of stable isotope-labeled peptides of interesting biomarker proteins in concentrations ranging from 0.1 to 100 fmol is added to 3 µg digest. These peptides are used as an internal calibration curve to accurately quantify endogenous peptides and corresponding proteins in a pooled platelet reference sample by nanoLC-MS/MS with parallel reaction monitoring. In order to assure a valid quantification, limit of detection (LOD) and limit of quantification (LOQ), as well as linear range, were determined. This quantification of platelet activation and proteins by targeted mass spectrometry may enable novel diagnostic strategies in the detection and prevention of cardiovascular diseases. -
Genomic Instability and DNA Ploidy Are Linked to DNA Copy Number Aberrations of 8P23 and 22Q11.23 in Gastric Cancers
333-339.qxd 15/7/2010 11:08 Ì ™ÂÏ›‰·333 INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 26: 333-339, 2010 333 Genomic instability and DNA ploidy are linked to DNA copy number aberrations of 8p23 and 22q11.23 in gastric cancers SHIGETO KAWAUCHI1, TOMOKO FURUAY1, TETSUJI UCHIYAMA2, ATSUSHI ADACHI2, TAKAE OKADA1 MOTONAO NAKAO1, ATSUNORI OGA1, KENICHIRO UCHIDA1 and KOHSUKE SASAKI1 1Department of Pathology, Yamaguchi University Graduate School of Medicine, Ube 755-8505; 2Department of Surgery, Iwakuni Medical Center, Iwakuni 740-0021, Japan Received April 8, 2010; Accepted June 2, 2010 DOI: 10.3892/ijmm_00000470 Abstract. The close relationship between chromosomal Introduction instability (CIN) and aneuploidy has been reported. The purpose of this study was to identify genomic aberrations Cancer progression is accompanied by the accumulation of present with CIN and aneuploidy in gastric cancers. FISH genetic alterations in the genes controlling cell proliferation and image cytometry were applied to 27 sporadic gastric and death. Indeed, some genomic abnormalities, ranging adenocarcinomas to identify CIN-positive tumors and to from point mutations to chromosomal aberrations, are determine DNA ploidy, respectively. In addition, array-based detected in virtually all cancers, including gastric cancers. comparative genomic hybridization was used to identify Although the biological characteristics of cancers greatly bacterial artificial chromosome clones that displayed vary from case to case, they are primarily affected by genomic differences in the frequency of copy number aberrations alterations. In general, cancer cells inherently take on genomic between CIN-positive and CIN-negative tumors, and instability that is conceptually divided into microsatellite between aneuploid and diploid tumors. There were many instability (MIN) and chromosomal instability (CIN) (1,2). -
Characterizing the Mechanisms of Kappa Opioid Receptor Signaling Within Mesolimbic Dopamine Circuitry Katie Reichard a Dissertat
Characterizing the mechanisms of kappa opioid receptor signaling within mesolimbic dopamine circuitry Katie Reichard A dissertation submitted in partial fulfillment of the degree requirements for the degree of: Doctor of Philosophy University of Washington 2020 Reading Committee: Charles Chavkin, Chair Paul Phillips Larry Zweifel Program Authorized to Confer Degree: Neuroscience Graduate Program TABLE OF CONTENTS Summary/Abstract………………………………………………………………………….……..6 Dedication……………………………………………………………………………….………...9 Chapter 1 The therapeutic potential of the targeting the kappa opioid receptor system in stress- associated mental health disorders……………………………….………………………………10 Section 1.1 Activation of the dynorphin/kappa opioid receptor system is associated with dysphoria, cognitive disruption, and increased preference for drugs of abuse…………………..13 Section 1.2 Contribution of the dyn/KOR system to substance use disorder, anxiety, and depression………………………………………………………………………………………..15 Section 1.3 KORs are expressed on dorsal raphe serotonin neurons and contribute to stress- induced plasticity with serotonin circuitry……………………………………………………….17 Section 1.4 Kappa opioid receptor expression in the VTA contributes to the behavioral response to stress……………………………………………………………………………………....…..19 Section 1.5 Other brain regions contributing to the KOR-mediated response to stress…………23 Section 1.6 G Protein signaling at the KOR …………………………………………………….25 Chapter 2: JNK-Receptor Inactivation Affects D2 Receptor through both agonist action and norBNI-mediated cross-inactivation -
Cilia Gene Expression Patterns in Cancer MAX SHPAK 1,2 , MARCUS M
CANCER GENOMICS & PROTEOMICS 11 : 13-24 (2014) Cilia Gene Expression Patterns in Cancer MAX SHPAK 1,2 , MARCUS M. GOLDBERG 2 and MATTHEW C. COWPERTHWAITE 3 1NeuroTexas Institute, St. David’s Health Care, Austin, TX, U.S.A.; 2Center for Systems and Synthetic Biology, University of Texas, Austin, TX, U.S.A.; 3Texas Advanced Computing Center, Austin, TX, U.S.A. Abstra ct. Non-motile cilia are thought to be important Cilia are organelles present on the surface of the majority of determinants of the progression of many types of cancers. human cell types. There are two classes of cilia: motile and Our goal was to identify patterns of cilia gene dysregulation non-motile. Non-motile (primary) cilia are generally sensory in eight cancer types (glioblastoma multiforme, colon organelles that are involved in signal transduction, response adenocarcinoma, breast adenocarcinoma, kidney renal clear to chemicals in the external environment, and cellular growth cell carcinoma, lung squamous cell carcinoma, lung and differentiation (1). Cilia also play an important adenocarcinoma, rectal adenocarcinoma, and ovarian developmental role in tissue and organ patterning, including cancer) profiled by The Cancer Genome Atlas. Among these cell adhesion/communication in the brain and the heart. types, 2.5-19.8% of cilia-associated genes were significantly Unsurprisingly, primary cilia are associated with a number differentially expressed (versus 5.5-32.4% dysregulation of human diseases, or ciliopathies, such as polycystic kidney across all genes). In four canc er types (breast disease, Bardet–Biedel syndrome, and Meckel–Gruber adenocarcinoma, colon adenocarcinoma, glioblastoma syndrome (2). multiforme, and ovarian cancer), cilia genes were on Primary cilia have also been implicated in cancer, and average down-reg ulated (median fold change from –1.53- tumorigenesis in particular, as a consequence of the –0.3), in the other four types, cilia genes were up- involvement of primary cilia in cell-cycle regulation. -
GNAZ Rabbit Polyclonal Antibody – TA321431 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA321431 GNAZ Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: IHC, WB Recommended Dilution: ELISA: 1:1000-5000, WB: 1:500-2000, IHC: 1:25-100 Reactivity: Human, Mouse, Rat Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: Fusion protein corresponding to C terminal 250 amino acids of human guanine nucleotide binding protein (G protein), alpha z polypeptide Formulation: PBS pH7.3, 0.05% NaN3, 50% glycerol Concentration: lot specific Purification: Antigen affinity purification Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 41 kDa Gene Name: G protein subunit alpha z Database Link: NP_002064 Entrez Gene 14687 MouseEntrez Gene 25740 RatEntrez Gene 2781 Human P19086 Background: Guanine nucleotide-binding protein G(z) subunit alpha is a protein that in humans is encoded by the GNAZ gene. The protein encoded by this gene is a member of a G protein subfamily that mediates signal transduction in pertussis toxin-insensitive systms. This encoded protein may play a role in maintaining the ionic balance of perilymphatic and endolymphatic cochlear fluids. Synonyms: alpha z polypeptide; guanine nucleotide binding protein; guanine nucleotide binding protein (G protein); transducin alpha This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 GNAZ Rabbit Polyclonal Antibody – TA321431 Protein Families: Druggable Genome Protein Pathways: Long-term depression Product images: Predicted band size: 41 kDa. -
Supplementary Table 1. Pain and PTSS Associated Genes (N = 604
Supplementary Table 1. Pain and PTSS associated genes (n = 604) compiled from three established pain gene databases (PainNetworks,[61] Algynomics,[52] and PainGenes[42]) and one PTSS gene database (PTSDgene[88]). These genes were used in in silico analyses aimed at identifying miRNA that are predicted to preferentially target this list genes vs. a random set of genes (of the same length). ABCC4 ACE2 ACHE ACPP ACSL1 ADAM11 ADAMTS5 ADCY5 ADCYAP1 ADCYAP1R1 ADM ADORA2A ADORA2B ADRA1A ADRA1B ADRA1D ADRA2A ADRA2C ADRB1 ADRB2 ADRB3 ADRBK1 ADRBK2 AGTR2 ALOX12 ANO1 ANO3 APOE APP AQP1 AQP4 ARL5B ARRB1 ARRB2 ASIC1 ASIC2 ATF1 ATF3 ATF6B ATP1A1 ATP1B3 ATP2B1 ATP6V1A ATP6V1B2 ATP6V1G2 AVPR1A AVPR2 BACE1 BAMBI BDKRB2 BDNF BHLHE22 BTG2 CA8 CACNA1A CACNA1B CACNA1C CACNA1E CACNA1G CACNA1H CACNA2D1 CACNA2D2 CACNA2D3 CACNB3 CACNG2 CALB1 CALCRL CALM2 CAMK2A CAMK2B CAMK4 CAT CCK CCKAR CCKBR CCL2 CCL3 CCL4 CCR1 CCR7 CD274 CD38 CD4 CD40 CDH11 CDK5 CDK5R1 CDKN1A CHRM1 CHRM2 CHRM3 CHRM5 CHRNA5 CHRNA7 CHRNB2 CHRNB4 CHUK CLCN6 CLOCK CNGA3 CNR1 COL11A2 COL9A1 COMT COQ10A CPN1 CPS1 CREB1 CRH CRHBP CRHR1 CRHR2 CRIP2 CRYAA CSF2 CSF2RB CSK CSMD1 CSNK1A1 CSNK1E CTSB CTSS CX3CL1 CXCL5 CXCR3 CXCR4 CYBB CYP19A1 CYP2D6 CYP3A4 DAB1 DAO DBH DBI DICER1 DISC1 DLG2 DLG4 DPCR1 DPP4 DRD1 DRD2 DRD3 DRD4 DRGX DTNBP1 DUSP6 ECE2 EDN1 EDNRA EDNRB EFNB1 EFNB2 EGF EGFR EGR1 EGR3 ENPP2 EPB41L2 EPHB1 EPHB2 EPHB3 EPHB4 EPHB6 EPHX2 ERBB2 ERBB4 EREG ESR1 ESR2 ETV1 EZR F2R F2RL1 F2RL2 FAAH FAM19A4 FGF2 FKBP5 FLOT1 FMR1 FOS FOSB FOSL2 FOXN1 FRMPD4 FSTL1 FYN GABARAPL1 GABBR1 GABBR2 GABRA2 GABRA4 -
Novel Driver Strength Index Highlights Important Cancer Genes in TCGA Pancanatlas Patients
medRxiv preprint doi: https://doi.org/10.1101/2021.08.01.21261447; this version posted August 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Novel Driver Strength Index highlights important cancer genes in TCGA PanCanAtlas patients Aleksey V. Belikov*, Danila V. Otnyukov, Alexey D. Vyatkin and Sergey V. Leonov Laboratory of Innovative Medicine, School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Moscow Region, Russia *Corresponding author: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2021.08.01.21261447; this version posted August 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Abstract Elucidating crucial driver genes is paramount for understanding the cancer origins and mechanisms of progression, as well as selecting targets for molecular therapy. Cancer genes are usually ranked by the frequency of mutation, which, however, does not necessarily reflect their driver strength. Here we hypothesize that driver strength is higher for genes that are preferentially mutated in patients with few driver mutations overall, because these few mutations should be strong enough to initiate cancer. -
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