Acute and Chronic Effects of Developmental Iron Deficiency On

Total Page:16

File Type:pdf, Size:1020Kb

Acute and Chronic Effects of Developmental Iron Deficiency On J Neural Transm (2006) [Suppl] 71: 173–196 # Springer-Verlag 2006 Acute and chronic effects of developmental iron deficiency on mRNA expression patterns in the brain S. L. Clardy1, X. Wang1, W. Zhao2,W.Liu2, G. A. Chase2, J. L. Beard3, B. True Felt4, J. R. Connor1 1 Department of Neurosurgery, M.S. Hershey Medical Center, Hershey, USA 2 Department of Health Evaluation Sciences, M.S. Hershey Medical Center, Hershey, USA 3 Department of Nutrition, Pennsylvania State University, College Park, USA 4 Department of Pediatrics and Communicable Diseases, University of Michigan, Ann Arbor, USA Summary Because of the multiple biochemical pathways that require iron, behavior and physiological responsiveness (Weinberg et al., iron deficiency can impact brain metabolism in many ways. The goal of this 1979). Decreased motor activity and reversed circadi- study was to identify a molecular footprint associated with ongoing versus long term consequences of iron deficiency using microarray analysis. Rats an rhythms of thermoregulation and motor activity were were born to iron-deficient mothers, and were analyzed at two different found in another study of rats that were iron-deprived for ages: 21 days, while weaning and iron-deficient; and six months, after a five 28 days postnatally, indicating the major role iron plays in month iron-sufficient recovery period. Overall, the data indicate that on- going iron deficiency impacts multiple pathways, whereas the long term the normal function of the dopaminergic system in the consequences of iron deficiency on gene expression are more limited. These brain (Youdim et al., 1981). More recent animal studies data suggest that the gene array profiles obtained at postnatal day 21 reflect have distinguished differences between pre- and post-natal a brain under development in a metabolically compromised setting that given appropriate intervention is mostly correctable. There are, however, recovery from iron deficiency. If the iron deficiency occurs long term consequences to the developmental iron deficiency that could during neonatal and post-weaning periods, and an iron suf- underlie the neurological deficits reported for iron deficiency. ficient diet is given two-to four weeks postnatally, recovery occurs upon iron repletion (Chen et al., 1995; Erikson et al., Introduction 1997; Pinero et al., 2000), but the effects of iron deficiency in utero appear irreversible, even after iron repletion Insufficient amounts of body iron affect up to one billion (Felt and Lozoff, 1996; Kwik-Uribe, Gietzen et al., 2000; people worldwide (Andrews, 2000). Iron is especially cru- Kwik-Uribe et al., 2000). cial during development, as it is required for proper In humans, a study of second grade children who were myelination, and is also a cofactor for enzymes in neuro- anemic in infancy revealed that the learning achievement transmitter synthesis (Larkin, 1990; Beard and Connor, score and the positive task orientation was significantly 2003; Beard et al., 2003). Studies in animals dating back lower in the anemic group than in the non-anemic control over three decades have documented the damage resulting group. Data were controlled for maternal education and sex from iron deficiency. Dallman et al. demonstrated that even of child (Palti et al., 1985). A more recent study by Lozoff after iron-deficient rats were returned to a normal iron et al. found that children who had iron deficiency in infancy diet for several days, non-heme iron remained depressed, scored lower on tests of mental and motor functioning as did ferritin in brain (Dallman et al., 1975). Weinberg as teens (greater than ten years later) than those infants et al. also noted that rats exposed to iron deficiency for who were not iron-deficient as infants. Additionally, more the first 28 days of life never recovered, exhibiting a per- of the previously iron-deficient infants had repeated a grade, sistent deficit in brain non-heme iron, as well as changes in had been referred for special services, and=or was the ob- ject of parental and teacher concern regarding anxiety, de- pression, social difficulties, or attention problems (Lozoff Correspondence: J. R. Connor, 500 University Drive, Department of Neurosurgery, H110, Hershey, PA 17033, USA et al., 2000). A study of iron deficiency anemia in young e-mail: [email protected] South African anemic mothers of full-term infants found 174 S. L. Clardy et al. that the infants of anemic mothers were developmentally RNA preparation and microarray analysis delayed at 10 weeks. At nine months, despite normalization Frozen brain tissue was homogenized and extracted with TRIzol reagent of iron status in some mothers, the developmental delays (Gibco BRL Life Technologies, Baltimore, MD, USA) and further purified with the Qiagen RNeasy kit (Qiagen, Valencia, CA) utilizing the clean-up were not diminished in the infants. The iron deficiency also step according to the manufacturer’s instructions. RNA quality was evalu- affected the mothers, and even nine months post-partum, ated by A260=A280 ratio. Randomly selected samples were further ana- anemic mothers were more negative, less engaged, and less lyzed for RNA integrity using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA); all samples analyzed demonstrated responsive toward their babies than were control mothers. acceptable quality. Synthesis of double-stranded DNA and biotinylated Mothers treated for iron deficiency exhibited behaviors cRNA from total RNA, and its subsequent hybridization to the chips, were similar to controls (Perez et al., 2005). A study of South performed according to Affymetrix (Santa Clara, CA) recommendations. African women by Beard et al. (2005) found that iron Streptavidin-phycoerythrin staining of arrays after hybridization also fol- lowed Affymetrix recommendations. Biotin-labeled and fragmented RNA treatment of anemic mothers up to nine months postpartum was hybridized to Rat Genome U34A Gene Chips containing approximately resulted in 25% improvement of depression, stress, and 7000 full-length sequences and 1000 expressed sequence tag (EST) clusters. cognitive function, further suggesting the importance of The microarrays were scanned by the Affymetrix gene array system (http:==www.affymetrix.com). Preliminary data analyses were performed maternal iron status on infant development (Beard et al., with the Affymetrix GCOS software package and the Affymetrix Data 2005). These studies highlight the need to study iron defi- Mining Tool. ciency over time, from infancy onward, and hint at the differences between ID at different stages in life (birth, Real-time PCR infancy, and motherhood). Total RNA was prepared for qualitative real-time PCR using Invitrogen’s It is now accepted that dietary iron deficiency lowers SuperScript(tm) III First-Strand Synthesis System for RT-PCR (Invitrogen brain iron and interferes with protein synthesis in the brain Corporation, Carlsbad, CA). PCR was performed using TaqMan detection probe and primers either purchased from inventory or designed with the (Beard and Connor, 2003). There is, however, a notable online software Custom TaqMan+ Gene Expression Assay File Builder lack of research into the effects of such early iron defi- (Applied Biosystems, Foster City, CA). Real-time PCR amplification of ciency in later, adult life. In these studies, we obtained a cDNA was performed using TaqMan Universal PCR Master Mix (Applied gene expression profile of rat brain to identify the molecu- Biosystems). Values were normalized to those obtained for ribosomal 18s mRNA. lar footprint of the iron-deficient brain. This information may point to the specific pathways causing the underlying Statistical analysis pathophysiology of both acute iron deficiency and its long- term, chronic effects. A benefit of microarrays in the analy- Before testing significant changes in gene expression, expression signals were normalized by using the R-Affy package from Bioconductor (version sis of iron-deficient brain is the ability to investigate global 1.2, Irizarry et al., 2003) to remove background noise and non-biological gene changes without the bias of a priori hypotheses. We variations among arrays. The background noise was removed from the PM also wanted to examine as broad a range of systems as pos- (perfect match) probe intensities using the ‘‘RMA’’ method (Irizarry, 2003), which assumes a global model for the distribution of probe intensities and sible in this first pass analysis in the iron-deficient brains, models the PM probe intensities as the sum of a normal noise component and and thus we tested the entire brain in our analysis to gain an an exponential signal component. Normalization was performed according understanding of the most dramatic and global changes to the quantile normalization method (Bolstad, 2003). Quantile normal- caused by iron deficiency. ization assumes that the expression of majority of genes on the arrays does not change in different treatments, and that the distribution of probe intensities for each array in the dataset is the same. For each probe set, the logs of the background corrected, normalized PM intensities were fitted Methods and materials with an additive multi-chip linear model, which had a chip-wise abundance term and a probe-wise affinity term. The robust median polish procedure was utilized for fitting (Tukey, 1977). Estimates were reported on the log2 Animal characteristics scale. Because approximately thirty percent of the probes were found with The studies reported here were performed in compliance with the animal MM (mismatch)
Recommended publications
  • Supplementary Data
    Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2).
    [Show full text]
  • Association Analyses of Known Genetic Variants with Gene
    ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac.
    [Show full text]
  • Table 2. Significant
    Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S.
    [Show full text]
  • Microrna Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms Behind Variable Drug Disposition and Strategy to Develop More Effective Therapy
    1521-009X/44/3/308–319$25.00 http://dx.doi.org/10.1124/dmd.115.067470 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 44:308–319, March 2016 Copyright ª 2016 by The American Society for Pharmacology and Experimental Therapeutics Minireview MicroRNA Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms behind Variable Drug Disposition and Strategy to Develop More Effective Therapy Ai-Ming Yu, Ye Tian, Mei-Juan Tu, Pui Yan Ho, and Joseph L. Jilek Department of Biochemistry & Molecular Medicine, University of California Davis School of Medicine, Sacramento, California Received September 30, 2015; accepted November 12, 2015 Downloaded from ABSTRACT Knowledge of drug absorption, distribution, metabolism, and excre- we review the advances in miRNA pharmacoepigenetics including tion (ADME) or pharmacokinetics properties is essential for drug the mechanistic actions of miRNAs in the modulation of Phase I and development and safe use of medicine. Varied or altered ADME may II drug-metabolizing enzymes, efflux and uptake transporters, and lead to a loss of efficacy or adverse drug effects. Understanding the xenobiotic receptors or transcription factors after briefly introducing causes of variations in drug disposition and response has proven the characteristics of miRNA-mediated posttranscriptional gene dmd.aspetjournals.org critical for the practice of personalized or precision medicine. The regulation. Consequently, miRNAs may have significant influence rise of noncoding microRNA (miRNA) pharmacoepigenetics and on drug disposition and response. Therefore, research on miRNA pharmacoepigenomics has come with accumulating evidence sup- pharmacoepigenetics shall not only improve mechanistic under- porting the role of miRNAs in the modulation of ADME gene standing of variations in pharmacotherapy but also provide novel expression and then drug disposition and response.
    [Show full text]
  • Cellular and Molecular Signatures in the Disease Tissue of Early
    Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of
    [Show full text]
  • Teaching an Old Dog New Tricks: Reactivated Developmental Signaling Pathways Regulate ABCB1 and Chemoresistance in Cancer
    Lee et al. Cancer Drug Resist 2021;4:424-52 Cancer DOI: 10.20517/cdr.2020.114 Drug Resistance Review Open Access Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer Wing-Kee Lee, Frank Thévenod Institute for Physiology, Pathophysiology and Toxicology, ZBAF, Witten/Herdecke University, Witten 58453, Germany. Correspondence to: Prof. Wing-Kee Lee, Institute for Physiology, Pathophysiology and Toxicology, Witten/Herdecke University, Stockumer Strasse 12, Witten 58453, Germany. E-mail: [email protected] How to cite this article: Lee WK, Thévenod F. Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer. Cancer Drug Resist 2021;4:424-52. http://dx.doi.org/10.20517/cdr.2020.114 Received: 11 Dec 2020 First Decision: 27 Jan 2021 Revised: 6 Feb 2021 Accepted: 20 Feb 2021 Available online: 19 Jun 2021 Academic Editor: Godefridus J. Peters Copy Editor: Yue-Yue Zhang Production Editor: Yue-Yue Zhang Abstract Oncogenic multidrug resistance (MDR) is a multifactorial phenotype intimately linked to deregulated expression of detoxification transporters. Drug efflux transporters, particularly the MDR P-glycoprotein ABCB1, represent a central mechanism by which not only chemotherapeutic drugs are extruded or sequestered to prevent drug delivery to their intracellular targets, but also for inhibiting apoptotic cell death cues, such as removal of proapoptotic signals. Several cell populations exhibiting the MDR phenotype co-exist within a tumor, such as cells forming the bulk tumor cell mass, cancer stem cells, and cancer persister cells. The key to regulation of ABCB1 expression is the cellular transcriptional machinery.
    [Show full text]
  • Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
    Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002)
    [Show full text]
  • High-Throughput Screening Studies of Inhibition of Human Carbonic Anhydrase II and Bacterial Flagella Antimicrobial Activity
    Western Michigan University ScholarWorks at WMU Dissertations Graduate College 5-2010 High-Throughput Screening Studies of Inhibition of Human Carbonic Anhydrase II and Bacterial Flagella Antimicrobial Activity Albert A. Barrese III Western Michigan University Follow this and additional works at: https://scholarworks.wmich.edu/dissertations Part of the Biochemistry, Biophysics, and Structural Biology Commons, and the Biology Commons Recommended Citation Barrese, Albert A. III, "High-Throughput Screening Studies of Inhibition of Human Carbonic Anhydrase II and Bacterial Flagella Antimicrobial Activity" (2010). Dissertations. 500. https://scholarworks.wmich.edu/dissertations/500 This Dissertation-Open Access is brought to you for free and open access by the Graduate College at ScholarWorks at WMU. It has been accepted for inclusion in Dissertations by an authorized administrator of ScholarWorks at WMU. For more information, please contact [email protected]. HIGH-THROUGHPUT SCREENING STUDIES OF INHIBITION OF HUMAN CARBONIC ANHYDRASE II AND BACTERIAL FLAGELLA ANTIMICROBIAL ACTIVITY by Albert A. Barrese III A Dissertation Submitted to the Faculty of The Graduate College in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Department of Biological Sciences Advisor: Brian C. Tripp, Ph.D. Western Michigan University Kalamazoo, Michigan May 2010 UMI Number: 3410393 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMT Dissertation Publishing UMI 3410393 Copyright 2010 by ProQuest LLC.
    [Show full text]
  • Quantigene Flowrna Probe Sets Currently Available
    QuantiGene FlowRNA Probe Sets Currently Available Accession No. Species Symbol Gene Name Catalog No. NM_003452 Human ZNF189 zinc finger protein 189 VA1-10009 NM_000057 Human BLM Bloom syndrome VA1-10010 NM_005269 Human GLI glioma-associated oncogene homolog (zinc finger protein) VA1-10011 NM_002614 Human PDZK1 PDZ domain containing 1 VA1-10015 NM_003225 Human TFF1 Trefoil factor 1 (breast cancer, estrogen-inducible sequence expressed in) VA1-10016 NM_002276 Human KRT19 keratin 19 VA1-10022 NM_002659 Human PLAUR plasminogen activator, urokinase receptor VA1-10025 NM_017669 Human ERCC6L excision repair cross-complementing rodent repair deficiency, complementation group 6-like VA1-10029 NM_017699 Human SIDT1 SID1 transmembrane family, member 1 VA1-10032 NM_000077 Human CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) VA1-10040 NM_003150 Human STAT3 signal transducer and activator of transcripton 3 (acute-phase response factor) VA1-10046 NM_004707 Human ATG12 ATG12 autophagy related 12 homolog (S. cerevisiae) VA1-10047 NM_000737 Human CGB chorionic gonadotropin, beta polypeptide VA1-10048 NM_001017420 Human ESCO2 establishment of cohesion 1 homolog 2 (S. cerevisiae) VA1-10050 NM_197978 Human HEMGN hemogen VA1-10051 NM_001738 Human CA1 Carbonic anhydrase I VA1-10052 NM_000184 Human HBG2 Hemoglobin, gamma G VA1-10053 NM_005330 Human HBE1 Hemoglobin, epsilon 1 VA1-10054 NR_003367 Human PVT1 Pvt1 oncogene homolog (mouse) VA1-10061 NM_000454 Human SOD1 Superoxide dismutase 1, soluble (amyotrophic lateral sclerosis 1 (adult))
    [Show full text]
  • 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
    [Show full text]
  • Molecular Pharmacology of Cancer Therapy in Human Colorectal Cancer by Gene Expression Profiling1,2
    [CANCER RESEARCH 63, 6855–6863, October 15, 2003] Molecular Pharmacology of Cancer Therapy in Human Colorectal Cancer by Gene Expression Profiling1,2 Paul A. Clarke,3 Mark L. George, Sandra Easdale, David Cunningham, R. Ian Swift, Mark E. Hill, Diana M. Tait, and Paul Workman Cancer Research UK Centre for Cancer Therapeutics, Institute of Cancer Research, Sutton, Surrey SM2 5NG [P. A. C., M. L. G., S. E., P. W.]; Department of Gastrointestinal Oncology, Royal Marsden Hospital, Sutton, Surrey [D. C., M. E. H., D. M. T.]; and Department of Surgery, Mayday Hospital, Croydon, Surrey [M. L. G., R. I. S.], United Kingdom ABSTRACT ment with a single dose of MMC4 and during a continuous infusion of 5FU. In this study, we report for the first time gene expression Global gene expression profiling has potential for elucidating the com- profiling in cancer patients before, and critically, during the period of plex cellular effects and mechanisms of action of novel targeted anticancer exposure to chemotherapy. We have demonstrated that the approach agents or existing chemotherapeutics for which the precise molecular is feasible, and we have detected a novel molecular response that mechanism of action may be unclear. In this study, decreased expression would not have been predicted from in vitro studies and that would of genes required for RNA and protein synthesis, and for metabolism were have otherwise been missed by conventional approaches. The results detected in rectal cancer biopsies taken from patients during a 5-fluorou- also suggest a possible new therapeutic approach. Overall our obser- racil infusion. Our observations demonstrate that this approach is feasible and can detect responses that may have otherwise been missed by con- vations suggest that gene expression profiling in response to treatment ventional methods.
    [Show full text]
  • An Update on the Metabolic Roles of Carbonic Anhydrases in the Model Alga Chlamydomonas Reinhardtii
    H OH metabolites OH Review An Update on the Metabolic Roles of Carbonic Anhydrases in the Model Alga Chlamydomonas reinhardtii Ashok Aspatwar 1,* ID , Susanna Haapanen 1 and Seppo Parkkila 1,2 1 Faculty of Medicine and Life Sciences, University of Tampere, FI-33014 Tampere, Finland; [email protected].fi (S.H.); [email protected].fi (S.P.) 2 Fimlab, Ltd., and Tampere University Hospital, FI-33520 Tampere, Finland * Correspondence: [email protected].fi; Tel.: +358-46-596-2117 Received: 11 January 2018; Accepted: 10 March 2018; Published: 13 March 2018 Abstract: Carbonic anhydrases (CAs) are metalloenzymes that are omnipresent in nature. − + CAs catalyze the basic reaction of the reversible hydration of CO2 to HCO3 and H in all living organisms. Photosynthetic organisms contain six evolutionarily different classes of CAs, which are namely: α-CAs, β-CAs, γ-CAs, δ-CAs, ζ-CAs, and θ-CAs. Many of the photosynthetic organisms contain multiple isoforms of each CA family. The model alga Chlamydomonas reinhardtii contains 15 CAs belonging to three different CA gene families. Of these 15 CAs, three belong to the α-CA gene family; nine belong to the β-CA gene family; and three belong to the γ-CA gene family. The multiple copies of the CAs in each gene family may be due to gene duplications within the particular CA gene family. The CAs of Chlamydomonas reinhardtii are localized in different subcellular compartments of this unicellular alga. The presence of a large number of CAs and their diverse subcellular localization within a single cell suggests the importance of these enzymes in the metabolic and biochemical roles they perform in this unicellular alga.
    [Show full text]