DOCSLIB.ORG

Supplementary Data

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Supplementary Data Figure S1. DDX3 expression is correlated with cell invasive activity and ATF4 expression. A, The protein lysates collected from confluent OECM1 and SAS cells were subjected to immunoblotting analysis; 3 batches of each line (upper panel) and the average intensity of DDX3/actin (lower panel) are shown. B, Cell growth (left panels) and Boydem chamber (up and right panels) assays of OECM1 cells transfected with indicated siRNAs. C, Boyden chamber assays of OECM1 cells transfected with the empty or FLAG-DDX3 expression vector. D, SAS and OECM1 cells were subjected to 3D invasion assay. Phase images were taken as indicated days after adding Matrigel. E, Representative images of primary tumors (tongue) and metastases (lymph node) in orthotopic OSCC models were taken by using the IVIS system. F, SAS/Luc2 cells isolated from lymph node (Meta) were cultured, and lysates from confluent parental (left lane) and meta SAS/Luc2 were subjected to immunoblotting analysis. G, SAS cells stably transfected with tetracycline-inducible shRNAs were treated with 2 µg/ml doxycyline for 5 days, and cell lysates were collected and subjected to immunoblotting analysis. H, SAS cells were incubated with AAV-shC or shD for 4 days, and cell lysates were collected and subjected to immunoblotting analysis. I, Tumor lysates from Fig. 2G were subjected to immunoblotting. Figure S2. Microarray-identified genes are enriched for pro-metastatic genes and ATF4 targets, and DDX3 is required for migration and ATF4 expression in all of the HNSCC cell lines examined. A, The log2 values of siD#1/siC obtained from two independent microarrays were plotted as a chart. Correlation coefficient (R) is labeled. B, Gene ontology analysis identified the top 10 biological processes that were enriched in downregulated or upregulated genes in DDX3 knockdown SAS cells according to p- value. C, Cellular functions and diseases that were negatively (–) or positively (+) affected by DDX3 knockdown, as predicted with Ingenuity Pathways Analysis. D, RT-qPCR analysis of known ATF4 target genes in siRNA-transfected OECM1 cells. E, Indicated cell lines were transfected with siC or siD#1 for 72 hours. The lysates were subjected to immunoblotting analysis. F, Indicated cell lines transfected as in panel E were subjected to Boyden chamber assays. Bar graph shows the relative migration efficiency (siD#1 vs. siC) of analyzed cell lines. Figure S3. DDX3 and ATF4 are required for EMT gene expression. A, shRNA vector- transfected SAS cells were subjected to the Boyden chamber (left) and 3D invasion (right) assays. Experiments were repeated three times to obtain mean ± SD. B, Immunoblotting of EMT-related proteins was analyzed in SAS cells transfected with indicated siRNA for 48 hours or shRNA for 72 hours. C, Immunfluorescence staining of E-cadherin and Vimentin in SAS cells transfected with control or 3 different DDX3 siRNAs for 48 hours. Figure S4. DDX3 does not regulate ATF4 protein stability. SAS cells transfected with siRNA for 48 hours were treated with MG132 for 4 hours and subsequently with cycloheximide for indicated time. Immunoblotting was performed using antibodies against indicated proteins. Figure S5. DDX3 regulate ATF4 translation independent of ER Stress. A, SAS cells transfected with siRNA for 48 hours and subsequently treated with Thapsigargin for 2 hours. Cell lysates were subjected to immunoblotting using antibodies against indicated proteins. B, In vivo translation assay was performed in SAS cells that were transfected with the ATF4-RL reporter and indicated vectors for 48 hours followed by Thapsigargin treatment for 6 hours. Bar graph shows relative luciferase activity as calculated in Figure 5; mean ± SD was obtained from 3 repeated experiments. Figure S6. The DDX3/CBC/eIF3 complex directly activates the translation of uORF-containing mRNAs in vitro and in vivo. A, In vitro transcribed mRNAs (RL or ATF4-RL) were each incubated with the SAS cell extract containing or not containing GST-DDX3 for 1 hour. The Renilla luciferase activity was subsequently measured. B, SAS cells were initially transfected with indicated shRNA-expressing vectors for 72 hours and then transfected with in vitro transcribed control (RL) or uORF-containing (ATF4, ATF5, DDIT3, CEBPA or ETV1) mRNA for 1 hour. The cell lysates were then collected for Renilla luciferase assay. C, Cells treated as in panel B were subjected to RT-qPCR analysis. Figure S7. RT-qPCR analysis of luciferase mRNAs in the in vivo translation assay. A-F, RT- qPCR analysis of Fig. 4D and F-J. G, Cell transfected with indicated reporters were subjected to RT-qPCR analysis. Figure S8. The CBC and eIF3 complexes are involved in the translation of uORF-containing mRNAs. A, The Venn diagrams shows unique or overlapped 5’ UTR CLIP tags among DDX3, eIF4A3 and CBP20 (left) and among DDX3, eIF4A3 and eIF3 (right). The numbers of DDX3-specific and eIF4A3-specific CLIP tags overlapping with CBP20 (left) or eIF3 (right) are labeled as blue and red, respectively. B, The Venn diagrams shows unique or overlapped 5’ UTR CLIP tags among DDX3, eIF3 and CBP20. The percentages of CLIP tags overlapping with uTIS and non-uTIS uTIS and non-uTIS containing genes retrieved from TISdb are labeled. C, RT-qPCR analysis of Fig. 5D. D, SAS cells transfected with indicated shRNA were subjected to immunoblotting. E, SAS cells transfected with indicated shRNA were subjected to immunoblotting. F, In vivo translation assay of indicated reporters cotransfected with indicated shRNAs for 48 hours. G, In vivo translation assay was performed in SAS cells that were initially transfected with the indicated shRNA vectors for 48 hours followed by the indicated overexpression vectors and the ATF4 reporter for further 24 hours. For panels E and F, relative luciferase activity was calculated as described in Figure 5. Supplementary Table S1. List of sense shRNA or siRNA sequences. shRNA/siRNA Sense sequence shC GCUUCUACCAAAUACACUUGA shD GAAACAUUGAGCUUACUCGUU shATF4 GAAAGCCUAGGUCUCUUAGAU shCBP20 GGAUGAGUAUCGGCAGGACUA shCBP80 GGUGCGACGAGAUUGGUAUGU sheIF3g GUGACAGAGUACAAGAUAGAU sheIF3i GGAGAGCUCAACCAGUAUAGU Tet-shC CUUCGAAAUGUCCGUUCGGUU Tet-shD#1 GACCUGAACUCUUCAGAUA Tet-shD#2 CGCUUGGAACAGGAACUCUUU siC GCGCUUCUACCAAAUACACUUGAUA siD#1 CCUAGACCUGAACUCUUCAGAUAAU siD#2 GGGAGAAAUUAUCAUGGGAAACAUU siD#3 CACCAACGAGAGAGUUGGCAGUACA Supplementary Table S2. Univariate and multivariate cox regression analyses in HNSCC patient samples. Supplementary Table S3. List of genes that showed more than two-fold changes upon DDX3 knockdown. ProbeName Exp1 Exp2 Average GeneSymbol A_33_P3672756 -3.2457285 -3.1393843 -3.1925564 LOC284561 A_24_P126060 -3.16082 -2.8644743 -3.01264715 DDX3X A_23_P19663 -2.6272717 -3.0723238 -2.84979775 CTGF A_22_P00014730 -2.6604695 -2.8590827 -2.7597761 lnc-SLC2A4RG-1 A_33_P3323959 -2.618907 -2.7437034 -2.6813052 RELN A_23_P381102 -2.5932717 -2.7077975 -2.6505346 CCDC74B A_24_P250922 -2.7136197 -2.5842419 -2.6489308 PTGS2 A_23_P69030 -2.7204385 -2.5039654 -2.61220195 COL8A1 A_23_P409093 -2.4106035 -2.4617586 -2.43618105 ANO4 A_19_P00315452 -2.2802095 -2.4505363 -2.3653729 LOC100130938 A_22_P00006060 -2.3473585 -2.3487363 -2.3480474 lnc-FAM131B-1 A_33_P3257297 -2.4315958 -2.2441187 -2.33785725 CFAP58 A_23_P2857 -2.2206445 -2.4522054 -2.33642495 CCDC70 A_23_P413157 -2.6971874 -1.9361424 -2.3166649 CXorf58 A_23_P121064 -2.275794 -2.3201835 -2.29798875 PTX3 A_23_P147786 -2.3058267 -2.239805 -2.27281585 RIMS2 A_19_P00321743 -2.193635 -2.274543 -2.234089 LOC100130938 A_24_P200219 -2.312551 -2.0688639 -2.19070745 UPK1B A_24_P391230 -2.189209 -2.1288314 -2.1590202 CYYR1 A_23_P323801 -1.7217016 -2.4646688 -2.0931852 BEST3 A_22_P00000938 -1.9366587 -2.1961193 -2.066389 LINC00704 A_19_P00322533 -2.08633 -2.022108 -2.054219 CRNDE A_33_P3379381 -2.0799832 -2.0108426 -2.0454129 WDR78 A_23_P326020 -2.1263115 -1.94181 -2.03406075 CSMD3 A_21_P0014483 -2.1743498 -1.8527889 -2.01356935 FGD5-AS1 A_22_P00008272 -1.9366459 -2.0696526 -2.00314925 CRNDE A_22_P00011688 -1.7390351 -2.1885347 -1.9637849 PDGFRB A_33_P3419190 -1.9389725 -1.987857 -1.96341475 AREG A_23_P405878 -1.908002 -2.0068078 -1.9574049 C12orf54 A_23_P259071 -1.9079303 -1.9981002 -1.95301525 AREG A_22_P00023317 -1.8614713 -2.040125 -1.95079815 LINC01468 A_23_P28834 -1.9107575 -1.9524698 -1.93161365 PHACTR3 A_22_P00008144 -2.3607192 -1.4584756 -1.9095974 LOC101927841 A_23_P102037 -2.0481038 -1.7292266 -1.8886652 COQ10B A_24_P709377 -1.8542476 -1.8928032 -1.8735254 PAX8-AS1 A_23_P145529 -1.781932 -1.9212033 -1.85156765 PKIB A_21_P0006938 -1.6937836 -2.0082424 -1.851013 LOC101927435 A_33_P3286873 -2.0457375 -1.6438757 -1.8448066 CD247 A_19_P00802607 -1.7883825 -1.8810377 -1.8347101 lnc-HK2-1 A_33_P3339070 -1.691214 -1.9489719 -1.82009295 LINC00704 A_22_P00000428 -1.9464568 -1.6747723 -1.81061455 lnc-AC073263.1-2 A_21_P0001880 -1.7863463 -1.8343409 -1.8103436 LINC01293 A_23_P104438 -1.7556653 -1.8254089 -1.7905371 MYPN A_22_P00010577 -1.8206011 -1.7209879 -1.7707945 RBM26-AS1 A_22_P00009085 -1.6835133 -1.836864 -1.76018865 LOC100507006 A_33_P3353051 -1.8678111 -1.6140289 -1.74092 C6orf48 A_24_P299474 -1.819312 -1.6609211 -1.74011655 TENM2 A_23_P48339 -1.9330316 -1.5418372 -1.7374344 IFT88 A_24_P137897 -1.7275401 -1.7334242 -1.73048215 IFRD1 A_33_P3279847 -1.8562082 -1.5746613 -1.71543475 RAET1E A_24_P88696 -1.6541246 -1.7635082 -1.7088164 SCG2 A_21_P0009321 -1.6703386 -1.7080823 -1.68921045 LOC101929494 A_33_P3242952 -1.784726 -1.5831519 -1.68393895 FAM72A A_23_P323563 -1.7429676 -1.6167072 -1.6798374 PLEKHG2 A_32_P148796
Recommended publications
  • Cytogenomic SNP Microarray - Fetal ARUP Test Code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells

    Cytogenomic SNP Microarray - Fetal ARUP Test Code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells

    Patient Report |FINAL Client: Example Client ABC123 Patient: Patient, Example 123 Test Drive Salt Lake City, UT 84108 DOB 2/13/1987 UNITED STATES Gender: Female Patient Identifiers: 01234567890ABCD, 012345 Physician: Doctor, Example Visit Number (FIN): 01234567890ABCD Collection Date: 00/00/0000 00:00 Cytogenomic SNP Microarray - Fetal ARUP test code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells Single fetal genotype present; no maternal cells present. Fetal and maternal samples were tested using STR markers to rule out maternal cell contamination. This result has been reviewed and approved by Maternal Specimen Yes Cytogenomic SNP Microarray - Fetal Abnormal * (Ref Interval: Normal) Test Performed: Cytogenomic SNP Microarray- Fetal (ARRAY FE) Specimen Type: Direct (uncultured) villi Indication for Testing: Patient with 46,XX,t(4;13)(p16.3;q12) (Quest: EN935475D) ----------------------------------------------------------------- ----- RESULT SUMMARY Abnormal Microarray Result (Male) Unbalanced Translocation Involving Chromosomes 4 and 13 Classification: Pathogenic 4p Terminal Deletion (Wolf-Hirschhorn syndrome) Copy number change: 4p16.3p16.2 loss Size: 5.1 Mb 13q Proximal Region Deletion Copy number change: 13q11q12.12 loss Size: 6.1 Mb ----------------------------------------------------------------- ----- RESULT DESCRIPTION This analysis showed a terminal deletion (1 copy present) involving chromosome 4 within 4p16.3p16.2 and a proximal interstitial deletion (1 copy present) involving chromosome 13 within 13q11q12.12. This
  • A Genome-Wide Association Study Lystra P

    A Genome-Wide Association Study Lystra P

    Hayden et al. Respiratory Research (2018) 19:209 https://doi.org/10.1186/s12931-018-0890-0 RESEARCH Open Access Childhood asthma is associated with COPD and known asthma variants in COPDGene: a genome-wide association study Lystra P. Hayden1,2* , Michael H. Cho2,3, Benjamin A. Raby1,2,3, Terri H. Beaty4, Edwin K. Silverman2,3, Craig P. Hersh2,3 and on behalf of the COPDGene Investigators Abstract Background: Childhood asthma is strongly influenced by genetics and is a risk factor for reduced lung function and chronic obstructive pulmonary disease (COPD) in adults. This study investigates self-reported childhood asthma in adult smokers from the COPDGene Study. We hypothesize that childhood asthma is associated with decreased lung function, increased risk for COPD, and that a genome-wide association study (GWAS) will show association with established asthma variants. Methods: We evaluated current and former smokers ages 45–80 of non-Hispanic white (NHW) or African American (AA) race. Childhood asthma was defined by self-report of asthma, diagnosed by a medical professional, with onset at < 16 years or during childhood. Subjects with a history of childhood asthma were compared to those who never had asthma based on lung function, development of COPD, and genetic variation. GWAS was performed in NHW and AA populations, and combined in meta-analysis. Two sets of established asthma SNPs from published literature were examined for association with childhood asthma. Results: Among 10,199 adult smokers, 730 (7%) reported childhood asthma and 7493 (73%) reported no history of asthma. Childhood asthmatics had reduced lung function and increased risk for COPD (OR 3.42, 95% CI 2.81–4.18).
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • Screening of a Clinically and Biochemically Diagnosed SOD Patient Using Exome Sequencing: a Case Report with a Mutations/Variations Analysis Approach

    Screening of a Clinically and Biochemically Diagnosed SOD Patient Using Exome Sequencing: a Case Report with a Mutations/Variations Analysis Approach

    The Egyptian Journal of Medical Human Genetics (2016) 17, 131–136 HOSTED BY Ain Shams University The Egyptian Journal of Medical Human Genetics www.ejmhg.eg.net www.sciencedirect.com CASE REPORT Screening of a clinically and biochemically diagnosed SOD patient using exome sequencing: A case report with a mutations/variations analysis approach Mohamad-Reza Aghanoori a,b,1, Ghazaleh Mohammadzadeh Shahriary c,2, Mahdi Safarpour d,3, Ahmad Ebrahimi d,* a Department of Medical Genetics, Shiraz University of Medical Sciences, Shiraz, Iran b Research and Development Division, RoyaBioGene Co., Tehran, Iran c Department of Genetics, Shahid Chamran University of Ahvaz, Ahvaz, Iran d Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Received 12 May 2015; accepted 15 June 2015 Available online 22 July 2015 KEYWORDS Abstract Background: Sulfite oxidase deficiency (SOD) is a rare neurometabolic inherited disor- Sulfite oxidase deficiency; der causing severe delay in developmental stages and premature death. The disease follows an auto- Case report; somal recessive pattern of inheritance and causes deficiency in the activity of sulfite oxidase, an Exome sequencing enzyme that normally catalyzes conversion of sulfite to sulfate. Aim of the study: SOD is an underdiagnosed disorder and its diagnosis can be difficult in young infants as early clinical features and neuroimaging changes may imitate some common diseases. Since the prognosis of the disease is poor, using exome sequencing as a powerful and efficient strat- egy for identifying the genes underlying rare mendelian disorders can provide important knowledge about early diagnosis, disease mechanisms, biological pathways, and potential therapeutic targets.
  • Breakout Room 5 Poster Presentation Event

    Breakout Room 5 Poster Presentation Event

    Akshara Chandrabalan 2020 NSERC USRA Bioresource Engineering, Supervisor Dr. Prasher 2020 Undergraduate Student Research Awards Predicting Biochar Sorption Capacities Using VIEW THE POSTERS Artificial Neural Networks Poster Presentation Event Breakout Room 5 Daniel Moses 2020 NSERC USRA (ZOOM) SEPTEMBER 17, 2020 @ 4pm Parasitology, Supervisor Dr. Salavati In search of the cryptic motif VI on trypanosomatid RNA editing ligases Richard Boivin 2020 NSERC USRA Antoine Gaudreau 2020 NSERC USRA 1 Natural Resource Sciences, Supervisor Dr. Humphries Bioresource Engineering, Supervisor Dr. Akbarzadeh Muriel Wong Min 2020 AES Brown Martlet USRA Evaluating regional patterns of traditional wildlife 3D Printed Agricultural Wastes for Advanced Food Science & Ag. Chemistry, Supervisor Dr. Karboune harvest in northern Quebec Biocomposites A Database Platform for The Selection of Appropriate Fat Substitutes as "Natural" Katerina Lazaris 2020 NSERC USRA Rowena Groeneveld 2020 NSERC USRA Food Ingredients Animal Science, Supervisor Dr. Bordignon Parasitology, Supervisor Dr. Beech Review: Methods to Improve Oocyte Competence and Modelling of a ligand gated ion channel from embryo Development in Prepubertal Animals to Caenorhabditis elegans experimentally shown to bind Liana Fortin-Hamel 2020 NSERC USRA Accerlerate genetic Gain 6 dopamine Parasitology, Supervisor Dr. Scott 2 Trisha Sackey 2020 NSERC USRA Effects of maternal nematode infection on spatial Food Science & Ag.Chemistry, Supervisor Dr. George Alex Zvezdin 2020 NSERC USRA learning and memory of young mouse pups Natural Resource Sciences, Supervisor Dr. Head Genotypic and Phenotypic Profiling of Staphylo- coccus aureus strains isolated from Canadian Impacts of Agricultural Practices on Yellow Perch Xavier Godin 2020 NSERC USRA Dairy Cattle for Antimicrobial Resistance Spawning Sites in Lac-Saint Pierre Québec Plant Science, Supervisor Dr.
  • Expression of the POTE Gene Family in Human Ovarian Cancer Carter J Barger1,2, Wa Zhang1,2, Ashok Sharma 1,2, Linda Chee1,2, Smitha R

    Expression of the POTE Gene Family in Human Ovarian Cancer Carter J Barger1,2, Wa Zhang1,2, Ashok Sharma 1,2, Linda Chee1,2, Smitha R

    www.nature.com/scientificreports OPEN Expression of the POTE gene family in human ovarian cancer Carter J Barger1,2, Wa Zhang1,2, Ashok Sharma 1,2, Linda Chee1,2, Smitha R. James3, Christina N. Kufel3, Austin Miller 4, Jane Meza5, Ronny Drapkin 6, Kunle Odunsi7,8,9, 2,10 1,2,3 Received: 5 July 2018 David Klinkebiel & Adam R. Karpf Accepted: 7 November 2018 The POTE family includes 14 genes in three phylogenetic groups. We determined POTE mRNA Published: xx xx xxxx expression in normal tissues, epithelial ovarian and high-grade serous ovarian cancer (EOC, HGSC), and pan-cancer, and determined the relationship of POTE expression to ovarian cancer clinicopathology. Groups 1 & 2 POTEs showed testis-specifc expression in normal tissues, consistent with assignment as cancer-testis antigens (CTAs), while Group 3 POTEs were expressed in several normal tissues, indicating they are not CTAs. Pan-POTE and individual POTEs showed signifcantly elevated expression in EOC and HGSC compared to normal controls. Pan-POTE correlated with increased stage, grade, and the HGSC subtype. Select individual POTEs showed increased expression in recurrent HGSC, and POTEE specifcally associated with reduced HGSC OS. Consistent with tumors, EOC cell lines had signifcantly elevated Pan-POTE compared to OSE and FTE cells. Notably, Group 1 & 2 POTEs (POTEs A/B/B2/C/D), Group 3 POTE-actin genes (POTEs E/F/I/J/KP), and other Group 3 POTEs (POTEs G/H/M) show within-group correlated expression, and pan-cancer analyses of tumors and cell lines confrmed this relationship. Based on their restricted expression in normal tissues and increased expression and association with poor prognosis in ovarian cancer, POTEs are potential oncogenes and therapeutic targets in this malignancy.
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD

    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
  • Molecular Features of Triple Negative Breast Cancer Cells by Genome-Wide Gene Expression Profiling Analysis

    Molecular Features of Triple Negative Breast Cancer Cells by Genome-Wide Gene Expression Profiling Analysis

    478 INTERNATIONAL JOURNAL OF ONCOLOGY 42: 478-506, 2013 Molecular features of triple negative breast cancer cells by genome-wide gene expression profiling analysis MASATO KOMATSU1,2*, TETSURO YOSHIMARU1*, TAISUKE MATSUO1, KAZUMA KIYOTANI1, YASUO MIYOSHI3, TOSHIHITO TANAHASHI4, KAZUHITO ROKUTAN4, RUI YAMAGUCHI5, AYUMU SAITO6, SEIYA IMOTO6, SATORU MIYANO6, YUSUKE NAKAMURA7, MITSUNORI SASA8, MITSUO SHIMADA2 and TOYOMASA KATAGIRI1 1Division of Genome Medicine, Institute for Genome Research, The University of Tokushima; 2Department of Digestive and Transplantation Surgery, The University of Tokushima Graduate School; 3Department of Surgery, Division of Breast and Endocrine Surgery, Hyogo College of Medicine, Hyogo 663-8501; 4Department of Stress Science, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima 770-8503; Laboratories of 5Sequence Analysis, 6DNA Information Analysis and 7Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639; 8Tokushima Breast Care Clinic, Tokushima 770-0052, Japan Received September 22, 2012; Accepted November 6, 2012 DOI: 10.3892/ijo.2012.1744 Abstract. Triple negative breast cancer (TNBC) has a poor carcinogenesis of TNBC and could contribute to the develop- outcome due to the lack of beneficial therapeutic targets. To ment of molecular targets as a treatment for TNBC patients. clarify the molecular mechanisms involved in the carcino- genesis of TNBC and to identify target molecules for novel Introduction anticancer drugs, we analyzed the gene expression profiles of 30 TNBCs as well as 13 normal epithelial ductal cells that were Breast cancer is one of the most common solid malignant purified by laser-microbeam microdissection. We identified tumors among women worldwide. Breast cancer is a heteroge- 301 and 321 transcripts that were significantly upregulated neous disease that is currently classified based on the expression and downregulated in TNBC, respectively.
  • NIH Public Access Provided by Digital.CSIC Author Manuscript Bioessays

    NIH Public Access Provided by Digital.CSIC Author Manuscript Bioessays

    View metadata, citation and similar papers at core.ac.uk brought to you by CORE NIH Public Access provided by Digital.CSIC Author Manuscript Bioessays. Author manuscript; available in PMC 2007 October 1. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Bioessays. 2007 April ; 29(4): 356±370. GTP-binding proteins of the Rho/Rac family: regulation, effectors and functions in vivo Xosé R. Bustelo*, Vincent Sauzeau, and Inmaculada M. Berenjeno Centro de Investigación del Cáncer and Instituto de Biología Molecular y Celular del Cáncer (IBMCC), CSIC-University of Salamanca, Salamanca, Spain. Summary Rho/Rac proteins constitute a subgroup of the Ras superfamily of GTP hydrolases. Although originally implicated in the control of cytoskeletal events, it is currently known that these GTPases coordinate diverse cellular functions, including cell polarity, vesicular trafficking, the cell cycle and transcriptomal dynamics. In this review, we will provide an overview on the recent advances in this field regarding the mechanism of regulation and signaling, and the roles in vivo of this important GTPase family. Introduction The isolation of rhoA,(1) the first member of the Rho/Rac family ever identified, was achieved by Richard Axel’s group in 1985 during the search for ras -related genes in Aplysia.(1) The subsequent use of conventional cloning techniques and the more-recent characterization of genomes revealed that the original gene is not alone, having numerous family counterparts in other species including, among many others, S. cerevisiae(7 genes), A. taliana(11 genes), C. elegans(9 genes), D. melanogaster(9 genes) and H.
  • Investigating Developmental and Functional Deficits in Neurodegenerative

    Investigating Developmental and Functional Deficits in Neurodegenerative

    UNIVERSITY OF CALIFORNIA, IRVINE Investigating developmental and functional deficits in neurodegenerative disease using transcriptomic analyses DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biomedical Sciences by Ryan Gar-Lok Lim Dissertation Committee: Professor Leslie M. Thompson, Chair Assistant Professor Dritan Agalliu Professor Peter Donovan Professor Suzanne Sandmeyer 2016 Introduction, Figure 1.1 © 2014 Macmillan Publishers Limited. Appendix 1 © 2016 Elsevier Ltd. All other materials © 2016 Ryan Gar-Lok Lim DEDICATION This dissertation is dedicated to my parents, sister, and my wife. I love you all very much and could not have accomplished any of this without your love and support. Please take the time to reflect back on all of the moments we’ve shared, and know, that it is because of those moments I have been able to succeed. This accomplishment is as much yours as it is mine. ii TABLE OF CONTENTS Page LIST OF FIGURES vi LIST OF TABLES ix ACKNOWLEDGMENTS x CURRICULUM VITAE xiii ABSTRACT OF THE DISSERTATION xv Introduction Huntington’s disease, the neurovascular unit and the blood-brain barrier 1 1.1 Huntington’s Disease 1.2 HTT structure and function 1.2.1 Normal HTT function and possible loss-of-function contributions to HD 1.3 mHTT pathogenesis 1.3.1 The dominant pathological features of mHTT - a gain-of- toxic function? 1.3.2 Cellular pathologies and non-neuronal contributions to HD 1.4 The neurovascular unit and the blood-brain barrier 1.4.1 Structure and function
  • Molecular Analyses of Malignant Pleural Mesothelioma

    Molecular Analyses of Malignant Pleural Mesothelioma

    Molecular Analyses of Malignant Pleural Mesothelioma Shir Kiong Lo National Heart and Lung Institute Imperial College Dovehouse Street London SW3 6LY A thesis submitted for MD (Res) Faculty of Medicine, Imperial College London 2016 1 Abstract Malignant pleural mesothelioma (MPM) is an aggressive cancer that is strongly associated with asbestos exposure. Majority of patients with MPM present with advanced disease and the treatment paradigm mainly involves palliative chemotherapy and best supportive care. The current chemotherapy options are limited and ineffective hence there is an urgent need to improve patient outcomes. This requires better understanding of the genetic alterations driving MPM to improve diagnostic, prognostic and therapeutic strategies. This research aims to gain further insights in the pathogenesis of MPM by exploring the tumour transcriptional and mutational profiles. We compared gene expression profiles of 25 MPM tumours and 5 non-malignant pleura. This revealed differentially expressed genes involved in cell migration, invasion, cell cycle and the immune system that contribute to the malignant phenotype of MPM. We then constructed MPM-associated co-expression networks using weighted gene correlation network analysis to identify clusters of highly correlated genes. These identified three distinct molecular subtypes of MPM associated with genes involved in WNT and TGF-ß signalling pathways. Our results also revealed genes involved in cell cycle control especially the mitotic phase correlated significantly with poor prognosis. Through exome analysis of seven paired tumour/blood and 29 tumour samples, we identified frequent mutations in BAP1 and NF2. Additionally, the mutational profile of MPM is enriched with genes encoding FAK, MAPK and WNT signalling pathways.
  • Genome-Wide Association Study Confirms Extant PD Risk Loci Among

    Genome-Wide Association Study Confirms Extant PD Risk Loci Among

    European Journal of Human Genetics (2011) 19, 655–661 & 2011 Macmillan Publishers Limited All rights reserved 1018-4813/11 www.nature.com/ejhg ARTICLE Genome-wide association study confirms extant PD risk loci among the Dutch Javier Simo´n-Sa´nchez*,1, Jacobus J van Hilten2, Bart van de Warrenburg3, Bart Post3, Henk W Berendse4, Sampath Arepalli5, Dena G Hernandez5, Rob MA de Bie6, Daan Velseboer6, Hans Scheffer7, Bas Bloem3, Karin D van Dijk4, Fernando Rivadeneira8,9, Albert Hofman8, Andre´ G Uitterlinden8,9, Patrizia Rizzu1, Zoltan Bochdanovits1, Andrew B Singleton5 and Peter Heutink1 In view of the population-specific heterogeneity in reported genetic risk factors for Parkinson’s disease (PD), we conducted a genome-wide association study (GWAS) in a large sample of PD cases and controls from the Netherlands. After quality control (QC), a total of 514 799 SNPs genotyped in 772 PD cases and 2024 controls were included in our analyses. Direct replication of SNPs within SNCA and BST1 confirmed these two genes to be associated with PD in the Netherlands (SNCA, rs2736990: P¼1.63Â10À5,OR¼1.325 and BST1, rs12502586: P¼1.63Â10À3,OR¼1.337). Within SNCA, two independent signals in two different linkage disequilibrium (LD) blocks in the 3¢ and 5¢ ends of the gene were detected. Besides, post-hoc analysis confirmed GAK/DGKQ, HLA and MAPT as PD risk loci among the Dutch (GAK/DGKQ, rs2242235: P¼1.22Â10À4,OR¼1.51; HLA, rs4248166: P¼4.39Â10À5,OR¼1.36; and MAPT, rs3785880: P¼1.9Â10À3,OR¼1.19). European Journal of Human Genetics (2011) 19, 655–661; doi:10.1038/ejhg.2010.254; published online 19 January 2011 Keywords: SNCA; BST1; GAK/DGKQ; HLA; MAPT;PD INTRODUCTION self-reported Caucasian individuals from the Netherlands.