(PAPSS1-BRAF): a 2.2 Cm Thick (Clar
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Figure S1. DMD Module Network. the Network Is Formed by 260 Genes from Disgenet and 1101 Interactions from STRING. Red Nodes Are the Five Seed Candidate Genes
Figure S1. DMD module network. The network is formed by 260 genes from DisGeNET and 1101 interactions from STRING. Red nodes are the five seed candidate genes. Figure S2. DMD module network is more connected than a random module of the same size. It is shown the distribution of the largest connected component of 10.000 random modules of the same size of the DMD module network. The green line (x=260) represents the DMD largest connected component, obtaining a z-score=8.9. Figure S3. Shared genes between BMD and DMD signature. A) A meta-analysis of three microarray datasets (GSE3307, GSE13608 and GSE109178) was performed for the identification of differentially expressed genes (DEGs) in BMD muscle biopsies as compared to normal muscle biopsies. Briefly, the GSE13608 dataset included 6 samples of skeletal muscle biopsy from healthy people and 5 samples from BMD patients. Biopsies were taken from either biceps brachii, triceps brachii or deltoid. The GSE3307 dataset included 17 samples of skeletal muscle biopsy from healthy people and 10 samples from BMD patients. The GSE109178 dataset included 14 samples of controls and 11 samples from BMD patients. For both GSE3307 and GSE10917 datasets, biopsies were taken at the time of diagnosis and from the vastus lateralis. For the meta-analysis of GSE13608, GSE3307 and GSE109178, a random effects model of effect size measure was used to integrate gene expression patterns from the two datasets. Genes with an adjusted p value (FDR) < 0.05 and an │effect size│>2 were identified as DEGs and selected for further analysis. A significant number of DEGs (p<0.001) were in common with the DMD signature genes (blue nodes), as determined by a hypergeometric test assessing the significance of the overlap between the BMD DEGs and the number of DMD signature genes B) MCODE analysis of the overlapping genes between BMD DEGs and DMD signature genes. -
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. -
Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent- Title Responsive Biomarker
Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent- Title Responsive Biomarker Author(s) 山村, 宏江 Citation 北海道大学. 博士(工学) 甲第11137号 Issue Date 2013-09-25 DOI 10.14943/doctoral.k11137 Doc URL http://hdl.handle.net/2115/77180 Type theses (doctoral) File Information Hiroe_Yamamura.pdf Instructions for use Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP Doctoral Thesis Toxicogenomic Approach to Impact Assessment of Whole Wastewater Effluents and Development of Effluent-Responsive Biomarker Hiroe Hara-Yamamura Acknowledgement My doctoral research works presented here cannot be completed without a numerous number of tangible and intangible supports from my peers, my supervisor, instructors, friends, and family. I would first express my deepest gratitude to Prof. Satoshi OKABE for his technical advices and crisp ideas which often came to break the deadlock of my research progress, and for continued provision of another chance to me, even in the least fruitful season. Indeed, my three years in Prof. OKABE’s lab was “luxuri- ous” time in my life with a lot of supports, encouragements, and chances. In addition, I appreciate both Prof. Daisuke SANO and Dr. Satoshi ISHII for offering their insights on my experimental design and data analysis as well as giving me words of encouragements from time to time. Also, thank you to Prof. Takashi KUSUI from Toyama Prefectural University for his assistance to bioassay techniques and valuable discussion dur- ing my 1st year and 2nd year evaluation presentations. Furthermore, I would like to express my gratitude to specific efforts kindly provide by: Mr. Kenzo Kudo, Prof. -
GSTP1 Is a Driver of Triple-Negative Breast Cancer Cell Metabolism and Pathogenicity
Article GSTP1 Is a Driver of Triple-Negative Breast Cancer Cell Metabolism and Pathogenicity Graphical Abstract Authors Sharon M. Louie, Elizabeth A. Grossman, Lisa A. Crawford, ..., Andrei Goga, Eranthie Weerapana, Daniel K. Nomura Correspondence [email protected] In Brief Using a reactivity-based chemoproteomic platform, Louie et al. have identified GSTP1 as a triple-negative breast cancer target that, when inhibited, impairs breast cancer pathogenicity through inhibiting GAPDH activity and downstream metabolism and signaling pathways. Highlights d We used chemoproteomics to profile metabolic drivers of breast cancer d GSTP1 is a novel triple-negative breast cancer-specific target d GSTP1 inhibition impairs triple-negative breast cancer pathogenicity d GSTP1 inhibition impairs GAPDH activity to affect metabolism and signaling Louie et al., 2016, Cell Chemical Biology 23, 1–12 May 19, 2016 ª 2016 Elsevier Ltd. http://dx.doi.org/10.1016/j.chembiol.2016.03.017 Please cite this article in press as: Louie et al., GSTP1 Is a Driver of Triple-Negative Breast Cancer Cell Metabolism and Pathogenicity, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.03.017 Cell Chemical Biology Article GSTP1 Is a Driver of Triple-Negative Breast Cancer Cell Metabolism and Pathogenicity Sharon M. Louie,1 Elizabeth A. Grossman,1 Lisa A. Crawford,2 Lucky Ding,1 Roman Camarda,3 Tucker R. Huffman,1 David K. Miyamoto,1 Andrei Goga,3 Eranthie Weerapana,2 and Daniel K. Nomura1,* 1Departments of Chemistry and Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA 94720, USA 2Department of Chemistry, Boston College, Chestnut Hill, MA 02467, USA 3Department of Cell and Tissue Biology and Medicine, University of California, San Francisco, San Francisco, CA 94143, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.chembiol.2016.03.017 SUMMARY subtypes that are correlated with heightened malignancy and poor prognosis remain poorly understood. -
Human Kinases Info Page
Human Kinase Open Reading Frame Collecon Description: The Center for Cancer Systems Biology (Dana Farber Cancer Institute)- Broad Institute of Harvard and MIT Human Kinase ORF collection from Addgene consists of 559 distinct human kinases and kinase-related protein ORFs in pDONR-223 Gateway® Entry vectors. All clones are clonal isolates and have been end-read sequenced to confirm identity. Kinase ORFs were assembled from a number of sources; 56% were isolated as single cloned isolates from the ORFeome 5.1 collection (horfdb.dfci.harvard.edu); 31% were cloned from normal human tissue RNA (Ambion) by reverse transcription and subsequent PCR amplification adding Gateway® sequences; 11% were cloned into Entry vectors from templates provided by the Harvard Institute of Proteomics (HIP); 2% additional kinases were cloned into Entry vectors from templates obtained from collaborating laboratories. All ORFs are open (stop codons removed) except for 5 (MST1R, PTK7, JAK3, AXL, TIE1) which are closed (have stop codons). Detailed information can be found at: www.addgene.org/human_kinases Handling and Storage: Store glycerol stocks at -80oC and minimize freeze-thaw cycles. To access a plasmid, keep the plate on dry ice to prevent thawing. Using a sterile pipette tip, puncture the seal above an individual well and spread a portion of the glycerol stock onto an agar plate. To patch the hole, use sterile tape or a portion of a fresh aluminum seal. Note: These plasmid constructs are being distributed to non-profit institutions for the purpose of basic -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
Immune Cells in Spleen and Mucosa + CD127 Neg Production of IL-17
Downloaded from http://www.jimmunol.org/ by guest on September 28, 2021 neg is online at: average * The Journal of Immunology published online 21 June 2010 Immune Cells in Spleen and Mucosa from submission to initial decision + 4 weeks from acceptance to publication TLR5 Signaling Stimulates the Innate Production of IL-17 and IL-22 by CD3 CD127 Laurye Van Maele, Christophe Carnoy, Delphine Cayet, Pascal Songhet, Laure Dumoutier, Isabel Ferrero, Laure Janot, François Erard, Julie Bertout, Hélène Leger, Florent Sebbane, Arndt Benecke, Jean-Christophe Renauld, Wolf-Dietrich Hardt, Bernhard Ryffel and Jean-Claude Sirard http://www.jimmunol.org/content/early/2010/06/21/jimmun ol.1000115 J Immunol Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2010/06/21/jimmunol.100011 5.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 28, 2021. Published June 21, 2010, doi:10.4049/jimmunol.1000115 -
Autocrine IFN Signaling Inducing Profibrotic Fibroblast Responses By
Downloaded from http://www.jimmunol.org/ by guest on September 23, 2021 Inducing is online at: average * The Journal of Immunology , 11 of which you can access for free at: 2013; 191:2956-2966; Prepublished online 16 from submission to initial decision 4 weeks from acceptance to publication August 2013; doi: 10.4049/jimmunol.1300376 http://www.jimmunol.org/content/191/6/2956 A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Autocrine IFN Signaling Feng Fang, Kohtaro Ooka, Xiaoyong Sun, Ruchi Shah, Swati Bhattacharyya, Jun Wei and John Varga J Immunol cites 49 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2013/08/20/jimmunol.130037 6.DC1 This article http://www.jimmunol.org/content/191/6/2956.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 23, 2021. The Journal of Immunology A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Inducing Autocrine IFN Signaling Feng Fang,* Kohtaro Ooka,* Xiaoyong Sun,† Ruchi Shah,* Swati Bhattacharyya,* Jun Wei,* and John Varga* Activation of TLR3 by exogenous microbial ligands or endogenous injury-associated ligands leads to production of type I IFN. -
Supplemental Figures 04 12 2017
Jung et al. 1 SUPPLEMENTAL FIGURES 2 3 Supplemental Figure 1. Clinical relevance of natural product methyltransferases (NPMTs) in brain disorders. (A) 4 Table summarizing characteristics of 11 NPMTs using data derived from the TCGA GBM and Rembrandt datasets for 5 relative expression levels and survival. In addition, published studies of the 11 NPMTs are summarized. (B) The 1 Jung et al. 6 expression levels of 10 NPMTs in glioblastoma versus non‐tumor brain are displayed in a heatmap, ranked by 7 significance and expression levels. *, p<0.05; **, p<0.01; ***, p<0.001. 8 2 Jung et al. 9 10 Supplemental Figure 2. Anatomical distribution of methyltransferase and metabolic signatures within 11 glioblastomas. The Ivy GAP dataset was downloaded and interrogated by histological structure for NNMT, NAMPT, 12 DNMT mRNA expression and selected gene expression signatures. The results are displayed on a heatmap. The 13 sample size of each histological region as indicated on the figure. 14 3 Jung et al. 15 16 Supplemental Figure 3. Altered expression of nicotinamide and nicotinate metabolism‐related enzymes in 17 glioblastoma. (A) Heatmap (fold change of expression) of whole 25 enzymes in the KEGG nicotinate and 18 nicotinamide metabolism gene set were analyzed in indicated glioblastoma expression datasets with Oncomine. 4 Jung et al. 19 Color bar intensity indicates percentile of fold change in glioblastoma relative to normal brain. (B) Nicotinamide and 20 nicotinate and methionine salvage pathways are displayed with the relative expression levels in glioblastoma 21 specimens in the TCGA GBM dataset indicated. 22 5 Jung et al. 23 24 Supplementary Figure 4. -
SUPPLEMENTARY MATERIALS and METHODS PBMC Transcriptomics
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Gut SUPPLEMENTARY MATERIALS AND METHODS PBMC transcriptomics identifies immune-metabolism disorder during the development of HBV-ACLF Contents l Supplementary methods l Supplementary Figure 1 l Supplementary Figure 2 l Supplementary Figure 3 l Supplementary Figure 4 l Supplementary Figure 5 l Supplementary Table 1 l Supplementary Table 2 l Supplementary Table 3 l Supplementary Table 4 l Supplementary Tables 5-14 l Supplementary Table 15 l Supplementary Table 16 l Supplementary Table 17 Li J, et al. Gut 2021;0:1–13. doi: 10.1136/gutjnl-2020-323395 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Gut SUPPLEMENTARY METHODS Test for HBV DNA The levels of HBV DNA were detected using real-time PCR with a COBAS® AmpliPrep/COBAS® TaqMan 48 System (Roche, Basel, Switzerland) and HBV Test v2.0. Criteria for diagnosing cirrhosis Pathology The gold standard for the diagnosis of cirrhosis is a liver biopsy obtained through a percutaneous or transjugular approach.1 Ultrasonography was performed 2-4 hours before biopsy. Liver biopsy specimens were obtained by experienced physicians. Percutaneous transthoracic puncture of the liver was performed according to the standard criteria. After biopsy, patients were monitored in the hospital with periodic analyses of haematocrit and other vital signs for 24 hours. Cirrhosis was diagnosed according to the globally agreed upon criteria.2 Cirrhosis is defined based on its pathological features under a microscope: (a) the presence of parenchymal nodules, (b) differences in liver cell size and appearance, (c) fragmentation of the biopsy specimen, (d) fibrous septa, and (d) an altered architecture and vascular relationships. -
(PAPSS1) Knockdown Sensitizes Non-Small Cell Lung Cancer Cells to DNA Damaging Agents Ada W
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 6, No. 19 3′-Phosphoadenosine 5′-phosphosulfate synthase 1 (PAPSS1) knockdown sensitizes non-small cell lung cancer cells to DNA damaging agents Ada W. Y. Leung1,2, Wieslawa H. Dragowska1, Daniel Ricaurte1, Brian Kwok1, Veena Mathew3, Jeroen Roosendaal1,4, Amith Ahluwalia1, Corinna Warburton1, Janessa J. Laskin5,6, Peter C. Stirling3,7, Mohammed A. Qadir1, Marcel B. Bally1,2,8,9 1Experimental Therapeutics, BC Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada 2Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, V6T 2B5, Canada 3Terry Fox Laboratory, BC Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada 4Department of Pharmaceutical Sciences, Utrecht University, Utrecht, TB, 3508, The Netherlands 5Medical Oncology, BC Cancer Research Centre, Vancouver, BC, V5Z1L3, Canada 6Department of Medicine, University of British Columbia, Vancouver, BC, V5Z 1M9, Canada 7Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada 8Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada 9Centre for Drug Research and Development, Vancouver, BC, V6T 1Z3, Canada Correspondence to: Ada Leung e-mail: [email protected] Keywords: PAPSS1, sensitization, non-small cell lung cancer, siRNA screen, DNA damage Received: November 19, 2014 Accepted: March 23, 2015 Published: April 11, 2015 ABSTRACT Standard treatment for advanced non-small cell lung cancer (NSCLC) with no known driver mutation is platinum-based chemotherapy, which has a response rate of only 30–33%. Through an siRNA screen, 3′-phosphoadenosine 5′-phosphosulfate (PAPS) synthase 1 (PAPSS1), an enzyme that synthesizes the biologically active form of sulfate PAPS, was identified as a novel platinum-sensitizing target in NSCLC cells. -
Kinome Expression Profiling to Target New Therapeutic Avenues in Multiple Myeloma
Plasma Cell DIsorders SUPPLEMENTARY APPENDIX Kinome expression profiling to target new therapeutic avenues in multiple myeloma Hugues de Boussac, 1 Angélique Bruyer, 1 Michel Jourdan, 1 Anke Maes, 2 Nicolas Robert, 3 Claire Gourzones, 1 Laure Vincent, 4 Anja Seckinger, 5,6 Guillaume Cartron, 4,7,8 Dirk Hose, 5,6 Elke De Bruyne, 2 Alboukadel Kassambara, 1 Philippe Pasero 1 and Jérôme Moreaux 1,3,8 1IGH, CNRS, Université de Montpellier, Montpellier, France; 2Department of Hematology and Immunology, Myeloma Center Brussels, Vrije Universiteit Brussel, Brussels, Belgium; 3CHU Montpellier, Laboratory for Monitoring Innovative Therapies, Department of Biologi - cal Hematology, Montpellier, France; 4CHU Montpellier, Department of Clinical Hematology, Montpellier, France; 5Medizinische Klinik und Poliklinik V, Universitätsklinikum Heidelberg, Heidelberg, Germany; 6Nationales Centrum für Tumorerkrankungen, Heidelberg , Ger - many; 7Université de Montpellier, UMR CNRS 5235, Montpellier, France and 8 Université de Montpellier, UFR de Médecine, Montpel - lier, France ©2020 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2018.208306 Received: October 5, 2018. Accepted: July 5, 2019. Pre-published: July 9, 2019. Correspondence: JEROME MOREAUX - [email protected] Supplementary experiment procedures Kinome Index A list of 661 genes of kinases or kinases related have been extracted from literature9, and challenged in the HM cohort for OS prognostic values The prognostic value of each of the genes was computed using maximally selected rank test from R package MaxStat. After Benjamini Hochberg multiple testing correction a list of 104 significant prognostic genes has been extracted. This second list has then been challenged for similar prognosis value in the UAMS-TT2 validation cohort.