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
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Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin a and Affects the Migration and Invasion Potential of Breast Cancer Cells
Published OnlineFirst February 28, 2010; DOI: 10.1158/0008-5472.CAN-08-1108 Tumor and Stem Cell Biology Cancer Research Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin A and Affects the Migration and Invasion Potential of Breast Cancer Cells Zhijiu Zhong, Wen-Shuz Yeow, Chunhua Zou, Richard Wassell, Chenguang Wang, Richard G. Pestell, Judy N. Quong, and Andrew A. Quong Abstract Cyclin D1 belongs to a family of proteins that regulate progression through the G1-S phase of the cell cycle by binding to cyclin-dependent kinase (cdk)-4 to phosphorylate the retinoblastoma protein and release E2F transcription factors for progression through cell cycle. Several cancers, including breast, colon, and prostate, overexpress the cyclin D1 gene. However, the correlation of cyclin D1 overexpression with E2F target gene regulation or of cdk-dependent cyclin D1 activity with tumor development has not been identified. This suggests that the role of cyclin D1 in oncogenesis may be independent of its function as a cell cycle regulator. One such function is the role of cyclin D1 in cell adhesion and motility. Filamin A (FLNa), a member of the actin-binding filamin protein family, regulates signaling events involved in cell motility and invasion. FLNa has also been associated with a variety of cancers including lung cancer, prostate cancer, melanoma, human bladder cancer, and neuroblastoma. We hypothesized that elevated cyclin D1 facilitates motility in the invasive MDA-MB-231 breast cancer cell line. We show that MDA-MB-231 motility is affected by disturbing cyclin D1 levels or cyclin D1-cdk4/6 kinase activity. -
Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
The HECT Domain Ubiquitin Ligase HUWE1 Targets Unassembled Soluble Proteins for Degradation
OPEN Citation: Cell Discovery (2016) 2, 16040; doi:10.1038/celldisc.2016.40 ARTICLE www.nature.com/celldisc The HECT domain ubiquitin ligase HUWE1 targets unassembled soluble proteins for degradation Yue Xu1, D Eric Anderson2, Yihong Ye1 1Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA; 2Advanced Mass Spectrometry Core Facility, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA In eukaryotes, many proteins function in multi-subunit complexes that require proper assembly. To maintain complex stoichiometry, cells use the endoplasmic reticulum-associated degradation system to degrade unassembled membrane subunits, but how unassembled soluble proteins are eliminated is undefined. Here we show that degradation of unassembled soluble proteins (referred to as unassembled soluble protein degradation, USPD) requires the ubiquitin selective chaperone p97, its co-factor nuclear protein localization protein 4 (Npl4), and the proteasome. At the ubiquitin ligase level, the previously identified protein quality control ligase UBR1 (ubiquitin protein ligase E3 component n-recognin 1) and the related enzymes only process a subset of unassembled soluble proteins. We identify the homologous to the E6-AP carboxyl terminus (homologous to the E6-AP carboxyl terminus) domain-containing protein HUWE1 as a ubiquitin ligase for substrates bearing unshielded, hydrophobic segments. We used a stable isotope labeling with amino acids-based proteomic approach to identify endogenous HUWE1 substrates. Interestingly, many HUWE1 substrates form multi-protein com- plexes that function in the nucleus although HUWE1 itself is cytoplasmically localized. Inhibition of nuclear entry enhances HUWE1-mediated ubiquitination and degradation, suggesting that USPD occurs primarily in the cytoplasm. -
Ubiquitination Is Not Omnipresent in Myeloid Leukemia Ramesh C
Editorials Ubiquitination is not omnipresent in myeloid leukemia Ramesh C. Nayak1 and Jose A. Cancelas1,2 1Division of Experimental Hematology and Cancer Biology, Cincinnati Children’s Hospital Medical Center and 2Hoxworth Blood Center, University of Cincinnati Academic Health Center, Cincinnati, OH, USA E-mail: JOSE A. CANCELAS - [email protected] / [email protected] doi:10.3324/haematol.2019.224162 hronic myelogenous leukemia (CML) is a clonal tination of target proteins through their cognate E3 ubiq- biphasic hematopoietic disorder most frequently uitin ligases belonging to three different families (RING, Ccaused by the expression of the BCR-ABL fusion HERCT, RING-between-RING or RBR type E3).7 protein. The expression of BCR-ABL fusion protein with The ubiquitin conjugating enzymes including UBE2N constitutive and elevated tyrosine kinase activity is suffi- (UBC13) and UBE2C are over-expressed in a myriad of cient to induce transformation of hematopoietic stem tumors such as breast, pancreas, colon, prostate, lym- cells (HSC) and the development of CML.1 Despite the phoma, and ovarian carcinomas.8 Higher expression of introduction of tyrosine kinase inhibitors (TKI), the dis- UBE2A is associated with poor prognosis of hepatocellu- ease may progress from a manageable chronic phase to a lar cancer.9 In leukemia, bone marrow (BM) cells from clinically challenging blast crisis phase with a poor prog- pediatric acute lymphoblastic patients show higher levels nosis,2 in which myeloid or lymphoid blasts fail to differ- of UBE2Q2 -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 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/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.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 © 2016 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 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Upregulation of Peroxisome Proliferator-Activated Receptor-Α And
Upregulation of peroxisome proliferator-activated receptor-α and the lipid metabolism pathway promotes carcinogenesis of ampullary cancer Chih-Yang Wang, Ying-Jui Chao, Yi-Ling Chen, Tzu-Wen Wang, Nam Nhut Phan, Hui-Ping Hsu, Yan-Shen Shan, Ming-Derg Lai 1 Supplementary Table 1. Demographics and clinical outcomes of five patients with ampullary cancer Time of Tumor Time to Age Differentia survival/ Sex Staging size Morphology Recurrence recurrence Condition (years) tion expired (cm) (months) (months) T2N0, 51 F 211 Polypoid Unknown No -- Survived 193 stage Ib T2N0, 2.41.5 58 F Mixed Good Yes 14 Expired 17 stage Ib 0.6 T3N0, 4.53.5 68 M Polypoid Good No -- Survived 162 stage IIA 1.2 T3N0, 66 M 110.8 Ulcerative Good Yes 64 Expired 227 stage IIA T3N0, 60 M 21.81 Mixed Moderate Yes 5.6 Expired 16.7 stage IIA 2 Supplementary Table 2. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of an ampullary cancer microarray using the Database for Annotation, Visualization and Integrated Discovery (DAVID). This table contains only pathways with p values that ranged 0.0001~0.05. KEGG Pathway p value Genes Pentose and 1.50E-04 UGT1A6, CRYL1, UGT1A8, AKR1B1, UGT2B11, UGT2A3, glucuronate UGT2B10, UGT2B7, XYLB interconversions Drug metabolism 1.63E-04 CYP3A4, XDH, UGT1A6, CYP3A5, CES2, CYP3A7, UGT1A8, NAT2, UGT2B11, DPYD, UGT2A3, UGT2B10, UGT2B7 Maturity-onset 2.43E-04 HNF1A, HNF4A, SLC2A2, PKLR, NEUROD1, HNF4G, diabetes of the PDX1, NR5A2, NKX2-2 young Starch and sucrose 6.03E-04 GBA3, UGT1A6, G6PC, UGT1A8, ENPP3, MGAM, SI, metabolism -
Apoptosis Induced by Proteasome Inhibition in Cancer Cells: Predominant Role of the P53/PUMA Pathway
Oncogene (2007) 26, 1681–1692 & 2007 Nature Publishing Group All rights reserved 0950-9232/07 $30.00 www.nature.com/onc ORIGINAL ARTICLE Apoptosis induced by proteasome inhibition in cancer cells: predominant role of the p53/PUMA pathway CG Concannon1, BF Koehler1,2, Claus Reimertz2, BM Murphy1, C Bonner1, N Thurow2, MW Ward1, AVillunger 3, AStrasser 4,DKo¨ gel2,5 and JHM Prehn1,5 1Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland; 2Experimental Neurosurgery, Centre for Neurology and Neurosurgery, Johann Wolfgang Goethe University Clinics, Theodor-Stern-Kai 7, Frankfurt/Main, Germany; 3Division of Experimental Pathophysiology and Immunology, Biocenter, Innsbruck Medical University, Innsbruck, Austria and 4The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia The proteasome has emerged as a novel target for Introduction antineoplastic treatment of hematological malignancies and solid tumors, including those of the central nervous The correct functioning of the ubiquitin-proteasome system. To identify cell death pathways activated in pathway is essential for the degradation of the majority response to inhibition of the proteasome system in cancer of intracellular proteins. Several key regulatory proteins cells, we treated human SH-SY5Y neuroblastoma cells involved in cell proliferation and differentiation are with the selective proteasome inhibitor (PI) epoxomicin regulated by proteasome-mediated proteolysis resulting (Epoxo). Prolonged exposure to Epoxo was associated in the activation or inhibition of specific cell signaling with increased levels of poly-ubiquitinylated proteins and pathways (Adams, 2004a). The proteasome is also p53, release of cytochrome c from the mitochondria, and central to the regulation of cell death and apoptosis. -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells. -
Uncovering Ubiquitin and Ubiquitin-Like Signaling Networks Alfred C
REVIEW pubs.acs.org/CR Uncovering Ubiquitin and Ubiquitin-like Signaling Networks Alfred C. O. Vertegaal* Department of Molecular Cell Biology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands CONTENTS 8. Crosstalk between Post-Translational Modifications 7934 1. Introduction 7923 8.1. Crosstalk between Phosphorylation and 1.1. Ubiquitin and Ubiquitin-like Proteins 7924 Ubiquitylation 7934 1.2. Quantitative Proteomics 7924 8.2. Phosphorylation-Dependent SUMOylation 7935 8.3. Competition between Different Lysine 1.3. Setting the Scenery: Mass Spectrometry Modifications 7935 Based Investigation of Phosphorylation 8.4. Crosstalk between SUMOylation and the and Acetylation 7925 UbiquitinÀProteasome System 7935 2. Ubiquitin and Ubiquitin-like Protein Purification 9. Conclusions and Future Perspectives 7935 Approaches 7925 Author Information 7935 2.1. Epitope-Tagged Ubiquitin and Ubiquitin-like Biography 7935 Proteins 7925 Acknowledgment 7936 2.2. Traps Based on Ubiquitin- and Ubiquitin-like References 7936 Binding Domains 7926 2.3. Antibody-Based Purification of Ubiquitin and Ubiquitin-like Proteins 7926 1. INTRODUCTION 2.4. Challenges and Pitfalls 7926 Proteomes are significantly more complex than genomes 2.5. Summary 7926 and transcriptomes due to protein processing and extensive 3. Ubiquitin Proteomics 7927 post-translational modification (PTM) of proteins. Hundreds ff fi 3.1. Proteomic Studies Employing Tagged of di erent modi cations exist. Release 66 of the RESID database1 (http://www.ebi.ac.uk/RESID/) contains 559 dif- Ubiquitin 7927 ferent modifications, including small chemical modifications 3.2. Ubiquitin Binding Domains 7927 such as phosphorylation, acetylation, and methylation and mod- 3.3. Anti-Ubiquitin Antibodies 7927 ification by small proteins, including ubiquitin and ubiquitin- 3.4. -
Type of the Paper (Article
Supplementary Material A Proteomics Study on the Mechanism of Nutmeg-induced Hepatotoxicity Wei Xia 1, †, Zhipeng Cao 1, †, Xiaoyu Zhang 1 and Lina Gao 1,* 1 School of Forensic Medicine, China Medical University, Shenyang 110122, P. R. China; lessen- [email protected] (W.X.); [email protected] (Z.C.); [email protected] (X.Z.) † The authors contributed equally to this work. * Correspondence: [email protected] Figure S1. Table S1. Peptide fraction separation liquid chromatography elution gradient table. Time (min) Flow rate (mL/min) Mobile phase A (%) Mobile phase B (%) 0 1 97 3 10 1 95 5 30 1 80 20 48 1 60 40 50 1 50 50 53 1 30 70 54 1 0 100 1 Table 2. Liquid chromatography elution gradient table. Time (min) Flow rate (nL/min) Mobile phase A (%) Mobile phase B (%) 0 600 94 6 2 600 83 17 82 600 60 40 84 600 50 50 85 600 45 55 90 600 0 100 Table S3. The analysis parameter of Proteome Discoverer 2.2. Item Value Type of Quantification Reporter Quantification (TMT) Enzyme Trypsin Max.Missed Cleavage Sites 2 Precursor Mass Tolerance 10 ppm Fragment Mass Tolerance 0.02 Da Dynamic Modification Oxidation/+15.995 Da (M) and TMT /+229.163 Da (K,Y) N-Terminal Modification Acetyl/+42.011 Da (N-Terminal) and TMT /+229.163 Da (N-Terminal) Static Modification Carbamidomethyl/+57.021 Da (C) 2 Table S4. The DEPs between the low-dose group and the control group. Protein Gene Fold Change P value Trend mRNA H2-K1 0.380 0.010 down Glutamine synthetase 0.426 0.022 down Annexin Anxa6 0.447 0.032 down mRNA H2-D1 0.467 0.002 down Ribokinase Rbks 0.487 0.000