A Gain of Function Senescence Bypass Screen Identifies the Homeobox Transcription Factor DLX2 As a Regulator of ATM-P53 Signaling
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Gene Therapy in Cancer Treatment: Why Go Nano?
pharmaceutics Review Gene Therapy in Cancer Treatment: Why Go Nano? Catarina Roma-Rodrigues 1 , Lorenzo Rivas-García 1,2 , Pedro V. Baptista 1,* and Alexandra R. Fernandes 1,* 1 UCIBIO, Departamento de Ciências da Vida, Faculdade de Ciências e Tecnologia, Campus de Caparica, 2829-516 Caparica, Portugal; [email protected] (C.R.-R.); [email protected] (L.R.-G.) 2 Biomedical Research Centre, Institute of Nutrition and Food Technology, Department of Physiology, Faculty of Pharmacy, University of Granada, Avda. del Conocimiento s/n. 18071 Armilla, Granada, Spain * Correspondence: [email protected] (P.V.B.); [email protected] (A.R.F.); Tel.: +351-212-948-530 (P.V.B. & A.R.F.) Received: 29 January 2020; Accepted: 3 March 2020; Published: 5 March 2020 Abstract: The proposal of gene therapy to tackle cancer development has been instrumental for the development of novel approaches and strategies to fight this disease, but the efficacy of the proposed strategies has still fallen short of delivering the full potential of gene therapy in the clinic. Despite the plethora of gene modulation approaches, e.g., gene silencing, antisense therapy, RNA interference, gene and genome editing, finding a way to efficiently deliver these effectors to the desired cell and tissue has been a challenge. Nanomedicine has put forward several innovative platforms to overcome this obstacle. Most of these platforms rely on the application of nanoscale structures, with particular focus on nanoparticles. Herein, we review the current trends on the use of nanoparticles designed for cancer gene therapy, including inorganic, organic, or biological (e.g., exosomes) variants, in clinical development and their progress towards clinical applications. -
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
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. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
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. -
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. -
TITLE PAGE Oxidative Stress and Response to Thymidylate Synthase
Downloaded from molpharm.aspetjournals.org at ASPET Journals on October 2, 2021 -Targeted -Targeted 1 , University of of , University SC K.W.B., South Columbia, (U.O., Carolina, This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. -
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 -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
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 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.