Distinct Patterns of Epigenetic Marks and Transcription Factor Binding Sites Across Promoters of Sense-Intronic Long Noncoding Rnas
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Tumor Elastography and Its Association with Cell-Free Tumor DNA in the Plasma of Breast Tumor Patients: a Pilot Study
3534 Original Article Tumor elastography and its association with cell-free tumor DNA in the plasma of breast tumor patients: a pilot study Yi Hao1#, Wei Yang2#, Wenyi Zheng2,3#, Xiaona Chen3,4, Hui Wang1,5, Liang Zhao1,5, Jinfeng Xu6,7, Xia Guo4 1Department of Ultrasound, South China Hospital of Shenzhen University, Shenzhen, China; 2Department of Ultrasound, Shenzhen Hospital, Southern Medical University, Shenzhen, China; 3The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China; 4Shenzhen Key Laboratory of Viral Oncology, Center for Clinical Research and Innovation (CCRI), Shenzhen Hospital, Southern Medical University, Shenzhen, China; 5Department of Ultrasound, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, China; 6Department of Ultrasound, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, Shenzhen, China; 7The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China #These authors contributed equally to this work. Correspondence to: Xia Guo. Shenzhen Key Laboratory of Viral Oncology, Center for Clinical Research and Innovation (CCRI), Shenzhen Hospital, Southern Medical University, Shenzhen 518000, China. Email: [email protected]; Jinfeng Xu. Department of Ultrasound, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, Shenzhen 518020, China; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China. Email: [email protected]. Background: Breast tumor stiffness, which can be objectively and noninvasively evaluated by ultrasound elastography (UE), has been useful for the differentiation of benign and malignant breast lesions and the prediction of clinical outcomes. Liquid biopsy analyses, including cell-free tumor DNA (ctDNA), exhibit great potential for personalized treatment. This study aimed to investigate the correlations between the UE and ctDNA for early breast cancer diagnosis. -
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 -
Functional Annotations of Single-Nucleotide Polymorphism
CLINICAL RESEARCH e-ISSN 1643-3750 © Med Sci Monit, 2020; 26: e922710 DOI: 10.12659/MSM.922710 Received: 2020.01.08 Accepted: 2020.02.20 Functional Annotations of Single-Nucleotide Available online: 2020.03.30 Published: 2020.05.25 Polymorphism (SNP)-Based and Gene-Based Genome-Wide Association Studies Show Genes Affecting Keratitis Susceptibility Authors’ Contribution: BCDEF 1 Yue Xu* 1 Department of Ophthalmology, First Affiliated Hospital of Soochow University, Study Design A BCDEF 2 Xiao-Lin Yang* Suzhou, Jiangsu, P.R. China Data Collection B 2 Center for Genetic Epidemiology and Genomics, School of Public Health, Medical Statistical Analysis C BCD 1 Xiao-Long Yang College of Soochow University, Suzhou, Jiangsu, P.R. China Data Interpretation D BC 1 Ya-Ru Ren Manuscript Preparation E BC 1 Xin-Yu Zhuang Literature Search F Funds Collection G ADE 2 Lei Zhang ADE 1 Xiao-Feng Zhang * Yue Xu and Xiao-Lin Yang contributed equally Corresponding Authors: Xiao-Feng Zhang, e-mail: [email protected], Lei Zhang, e-mail: [email protected] Source of support: Departmental sources Background: Keratitis is a complex condition in humans and is the second most common cause of legal blindness worldwide. Material/Methods: To reveal the genomic loci underlying keratitis, we performed functional annotations of SNP-based and gene- based genome-wide association studies of keratitis in the UK Biobank (UKB) cohort with 337 199 subjects of European ancestry. Results: The publicly available SNP-based association results showed a total of 34 SNPs, from 14 distinct loci, associated with keratitis in the UKB. Gene-based association analysis identified 2 significant genes:IQCF3 (p=2.0×10–6) and SOD3 (p=2.0×10–6). -
Molecular Characterization of Acute Myeloid Leukemia by Next Generation Sequencing: Identification of Novel Biomarkers and Targets of Personalized Therapies
Alma Mater Studiorum – Università di Bologna Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale Dottorato di Ricerca in Oncologia, Ematologia e Patologia XXX Ciclo Settore Scientifico Disciplinare: MED/15 Settore Concorsuale:06/D3 Molecular characterization of acute myeloid leukemia by Next Generation Sequencing: identification of novel biomarkers and targets of personalized therapies Presentata da: Antonella Padella Coordinatore Prof. Pier-Luigi Lollini Supervisore: Prof. Giovanni Martinelli Esame finale anno 2018 Abstract Acute myeloid leukemia (AML) is a hematopoietic neoplasm that affects myeloid progenitor cells and it is one of the malignancies best studied by next generation sequencing (NGS), showing a highly heterogeneous genetic background. The aim of the study was to characterize the molecular landscape of 2 subgroups of AML patients carrying either chromosomal number alterations (i.e. aneuploidy) or rare fusion genes. We performed whole exome sequencing and we integrated the mutational data with transcriptomic and copy number analysis. We identified the cell cycle, the protein degradation, response to reactive oxygen species, energy metabolism and biosynthetic process as the pathways mostly targeted by alterations in aneuploid AML. Moreover, we identified a 3-gene expression signature including RAD50, PLK1 and CDC20 that characterize this subgroup. Taking advantage of RNA sequencing we aimed at the discovery of novel and rare gene fusions. We detected 9 rare chimeric transcripts, of which partner genes were transcription factors (ZEB2, BCL11B and MAFK) or tumor suppressors (SAV1 and PUF60) rarely translocated across cancer types. Moreover, we detected cryptic events hiding the loss of NF1 and WT1, two recurrently altered genes in AML. Finally, we explored the oncogenic potential of the ZEB2-BCL11B fusion, which revealed no transforming ability in vitro. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
OR4F16 Antibody Cat
OR4F16 Antibody Cat. No.: 57-758 OR4F16 Antibody Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human This OR4F16 antibody is generated from rabbits immunized with a KLH conjugated IMMUNOGEN: synthetic peptide between 68-96 amino acids from the N-terminal region of human OR4F16. TESTED APPLICATIONS: WB APPLICATIONS: For WB starting dilution is: 1:1000 PREDICTED MOLECULAR 35 kDa WEIGHT: Properties This antibody is purified through a protein A column, followed by peptide affinity PURIFICATION: purification. CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated September 27, 2021 1 https://www.prosci-inc.com/or4f16-antibody-57-758.html PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: OR4F3 ALTERNATE NAMES: Olfactory receptor 4F3/4F16/4F29, Olfactory receptor OR1-1, OR4F3 ACCESSION NO.: Q6IEY1 PROTEIN GI NO.: 74762307 GENE ID: 26683, 729759, 81399 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References Olfactory receptors interact with odorant molecules in the nose, to initiate a neuronal response that triggers the perception of a smell. The olfactory receptor proteins are members of a large family of G-protein-coupled receptors (GPCR) arising from single coding-exon genes. Olfactory receptors share a 7-transmembrane domain structure with BACKGROUND: many neurotransmitter and hormone receptors and are responsible for the recognition and G protein-mediated transduction of odorant signals. -
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 -
Wo2017/132291
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date W O 2017/132291 A l 3 August 2017 (03.08.2017) P O P C T (51) International Patent Classification: [US/US]; 77 Massachusetts Avenue, Cambridge, MA A61K 48/00 (2006.01) C12Q 1/68 (2006.01) 02139 (US). THE GENERAL HOSPITAL CORPORA¬ A61K 39/395 (2006.01) G01N 33/574 (2006.01) TION [US/US]; 55 Fruit Street, Boston, MA 021 14 (US). C12N 15/11 (2006.01) (72) Inventors; and (21) International Application Number: (71) Applicants : REGEV, Aviv [US/US]; 415 Main Street, PCT/US2017/014995 Cambridge, MA 02142 (US). BERNSTEIN, Bradley [US/US]; 55 Fruit Street, Boston, MA 021 14 (US). (22) International Filing Date: TIROSH, Itay [US/US]; 415 Main Street, Cambridge, 25 January 20 17 (25.01 .2017) MA 02142 (US). SUVA, Mario [US/US]; 55 Fruit Street, (25) Filing Language: English Bostn, MA 02144 (US). ROZENBALTT-ROSEN, Orit [US/US]; 415 Main Street, Cambridge, MA 02142 (US). (26) Publication Language: English (74) Agent: NIX, F., Brent; Johnson, Marcou & Isaacs, LLC, (30) Priority Data: 317A East Liberty St., Savannah, GA 31401 (US). 62/286,850 25 January 2016 (25.01.2016) US 62/437,558 2 1 December 201 6 (21. 12.2016) US (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, (71) Applicants: THE BROAD INSTITUTE, INC. [US/US]; AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, 415 Main Street, Cambridge, MA 02142 (US). -
King's Research Portal
King’s Research Portal DOI: 10.1136/annrheumdis-2017-211214 Document Version Peer reviewed version Link to publication record in King's Research Portal Citation for published version (APA): Hollander, W. D., Boer, C. G., Hart, D. J., Yau, M. S., Ramos, Y. F. M., Metrustry, S., Broer, L., Deelen, J., Cupples, L. A., Rivadeneira, F., Kloppenburg, M., Peters, M., Spector, T. D., Hofman, A., Slagboom, P. E., Nelissen, R. G. H. H., Uitterlinden, A. G., Felson, D. T., Valdes, A. M., ... van Meurs, J. J. B. (2017). Genome- wide association and functional studies identify a role for matrix Gla protein in osteoarthritis of the hand. Annals of the rheumatic diseases, 76(12), 2046-2053. https://doi.org/10.1136/annrheumdis-2017-211214 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections. General rights Copyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights. •Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research. -
Bioinformatics Analysis for the Identification of Differentially Expressed Genes and Related Signaling Pathways in H
Bioinformatics analysis for the identification of differentially expressed genes and related signaling pathways in H. pylori-CagA transfected gastric cancer cells Dingyu Chen*, Chao Li, Yan Zhao, Jianjiang Zhou, Qinrong Wang and Yuan Xie* Key Laboratory of Endemic and Ethnic Diseases , Ministry of Education, Guizhou Medical University, Guiyang, China * These authors contributed equally to this work. ABSTRACT Aim. Helicobacter pylori cytotoxin-associated protein A (CagA) is an important vir- ulence factor known to induce gastric cancer development. However, the cause and the underlying molecular events of CagA induction remain unclear. Here, we applied integrated bioinformatics to identify the key genes involved in the process of CagA- induced gastric epithelial cell inflammation and can ceration to comprehend the potential molecular mechanisms involved. Materials and Methods. AGS cells were transected with pcDNA3.1 and pcDNA3.1::CagA for 24 h. The transfected cells were subjected to transcriptome sequencing to obtain the expressed genes. Differentially expressed genes (DEG) with adjusted P value < 0.05, | logFC |> 2 were screened, and the R package was applied for gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The differential gene protein–protein interaction (PPI) network was constructed using the STRING Cytoscape application, which conducted visual analysis to create the key function networks and identify the key genes. Next, the Submitted 20 August 2020 Kaplan–Meier plotter survival analysis tool was employed to analyze the survival of the Accepted 11 March 2021 key genes derived from the PPI network. Further analysis of the key gene expressions Published 15 April 2021 in gastric cancer and normal tissues were performed based on The Cancer Genome Corresponding author Atlas (TCGA) database and RT-qPCR verification. -
1 Novel Expression Signatures Identified by Transcriptional Analysis
ARD Online First, published on October 7, 2009 as 10.1136/ard.2009.108043 Ann Rheum Dis: first published as 10.1136/ard.2009.108043 on 7 October 2009. Downloaded from Novel expression signatures identified by transcriptional analysis of separated leukocyte subsets in SLE and vasculitis 1Paul A Lyons, 1Eoin F McKinney, 1Tim F Rayner, 1Alexander Hatton, 1Hayley B Woffendin, 1Maria Koukoulaki, 2Thomas C Freeman, 1David RW Jayne, 1Afzal N Chaudhry, and 1Kenneth GC Smith. 1Cambridge Institute for Medical Research and Department of Medicine, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK 2Roslin Institute, University of Edinburgh, Roslin, Midlothian, EH25 9PS, UK Correspondence should be addressed to Dr Paul Lyons or Prof Kenneth Smith, Department of Medicine, Cambridge Institute for Medical Research, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK. Telephone: +44 1223 762642, Fax: +44 1223 762640, E-mail: [email protected] or [email protected] Key words: Gene expression, autoimmune disease, SLE, vasculitis Word count: 2,906 The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Annals of the Rheumatic Diseases and any other BMJPGL products to exploit all subsidiary rights, as set out in their licence (http://ard.bmj.com/ifora/licence.pdf). http://ard.bmj.com/ on September 29, 2021 by guest. Protected copyright. 1 Copyright Article author (or their employer) 2009.