Hierarchical Clustering of Gene Expression Patterns in the Eomes +
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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 -
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. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
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. -
Circular RNA Hsa Circ 0005114‑Mir‑142‑3P/Mir‑590‑5P‑ Adenomatous
ONCOLOGY LETTERS 21: 58, 2021 Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p‑ adenomatous polyposis coli protein axis as a potential target for treatment of glioma BO WEI1*, LE WANG2* and JINGWEI ZHAO1 1Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033; 2Department of Ophthalmology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130021, P.R. China Received September 12, 2019; Accepted October 22, 2020 DOI: 10.3892/ol.2020.12320 Abstract. Glioma is the most common type of brain tumor APC expression with a good overall survival rate. UALCAN and is associated with a high mortality rate. Despite recent analysis using TCGA data of glioblastoma multiforme and the advances in treatment options, the overall prognosis in patients GSE25632 and GSE103229 microarray datasets showed that with glioma remains poor. Studies have suggested that circular hsa‑miR‑142‑3p/hsa‑miR‑590‑5p was upregulated and APC (circ)RNAs serve important roles in the development and was downregulated. Thus, hsa‑miR‑142‑3p/hsa‑miR‑590‑5p‑ progression of glioma and may have potential as therapeutic APC‑related circ/ceRNA axes may be important in glioma, targets. However, the expression profiles of circRNAs and their and hsa_circ_0005114 interacted with both of these miRNAs. functions in glioma have rarely been studied. The present study Functional analysis showed that hsa_circ_0005114 was aimed to screen differentially expressed circRNAs (DECs) involved in insulin secretion, while APC was associated with between glioma and normal brain tissues using sequencing the Wnt signaling pathway. In conclusion, hsa_circ_0005114‑ data collected from the Gene Expression Omnibus database miR‑142‑3p/miR‑590‑5p‑APC ceRNA axes may be potential (GSE86202 and GSE92322 datasets) and explain their mecha‑ targets for the treatment of glioma. -
Celsr1-3 Cadherins in PCP and Brain Development
CHAPTER SEVEN Celsr1–3 Cadherins in PCP and Brain Development Camille Boutin, André M. Goffinet1, Fadel Tissir1 Institute of Neuroscience, Developmental Neurobiology, Universite´ Catholique de Louvain, Brussels, Belgium 1Corresponding authors: Equal contribution. e-mail address: [email protected]; andre. [email protected] Contents 1. Celsr1–3 Expression Patterns 164 2. Celsr1: A Major Player in Vertebrate PCP 165 3. Celsr2 and 3 in Ciliogenesis 169 4. Celsr1–3 in Neuronal Migration 171 5. Celsr2 and Celsr3 in Brain Wiring 174 5.1 Motifs of Celsr important for their functions 176 References 179 Abstract Cadherin EGF LAG seven-pass G-type receptors 1, 2, and 3 (Celsr1–3) form a family of three atypical cadherins with multiple functions in epithelia and in the nervous system. During the past decade, evidence has accumulated for important and distinct roles of Celsr1–3 in planar cell polarity (PCP) and brain development and maintenance. Although the role of Celsr in PCP is conserved from flies to mammals, other functions may be more distantly related, with Celsr working only with one or a subset of the classical PCP partners. Here, we review the literature on Celsr in PCP and neural devel- opment, point to several remaining questions, and consider future challenges and possible research trends. Celsr1–3 genes encode atypical cadherins of more than 3000 amino acids ( Fig. 7.1). Their large ectodomain is composed of nine N-terminal cadherin repeats (typical cadherins have five repeats), six epidermal growth factor (EGF)-like domains, two laminin G repeats, one hormone receptor motif (HRM), and a G-protein-coupled receptor proteolytic site (GPS). -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
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 -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Learning from Cadherin Structures and Sequences: Affinity Determinants and Protein Architecture
Learning from cadherin structures and sequences: affinity determinants and protein architecture Klára Fels ıvályi Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Klara Felsovalyi All rights reserved ABSTRACT Learning from cadherin structures and sequences: affinity determinants and protein architecture Klara Felsovalyi Cadherins are a family of cell-surface proteins mediating adhesion that are important in development and maintenance of tissues. The family is defined by the repeating cadherin domain (EC) in their extracellular region, but they are diverse in terms of protein size, architecture and cellular function. The best-understood subfamily is the type I classical cadherins, which are found in vertebrates and have five EC domains. Among the five different type I classical cadherins, the binding interactions are highly specific in their homo- and heterophilic binding affinities, though their sequences are very similar. As previously shown, E- and N-cadherins, two prototypic members of the subfamily, differ in their homophilic K D by about an order of magnitude, while their heterophilic affinity is intermediate. To examine the source of the binding affinity differences among type I cadherins, we used crystal structures, analytical ultracentrifugation (AUC), surface plasmon resonance (SPR), and electron paramagnetic resonance (EPR) studies. Phylogenetic analysis and binding affinity behavior show that the type I cadherins can be further divided into two subgroups, with E- and N-cadherin representing each. In addition to the affinity differences in their wild-type binding through the strand-swapped interface, a second interface also shows an affinity difference between E- and N-cadherin. -
CDH12 Cadherin 12, Type 2 N-Cadherin 2 RPL5 Ribosomal
5 6 6 5 . 4 2 1 1 1 2 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 A A A A A A A A A A A A A A A A A A A A C C C C C C C C C C C C C C C C C C C C R R R R R R R R R R R R R R R R R R R R B , B B B B B B B B B B B B B B B B B B B , 9 , , , , 4 , , 3 0 , , , , , , , , 6 2 , , 5 , 0 8 6 4 , 7 5 7 0 2 8 9 1 3 3 3 1 1 7 5 0 4 1 4 0 7 1 0 2 0 6 7 8 0 2 5 7 8 0 3 8 5 4 9 0 1 0 8 8 3 5 6 7 4 7 9 5 2 1 1 8 2 2 1 7 9 6 2 1 7 1 1 0 4 5 3 5 8 9 1 0 0 4 2 5 0 8 1 4 1 6 9 0 0 6 3 6 9 1 0 9 0 3 8 1 3 5 6 3 6 0 4 2 6 1 0 1 2 1 9 9 7 9 5 7 1 5 8 9 8 8 2 1 9 9 1 1 1 9 6 9 8 9 7 8 4 5 8 8 6 4 8 1 1 2 8 6 2 7 9 8 3 5 4 3 2 1 7 9 5 3 1 3 2 1 2 9 5 1 1 1 1 1 1 5 9 5 3 2 6 3 4 1 3 1 1 4 1 4 1 7 1 3 4 3 2 7 6 4 2 7 2 1 2 1 5 1 6 3 5 6 1 3 6 4 7 1 6 5 1 1 4 1 6 1 7 6 4 7 e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e e l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m -
Complexin-1 Is a Biomarker of Synucleinopathy
DMM Advance Online Articles. Posted 20 January 2017 as doi: 10.1242/dmm.028035 Access the most recent version at http://dmm.biologists.org/lookup/doi/10.1242/dmm.028035 BLOOD RNA BIOMARKERS IN PRODROMAL PARK4 AND REM SLEEP BEHAVIOR DISORDER SHOW ROLE OF COMPLEXIN-1 LOSS FOR RISK OF PARKINSON’S DISEASE Suna Lahut1,2, Suzana Gispert1, Özgür Ömür1,2, Candan Depboylu3, Kay Seidel4, Jorge Antolio Domínguez-Bautista1, Nadine Brehm1, Hülya Tireli5, Karl Hackmann6, Caroline Pirkevi2, Barbara Leube7, Vincent Ries3, Kerstin Reim8, Nils Brose8, Wilfred F. den Dunnen9, Madrid Johnson10, Zsuzsanna Wolf11, Marc Schindewolf12, Wiebke Schrempf13, Kathrin Reetz14, Peter Young15, David Vadasz3, Achilleas S. Frangakis10, Evelin Schröck6, Helmuth Steinmetz1, Marina Jendrach1, Udo Rüb4, Ayşe Nazlı Başak2¶, Wolfgang Oertel3¶, Georg Auburger1¶ 1Exp. Neurology, Goethe University Medical School, 60590 Frankfurt/Main, Germany; 2NDAL, Boğaziçi University, 34342 Istanbul, Turkey; 3Dept. of Neurology, Philipps University, Baldingerstrasse, 35043 Marburg, Germany; 4Dr. Senckenberg Chronomedical Institute, Goethe University, 60590 Frankfurt/Main, Germany; 5Dept. of Neurology, Haydarpaşa Numune Training and Research Hospital, 34668 Istanbul, Turkey; 6Institute for Clinical Genetics, Faculty of Medicine Carl Gustav Carus, TU Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; 7Institute of Human Genetics, Heinrich Heine University, 40225 Düsseldorf, Germany; 8Dept. of Molecular Neurobiology and Center for the Molecular Physiology of the Brain, Max Planck Institute of Experimental Medicine, 37075 Göttingen, Germany; 9Dept. of Pathology and Medical Biology, Medical Center, University, 9700 RB Groningen, Netherlands; 10Institut für Biophysik and Frankfurt Institute for Molecular Life Sciences, Goethe University, 60438 Frankfurt/Main, Germany; 11Hemophilia Centre, Medical Clinic III, Institute of Transfusion Medicine and Immunhematology Goethe University, 60590 Frankfurt/Main, Germany; 12Dept.