Datasheet A11267-1 Anti-ZNF318 Antibody

Total Page：16

File Type：pdf, Size：1020Kb

Product datasheet Anti-ZNF318 Antibody Catalog Number: A11267-1 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Basic Information Product Name Anti-ZNF318 Antibody Gene Name ZNF318 Source Rabbit IgG Species Reactivity human, rat Tested Application WB, FCM, Direct ELISA Contents 500 ug/ml antibody with PBS ，0.02% NaN3 , 1 mg BSA and 50% glycerol. Immunogen E.coli-derived human ZNF318 recombinant protein (Position: E680-Q1197). Purification Immunogen affinity purified. Observed MW 290KD Dilution Ratios Western blot: 1:500-2000 Flow cytometry (FCM)： 1-3μg/1x106 cells Direct ELISA： 1:100-1000 Storage 12 months from date of receipt，-20℃ as supplied.6 months 2 to 8℃ after reconstitution. Avoid repeated freezing and thawing Background Information Zinc finger protein 318 is a protein that in humans is encoded by the ZNF318 gene. ZNF318 encodes a nuclear protein with a zinc finger motif of the Cys2-His2 type that is a novel corepressor of androgen receptor (AR). Reference Anti-ZNF318 Antibody被引用在0文献中。暂无引用 FOR RESEARCH USE ONLY. NOT FOR DIAGNOSTIC AND CLINICAL USE. 1 Product datasheet Anti-ZNF318 Antibody Catalog Number: A11267-1 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Selected Validation Data Figure 1. Western blot Figure 2. Flow cytometry analysis of anti- ZNF318 analysis of A431 cell Antibody (A11267-1). The (1x106) DyLight 488 sample well of each lane conjugated goat anti- was loaded with 50ug of rabbit IgG(blue) was used sample under reducing as secondary conditions. antibody.Isotype control Lane 1: THP-1 whole cell antibody (Green line) was lysates, rabbit IgG DyLight 488. Lane 2: rat stomach tissue Unlabelled sample (Red lysates, line). Lane 3: C6 whole cell lysates, Use rabbit anti- ZNF318 1:1000, probed with a goat anti-rabbit IgG-HRP secondary antibody. The signal is developed using an Enhanced Chemiluminescent detection (ECL) kit (Catalog # EK1002). A specific band was detected for ZNF318 at approximately 290KD. The expected band size for ZNF318 is at 251KD. FOR RESEARCH USE ONLY. NOT FOR DIAGNOSTIC AND CLINICAL USE. 2 Powered by TCPDF (www.tcpdf.org).

Copy Link

Recommended publications

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.
[Show full text]
Enzyme DHRS7
Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d.
[Show full text]
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.
[Show full text]
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
[Show full text]
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.
[Show full text]
Supplementary Table 1
Supplementary Table 1. 492 genes are unique to 0 h post-heat timepoint. The name, p-value, fold change, location and family of each gene are indicated. Genes were filtered for an absolute value log2 ration 1.5 and a significance value of p ≤ 0.05. Symbol p-value Log Gene Name Location Family Ratio ABCA13 1.87E-02 3.292 ATP-binding cassette, sub-family unknown transporter A (ABC1), member 13 ABCB1 1.93E-02 −1.819 ATP-binding cassette, sub-family Plasma transporter B (MDR/TAP), member 1 Membrane ABCC3 2.83E-02 2.016 ATP-binding cassette, sub-family Plasma transporter C (CFTR/MRP), member 3 Membrane ABHD6 7.79E-03 −2.717 abhydrolase domain containing 6 Cytoplasm enzyme ACAT1 4.10E-02 3.009 acetyl-CoA acetyltransferase 1 Cytoplasm enzyme ACBD4 2.66E-03 1.722 acyl-CoA binding domain unknown other containing 4 ACSL5 1.86E-02 −2.876 acyl-CoA synthetase long-chain Cytoplasm enzyme family member 5 ADAM23 3.33E-02 −3.008 ADAM metallopeptidase domain Plasma peptidase 23 Membrane ADAM29 5.58E-03 3.463 ADAM metallopeptidase domain Plasma peptidase 29 Membrane ADAMTS17 2.67E-04 3.051 ADAM metallopeptidase with Extracellular other thrombospondin type 1 motif, 17 Space ADCYAP1R1 1.20E-02 1.848 adenylate cyclase activating Plasma G-protein polypeptide 1 (pituitary) receptor Membrane coupled type I receptor ADH6 (includes 4.02E-02 −1.845 alcohol dehydrogenase 6 (class Cytoplasm enzyme EG:130) V) AHSA2 1.54E-04 −1.6 AHA1, activator of heat shock unknown other 90kDa protein ATPase homolog 2 (yeast) AK5 3.32E-02 1.658 adenylate kinase 5 Cytoplasm kinase AK7
[Show full text]
Engineered Type 1 Regulatory T Cells Designed for Clinical Use Kill Primary
ARTICLE Acute Myeloid Leukemia Engineered type 1 regulatory T cells designed Ferrata Storti Foundation for clinical use kill primary pediatric acute myeloid leukemia cells Brandon Cieniewicz,1* Molly Javier Uyeda,1,2* Ping (Pauline) Chen,1 Ece Canan Sayitoglu,1 Jeffrey Mao-Hwa Liu,1 Grazia Andolfi,3 Katharine Greenthal,1 Alice Bertaina,1,4 Silvia Gregori,3 Rosa Bacchetta,1,4 Norman James Lacayo,1 Alma-Martina Cepika1,4# and Maria Grazia Roncarolo1,2,4# Haematologica 2021 Volume 106(10):2588-2597 1Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 2Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 3San Raffaele Telethon Institute for Gene Therapy, Milan, Italy and 4Center for Definitive and Curative Medicine, Stanford School of Medicine, Stanford, CA, USA *BC and MJU contributed equally as co-first authors #AMC and MGR contributed equally as co-senior authors ABSTRACT ype 1 regulatory (Tr1) T cells induced by enforced expression of interleukin-10 (LV-10) are being developed as a novel treatment for Tchemotherapy-resistant myeloid leukemias. In vivo, LV-10 cells do not cause graft-versus-host disease while mediating graft-versus-leukemia effect against adult acute myeloid leukemia (AML). Since pediatric AML (pAML) and adult AML are different on a genetic and epigenetic level, we investigate herein whether LV-10 cells also efficiently kill pAML cells. We show that the majority of primary pAML are killed by LV-10 cells, with different levels of sensitivity to killing. Transcriptionally, pAML sensitive to LV-10 killing expressed a myeloid maturation signature.
[Show full text]
Supp Data.Pdf
Supplementary Methods Verhaak sub-classification The Verhaak called tumor subtype was assigned as determined in the Verhaak et al. manuscript, for those TCGA tumors that were included at the time. TCGA data for expression (Affymetrix platform, level 1) and methylation (Infinium platform level 3) were downloaded from the TCGA portal on 09/29/2011. Affymetrix data were processed using R and Biocondutor with a RMA algorithm using quantile normalization and custom CDF. Level 3 methylation data has already been processed and converted to a beta-value. The genes that make up the signature for each of the 4 Verhaak groups (i.e. Proneural, Neural, Mesenchymal, and Classical) were downloaded. For each tumor, the averaged expression of the 4 genes signatures was calculated generating 4 ‘metagene’ scores, one for each subtype, (Colman et al.2010) for every tumor. Then each subtype metagene score was z-score corrected to allow comparison among the 4 metagenes. Finally, for each tumor the subtype with the highest metagene z-score among the four was used to assign subtype. Thus by this method, a tumor is assigned to the group to which it has the strongest expression signature. The shortcoming is that if a tumor has a ‘dual personality’ – for instance has strong expression of both classical and mesenchymal signature genes, there is some arbitrariness to the tumor’s assignment. Western Blot Analysis and cell fractionation Western blot analysis was performed using standard protocols. To determine protein expression we used the following antibodies: TAZ (Sigma and BD Biosciences), YAP (Santa Cruz Biotechnology), CD44 (Cell Signaling), FN1 (BD Biosciences), TEAD1, TEAD2, TEAD3, TEAD4 (Santa Cruz Biotechnology), MST1, p-MST1, MOB1, LATS1, LATS2, 14-3-3-, 1 ACTG2, (Cell Signaling), p-LATS1/2 (Abcam), Flag (Sigma Aldrich), Actin (Calbiochem), CAV2 (BD Biosciences), CTGF (Santa Cruz), RUNX2 (Sigma Aldrich), Cylin A, Cyclin E, Cyclin B1, p-cdk1, p-cdk4 (Cell Signaling Technologies).
[Show full text]
UNIVERSIDADE DO ALGARVE Expression Profile And
UNIVERSIDADE DO ALGARVE Expression profile and pharmacogenetics of genes candidate to play a role in cardiovascular disease Vera Lúcia Martins Dias Doutoramento em Ciências Biológicas Especialidade de Biologia Celular e Molecular 2010 UNIVERSIDADE DO ALGARVE Expression profile and pharmacogenetics of genes candidate to play a role in cardiovascular disease Vera Lúcia Martins Dias Tese orientada pela Professora Doutora Vera Linda Ribeiro Marques Doutoramento em Ciências Biológicas Especialidade de Biologia Celular e Molecular 2010 Acknowledgments Acknowledgements Muitas foram as pessoas que, ao longo destes anos, me apoiaram directa ou indirectamente. A todos os que tornaram este projecto possível quero manifestar o meu sincero agradecimento. À Professora Doutora Vera Ribeiro Marques, quero agradecer a confiança e a oportunidade de realizar este trabalho sob sua orientação e pela forma como o fez ao longo destes anos; além do apoio e incentivo deu-me a oportunidade e liberdade de crescer profissional e cientificamente. Por tudo isso, os meus sinceros agradecimentos. À Ana Luísa, quero agradecer por me ter ajudado ao longo destes anos, por me ouvir e aconselhar, nem sempre apenas sobre assuntos científicos. Muito obrigada pela tua amizade. Ao Jorge, quero agradecer por todas as contribuições dadas e pelo bom ambiente de trabalho que sempre proporcionaste. Á Filomena, à Elsa, à Cátia, que estiveram presentes nos meus primeiros anos no laboratório e me ajudaram em tudo o que precisei. Muito agradecida por me terem recebido e pela vossa amizade. E a todos aqueles que, ao longo destes nos, passaram pelo laboratório, por terem tornado este percurso muito mais agradável, tendo proporcionado sempre um bom ambiente de laboratório.
[Show full text]
Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib
Supplementary Online Content Chen G, McQuade JL, Panka DJ, et al. Clinical, molecular and immune analysis of dabrafenib-trametinib combination treatment for metastatic melanoma that progressed during BRAF inhibitor monotherapy: a phase 2 clinical trial. JAMA Oncology. Published online April 28, 2016. doi:10.1001/jamaoncol.2016.0509. eMethods. eReferences. eTable 1. Clinical efficacy eTable 2. Adverse events eTable 3. Correlation of baseline patient characteristics with treatment outcomes eTable 4. Patient responses and baseline IHC results eFigure 1. Kaplan-Meier analysis of overall survival eFigure 2. Correlation between IHC and RNAseq results eFigure 3. pPRAS40 expression and PFS eFigure 4. Baseline and treatment-induced changes in immune infiltrates eFigure 5. PD-L1 expression eTable 5. Nonsynonymous mutations detected by WES in baseline tumors This supplementary material has been provided by the authors to give readers additional information about their work. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eMethods Whole exome sequencing Whole exome capture libraries for both tumor and normal samples were constructed using 100ng genomic DNA input and following the protocol as described by Fisher et al.,3 with the following adapter modification: Illumina paired end adapters were replaced with palindromic forked adapters with unique 8 base index sequences embedded within the adapter. In-solution hybrid selection was performed using the Illumina Rapid Capture Exome enrichment kit with 38Mb target territory (29Mb baited). The targeted region includes 98.3% of the intervals in the Refseq exome database. Dual-indexed libraries were pooled into groups of up to 96 samples prior to hybridization.
[Show full text]
SF3B1-Mutated Chronic Lymphocytic Leukemia Shows Evidence Of
SF3B1-mutated chronic lymphocytic leukemia shows evidence of NOTCH1 pathway activation including CD20 downregulation by Federico Pozzo, Tamara Bittolo, Erika Tissino, Filippo Vit, Elena Vendramini, Luca Laurenti, Giovanni D'Arena, Jacopo Olivieri, Gabriele Pozzato, Francesco Zaja, Annalisa Chiarenza, Francesco Di Raimondo, Antonella Zucchetto, Riccardo Bomben, Francesca Maria Rossi, Giovanni Del Poeta, Michele Dal Bo, and Valter Gattei Haematologica 2020 [Epub ahead of print] Citation: Federico Pozzo, Tamara Bittolo, Erika Tissino, Filippo Vit, Elena Vendramini, Luca Laurenti, Giovanni D'Arena, Jacopo Olivieri, Gabriele Pozzato, Francesco Zaja, Annalisa Chiarenza, Francesco Di Raimondo, Antonella Zucchetto, Riccardo Bomben, Francesca Maria Rossi, Giovanni Del Poeta, Michele Dal Bo, and Valter Gattei SF3B1-mutated chronic lymphocytic leukemia shows evidence of NOTCH1 pathway activation including CD20 downregulation. Haematologica. 2020; 105:xxx doi:10.3324/haematol.2020.261891 Publisher's Disclaimer. E-publishing ahead of print is increasingly important for the rapid dissemination of science. Haematologica is, therefore, E-publishing PDF files of an early version of manuscripts that have completed a regular peer review and have been accepted for publication. E-publishing of this PDF file has been approved by the authors. After having E-published Ahead of Print, manuscripts will then undergo technical and English editing, typesetting, proof correction and be presented for the authors' final approval; the final version of the manuscript will
[Show full text]
1 Type I Interferon Transcriptional Network Regulates Expression Of
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.30.362947; this version posted October 31, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Type I Interferon Transcriptional Network Regulates Expression of Coinhibitory Receptors in Human T cells Tomokazu S. Sumida*1, Shai Dulberg2*, Jonas Schupp3*, Helen A. Stillwell1, Pierre-Paul Axisa1, Michela Comi1, Matthew Lincoln1, Avraham Unterman3, Naftali Kaminski3, Asaf Madi2,4, Vijay K. Kuchroo4,5,†, David A. Hafler1,5,† 1Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, USA. 2 Department of Pathology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. 3Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA. 4 Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA. 5Broad Institute of MIT and Harvard, Cambridge, MA, USA. *Equal Contributions † Correspondence to Drs. Vijay Kuchroo ([email protected]) or David Hafler ([email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.10.30.362947; this version posted October 31, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
[Show full text]