Identification of Novel Fusion Genes with 28S Ribosomal DNA in Hematologic Malignancies
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The T-ALL Related Gene BCL11B Regulates the Initial Stages of Human T-Cell Differentiation
Leukemia (2017) 31, 2503–2514 © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved 0887-6924/17 www.nature.com/leu ORIGINAL ARTICLE The T-ALL related gene BCL11B regulates the initial stages of human T-cell differentiation VL Ha1, A Luong1,FLi2, D Casero3, J Malvar1,YMKim1,4, R Bhatia5, GM Crooks3,6,7,8 and C Parekh1,4 The initial stages of T-cell differentiation are characterized by a progressive commitment to the T-cell lineage, a process that involves the loss of alternative (myelo-erythroid, NK, B) lineage potentials. Aberrant differentiation during these stages can result in T-cell acute lymphoblastic leukemia (T-ALL). However, the mechanisms regulating the initial stages of human T-cell differentiation are obscure. Through loss of function studies, we showed BCL11B, a transcription factor recurrently mutated T-ALL, is essential for T-lineage commitment, particularly the repression of NK and myeloid potentials, and the induction of T-lineage genes, during the initial stages of human T-cell differentiation. In gain of function studies, BCL11B inhibited growth of and induced a T-lineage transcriptional program in T-ALL cells. We found previously unknown differentiation stage-specific DNA binding of BCL11B at multiple T-lineage genes; target genes showed BCL11B-dependent expression, suggesting a transcriptional activator role for BCL11B at these genes. Transcriptional analyses revealed differences in the regulatory actions of BCL11B between human and murine thymopoiesis. Our studies show BCL11B is a key regulator of the initial stages of human T-cell differentiation and delineate the BCL11B transcriptional program, enabling the dissection of the underpinnings of normal T-cell differentiation and providing a resource for understanding dysregulations in T-ALL. -
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. -
The Histone Methyltransferase DOT1L Prevents Antigen-Independent
bioRxiv preprint doi: https://doi.org/10.1101/826255; this version posted November 18, 2019. 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. The histone methyltransferase DOT1L prevents antigen-independent differentiation and safeguards epigenetic identity of CD8+ T cells Eliza Mari Kwesi-Maliepaard1*, Muhammad Assad Aslam2,3*, Mir Farshid Alemdehy2*, Teun van den Brand4, Chelsea McLean1, Hanneke Vlaming1, Tibor van Welsem1, Tessy Korthout1, Cesare Lancini1, Sjoerd Hendriks1, Tomasz Ahrends5, Dieke van Dinther6, Joke M.M. den Haan6, Jannie Borst5, Elzo de Wit4, Fred van Leeuwen1,7,#, and Heinz Jacobs2,# 1Division of Gene Regulation, Netherlands Cancer Institute, 1066CX Amsterdam, The Netherlands 2Division of Tumor Biology & Immunology, Netherlands Cancer Institute, 1066CX Amsterdam, The Netherlands 3Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University, 60800 Multan, Pakistan 4Division of Gene Regulation, Netherlands Cancer Institute, 1066CX Amsterdam, and Oncode Institute, The Netherlands 5Division of Tumor Biology & Immunology, Netherlands Cancer Institute, 1066CX Amsterdam, and Oncode Institute, The Netherlands 6Department of Molecular Cell Biology and Immunology, Amsterdam UMC, Location VUmc, 1081HV Amsterdam, The Netherlands 7Department of Medical Biology, Amsterdam UMC, location AMC, UvA, 1105 AZ Amsterdam, The Netherlands * These authors contributed equally to this work. # Equal contribution and corresponding authors [email protected]; [email protected] Lead contact: Fred van Leeuwen 1 bioRxiv preprint doi: https://doi.org/10.1101/826255; this version posted November 18, 2019. 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. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Large-Scale Rnai Screening Uncovers New Therapeutic Targets in the Human Parasite
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.05.935833; this version posted February 6, 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 4.0 International license. 1 Large-scale RNAi screening uncovers new therapeutic targets in the human parasite 2 Schistosoma mansoni 3 4 Jipeng Wang1*, Carlos Paz1*, Gilda Padalino2, Avril Coghlan3, Zhigang Lu3, Irina Gradinaru1, 5 Julie N.R. Collins1, Matthew Berriman3, Karl F. Hoffmann2, James J. Collins III1†. 6 7 8 1Department of Pharmacology, UT Southwestern Medical Center, Dallas, Texas 75390 9 2Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, 10 Aberystwyth, Wales, UK. 11 3Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK 12 *Equal Contribution 13 14 15 16 17 18 19 20 21 22 23 †To whom correspondence should be addressed 24 [email protected] 25 UT Southwestern Medical Center 26 Department of Pharmacology 27 6001 Forest Park. Rd. 28 Dallas, TX 75390 29 United States of America bioRxiv preprint doi: https://doi.org/10.1101/2020.02.05.935833; this version posted February 6, 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 4.0 International license. 30 ABSTRACT 31 Schistosomes kill 250,000 people every year and are responsible for serious morbidity in 240 32 million of the world’s poorest people. -
Figure S17 Figure S16
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3D Genome Analysis Identifies Enhancer Hijacking Mechanism for High-Risk 2 Factors in Human T-Lineage Acute Lymphoblastic Leukemia
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.11.988279; this version posted March 12, 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. 1 3D Genome Analysis Identifies Enhancer Hijacking Mechanism for High-Risk 2 Factors in Human T-Lineage Acute Lymphoblastic Leukemia 3 Lu Yang1,2,3^, Fengling Chen4^, Haichuan Zhu1,2,3^§, Yang Chen4, Bingjie Dong1,2,3, 4 Minglei Shi4, Weitao Wang1,2,3, Qian Jiang6, Leping Zhang7, Xiaojun Huang2,6*, 5 Michael Q. Zhang4,5,8* and Hong Wu1,2,3,6* 6 7 1The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life 8 Sciences, 2Peking-Tsinghua Center for Life Sciences and 3Beijing Advanced 9 Innovation Center for Genomics, Peking University, Beijing 100871, China; 4MOE Key 10 Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, 11 Bioinformatics Division, BNRist, Department of Automation, 5School of Medicine, 12 Tsinghua University, Beijing 100084, China; 6Peking University Institute of Hematology, 13 National Clinical Research Center for Hematologic Disease, 7Department of Pediatric 14 Hematology/Oncology, Peking University People’s Hospital, Beijing 100044, China; 15 8Department of Biological Sciences, Center for Systems Biology, The University of 16 Texas, Dallas 800 West Campbell Road, RL11, Richardson, TX 75080-3021, USA 17 18 ^ These authors contributed equally to this work. 19 §Current address: Institute of Biology and Medicine, College of Life and Health 20 Sciences, Wuhan University of Science and Technology, Hubei 430081, China. -
Open Data for Differential Network Analysis in Glioma
International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. -
Bcl11b and Combinatorial Resolution of Cell Fate in the T-Cell Gene
PAPER Bcl11b and combinatorial resolution of cell fate in the COLLOQUIUM T-cell gene regulatory network William J. R. Longabaugha,1,2, Weihua Zengb,1, Jingli A. Zhangc,3, Hiroyuki Hosokawac, Camden S. Jansenb, Long Lic,4,5, Maile Romero-Wolfc, Pentao Liud, Hao Yuan Kuehc,6, Ali Mortazavib,2, and Ellen V. Rothenbergc,2 aInstitute for Systems Biology, Seattle, WA 98109; bDepartment of Developmental and Cell Biology, University of California, Irvine, CA 92697; cDivision of Biology & Biological Engineering, California Institute of Technology, Pasadena, CA 91125; and dWellcome Trust Medical Research Council, Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 1QR, United Kingdom Edited by Neil H. Shubin, The University of Chicago, Chicago, IL, and approved January 30, 2017 (received for review October 25, 2016) T-cell development from hematopoietic progenitors depends on The robust change in potential from DN2a to DN2b is also multiple transcription factors, mobilized and modulated by intra- accompanied by dynamic transcription factor expression changes thymic Notch signaling. Key aspects of T-cell specification network (8, 9) At least 20 regulatory genes have expression patterns that architecture have been illuminated through recent reports de- can be classed as “phase 1” (expressed in ETP and DN2a, then fining roles of transcription factors PU.1, GATA-3, and E2A, their down-regulated) or “phase 2” (turned on or significantly up- interactions with Notch signaling, and roles of Runx1, TCF-1, and regulated around commitment in DN2b) (5). To date, the most- Hes1, providing bases for a comprehensively updated model of the studied regulators of the phase 1 to phase 2 transition have been Notch signaling, GATA-3, TCF-1, and E2A, and PU.1 as a T-cell specification gene regulatory network presented herein. -
Genome-Wide Analyses Identify KLF4 As an Important Negative Regulator
Li et al. Molecular Cancer (2015) 14:26 DOI 10.1186/s12943-014-0285-x RESEARCH Open Access Genome-wide analyses identify KLF4 as an important negative regulator in T-cell acute lymphoblastic leukemia through directly inhibiting T-cell associated genes Wei Li1,2†, Zhiwu Jiang1,2†, Tianzhong Li1,2, Xinru Wei1,2,YiZheng1,2, Donghai Wu1,2, Lijian Yang3,4,ShaohuaChen3,4, Bing Xu5, Mei Zhong6,JueJiang7,YufengHu7,HexiuSu7, Minjie Zhang8,XiaojunHuang9,SuxiaGeng10, Jianyu Weng10,XinDu10,PentaoLiu11, Yangqiu Li3,4,HudanLiu7,YaoYao12* andPengLi1,2* Abstract Background: Kruppel-like factor 4 (KLF4) induces tumorigenesis or suppresses tumor growth in a tissue-dependent manner. However, the roles of KLF4 in hematological malignancies and the mechanisms of action are not fully understood. Methods: Inducible KLF4-overexpression Jurkat cell line combined with mouse models bearing cell-derived xenografts and primary T-cell acute lymphoblastic leukemia (T-ALL) cells from four patients were used to assess the functional role of KLF4 in T-ALL cells in vitro and in vivo. A genome-wide RNA-seq analysis was conducted to identify genes regulated by KLF4 in T-ALL cells. Chromatin immunoprecipitation (ChIP) PCR was used to determine direct binding sites of KLF4 in T-ALL cells. Results: Here we reveal that KLF4 induced apoptosis through the BCL2/BCLXL pathway in human T-ALL cell lines and primary T-ALL specimens. In consistence, mice engrafted with KLF4-overexpressing T-ALL cells exhibited prolonged survival. Interestingly, the KLF4-induced apoptosis in T-ALL cells was compromised in xenografts but the invasion capacity of KLF4-expressing T-ALL cells to hosts was dramatically dampened. -
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. -
(Siberian Roe Deer and Grey Brocket Deer) Unravelled by Chromosome-Specific DNA Sequencing Alexey I
Nova Southeastern University NSUWorks Biology Faculty Articles Department of Biological Sciences 8-11-2016 Contrasting Origin of B Chromosomes in Two Cervids (Siberian Roe Deer and Grey Brocket Deer) Unravelled by Chromosome-Specific DNA Sequencing Alexey I. Makunin Institute of Molecular and Cell Biology - Novosibirsk, Russia; St. Petersburg State University - Russia Ilya G. Kichigin Institute of Molecular and Cell Biology - Novosibirsk, Russia Denis M. Larkin University of London - United Kingdom Patricia C. M. O'Brien Cambridge University - United Kingdom Malcolm A. Ferguson-Smith University of Cambridge - United Kingdom See next page for additional authors Follow this and additional works at: https://nsuworks.nova.edu/cnso_bio_facarticles Part of the Animal Sciences Commons, and the Genetics and Genomics Commons NSUWorks Citation Makunin, Alexey I.; Ilya G. Kichigin; Denis M. Larkin; Patricia C. M. O'Brien; Malcolm A. Ferguson-Smith; Fengtang Yang; Anastasiya A. Proskuryakova; Nadezhda V. Vorobieva; Ekaterina N. Chernyaeva; Stephen J. O'Brien; Alexander S. Graphodatsky; and Vladimir Trifonov. 2016. "Contrasting Origin of B Chromosomes in Two Cervids (Siberian Roe Deer and Grey Brocket Deer) Unravelled by Chromosome-Specific DNA eS quencing." BMC Genomics 17, (618): 1-14. doi:10.1186/s12864-016-2933-6. This Article is brought to you for free and open access by the Department of Biological Sciences at NSUWorks. It has been accepted for inclusion in Biology Faculty Articles by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Authors Alexey I. Makunin, Ilya G. Kichigin, Denis M. Larkin, Patricia C. M. O'Brien, Malcolm A. Ferguson-Smith, Fengtang Yang, Anastasiya A.