DOCSLIB.ORG

MDM4 Is Targeted by 1Q Gain and Drives Disease in Burkitt Lymphoma

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
MDM4 Is Targeted by 1Q Gain and Drives Disease in Burkitt Lymphoma Published OnlineFirst April 18, 2019; DOI: 10.1158/0008-5472.CAN-18-3438 Cancer Translational Science Research MDM4 Is Targeted by 1q Gain and Drives Disease in Burkitt Lymphoma Jennifer Hullein€ 1,2, Mikołaj Słabicki1, Maciej Rosolowski3, Alexander Jethwa1,2, Stefan Habringer4, Katarzyna Tomska1, Roma Kurilov5, Junyan Lu6, Sebastian Scheinost1, Rabea Wagener7,8, Zhiqin Huang9, Marina Lukas1, Olena Yavorska6, Hanne Helfrich10,Rene Scholtysik11, Kyle Bonneau12, Donato Tedesco12,RalfKuppers€ 11, Wolfram Klapper13, Christiane Pott14, Stephan Stilgenbauer10, Birgit Burkhardt15, Markus Lof€ fler3, Lorenz H. Trumper€ 16, Michael Hummel17, Benedikt Brors5, Marc Zapatka9, Reiner Siebert7,8, Markus Kreuz3, Ulrich Keller4,18, Wolfgang Huber6, and Thorsten Zenz1,19 Abstract Oncogenic MYC activation promotes proliferation in growth in a xenograft model in a p53-dependent manner. Burkitt lymphoma, but also induces cell-cycle arrest and Small molecule inhibition of the MDM4–p53 interaction apoptosis mediated by p53, a tumor suppressor that is was effective only in TP53wt Burkitt lymphoma cell lines. mutated in 40% of Burkitt lymphoma cases. To identify Moreover, primary TP53wt Burkitt lymphoma samples fre- molecular dependencies in Burkitt lymphoma, we per- quently acquired gains of chromosome 1q, which includes formed RNAi-based, loss-of-function screening in eight the MDM4 locus, and showed elevated MDM4 mRNA levels. Burkitt lymphoma cell lines and integrated non-Burkitt 1q gain was associated with TP53wt across 789 cancer cell lymphoma RNAi screens and genetic data. We identified lines and MDM4 was essential in the TP53wt-context in 216 76 genes essential to Burkitt lymphoma, including genes cell lines representing 19 cancer entities from the Achilles associated with hematopoietic cell differentiation (FLI1, Project. Our findings highlight the critical role of p53 as a BCL11A) or B-cell development and activation (PAX5, tumor suppressor in Burkitt lymphoma and identify MDM4 CDKN1B, JAK2, CARD11) and found a number of con- as a functional target of 1q gain in a wide range of cancers text-specific dependencies including oncogene addiction in that is therapeutically targetable. cell lines with TCF3/ID3 or MYD88 mutation. The strongest genotype–phenotype association was seen for TP53.MDM4, Significance: Targeting MDM4 to alleviate degradation of a negative regulator of TP53,wasessentialinTP53 wild-type p53 can be exploited therapeutically across Burkitt lymphoma (TP53wt) Burkitt lymphoma cell lines. MDM4 knockdown and other cancers with wild-type p53 harboring 1q gain, the activated p53, induced cell-cycle arrest, and decreased tumor most frequent copy number alteration in cancer. 1Molecular Therapy in Hematology and Oncology & Department of Translational (CBF), Charite, Berlin, Germany. 19Department of Medical Oncology and Hema- Oncology, NCT and DKFZ, Heidelberg, Germany. 2Faculty of Biosciences, tology, University Hospital Zurich, Zurich, Switzerland. Heidelberg University, Heidelberg, Germany. 3Department for Statistics and Epidemiology, Institute for Medical Informatics, Leipzig, Germany. 4III. Medical Note: Supplementary data for this article are available at Cancer Research Department of Hematology and Medical Oncology, Technical University of Online (http://cancerres.aacrjournals.org/). Munich, Germany. 5Division of Applied Bioinformatics, DKFZ, Heidelberg, Germany. 6European Molecular Biology Laboratory (EMBL), Heidelberg, M. Rosolowski, R. Scholtysik, R. Kuppers,€ W. Klapper, C. Pott, S. Stilgenbauer, B. Germany. 7Institute of Human Genetics, Ulm University & Ulm University Medical Burkhardt, M. Lof€ fler, L.H. Trumper,€ M. Hummel, R. Siebert, M. Kreuz, T. Zenz are Center, Germany. 8Institute of Human Genetics, University of Kiel, Kiel, Germany. members of the MMML consortium. 9Division of Molecular Genetics, DKFZ, Heidelberg, Germany. 10Department of Internal Medicine III, University of Ulm, Ulm, Germany. 11Institute of Cell Biology M. Słabicki is the co-first author and T. Zenz is the lead author. (Cancer Research), University of Duisburg-Essen, Medical School, Essen, Germany, and the German Cancer Consortium (DKTK). 12Cellecta, Inc., Mountain This manuscript is available on BioRxiv: https://doi.org/10.1101/289363. View, California. 13Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel, Corresponding Author: Thorsten Zenz, University Hospital and University of Christian-Albrechts-University Kiel, Kiel, Germany. 14Second Medical Depart- Zurich, Zurich€ 8091, Germany. Phone: 41-44-255 9469; E-mail: ment, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany. [email protected] 15Department of Pediatric Hematology and Oncology, NHL-BFM Study Center, Cancer Res 2019;79:3125–38 University Children's Hospital, Munster,€ Germany. 16Department of Hematology € € and Medical Oncology, Gottingen University Medical Center, Gottingen, doi: 10.1158/0008-5472.CAN-18-3438 Germany. 17Institute of Pathology, Charite–University Medicine Berlin, Berlin, Germany. 18Division of Hematology and Oncology at Campus Benjamin Franklin Ó2019 American Association for Cancer Research. www.aacrjournals.org 3125 Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2019 American Association for Cancer Research. Published OnlineFirst April 18, 2019; DOI: 10.1158/0008-5472.CAN-18-3438 Hullein€ et al. Introduction RNAi screen and shRNA-mediated knockdown The RNAi screen was performed as described previously (17) Burkitt lymphoma is an aggressive B-cell lymphoma that is with modifications using the DECIPHER Human Module I characterized by translocation of the MYC gene to immunoglob- pooled lentiviral shRNA library (#DHPAC-M1-P) targeting ulin loci (1). Although oncogenic MYC promotes cell growth and 5,045 genes in key signaling pathways with four to five shRNAs proliferation, it also evokes failsafe mechanisms such as p53 per gene (Cellecta). shRNA representation was determined two activation that have to be overcome for transformation (2). About and 14 days posttransduction using high-throughput sequencing. 40% of Burkitt lymphoma acquire TP53 mutations evading MYC- P values for shRNA depletion were calculated using the edgeR induced stress signals (3, 4). package (18) and collapsed into gene scores using weighted Recent mutational cartography efforts in Burkitt lymphoma Z-transformation (19). P values for differential shRNA viability identified additional recurrent mutations in TCF3, ID3, effects were calculated as described previously using public soft- GNA13, RET, PIK3R1, DDX3X, FBXO11,andtheSWI/SNF ware and collapsed into gene scores using Kolmogorov–Smirnov genes ARID1A and SMARCA4 (5–8). Burkitt lymphoma also statistics (https://software.broadinstitute.org/GENE-E/index.html). display copy number alterations (CNA) in addition to the RNAi results in non-Burkitt lymphoma cell lines screened with the MYC translocation, targeting chromosomes 1q, 13q31, 17p13 same library were provided by Cellecta as raw read counts and (including TP53), and 9p21.2 (including CDKN2A;refs.9, genome-wide RNAi results in 216 cell lines were publically available 10). A gain of 1q is found in 30% of Burkitt lymphoma and as log -transformed shRNA fold changes (13). Single shRNAs were often affects large regions (11), which has contributed to the 2 coexpressed with RFP constitutively from the pRSI12-U6-(sh)-UbiC- limited understanding of oncogenic mechanisms involved. TagRFP-2A-Puro vector backbone. shRNA cytotoxicity was deter- The implications of these mutations and CNAs are currently mined by transduction of 50% of cells and relative RFP-loss com- unclear. pared with a scrambled shRNA (shNT). RNAi-based genomics screens allow querying of functional dependencies in an unbiased fashion and in high through- Genetic annotation of cell lines put. Using panels of representative cell lines, context-specific Mutations in Burkitt lymphoma cell lines were identified from vulnerabilities have been linked to genetic and pathologic genomic DNA using a self-designed amplicon panel (20) or from subgroups (12). The Achilles Project reported comprehensive RNA sequencing on the Illumina HiSeq2000. Sequences were screening data in 501 cell lines using RNAi (13, 14). While mapped against the human reference genome hg19 using the activating mutations caused direct oncogene addiction, as STAR alignment tool. Mutations were called as described previ- seen in cell lines with BRAF, KRAS,orPI3K mutation, ously (21). Genetic information for non-Burkitt lymphoma cell secondary gene dependencies were observed for loss-of- lines was extracted from Cancer Cell Line Encyclopedia (CCLE; function mutations in tumor suppressor genes, such as https://portals.broadinstitute.org/ccle/home) and COSMIC ARID1A (15). Integration of gene expression and drug sen- (GDSC, http://www.cancerrxgene.org/). sitivity profiles may provide further insight into the molec- ular basis of diseases and might be used to tailor targeted RT-qPCR therapies (16). Total RNA was isolated with RNeasy Mini Kit (Qiagen) and on- For a comprehensive dissection of molecular dependencies column DNase I (Qiagen) digestion. RNA was reverse-transcribed in Burkitt lymphoma, we performed a loss-of-function RNAi by SuperScript III First-Strand Synthesis SuperMix (Invitrogen) screen across a panel of genetically characterized Burkitt lym- and quantified using QuantiFast SYBR Green RT-PCR (Qiagen) or phoma cell lines and intersected our findings on genotype- Power SYBR
Load more

Recommended publications
  • A Genetic Screening Identifies a Component of the SWI/SNF Complex, Arid1b As a Senescence Regulator
    A genetic screening identifies a component of the SWI/SNF complex, Arid1b as a senescence regulator Sadaf Khan A thesis submitted to Imperial College London for the degree of Doctor in Philosophy MRC Clinical Sciences Centre Imperial College London, School of Medicine July 2013 Statement of originality All experiments included in this thesis were performed by myself unless otherwise stated. Copyright Declaration The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives license. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the license terms of this work. 2 Abstract Senescence is an important tumour suppressor mechanism, which prevents the proliferation of stressed or damaged cells. The use of RNA interference to identify genes with a role in senescence is an important tool in the discovery of novel cancer genes. In this work, a protocol was established for conducting bypass of senescence screenings, using shRNA libraries together with next-generation sequencing. Using this approach, the SWI/SNF subunit Arid1b was identified as a regulator of cellular lifespan in MEFs. SWI/SNF is a large multi-subunit complex that remodels chromatin. Mutations in SWI/SNF proteins are frequently associated with cancer, suggesting that SWI/SNF components are tumour suppressors. Here the role of ARID1B during senescence was investigated. Depletion of ARID1B extends the proliferative capacity of primary mouse and human fibroblasts.
    [Show full text]
  • ARID1B Is a Specific Vulnerability in ARID1A-Mutant Cancers The
    ARID1B is a specific vulnerability in ARID1A-mutant cancers The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Helming, K. C., X. Wang, B. G. Wilson, F. Vazquez, J. R. Haswell, H. E. Manchester, Y. Kim, et al. 2014. “ARID1B is a specific vulnerability in ARID1A-mutant cancers.” Nature medicine 20 (3): 251-254. doi:10.1038/nm.3480. http://dx.doi.org/10.1038/nm.3480. Published Version doi:10.1038/nm.3480 Accessed February 16, 2015 10:04:32 PM EST Citable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:12987227 Terms of Use This article was downloaded from Harvard University's DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA (Article begins on next page) NIH Public Access Author Manuscript Nat Med. Author manuscript; available in PMC 2014 September 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nat Med. 2014 March ; 20(3): 251–254. doi:10.1038/nm.3480. ARID1B is a specific vulnerability in ARID1A-mutant cancers Katherine C. Helming1,2,3,4,*, Xiaofeng Wang1,2,3,*, Boris G. Wilson1,2,3, Francisca Vazquez5, Jeffrey R. Haswell1,2,3, Haley E. Manchester1,2,3, Youngha Kim1,2,3, Gregory V. Kryukov5, Mahmoud Ghandi5, Andrew J. Aguirre5,6,7, Zainab Jagani8, Zhong Wang9, Levi A. Garraway6, William C. Hahn6,7, and Charles W.
    [Show full text]
  • The Genetic Basis of Hepatosplenic T-Cell Lymphoma
    Published OnlineFirst January 25, 2017; DOI: 10.1158/2159-8290.CD-16-0330 RESEARCH BRIEF The Genetic Basis of Hepatosplenic T-cell Lymphoma Matthew McKinney 1 , Andrea B. Moffi tt 2 , Philippe Gaulard 3 , Marion Travert 3 , Laurence De Leval4 , Alina Nicolae 5 , Mark Raffeld 5 , Elaine S. Jaffe 5 , Stefania Pittaluga 5 , Liqiang Xi 5 , Tayla Heavican 6 , Javeed Iqbal 6 , Karim Belhadj 3 , Marie Helene Delfau-Larue 3 , Virginie Fataccioli 3 , Magdalena B. Czader7 , Izidore S. Lossos 8 , Jennifer R. Chapman-Fredricks 8 , Kristy L. Richards 9 , Yuri Fedoriw 9 , Sarah L. Ondrejka10 , Eric D. Hsi 10 , Lawrence Low 11 , Dennis Weisenburger 11 , Wing C. Chan 11 , Neha Mehta-Shah12 , Steven Horwitz 12 , Leon Bernal-Mizrachi 13 , Christopher R. Flowers 13 , Anne W. Beaven 1 , Mayur Parihar 14 , Lucile Baseggio 15 , Marie Parrens 16 , Anne Moreau 17 , Pierre Sujobert 18 , Monika Pilichowska 19 , Andrew M. Evens 19 , Amy Chadburn 20 , Rex K.H. Au-Yeung 21 , Gopesh Srivastava 21 , William W. L. Choi 21 , John R. Goodlad 22 , Igor Aurer 23 , Sandra Basic-Kinda 23 , Randy D. Gascoyne 24 , Nicholas S. Davis 1 , Guojie Li 1 , Jenny Zhang 1 , Deepthi Rajagopalan 1 , Anupama Reddy 1 , Cassandra Love 1 , Shawn Levy 25 , Yuan Zhuang 1 , Jyotishka Datta 26 , David B. Dunson 26 , and Sandeep S. Davé 1 , 2 ABSTRACT Hepatosplenic T-cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown. Through whole-exome sequencing of 68 HSTLs, we defi ne recurrently mutated driver genes and copy-number alterations in the disease.
    [Show full text]
  • MECHANISMS in ENDOCRINOLOGY: Novel Genetic Causes of Short Stature
    J M Wit and others Genetics of short stature 174:4 R145–R173 Review MECHANISMS IN ENDOCRINOLOGY Novel genetic causes of short stature 1 1 2 2 Jan M Wit , Wilma Oostdijk , Monique Losekoot , Hermine A van Duyvenvoorde , Correspondence Claudia A L Ruivenkamp2 and Sarina G Kant2 should be addressed to J M Wit Departments of 1Paediatrics and 2Clinical Genetics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, Email The Netherlands [email protected] Abstract The fast technological development, particularly single nucleotide polymorphism array, array-comparative genomic hybridization, and whole exome sequencing, has led to the discovery of many novel genetic causes of growth failure. In this review we discuss a selection of these, according to a diagnostic classification centred on the epiphyseal growth plate. We successively discuss disorders in hormone signalling, paracrine factors, matrix molecules, intracellular pathways, and fundamental cellular processes, followed by chromosomal aberrations including copy number variants (CNVs) and imprinting disorders associated with short stature. Many novel causes of GH deficiency (GHD) as part of combined pituitary hormone deficiency have been uncovered. The most frequent genetic causes of isolated GHD are GH1 and GHRHR defects, but several novel causes have recently been found, such as GHSR, RNPC3, and IFT172 mutations. Besides well-defined causes of GH insensitivity (GHR, STAT5B, IGFALS, IGF1 defects), disorders of NFkB signalling, STAT3 and IGF2 have recently been discovered. Heterozygous IGF1R defects are a relatively frequent cause of prenatal and postnatal growth retardation. TRHA mutations cause a syndromic form of short stature with elevated T3/T4 ratio. Disorders of signalling of various paracrine factors (FGFs, BMPs, WNTs, PTHrP/IHH, and CNP/NPR2) or genetic defects affecting cartilage extracellular matrix usually cause disproportionate short stature.
    [Show full text]
  • 1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
    xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A
    [Show full text]
  • XPO7 Is a Tumor Suppressor Regulating P21cip1-Dependent Senescence
    Downloaded from genesdev.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press XPO7 is a tumor suppressor regulating p21CIP1-dependent senescence Andrew J. Innes,1,2,3 Bin Sun,1,2 Verena Wagner,1,2 Sharon Brookes,1,2 Domhnall McHugh,1,2 Joaquim Pombo,1,2 Rosa María Porreca,1,2 Gopuraja Dharmalingam,1,2 Santiago Vernia,1,2 Johannes Zuber,4 Jean-Baptiste Vannier,1,2 Ramón García-Escudero,5,6,7 and Jesús Gil1,2 1MRC London Institute of Medical Sciences (LMS), London W12 0NN, United Kingdom; 2Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London W12 0NN, United Kingdom; 3Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London W12 0NN, United Kingdom; 4Research Institute of Molecular Pathology (IMP), 1030 Vienna, Austria; 5Molecular Oncology Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), 28040 Madrid, Spain; 6Research Institute 12 de Octubre (i+12), 28041 Madrid, Spain; 7Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain Senescence is a key barrier to neoplastic transformation. To identify senescence regulators relevant to cancer, we screened a genome-wide shRNA library. Here, we describe exportin 7 (XPO7) as a novel regulator of senescence and validate its function in telomere-induced, replicative, and oncogene-induced senescence (OIS). XPO7 is a bidirec- tional transporter that regulates the nuclear-cytoplasmic shuttling of a broad range of substrates. Depletion of XPO7 results in reduced levels of TCF3 and an impaired induction of the cyclin-dependent kinase inhibitor p21CIP1 during OIS. Deletion of XPO7 correlates with poorer overall survival in several cancer types.
    [Show full text]
  • Genome-Wide DNA Methylation Analysis Reveals Molecular Subtypes of Pancreatic Cancer
    www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 17), pp: 28990-29012 Research Paper Genome-wide DNA methylation analysis reveals molecular subtypes of pancreatic cancer Nitish Kumar Mishra1 and Chittibabu Guda1,2,3,4 1Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, 68198, USA 2Bioinformatics and Systems Biology Core, University of Nebraska Medical Center, Omaha, NE, 68198, USA 3Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, 68198, USA 4Fred and Pamela Buffet Cancer Center, University of Nebraska Medical Center, Omaha, NE, 68198, USA Correspondence to: Chittibabu Guda, email: [email protected] Keywords: TCGA, pancreatic cancer, differential methylation, integrative analysis, molecular subtypes Received: October 20, 2016 Accepted: February 12, 2017 Published: March 07, 2017 Copyright: Mishra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients.
    [Show full text]
  • Lineage Transcription Factors Co-Regulate Subtype-Specific Genes Providing a Roadmap For
    bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249029; this version posted August 14, 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. Lineage transcription factors co-regulate subtype-specific genes providing a roadmap for systematic identification of small cell lung cancer vulnerabilities Karine Pozo1,2, Rahul K. Kollipara3, Demetra P. Kelenis1, Kathia E. Rodarte1, Xiaoyang Zhang4, John D. Minna5,6,7,8 and Jane E. Johnson1,6,8 1Department of Neuroscience, 2Department of Surgery, 3McDermott Center for Human Growth and Development, UT Southwestern Medical Center, Dallas, TX 75390, USA 4Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 5Hamon Center for Therapeutic Oncology Research, 6Simmons Comprehensive Cancer Center, 7Department of Internal Medicine, 8Department of Pharmacology, UT Southwestern Medical Center, Dallas, TX 75390, USA JDM receives licensing fees for lung cancer lines from the NIH and UT Southwestern. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.13.249029; this version posted August 14, 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. ABSTRACT Lineage-defining transcription factors (LTFs) play key roles in tumor cell growth, making them highly attractive, but currently “undruggable”, small cell lung cancer (SCLC) vulnerabilities.
    [Show full text]
  • Blueprint Genetics Comprehensive Growth Disorders / Skeletal
    Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders Panel Test code: MA4301 Is a 374 gene panel that includes assessment of non-coding variants. This panel covers the majority of the genes listed in the Nosology 2015 (PMID: 26394607) and all genes in our Malformation category that cause growth retardation, short stature or skeletal dysplasia and is therefore a powerful diagnostic tool. It is ideal for patients suspected to have a syndromic or an isolated growth disorder or a skeletal dysplasia. About Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders This panel covers a broad spectrum of diseases associated with growth retardation, short stature or skeletal dysplasia. Many of these conditions have overlapping features which can make clinical diagnosis a challenge. Genetic diagnostics is therefore the most efficient way to subtype the diseases and enable individualized treatment and management decisions. Moreover, detection of causative mutations establishes the mode of inheritance in the family which is essential for informed genetic counseling. For additional information regarding the conditions tested on this panel, please refer to the National Organization for Rare Disorders and / or GeneReviews. Availability 4 weeks Gene Set Description Genes in the Comprehensive Growth Disorders / Skeletal Dysplasias and Disorders Panel and their clinical significance Gene Associated phenotypes Inheritance ClinVar HGMD ACAN# Spondyloepimetaphyseal dysplasia, aggrecan type, AD/AR 20 56 Spondyloepiphyseal dysplasia, Kimberley
    [Show full text]
  • Characterization of TCF3 Rearrangements in Pediatric B-Lymphoblastic Leukemia/Lymphoma by Mate-Pair Sequencing
    Rowsey et al. Blood Cancer Journal (2019) 9:81 https://doi.org/10.1038/s41408-019-0239-z Blood Cancer Journal ARTICLE Open Access Characterization of TCF3 rearrangements in pediatric B-lymphoblastic leukemia/lymphoma by mate-pair sequencing (MPseq) identifies complex genomic rearrangements and a novel TCF3/TEF gene fusion Ross A. Rowsey1, Stephanie A. Smoley1, Cynthia M. Williamson1,GeorgeVasmatzis2, James B. Smadbeck2,YiNing3, Patricia T. Greipp1, Nicole L. Hoppman1, Linda B. Baughn1, Rhett P. Ketterling1 and Jess F. Peterson1 Abstract The TCF3/PBX1 gene fusion is a recurrent genetic abnormality in pediatric B-lymphoblastic leukemia/lymphoma (B-ALL/LBL). While dual-color, dual-fusion fluorescence in situ hybridization (D-FISH) probes can detect TCF3/PBX1 fusions, further characterization of atypical TCF3 FISH patterns as indicated by additional or diminished TCF3 signals is currently limited. Herein we describe the use of a next-generation sequencing assay, mate-pair sequencing (MPseq), to characterize typical and cryptic TCF3/PBX1 fusions and to identify TCF3 translocation partners based on results obtained from our laboratory-developed TCF3/PBX1 D-FISH probe set. MPseq was performed on 21 cases of pediatric B-ALL/LBL with either TCF3/PBX1 fusion, or no TCF3/PBX1 fusion but with additional or diminished TCF3 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; signals obtained by our PBX1/TCF3 D-FISH probe set. In addition, MPseq was performed on one pediatric B-ALL/LBL case with an apparently normal karyotype and abnormal TCF3 break-apart probe results. Of 22 specimens successfully evaluated by MPseq, 13 cases (59%) demonstrated TCF3/PBX1 fusion, including three cases with previously undescribed insertional rearrangements.
    [Show full text]
  • TP53 Mutations As a Driver of Metastasis Signaling in Advanced Cancer Patients
    cancers Article TP53 Mutations as a Driver of Metastasis Signaling in Advanced Cancer Patients Ritu Pandey 1,2,*, Nathan Johnson 3, Laurence Cooke 1, Benny Johnson 4, Yuliang Chen 1, Manjari Pandey 5, Jason Chandler 5 and Daruka Mahadevan 6,* 1 Cancer Center, University of Arizona, Tucson, AZ 85724, USA; [email protected] (L.C.); [email protected] (Y.C.) 2 Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ 85724, USA 3 School of Medicine, Vanderbilt University, Nashville, TN 37325, USA; [email protected] 4 MD Anderson Cancer Center, Houston, TX 77030, USA; [email protected] 5 West Cancer Center, 7945 Wolf River Blvd, Germantown, TN 38138, USA; [email protected] (M.P.); [email protected] (J.C.) 6 Mays Cancer Center, University of Texas Health San Antonio, San Antonio, TX 78229, USA * Correspondence: [email protected] (R.P.); [email protected] (D.M.) Simple Summary: The DNA sequencing of cancer provides information about specific genetic changes that could help with treatment decisions. Tumors from different tissues change over time and acquire new genetic changes particularly with treatment. Our study analyzed the gene changes of 171 advanced cancer patients. We predicted that tumors gain new mutations but that TP53 mutations (guardian of the human genome) are conserved as the tumor progresses from primary to metastatic sites and across tissue types. We analyzed the primary and metastatic site gene changes in 25 tissue types and conducted in-depth analysis of colon and lung cancer sites for substantial changes. TP53 site specific mutations were different across tissue types and suggest different molecular changes.
    [Show full text]
  • Supplementary Table 1A. Genes Significantly Altered in A4573 ESFT
    Supplementary Table 1A. Genes significantly altered in A4573 ESFT cells following BMI-1knockdown genesymbol genedescription siControl siBMI1 FC Direction P-value AASS aminoadipate-semialdehyde synthase | tetra-peptide repeat homeobox-like6.68 7.24 1.5 Up 0.007 ABCA2 ATP-binding cassette, sub-family A (ABC1), member 2 | neural5.44 proliferation,6.3 differentiation1.8 and Upcontrol, 1 0.006 ABHD4 abhydrolase domain containing 4 7.51 6.69 1.8 Down 0.002 ACACA acetyl-Coenzyme A carboxylase alpha | peroxiredoxin 5 | similar6.2 to High mobility7.26 group2.1 protein UpB1 (High mobility0.009 group protein 1) (HMG-1) (Amphoterin) (Heparin-binding protein p30) | Coenzyme A synthase ACAD9 acyl-Coenzyme A dehydrogenase family, member 9 9.25 8.59 1.6 Down 0.008 ACBD3 acyl-Coenzyme A binding domain containing 3 7.89 8.53 1.6 Up 0.008 ACCN2 amiloride-sensitive cation channel 2, neuronal 5.47 6.28 1.8 Up 0.005 ACIN1 apoptotic chromatin condensation inducer 1 7.15 7.79 1.6 Up 0.008 ACPL2 acid phosphatase-like 2 6.04 7.6 2.9 Up 0.000 ACSL4 acyl-CoA synthetase long-chain family member 4 6.72 5.8 1.9 Down 0.001 ACTA2 actin, alpha 2, smooth muscle, aorta 9.18 8.44 1.7 Down 0.003 ACYP1 acylphosphatase 1, erythrocyte (common) type 7.09 7.66 1.5 Up 0.009 ADA adenosine deaminase 6.34 7.1 1.7 Up 0.009 ADAL adenosine deaminase-like 7.88 6.89 2.0 Down 0.006 ADAMTS1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 6.57 7.65 2.1 Up 0.000 ADARB1 adenosine deaminase, RNA-specific, B1 (RED1 homolog rat) 6.49 7.13 1.6 Up 0.008 ADCY9 adenylate cyclase 9 6.5 7.18
    [Show full text]