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Molecular Cytogenetic Analysis for TFE3 Rearrangement In
Modern Pathology (2014) 27, 113–127 & 2014 USCAP, Inc. All rights reserved 0893-3952/14 $32.00 113 Molecular cytogenetic analysis for TFE3 rearrangement in Xp11.2 renal cell carcinoma and alveolar soft part sarcoma: validation and clinical experience with 75 cases Jennelle C Hodge, Kathryn E Pearce, Xiaoke Wang, Anne E Wiktor, Andre M Oliveira and Patricia T Greipp Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA Renal cell carcinoma with TFE3 rearrangement at Xp11.2 is a distinct subtype manifesting an indolent clinical course in children, with recent reports suggesting a more aggressive entity in adults. This subtype is morphologically heterogeneous and can be misclassified as clear cell or papillary renal cell carcinoma. TFE3 is also rearranged in alveolar soft part sarcoma. To aid in diagnosis, a break-apart strategy fluorescence in situ hybridization (FISH) probe set specific for TFE3 rearrangement and a reflex dual-color, single-fusion strategy probe set involving the most common TFE3 partner gene, ASPSCR1, were validated on formalin-fixed, paraffin- embedded tissues from nine alveolar soft part sarcoma, two suspected Xp11.2 renal cell carcinoma, and nine tumors in the differential diagnosis. The impact of tissue cut artifact was reduced through inclusion of a chromosome X centromere control probe. Analysis of the UOK-109 renal carcinoma cell line confirmed the break-apart TFE3 probe set can distinguish the subtle TFE3/NONO fusion-associated inversion of chromosome X. Subsequent extensive clinical experience was gained through analysis of 75 cases with an indication of Xp11.2 renal cell carcinoma (n ¼ 54), alveolar soft part sarcoma (n ¼ 13), perivascular epithelioid cell neoplasms (n ¼ 2), chordoma (n ¼ 1), or unspecified (n ¼ 5). -
Influencers on Thyroid Cancer Onset: Molecular Genetic Basis
G C A T T A C G G C A T genes Review Influencers on Thyroid Cancer Onset: Molecular Genetic Basis Berta Luzón-Toro 1,2, Raquel María Fernández 1,2, Leticia Villalba-Benito 1,2, Ana Torroglosa 1,2, Guillermo Antiñolo 1,2 and Salud Borrego 1,2,* 1 Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville (IBIS), University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain; [email protected] (B.L.-T.); [email protected] (R.M.F.); [email protected] (L.V.-B.); [email protected] (A.T.); [email protected] (G.A.) 2 Centre for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain * Correspondence: [email protected]; Tel.: +34-955-012641 Received: 3 September 2019; Accepted: 6 November 2019; Published: 8 November 2019 Abstract: Thyroid cancer, a cancerous tumor or growth located within the thyroid gland, is the most common endocrine cancer. It is one of the few cancers whereby incidence rates have increased in recent years. It occurs in all age groups, from children through to seniors. Most studies are focused on dissecting its genetic basis, since our current knowledge of the genetic background of the different forms of thyroid cancer is far from complete, which poses a challenge for diagnosis and prognosis of the disease. In this review, we describe prevailing advances and update our understanding of the molecular genetics of thyroid cancer, focusing on the main genes related with the pathology, including the different noncoding RNAs associated with the disease. -
Antisense RNA Polymerase II Divergent Transcripts Are P-Tefb Dependent and Substrates for the RNA Exosome
Antisense RNA polymerase II divergent transcripts are P-TEFb dependent and substrates for the RNA exosome Ryan A. Flynna,1,2, Albert E. Almadaa,b,1, Jesse R. Zamudioa, and Phillip A. Sharpa,b,3 aDavid H. Koch Institute for Integrative Cancer Research, Cambridge, MA 02139; and bDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139 Contributed by Phillip A. Sharp, May 12, 2011 (sent for review March 3, 2011) Divergent transcription occurs at the majority of RNA polymerase II PII carboxyl-terminal domain (CTD) at serine 2, DSIF, and (RNAPII) promoters in mouse embryonic stem cells (mESCs), and NELF results in the dissociation of NELF from the elongation this activity correlates with CpG islands. Here we report the char- complex and continuation of transcription (13). More recently acterization of upstream antisense transcription in regions encod- it was recognized, in mESCs, that c-Myc stimulates transcription ing transcription start site associated RNAs (TSSa-RNAs) at four at over a third of all cellular promoters by recruitment of P-TEFb divergent CpG island promoters: Isg20l1, Tcea1, Txn1, and Sf3b1. (12). Intriguingly in these same cells, NELF and DSIF have bi- We find that upstream antisense RNAs (uaRNAs) have distinct modal binding profiles at divergent TSSs. This suggests divergent capped 5′ termini and heterogeneous nonpolyadenylated 3′ ends. RNAPII complexes might be poised for signals controlling elon- uaRNAs are short-lived with average half-lives of 18 minutes and gation and opens up the possibility that in the antisense direction are present at 1–4 copies per cell, approximately one RNA per DNA P-TEF-b recruitment may be regulating release for productive template. -
Genome-Wide Analysis of Host-Chromosome Binding Sites For
Lu et al. Virology Journal 2010, 7:262 http://www.virologyj.com/content/7/1/262 RESEARCH Open Access Genome-wide analysis of host-chromosome binding sites for Epstein-Barr Virus Nuclear Antigen 1 (EBNA1) Fang Lu1, Priyankara Wikramasinghe1, Julie Norseen1,2, Kevin Tsai1, Pu Wang1, Louise Showe1, Ramana V Davuluri1, Paul M Lieberman1* Abstract The Epstein-Barr Virus (EBV) Nuclear Antigen 1 (EBNA1) protein is required for the establishment of EBV latent infection in proliferating B-lymphocytes. EBNA1 is a multifunctional DNA-binding protein that stimulates DNA replication at the viral origin of plasmid replication (OriP), regulates transcription of viral and cellular genes, and tethers the viral episome to the cellular chromosome. EBNA1 also provides a survival function to B-lymphocytes, potentially through its ability to alter cellular gene expression. To better understand these various functions of EBNA1, we performed a genome-wide analysis of the viral and cellular DNA sites associated with EBNA1 protein in a latently infected Burkitt lymphoma B-cell line. Chromatin-immunoprecipitation (ChIP) combined with massively parallel deep-sequencing (ChIP-Seq) was used to identify cellular sites bound by EBNA1. Sites identified by ChIP- Seq were validated by conventional real-time PCR, and ChIP-Seq provided quantitative, high-resolution detection of the known EBNA1 binding sites on the EBV genome at OriP and Qp. We identified at least one cluster of unusually high-affinity EBNA1 binding sites on chromosome 11, between the divergent FAM55 D and FAM55B genes. A con- sensus for all cellular EBNA1 binding sites is distinct from those derived from the known viral binding sites, sug- gesting that some of these sites are indirectly bound by EBNA1. -
Renal Cell Carcinoma – Detection of PRCC-TFE3 and Alpha-TFEB Gene Fusions Using RT-PCR on Tissues (Odes 60153 and 60154) Notice of Assessment
Renal Cell Carcinoma – Detection of PRCC-TFE3 and Alpha-TFEB Gene Fusions Using RT-PCR on Tissues (odes 60153 and 60154) Notice of Assessment June 2013 DISCLAIMER: This document was originally drafted in French by the Institut national d'excellence en santé et en services sociaux (INESSS), and that version can be consulted at http://www.inesss.qc.ca/fileadmin/doc/INESSS/Analyse_biomedicale/Juin_2013/INESSS_Analyse_15.pdf http://www.inesss.qc.ca/fileadmin/doc/INESSS/Analyse_biomedicale/Juin_2013/INESSS_Analyse_16.pdf It was translated into English by the Canadian Agency for Drugs and Technologies in Health (CADTH) with INESSS’s permission. INESSS assumes no responsibility with regard to the quality or accuracy of the translation. While CADTH has taken care in the translation of the document to ensure it accurately represents the content of the original document, CADTH does not make any guarantee to that effect. CADTH is not responsible for any errors or omissions or injury, loss, or damage arising from or relating to the use (or misuse) of any information, statements, or conclusions contained in or implied by the information in this document, the original document, or in any of the source documentation. 1 GENERAL INFORMATION 1.1 Requestor: Centre hospitalier universitaire de Québec (CHUQ). 1.2 Application Submitted: August 1, 2012. 1.3 Notice Issued: April 12, 2013. Note: This notice is based on the scientific and commercial information (submitted by the requestor[s]) and on a complementary review of the literature according to the data available at the time that this test was assessed by INESSS. 2 TECHNOLOGY, COMPANY, AND LICENCE(S) 2.1 Name of the Technology Reverse transcription of messenger RNA and amplification (RT-PCR). -
A Gene-Level Methylome-Wide Association Analysis Identifies Novel
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.201376; this version posted July 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. 1 A gene-level methylome-wide association analysis identifies novel 2 Alzheimer’s disease genes 1 1 2 3 4 3 Chong Wu , Jonathan Bradley , Yanming Li , Lang Wu , and Hong-Wen Deng 1 4 Department of Statistics, Florida State University; 2 5 Department of Biostatistics & Data Science, University of Kansas Medical Center; 3 6 Population Sciences in the Pacific Program, University of Hawaii Cancer center; 4 7 Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, 8 Tulane University School of Medicine 9 Corresponding to: Chong Wu, Assistant Professor, Department of Statistics, Florida State 10 University, email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.201376; this version posted July 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. 11 Abstract 12 Motivation: Transcriptome-wide association studies (TWAS) have successfully facilitated the dis- 13 covery of novel genetic risk loci for many complex traits, including late-onset Alzheimer’s disease 14 (AD). However, most existing TWAS methods rely only on gene expression and ignore epige- 15 netic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer- 16 promoter interactions), both of which contribute significantly to the genetic basis ofAD. -
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. -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells. -
Androgen Receptor Interacting Proteins and Coregulators Table
ANDROGEN RECEPTOR INTERACTING PROTEINS AND COREGULATORS TABLE Compiled by: Lenore K. Beitel, Ph.D. Lady Davis Institute for Medical Research 3755 Cote Ste Catherine Rd, Montreal, Quebec H3T 1E2 Canada Telephone: 514-340-8260 Fax: 514-340-7502 E-Mail: [email protected] Internet: http://androgendb.mcgill.ca Date of this version: 2010-08-03 (includes articles published as of 2009-12-31) Table Legend: Gene: Official symbol with hyperlink to NCBI Entrez Gene entry Protein: Protein name Preferred Name: NCBI Entrez Gene preferred name and alternate names Function: General protein function, categorized as in Heemers HV and Tindall DJ. Endocrine Reviews 28: 778-808, 2007. Coregulator: CoA, coactivator; coR, corepressor; -, not reported/no effect Interactn: Type of interaction. Direct, interacts directly with androgen receptor (AR); indirect, indirect interaction; -, not reported Domain: Interacts with specified AR domain. FL-AR, full-length AR; NTD, N-terminal domain; DBD, DNA-binding domain; h, hinge; LBD, ligand-binding domain; C-term, C-terminal; -, not reported References: Selected references with hyperlink to PubMed abstract. Note: Due to space limitations, all references for each AR-interacting protein/coregulator could not be cited. The reader is advised to consult PubMed for additional references. Also known as: Alternate gene names Gene Protein Preferred Name Function Coregulator Interactn Domain References Also known as AATF AATF/Che-1 apoptosis cell cycle coA direct FL-AR Leister P et al. Signal Transduction 3:17-25, 2003 DED; CHE1; antagonizing regulator Burgdorf S et al. J Biol Chem 279:17524-17534, 2004 CHE-1; AATF transcription factor ACTB actin, beta actin, cytoplasmic 1; cytoskeletal coA - - Ting HJ et al. -
RET/PTC Activation in Papillary Thyroid Carcinoma
European Journal of Endocrinology (2006) 155 645–653 ISSN 0804-4643 INVITED REVIEW RET/PTC activation in papillary thyroid carcinoma: European Journal of Endocrinology Prize Lecture Massimo Santoro1, Rosa Marina Melillo1 and Alfredo Fusco1,2 1Istituto di Endocrinologia ed Oncologia Sperimentale del CNR ‘G. Salvatore’, c/o Dipartimento di Biologia e Patologia Cellulare e Molecolare, University ‘Federico II’, Via S. Pansini, 5, 80131 Naples, Italy and 2NOGEC (Naples Oncogenomic Center)–CEINGE, Biotecnologie Avanzate & SEMM, European School of Molecular Medicine, Naples, Italy (Correspondence should be addressed to M Santoro; Email: [email protected]) Abstract Papillary thyroid carcinoma (PTC) is frequently associated with RET gene rearrangements that generate the so-called RET/PTC oncogenes. In this review, we examine the data about the mechanisms of thyroid cell transformation, activation of downstream signal transduction pathways and modulation of gene expression induced by RET/PTC. These findings have advanced our understanding of the processes underlying PTC formation and provide the basis for novel therapeutic approaches to this disease. European Journal of Endocrinology 155 645–653 RET/PTC rearrangements in papillary growth factor, have been described in a fraction of PTC thyroid carcinoma patients (7). As illustrated in figure 1, many different genes have been found to be rearranged with RET in The rearranged during tansfection (RET) proto-onco- individual PTC patients. RET/PTC1 and 3 account for gene, located on chromosome 10q11.2, was isolated in more than 90% of all rearrangements and are hence, by 1985 and shown to be activated by a DNA rearrange- far, the most frequent variants (8–11). They result from ment (rearranged during transfection) (1).As the fusion of RET to the coiled-coil domain containing illustrated in Fig. -
Genome-Wide Analysis of Androgen Receptor Binding and Gene Regulation in Two CWR22-Derived Prostate Cancer Cell Lines
Endocrine-Related Cancer (2010) 17 857–873 Genome-wide analysis of androgen receptor binding and gene regulation in two CWR22-derived prostate cancer cell lines Honglin Chen1, Stephen J Libertini1,4, Michael George1, Satya Dandekar1, Clifford G Tepper 2, Bushra Al-Bataina1, Hsing-Jien Kung2,3, Paramita M Ghosh2,3 and Maria Mudryj1,4 1Department of Medical Microbiology and Immunology, University of California Davis, 3147 Tupper Hall, Davis, California 95616, USA 2Division of Basic Sciences, Department of Biochemistry and Molecular Medicine, Cancer Center and 3Department of Urology, University of California Davis, Sacramento, California 95817, USA 4Veterans Affairs Northern California Health Care System, Mather, California 95655, USA (Correspondence should be addressed to M Mudryj at Department of Medical Microbiology and Immunology, University of California, Davis; Email: [email protected]) Abstract Prostate carcinoma (CaP) is a heterogeneous multifocal disease where gene expression and regulation are altered not only with disease progression but also between metastatic lesions. The androgen receptor (AR) regulates the growth of metastatic CaPs; however, sensitivity to androgen ablation is short lived, yielding to emergence of castrate-resistant CaP (CRCaP). CRCaP prostate cancers continue to express the AR, a pivotal prostate regulator, but it is not known whether the AR targets similar or different genes in different castrate-resistant cells. In this study, we investigated AR binding and AR-dependent transcription in two related castrate-resistant cell lines derived from androgen-dependent CWR22-relapsed tumors: CWR22Rv1 (Rv1) and CWR-R1 (R1). Expression microarray analysis revealed that R1 and Rv1 cells had significantly different gene expression profiles individually and in response to androgen. -
Snapshot: the Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J
192 Cell SnapShot: The Splicing Regulatory Machinery Mathieu Gabut, Sidharth Chaudhry, and Benjamin J. Blencowe 133 Banting and Best Department of Medical Research, University of Toronto, Toronto, ON M5S 3E1, Canada Expression in mouse , April4, 2008©2008Elsevier Inc. Low High Name Other Names Protein Domains Binding Sites Target Genes/Mouse Phenotypes/Disease Associations Amy Ceb Hip Hyp OB Eye SC BM Bo Ht SM Epd Kd Liv Lu Pan Pla Pro Sto Spl Thy Thd Te Ut Ov E6.5 E8.5 E10.5 SRp20 Sfrs3, X16 RRM, RS GCUCCUCUUC SRp20, CT/CGRP; −/− early embryonic lethal E3.5 9G8 Sfrs7 RRM, RS, C2HC Znf (GAC)n Tau, GnRH, 9G8 ASF/SF2 Sfrs1 RRM, RS RGAAGAAC HipK3, CaMKIIδ, HIV RNAs; −/− embryonic lethal, cond. KO cardiomyopathy SC35 Sfrs2 RRM, RS UGCUGUU AChE; −/− embryonic lethal, cond. KO deficient T-cell maturation, cardiomyopathy; LS SRp30c Sfrs9 RRM, RS CUGGAUU Glucocorticoid receptor SRp38 Fusip1, Nssr RRM, RS ACAAAGACAA CREB, type II and type XI collagens SRp40 Sfrs5, HRS RRM, RS AGGAGAAGGGA HipK3, PKCβ-II, Fibronectin SRp55 Sfrs6 RRM, RS GGCAGCACCUG cTnT, CD44 DOI 10.1016/j.cell.2008.03.010 SRp75 Sfrs4 RRM, RS GAAGGA FN1, E1A, CD45; overexpression enhances chondrogenic differentiation Tra2α Tra2a RRM, RS GAAARGARR GnRH; overexpression promotes RA-induced neural differentiation SR and SR-Related Proteins Tra2β Sfrs10 RRM, RS (GAA)n HipK3, SMN, Tau SRm160 Srrm1 RS, PWI AUGAAGAGGA CD44 SWAP Sfrs8 RS, SWAP ND SWAP, CD45, Tau; possible asthma susceptibility gene hnRNP A1 Hnrnpa1 RRM, RGG UAGGGA/U HipK3, SMN2, c-H-ras; rheumatoid arthritis, systemic lupus