DOCSLIB.ORG

Open Full Page

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Open Full Page Published OnlineFirst June 4, 2014; DOI: 10.1158/1078-0432.CCR-13-3036 Clinical Cancer Biology of Human Tumors Research Next-Generation Sequencing of Translocation Renal Cell Carcinoma Reveals Novel RNA Splicing Partners and Frequent Mutations of Chromatin-Remodeling Genes Gabriel G. Malouf1, Xiaoping Su7, Hui Yao7, Jianjun Gao8, Liangwen Xiong8, Qiuming He8, Eva Comperat 2, Jer ome^ Couturier3, Vincent Molinie4, Bernard Escudier5, Philippe Camparo6, Denaha J. Doss9, Erika J. Thompson9, David Khayat1, Christopher G. Wood10, Willie Yu11, Bin T. Teh11, John Weinstein7, and Nizar M. Tannir8 Abstract Purpose: MITF/TFE translocation renal cell carcinoma (TRCC) is a rare subtype of kidney cancer. Its incidence and the genome-wide characterization of its genetic origin have not been fully elucidated. Experimental Design: We performed RNA and exome sequencing on an exploratory set of TRCC (n ¼ 7), and validated our findings using The Cancer Genome Atlas (TCGA) clear-cell RCC (ccRCC) dataset (n ¼ 460). Results: Using the TCGA dataset, we identified seven TRCC (1.5%) cases and determined their genomic profile. We discovered three novel partners of MITF/TFE (LUC7L3, KHSRP, and KHDRBS2) that are involved in RNA splicing. TRCC displayed a unique gene expression signature as compared with other RCC types, and showed activation of MITF, the transforming growth factor b1 and the PI3K complex targets. Genes differentially spliced between TRCC and other RCC types were enriched for MITF and ID2 targets. Exome sequencing of TRCC revealed a distinct mutational spectrum as compared with ccRCC, with frequent mutations in chromatin-remodeling genes (six of eight cases, three of which were from the TCGA). In two cases, we identified mutations in INO80D, an ATP-dependent chromatin-remodeling gene, previously shown to control the amplitude of the S phase. Knockdown of INO80D decreased cell proliferation in a novel cell line bearing LUC7L3–TFE3 translocation. Conclusions: This genome-wide study defines the incidence of TRCC within a ccRCC-directed project and expands the genomic spectrum of TRCC by identifying novel MITF/TFE partners involved in RNA splicing and frequent mutations in chromatin-remodeling genes. Clin Cancer Res; 20(15); 4129–40. Ó2014 AACR. Introduction Authors' Affiliations: Departments of 1Medical Oncology and 2Pathology, Groupe Hospitalier Pitie-Salp etri^ ere, Assistance Publique Hopitaux de Translocation renal cell carcinoma (TRCC) is a rare Paris, Faculty of Medicine Pierre et Marie Curie, Institut Universitaire de Cancerologie GRC5, University Paris 6; 3Department of Genetics, Institut subtype of kidney cancer that was added to the World Curie; 4Department of Pathology, Hopital^ Saint Joseph, Paris; 5Department Health Organization (WHO) classification in 2004 (1) and of Medical Oncology, Institut Gustave Roussy, Villejuif; 6Centre de Patho- is histologically and genomically a heterogeneous disease logie, Amiens, Picardie, France; Departments of 7Bioinformatics and Computational Biology and 8Genitourinary Medical Oncology, 9DNA Anal- (2, 3). TRCC is characterized by translocations involving the ysis Facility, Department of Genetics, 10Division of Surgery, Department of genes for transcription factors E3 (TFE3) and EB (TFEB; Urology, The University of Texas MD Anderson Cancer Center, Houston, refs. 1–4). TFE3 and TFEB belong to the microphthalmia Texas; and 11Cancer and Stem Cell Biology Program, Duke-NUS Graduate Medical School, Singapore, Singapore transcription factor/transcription factor E (MITF/TFE) fam- Note: Supplementary data for this article are available at Clinical Cancer ily of basic helix-loop-helix leucine zipper (bHLH-LZ), and Research Online (http://clincancerres.aacrjournals.org/). are often called MITF TRCC. Although the TFEB gene has been reported to fuse exclusively with the Alpha gene, G.G. Malouf, X. Su, and H. Yao contributed equally to this article and share first authorship. leading to t(6;11)(p21;q21) translocation, the TFE3 gene Corresponding Authors: Nizar M. Tannir, University of Texas MD Ander- (Xp11.2) has been found to rearrange with at least five son Cancer Center, 1155 Pressler Street, Unit 1374, Houston, TX 77030- different partners: PRCC (1q21), ASPSCR1 (17q25), SFPQ 3721. Phone: 713-563-7265; Fax: 713-745-0422; E-mail: (1p34), NONO (Xq12), and CLTC (17q23; refs. 1–6). The [email protected]; and Gabriel G. Malouf, Department of Medical Oncology, Hopital^ de la Pitie-salp etriere,^ 43, Boulevard de l'Hopital,^ 75013, breakpoints of those translocations differ according to the Paris, France. Phone: þ33 1 42 16 04 61; Fax: þ33142160423; TFE3 partner, and all TFE3 fusion proteins contain the [email protected] bHLH-LZ and transcriptional activation domains of TFE3 doi: 10.1158/1078-0432.CCR-13-3036 (7). Unlike TFE3, the TFEB gene rearranges with Alpha,an Ó2014 American Association for Cancer Research. intronless gene, leading to a translocation that preserves the www.aacrjournals.org 4129 Downloaded from clincancerres.aacrjournals.org on September 26, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst June 4, 2014; DOI: 10.1158/1078-0432.CCR-13-3036 Malouf et al. Cancer Center (MDACC) and Institut Curie, fresh tissue Translational Relevance specimens were obtained at the time of nephrectomy and We performed exome and RNA sequencing on seven stored at À80C until DNA and RNA extraction were MITF/TFE translocation renal cell carcinoma (TRCC) carried out. The clinicopathologic characteristics of these tumors and validated our findings in seven of 460 cases are summarized in Supplementary Table S1. Geno- (1.5%) clear-cell RCC cases from The Cancer Genome mic DNA with matched normal DNA (adjacent normal Atlas (TCGA). We discovered three novel partners of kidney tissue) was available from three cases (Supple- MITF/TFE (LUC7L3, KHSRP, and KHDRBS2) that are mentary Table S1). RNA from seven controls (three pap- involved in RNA splicing. TRCC displayed a unique gene illary RCC, one ccRCC, and three normal kidney samples) expression signature with activation of MITF, the trans- was included. RNA was available for seven cases (Sup- forming growth factor b1, and the PI3K complexes. plementary Table S1). DNA extraction was performed Genes differentially spliced between TRCC and using the DNeasy Blood & Tissue Kit (Qiagen) according other RCC types were enriched for MITF targets, sug- to the manufacturer’s instructions. RNA extraction was gesting a putative role for RNA splicing in kidney performed using the RNeasy Kit (Qiagen) according to carcinogenesis. Exome sequencing revealed mutations the manufacturer’s instructions. in the chromatin-remodeling gene INO80D.Ourstudy expands the spectrum of TRCC and raises potential RNA sequencing therapeutic implications. Total RNA for each sample was converted into a library of template molecules for sequencing on the Illumina HiSeq 2000 according to the NuGen Ovation RNA-Seq System V2 protocol. The details are reported in Supplementary Mate- TFEB full-length coding region, which becomes dysregu- rials and Methods. lated by the Alpha gene promoter (8). TRCC represents 15% of RCC in patients younger than Mapping/alignment 40 years (9, 10). The incidence of TRCC varies between 1% We checked the quality of the sequencing data by using and 6% according to previously published studies, several HTSeq package. The raw paired-end reads in FASTQ format TFE3 of which used morphology and expression alone to were then aligned to the human reference genome, screen for RCC cases with translocation (10–12). However, GRCh37/hg19, using MOSAIK alignment software (20). the true incidence of TRCC in an unselected cohort of MOSAIK works with paired-end reads from Illumina HiSeq pathologically confirmed clear-cell RCC (ccRCC) remains 2000 and uses both a hashing scheme and the Smith– to be determined. Next-generation sequencing highly Waterman algorithm to produce gapped optimal align- improved our understanding of ccRCC, known to bear ments and to map exon junction-spanning reads with a inactivation of the von Hippel-Lindau (VHL) tumor-sup- local alignment option for RNA-Seq. The resulting pair-wise pressor gene, located on chromosome 3p arm (13). Large- alignments were then consolidated into a multiple scale screening has identified several new cancer genes that sequence alignment (assembly) and saved as a standard PBRM1 include mutations in the SWI/SNF family gene (14) bam file. and BAP1 (15), as well as mutations in chromatin remo- KDM6A KDM5C SETD2 ( ) delers such as (16), , and 17 .To Identification of differentially expressed genes from date, the genetic basis and origins of TRCC remain poorly RNA-Seq understood on a genome-wide scale. The details are presented in Supplementary Materials and Compared with ccRCC, which displays gene expression Methods. profiles composed of two main transcriptomic subsets named ccA and ccB (18), the transcriptomic signature of Fusion detection from RNA-Seq TRCC remains obscure. Although in a previous study A modified version of VirusSeq that implements a MITF/TFE tumors of the family were shown to display a greedy algorithm with a robust statistical model was unique gene expression signature (19), their full transcrip- implemented and used in gene fusion discovery for tomic signature remains unknown. RNA-Seq data (21). The TRCC cases were confirmed by In this study, we report the incidence and describe the another bioinformatic pipeline called FusionSeq (22). MITF/TFE genomic profile of translocations of the family Specifically,
Load more

Recommended publications
  • Prevalence and Significance of Nonsense-‐Mediated Mrna Decay
    Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms By Courtney Elizabeth French A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Molecular and Cell Biology in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Steven E. Brenner, Co-Chair Professor Donald C. Rio, Co-Chair Professor Britt A. Glaunsinger Professor Sandrine Dudoit Spring 2016 Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms Copyright 2016 by Courtney Elizabeth French Abstract Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms by Courtney Elizabeth French Doctor of Philosophy in Molecular and Cell Biology University of California, Berkeley Professor Steven E. Brenner, Co-Chair Professor Donald C. Rio, Co-Chair Alternative splicing plays a crucial role in increasing the amount of protein diversity and in regulating gene expression at the post-transcriptional level. In humans, almost all genes produce more than one mRNA isoform and, while the fraction varies, many other species also have a substantial number of alternatively spliced genes. Alternative splicing is regulated by splicing factors, often in a developmental time- or tissue-specific manner. Mis- regulation of alternative splicing, via mutations in splice sites, splicing regulatory elements, or splicing factors, can lead to disease states, including cancers. Thus, characterizing how alternative splicing shapes the transcriptome will lead to greater insights into the regulation of numerous cellular pathways and many aspects of human health. A critical tool for investigating alternative splicing is high-throughput mRNA sequencing (RNA-seq).
    [Show full text]
  • Mygene.Info R Client
    MyGene.info R Client Adam Mark, Ryan Thompson, Chunlei Wu May 19, 2021 Contents 1 Overview ..............................2 2 Gene Annotation Service ...................2 2.1 getGene .............................2 2.2 getGenes ............................2 3 Gene Query Service ......................3 3.1 query ..............................3 3.2 queryMany ...........................4 4 makeTxDbFromMyGene....................5 5 Tutorial, ID mapping .......................6 5.1 Mapping gene symbols to Entrez gene ids ........6 5.2 Mapping gene symbols to Ensembl gene ids .......7 5.3 When an input has no matching gene ...........8 5.4 When input ids are not just symbols ............8 5.5 When an input id has multiple matching genes ......9 5.6 Can I convert a very large list of ids?............ 11 6 References ............................. 11 MyGene.info R Client 1 Overview MyGene.Info provides simple-to-use REST web services to query/retrieve gene annotation data. It’s designed with simplicity and performance emphasized. mygene is an easy-to-use R wrapper to access MyGene.Info services. 2 Gene Annotation Service 2.1 getGene • Use getGene, the wrapper for GET query of "/gene/<geneid>" service, to return the gene object for the given geneid. > gene <- getGene("1017", fields="all") > length(gene) [1] 1 > gene["name"] [[1]] NULL > gene["taxid"] [[1]] NULL > gene["uniprot"] [[1]] NULL > gene["refseq"] [[1]] NULL 2.2 getGenes • Use getGenes, the wrapper for POST query of "/gene" service, to return the list of gene objects for the given character vector of geneids. > getGenes(c("1017","1018","ENSG00000148795")) DataFrame with 3 rows and 7 columns 2 MyGene.info R Client query _id X_version entrezgene name <character> <character> <integer> <character> <character> 1 1017 1017 4 1017 cyclin dependent kin.
    [Show full text]
  • Arginine-Enriched Mixed-Charge Domains Provide Cohesion for Nuclear Speckle Condensation
    bioRxiv preprint doi: https://doi.org/10.1101/771592; this version posted September 16, 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. 1 Arginine-enriched mixed-charge domains provide cohesion for nuclear 2 speckle condensation 3 4 Jamie A. Greig1, Tu Anh Nguyen1, Michelle Lee1, Alex S. Holehouse2, Ammon E. 5 Posey2, Rohit V. Pappu2, and Gregory JeDD1* 6 7 1Temasek Life Sciences Laboratory & Department of Biological Sciences, The 8 National University of Singapore, Singapore 117604 9 2Department of BiomeDical Engineering anD Center for Science & Engineering of 10 Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO 63130, 11 USA 12 13 *CorresponDence: [email protected] 14 15 Abstract 16 Low-complexity protein Domains promote the formation of various biomolecular 17 conDensates. However, in many cases, the precise sequence features governing 18 conDensate formation anD iDentity remain unclear. Here, we investigate the role of 19 intrinsically DisordereD mixeD-charge Domains (MCDs) in nuclear speckle 20 conDensation. Proteins composeD exclusively of arginine/aspartic-aciD DipeptiDe 21 repeats unDergo length-DepenDent conDensation anD speckle incorporation. 22 Substituting arginine with lysine in synthetic anD natural speckle-associateD MCDs 23 abolishes these activities, iDentifying a key role for multivalent contacts through 24 arginine’s guaniDinium ion. MCDs can synergise with a speckle-associateD RNA 25 recognition motif to promote speckle specificity anD resiDence. MCD behaviour is 26 tuneable through net-charge: increasing negative charge abolishes conDensation anD 27 speckle incorporation.
    [Show full text]
  • RNA Splicing Regulated by RBFOX1 Is Essential for Cardiac Function in Zebrafish Karen S
    © 2015. Published by The Company of Biologists Ltd | Journal of Cell Science (2015) 128, 3030-3040 doi:10.1242/jcs.166850 RESEARCH ARTICLE RNA splicing regulated by RBFOX1 is essential for cardiac function in zebrafish Karen S. Frese1,2,*, Benjamin Meder1,2,*, Andreas Keller3,4, Steffen Just5, Jan Haas1,2, Britta Vogel1,2, Simon Fischer1,2, Christina Backes4, Mark Matzas6, Doreen Köhler1, Vladimir Benes7, Hugo A. Katus1,2 and Wolfgang Rottbauer5,‡ ABSTRACT U2, U4, U5 and U6) and several hundred associated regulator Alternative splicing is one of the major mechanisms through which proteins (Wahl et al., 2009). Some of the best-characterized the proteomic and functional diversity of eukaryotes is achieved. splicing regulators include the serine-arginine (SR)-rich family, However, the complex nature of the splicing machinery, its associated heterogeneous nuclear ribonucleoproteins (hnRNPs) proteins, and splicing regulators and the functional implications of alternatively the Nova1 and Nova2, and the PTB and nPTB (also known as spliced transcripts are only poorly understood. Here, we investigated PTBP1 and PTBP2) families (David and Manley, 2008; Gabut et al., the functional role of the splicing regulator rbfox1 in vivo using the 2008; Li et al., 2007; Matlin et al., 2005). The diversity in splicing is zebrafish as a model system. We found that loss of rbfox1 led to further increased by the location and nucleotide sequence of pre- progressive cardiac contractile dysfunction and heart failure. By using mRNA enhancer and silencer motifs that either promote or inhibit deep-transcriptome sequencing and quantitative real-time PCR, we splicing by the different regulators. Adding to this complexity, show that depletion of rbfox1 in zebrafish results in an altered isoform regulating motifs are very common throughout the genome, but are expression of several crucial target genes, such as actn3a and hug.
    [Show full text]
  • Mygene.Info R Client
    MyGene.info R Client Adam Mark, Ryan Thompson, Chunlei Wu May 19, 2021 Contents 1 Overview ..............................2 2 Gene Annotation Service ...................2 2.1 getGene .............................2 2.2 getGenes ............................2 3 Gene Query Service ......................3 3.1 query ..............................3 3.2 queryMany ...........................4 4 makeTxDbFromMyGene....................5 5 Tutorial, ID mapping .......................6 5.1 Mapping gene symbols to Entrez gene ids ........6 5.2 Mapping gene symbols to Ensembl gene ids .......7 5.3 When an input has no matching gene ...........8 5.4 When input ids are not just symbols ............8 5.5 When an input id has multiple matching genes ......9 5.6 Can I convert a very large list of ids?............ 11 6 References ............................. 11 MyGene.info R Client 1 Overview MyGene.Info provides simple-to-use REST web services to query/retrieve gene annotation data. It’s designed with simplicity and performance emphasized. mygene is an easy-to-use R wrapper to access MyGene.Info services. 2 Gene Annotation Service 2.1 getGene • Use getGene, the wrapper for GET query of "/gene/<geneid>" service, to return the gene object for the given geneid. > gene <- getGene("1017", fields="all") > length(gene) [1] 1 > gene["name"] [[1]] NULL > gene["taxid"] [[1]] NULL > gene["uniprot"] [[1]] NULL > gene["refseq"] [[1]] NULL 2.2 getGenes • Use getGenes, the wrapper for POST query of "/gene" service, to return the list of gene objects for the given character vector of geneids. > getGenes(c("1017","1018","ENSG00000148795")) DataFrame with 3 rows and 7 columns 2 MyGene.info R Client query _id X_version entrezgene name <character> <character> <integer> <character> <character> 1 1017 1017 4 1017 cyclin dependent kin.
    [Show full text]
  • Inhibition of the MID1 Protein Complex
    Matthes et al. Cell Death Discovery (2018) 4:4 DOI 10.1038/s41420-017-0003-8 Cell Death Discovery ARTICLE Open Access Inhibition of the MID1 protein complex: a novel approach targeting APP protein synthesis Frank Matthes1,MoritzM.Hettich1, Judith Schilling1, Diana Flores-Dominguez1, Nelli Blank1, Thomas Wiglenda2, Alexander Buntru2,HannaWolf1, Stephanie Weber1,InaVorberg 1, Alina Dagane2, Gunnar Dittmar2,3,ErichWanker2, Dan Ehninger1 and Sybille Krauss1 Abstract Alzheimer’s disease (AD) is characterized by two neuropathological hallmarks: senile plaques, which are composed of amyloid-β (Aβ) peptides, and neurofibrillary tangles, which are composed of hyperphosphorylated tau protein. Aβ peptides are derived from sequential proteolytic cleavage of the amyloid precursor protein (APP). In this study, we identified a so far unknown mode of regulation of APP protein synthesis involving the MID1 protein complex: MID1 binds to and regulates the translation of APP mRNA. The underlying mode of action of MID1 involves the mTOR pathway. Thus, inhibition of the MID1 complex reduces the APP protein level in cultures of primary neurons. Based on this, we used one compound that we discovered previously to interfere with the MID1 complex, metformin, for in vivo experiments. Indeed, long-term treatment with metformin decreased APP protein expression levels and consequently Aβ in an AD mouse model. Importantly, we have initiated the metformin treatment late in life, at a time-point where mice were in an already progressed state of the disease, and could observe an improved behavioral phenotype. These 1234567890 1234567890 findings together with our previous observation, showing that inhibition of the MID1 complex by metformin also decreases tau phosphorylation, make the MID1 complex a particularly interesting drug target for treating AD.
    [Show full text]
  • Bioinformatics Tools for the Analysis of Gene-Phenotype Relationships Coupled with a Next Generation Chip-Sequencing Data Processing Pipeline
    Bioinformatics Tools for the Analysis of Gene-Phenotype Relationships Coupled with a Next Generation ChIP-Sequencing Data Processing Pipeline Erinija Pranckeviciene Thesis submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the Doctorate in Philosophy degree in Cellular and Molecular Medicine Department of Cellular and Molecular Medicine Faculty of Medicine University of Ottawa c Erinija Pranckeviciene, Ottawa, Canada, 2015 Abstract The rapidly advancing high-throughput and next generation sequencing technologies facilitate deeper insights into the molecular mechanisms underlying the expression of phenotypes in living organisms. Experimental data and scientific publications following this technological advance- ment have rapidly accumulated in public databases. Meaningful analysis of currently avail- able data in genomic databases requires sophisticated computational tools and algorithms, and presents considerable challenges to molecular biologists without specialized training in bioinfor- matics. To study their phenotype of interest molecular biologists must prioritize large lists of poorly characterized genes generated in high-throughput experiments. To date, prioritization tools have primarily been designed to work with phenotypes of human diseases as defined by the genes known to be associated with those diseases. There is therefore a need for more prioritiza- tion tools for phenotypes which are not related with diseases generally or diseases with which no genes have yet been associated in particular. Chromatin immunoprecipitation followed by next generation sequencing (ChIP-Seq) is a method of choice to study the gene regulation processes responsible for the expression of cellular phenotypes. Among publicly available computational pipelines for the processing of ChIP-Seq data, there is a lack of tools for the downstream analysis of composite motifs and preferred binding distances of the DNA binding proteins.
    [Show full text]
  • Anti-LUC7L3 (Aa 1-110) Polyclonal Antibody (DPAB-DC2207) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
    Anti-LUC7L3 (aa 1-110) polyclonal antibody (DPAB-DC2207) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Antigen Description This gene encodes a protein with an N-terminal half that contains cysteine/histidine motifs and leucine zipper-like repeats, and the C-terminal half is rich in arginine and glutamate residues (RE domain) and arginine and serine residues (RS domain). This protein localizes with a speckled pattern in the nucleus, and could be involved in the formation of splicesome via the RE and RS domains. Two alternatively spliced transcript variants encoding the same protein have been found for this gene. Immunogen CROP (NP_006098, 1 a.a. ~ 110 a.a) partial recombinant protein with GST tag. The sequence is MISAAQLLDELMGRDRNLAPDEKRSNVRWDHESVCKYYLCGFCPAELFTNTRSDLGPCEKIHD ENLRKQYEKSSRFMKVGYERDFLRYLQSLLAEVERRIRRGHARLALS Source/Host Mouse Species Reactivity Human Conjugate Unconjugated Applications WB (Cell lysate), WB (Recombinant protein), ELISA, Size 50 μl Buffer 50 % glycerol Preservative None Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. GENE INFORMATION Gene Name LUC7L3 LUC7-like 3 (S. cerevisiae) [ Homo sapiens (human) ] Official Symbol LUC7L3 Synonyms LUC7L3; LUC7-like 3 (S. cerevisiae); CRA; CROP; LUC7A; hLuc7A; CREAP-1; OA48-18; luc7- like protein 3; CRE-associated protein 1; cAMP regulatory element-associated protein 1; okadaic 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221
    [Show full text]
  • Multi-Cancer Molecular Signatures and Their Interrelationships
    Multi-cancer molecular signatures and their interrelationships Wei-Yi Cheng1, Tai-Hsien Ou Yang1, Hui Shen2, Peter W. Laird2, Dimitris Anastassiou1 and the Cancer Genome Atlas Research Network 1Columbia Initiative in Systems Biology and Department of Electrical Engineering, Columbia University, New York, NY, USA 2USC Epigenome Center, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. Corresponding Author Dimitris Anastassiou, Columbia Initiative in Systems Biology and Department of Electrical Engineering, Columbia University, 1312S.W.Mudd Building, – Mail Code 4712, 500 West 120th Street, USA. Phone:+1212854-3113; E-mail: [email protected] This is version 2. A previous version of the same article appears at http://arxiv.org/pdf/1306.2584v1.pdf dated June 11, 2013. Please note: The pan-cancer molecular signatures disclosed in this article are the results of applying our data mining algorithm to the rich TCGA “pancan12” data sets from twelve different cancer types. These signatures have been identified as patterns, without any indication about their arXiv:1306.2584v2 [q-bio.QM] 11 Jul 2013 role or potential usefulness. We believe that each of them represents an important biomolecular event in cancer. We invite the cancer research community to contact us and help us interpret each of these pan-cancer signatures, and to investigate them for potential applications in diagnostic, prognostic and therapeutic products applicable to multiple cancer types. There will be additional versions of this article and we expect that the final version will contain many co-authors. 1 Although cancer is known to be characterized by several unifying biological hallmarks, systems biology has had limited success in identifying molecular signatures present in in all types of cancer.
    [Show full text]
  • C9orf72-Associated SMCR8 Protein Binds in the Ubiquitin Pathway and with Proteins Linked with Neurological Disease John L
    Goodier et al. Acta Neuropathologica Communications (2020) 8:110 https://doi.org/10.1186/s40478-020-00982-x RESEARCH Open Access C9orf72-associated SMCR8 protein binds in the ubiquitin pathway and with proteins linked with neurological disease John L. Goodier1*, Alisha O. Soares1, Gavin C. Pereira1, Lauren R. DeVine2, Laura Sanchez3, Robert N. Cole2 and Jose Luis García-Pérez3,4 Abstract A pathogenic GGGCCC hexanucleotide expansion in the first intron/promoter region of the C9orf72 gene is the most common mutation associated with amyotrophic lateral sclerosis (ALS). The C9orf72 gene product forms a complex with SMCR8 (Smith-Magenis Syndrome Chromosome Region, Candidate 8) and WDR41 (WD Repeat domain 41) proteins. Recent studies have indicated roles for the complex in autophagy regulation, vesicle trafficking, and immune response in transgenic mice, however a direct connection with ALS etiology remains unclear. With the aim of increasing understanding of the multi-functional C9orf72-SMCR8-WDR41 complex, we determined by mass spectrometry analysis the proteins that directly associate with SMCR8. SMCR8 protein binds many components of the ubiquitin-proteasome system, and we demonstrate its poly-ubiquitination without obvious degradation. Evidence is also presented for localization of endogenous SMCR8 protein to cytoplasmic stress granules. However, in several cell lines we failed to reproduce previous observations that C9orf72 protein enters these granules. SMCR8 protein associates with many products of genes associated with various Mendelian neurological disorders in addition to ALS, implicating SMCR8-containing complexes in a range of neuropathologies. We reinforce previous observations that SMCR8 and C9orf72 protein levels are positively linked, and now show in vivo that SMCR8 protein levels are greatly reduced in brain tissues of C9orf72 gene expansion carrier individuals.
    [Show full text]
  • LUC7L3/CROP Inhibits Replication of Hepatitis B Virus Via Suppressing Enhancer II/Basal Core Promoter Activity
    www.nature.com/scientificreports OPEN LUC7L3/CROP inhibits replication of hepatitis B virus via suppressing enhancer II/basal core promoter Received: 27 May 2016 Accepted: 20 October 2016 activity Published: 18 NOvember 2016 Yuan Li, Masahiko Ito, Suofeng Sun, Takeshi Chida, Kenji Nakashima & Tetsuro Suzuki The core promoter of hepatitis B virus (HBV) genome is a critical region for transcriptional initiation of 3.5 kb, pregenome and precore RNAs and for the viral replication. Although a number of host-cell factors that potentially regulate the viral promoter activities have been identified, the molecular mechanisms of the viral gene expression, in particular, regulatory mechanisms of the transcriptional repression remain elusive. In this study, we identified LUC7 like 3 pre-mRNA splicing factor (LUC7L3, also known as hLuc7A or CROP) as a novel interacting partner of HBV enhancer II and basal core promoter (ENII/BCP), key elements within the core promoter, through the proteomic screening and found that LUC7L3 functions as a negative regulator of ENII/BCP. Gene silencing of LUC7L3 significantly increased expression of the viral genes and antigens as well as the activities of ENII/BCP and core promoter. In contrast, overexpression of LUC7L3 inhibited their activities and HBV replication. In addition, LUC7L3 possibly contributes to promotion of the splicing of 3.5 kb RNA, which may also be involved in negative regulation of the pregenome RNA level. This is the first to demonstrate the involvement of LUC7L3 in regulation of gene transcription and in viral replication. Hepatitis B virus (HBV) infection is a major cause of acute and chronic hepatitis and is closely associated with development of cirrhosis and hepatocellular carcinoma (HCC) worldwide.
    [Show full text]
  • Changes in the Gene Expression Profile During Spontaneous Migraine Attacks
    www.nature.com/scientificreports OPEN Changes in the gene expression profle during spontaneous migraine attacks Lisette J. A. Kogelman1,7*, Katrine Falkenberg1,7, Alfonso Buil2, Pau Erola3, Julie Courraud4, Susan Svane Laursen4, Tom Michoel5, Jes Olesen1 & Thomas F. Hansen1,2,6* Migraine attacks are delimited, allowing investigation of changes during and outside attack. Gene expression fuctuates according to environmental and endogenous events and therefore, we hypothesized that changes in RNA expression during and outside a spontaneous migraine attack exist which are specifc to migraine. Twenty-seven migraine patients were assessed during a spontaneous migraine attack, including headache characteristics and treatment efect. Blood samples were taken during attack, two hours after treatment, on a headache-free day and after a cold pressor test. RNA- Sequencing, genotyping, and steroid profling were performed. RNA-Sequences were analyzed at gene level (diferential expression analysis) and at network level, and genomic and transcriptomic data were integrated. We found 29 diferentially expressed genes between ‘attack’ and ‘after treatment’, after subtracting non-migraine specifc genes, that were functioning in fatty acid oxidation, signaling pathways and immune-related pathways. Network analysis revealed mechanisms afected by changes in gene interactions, e.g. ‘ion transmembrane transport’. Integration of genomic and transcriptomic data revealed pathways related to sumatriptan treatment, i.e. ‘5HT1 type receptor mediated signaling pathway’. In conclusion, we uniquely investigated intra-individual changes in gene expression during a migraine attack. We revealed both genes and pathways potentially involved in the pathophysiology of migraine and/or migraine treatment. With a world-wide prevalence of 14.4% and global estimates of 5.6 years lost to disability, migraine is placed as the 2nd most disabling disease by the World Health Organization 1.
    [Show full text]