DOCSLIB.ORG

Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers Published OnlineFirst May 2, 2014; DOI: 10.1158/2159-8290.CD-14-0212 RESEARCH ARTICLE Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers Daniel J. Park 1 , K a y o k o Ta o 7 , Florence Le Calvez-Kelm 17 , Tu Nguyen-Dumont 1 , Nivonirina Robinot 17 , Fleur Hammet1 , Fabrice Odefrey 1 , Helen Tsimiklis 1 , Zhi L. Teo 1 , Louise B. Thingholm 1 , Erin L. Young 7 , Catherine Voegele 17 , Andrew Lonie 4 , Bernard J. Pope 2 , 4 , Terrell C. Roane 10 , Russell Bell 7 , Hao Hu 11 , Shankaracharya 11 , Chad D. Huff 11 , Jonathan Ellis 6 , Jun Li 6 , Igor V. Makunin 6 , Esther M. John 12 , 13 , Irene L. Andrulis 19 , Mary B. Terry 14 , Mary Daly 15 , Saundra S. Buys 9 , Carrie Snyder 16 , Henry T. Lynch 16 , Peter Devilee20 , Graham G. Giles 3 , 5 , John L. Hopper 3 , 21 , Bing-Jian Feng 8 , 9 , Fabienne Lesueur 17 , 18 , Sean V. Tavtigian 7 , Melissa C. Southey 1 , and David E. Goldgar 8 , 9 ABSTRACT Approximately half of the familial aggregation of breast cancer remains unex- plained. A multiple-case breast cancer family exome-sequencing study identifi ed three likely pathogenic mutations in RINT1 (NM_021930.4) not present in public sequencing data- bases: RINT1 c.343C>T (p.Q115X), c.1132_1134del (p.M378del), and c.1207G>T (p.D403Y). On the basis of this fi nding, a population-based case–control mutation-screening study was conducted that identifi ed 29 carriers of rare (minor allele frequency < 0.5%), likely pathogenic variants: 23 in 1,313 early-onset breast cancer cases and six in 1,123 frequency-matched controls [OR, 3.24; 95% confi - dence interval (CI), 1.29–8.17; P = 0.013]. RINT1 mutation screening of probands from 798 multiple- case breast cancer families identifi ed four additional carriers of rare genetic variants. Analysis of the incidence of fi rst primary cancers in families of women carrying RINT1 mutations estimated that car- riers were at increased risk of Lynch syndrome–spectrum cancers [standardized incidence ratio (SIR), 3.35; 95% CI, 1.7–6.0; P = 0.005], particularly for relatives diagnosed with cancer under the age of 60 years (SIR, 10.9; 95% CI, 4.7–21; P = 0.0003). SIGNIFICANCE: The work described in this study adds RINT1 to the growing list of genes in which rare sequence variants are associated with intermediate levels of breast cancer risk. Given that RINT1 is also associated with a spectrum of cancers with mismatch repair defects, these fi ndings have clinical applications and raise interesting biological questions. Cancer Discov; 4(7); 804–15. ©2014 AACR. See related commentary by Ngeow and Eng, p. 762. 804 | CANCER DISCOVERYJULY 2014 www.aacrjournals.org Downloaded from cancerdiscovery.aacrjournals.org on September 27, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst May 2, 2014; DOI: 10.1158/2159-8290.CD-14-0212 INTRODUCTION Although there has been substantial progress in the last 20 years in identifying genetic causes of breast cancer, a Large population-based studies have established that considerable proportion of the familial risk remains unex- women with a family history of breast cancer are at approx- plained. The current estimate of the proportion of familial imately 2- to 3-fold increased risk of the disease ( 1–3 ). risk explained by rare mutations in the high-risk breast Authors’ Affi liations: 1 Genetic Epidemiology Laboratory, Department of ada; 20Department of Human Genetics, Leiden University Medical Center, Pathology; 2 Department of Computing and Information Systems; 3 Centre Leiden, the Netherlands; and 21 School of Public Health, Seoul National for Epidemiology and Biostatistics, Melbourne School of Population and University, Seoul, Korea 4 Global Health, The University of Melbourne, Melbourne; Victorian Life Note: Supplementary data for this article are available at Cancer Discovery 5 Sciences Computation Initiative; Centre for Cancer Epidemiology, The Online (http://cancerdiscovery.aacrjournals.org/). Cancer Council Victoria, Carlton, Victoria; 6 The QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia; Departments of 7 Onco- D.J. Park, K. Tao, and F. Le Calvez-Kelm contributed equally to this work. F. Lesueur, logical Sciences and 8 Dermatology, Huntsman Cancer Institute, University S.V. Tavtigian, M.C. Southey, and D.E. Goldgar contributed equally to this work. of Utah School of Medicine; 9 Huntsman Cancer Institute, University of Esther M. John’s contribution to this article is, in part, on behalf of the Breast Utah Health Sciences Center, Salt Lake City, Utah; 10 University of Texas at Cancer Family Registry. Melissa C. Southey’s contribution to this article is, Austin, Austin; 11 Department of Epidemiology, The University of Texas MD in part, on behalf of the Kathleen Cuningham Foundation Consortium for Anderson Cancer Center, Houston, Texas; 12 Cancer Prevention Institute of Research into Familial Breast Cancer. 13 California, Fremont; Department of Health Research and Policy, Stanford Corresponding Authors: Melissa C. Southey, Department of Pathology, 14 Cancer Institute, Stanford, California; Department of Epidemiology, Mail- The University of Melbourne, Melbourne, VIC 3010, Australia. Phone: man School of Public Health, Columbia University, New York, New York; 61-3-8344-4895; Fax: 61-3-8344-4004; E-mail: [email protected]. 15 16 Fox Chase Cancer Center, Philadelphia, Pennsylvania; Department of au ; and David E. Goldgar, Department of Dermatology, Huntsman Cancer 17 Preventive Medicine, Creighton University, Omaha, Nebraska; Genetic Institute, University of Utah School of Medicine, 30 N. Medical Drive, Salt Cancer Susceptibility Group, International Agency for Research on Can- Lake City, UT 84112. Phone: 801-585-0337; Fax: 801-585-0990; E-mail: 18 cer, Lyon; Genetic Epidemiology of Cancer Team, Institut National de la [email protected] Santé et de la Recherche Medicale (INSERM), U900, Institut Curie, Mines doi: 10.1158/2159-8290.CD-14-0212 ParisTech, Paris, France; 19 Department of Molecular Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Can- © 2014 American Association for Cancer Research. JULY 2014CANCER DISCOVERY | 805 Downloaded from cancerdiscovery.aacrjournals.org on September 27, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst May 2, 2014; DOI: 10.1158/2159-8290.CD-14-0212 RESEARCH ARTICLE Park et al. cancer susceptibility genes BRCA1 [Mendelian Inheritance in the public sequencing databases. The nonsense substitu- in Man (MIM) 113705], BRCA2 (MIM 600185), and PALB2 tion was carried by both women included in the WES from (MIM 610355) is 20%, and another 28% is explained by asso- the family in which it was observed. The in-frame deletion ciations with common genetic variants ( 4 ), although these (c.1132_1134del) and missense substitution (c.1207G>T; proportions are highly dependent on age at diagnosis. A fur- p.D403Y) were observed in one WES subject each, but both ther approximately 5% is likely to be explained by mutations fall at protein positions that are highly evolutionarily con- in genes in the homologous recombination repair detection served and are thus likely to be damaging to protein function and signaling pathways, including MRE11A (MIM 600814), (Figs. 1 and 2 ). RAD50 (MIM 604040), NBN (MIM 602667), ATM (MIM 607585), and CHEK2 (MIM 604373), and the RAD51 para- Additional Genotyping in WES Pedigrees logs RAD51C (MIM 602774), RAD51D (MIM 602954), and In the family in which RINT1 c.343C>T (p.Q115X) was XRCC2 (MIM 600375), which are all currently under inves- identifi ed, the mutation was carried by both women for tigation. The potential for intrafamily exome-sequencing whom WES was conducted (II-2 and I-4; Fig. 1A ), and approaches to identify additional breast cancer susceptibility subsequent testing revealed that the two other female rela- genes has been demonstrated recently ( 5–7 ). Although large- tives diagnosed with breast cancer in the family (II-1 and scale validation of fi ndings from these studies has provided II-4) and a male relative (I-2) affected by bladder and lung further insight into the possible roles and clinical signifi - cancers were also carriers ( Fig. 1A ). The RINT1 c.1207G>T cance of these susceptibility genes in cancer predisposition, (p.D403Y) variant was identifi ed in 1 of the 2 affected these studies have also illustrated the challenges posed in women selected for WES (III-8 but not III-1; Fig. 1B ). This the context of breast cancer, a disease that has variable phe- family had an extensive family history of cancer, including notypes and is likely to involve a great number of intermedi- 9 diagnoses of breast cancer in 7 female members [2 women ate- to high-risk rare variants in multiple susceptibility genes were found to be carriers (III-8 and II-10), 2 were found to be (5, 6 , 8–11 ). noncarriers (III-1 and II-12), and 3 could not be genotyped In many, if not most, cases, mutations in specifi c cancer (II-1, II-7, and I-4) for c.1207G>T]. The family also had 4 susceptibility genes are associated with high risks of cancer individuals (II-4, II-9, II-10, and III-10) who had malignant at one or two primary sites, but are also associated with more melanoma at early ages (39, 39, 36, and 33 years, respec- modest increases in risk for a number of other cancer types. tively). Of these cases, 3 were carriers of c.1207G>T (II-4, For instance, BRCA2 mutations confer high risk of breast and II-9, and II-10) and 1 could not be genotyped. The RINT1 ovarian cancers but are also associated with increased risk of c.1132_1134del (p.378del) variant was carried by 1 of the 2 prostate cancer with an estimated relative risk of 2.5 ( 12 ) and women selected for WES (II-1 but not III-1), whereas the car- pancreatic cancer with an increased risk of 6-fold reported rier’s mother (I-4), affected by breast cancer at the age of 42 in two large independent studies ( 12, 13 ).
Load more

Recommended publications
  • Gene Expression Imputation Across Multiple Brain Regions Provides Insights Into Schizophrenia Risk
    VU Research Portal Gene expression imputation across multiple brain regions provides insights into schizophrenia risk iPSYCH-GEMS Schizophrenia Working Group; CommonMind Consortium; The Schizophrenia Working Group of the PsyUniversity of Copenhagenchiatric Genomics Consortium published in Nature Genetics 2019 DOI (link to publisher) 10.1038/s41588-019-0364-4 document version Publisher's PDF, also known as Version of record document license Article 25fa Dutch Copyright Act Link to publication in VU Research Portal citation for published version (APA) iPSYCH-GEMS Schizophrenia Working Group, CommonMind Consortium, & The Schizophrenia Working Group of the PsyUniversity of Copenhagenchiatric Genomics Consortium (2019). Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nature Genetics, 51(4), 659–674. https://doi.org/10.1038/s41588-019-0364-4 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. E-mail address: [email protected] Download date: 28.
    [Show full text]
  • Rab18 Promotes Lipid Droplet (LD) Growth by Tethering the ER to Lds Through SNARE​ and NRZ Interactions
    Published Online: 24 January, 2018 | Supp Info: http://doi.org/10.1083/jcb.201704184 Article Downloaded from jcb.rupress.org on August 7, 2018 Rab18 promotes lipid droplet (LD) growth by tethering the ER to LDs through SNARE and NRZ interactions Dijin Xu,1* Yuqi Li,1* Lizhen Wu,1* Ying Li,1 Dongyu Zhao,1 Jinhai Yu,1 Tuozhi Huang,1 Charles Ferguson,2 Robert G. Parton,2,3 Hongyuan Yang,4 and Peng Li1 1State Key Laboratory of Membrane Biology, Tsinghua-Peking Center for Life Sciences, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China 2Institute for Molecular Bioscience and 3Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, Australia 4School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Australia Lipid incorporation from endoplasmic reticulum (ER) to lipid droplet (LD) is important in controlling LD growth and intra- cellular lipid homeostasis. However, the molecular link mediating ER and LD cross talk remains elusive. Here, we identi- fied Rab18 as an important Rab guanosine triphosphatase in controlling LD growth and maturation.Rab18 deficiency resulted in a drastically reduced number of mature LDs and decreased lipid storage, and was accompanied by increased ER stress. Rab3GAP1/2, the GEF of Rab18, promoted LD growth by activating and targeting Rab18 to LDs. LD-associated Rab18 bound specifically to the ER-associated NAG-RINT1-ZW10 (NRZ) tethering complex and their associated SNAREs (Syntaxin18, Use1, BNIP1), resulting in the recruitment of ER to LD and the formation of direct ER–LD contact. Cells with defects in the NRZ/SNA RE complex function showed reduced LD growth and lipid storage.
    [Show full text]
  • Identification of Rab18 As an Essential Host Factor for Bkpyv Infection Using a Whole Genome RNA 2 Interference Screen
    bioRxiv preprint doi: https://doi.org/10.1101/157602; this version posted June 29, 2017. 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 Identification of Rab18 as an Essential Host Factor for BKPyV Infection Using a Whole Genome RNA 2 Interference Screen 3 4 Linbo Zhaoa, Michael J. Imperialea,b,* 5 6 aDepartment of Microbiology and Immunology, bComprehensive Cancer Center, University of Michigan, 7 Ann Arbor, MI, 48109, USA 8 9 10 11 12 13 14 15 16 17 18 * Corresponding author. Department of Microbiology and Immunology, 1150 West Medical Center 19 Drive, 5724 Medical Science II, Ann Arbor, MI 48109-5620, USA. Tel. +1 (734) 763 9162. Fax: +1 (734) 20 764 3562. 21 E-mail addresses: [email protected] (L. Zhao); [email protected] (M.J. Imperiale). 22 23 24 1 bioRxiv preprint doi: https://doi.org/10.1101/157602; this version posted June 29, 2017. 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. 25 Abstract 26 27 BK polyomavirus (BKPyV) is a human pathogen first isolated in 1971. BKPyV infection is ubiquitous in the 28 human population, with over 80% of adults worldwide being seropositive for BKPyV. BKPyV infection is 29 usually asymptomatic; however, BKPyV reactivation in immunosuppressed transplant patients causes 30 two diseases, polyomavirus-associated nephropathy and hemorrhagic cystitis.
    [Show full text]
  • On the Role of Chromosomal Rearrangements in Evolution
    On the role of chromosomal rearrangements in evolution: Reconstruction of genome reshuffling in rodents and analysis of Robertsonian fusions in a house mouse chromosomal polymorphism zone by Laia Capilla Pérez A thesis submitted for the degree of Doctor of Philosophy in Animal Biology Supervisors: Dra. Aurora Ruiz-Herrera Moreno and Dr. Jacint Ventura Queija Institut de Biotecnologia i Biomedicina (IBB) Departament de Biologia Cel·lular, Fisiologia i Immunologia Departament de Biologia Animal, Biologia Vegetal i Ecologia Universitat Autònoma de Barcelona Supervisor Supervisor PhD candidate Aurora Ruiz-Herrera Moreno Jacint Ventura Queija Laia Capilla Pérez Bellaterra, 2015 A la mare Al pare Al mano “Visto a la luz de la evolución, la biología es, quizás, la ciencia más satisfactoria e inspiradora. Sin esa luz, se convierte en un montón de hechos varios, algunos de ellos interesantes o curiosos, pero sin formar ninguna visión conjunta.” Theodosius Dobzhansky “La evolución es tan creativa. Por eso tenemos jirafas.” Kurt Vonnegut This thesis was supported by grants from: • Ministerio de Economía y Competitividad (CGL2010-15243 and CGL2010- 20170). • Generalitat de Catalunya, GRQ 1057. • Ministerio de Economía y Competitividad. Beca de Formación de Personal Investigador (FPI) (BES-2011-047722). • Ministerio de Economía y Competitividad. Beca para la realización de estancias breves (EEBB-2011-07350). Covers designed by cintamontserrat.blogspot.com INDEX Abstract 15-17 Acronyms 19-20 1. GENERAL INTRODUCTION 21-60 1.1 Chromosomal rearrangements
    [Show full text]
  • Evaluation of Rint1 As a Modifier of Intestinal Tumorigenesis and Cancer Risk
    RESEARCH ARTICLE Evaluation of Rint1 as a modifier of intestinal tumorigenesis and cancer risk Karla L. Otterpohl¤, Karen A. Gould* Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, Nebraska, United States of America ¤ Current address: Children's Health Research Center, Sanford Research, Sioux Falls, South Dakota, United States of America * [email protected] a1111111111 Abstract a1111111111 a1111111111 The Rad50 Interacting Protein 1 (Rint1) influences cellular homeostasis through mainte- a1111111111 nance of endoplasmic reticulum, Golgi and centrosome integrity and regulation of vesicle a1111111111 transport, autophagy and the G2/M checkpoint. Rint1 has been postulated to function as a tumor suppressor as well as an oncogene, with its role depending perhaps upon the precise cellular and/or experimental context. In humans, heterozygosity for germline missense vari- ants in RINT1 have, in some studies, been associated with increased risk of both breast and OPEN ACCESS Lynch syndrome type cancers. However, it is not known if these germline variants represent Citation: Otterpohl KL, Gould KA (2017) Evaluation loss of function alleles or gain of function alleles. Based upon these findings, as well as our of Rint1 as a modifier of intestinal tumorigenesis initial consideration of Rint1 as a potential candidate for Mom5, a genetic modifier of intesti- and cancer risk. PLoS ONE 12(3): e0172247. Min/+ doi:10.1371/journal.pone.0172247 nal tumorigenesis in Apc mice, we sought to explicitly examine the impact of Rint1 on tumorigenesis in ApcMin/+ mice. However, heterozygosity for a knockout of Rint1 had no Editor: Alvaro Galli, CNR, ITALY impact on tumorigenesis in Rint1+/-; ApcMin/+ mice.
    [Show full text]
  • The FEM R Package: Identification of Functional Epigenetic Modules
    The FEM R package: Identification of Functional Epigenetic Modules Yinming Jiao and Andrew E. Teschendorff April 24, 2017 1 Summary This vignette provides examples of how to use the package FEM to identify interactome hotspots of differential promoter methylation and differential ex- pression, where an inverse association between promoter methylation and gene expression is assumed [1]. By \interactome hotspot" we mean a connected sub- network of the protein interaction network (PIN) with an exceptionally large average edge-weight density in relation to the rest of the network. The weight edges are constructed from the statistics of association of DNA methylation and gene expression with the phenotype of interest. Thus, the FEM algorithm can be viewed as a functional supervised algorithm, which uses a network of relations between genes (in our case a PPI network), to identify subnetworks where a significant number of genes are associated with a phenotype of interest (POI). We call these \hotspots" also Functional Epigenetic Modules (FEMs). Current functionality of FEM works for Illumina Infinium 450k data, how- ever, the structure is modular allowing easy application or generalization to DNA methylation data generated with other technologies. The FEM algorithm on Illumina 27k data was first presented in [2], with its extension to Illumina 450k data described in [1]. The module detection algorithm used is the spin- glass algorithm of [3]. The PIN used in this vignette includes only protein- protein interactions, derives from Pathway Commons [4] and is available from http://sourceforge.net/projects/funepimod/files under filename hprdAsigH*.Rd, but the user is allowed to specify his own network.
    [Show full text]
  • Endometrial Cancer Gene Panels: Clinical Diagnostic Vs Research Germline DNA Testing Amanda B Spurdle1, Michael a Bowman1, Jannah Shamsani1 and Judy Kirk2
    Modern Pathology (2017) 30, 1048–1068 1048 © 2017 USCAP, Inc All rights reserved 0893-3952/17 $32.00 Endometrial cancer gene panels: clinical diagnostic vs research germline DNA testing Amanda B Spurdle1, Michael A Bowman1, Jannah Shamsani1 and Judy Kirk2 1Molecular Cancer Epidemiology Laboratory, Genetics and Computational Biology Division, Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia and 2Familial Cancer Service, Crown Princess Mary Cancer Centre, Westmead Hospital, Sydney Medical School, University of Sydney, Centre for Cancer Research, The Westmead Institute for Medical Research, Westmead, NSW, Australia Endometrial cancer is the most common gynecological cancer, but is nevertheless uncommon enough to have value as a signature cancer for some hereditary cancer syndromes. Commercial multigene testing panels include up to 13 different genes annotated for germline DNA testing of patients with endometrial cancer. Many other genes have been reported as relevant to familial endometrial cancer from directed genome-wide sequencing studies or multigene panel testing, or research. This review assesses the evidence supporting association with endometrial cancer risk for 32 genes implicated in hereditary endometrial cancer, and presents a summary of rare germline variants in these 32 genes detected by analysis of quasi-population-based endometrial cancer patients from The Cancer Genome Atlas project. This comprehensive investigation has led to the conclusion that convincing evidence currently exists to support clinical testing of only six of these genes for diagnosis of hereditary endometrial cancer. Testing of endometrial cancer patients for the remaining genes should be considered in the context of research studies, as a means to better establish the level of endometrial cancer risk, if any, associated with genetic variants that are deleterious to gene or protein function.
    [Show full text]
  • Download Special Issue
    BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Guest Editors: Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 GuestEditors:TaoHuang,LeiChen,JiangningSong, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Copyright © 2016 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Volume 2016, Article ID 6585069, 2 pages New Trends of Digital Data Storage in DNA Pavani Yashodha De Silva and Gamage Upeksha Ganegoda Volume 2016, Article ID 8072463, 14 pages Analyzing the miRNA-Gene Networks to Mine the Important miRNAs under Skin of Human and Mouse Jianghong Wu, Husile Gong, Yongsheng Bai, and Wenguang Zhang Volume 2016, Article ID 5469371, 9 pages Differential Regulatory Analysis Based on Coexpression Network in Cancer Research Junyi
    [Show full text]
  • (12) Patent Application Publication (10) Pub. No.: US 2010/0267569 A1 Salmon Et Al
    US 2010O267569A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2010/0267569 A1 Salmon et al. (43) Pub. Date: Oct. 21, 2010 (54) COMPOSITIONS, METHODS AND KITS FOR (30) Foreign Application Priority Data THE DAGNOSS OF CARRIERS OF MUTATIONS IN THE BRCA1 AND BRCA2 Jul. 8, 2007 (IL) .......................................... 184478 GENES AND EARLY DAGNOSS OF CANCEROUS DISORDERS ASSOCATED Publication Classification WITH MUTATIONS IN BRCA1 AND BRCA2 GENES (51) Int. Cl. CI2O I/68 (2006.01) (75) Inventors: Asher Salmon, Jerusalem (IL); C40B 40/06 (2006.01) Tamar Peretz, Jerusalem (IL) C40B 30/00 (2006.01) GOIN 33/53 (2006.01) Correspondence Address: GOIN 33/50 (2006.01) KEVIN D. MCCARTHY ROACH BROWN MCCARTHY & GRUBER, P.C. (52) U.S. Cl. .................... 506/7; 435/6:506/16:435/7.1; 424 MAIN STREET, 1920 LIBERTY BUILDING 435/7.92; 436/86 BUFFALO, NY 14202 (US) (73) Assignee: Hadasit Medical Research (57) ABSTRACT Services and Development Ltd., The present invention relates to diagnostic compositions Jerusalem (IL) methods and kits for the detection of carriers of mutations in Appl. No.: 12/668,154 the BRCA1 and BRCA2 genes. The detection is based on the (21) use of detecting nucleic acids oramino acid based molecules, (22) PCT Fled: Jul. 8, 2008 specific for determination of the expression of at least six marker genes of the invention, in a test sample. The invention (86) PCT NO.: PCT/ILO8/OO934 thereby provides methods compositions and kits for the diag nosis of cancerous disorders associated with mutations in the S371 (c)(1), BRCA1 and BRCA2 genes, specifically, of ovarian and breast (2), (4) Date: Apr.
    [Show full text]
  • NCCN: Genetic/Familial High-Risk Assessment: Breast and Ovarian
    NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) Genetic/Familial High-Risk Assessment: Breast and Ovarian Version 3.2019 — January 18, 2019 NCCN.org Continue Version 3.2019, 01/18/19 © 2019 National Comprehensive Cancer Network® (NCCN®), All rights reserved. NCCN Guidelines® and this illustration may not be reproduced in any form without the express written permission of NCCN. NCCN Guidelines Index NCCN Guidelines Version 3.2019 Table of Contents Genetic/Familial High-Risk Assessment: Breast and Ovarian Discussion *Mary B. Daly, MD, PhD/Chair † Catherine Klein, MD † Þ Holly J. Pederson, MD Fox Chase Cancer Center University of Colorado Cancer Center Case Comprehensive Cancer Center/ University Hospitals Seidman Cancer Center *Robert Pilarski, MS, CGC/Vice-chair ∆ Wendy Kohlmann, MS, CGC ∆ and Cleveland Clinic Taussig Cancer Institute The Ohio State University Comprehensive Huntsman Cancer Institute Cancer Center - James Cancer Hospital at the University of Utah Gwen Reiser, MS, CGC ∆ and Solove Research Institute Fred & Pamela Buffett Cancer Center Allison W. Kurian, MD, MSc † Þ ∆ Michael P. Berry, MD ¶ Stanford Cancer Institute Kristen Mahoney Shannon, MS, CGC † ∆ St. Jude Children’s Research Hospital/ Massachusetts General Hospital The University of Tennessee Health Christine Laronga, MD ¶ Cancer Center Science Center Moffitt Cancer Center Premal Thaker, MD Ω Saundra S. Buys, MD ‡ Þ † Jennifer K. Litton, MD † Siteman Cancer Center at Barnes- Huntsman Cancer Institute The University of Texas Jewish Hospital and Washington at the University of Utah MD Anderson Cancer Center University School of Medicine Susan Friedman, DVM ¥ Lisa Madlensky, PhD, CGC ∆ Kala Visvanathan, MD, MHS † Þ FORCE: Facing Our Risk of Cancer UC San Diego Moores Cancer Center The Sidney Kimmel Comprehensive Empowered Cancer Center at Johns Hopkins Julie S.
    [Show full text]
  • DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines
    DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Sun, Shuying, Sunny Tian, Karina Bertelsmann, Linda Yu, and Shuying Sun. “DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines.” Cancer Informatics (September 2016): 1. © 2016 the authors, publisher and licensee Libertas Academica Limited As Published http://dx.doi.org/10.4137/cin.s40300 Publisher Libertas Academica, Ltd. Version Final published version Citable link http://hdl.handle.net/1721.1/108129 Terms of Use Creative Commons Attribution-NonCommercial 3.0 Unported Detailed Terms https://creativecommons.org/licenses/by-nc/3.0/ DNA Methylation Heterogeneity Patterns in Breast Cancer Cell Lines Sunny Tian1, Karina Bertelsmann2, Linda Yu3 and Shuying Sun4 1Massachusetts Institute of Technology, Cambridge, MA, USA. 2Clear Creek High School, League City, TX, USA. 3St. John’s School, Houston, TX, USA. 4Department of Mathematics, Texas State University, San Marcos, TX, USA. Supplementary Issue: Computer Simulation, Bioinformatics, and Statistical Analysis of Cancer Data and Processes (A) ABSTR ACT: Heterogeneous DNA methylation patterns are linked to tumor growth. In order to study DNA methylation heterogeneity patterns for breast cancer cell lines, we comparatively study four metrics: variance, I2 statistic, entropy, and methylation state. Using the categorical metric methylation state, we select the two most heterogeneous states to identify genes that directly affect tumor suppressor genes and high- or moderate-risk breast cancer genes. Utilizing the Gene Set Enrichment Analysis software and the ConsensusPath Database visualization tool, we generate integrated gene networks to study biological relations of heterogeneous genes.
    [Show full text]
  • Analyzing the Mirna-Gene Networks to Mine the Important Mirnas Under Skin of Human and Mouse
    Hindawi Publishing Corporation BioMed Research International Volume 2016, Article ID 5469371, 9 pages http://dx.doi.org/10.1155/2016/5469371 Research Article Analyzing the miRNA-Gene Networks to Mine the Important miRNAs under Skin of Human and Mouse Jianghong Wu,1,2,3,4,5 Husile Gong,1,2 Yongsheng Bai,5,6 and Wenguang Zhang1 1 College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China 2Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China 3Inner Mongolia Prataculture Research Center, Chinese Academy of Science, Hohhot 010031, China 4State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China 5Department of Biology, Indiana State University, Terre Haute, IN 47809, USA 6The Center for Genomic Advocacy, Indiana State University, Terre Haute, IN 47809, USA Correspondence should be addressed to Yongsheng Bai; [email protected] and Wenguang Zhang; [email protected] Received 11 April 2016; Revised 15 July 2016; Accepted 27 July 2016 Academic Editor: Nicola Cirillo Copyright © 2016 Jianghong Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Genetic networks provide new mechanistic insights into the diversity of species morphology. In this study, we have integrated the MGI, GEO, and miRNA database to analyze the genetic regulatory networks under morphology difference of integument of humans and mice. We found that the gene expression network in the skin is highly divergent between human and mouse.
    [Show full text]