Chromosomal Abnormalities in Endometrial and Ovarian Carcinomas
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Clinical Validation of the Tempus Xt Next-Generation Targeted Oncology Sequencing Assay
www.oncotarget.com Oncotarget, 2019, Vol. 10, (No. 24), pp: 2384-2396 Research Paper Clinical validation of the tempus xT next-generation targeted oncology sequencing assay Nike Beaubier1, Robert Tell1, Denise Lau1, Jerod R. Parsons1, Stephen Bush1, Jason Perera1, Shelly Sorrells1, Timothy Baker1, Alan Chang1, Jackson Michuda1, Catherine Iguartua1, Shelley MacNeil1, Kaanan Shah1, Philip Ellis1, Kimberly Yeatts1, Brett Mahon1, Timothy Taxter1, Martin Bontrager1, Aly Khan1, Robert Huether1, Eric Lefkofsky1 and Kevin P. White1 1Tempus Labs Inc., Chicago, IL 60654, USA Correspondence to: Nike Beaubier, email: [email protected] Kevin P. White, email: [email protected] Keywords: tumor profiling, next-generation sequencing assay validation Received: August 03, 2018 Accepted: February 03, 2019 Published: March 22, 2019 Copyright: Beaubier et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT We developed and clinically validated a hybrid capture next generation sequencing assay to detect somatic alterations and microsatellite instability in solid tumors and hematologic malignancies. This targeted oncology assay utilizes tumor- normal matched samples for highly accurate somatic alteration calling and whole transcriptome RNA sequencing for unbiased identification of gene fusion events. The assay was validated with a combination of clinical specimens and cell lines, and recorded a sensitivity of 99.1% for single nucleotide variants, 98.1% for indels, 99.9% for gene rearrangements, 98.4% for copy number variations, and 99.9% for microsatellite instability detection. This assay presents a wide array of data for clinical management and clinical trial enrollment while conserving limited tissue. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Wo 2010/081001 A2
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date 15 July 2010 (15.07.2010) WO 2010/081001 A2 (51) International Patent Classification: (81) Designated States (unless otherwise indicated, for every C12Q 1/68 (2006.01) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, (21) International Application Number: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, PCT/US20 10/020501 DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, (22) International Filing Date: HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, ! January 2010 (08.01 .2010) KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, (25) Filing Language: English NO, NZ, OM, PE, PG, PH, PL, PT, RO, RS, RU, SC, SD, (26) Publication Language: English SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (30) Priority Data: 61/143,598 9 January 2009 (09.01 .2009) US (84) Designated States (unless otherwise indicated, for every 61/187,776 17 June 2009 (17.06.2009) US kind of regional protection available): ARIPO (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, (71) Applicant (for all designated States except US): THE ZW), Eurasian (AM, AZ, BY, KG, KZ, MD, RU, TJ, REGENTS OF THE UNIVERSITY OF MICHIGAN TM), European (AT, BE, BG, CH, CY, CZ, DE, DK, EE, [US/US]; 1214 South University, 2nd Floor, Ann Arbor, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, Michigan 48104 (US). -
Understanding the Genetics of Coronary Artery Disease Through Novel Statistical Approaches
Fakultät für Medizin Deutsches Herzzentrum München - Klinik an der Technischen Universität München Understanding the genetics of coronary artery disease through novel statistical approaches Lingyao Zeng Vollständiger Abdruck der von der Fakultät für Medizin der Technischen Universität München zur Erlangung des akademischen Grades eines Doctor of Philosophy (Ph.D.) genehmigten Dissertation. Vorsitzende/r: Prof. Dr. Dr. Stefan Engelhardt Betreuer/in: Prof. Dr. Adnan Kastrati Prüfer der Dissertation: 1. Prof. Dr. Heribert Schunkert 2. Prof. Dr. Dr. Fabian Theis Die Dissertation wurde am 29.07.2016 bei der Fakultät für Medizin der Technischen Universität München eingereicht und durch die Fakultät für Medizin am 14.09.2016 angenommen. Acknowledgement First of all, I would like to express my sincere gratitude and thanks to my advisor Prof. Heribert Schunkert. It is my honor to join his research group. He has been actively interested in my work and offered tremendous support and guidance at all levels of my PhD research over the last few years. I greatly appreciate all his knowledge, kindness, enthusiasm, and encouragement. I would like to thank the other members of my committee, Prof. Adnan Kastrati and Prof. Fabian Theis. I thank Prof. Adnan Kastrati, who as my supervisor has given me the opportunity to pursue my PhD research at the Deutsches Herzzentrum München and Technische Universität München. I also thank him for the generosity and patience offering the clinical data and descriptions. I thank Prof. Fabian Theis for all his valuable comments and encouragement at both the committee meetings and e:AtheroSysMed project conferences. I am grateful to Prof. Bertram Müller-Myhsok from the Department of Statistical Genetics, Max Planck Institute of Psychiatry, and his team member Dr. -
LHCGR (Luteinizing Hormone/Choriogonadotropin Receptor); LPHN2 (Latrophilin 2) (1P31.1)
Atlas of Genetics and Cytogenetics in Oncology and Haematology Home Genes Leukemias Solid Tumours Cancer-Prone Deep Insight Portal Teaching X Y 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 NA Atlas Journal Atlas Journal versus Atlas Database: the accumulation of the issues of the Journal constitutes the body of the Database/Text-Book. TABLE OF CONTENTS Volume 8, Number 1, Jan-Mar 2004 Previous Issue / Next Issue Genes ATBF1 (AT-binding transcription factor 1) (16q22.3-q23.1). Nadine Van Roy, Frank Speleman. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 1-7. [Full Text] [PDF] URL : http://AtlasGeneticsOncology.org/Genes/ATBF1ID357.html DIRC2 (3q21). Anita Bonné, Danièlle Bodmer, Marc Eleveld, Eric Schoenmakers, Ad Geurts van Kessel.. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 8-11. [Full Text] [PDF] URL : http://AtlasGeneticsOncology.org/Genes/DIRC2ID497.html DIRC3 (2q35). Anita Bonné, Danièlle Bodmer, Marc Eleveld, Eric Schoenmakers, Ad Geurts van Kessel.. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 12-14. [Full Text] [PDF] URL : http://AtlasGeneticsOncology.org/Genes/DIRC3ID498..html RAP1GDS1 (4q22.3). Franck Viguié. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 15-18. [Full Text] [PDF] URL : http://AtlasGeneticsOncology.org/Genes/RAP1GDS1ID400.html RET (REarranged during Transfection) (10q11.2). Patricia Niccoli-Sire. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 19-25. [Full Text] [PDF] URL : http://AtlasGeneticsOncology.org/Genes/RETID76.html LHCGR (luteinizing hormone/choriogonadotropin receptor); LPHN2 (latrophilin 2) (1p31.1). Jim Heighway. Atlas Genet Cytogenet Oncol Haematol 2004; 8 (1): 26-36. -
Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis
Getting “Under the Skin”: Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis by Kristen Monét Brown A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Epidemiological Science) in the University of Michigan 2017 Doctoral Committee: Professor Ana V. Diez-Roux, Co-Chair, Drexel University Professor Sharon R. Kardia, Co-Chair Professor Bhramar Mukherjee Assistant Professor Belinda Needham Assistant Professor Jennifer A. Smith © Kristen Monét Brown, 2017 [email protected] ORCID iD: 0000-0002-9955-0568 Dedication I dedicate this dissertation to my grandmother, Gertrude Delores Hampton. Nanny, no one wanted to see me become “Dr. Brown” more than you. I know that you are standing over the bannister of heaven smiling and beaming with pride. I love you more than my words could ever fully express. ii Acknowledgements First, I give honor to God, who is the head of my life. Truly, without Him, none of this would be possible. Countless times throughout this doctoral journey I have relied my favorite scripture, “And we know that all things work together for good, to them that love God, to them who are called according to His purpose (Romans 8:28).” Secondly, I acknowledge my parents, James and Marilyn Brown. From an early age, you two instilled in me the value of education and have been my biggest cheerleaders throughout my entire life. I thank you for your unconditional love, encouragement, sacrifices, and support. I would not be here today without you. I truly thank God that out of the all of the people in the world that He could have chosen to be my parents, that He chose the two of you. -
Chimeric Transcript Discovery by Paired-End Transcriptome Sequencing
Chimeric transcript discovery by paired-end transcriptome sequencing Christopher A. Mahera,b, Nallasivam Palanisamya,b, John C. Brennera,b, Xuhong Caoa,c, Shanker Kalyana-Sundarama,b, Shujun Luod, Irina Khrebtukovad, Terrence R. Barrettea,b, Catherine Grassoa,b, Jindan Yua,b, Robert J. Lonigroa,b, Gary Schrothd, Chandan Kumar-Sinhaa,b, and Arul M. Chinnaiyana,b,c,e,f,1 aMichigan Center for Translational Pathology, Ann Arbor, MI 48109; Departments of bPathology and eUrology, University of Michigan, Ann Arbor, MI 48109; cHoward Hughes Medical Institute and fComprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109; and dIllumina Inc., 25861 Industrial Boulevard, Hayward, CA 94545 Communicated by David Ginsburg, University of Michigan Medical School, Ann Arbor, MI, May 4, 2009 (received for review March 16, 2009) Recurrent gene fusions are a prevalent class of mutations arising from (SAGE)-like sequencing (13), and next-generation DNA sequenc- the juxtaposition of 2 distinct regions, which can generate novel ing (14). Despite unveiling many novel genomic rearrangements, functional transcripts that could serve as valuable therapeutic targets solid tumors accumulate multiple nonspecific aberrations through- in cancer. Therefore, we aim to establish a sensitive, high-throughput out tumor progression; thus, making causal and driver aberrations methodology to comprehensively catalog functional gene fusions in indistinguishable from secondary and insignificant mutations, cancer by evaluating a paired-end transcriptome sequencing strategy. respectively. Not only did a paired-end approach provide a greater dynamic range The deep unbiased view of a cancer cell enabled by massively in comparison with single read based approaches, but it clearly parallel transcriptome sequencing has greatly facilitated gene fu- distinguished the high-level ‘‘driving’’ gene fusions, such as BCR-ABL1 sion discovery. -
Milger Et Al. Pulmonary CCR2+CD4+ T Cells Are Immune Regulatory And
Milger et al. Pulmonary CCR2+CD4+ T cells are immune regulatory and attenuate lung fibrosis development Supplemental Table S1 List of significantly regulated mRNAs between CCR2+ and CCR2- CD4+ Tcells on Affymetrix Mouse Gene ST 1.0 array. Genewise testing for differential expression by limma t-test and Benjamini-Hochberg multiple testing correction (FDR < 10%). Ratio, significant FDR<10% Probeset Gene symbol or ID Gene Title Entrez rawp BH (1680) 10590631 Ccr2 chemokine (C-C motif) receptor 2 12772 3.27E-09 1.33E-05 9.72 10547590 Klrg1 killer cell lectin-like receptor subfamily G, member 1 50928 1.17E-07 1.23E-04 6.57 10450154 H2-Aa histocompatibility 2, class II antigen A, alpha 14960 2.83E-07 1.71E-04 6.31 10590628 Ccr3 chemokine (C-C motif) receptor 3 12771 1.46E-07 1.30E-04 5.93 10519983 Fgl2 fibrinogen-like protein 2 14190 9.18E-08 1.09E-04 5.49 10349603 Il10 interleukin 10 16153 7.67E-06 1.29E-03 5.28 10590635 Ccr5 chemokine (C-C motif) receptor 5 /// chemokine (C-C motif) receptor 2 12774 5.64E-08 7.64E-05 5.02 10598013 Ccr5 chemokine (C-C motif) receptor 5 /// chemokine (C-C motif) receptor 2 12774 5.64E-08 7.64E-05 5.02 10475517 AA467197 expressed sequence AA467197 /// microRNA 147 433470 7.32E-04 2.68E-02 4.96 10503098 Lyn Yamaguchi sarcoma viral (v-yes-1) oncogene homolog 17096 3.98E-08 6.65E-05 4.89 10345791 Il1rl1 interleukin 1 receptor-like 1 17082 6.25E-08 8.08E-05 4.78 10580077 Rln3 relaxin 3 212108 7.77E-04 2.81E-02 4.77 10523156 Cxcl2 chemokine (C-X-C motif) ligand 2 20310 6.00E-04 2.35E-02 4.55 10456005 Cd74 CD74 antigen -
About the Origin and Development of Hereditary Conventional Renal Cell Carcinoma in a Four-Generation T(3;8)(P14.1;Q24.23) Family
European Journal of Human Genetics (2005) 13, 570–578 & 2005 Nature Publishing Group All rights reserved 1018-4813/05 $30.00 www.nature.com/ejhg ARTICLE About the origin and development of hereditary conventional renal cell carcinoma in a four-generation t(3;8)(p14.1;q24.23) family Laura Valle*,1, Alberto Casco´n2, Lorenzo Melchor1, Ignacio Otero3, Sandra Rodrı´guez-Perales4, Lydia Sa´nchez5, Juan Cruz Cigudosa4, Mercedes Robledo2, Barbara Weber6, Miguel Urioste1 and Javier Benı´tez1 1Department of Human Genetics, Spanish National Cancer Centre (CNIO), Madrid, Spain; 2Hereditary Endocrine Cancer Group, Spanish National Cancer Centre (CNIO), Madrid, Spain; 3Urology Service, Hospital General de Guadalajara, Guadalajara, Spain; 4Cytogenetics Unit, Spanish National Cancer Centre (CNIO), Madrid, Spain; 5Immunohistochemistry Unit, Spanish National Cancer Centre (CNIO), Madrid, Spain; 6Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, USA Conventional renal cell carcinoma (CRCC) may appear in families with germline translocations involving chromosome 3, although a recurrent responsible gene has not been found. We recently described a family with CRCC and a constitutional t(3;8)(p14.1;q24.23), and we demonstrated that no genes were disrupted by the translocation breakpoints. In order to investigate the genetic origin and features of the CRCC tumors that occurred in this family, we have extended the pedigree up to four generations, and analyzed peripheral blood samples from 36 members, CRCC tumors, normal renal tissues, and a gastric tumor. (1) By means of comparative genomic hybridization (CGH), we have detected loss of the derivative chromosome carrying 3p in all CRCC but not in the corresponding normal renal tissue. -
Comparison of Selection Signatures Between Korean Native and Commercial Chickens Using 600K SNP Array Data
G C A T T A C G G C A T genes Article Comparison of Selection Signatures between Korean Native and Commercial Chickens Using 600K SNP Array Data Sunghyun Cho 1, Prabuddha Manjula 1, Minjun Kim 1,2, Eunjin Cho 1, Dooho Lee 1, Seung Hwan Lee 1,2, Jun Heon Lee 1,2 and Dongwon Seo 1,2,* 1 Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea; [email protected] (S.C.); [email protected] (P.M.); [email protected] (M.K.); fl[email protected] (E.C.); [email protected] (D.L.); [email protected] (S.H.L.); [email protected] (J.H.L.) 2 Bio-AI Convergence Research Center, Chungnam National University, Daejeon 34134, Korea * Correspondence: [email protected]; Tel.: +82-42-821-5878 Abstract: Korean native chickens (KNCs) comprise an indigenous chicken breed of South Korea that was restored through a government project in the 1990s. The KNC population has not been developed well and has mostly been used to maintain purebred populations in the government research institution. We investigated the genetic features of the KNC population in a selection signal study for the efficient improvement of this breed. We used 600K single nucleotide polymorphism data sampled from 191 KNCs (NG, 38; NL, 29; NR, 52; NW, 39; and NY, 33) and 54 commercial chickens (Hy-line Brown, 10; Lohmann Brown, 10; Arbor Acres, 10; Cobb, 12; and Ross, 12). Haplotype phasing was performed using EAGLE software as the initial step for the primary data analysis. Pre-processed data were analyzed to detect selection signals using the ‘rehh’ package in R software. -
1 Supplementary Material Figure S1. Volcano Plot of Differentially
Supplementary material Figure S1. Volcano Plot of differentially expressed genes between preterm infants fed own mother’s milk (OMM) or pasteurized donated human milk (DHM). Table S1. The 10 most representative biological processes filtered for enrichment p- value in preterm infants. Biological Processes p-value Quantity of DEG* Transcription, DNA-templated 3.62x10-24 189 Regulation of transcription, DNA-templated 5.34x10-22 188 Transport 3.75x10-17 140 Cell cycle 1.03x10-13 65 Gene expression 3.38x10-10 60 Multicellular organismal development 6.97x10-10 86 1 Protein transport 1.73x10-09 56 Cell division 2.75x10-09 39 Blood coagulation 3.38x10-09 46 DNA repair 8.34x10-09 39 Table S2. Differential genes in transcriptomic analysis of exfoliated epithelial intestinal cells between preterm infants fed own mother’s milk (OMM) and pasteurized donated human milk (DHM). Gene name Gene Symbol p-value Fold-Change (OMM vs. DHM) (OMM vs. DHM) Lactalbumin, alpha LALBA 0.0024 2.92 Casein kappa CSN3 0.0024 2.59 Casein beta CSN2 0.0093 2.13 Cytochrome c oxidase subunit I COX1 0.0263 2.07 Casein alpha s1 CSN1S1 0.0084 1.71 Espin ESPN 0.0008 1.58 MTND2 ND2 0.0138 1.57 Small ubiquitin-like modifier 3 SUMO3 0.0037 1.54 Eukaryotic translation elongation EEF1A1 0.0365 1.53 factor 1 alpha 1 Ribosomal protein L10 RPL10 0.0195 1.52 Keratin associated protein 2-4 KRTAP2-4 0.0019 1.46 Serine peptidase inhibitor, Kunitz SPINT1 0.0007 1.44 type 1 Zinc finger family member 788 ZNF788 0.0000 1.43 Mitochondrial ribosomal protein MRPL38 0.0020 1.41 L38 Diacylglycerol -
Genetic and Chromosomal Aberrations and Their Clinical Significance in Renal Neoplasms
Hindawi Publishing Corporation BioMed Research International Volume 2015, Article ID 476508, 22 pages http://dx.doi.org/10.1155/2015/476508 Review Article Genetic and Chromosomal Aberrations and Their Clinical Significance in Renal Neoplasms Ning Yi Yap,1 Retnagowri Rajandram,1,2,3 Keng Lim Ng,1,2 Jayalakshmi Pailoor,4 Ahmad Fadzli,1 and Glenda Carolyn Gobe2 1 Department of Surgery, Faculty of Medicine, University of Malaya, Jalan Universiti, Kuala Lumpur, Malaysia 2Centre for Kidney Disease Research, University of Queensland, Translational Research Institute, 37 Kent Street, Brisbane QLD 4102, Australia 3University of Malaya Cancer Research Institute, University of Malaya, Jalan Universiti, Kuala Lumpur, Malaysia 4Department of Pathology, Faculty of Medicine, University of Malaya, Jalan Universiti, Kuala Lumpur, Malaysia Correspondence should be addressed to Retnagowri Rajandram; [email protected] Received 23 January 2015; Revised 23 May 2015; Accepted 25 May 2015 Academic Editor: Konstantinos Arnaoutakis Copyright © 2015 Ning Yi Yap 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. The most common form of malignant renal neoplasms is renal cell carcinoma (RCC), which is classified into several different subtypes based on the histomorphological features. However, overlaps in these characteristics may present difficulties in the accurate diagnosis of these subtypes, which have different clinical outcomes. Genomic and molecular studies have revealed unique genetic aberrations in each subtype. Knowledge of these genetic changes in hereditary and sporadic renal neoplasms has given an insight into the various proteins and signalling pathways involved in tumour formation and progression.