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Wo 2010/075007 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 1 July 2010 (01.07.2010) WO 2010/075007 A2 (51) International Patent Classification: (81) Designated States (unless otherwise indicated, for every C12Q 1/68 (2006.01) G06F 19/00 (2006.01) kind of national protection available): AE, AG, AL, AM, C12N 15/12 (2006.01) AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, (21) International Application Number: DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, PCT/US2009/067757 HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, (22) International Filing Date: KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, 11 December 2009 ( 11.12.2009) ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PE, PG, PH, PL, PT, RO, RS, RU, SC, SD, (25) Filing Language: English SE, SG, SK, SL, SM, ST, SV, SY, TJ, TM, TN, TR, TT, (26) Publication Language: English TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (30) Priority Data: (84) Designated States (unless otherwise indicated, for every 12/3 16,877 16 December 2008 (16.12.2008) 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): DODDS, ZW), Eurasian (AM, AZ, BY, KG, KZ, MD, RU, TJ, W., Jean [US/US]; 938 Stanford Street, Santa Monica, TM), European (AT, BE, BG, CH, CY, CZ, DE, DK, EE, CA 90403 (US). -
HERV-K(HML7) Integrations in the Human Genome: Comprehensive Characterization and Comparative Analysis in Non-Human Primates
biology Article HERV-K(HML7) Integrations in the Human Genome: Comprehensive Characterization and Comparative Analysis in Non-Human Primates Nicole Grandi 1,* , Maria Paola Pisano 1 , Eleonora Pessiu 1, Sante Scognamiglio 1 and Enzo Tramontano 1,2 1 Laboratory of Molecular Virology, Department of Life and Environmental Sciences, University of Cagliari, 09042 Monserrato, Cagliari, Italy; [email protected] (M.P.P.); [email protected] (E.P.); [email protected] (S.S.); [email protected] (E.T.) 2 Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), 09042 Monserrato, Cagliari, Italy * Correspondence: [email protected] Simple Summary: The human genome is not human at all, but it includes a multitude of sequences inherited from ancient viral infections that affected primates’ germ line. These elements can be seen as the fossils of now-extinct retroviruses, and are called Human Endogenous Retroviruses (HERVs). View as “junk DNA” for a long time, HERVs constitute 4 times the amount of DNA needed to produce all cellular proteins, and growing evidence indicates their crucial role in primate brain evolution, placenta development, and innate immunity shaping. HERVs are also intensively studied for a pathological role, even if the incomplete knowledge about their exact number and genomic position has thus far prevented any causal association. Among possible relevant HERVs, the HERV-K Citation: Grandi, N.; Pisano, M.P.; supergroup is of particular interest, including some of the oldest (HML5) as well as youngest (HML2) Pessiu, E.; Scognamiglio, S.; integrations. Among HERV-Ks, the HML7 group still lack a detailed description, and the present Tramontano, E. -
Supplementary File 2A Revised
Supplementary file 2A. Differentially expressed genes in aldosteronomas compared to all other samples, ranked according to statistical significance. Missing values were not allowed in aldosteronomas, but to a maximum of five in the other samples. Acc UGCluster Name Symbol log Fold Change P - Value Adj. P-Value B R99527 Hs.8162 Hypothetical protein MGC39372 MGC39372 2,17 6,3E-09 5,1E-05 10,2 AA398335 Hs.10414 Kelch domain containing 8A KLHDC8A 2,26 1,2E-08 5,1E-05 9,56 AA441933 Hs.519075 Leiomodin 1 (smooth muscle) LMOD1 2,33 1,3E-08 5,1E-05 9,54 AA630120 Hs.78781 Vascular endothelial growth factor B VEGFB 1,24 1,1E-07 2,9E-04 7,59 R07846 Data not found 3,71 1,2E-07 2,9E-04 7,49 W92795 Hs.434386 Hypothetical protein LOC201229 LOC201229 1,55 2,0E-07 4,0E-04 7,03 AA454564 Hs.323396 Family with sequence similarity 54, member B FAM54B 1,25 3,0E-07 5,2E-04 6,65 AA775249 Hs.513633 G protein-coupled receptor 56 GPR56 -1,63 4,3E-07 6,4E-04 6,33 AA012822 Hs.713814 Oxysterol bining protein OSBP 1,35 5,3E-07 7,1E-04 6,14 R45592 Hs.655271 Regulating synaptic membrane exocytosis 2 RIMS2 2,51 5,9E-07 7,1E-04 6,04 AA282936 Hs.240 M-phase phosphoprotein 1 MPHOSPH -1,40 8,1E-07 8,9E-04 5,74 N34945 Hs.234898 Acetyl-Coenzyme A carboxylase beta ACACB 0,87 9,7E-07 9,8E-04 5,58 R07322 Hs.464137 Acyl-Coenzyme A oxidase 1, palmitoyl ACOX1 0,82 1,3E-06 1,2E-03 5,35 R77144 Hs.488835 Transmembrane protein 120A TMEM120A 1,55 1,7E-06 1,4E-03 5,07 H68542 Hs.420009 Transcribed locus 1,07 1,7E-06 1,4E-03 5,06 AA410184 Hs.696454 PBX/knotted 1 homeobox 2 PKNOX2 1,78 2,0E-06 -
A Novel Foxp3-Related Immune Prognostic Signature for Glioblastoma Multiforme Based on Immunogenomic Profiling
www.aging-us.com AGING 2021, Vol. 13, No. 3 Research Paper A novel foxp3-related immune prognostic signature for glioblastoma multiforme based on immunogenomic profiling Xiao-Yu Guo1,*, Guan-Hua Zhang1,2,*, Zhen-Ning Wang1, Hao Duan1, Tian Xie1, Lun Liang1, Rui Cui1, Hong-Rong Hu1, Yi Wu3, Jia-jun Dong3, Zhen-Qiang He1, Yong-Gao Mou1 1Department of Neurosurgery AND Neuro-Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China 2Department of Cerebrovascular Surgery, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510000, China 3Department of Neurosurgery, Jiangmen Central Hospital, Jiangmen 529030, China *Equal contribution Correspondence to: Yong-Gao Mou, Zhen-Qiang He; email: [email protected], [email protected] Keywords: glioblastoma multiforme, Foxp3, regulatory T cells, immune prognostic signature, nomogram Received: June 8, 2020 Accepted: October 31, 2020 Published: January 10, 2021 Copyright: © 2021 Guo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Foxp3+ regulatory T cells (Treg) play an important part in the glioma immunosuppressive microenvironment. This study analyzed the effect of Foxsp3 on the immune microenvironment and constructed a Foxp3-related immune prognostic signature (IPS)for predicting prognosis in glioblastoma multiforme (GBM). Immunohistochemistry (IHC) staining for Foxp3 was performed in 72 high-grade glioma specimens. RNA-seq data from 152 GBM samples were obtained from The Cancer Genome Atlas database (TCGA) and divided into two groups, Foxp3 High (Foxp3_H) and Foxp3 Low (Foxp3_L), based on Foxp3 expression. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Lineage-Specific Programming Target Genes Defines Potential for Th1 Temporal Induction Pattern of STAT4
Downloaded from http://www.jimmunol.org/ by guest on October 1, 2021 is online at: average * The Journal of Immunology published online 26 August 2009 from submission to initial decision 4 weeks from acceptance to publication J Immunol http://www.jimmunol.org/content/early/2009/08/26/jimmuno l.0901411 Temporal Induction Pattern of STAT4 Target Genes Defines Potential for Th1 Lineage-Specific Programming Seth R. Good, Vivian T. Thieu, Anubhav N. Mathur, Qing Yu, Gretta L. Stritesky, Norman Yeh, John T. O'Malley, Narayanan B. Perumal and Mark H. Kaplan Submit online. Every submission reviewed by practicing scientists ? is published twice each month by http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://www.jimmunol.org/content/suppl/2009/08/26/jimmunol.090141 1.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* • Why • • Material Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2009 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of October 1, 2021. Published August 26, 2009, doi:10.4049/jimmunol.0901411 The Journal of Immunology Temporal Induction Pattern of STAT4 Target Genes Defines Potential for Th1 Lineage-Specific Programming1 Seth R. Good,2* Vivian T. Thieu,2† Anubhav N. Mathur,† Qing Yu,† Gretta L. -
Abnormal Spermatogenesis and Reduced Fertility in Transition Nuclear Protein 1-Deficient Mice
Abnormal spermatogenesis and reduced fertility in transition nuclear protein 1-deficient mice Y. Eugene Yu*†,Yun Zhang*, Emmanual Unni*‡, Cynthia R. Shirley*, Jian M. Deng§, Lonnie D. Russell¶, Michael M. Weil*, Richard R. Behringer§, and Marvin L. Meistrich*ʈ Departments of *Experimental Radiation Oncology, and §Molecular Genetics, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030-4095; and ¶Department of Physiology, Southern Illinois University, School of Medicine, Carbondale, IL 62901 Edited by Richard D. Palmiter, University of Washington School of Medicine, Seattle, WA, and approved February 22, 2000 (received for review May 3, 1999) Transition nuclear proteins (TPs), the major proteins found in (15), suggesting some functional relationship between the three chromatin of condensing spermatids, are believed to be important proteins exists. Tnp1, however, is on a separate chromosome and for histone displacement and chromatin condensation during is not clearly related to the other three proteins. mammalian spermatogenesis. We generated mice lacking the ma- In vitro, TP1 decreases the melting temperature of DNA (16) jor TP, TP1, by targeted deletion of the Tnp1 gene in mouse and relaxes the DNA in nucleosomal core particles (17), which embryonic stem cells. Surprisingly, testis weights and sperm pro- led to the proposal that TP1 reduces the interaction of DNA duction were normal in the mutant mice, and only subtle abnor- with the nucleosome core. In contrast, TP2 increases the malities were observed in sperm morphology. Electron microscopy melting temperature of DNA and compacts the DNA in revealed large rod-like structures in the chromatin of mutant step nucleosomal cores, suggesting that it is a DNA-condensing 13 spermatids, in contrast to the fine chromatin fibrils observed in protein (18). -
Concurrent Mutations Associated with Trastuzumab-Resistance Revealed by Single Cell Sequencing
Concurrent Mutations Associated With Trastuzumab-resistance Revealed by Single Cell Sequencing Yan Gao Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital Ning Wu Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital Shuai Wang Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital Xue Yang Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital Xin Wang Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital Bo Xu ( [email protected] ) Tianjin Medical University Cancer Institute and Hospital: Tianjin Tumor Hospital https://orcid.org/0000-0001-8693-3060 Research Article Keywords: HER2-positive breast cancer, trastuzumab-resistance, single cell sequencing, concurrent mutations Posted Date: February 25th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-253665/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/17 Abstract Purpose: HER2-positive breast cancer patients benet from HER2 targeted therapies, among which the most commonly used is trastuzumab. However, acquired resistance typically happens within one year. The cellular heterogeneity of it is less clear. Methods: Here we generated trastuzumab-resistant cells in two HER2-positive breast cancer cell lines, SK- BR-3 and BT-474. Cells at different time points during the resistance induction were examined by exome sequencing to study changes of genomic alterations over time. Single cell targeted sequencing was also used to identify resistance associated concurrent mutations. Results: We found a rapid increase of copy number variation (CNV) regions and gradual accumulation of single nucleotide variations (SNVs). On the pathway level, nonsynonymous SNVs for SK-BR-3 cells were enriched in the MAPK signaling pathway, while for BT-474 cells were enriched in mTOR and PI3K-Akt signaling pathways. -
Open Data for Differential Network Analysis in Glioma
International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. -
Supplementary Table 1
Supplementary Table 1. 492 genes are unique to 0 h post-heat timepoint. The name, p-value, fold change, location and family of each gene are indicated. Genes were filtered for an absolute value log2 ration 1.5 and a significance value of p ≤ 0.05. Symbol p-value Log Gene Name Location Family Ratio ABCA13 1.87E-02 3.292 ATP-binding cassette, sub-family unknown transporter A (ABC1), member 13 ABCB1 1.93E-02 −1.819 ATP-binding cassette, sub-family Plasma transporter B (MDR/TAP), member 1 Membrane ABCC3 2.83E-02 2.016 ATP-binding cassette, sub-family Plasma transporter C (CFTR/MRP), member 3 Membrane ABHD6 7.79E-03 −2.717 abhydrolase domain containing 6 Cytoplasm enzyme ACAT1 4.10E-02 3.009 acetyl-CoA acetyltransferase 1 Cytoplasm enzyme ACBD4 2.66E-03 1.722 acyl-CoA binding domain unknown other containing 4 ACSL5 1.86E-02 −2.876 acyl-CoA synthetase long-chain Cytoplasm enzyme family member 5 ADAM23 3.33E-02 −3.008 ADAM metallopeptidase domain Plasma peptidase 23 Membrane ADAM29 5.58E-03 3.463 ADAM metallopeptidase domain Plasma peptidase 29 Membrane ADAMTS17 2.67E-04 3.051 ADAM metallopeptidase with Extracellular other thrombospondin type 1 motif, 17 Space ADCYAP1R1 1.20E-02 1.848 adenylate cyclase activating Plasma G-protein polypeptide 1 (pituitary) receptor Membrane coupled type I receptor ADH6 (includes 4.02E-02 −1.845 alcohol dehydrogenase 6 (class Cytoplasm enzyme EG:130) V) AHSA2 1.54E-04 −1.6 AHA1, activator of heat shock unknown other 90kDa protein ATPase homolog 2 (yeast) AK5 3.32E-02 1.658 adenylate kinase 5 Cytoplasm kinase AK7 -
Epigenetic Mechanisms Are Involved in the Oncogenic Properties of ZNF518B in Colorectal Cancer
Epigenetic mechanisms are involved in the oncogenic properties of ZNF518B in colorectal cancer Francisco Gimeno-Valiente, Ángela L. Riffo-Campos, Luis Torres, Noelia Tarazona, Valentina Gambardella, Andrés Cervantes, Gerardo López-Rodas, Luis Franco and Josefa Castillo SUPPLEMENTARY METHODS 1. Selection of genomic sequences for ChIP analysis To select the sequences for ChIP analysis in the five putative target genes, namely, PADI3, ZDHHC2, RGS4, EFNA5 and KAT2B, the genomic region corresponding to the gene was downloaded from Ensembl. Then, zoom was applied to see in detail the promoter, enhancers and regulatory sequences. The details for HCT116 cells were then recovered and the target sequences for factor binding examined. Obviously, there are not data for ZNF518B, but special attention was paid to the target sequences of other zinc-finger containing factors. Finally, the regions that may putatively bind ZNF518B were selected and primers defining amplicons spanning such sequences were searched out. Supplementary Figure S3 gives the location of the amplicons used in each gene. 2. Obtaining the raw data and generating the BAM files for in silico analysis of the effects of EHMT2 and EZH2 silencing The data of siEZH2 (SRR6384524), siG9a (SRR6384526) and siNon-target (SRR6384521) in HCT116 cell line, were downloaded from SRA (Bioproject PRJNA422822, https://www.ncbi. nlm.nih.gov/bioproject/), using SRA-tolkit (https://ncbi.github.io/sra-tools/). All data correspond to RNAseq single end. doBasics = TRUE doAll = FALSE $ fastq-dump -I --split-files SRR6384524 Data quality was checked using the software fastqc (https://www.bioinformatics.babraham. ac.uk /projects/fastqc/). The first low quality removing nucleotides were removed using FASTX- Toolkit (http://hannonlab.cshl.edu/fastxtoolkit/). -
A Systems-Genetics Analyses of Complex Phenotypes
A systems-genetics analyses of complex phenotypes A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Life Sciences 2015 David Ashbrook Table of contents Table of contents Table of contents ............................................................................................... 1 Tables and figures ........................................................................................... 10 General abstract ............................................................................................... 14 Declaration ....................................................................................................... 15 Copyright statement ........................................................................................ 15 Acknowledgements.......................................................................................... 16 Chapter 1: General introduction ...................................................................... 17 1.1 Overview................................................................................................... 18 1.2 Linkage, association and gene annotations .............................................. 20 1.3 ‘Big data’ and ‘omics’ ................................................................................ 22 1.4 Systems-genetics ..................................................................................... 24 1.5 Recombinant inbred (RI) lines and the BXD .............................................. 25 Figure 1.1: