DOCSLIB.ORG

Presentación De Powerpoint

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Presentación De Powerpoint P5-12-03 GENOME COPY NUMBER ENTROPY AS PREDICTOR OF RESPONSE FOR NEOADJUVANT THERAPY IN EARLY BREAST CANCER Emilio Alba1,2,15, Oscar M. Rueda3, Ana Lluch2,4,15, Joan Albanell2,5, Suet-Feung Chin3, Jose Ignacio Chacón López-Muñiz2,6, Lourdes Calvo2,7, Juan de la Haba-Rodriguez2,8,15, Begoña Bermejo2,4,15, Nuria Ribelles1, Pedro Sánchez Rovira2,9, Arrate Plazaola2,10, San Antonio Breast Agustí Barnadas2,11, Beatriz Cirauqui2,12, Manuel Ramos Vázquez2,13, Angels Arcusa2,14, Eva Carrasco2, Jesús Herranz2, Massimo Chiesa2, Rosalía Caballero2, Ángela Santonja1,3, Federico Rojo2,15,16, Carlos Caldas3 1Instituto de Investigación Biomédica de Málaga (IBIMA) - Hospital Clínico Universitario Virgen de la Victoria, Málaga, Spain, 2GEICAM Spanish Breast Cancer Group, San Sebastián de los Reyes, Madrid, Spain, 3Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cancer Symposium Robinson Way, Cambridge CB2 0RE, UK, 4Hospital Clínico Universitario de Valencia, Valencia, Spain, 5Hospital del Mar, Barcelona, Spain, 6Hospital Virgen de la Salud, Toledo, Spain, 7Complejo Hospitalario Universitario de A Coruña, A Coruña, Spain, 8Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC)–H. Universitario Reina Sofía, Universidad de Córdoba, Córdoba, Spain, 9Complejo Hospitalario de Jaén, Jaén, Spain, 10Onkologikoa, San Sebastián, Spain, 11Hospital de la Santa Creu i Sant Pau, Barcelona, Spain, 12Hospital Germans Trias i Pujol, Barcelona, Spain, 13Centro December 4-8, 2018 Oncológico de Galicia, A Coruña, Spain, 14Consorci Sanitari de Terrassa, Barcelona, Spain, 15Centro de Investigación Biomédica en Red de Oncología, CIBERONC-ISCIII, Spain, 16Fundación Jiménez Díaz, Madrid, Spain INTRODUCTION A total of 204 tumors (100 pre- and 104 post-treatment, 78 paired) from 165 patients from the GEICAM/2006 - 03 (113 RESULTS patients (68%); 81 treated with CT and 32 with HT) and GEICAM/2006-14 trials (52 patients (32%); 26 by ttm arm) were • Copy Number Alterations (CNAs) represent changes in copy number of genomic regions included in the CNAs analysis (Tab. 1). CNA 1 Tab.2 Comparative analysis of Chromosome CNA (GAIN/LOSS) p-value that arise in somatic cells as direct consequence of chromosomal instability (1). 2 Regions VARIABLE N (%) the CNA-regions revealed 11 (Start-End) pre- vs post-ttm tumor % adj. BH 3 # Tumor size 4 regions with CNAs (loss or • The presence of CNAs may affect the function of onco- and tumor-suppressor genes and 5 115 3 (187400001-189600001) GAIN (19% vs 43%) 0.0364 cT1+cT2 123 (75%) 6 gain) with a statistically therefore can be involved in tumor development and evolution (2) 7 >cT3 42 (25%) significant different distribution 172 6 (16300001-17900001) GAIN (8% vs 25%) 0.0431 8 Lymph nodes 9 between the 100 pre- and 104 175 6 (33400001-33500001) GAIN (5% vs 17%) 0.0466 • At the same time, the genomic imbalance due to CNAs can play a role in the response to pN0 94 (57%) 10 176 6 (33600001-34100001) GAIN (5% vs 18%) 0.0255 11 post-treatment tumors (p-value anti-cancer therapy and ultimately determine their efficacy (3) pN1-2-3 68 (41%) 12 177 6 (34200001-40900001) GAIN (5% vs 20%) 0.0149 13 adj. BH <0.05; p-value adjusted Unknown 3 (2%) 14 178 6 (41000001-41100001) GAIN (6% vs 18%) 0.0449 Chromosome # Chromosome for multiple comparison Tumor grade 15 16 according to Benjamini- 245 8 (400001-6100001) LOSS (20% vs 50%) 0.0033 OBJECTIVE G1+G2 91 (55%) 17 18 Hochberg). 356 10 (129900001-135300001) LOSS (8% vs 29%) 0.0214 G3 66 (40%) 19 418 11 (130800001-134700001) LOSS (20% vs 44%) 0.0253 We aimed to identify tumoral genomic specific alterations (CNAs) that may predict response to GX 8 (5%) 20 neoadjuvant treatment in the GEICAM/2006-03 and GEICAM/2006-14 clinical trials 21 454 12 (125600001-131900001) LOSS (11% vs 46%) 0 Ki67 50% 22 X 455 12 (132200001-133700001) LOSS (9% vs 30%) 0.0045 Low (<50) 90 (55%) High (≥50) 61 (37%) 0.0e+00 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08 MATERIALS AND METHODS Subtype Base # Luminal 64 (39%) Fig.1 We identified 672 CNA-regions with the “CGH-Regions” tool covering the 1 2 3 4 1 2 3 4 Tab.3 and Fig.5 Association with pCR of gene expression of 21q22.12 locus in the • Patients and tumor samples: GEICAM/2006-03 (NCT00432172) HER2-negative patients Her2+ 52 (31%) whole genome upon analysis of CNAs data. Regions are displayed as a bi-colored Hatzis neoadjuvant dataset (GSE25066) (9). Genes whose expression were significantly were selectively treated according to clinical subtypes: triple negative (TN) patients were Triple Negative 49 (30%) segments, the lower and upper part of which correspond to the proportions of increased in the cohort of patients that reached pCR (p-value adjusted BH <0.05 and t- treated with standard taxane/anthracycline-based chemotherapy (TA-CT) +/- carboplatin, Tab.1 Main clinical-pathological samples with a loss (red) or gain (green), respectively. Regions were then categorized test<0) are reported in red. These data indirectly point to a putative role in neoadjuvant while luminal patients were randomized to TA-CT vs. hormonotherapy (HT). GEICAM/2006- patients’ characteristics according to their alteration status as gain, normal and loss. treatment response of specific genes localized in the 21q22.12 locus. A brief description 14 (NCT00841828) HER2+ patients received TA-CT plus anti-HER2 therapy (Trastuzumab of published evidences supporting the relation of these genes with BC is reported, or Lapatinib). Pathological complete response (pCR) in breast and axilla was used to together with a scheme showing their localization in the locus. measure treatment (ttm) response, according to Miller & Payne criteria. Available pre- and Genomic location CNA Region Tumors Tumors (Chr: start-end) # p-val pCR=YES pCR=NO post-ttm tumors were analyzed from patients included in both clinical trials. (%) (%) pCR locus 11q12 association Gene Evidences of association with BC p-val • CNAs identification: Tumoral DNA extracted from FFPE samples was used to generate t-test adj BH sequencing libraries. Single-read 50bp whole-genome sequencing (WGS) was performed on Chromatin Assembly Factor 1 subunit a HiSeq4000 (Illumina). Data were pre-processed and normalized with “QDNAseq“ package locus 16q22 CHAF1B 4.7e-08 -6,47 B: associated with proliferation and bad (4). Segmentation was implemented with “DNA Copy” software (5) while “CGH call” (6) was prognosis (10, 11, 12) used for copy number call. Recurrent altered genomic regions were defined as CNAs CBR3 2.3e-05 -5,07 Carbonyl reductases (1 & 3): lower activity are associated with increased CT adopting 3 categories: Loss (single/double), Normal and Gain (gain/amplification). CBR1 0.0006 -4,21 efficacy (13, 14) Regulator of Calcineurin 1: growth and • CNAs Regions: CNAs data were independently analyzed with “CGH regions” metastasis suppressor that functions in RCAN1 0.0079 -3,36 part through NFE2L3 transcription factor, (Bioconductor) and “GISTIC2.0” tools (7, 8) in order to identify specific genomic regions that locus 21q22 overexpressed in BC (15,16) show significant copy number alterations amongst samples. Wilcoxon test was used to Solute Carrier Family 5 Member 3: analyze the frequency of altered regions between pre- and post-treatment populations and Prevents intracellular accumulation of SLC5A3 0.0286 -2,87 logistic regression analyses were used to explore their association with treatment response myo-inositol – no described connection with cancer (pCR). Genes localized in significant genomic regions were identified according to the “hg19” RUNX1 transcription factor: tumor CGH alteration: genome assembly. RUNX1 0.0008 4,11 suppressor role in ER+ lum BC and Fig.4 Analysis of CNAs data with “GISTIC 2.0” tool identifies 68 amplified oncogenic role in TNBC (17) • Validation in the Hatzis dataset (GSE25066): gene expression of CNA-regions associated Fig.3 We identified 8 CNA-regions (“CGH regions” tool) whose alterations were significantly associated with treatment response (pCR): gain of regions #374, 653, 654, (red peaks) and 50 deleted loci (blue peaks). The amplified locus 21q22.12 with pCR was analyzed in Hatzis microarray-based dataset including HER2-neg breast Other genes found in this locus not associated with pCR are: SETD4, ATP5O, DOPEY2, ITSN1, (marked with “ “) corresponds to the amplified CNA-regions #653 and 654 cancer (BC) patients treated with neoadjuvant AT-CT (9). 655 or 656 were associated with pCR while loss of regions #533, 534 or 535 were RUNX1-IT1, MORC3, KCNE1, KCNE2, LINC00160, MRPS6, LINC00310, MIR802, associated with no-pCR (p-value adj. BH<0.05) previously shown to be associated with pCR. LOC100133286, CBR3-AS1 CONCLUSIONS REFERENCES ACKNOWLEDGMENTS This presentation is the 1. Tang et al., Cell. 2013; 152(3): 394–405. 10. Polo et al. Cancer Res. 2004, 64(7): 2371-81 intellectual property of the 2. Negrini et al., Nat Rev Mol Cell Biol. 2010;11(3):220-8 11. Polo et al., Histopathology. 2010; 57(5):716-24. • Genomic aberrations landscape is modulated by neoadjuvant therapy in 3. Vargas-Rondón et al., Cancers, 2017; 10(1):4 12. Montes de Oca et al., Mol Oncol, 9(3): 657-74 We thank all investigators and patients author/presenter. Contact at: Breast Cancer. 4. Scheinin et al., Genome Res. 2014; 24: 2022–2032. 13. Jo et al., Antioxid Redox Signal, 2017 26(2):70-83. participating in the GEICAM/2006-03 5. Seshan et al., 2018 R package version 1.54.0 14. Fan et al., Pharmacogenet Genomics, 18(7): 621-31 secretaria- and GEICAM/2006-14 studies. [email protected] • 6. van de Wiel et al., Bioinformatics. 2007; 23(7):892-4 15. Wang et al., JCI Insight; 2017, 2(5): e90651 QR 21q22.12 gene locus amplification might be associated with neoadjuvant 7.
Load more

Recommended publications
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Investigation of Copy Number Variations on Chromosome 21 Detected by Comparative Genomic Hybridization
    Li et al. Molecular Cytogenetics (2018) 11:42 https://doi.org/10.1186/s13039-018-0391-3 RESEARCH Open Access Investigation of copy number variations on chromosome 21 detected by comparative genomic hybridization (CGH) microarray in patients with congenital anomalies Wenfu Li, Xianfu Wang and Shibo Li* Abstract Background: The clinical features of Down syndrome vary among individuals, with those most common being congenital heart disease, intellectual disability, developmental abnormity and dysmorphic features. Complex combination of Down syndrome phenotype could be produced by partially copy number variations (CNVs) on chromosome 21 as well. By comparing individual with partial CNVs of chromosome 21 with other patients of known CNVs and clinical phenotypes, we hope to provide a better understanding of the genotype-phenotype correlation of chromosome 21. Methods: A total of 2768 pediatric patients sample collected at the Genetics Laboratory at Oklahoma University Health Science Center were screened using CGH Microarray for CNVs on chromosome 21. Results: We report comprehensive clinical and molecular descriptions of six patients with microduplication and seven patients with microdeletion on the long arm of chromosome 21. Patients with microduplication have varied clinical features including developmental delay, microcephaly, facial dysmorphic features, pulmonary stenosis, autism, preauricular skin tag, eye pterygium, speech delay and pain insensitivity. We found that patients with microdeletion presented with developmental delay, microcephaly, intrauterine fetal demise, epilepsia partialis continua, congenital coronary anomaly and seizures. Conclusion: Three patients from our study combine with four patients in public database suggests an association between 21q21.1 microduplication of CXADR gene and patients with developmental delay. One patient with 21q22.13 microdeletion of DYRK1A shows association with microcephaly and scoliosis.
    [Show full text]
  • Whole Exome Sequencing in ADHD Trios from Single and Multi-Incident Families Implicates New Candidate Genes and Highlights Polygenic Transmission
    European Journal of Human Genetics (2020) 28:1098–1110 https://doi.org/10.1038/s41431-020-0619-7 ARTICLE Whole exome sequencing in ADHD trios from single and multi-incident families implicates new candidate genes and highlights polygenic transmission 1,2 1 1,2 1,3 1 Bashayer R. Al-Mubarak ● Aisha Omar ● Batoul Baz ● Basma Al-Abdulaziz ● Amna I. Magrashi ● 1,2 2 2,4 2,4,5 6 Eman Al-Yemni ● Amjad Jabaan ● Dorota Monies ● Mohamed Abouelhoda ● Dejene Abebe ● 7 1,2 Mohammad Ghaziuddin ● Nada A. Al-Tassan Received: 26 September 2019 / Revised: 26 February 2020 / Accepted: 10 March 2020 / Published online: 1 April 2020 © The Author(s) 2020. This article is published with open access Abstract Several types of genetic alterations occurring at numerous loci have been described in attention deficit hyperactivity disorder (ADHD). However, the role of rare single nucleotide variants (SNVs) remains under investigated. Here, we sought to identify rare SNVs with predicted deleterious effect that may contribute to ADHD risk. We chose to study ADHD families (including multi-incident) from a population with a high rate of consanguinity in which genetic risk factors tend to 1234567890();,: 1234567890();,: accumulate and therefore increasing the chance of detecting risk alleles. We employed whole exome sequencing (WES) to interrogate the entire coding region of 16 trios with ADHD. We also performed enrichment analysis on our final list of genes to identify the overrepresented biological processes. A total of 32 rare variants with predicted damaging effect were identified in 31 genes. At least two variants were detected per proband, most of which were not exclusive to the affected individuals.
    [Show full text]
  • Title CNV Analysis in Tourette Syndrome Implicates Large Genomic Rearrangements in COL8A1 and NRXN1 Author(S)
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by HKU Scholars Hub CNV Analysis in Tourette Syndrome Implicates Large Genomic Title Rearrangements in COL8A1 and NRXN1 Nag, A; Bochukova, EG; Kremeyer, B; Campbell, DD; et al.,; Author(s) Ruiz-Linares, A Citation PLoS ONE, 2013, v. 8 n. 3 Issued Date 2013 URL http://hdl.handle.net/10722/189374 Rights Creative Commons: Attribution 3.0 Hong Kong License CNV Analysis in Tourette Syndrome Implicates Large Genomic Rearrangements in COL8A1 and NRXN1 Abhishek Nag1, Elena G. Bochukova2, Barbara Kremeyer1, Desmond D. Campbell1, Heike Muller1, Ana V. Valencia-Duarte3,4, Julio Cardona5, Isabel C. Rivas5, Sandra C. Mesa5, Mauricio Cuartas3, Jharley Garcia3, Gabriel Bedoya3, William Cornejo4,5, Luis D. Herrera6, Roxana Romero6, Eduardo Fournier6, Victor I. Reus7, Thomas L Lowe7, I. Sadaf Farooqi2, the Tourette Syndrome Association International Consortium for Genetics, Carol A. Mathews7, Lauren M. McGrath8,9, Dongmei Yu9, Ed Cook10, Kai Wang11, Jeremiah M. Scharf8,9,12, David L. Pauls8,9, Nelson B. Freimer13, Vincent Plagnol1, Andre´s Ruiz-Linares1* 1 UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom, 2 University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom, 3 Laboratorio de Gene´tica Molecular, SIU, Universidad de Antioquia, Medellı´n, Colombia, 4 Escuela de Ciencias de la Salud, Universidad Pontificia
    [Show full text]
  • Supp Table 6.Pdf
    Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin
    [Show full text]
  • UC Irvine UC Irvine Previously Published Works
    UC Irvine UC Irvine Previously Published Works Title Analysis of copy number variation in Alzheimer's disease in a cohort of clinically characterized and neuropathologically verified individuals. Permalink https://escholarship.org/uc/item/0wh7t3r9 Journal PloS one, 7(12) ISSN 1932-6203 Authors Swaminathan, Shanker Huentelman, Matthew J Corneveaux, Jason J et al. Publication Date 2012 DOI 10.1371/journal.pone.0050640 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Analysis of Copy Number Variation in Alzheimer’s Disease in a Cohort of Clinically Characterized and Neuropathologically Verified Individuals Shanker Swaminathan1,2, Matthew J. Huentelman3,4, Jason J. Corneveaux3,4, Amanda J. Myers5,6, Kelley M. Faber2, Tatiana Foroud1,2,7, Richard Mayeux8, Li Shen1,7, Sungeun Kim1,7, Mari Turk3,4, John Hardy9, Eric M. Reiman3,4,10, Andrew J. Saykin1,2,7*, for the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the NIA-LOAD/NCRAD Family Study Group 1 Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 2 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 3 Neurogenomics Division, The Translational Genomics Research Institute (TGen), Phoenix, Arizona, United States of America, 4 The Arizona Alzheimer’s Consortium, Phoenix, Arizona, United States of America, 5 Departments of Psychiatry and Behavioral Sciences, and Human Genetics and Genomics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America, 6 Johnnie B. Byrd Sr.
    [Show full text]
  • Strand Breaks for P53 Exon 6 and 8 Among Different Time Course of Folate Depletion Or Repletion in the Rectosigmoid Mucosa
    SUPPLEMENTAL FIGURE COLON p53 EXONIC STRAND BREAKS DURING FOLATE DEPLETION-REPLETION INTERVENTION Supplemental Figure Legend Strand breaks for p53 exon 6 and 8 among different time course of folate depletion or repletion in the rectosigmoid mucosa. The input of DNA was controlled by GAPDH. The data is shown as ΔCt after normalized to GAPDH. The higher ΔCt the more strand breaks. The P value is shown in the figure. SUPPLEMENT S1 Genes that were significantly UPREGULATED after folate intervention (by unadjusted paired t-test), list is sorted by P value Gene Symbol Nucleotide P VALUE Description OLFM4 NM_006418 0.0000 Homo sapiens differentially expressed in hematopoietic lineages (GW112) mRNA. FMR1NB NM_152578 0.0000 Homo sapiens hypothetical protein FLJ25736 (FLJ25736) mRNA. IFI6 NM_002038 0.0001 Homo sapiens interferon alpha-inducible protein (clone IFI-6-16) (G1P3) transcript variant 1 mRNA. Homo sapiens UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 15 GALNTL5 NM_145292 0.0001 (GALNT15) mRNA. STIM2 NM_020860 0.0001 Homo sapiens stromal interaction molecule 2 (STIM2) mRNA. ZNF645 NM_152577 0.0002 Homo sapiens hypothetical protein FLJ25735 (FLJ25735) mRNA. ATP12A NM_001676 0.0002 Homo sapiens ATPase H+/K+ transporting nongastric alpha polypeptide (ATP12A) mRNA. U1SNRNPBP NM_007020 0.0003 Homo sapiens U1-snRNP binding protein homolog (U1SNRNPBP) transcript variant 1 mRNA. RNF125 NM_017831 0.0004 Homo sapiens ring finger protein 125 (RNF125) mRNA. FMNL1 NM_005892 0.0004 Homo sapiens formin-like (FMNL) mRNA. ISG15 NM_005101 0.0005 Homo sapiens interferon alpha-inducible protein (clone IFI-15K) (G1P2) mRNA. SLC6A14 NM_007231 0.0005 Homo sapiens solute carrier family 6 (neurotransmitter transporter) member 14 (SLC6A14) mRNA.
    [Show full text]
  • Quantitative Proteomic Analysis of Amniocytes Reveals Potentially Dysregulated Molecular Networks in Down Syndrome
    Cho et al. Clinical Proteomics 2013, 10:2 http://www.clinicalproteomicsjournal.com/content/10/1/2 CLINICAL PROTEOMICS RESEARCH Open Access Quantitative proteomic analysis of amniocytes reveals potentially dysregulated molecular networks in Down syndrome Chan-Kyung J Cho1, Andrei P Drabovich2, George S Karagiannis1,2, Eduardo Martínez-Morillo2, Shawn Dason1, Apostolos Dimitromanolakis2 and Eleftherios P Diamandis1,2,3,4* Abstract Background: Down syndrome (DS), caused by an extra copy of chromosome 21, affects 1 in 750 live births and is characterized by cognitive impairment and a constellation of congenital defects. Currently, little is known about the molecular pathogenesis and no direct genotype-phenotype relationship has yet been confirmed. Since DS amniocytes are expected to have a distinct biological behaviour compared to normal amniocytes, we hypothesize that relative quantification of proteins produced from trisomy and euploid (chromosomally normal) amniocytes will reveal dysregulated molecular pathways. Results: Chromosomally normal- and Trisomy 21-amniocytes were quantitatively analyzed by using Stable Isotope Labeling of Amino acids in Cell culture and tandem mass spectrometry. A total of 4919 unique proteins were identified from the supernatant and cell lysate proteome. More specifically, 4548 unique proteins were identified from the lysate, and 91% of these proteins were quantified based on MS/MS spectra ratios of peptides containing isotope-labeled amino acids. A total of 904 proteins showed significant differential expression and were involved in 25 molecular pathways, each containing a minimum of 16 proteins. Sixty of these proteins consistently showed aberrant expression from trisomy 21 affected amniocytes, indicating their potential role in DS pathogenesis. Nine proteins were analyzed with a multiplex selected reaction monitoring assay in an independent set of Trisomy 21-amniocyte samples and two of them (SOD1 and NES) showed a consistent differential expression.
    [Show full text]
  • Epigenetic Changes in Human Model KMT2A Leukemias Highlight Early Events During Leukemogenesis
    Epigenetic changes in human model KMT2A leukemias highlight early events during leukemogenesis Thomas Milan1, Magalie Celton1, Karine Lagacé1, Élodie Roques1, Safia Safa-Tahar-Henni1, Eva Bresson2,3,4, Anne Bergeron2,3,4, Josée Hebert5,6, Soheil Meshinchi7, Sonia Cellot8, Frédéric Barabé2,3,4, 1,6 Brian T Wilhelm Author contributions: BTW and TM designed the study, analyzed data and drafted the manuscript. TM and KL performed ChIP-seq and ATAC-seq, analysed the data and generated figures. MC performed Methyl-seq experiments, analysed data, generated figures and drafted the manuscript. SS-T-H assisted with the ATAC-seq analysis and generation of figures. KL, ER, EB, and AB helped with molecular biology work, cloning and cell culture. EB, AB and FB generated the model on mice from CD34+ cells. SM provided expression and clinical data for patient samples and JH and SC collected, characterized, and banked the local patient samples used in this study. Affiliations: 1Laboratory for High Throughput Biology, Institute for Research in Immunology and Cancer, Montréal, QC, Canada 2Centre de recherche en infectiologie du CHUL, Centre de recherche du CHU de Québec – Université Laval, Québec City, QC, Canada, 3CHU de Québec – Université Laval – Hôpital Enfant-Jésus; Québec City, QC, Canada; 4Department of Medicine, Université Laval, Quebec City, QC, Canada 5Division of Hematology-Oncology and Leukemia Cell Bank of Quebec, Maisonneuve-Rosemont Hospital, Montréal, QC, Canada, 6Department of Medicine, Université de Montréal, Montréal, QC, Canada, 7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA 8Department of pediatrics, division of Hematology, Ste-Justine Hospital, Montréal, QC, Canada Running head: Early epigenetic changes in KM3-AML *Correspondence to: Brian T Wilhelm Institute for Research in Immunology and Cancer Université de Montréal P.O.
    [Show full text]
  • Publications from Dynamic Molecular Cell Biology Students 2019 Simonetti, B., & Cullen, P
    Publications from Dynamic Molecular Cell Biology students 2019 Simonetti, B., & Cullen, P. J. (2019). Actin-dependent endosomal receptor recycling. Current Opinion in Cell Biology, 56, 22–33. https://doi.org/10.1016/j.ceb.2018.08.006 Stathakos, P., Jimenez-Moreno, N., Crompton, L., Nistor, P., Caldwell, M. A., & Lane, J. D. (2019). Imaging Autophagy in hiPSC-Derived Midbrain Dopaminergic Neuronal Cultures for Parkinson’s Disease Research. Methods in Molecular Biology (Clifton, N.J.), 1880, 257–280. https://doi.org/10.1007/978-1-4939-8873-0_17 2018 Daly, J. L., & Cullen, P. J. (2018). Endoplasmic Reticulum–Endosome Contact Sites: Specialized Interfaces for Orchestrating Endosomal Tubule Fission? Biochemistry, 57(49), 6738–6740. https://doi.org/10.1021/acs.biochem.8b01176 Gurevich, D. B., Severn, C. E., Twomey, C., Greenhough, A., Cash, J., Toye, A. M., … Martin, P. (2018). Live imaging of wound angiogenesis reveals macrophage orchestrated vessel sprouting and regression. The EMBO Journal, 37(13), e97786. https://doi.org/10.15252/embj.201797786 Gurung, S., Evans, A. J., Wilkinson, K. A., & Henley, J. M. (2018). ADAR2-mediated Q/R editing of GluK2 regulates kainate receptor upscaling in response to suppression of synaptic activity. Journal of Cell Science, 131(24), jcs222273. https://doi.org/10.1242/jcs.222273 Hawkins, S. J., Crompton, L. A., Sood, A., Saunders, M., Boyle, N. T., Buckley, A., Minogue, A. M., McComish, S. F., Jiménez-Moreno, N., Cordero-Llana, O., Stathakos, P., Gilmore, C. E., Kelly, S., Lane, J. D., Case, C. P. & Caldwell, M. A. (2018). Nanoparticle-induced neuronal toxicity across placental barriers is mediated by autophagy and dependent on astrocytes.
    [Show full text]
  • Published Version
    PUBLISHED VERSION King-Hwa Ling, Chelsee A Hewitt, Kai-Leng Tan, Pike-See Cheah, Sharmili Vidyadaran, Mei-I Lai, Han- Chung Lee, Ken Simpson, Lavinia Hyde, Melanie A Pritchard, Gordon K Smyth, Tim Thomas, and Hamish S Scott Functional transcriptome analysis of the postnatal brain of the Ts1Cje mouse model for Down syndrome reveals global disruption of interferon-related molecular networks BMC Genomics, 2014; 15(1):624-1-624-19 © 2014 Ling et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Originally published at: http://doi.org/10.1186/1471-2164-15-624 PERMISSIONS http://creativecommons.org/licenses/by/4.0/ http://hdl.handle.net/2440/97389 Ling et al. BMC Genomics 2014, 15:624 http://www.biomedcentral.com/1471-2164/15/624 RESEARCH ARTICLE Open Access Functional transcriptome analysis of the postnatal brain of the Ts1Cje mouse model for Down syndrome reveals global disruption of interferon-related molecular networks King-Hwa Ling1,2,3*†, Chelsee A Hewitt2,4†, Kai-Leng Tan1,5†, Pike-See Cheah1,5, Sharmili Vidyadaran1,6, Mei-I Lai1,6, Han-Chung Lee1, Ken Simpson2, Lavinia Hyde2, Melanie A Pritchard7, Gordon K Smyth2, Tim Thomas2 and Hamish S Scott2,8,9* Abstract Background: The Ts1Cje mouse model of Down syndrome (DS) has partial triplication of mouse chromosome 16 (MMU16), which is partially homologous to human chromosome 21.
    [Show full text]
  • Autocrine IFN Signaling Inducing Profibrotic Fibroblast Responses By
    Downloaded from http://www.jimmunol.org/ by guest on September 23, 2021 Inducing is online at: average * The Journal of Immunology , 11 of which you can access for free at: 2013; 191:2956-2966; Prepublished online 16 from submission to initial decision 4 weeks from acceptance to publication August 2013; doi: 10.4049/jimmunol.1300376 http://www.jimmunol.org/content/191/6/2956 A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Autocrine IFN Signaling Feng Fang, Kohtaro Ooka, Xiaoyong Sun, Ruchi Shah, Swati Bhattacharyya, Jun Wei and John Varga J Immunol cites 49 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2013/08/20/jimmunol.130037 6.DC1 This article http://www.jimmunol.org/content/191/6/2956.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 23, 2021. The Journal of Immunology A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Inducing Autocrine IFN Signaling Feng Fang,* Kohtaro Ooka,* Xiaoyong Sun,† Ruchi Shah,* Swati Bhattacharyya,* Jun Wei,* and John Varga* Activation of TLR3 by exogenous microbial ligands or endogenous injury-associated ligands leads to production of type I IFN.
    [Show full text]