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Functional Roles of Bromodomain Proteins in Cancer
cancers Review Functional Roles of Bromodomain Proteins in Cancer Samuel P. Boyson 1,2, Cong Gao 3, Kathleen Quinn 2,3, Joseph Boyd 3, Hana Paculova 3 , Seth Frietze 3,4,* and Karen C. Glass 1,2,4,* 1 Department of Pharmaceutical Sciences, Albany College of Pharmacy and Health Sciences, Colchester, VT 05446, USA; [email protected] 2 Department of Pharmacology, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA; [email protected] 3 Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; [email protected] (C.G.); [email protected] (J.B.); [email protected] (H.P.) 4 University of Vermont Cancer Center, Burlington, VT 05405, USA * Correspondence: [email protected] (S.F.); [email protected] (K.C.G.) Simple Summary: This review provides an in depth analysis of the role of bromodomain-containing proteins in cancer development. As readers of acetylated lysine on nucleosomal histones, bromod- omain proteins are poised to activate gene expression, and often promote cancer progression. We examined changes in gene expression patterns that are observed in bromodomain-containing proteins and associated with specific cancer types. We also mapped the protein–protein interaction network for the human bromodomain-containing proteins, discuss the cellular roles of these epigenetic regu- lators as part of nine different functional groups, and identify bromodomain-specific mechanisms in cancer development. Lastly, we summarize emerging strategies to target bromodomain proteins in cancer therapy, including those that may be essential for overcoming resistance. Overall, this review provides a timely discussion of the different mechanisms of bromodomain-containing pro- Citation: Boyson, S.P.; Gao, C.; teins in cancer, and an updated assessment of their utility as a therapeutic target for a variety of Quinn, K.; Boyd, J.; Paculova, H.; cancer subtypes. -
Clinical Report of a Neonate Carrying a Large Deletion in the 10P15.3P13
Shao et al. Mol Cytogenet (2021) 14:29 https://doi.org/10.1186/s13039-021-00546-1 CASE REPORT Open Access Clinical report of a neonate carrying a large deletion in the 10p15.3p13 region and review of the literature Qiao‑Yan Shao, Pei‑Lin Wu, Bi‑Yun Lin, Sen‑Jing Chen, Jian Liu and Su‑Qing Chen* Abstract Background: Terminal deletion of chromosome 10p is a rare chromosomal abnormality. We report a neonatal case with a large deletion of 10p15.3p13 diagnosed early because of severe clinical manifestations. Case presentation: Our patient presented with specifc facial features, hypoparathyroidism, sen sorineural deafness, renal abnormalities, and developmental retardation, and carried a 12.6 Mb deletion in the 10p15.3 p13 region. The terminal 10p deletion involved in our patient is the second largest reported terminal deletion reported to date, and includes the ZMYND11 and GATA3 genes and a partial critical region of the DiGeorge syndrome 2 gene (DGS2). Conclusion: On the basis of a literature review, this terminal 10p deletion in the present case is responsible for a spe‑ cifc contiguous gene syndrome. This rare case may help the understanding of the genotype–phenotype spectrum of terminal deletion of chromosome 10p. Keywords: 10p15.3 microdeletion syndrome, HDR syndrome, DiGeorge critical region 2, ZMYND11, GATA3 Background Here, we report a Chinese infant showing specifc Terminal deletion of chromosome 10p is a rare chromo- facial features, congenital hypoparathyroidism, sen- somal disorder. Te haploinsufciency in the distal region sorineural hearing loss, absence of the right kidney, a of 10p15.3 is responsible for 10p15.3 microdeletion syn- sacrococcygeal mass, a right frontal cyst, and psycho- drome (OMIM 608,668), characterized by specifc facial motor retardation. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 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/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.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 © 2016 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 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Gene Expression Studies: from Case-Control to Multiple-Population-Based Studies
From the Institute of Human Genetics, Helmholtz Zentrum Munchen,¨ Deutsches Forschungszentrum fur¨ Gesundheit und Umwelt (GmbH) Head: Prof. Dr. Thomas Meitinger Gene expression studies: From case-control to multiple-population-based studies Thesis Submitted for a Doctoral Degree in Natural Sciences at the Faculty of Medicine, Ludwig-Maximilians-Universitat¨ Munchen¨ Katharina Schramm Dachau, Germany 2016 With approval of the Faculty of Medicine Ludwig-Maximilians-Universit¨atM ¨unchen Supervisor/Examiner: Prof. Dr. Thomas Illig Co-Examiners: Prof. Dr. Roland Kappler Dean: Prof. Dr. med. dent. Reinhard Hickel Date of oral examination: 22.12.2016 II Dedicated to my family. III Abstract Recent technological developments allow genome-wide scans of gene expression levels. The reduction of costs and increasing parallelization of processing enable the quantification of 47,000 transcripts in up to twelve samples on a single microarray. Thereby the data collec- tion of large population-based studies was improved. During my PhD, I first developed a workflow for the statistical analyses of case-control stu- dies of up to 50 samples. With large population-based data sets generated I established a pipeline for quality control, data preprocessing and correction for confounders, which re- sulted in substantially improved data. In total, I processed more than 3,000 genome-wide expression profiles using the generated pipeline. With 993 whole blood samples from the population-based KORA (Cooperative Health Research in the Region of Augsburg) study we established one of the largest population-based resource. Using this data set we contributed to a number of transcriptome-wide association studies within national (MetaXpress) and international (CHARGE) consortia. -
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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Supporting Information
Supporting Information Muro et al. 10.1073/pnas.0807813105 SI Text (Fig. S1) showed for 10 of the PAS variants a marked tendency 1. Algorithm for Automated Recognition of EST End Clusters. To to lie 10–30 nt upstream of EST ends, whereas no strong trend determine the coordinates of genomic EST alignments we used was seen for 3 additional variants. Based on this simple analysis the UCSC genome annotation (1), a regularly updated database we chose to accept only 10 of the variants as functional PAS which includes mouse and human EST sequences and their (Table S1), and only EST ends validated by a PAS 10–30 nt positions in the genome. The UCSC Golden Path version was upstream. Furthermore, we considered all EST ends validated by mm6 for mouse (equivalent to NCBI build 34, March 2005) and the same PAS and ending within 20 nt of one another to hg18 for human (NCBI Build 36.1, March 2006). The UCSC represent the same transcript end and to be clustered together, mapping database is based on alignments of ESTs to the as others have also proposed (6). corresponding genome using the BLAT program (2). Because of Next, we studied the distribution of individual EST ends the relatively low accuracy of EST sequencing and recent around our predicted rough ends (Fig. S2). The graph indicates genomic duplications (3), some ESTs can be aligned to more that in a range of Ϫ200 to ϩ150 nt around these rough ends the than 1 genomic position. To avoid possible misidentifications, frequency of EST ends is distinguishable from the surrounding ambiguously aligning ESTs were excluded from our analysis. -
An Integrative, Genomic, Transcriptomic and Network-Assisted
Yan et al. BMC Medical Genomics 2020, 13(Suppl 5):39 https://doi.org/10.1186/s12920-020-0675-4 RESEARCH Open Access An integrative, genomic, transcriptomic and network-assisted study to identify genes associated with human cleft lip with or without cleft palate Fangfang Yan1†, Yulin Dai1†, Junichi Iwata2,3, Zhongming Zhao1,4,5* and Peilin Jia1* From The International Conference on Intelligent Biology and Medicine (ICIBM) 2019 Columbus, OH, USA. 9-11 June 2019 Abstract Background: Cleft lip with or without cleft palate (CL/P) is one of the most common congenital human birth defects. A combination of genetic and epidemiology studies has contributed to a better knowledge of CL/P-associated candidate genes and environmental risk factors. However, the etiology of CL/P remains not fully understood. In this study, to identify new CL/P-associated genes, we conducted an integrative analysis using our in-house network tools, dmGWAS [dense module search for Genome-Wide Association Studies (GWAS)] and EW_dmGWAS (Edge-Weighted dmGWAS), in a combination with GWAS data, the human protein-protein interaction (PPI) network, and differential gene expression profiles. Results: A total of 87 genes were consistently detected in both European and Asian ancestries in dmGWAS. There were 31.0% (27/87) showed nominal significance with CL/P (gene-based p < 0.05), with three genes showing strong association signals, including KIAA1598, GPR183,andZMYND11 (p <1×10− 3). In EW_dmGWAS, we identified 253 and 245 module genes associated with CL/P for European ancestry and the Asian ancestry, respectively. Functional enrichment analysis demonstrated that these genes were involved in cell adhesion, protein localization to the plasma membrane, the regulation of the apoptotic signaling pathway, and other pathological conditions. -
Mouse Wdr37 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Wdr37 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Wdr37 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Wdr37 gene (NCBI Reference Sequence: NM_001039388 ; Ensembl: ENSMUSG00000021147 ) is located on Mouse chromosome 13. 14 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 14 (Transcript: ENSMUST00000054251). Exon 3 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Wdr37 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-90H23 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 9.34% of the coding region. The knockout of Exon 3 will result in frameshift of the gene. The size of intron 2 for 5'-loxP site insertion: 4159 bp, and the size of intron 3 for 3'-loxP site insertion: 2736 bp. The size of effective cKO region: ~597 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 3 14 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Wdr37 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Role and Regulation of the P53-Homolog P73 in the Transformation of Normal Human Fibroblasts
Role and regulation of the p53-homolog p73 in the transformation of normal human fibroblasts Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg vorgelegt von Lars Hofmann aus Aschaffenburg Würzburg 2007 Eingereicht am Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Dr. Martin J. Müller Gutachter: Prof. Dr. Michael P. Schön Gutachter : Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am Erklärung Hiermit erkläre ich, dass ich die vorliegende Arbeit selbständig angefertigt und keine anderen als die angegebenen Hilfsmittel und Quellen verwendet habe. Diese Arbeit wurde weder in gleicher noch in ähnlicher Form in einem anderen Prüfungsverfahren vorgelegt. Ich habe früher, außer den mit dem Zulassungsgesuch urkundlichen Graden, keine weiteren akademischen Grade erworben und zu erwerben gesucht. Würzburg, Lars Hofmann Content SUMMARY ................................................................................................................ IV ZUSAMMENFASSUNG ............................................................................................. V 1. INTRODUCTION ................................................................................................. 1 1.1. Molecular basics of cancer .......................................................................................... 1 1.2. Early research on tumorigenesis ................................................................................. 3 1.3. Developing -
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 -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo