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Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin a and Affects the Migration and Invasion Potential of Breast Cancer Cells
Published OnlineFirst February 28, 2010; DOI: 10.1158/0008-5472.CAN-08-1108 Tumor and Stem Cell Biology Cancer Research Cyclin D1/Cyclin-Dependent Kinase 4 Interacts with Filamin A and Affects the Migration and Invasion Potential of Breast Cancer Cells Zhijiu Zhong, Wen-Shuz Yeow, Chunhua Zou, Richard Wassell, Chenguang Wang, Richard G. Pestell, Judy N. Quong, and Andrew A. Quong Abstract Cyclin D1 belongs to a family of proteins that regulate progression through the G1-S phase of the cell cycle by binding to cyclin-dependent kinase (cdk)-4 to phosphorylate the retinoblastoma protein and release E2F transcription factors for progression through cell cycle. Several cancers, including breast, colon, and prostate, overexpress the cyclin D1 gene. However, the correlation of cyclin D1 overexpression with E2F target gene regulation or of cdk-dependent cyclin D1 activity with tumor development has not been identified. This suggests that the role of cyclin D1 in oncogenesis may be independent of its function as a cell cycle regulator. One such function is the role of cyclin D1 in cell adhesion and motility. Filamin A (FLNa), a member of the actin-binding filamin protein family, regulates signaling events involved in cell motility and invasion. FLNa has also been associated with a variety of cancers including lung cancer, prostate cancer, melanoma, human bladder cancer, and neuroblastoma. We hypothesized that elevated cyclin D1 facilitates motility in the invasive MDA-MB-231 breast cancer cell line. We show that MDA-MB-231 motility is affected by disturbing cyclin D1 levels or cyclin D1-cdk4/6 kinase activity. -
Molecular Subtypes of Diffuse Large B-Cell Lymphoma Arise by Distinct Genetic Pathways
Molecular subtypes of diffuse large B-cell lymphoma arise by distinct genetic pathways Georg Lenza, George W. Wrightb, N. C. Tolga Emrea, Holger Kohlhammera, Sandeep S. Davea, R. Eric Davisa, Shannon Cartya, Lloyd T. Lama, A. L. Shaffera, Wenming Xiaoc, John Powellc, Andreas Rosenwaldd, German Ottd,e, Hans Konrad Muller-Hermelinkd, Randy D. Gascoynef, Joseph M. Connorsf, Elias Campog, Elaine S. Jaffeh, Jan Delabiei, Erlend B. Smelandj,k, Lisa M. Rimszal, Richard I. Fisherm,n, Dennis D. Weisenburgero, Wing C. Chano, and Louis M. Staudta,q aMetabolism Branch, bBiometric Research Branch, cCenter for Information Technology, and hLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892; dDepartment of Pathology, University of Wu¨rzburg, 97080 Wu¨rzburg, Germany; eDepartment of Clinical Pathology, Robert-Bosch-Krankenhaus, 70376 Stuttgart, Germany; fBritish Columbia Cancer Agency, Vancouver, British Columbia, Canada V5Z 4E6; gHospital Clinic, University of Barcelona, 08036 Barcelona, Spain; iPathology Clinic and jInstitute for Cancer Research, Rikshospitalet Hospital, Oslo, Norway; kCentre for Cancer Biomedicine, Faculty Division the Norwegian Radium Hospital, N-0310, Oslo, Norway; lDepartment of Pathology, University of Arizona, Tucson, AZ 85724; mSouthwest Oncology Group, 24 Frank Lloyd Wright Drive, Ann Arbor, MI 48106 ; nJames P. Wilmot Cancer Center, University of Rochester, Rochester, NY 14642; and oDepartments of Pathology and Microbiology, University of Nebraska, Omaha, NE 68198 Edited by Ira -
CCNL1 (NM 020307) Human Untagged Clone – SC113160 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC113160 CCNL1 (NM_020307) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: CCNL1 (NM_020307) Human Untagged Clone Tag: Tag Free Symbol: CCNL1 Synonyms: ania-6a; ANIA6A; BM-001; PRO1073 Vector: pCMV6-XL5 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None Fully Sequenced ORF: >NCBI ORF sequence for NM_020307, the custom clone sequence may differ by one or more nucleotides ATGGCGTCCGGGCCTCATTCGACAGCTACTGCTGCCGCAGCCGCCTCATCGGCCGCCCCAAGCGCGGGCG GCTCCAGCTCCGGGACGACGACCACGACGACGACCACGACGGGAGGGATCCTGATCGGCGATCGCCTGTA CTCGGAAGTTTCACTTACCATCGACCACTCTCTGATTCCGGAGGAGAGGCTCTCGCCCACCCCATCCATG CAGGATGGGCTCGACCTGCCCAGTGAGACGGACTTACGCATCCTGGGCTGCGAGCTCATCCAGGCCGCCG GCATTCTCCTCCGGCTGCCGCAGGTGGCGATGGCAACGGGGCAGGTGTTGTTTCATCGTTTTTTCTACTC CAAATCTTTCGTCAAACACAGTTTCGAGATTGTTGCTATGGCTTGTATTAATCTTGCATCAAAAATCGAA GAAGCACCTAGAAGAATAAGAGATGTGATTAATGTATTCCACCACCTCCGCCAGTTAAGAGGAAAAAGGA CTCCAAGCCCCCTGATCCTTGATCAGAACTACATTAACACCAAAAATCAAGTTATCAAAGCAGAGAGGAG GGTGCTAAAGGAGTTGGGATTTTGTGTTCATGTCAAGCATCCTCATAAGATCATTGTTATGTATTTACAA GTCTTAGAATGTGAACGTAATCAAACCCTGGTTCAAACTGCCTGGAATTACATGAATGACAGTCTTCGAA CCAATGTGTTTGTTCGATTTCAACCAGAGACTATAGCATGTGCTTGCATCTACCTTGCAGCTAGAGCACT TCAGATTCCGTTGCCAACTCGTCCCCATTGGTTTCTTCTTTTTGGTACTACAGAAGAGGAAATCCAGGAA ATCTGCATAGAAACACTTAGGCTTTATACCAGAAAAAAGCCAAACTATGAATTACTGGAAAAAGAAGTAG AAAAAAGAAAAGTAGCCTTACAAGAAGCCAAATTAAAAGCAAAGGGATTGAATCCGGATGGAACTCCAGC -
Co-Occupancy by Multiple Cardiac Transcription Factors Identifies
Co-occupancy by multiple cardiac transcription factors identifies transcriptional enhancers active in heart Aibin Hea,b,1, Sek Won Konga,b,c,1, Qing Maa,b, and William T. Pua,b,2 aDepartment of Cardiology and cChildren’s Hospital Informatics Program, Children’s Hospital Boston, Boston, MA 02115; and bHarvard Stem Cell Institute, Harvard University, Cambridge, MA 02138 Edited by Eric N. Olson, University of Texas Southwestern, Dallas, TX, and approved February 23, 2011 (received for review November 12, 2010) Identification of genomic regions that control tissue-specific gene study of a handful of model genes (e.g., refs. 7–10), it has not been expression is currently problematic. ChIP and high-throughput se- evaluated using unbiased, genome-wide approaches. quencing (ChIP-seq) of enhancer-associated proteins such as p300 In this study, we used a modified ChIP-seq approach to define identifies some but not all enhancers active in a tissue. Here we genome wide the binding sites of these cardiac TFs (1). We show that co-occupancy of a chromatin region by multiple tran- provide unbiased support for collaborative TF interactions in scription factors (TFs) identifies a distinct set of enhancers. GATA- driving cardiac gene expression and use this principle to show that chromatin co-occupancy by multiple TFs identifies enhancers binding protein 4 (GATA4), NK2 transcription factor-related, lo- with cardiac activity in vivo. The majority of these multiple TF- cus 5 (NKX2-5), T-box 5 (TBX5), serum response factor (SRF), and “ binding loci (MTL) enhancers were distinct from p300-bound myocyte-enhancer factor 2A (MEF2A), here referred to as cardiac enhancers in location and functional properties. -
Epigenome-Wide Study Identified Methylation Sites Associated With
nutrients Article Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity Majid Nikpay 1,*, Sepehr Ravati 2, Robert Dent 3 and Ruth McPherson 1,4,* 1 Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, 40 Ruskin St–H4208, Ottawa, ON K1Y 4W7, Canada 2 Plastenor Technologies Company, Montreal, QC H2P 2G4, Canada; [email protected] 3 Department of Medicine, Division of Endocrinology, University of Ottawa, the Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada; [email protected] 4 Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada * Correspondence: [email protected] (M.N.); [email protected] (R.M.) Abstract: Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 Citation: Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. -
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 -
Human Lectins, Their Carbohydrate Affinities and Where to Find Them
biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body. -
Early Growth Response 1 Regulates Hematopoietic Support and Proliferation in Human Primary Bone Marrow Stromal Cells
Hematopoiesis SUPPLEMENTARY APPENDIX Early growth response 1 regulates hematopoietic support and proliferation in human primary bone marrow stromal cells Hongzhe Li, 1,2 Hooi-Ching Lim, 1,2 Dimitra Zacharaki, 1,2 Xiaojie Xian, 2,3 Keane J.G. Kenswil, 4 Sandro Bräunig, 1,2 Marc H.G.P. Raaijmakers, 4 Niels-Bjarne Woods, 2,3 Jenny Hansson, 1,2 and Stefan Scheding 1,2,5 1Division of Molecular Hematology, Department of Laboratory Medicine, Lund University, Lund, Sweden; 2Lund Stem Cell Center, Depart - ment of Laboratory Medicine, Lund University, Lund, Sweden; 3Division of Molecular Medicine and Gene Therapy, Department of Labora - tory Medicine, Lund University, Lund, Sweden; 4Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands and 5Department of Hematology, Skåne University Hospital Lund, Skåne, Sweden ©2020 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2019.216648 Received: January 14, 2019. Accepted: July 19, 2019. Pre-published: August 1, 2019. Correspondence: STEFAN SCHEDING - [email protected] Li et al.: Supplemental data 1. Supplemental Materials and Methods BM-MNC isolation Bone marrow mononuclear cells (BM-MNC) from BM aspiration samples were isolated by density gradient centrifugation (LSM 1077 Lymphocyte, PAA, Pasching, Austria) either with or without prior incubation with RosetteSep Human Mesenchymal Stem Cell Enrichment Cocktail (STEMCELL Technologies, Vancouver, Canada) for lineage depletion (CD3, CD14, CD19, CD38, CD66b, glycophorin A). BM-MNCs from fetal long bones and adult hip bones were isolated as reported previously 1 by gently crushing bones (femora, tibiae, fibulae, humeri, radii and ulna) in PBS+0.5% FCS subsequent passing of the cell suspension through a 40-µm filter. -
High-Throughput Bioinformatics Approaches to Understand Gene Expression Regulation in Head and Neck Tumors
High-throughput bioinformatics approaches to understand gene expression regulation in head and neck tumors by Yanxiao Zhang A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2016 Doctoral Committee: Associate Professor Maureen A. Sartor, Chair Professor Thomas E. Carey Assistant Professor Hui Jiang Professor Ronald J. Koenig Associate Professor Laura M. Rozek Professor Kerby A. Shedden c Yanxiao Zhang 2016 All Rights Reserved I dedicate this thesis to my family. For their unfailing love, understanding and support. ii ACKNOWLEDGEMENTS I would like to express my gratitude to Dr. Maureen Sartor for her guidance in my research and career development. She is a great mentor. She patiently taught me when I started new in this field, granted me freedom to explore and helped me out when I got lost. Her dedication to work, enthusiasm in teaching, mentoring and communicating science have inspired me to feel the excite- ment of research beyond novel scientific discoveries. I’m also grateful to have an interdisciplinary committee. Their feedback on my research progress and presentation skills is very valuable. In particular, I would like to thank Dr. Thomas Carey and Dr. Laura Rozek for insightful discussions on the biology of head and neck cancers and human papillomavirus, Dr. Ronald Koenig for expert knowledge on thyroid cancers, Dr. Hui Jiang and Dr. Kerby Shedden for feedback on the statistics part of my thesis. I would like to thank all the past and current members of Sartor lab for making the lab such a lovely place to stay and work in. -
Gene Expression Responses to DNA Damage Are Altered in Human Aging and in Werner Syndrome
Oncogene (2005) 24, 5026–5042 & 2005 Nature Publishing Group All rights reserved 0950-9232/05 $30.00 www.nature.com/onc Gene expression responses to DNA damage are altered in human aging and in Werner Syndrome Kasper J Kyng1,2, Alfred May1, Tinna Stevnsner2, Kevin G Becker3, Steen Klvra˚ 4 and Vilhelm A Bohr*,1 1Laboratory of Molecular Gerontology, National Institute on Aging, National Institutes of Health, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA; 2Danish Center for Molecular Gerontology, Department of Molecular Biology, University of Aarhus, DK-8000 Aarhus C, Denmark; 3Gene Expression and Genomics Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA; 4Institute for Human Genetics, University of Aarhus, Denmark The accumulation of DNA damage and mutations is syndromes, caused by heritable mutations inactivating considered a major cause of cancer and aging. While it is proteins that sense or repair DNA damage, which known that DNA damage can affect changes in gene accelerate some but not all signs of normal aging (Hasty expression, transcriptional regulation after DNA damage et al., 2003). Age is associated withan increase in is poorly understood. We characterized the expression of susceptibility to various forms of stress, and sporadic 6912 genes in human primary fibroblasts after exposure to reports suggest that an age-related decrease in DNA three different kinds of cellular stress that introduces repair may increase the susceptibility of cells to agents DNA damage: 4-nitroquinoline-1-oxide (4NQO), c-irra- causing DNA damage. Reduced base excision repair has diation, or UV-irradiation. Each type of stress elicited been demonstrated in nuclear extracts from aged human damage specific gene expression changes of up to 10-fold. -
SUPPLEMENTARY DATA Supplementary Table 1. Top Ten
SUPPLEMENTARY DATA Supplementary Table 1. Top ten most highly expressed protein-coding genes in the EndoC-βH1 cell line. Expression levels provided for non-mitochondrial genes in EndoC-βH1 and the corresponding expression levels in sorted primary human β-cells (1). Ensembl gene ID Gene Name EndoC-βH1 [RPKM] Primary β cells [RPKM] ENSG00000254647.2 INS 8012.452 166347.111 ENSG00000087086.9 FTL 3090.7454 2066.464 ENSG00000100604.8 CHGA 2853.107 1113.162 ENSG00000099194.5 SCD 1411.631 238.714 ENSG00000118271.5 TTR 1312.8928 1488.996 ENSG00000184009.5 ACTG1 1108.0277 839.681 ENSG00000124172.5 ATP5E 863.42334 254.779 ENSG00000156508.13 EEF1A1 831.17316 637.281 ENSG00000112972.10 HMGCS1 719.7504 22.104 ENSG00000167552.9 TUBA1A 689.1415 511.699 ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0361/-/DC1 SUPPLEMENTARY DATA Supplementary Table 2. List of genes selected for inclusion in the primary screen. Expression levels in EndoC-βH1 and sorted primary human β-cells are shown for all genes targeted for silencing in the primary screen, ordered by locus association (1). For gene selection, the following criteria were applied: we first considered (1) all protein-coding genes within 1 Mb of a type 2 diabetes association signal that (2) had non-zero expression (RPKM > 0) in both EndoC-βH1 and primary human β-cells. Previous studies have shown cis-eQTLs to form a relatively tight, symmetrical distribution around the target-gene transcription start site, and a 1 Mb cut-off is thus likely to capture most effector transcripts subject to cis regulation (2-5). -
Investigation of Adiposity Phenotypes in AA Associated with GALNT10 & Related Pathway Genes
Investigation of Adiposity Phenotypes in AA Associated With GALNT10 & Related Pathway Genes By Mary E. Stromberg A Dissertation Submitted to the Graduate Faculty of WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY In Molecular Genetics and Genomics December 2018 Winston-Salem, North Carolina Approved by: Donald W. Bowden, Ph.D., Advisor Maggie C.Y. Ng, Ph.D., Advisor Timothy D. Howard, Ph.D., Chair Swapan Das, Ph.D. John P. Parks, Ph.D. Acknowledgements I would first like to thank my mentors, Dr. Bowden and Dr. Ng, for guiding my learning and growth during my years at Wake Forest University School of Medicine. Thank you Dr. Ng for spending so much time ensuring that I learn every detail of every protocol, and supporting me through personal difficulties over the years. Thank you Dr. Bowden for your guidance in making me a better scientist and person. I would like to thank my committee for their patience and the countless meetings we have had in discussing this project. I would like to say thank you to the members of our lab as well as the Parks lab for their support and friendship as well as their contributions to my project. Special thanks to Dean Godwin for his support and understanding. The umbrella program here at WFU has given me the chance to meet some of the best friends I could have wished for. I would like to also thank those who have taught me along the way and helped me to get to this point of my life, with special thanks to the late Dr.