RB and Cell Cycle Progression
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
DNA Damage Checkpoint Dynamics Drive Cell Cycle Phase Transitions
bioRxiv preprint doi: https://doi.org/10.1101/137307; this version posted August 4, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. DNA damage checkpoint dynamics drive cell cycle phase transitions Hui Xiao Chao1,2, Cere E. Poovey1, Ashley A. Privette1, Gavin D. Grant3,4, Hui Yan Chao1, Jeanette G. Cook3,4, and Jeremy E. Purvis1,2,4,† 1Department of Genetics 2Curriculum for Bioinformatics and Computational Biology 3Department of Biochemistry and Biophysics 4Lineberger Comprehensive Cancer Center University of North Carolina, Chapel Hill 120 Mason Farm Road Chapel Hill, NC 27599-7264 †Corresponding Author: Jeremy Purvis Genetic Medicine Building 5061, CB#7264 120 Mason Farm Road Chapel Hill, NC 27599-7264 [email protected] ABSTRACT DNA damage checkpoints are cellular mechanisms that protect the integrity of the genome during cell cycle progression. In response to genotoxic stress, these checkpoints halt cell cycle progression until the damage is repaired, allowing cells enough time to recover from damage before resuming normal proliferation. Here, we investigate the temporal dynamics of DNA damage checkpoints in individual proliferating cells by observing cell cycle phase transitions following acute DNA damage. We find that in gap phases (G1 and G2), DNA damage triggers an abrupt halt to cell cycle progression in which the duration of arrest correlates with the severity of damage. However, cells that have already progressed beyond a proposed “commitment point” within a given cell cycle phase readily transition to the next phase, revealing a relaxation of checkpoint stringency during later stages of certain cell cycle phases. -
Specific Functions of the Wnt Signaling System in Gene Regulatory Networks
Specific functions of the Wnt signaling system in PNAS PLUS gene regulatory networks throughout the early sea urchin embryo Miao Cui, Natnaree Siriwon1, Enhu Li2, Eric H. Davidson3, and Isabelle S. Peter3 Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 Contributed by Eric H. Davidson, October 9, 2014 (sent for review September 12, 2014; reviewed by Robert D. Burke and Randall T. Moon) Wnt signaling affects cell-fate specification processes throughout Fig. 1A. Cells located at the vegetal pole will become skeleto- embryonic development. Here we take advantage of the well-studied genic mesodermal cells. These cells are surrounded by the veg2 gene regulatory networks (GRNs) that control pregastrular sea urchin cell lineage. This lineage consists of veg2 mesodermal cells, lo- embryogenesis to reveal the gene regulatory functions of the entire cated adjacent to skeletogenic cells and giving rise to all other Wnt-signaling system. Five wnt genes, three frizzled genes, two se- mesodermal cell fates such as esophageal muscle cells, blasto- creted frizzled-related protein 1 genes, and two Dickkopf genes are coelar cells, and pigment cells, and of veg2 endoderm cells, expressed in dynamic spatial patterns in the pregastrular embryo of which will form the foregut and parts of the midgut. At a further Strongylocentrotus purpuratus. We present a comprehensive analysis distance from the vegetal pole, but still within the vegetal half of of these genes in each embryonic domain. Total functions of the the embryo, is the veg1 lineage, consisting of veg1 endoderm, Wnt-signaling system in regulatory gene expression throughout the located adjacent to veg2 endoderm and giving rise to the other embryo were studied by use of the Porcupine inhibitor C59, which parts of the midgut and the hindgut, and of veg1 ectoderm, the interferes with zygotic Wnt ligand secretion. -
G2 Phase Cell Cycle Regulation by E2F4 Following Genotoxic Stress
G2 Phase Cell Cycle Regulation by E2F4 Following Genotoxic Stress by MEREDITH ELLEN CROSBY Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Thesis Advisor: Dr. Alex Almasan Department of Environmental Health Sciences CASE WESTERN RESERVE UNIVERSITY May, 2006 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the dissertation of ______________________________________________________ candidate for the Ph.D. degree *. (signed)_______________________________________________ (chair of the committee) ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ (date) _______________________ *We also certify that written approval has been obtained for any proprietary material contained therein. TABLE OF CONTENTS TABLE OF CONTENTS………………………………………………………………….1 LIST OF FIGURES……………………………………………………………………….5 LIST OF TABLES………………………………………………………………………...7 ACKNOWLEDGEMENTS……………………………………………………………….8 LIST OF ABBREVIATIONS……………………………………………………………10 ABSTRACT……………………………………………………………………………...15 CHAPTER 1. INTRODUCTION 1.1. CELL CYCLE REGULATION: HISTORICAL OVERVIEW………………...17 1.2. THE E2F FAMILY OF TRANSCRIPTION FACTORS……………………….22 1.3. E2F AND CELL CYCLE CONTROL 1.3.1. G0/G1 Phase Transition………………………………………………….28 1.3.2. S Phase…………………………………………………………………...28 1.3.3. G2/M Phase Transition…………………………………………………..30 1.4. -
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. -
Cyclin-Dependent Kinases and P53 Pathways Are Activated Independently and Mediate Bax Activation in Neurons After DNA Damage
The Journal of Neuroscience, July 15, 2001, 21(14):5017–5026 Cyclin-Dependent Kinases and P53 Pathways Are Activated Independently and Mediate Bax Activation in Neurons after DNA Damage Erick J. Morris,1 Elizabeth Keramaris,2 Hardy J. Rideout,3 Ruth S. Slack,2 Nicholas J. Dyson,1 Leonidas Stefanis,3 and David S. Park2 1Massachusetts General Hospital Cancer Center, Laboratory of Molecular Oncology, Charlestown, Massachusetts 02129, 2Neuroscience Research Institute, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada, and 3Columbia University, New York, New York 10032 DNA damage has been implicated as one important initiator of ization, and DNA binding that result from DNA damage are not cell death in neuropathological conditions such as stroke. Ac- affected by the inhibition of CDK activity. Conversely, no de- cordingly, it is important to understand the signaling processes crease in retinoblastoma protein (pRb) phosphorylation was that control neuronal death induced by this stimulus. Previous observed in p53-deficient neurons that were treated with camp- evidence has shown that the death of embryonic cortical neu- tothecin. However, either p53 deficiency or the inhibition of rons treated with the DNA-damaging agent camptothecin is CDK activity alone inhibited Bax translocation, cytochrome c dependent on the tumor suppressor p53 and cyclin-dependent release, and caspase-3-like activation. Taken together, our re- kinase (CDK) activity and that the inhibition of either pathway sults indicate that p53 and CDK are activated independently alone leads to enhanced and prolonged survival. We presently and then act in concert to control Bax-mediated apoptosis. show that p53 and CDKs are activated independently on par- allel pathways. -
Ret Oncogene and Thyroid Carcinoma
ndrom Sy es tic & e G n e e n G e f T o Elisei et al., J Genet Syndr Gene Ther 2014, 5:1 Journal of Genetic Syndromes h l e a r n a DOI: 10.4172/2157-7412.1000214 r p u y o J & Gene Therapy ISSN: 2157-7412 Review Article Open Access Ret Oncogene and Thyroid Carcinoma Elisei R, Molinaro E, Agate L, Bottici V, Viola D, Biagini A, Matrone A, Tacito A, Ciampi R, Vivaldi A and Romei C* Endocrine Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy Abstract Thyroid cancer is a malignant neoplasm that originates from follicular or parafollicular thyroid cells and is categorized as papillary (PTC), follicular (FTC), anaplastic (ATC) or medullary thyroid carcinoma (MTC). The alteration of the Rearranged during trasfection (RET) (proto-oncogene, a gene coding for a tyrosine-kinase receptor involved in the control of cell differentiation and proliferation, has been found to cause PTC and MTC. In particular, RET/PTC rearrangements and RET point mutations are related to PTC and MTC, respectively. Although RET/PTC rearrangements have been identified in both spontaneous and radiation-induced PTC, they occur more frequently in radiation-associated tumors. RET/PTC rearrangements have also been reported in follicular adenomas. Although controversial, correlations between RET/PTC rearrangements, especially RET/PTC3, and a more aggressive phenotype and a more advanced stage have been identified. Germline point mutations in the RET proto-oncogene are associated with nearly all cases of hereditary MTC, and a strict correlation between genotype and phenotype has been demonstrated. -
A Gain-Of-Function P53-Mutant Oncogene Promotes Cell Fate Plasticity and Myeloid Leukemia Through the Pluripotency Factor FOXH1
Published OnlineFirst May 8, 2019; DOI: 10.1158/2159-8290.CD-18-1391 RESEARCH ARTICLE A Gain-of-Function p53-Mutant Oncogene Promotes Cell Fate Plasticity and Myeloid Leukemia through the Pluripotency Factor FOXH1 Evangelia Loizou1,2, Ana Banito1, Geulah Livshits1, Yu-Jui Ho1, Richard P. Koche3, Francisco J. Sánchez-Rivera1, Allison Mayle1, Chi-Chao Chen1, Savvas Kinalis4, Frederik O. Bagger4,5, Edward R. Kastenhuber1,6, Benjamin H. Durham7, and Scott W. Lowe1,8 Downloaded from cancerdiscovery.aacrjournals.org on September 27, 2021. © 2019 American Association for Cancer Research. Published OnlineFirst May 8, 2019; DOI: 10.1158/2159-8290.CD-18-1391 ABSTRACT Mutations in the TP53 tumor suppressor gene are common in many cancer types, including the acute myeloid leukemia (AML) subtype known as complex karyotype AML (CK-AML). Here, we identify a gain-of-function (GOF) Trp53 mutation that accelerates CK-AML initiation beyond p53 loss and, surprisingly, is required for disease maintenance. The Trp53 R172H muta- tion (TP53 R175H in humans) exhibits a neomorphic function by promoting aberrant self-renewal in leu- kemic cells, a phenotype that is present in hematopoietic stem and progenitor cells (HSPC) even prior to their transformation. We identify FOXH1 as a critical mediator of mutant p53 function that binds to and regulates stem cell–associated genes and transcriptional programs. Our results identify a context where mutant p53 acts as a bona fi de oncogene that contributes to the pathogenesis of CK-AML and suggests a common biological theme for TP53 GOF in cancer. SIGNIFICANCE: Our study demonstrates how a GOF p53 mutant can hijack an embryonic transcrip- tion factor to promote aberrant self-renewal. -
Mitosis Vs. Meiosis
Mitosis vs. Meiosis In order for organisms to continue growing and/or replace cells that are dead or beyond repair, cells must replicate, or make identical copies of themselves. In order to do this and maintain the proper number of chromosomes, the cells of eukaryotes must undergo mitosis to divide up their DNA. The dividing of the DNA ensures that both the “old” cell (parent cell) and the “new” cells (daughter cells) have the same genetic makeup and both will be diploid, or containing the same number of chromosomes as the parent cell. For reproduction of an organism to occur, the original parent cell will undergo Meiosis to create 4 new daughter cells with a slightly different genetic makeup in order to ensure genetic diversity when fertilization occurs. The four daughter cells will be haploid, or containing half the number of chromosomes as the parent cell. The difference between the two processes is that mitosis occurs in non-reproductive cells, or somatic cells, and meiosis occurs in the cells that participate in sexual reproduction, or germ cells. The Somatic Cell Cycle (Mitosis) The somatic cell cycle consists of 3 phases: interphase, m phase, and cytokinesis. 1. Interphase: Interphase is considered the non-dividing phase of the cell cycle. It is not a part of the actual process of mitosis, but it readies the cell for mitosis. It is made up of 3 sub-phases: • G1 Phase: In G1, the cell is growing. In most organisms, the majority of the cell’s life span is spent in G1. • S Phase: In each human somatic cell, there are 23 pairs of chromosomes; one chromosome comes from the mother and one comes from the father. -
The Involvement of Ubiquitination Machinery in Cell Cycle Regulation and Cancer Progression
International Journal of Molecular Sciences Review The Involvement of Ubiquitination Machinery in Cell Cycle Regulation and Cancer Progression Tingting Zou and Zhenghong Lin * School of Life Sciences, Chongqing University, Chongqing 401331, China; [email protected] * Correspondence: [email protected] Abstract: The cell cycle is a collection of events by which cellular components such as genetic materials and cytoplasmic components are accurately divided into two daughter cells. The cell cycle transition is primarily driven by the activation of cyclin-dependent kinases (CDKs), which activities are regulated by the ubiquitin-mediated proteolysis of key regulators such as cyclins, CDK inhibitors (CKIs), other kinases and phosphatases. Thus, the ubiquitin-proteasome system (UPS) plays a pivotal role in the regulation of the cell cycle progression via recognition, interaction, and ubiquitination or deubiquitination of key proteins. The illegitimate degradation of tumor suppressor or abnormally high accumulation of oncoproteins often results in deregulation of cell proliferation, genomic instability, and cancer occurrence. In this review, we demonstrate the diversity and complexity of the regulation of UPS machinery of the cell cycle. A profound understanding of the ubiquitination machinery will provide new insights into the regulation of the cell cycle transition, cancer treatment, and the development of anti-cancer drugs. Keywords: cell cycle regulation; CDKs; cyclins; CKIs; UPS; E3 ubiquitin ligases; Deubiquitinases (DUBs) Citation: Zou, T.; Lin, Z. The Involvement of Ubiquitination Machinery in Cell Cycle Regulation and Cancer Progression. 1. Introduction Int. J. Mol. Sci. 2021, 22, 5754. https://doi.org/10.3390/ijms22115754 The cell cycle is a ubiquitous, complex, and highly regulated process that is involved in the sequential events during which a cell duplicates its genetic materials, grows, and di- Academic Editors: Kwang-Hyun Bae vides into two daughter cells. -
The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells. -
Animal Cells Anterior Epidermis Anterior Epidermis A-Neural
Anterior Epidermis Anterior Epidermis KH2012 TF common name Log2FC -Log(pvalue) Log2FC -Log(pvalue) DE in Imai Matched PWM PWM Cluster KH2012 TF common name Log2FC -Log(pvalue) Log2FC -Log(pvalue) DE in Imai Matched PWM PWM Cluster gene model Sibling Cluster Sibling Cluster Parent Cluster Parent Cluster z-score z-score gene model Sibling Cluster Sibling Cluster Parent Cluster Parent Cluster z-score z-score KH2012:KH.C11.485 Irx-B 1.0982 127.5106 0.9210 342.5323 Yes No PWM Hits No PWM Hits KH2012:KH.C1.159 E(spl)/hairy-a 1.3445 65.6302 0.6908 14.3413 Not Analyzed -15.2125 No PWM Hits KH2012:KH.L39.1 FoxH-b 0.6677 45.8148 1.1074 185.2909 No -3.3335 5.2695 KH2012:KH.C1.99 SoxB1 1.2482 73.2413 0.3331 9.3534 Not Analyzed No PWM match No PWM match KH2012:KH.C1.159 E(spl)/hairy-a 0.6233 47.2239 0.4339 77.0192 Yes -10.496 No PWM Hits KH2012:KH.C11.485 Irx-B 1.2355 72.8859 0.1608 0.0137 Not Analyzed No PWM Hits No PWM Hits KH2012:KH.C7.43 AP-2-like2 0.4991 31.7939 0.4775 68.8091 Yes 10.551 21.586 KH2012:KH.C1.1016 GCNF 0.8556 36.2030 1.3828 100.1236 Not Analyzed No PWM match No PWM match KH2012:KH.C1.99 SoxB1 0.4913 33.7808 0.3406 39.0890 No No PWM match No PWM match KH2012:KH.L108.4 CREB/ATF-a 0.6859 37.8207 0.3453 15.8154 Not Analyzed 6.405 8.6245 KH2012:KH.C7.157 Emc 0.4139 19.2080 1.1001 173.3024 Yes No PWM match No PWM match KH2012:KH.S164.12 SoxB2 0.6194 22.8414 0.6433 35.7335 Not Analyzed 8.722 17.405 KH2012:KH.C4.366 ERF2 -0.4878 -32.3767 -0.1770 -0.2316 No -10.324 9.7885 KH2012:KH.L4.17 Zinc Finger (C2H2)-18 0.6166 24.8925 0.2386 5.3130