Differential Pax5 Levels Promote Mcl Dispersal and Progression and Predict a Poor Prognosis in Advanced Mcl Patients
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
PAX5 Expression in Acute Leukemias: Higher B-Lineage Specificity Than Cd79a and Selective Association with T(8;21)-Acute Myelogenous Leukemia
[CANCER RESEARCH 64, 7399–7404, October 15, 2004] PAX5 Expression in Acute Leukemias: Higher B-Lineage Specificity Than CD79a and Selective Association with t(8;21)-Acute Myelogenous Leukemia Enrico Tiacci,1 Stefano Pileri,2 Annette Orleth,1 Roberta Pacini,1 Alessia Tabarrini,1 Federica Frenguelli,1 Arcangelo Liso,3 Daniela Diverio,4 Francesco Lo-Coco,5 and Brunangelo Falini1 1Institutes of Hematology and Internal Medicine, University of Perugia, Perugia, Italy; 2Unit of Hematopathology, University of Bologne, Bologne, Italy; 3Section of Hematology, University of Foggia, Foggia, Italy; 4Department of Cellular Biotechnologies and Hematology, University La Sapienza of Rome, Rome, Italy; and 5Department of Biopathology, University Tor Vergata of Rome, Rome, Italy ABSTRACT (13, 16). PAX5 expression also occurs in the adult testis and in the mesencephalon and spinal cord during embryogenesis (17), suggesting an The transcription factor PAX5 plays a key role in the commitment of important role in the development of these tissues. hematopoietic precursors to the B-cell lineage, but its expression in acute Rearrangement of the PAX5 gene through reciprocal chromosomal leukemias has not been thoroughly investigated. Hereby, we analyzed routine biopsies from 360 acute leukemias of lymphoid (ALLs) and mye- translocations has been described in different types of B-cell malig- loid (AMLs) origin with a specific anti-PAX5 monoclonal antibody. Blasts nancies (18–23), and, more recently, PAX5 has also been shown to be from 150 B-cell ALLs showed strong PAX5 nuclear expression, paralleling targeted by aberrant hypermutation in Ͼ50% of diffuse large B-cell that of CD79a in the cytoplasm. Conversely, PAX5 was not detected in 50 lymphomas (24). -
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. -
Further Delineation of Chromosomal Consensus Regions in Primary
Leukemia (2007) 21, 2463–2469 & 2007 Nature Publishing Group All rights reserved 0887-6924/07 $30.00 www.nature.com/leu ORIGINAL ARTICLE Further delineation of chromosomal consensus regions in primary mediastinal B-cell lymphomas: an analysis of 37 tumor samples using high-resolution genomic profiling (array-CGH) S Wessendorf1,6, TFE Barth2,6, A Viardot1, A Mueller3, HA Kestler3, H Kohlhammer1, P Lichter4, M Bentz5,HDo¨hner1,PMo¨ller2 and C Schwaenen1 1Klinik fu¨r Innere Medizin III, Zentrum fu¨r Innere Medizin der Universita¨t Ulm, Ulm, Germany; 2Institut fu¨r Pathologie, Universita¨t Ulm, Ulm, Germany; 3Forschungsdozentur Bioinformatik, Universita¨t Ulm, Ulm, Germany; 4Abt. Molekulare Genetik, Deutsches Krebsforschungszentrum, Heidelberg, Germany and 5Sta¨dtisches Klinikum Karlsruhe, Karlsruhe, Germany Primary mediastinal B-cell lymphoma (PMBL) is an aggressive the expression of BSAP, BOB1, OCT2, PAX5 and PU1 was extranodal B-cell non-Hodgkin’s lymphoma with specific clin- added to the spectrum typical of PMBL features.9 ical, histopathological and genomic features. To characterize Genetically, a pattern of highly recurrent karyotype alterations further the genotype of PMBL, we analyzed 37 tumor samples and PMBL cell lines Med-B1 and Karpas1106P using array- with the hallmark of chromosomal gains of the subtelomeric based comparative genomic hybridization (matrix- or array- region of chromosome 9 supported the concept of a unique CGH) to a 2.8k genomic microarray. Due to a higher genomic disease entity that distinguishes PMBL from other B-cell non- resolution, we identified altered chromosomal regions in much Hodgkin’s lymphomas.10,11 Together with less specific gains on higher frequencies compared with standard CGH: for example, 2p15 and frequent mutations of the SOCS1 gene, a notable þ 9p24 (68%), þ 2p15 (51%), þ 7q22 (32%), þ 9q34 (32%), genomic similarity to classical Hodgkin’s lymphoma was þ 11q23 (18%), þ 12q (30%) and þ 18q21 (24%). -
Genomic Profiling of Adult Acute Lymphoblastic Leukemia by Single
SUPPLEMENTARY APPENDIX Genomic profiling of adult acute lymphoblastic leukemia by single nucleotide polymorphism oligonucleotide microarray and comparison to pediatric acute lymphoblastic leukemia Ryoko Okamoto,1 Seishi Ogawa,2 Daniel Nowak,1 Norihiko Kawamata,1 Tadayuki Akagi,1,3 Motohiro Kato,2 Masashi Sanada,2 Tamara Weiss,4 Claudia Haferlach,4 Martin Dugas,5 Christian Ruckert,5 Torsten Haferlach,4 and H. Phillip Koeffler1,6 1Division of Hematology and Oncology, Cedars-Sinai Medical Center, UCLA School of Medicine, Los Angeles, CA, USA; 2Cancer Genomics Project, Graduate School of Medicine, University of Tokyo, Tokyo, Japan; 3Department of Stem Cell Biology, Graduate School of Medical Science, Kanazawa University 4MLL Munich Leukemia Laboratory, Munich, Germany; 5Department of Medical Informatics and Biomathematics, University of Münster, Münster, Germany; 6Cancer Science Institute of Singapore, National University of Singapore, Singapore Citation: Okamoto R, Ogawa S, Nowak D, Kawamata N, Akagi T, Kato M, Sanada M, Weiss T, Haferlach C, Dugas M, Ruckert C, Haferlach T, and Koeffler HP. Genomic profiling of adult acute lymphoblastic leukemia by single nucleotide polymorphism oligonu- cleotide microarray and comparison to pediatric acute lymphoblastic leukemia. Haematologica 2010;95(9):1481-1488. doi:10.3324/haematol.2009.011114 Online Supplementary Data ed by PCR of genomic DNA and subsequent direct sequencing of SNP in a region of CNN-LOH in an ALL sample versus the corresponding Design and Methods matched normal sample (Online Supplementary -
A PAX5-OCT4-PRDM1 Developmental Switch Specifies Human Primordial Germ Cells
A PAX5-OCT4-PRDM1 Developmental Switch Specifies Human Primordial Germ Cells Fang Fang1,2, Benjamin Angulo1,2, Ninuo Xia1,2, Meena Sukhwani3, Zhengyuan Wang4, Charles C Carey5, Aurélien Mazurie5, Jun Cui1,2, Royce Wilkinson5, Blake Wiedenheft5, Naoko Irie6, M. Azim Surani6, Kyle E Orwig3, Renee A Reijo Pera1,2 1Department of Cell Biology and Neurosciences, Montana State University, Bozeman, MT 59717, USA 2Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59717, USA 3Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, School of Medicine; Magee Women’s Research Institute, Pittsburgh, PA, 15213, USA 4Genomic Medicine Division, Hematology Branch, NHLBI/NIH, MD 20850, USA 5Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA. 6Wellcome Trust Cancer Research UK Gurdon Institute, Tennis Court Road, University of Cambridge, Cambridge CB2 1QN, UK. Correspondence should be addressed to F.F. (e-mail: [email protected]) 1 Abstract Dysregulation of genetic pathways during human germ cell development leads to infertility. Here, we analyzed bona fide human primordial germ cells (hPGCs) to probe the developmental genetics of human germ cell specification and differentiation. We examined distribution of OCT4 occupancy in hPGCs relative to human embryonic stem cells (hESCs). We demonstrate that development, from pluripotent stem cells to germ cells, is driven by switching partners with OCT4 from SOX2 to PAX5 and PRDM1. Gain- and loss-of-function studies revealed that PAX5 encodes a critical regulator of hPGC development. Moreover, analysis of epistasis indicates that PAX5 acts upstream of OCT4 and PRDM1. The PAX5-OCT4-PRDM1 proteins form a core transcriptional network that activates germline and represses somatic programs during human germ cell differentiation. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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 The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. -
Supplementary Data
SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche). -
Proteogenomic Analysis of Inhibitor of Differentiation 4 (ID4) in Basal-Like Breast Cancer Laura A
Baker et al. Breast Cancer Research (2020) 22:63 https://doi.org/10.1186/s13058-020-01306-6 RESEARCH ARTICLE Open Access Proteogenomic analysis of Inhibitor of Differentiation 4 (ID4) in basal-like breast cancer Laura A. Baker1,2, Holly Holliday1,2†, Daniel Roden1,2†, Christoph Krisp3,4†, Sunny Z. Wu1,2, Simon Junankar1,2, Aurelien A. Serandour5, Hisham Mohammed5, Radhika Nair6, Geetha Sankaranarayanan5, Andrew M. K. Law1,2, Andrea McFarland1, Peter T. Simpson7, Sunil Lakhani7,8, Eoin Dodson1,2, Christina Selinger9, Lyndal Anderson9,10, Goli Samimi11, Neville F. Hacker12, Elgene Lim1,2, Christopher J. Ormandy1,2, Matthew J. Naylor13, Kaylene Simpson14,15, Iva Nikolic14, Sandra O’Toole1,2,9,10, Warren Kaplan1, Mark J. Cowley1,2, Jason S. Carroll5, Mark Molloy3 and Alexander Swarbrick1,2* Abstract Background: Basal-like breast cancer (BLBC) is a poorly characterised, heterogeneous disease. Patients are diagnosed with aggressive, high-grade tumours and often relapse with chemotherapy resistance. Detailed understanding of the molecular underpinnings of this disease is essential to the development of personalised therapeutic strategies. Inhibitor of differentiation 4 (ID4) is a helix-loop-helix transcriptional regulator required for mammary gland development. ID4 is overexpressed in a subset of BLBC patients, associating with a stem-like poor prognosis phenotype, and is necessary for the growth of cell line models of BLBC through unknown mechanisms. Methods: Here, we have defined unique molecular insights into the function of ID4 in BLBC and the related disease high-grade serous ovarian cancer (HGSOC), by combining RIME proteomic analysis, ChIP-seq mapping of genomic binding sites and RNA-seq. -
Cytoplasmic E2f4 Forms Organizing Centres for Initiation of Centriole Amplification During Multiciliogenesis
ARTICLE Received 13 Feb 2017 | Accepted 8 May 2017 | Published 4 Jul 2017 DOI: 10.1038/ncomms15857 OPEN Cytoplasmic E2f4 forms organizing centres for initiation of centriole amplification during multiciliogenesis Munemasa Mori1, Renin Hazan2, Paul S. Danielian2, John E. Mahoney1,w, Huijun Li1, Jining Lu1, Emily S. Miller2, Xueliang Zhu3, Jacqueline A. Lees2 & Wellington V. Cardoso1 Abnormal development of multiciliated cells is a hallmark of a variety of human conditions associated with chronic airway diseases, hydrocephalus and infertility. Multiciliogenesis requires both activation of a specialized transcriptional program and assembly of cytoplasmic structures for large-scale centriole amplification that generates basal bodies. It remains unclear, however, what mechanism initiates formation of these multiprotein complexes in epithelial progenitors. Here we show that this is triggered by nucleocytoplasmic translocation of the transcription factor E2f4. After inducing a transcriptional program of centriole biogenesis, E2f4 forms apical cytoplasmic organizing centres for assembly and nucleation of deuterosomes. Using genetically altered mice and E2F4 mutant proteins we demonstrate that centriole amplification is crucially dependent on these organizing centres and that, without cytoplasmic E2f4, deuterosomes are not assembled, halting multiciliogenesis. Thus, E2f4 integrates nuclear and previously unsuspected cytoplasmic events of centriole amplification, providing new perspectives for the understanding of normal ciliogenesis, ciliopathies and cancer. 1 Columbia Center for Human Development, Department of Medicine, Pulmonary Allergy Critical Care, Columbia University Medical Center, New York City, New York 10032, USA. 2 David H. Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts 02139, USA. 3 State Key Laboratory of Cell Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China. -
Repressing the Repressor: Fra1 Controls Plasma Cell Generation
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 6, No. 20 Editorial Repressing the repressor: Fra1 controls plasma cell generation Dirk Mielenz , Bettina Grötsch and Jean-Pierre David B cell differentiation from the early commitment become quickly up-regulated upon B cell activation [5]. into the B lymphoid lineage in the bone marrow up In addition, c-Fos had been shown to promote Blimp1 to the differentiation into antibody secreting plasma expression [6]. However, the physiological relevance cells is tightly controlled by a transcriptional program of these observations was not demonstrated in vivo. We dominated by a cascade of repression. Indeed, each recently showed by gain and loss of function experiments step of B cell differentiation to mature B cells appears that Fra1 enhances activation induced cell death (AICD) to depend on transcription factors that, in addition to upon its induction in activated B cells, and as well limits promoting differentiation, repress key determinants of B cell proliferation [7]. Moreover, transgenic over- other hematopoietic lineages or even key regulators of expression of Fra1 blocks plasma cell differentiation the next or previous steps of B cell differentiation. For and immunoglobulin production in vitro and in vivo. instance, Pax5 that is required for early B cell commitment In accordance, mice with B cell-specific deletion of and maintenance of B cell identity acts by repressing the Fra1 show enhanced plasma cell differentiation in vitro differentiation of lymphoid precursor cells into the other and in vivo as well as exacerbated antibody responses. hematopoietic lineages [1]. Globally, key transcriptional Interestingly, transgenic Bcl2 overexpression alleviated regulators of B cell identity such as Pax5, Bcl6 or Bach2, Fra1 elicited AICD and corrected the B cell proliferation all inhibit the generation of antibody secreting plasma defect.