High CENPM Mrna Expression and Its Prognostic Signifcance in Hepatocellular Carcinoma: a Study Based on Data Mining Zeng‑Hong Wu and Dong‑Liang Yang*
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
View the Poster.Pdf
Identifying Novel Associations for Iron-Related Genes in High-Grade Ovarian Cancer Abigail Descoteaux*1, José W. Velázquez*2, Anna Konstorum3, Reinhard Laubenbacher3,4 1Vassar College, 2University of Puerto Rico at Cayey, 3Center for Quantitative Medicine, UConn Health, 4The Jackson Laboratory for Genomic Medicine *These authors contributed equally to this work Introduction Methods Testable Hypothesis § Iron can gain and lose electrons, making it enzymatically Microarray gene expression Adjacency matrix Community detection in a weighted, KEGG pathways Tumor cells promote an inflammatory microenvironment via [1] data from HGSOC clinical • Top 10,000 most variable genes undirected network • Manually curated biological pathways useful in cell replication, metabolism, and growth • Bicor derived from Pearson but • ORA: ask whether any known pathways • Order Statistics Local Optimization Method (OSLOM) recruitment of tumor-associated macrophages, that in turn samples less sensitive to outliers are significantly over-represented in the • Assembled unsupervised with respect to biology by locally § Cancer cells sequester iron by altering the expression of • The Cancer Genome Atlas (TCGA) • Correlation cut-off at 0.45 genes within the community secrete IL4 and CCL4 to promote an iron-influx phenotype in optimizing the statistical significance of clusters and using [1] • Affymetrix HGU133A (n=488) (FDR corrected, α=0.01) Pathway 2 several regulators of iron metabolism (Figure 1) • Tothill et al. [2] this as a fitness score ovarian cancer tumor cells. • • HGU133plus2 (n=217) Accounts for edge weight, overlapping communities, and Pathway 1 hierarchies a. Normal epithelial cell Fe3+ Fe3+ Pathway 3 Tumor-associated 3+ 3+ Tumor cells Fe Fe macrophages Hepcidin (HAMP) samples genes Biweight midcorrelation Over-representation (bicor) Hypothesis CSF1R Ferroportin OSLOM analysis (ORA) CCR1[8] (SLC40A1) generation and [7] genes genes 1. -
Gene Knockdown of CENPA Reduces Sphere Forming Ability and Stemness of Glioblastoma Initiating Cells
Neuroepigenetics 7 (2016) 6–18 Contents lists available at ScienceDirect Neuroepigenetics journal homepage: www.elsevier.com/locate/nepig Gene knockdown of CENPA reduces sphere forming ability and stemness of glioblastoma initiating cells Jinan Behnan a,1, Zanina Grieg b,c,1, Mrinal Joel b,c, Ingunn Ramsness c, Biljana Stangeland a,b,⁎ a Department of Molecular Medicine, Institute of Basic Medical Sciences, The Medical Faculty, University of Oslo, Oslo, Norway b Norwegian Center for Stem Cell Research, Department of Immunology and Transfusion Medicine, Oslo University Hospital, Oslo, Norway c Vilhelm Magnus Laboratory for Neurosurgical Research, Institute for Surgical Research and Department of Neurosurgery, Oslo University Hospital, Oslo, Norway article info abstract Article history: CENPA is a centromere-associated variant of histone H3 implicated in numerous malignancies. However, the Received 20 May 2016 role of this protein in glioblastoma (GBM) has not been demonstrated. GBM is one of the most aggressive Received in revised form 23 July 2016 human cancers. GBM initiating cells (GICs), contained within these tumors are deemed to convey Accepted 2 August 2016 characteristics such as invasiveness and resistance to therapy. Therefore, there is a strong rationale for targeting these cells. We investigated the expression of CENPA and other centromeric proteins (CENPs) in Keywords: fi CENPA GICs, GBM and variety of other cell types and tissues. Bioinformatics analysis identi ed the gene signature: fi Centromeric proteins high_CENP(AEFNM)/low_CENP(BCTQ) whose expression correlated with signi cantly worse GBM patient Glioblastoma survival. GBM Knockdown of CENPA reduced sphere forming ability, proliferation and cell viability of GICs. We also Brain tumor detected significant reduction in the expression of stemness marker SOX2 and the proliferation marker Glioblastoma initiating cells and therapeutic Ki67. -
IL21R Expressing CD14+CD16+ Monocytes Expand in Multiple
Plasma Cell Disorders SUPPLEMENTARY APPENDIX IL21R expressing CD14 +CD16 + monocytes expand in multiple myeloma patients leading to increased osteoclasts Marina Bolzoni, 1 Domenica Ronchetti, 2,3 Paola Storti, 1,4 Gaetano Donofrio, 5 Valentina Marchica, 1,4 Federica Costa, 1 Luca Agnelli, 2,3 Denise Toscani, 1 Rosanna Vescovini, 1 Katia Todoerti, 6 Sabrina Bonomini, 7 Gabriella Sammarelli, 1,7 Andrea Vecchi, 8 Daniela Guasco, 1 Fabrizio Accardi, 1,7 Benedetta Dalla Palma, 1,7 Barbara Gamberi, 9 Carlo Ferrari, 8 Antonino Neri, 2,3 Franco Aversa 1,4,7 and Nicola Giuliani 1,4,7 1Myeloma Unit, Dept. of Medicine and Surgery, University of Parma; 2Dept. of Oncology and Hemato-Oncology, University of Milan; 3Hematology Unit, “Fondazione IRCCS Ca’ Granda”, Ospedale Maggiore Policlinico, Milan; 4CoreLab, University Hospital of Parma; 5Dept. of Medical-Veterinary Science, University of Parma; 6Laboratory of Pre-clinical and Translational Research, IRCCS-CROB, Referral Cancer Center of Basilicata, Rionero in Vulture; 7Hematology and BMT Center, University Hospital of Parma; 8Infectious Disease Unit, University Hospital of Parma and 9“Dip. Oncologico e Tecnologie Avanzate”, IRCCS Arcispedale Santa Maria Nuova, Reggio Emilia, Italy ©2017 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2016.153841 Received: August 5, 2016. Accepted: December 23, 2016. Pre-published: January 5, 2017. Correspondence: [email protected] SUPPLEMENTAL METHODS Immunophenotype of BM CD14+ in patients with monoclonal gammopathies. Briefly, 100 μl of total BM aspirate was incubated in the dark with anti-human HLA-DR-PE (clone L243; BD), anti-human CD14-PerCP-Cy 5.5, anti-human CD16-PE-Cy7 (clone B73.1; BD) and anti-human CD45-APC-H 7 (clone 2D1; BD) for 20 min. -
Research Article the Oncogenic Role of CENPA in Hepatocellular Carcinoma Development: Evidence from Bioinformatic Analysis
Hindawi BioMed Research International Volume 2020, Article ID 3040839, 8 pages https://doi.org/10.1155/2020/3040839 Research Article The Oncogenic Role of CENPA in Hepatocellular Carcinoma Development: Evidence from Bioinformatic Analysis Yuan Zhang ,1 Lei Yang ,2 Jia Shi ,1 Yunfei Lu ,1 Xiaorong Chen ,1 and Zongguo Yang 1 1Department of Integrative Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China 2Department of Acupuncture and Moxibustion, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100007, China Correspondence should be addressed to Xiaorong Chen; [email protected] and Zongguo Yang; [email protected] Received 27 September 2019; Revised 14 March 2020; Accepted 20 March 2020; Published 8 April 2020 Academic Editor: Ali A. Khraibi Copyright © 2020 Yuan Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. This study is aimed at investigating the predictive value of CENPA in hepatocellular carcinoma (HCC) development. Methods. Using integrated bioinformatic analysis, we evaluated the CENPA mRNA expression in tumor and adjacent tissues and correlated it with HCC survival and clinicopathological features. A Cox regression hazard model was also performed. Results. CENPA mRNA was significantly upregulated in tumor tissues compared with that in adjacent tissues, which were validated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (all P <0:01). In the Kaplan-Meier plotter platform, the high level of CENPA mRNA was significantly correlated with overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and progression-free survival (PFS) in HCC patients (all log rank P <0:01). -
Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2. -
Explorative Bioinformatic Analysis of Cardiomyocytes in 2D &3D in Vitro Culture System
EXPLORATIVE BIOINFORMATIC ANALYSIS OF CARDIOMYOCYTES IN 2D &3D IN VITRO CULTURE SYSTEM VERSION 2 Master Degree Project in Bioscience One years Level, 60 ECTS Sruthy Janardanan [email protected] Supervisor: Jane Synnergren [email protected] Examiner: Sanja Jurcevic [email protected] Abstract The in vitro cell culture models of human pluripotent stem cells (hPSC)-derived cardiomyocytes (CMs) have gained a predominant value in the field of drug discovery and is considered an attractive tool for cardiovascular disease modellings. However, despite several reports of different protocols for the hPSC-differentiation into CMs, the development of an efficient, controlled and reproducible 3D differentiation remains challenging. The main aim of this research study was to understand the changes in the gene expression as an impact of spatial orientation of hPSC-derived CMs in 2D(two-dimensional) and 3D(three-dimensional) culture conditions and to identify the topologically important Hub and Hub-Bottleneck proteins using centrality measures to gain new knowledge for standardizing the pre-clinical models for the regeneration of CMs. The above-mentioned aim was achieved through an extensive bioinformatic analysis on the list of differentially expressed genes (DEGs) identified from RNA-sequencing (RNA-Seq). Functional annotation analysis of the DEGs from both 2D and 3D was performed using Cytoscape plug-in ClueGO. Followed by the topological analysis of the protein-protein interaction network (PPIN) using two centrality parameters; Degree and Betweeness in Cytoscape plug-in CenTiScaPe. The results obtained revealed that compared to 2D, DEGs in 3D are primarily associated with cell signalling suggesting the interaction between cells as an impact of the 3D microenvironment and topological analysis revealed 32 and 39 proteins as Hub and Hub-Bottleneck proteins, respectively in 3D indicating the possibility of utilizing those identified genes and their corresponding proteins as cardiac disease biomarkers in future by further research. -
WNT16 Is a New Marker of Senescence
Table S1. A. Complete list of 177 genes overexpressed in replicative senescence Value Gene Description UniGene RefSeq 2.440 WNT16 wingless-type MMTV integration site family, member 16 (WNT16), transcript variant 2, mRNA. Hs.272375 NM_016087 2.355 MMP10 matrix metallopeptidase 10 (stromelysin 2) (MMP10), mRNA. Hs.2258 NM_002425 2.344 MMP3 matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3), mRNA. Hs.375129 NM_002422 2.300 HIST1H2AC Histone cluster 1, H2ac Hs.484950 2.134 CLDN1 claudin 1 (CLDN1), mRNA. Hs.439060 NM_021101 2.119 TSPAN13 tetraspanin 13 (TSPAN13), mRNA. Hs.364544 NM_014399 2.112 HIST2H2BE histone cluster 2, H2be (HIST2H2BE), mRNA. Hs.2178 NM_003528 2.070 HIST2H2BE histone cluster 2, H2be (HIST2H2BE), mRNA. Hs.2178 NM_003528 2.026 DCBLD2 discoidin, CUB and LCCL domain containing 2 (DCBLD2), mRNA. Hs.203691 NM_080927 2.007 SERPINB2 serpin peptidase inhibitor, clade B (ovalbumin), member 2 (SERPINB2), mRNA. Hs.594481 NM_002575 2.004 HIST2H2BE histone cluster 2, H2be (HIST2H2BE), mRNA. Hs.2178 NM_003528 1.989 OBFC2A Oligonucleotide/oligosaccharide-binding fold containing 2A Hs.591610 1.962 HIST2H2BE histone cluster 2, H2be (HIST2H2BE), mRNA. Hs.2178 NM_003528 1.947 PLCB4 phospholipase C, beta 4 (PLCB4), transcript variant 2, mRNA. Hs.472101 NM_182797 1.934 PLCB4 phospholipase C, beta 4 (PLCB4), transcript variant 1, mRNA. Hs.472101 NM_000933 1.933 KRTAP1-5 keratin associated protein 1-5 (KRTAP1-5), mRNA. Hs.534499 NM_031957 1.894 HIST2H2BE histone cluster 2, H2be (HIST2H2BE), mRNA. Hs.2178 NM_003528 1.884 CYTL1 cytokine-like 1 (CYTL1), mRNA. Hs.13872 NM_018659 tumor necrosis factor receptor superfamily, member 10d, decoy with truncated death domain (TNFRSF10D), 1.848 TNFRSF10D Hs.213467 NM_003840 mRNA. -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
Suppl Info 2021-01-04 Fv
Supplemental Information Outline……………………………………………….……….………….………………………….………………..….1 Supplemental Figures (S1-S13) Figure S1: A mouse strain carrying a CRTC1-MAML2 knock-in allele under the Crtc1 natural regulatory control (mimicking the t(11;19) genetic aBnormality in human MEC) died after Birth.... .............................. 2 Figure S2: The transgene construct, genotyping, and transgene copy numbers in three Cre-regulated CRTC1-MAML2 transgenic mouse lines were shown. ............................................................................... 3 Figure S3: Western Blotting analysis of the CRTC1-MAML2 fusion transgene expression in salivary gland tumors developed from Line 1 and Line 2 mCre-CM (+) mice………………………………………………..….4 Figure S4: Western Blot analysis of the CRTC1-MAML2 transgene expression in various tissues of the mCre;CM(+) mouse line............................................................................................................................ 5 Figure S5: The mCre-CM1(+) mice developed ear cysts with CRTC1-MAML2 fusion expression ………...6 Figure S6: The Cre-regulated CRTC1-MAML2 transgenic line, after being crossed with Dcpp1-Cre-ERT2 or Pip-Cre-ERT2 transgenic mice, expressed low levels of the CRTC1-MAML2 fusion in salivary glands…..7 Figure S7: Salivary gland tumors developed from the Line 2 mCre-CM(+) mice displayed a characteristic histological feature of human MEC and expressed the CRTC1-MAML2 fusion. ……………………………...8 Figure S8: Representative images showed aBnormal ducts in the salivary glands of mCre-CM(+) -
New Insights on Human Essential Genes Based on Integrated Multi
bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted February 5, 2018. 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. New insights on human essential genes based on integrated multi- omics analysis Hebing Chen1,2, Zhuo Zhang1,2, Shuai Jiang 1,2, Ruijiang Li1, Wanying Li1, Hao Li1,* and Xiaochen Bo1,* 1Beijing Institute of Radiation Medicine, Beijing 100850, China. 2 Co-first author *Correspondence: [email protected]; [email protected] Abstract Essential genes are those whose functions govern critical processes that sustain life in the organism. Comprehensive understanding of human essential genes could enable breakthroughs in biology and medicine. Recently, there has been a rapid proliferation of technologies for identifying and investigating the functions of human essential genes. Here, according to gene essentiality, we present a global analysis for comprehensively and systematically elucidating the genetic and regulatory characteristics of human essential genes. We explain why these genes are essential from the genomic, epigenomic, and proteomic perspectives, and we discuss their evolutionary and embryonic developmental properties. Importantly, we find that essential human genes can be used as markers to guide cancer treatment. We have developed an interactive web server, the Human Essential Genes Interactive Analysis Platform (HEGIAP) (http://sysomics.com/HEGIAP/), which integrates abundant analytical tools to give a global, multidimensional interpretation of gene essentiality. bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted February 5, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Molecular Codes Through Complex Formation in a Model of the Human Inner Kinetochore
Preprint. Final manuscript published in: Biosemiotics 7(2):223-247 (2014) doi: 10.1007/s12304-013-9193-5 Biosemiotics manuscript No. (will be inserted by the editor) Molecular Codes Through Complex Formation in a Model of the Human Inner Kinetochore Dennis G¨orlich · Gabi Escuela · Gerd Gruenert · Peter Dittrich* · Bashar Ibrahim* Received: date / Accepted: date This work was supported by the German Research Foundation priority programs InKoMBio (SPP 1395, Grant DI 852/10-1), the European Commission NeuNeu Project (248992) and the Jena School for Microbial Communication (JSMC). Dennis G¨orlich Institute of Biostatistics and Clinical Research, University of Muenster, Muenster, Germany Tel: +49-251-8353605 E-mail: [email protected] Gabi Escuela · Gerd Gruenert · Peter Dittrich Bio Systems Analysis Group, Institute of Computer Science, Jena Center for Bioinformatics and Friedrich Schiller University Jena, Jena, Germany Tel.:+49-3641-9-46460 Fax: +49-3641-9-46452 E-mail: [email protected] Bashar Ibrahim Bio Systems Analysis Group, Institute of Computer Science, Jena Center for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany, and German Cancer Research Center, DKFZ-ZMBH Alliance, Heidelberg, Germany Tel.:+49-3641-9-46463 Fax: +49-3641-9-46452 E-mail: [email protected] 2 Dennis G¨orlich et al. Abstract We apply molecular code theory to a rule-based model of the hu- man inner kinetochore and study how complex formation in general can give rise to molecular codes. We analyze 105 reaction networks generated from the rule-based inner kinetochore model in two variants: with and without disso- ciation of complexes. -
A Framework to Identify Contributing Genes in Patients with Phelan-Mcdermid Syndrome
www.nature.com/npjgenmed Corrected: Author Correction ARTICLE OPEN A framework to identify contributing genes in patients with Phelan-McDermid syndrome Anne-Claude Tabet 1,2,3,4, Thomas Rolland2,3,4, Marie Ducloy2,3,4, Jonathan Lévy1, Julien Buratti2,3,4, Alexandre Mathieu2,3,4, Damien Haye1, Laurence Perrin1, Céline Dupont 1, Sandrine Passemard1, Yline Capri1, Alain Verloes1, Séverine Drunat1, Boris Keren5, Cyril Mignot6, Isabelle Marey7, Aurélia Jacquette7, Sandra Whalen7, Eva Pipiras8, Brigitte Benzacken8, Sandra Chantot-Bastaraud9, Alexandra Afenjar10, Delphine Héron10, Cédric Le Caignec11, Claire Beneteau11, Olivier Pichon11, Bertrand Isidor11, Albert David11, Laila El Khattabi12, Stephan Kemeny13, Laetitia Gouas13, Philippe Vago13, Anne-Laure Mosca-Boidron14, Laurence Faivre15, Chantal Missirian16, Nicole Philip16, Damien Sanlaville17, Patrick Edery18, Véronique Satre19, Charles Coutton19, Françoise Devillard19, Klaus Dieterich20, Marie-Laure Vuillaume21, Caroline Rooryck21, Didier Lacombe21, Lucile Pinson22, Vincent Gatinois22, Jacques Puechberty22, Jean Chiesa23, James Lespinasse24, Christèle Dubourg25, Chloé Quelin25, Mélanie Fradin25, Hubert Journel26, Annick Toutain27, Dominique Martin28, Abdelamdjid Benmansour1, Claire S. Leblond2,3,4, Roberto Toro2,3,4, Frédérique Amsellem29, Richard Delorme2,3,4,29 and Thomas Bourgeron2,3,4 Phelan-McDermid syndrome (PMS) is characterized by a variety of clinical symptoms with heterogeneous degrees of severity, including intellectual disability (ID), absent or delayed speech, and autism spectrum disorders (ASD). It results from a deletion of the distal part of chromosome 22q13 that in most cases includes the SHANK3 gene. SHANK3 is considered a major gene for PMS, but the factors that modulate the severity of the syndrome remain largely unknown. In this study, we investigated 85 patients with different 22q13 rearrangements (78 deletions and 7 duplications).