Mallin2015.Pdf
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
High-Mobility Group A1 Proteins May Be Involved in Estrogen Receptor Status of Breast Cancer
3786 Editorial Commentary High-mobility group A1 proteins may be involved in estrogen receptor status of breast cancer Yoshihiro Harada, Kenji Ohe Department of Pharmacotherapeutics, Faculty of Pharmaceutical Sciences, Fukuoka University, Jonan-ku, Fukuoka, Japan Correspondence to: Kenji Ohe. Department of Pharmacotherapeutics, Faculty of Pharmaceutical Sciences, Fukuoka University, Building 17, 8-19-1 Nanakuma, Jonan-ku, Fukuoka 814-180, Japan. Email: [email protected]. Provenance and Peer Review: This article was commissioned by the editorial office, Translational Cancer Research. The article did not undergo external peer review. Comment on: Gorbounov M, Carleton NM, Asch-Kendrick RJ, et al. High mobility group A1 (HMGA1) protein and gene expression correlate with ER-negativity and poor outcomes in breast cancer. Breast Cancer Res Treat 2020;179:25-35. Submitted Apr 27, 2020. Accepted for publication May 13, 2020. doi: 10.21037/tcr-20-1921 View this article at: http://dx.doi.org/10.21037/tcr-20-1921 The three types of breast cancer HMGA1 proteins: old and new proteins in breast cancer Breast cancer is one of the most common of cancers in woman. About 316,700 new cases were diagnosed as breast HMGA1 (previously called HMGI/Y) is a member of the cancer in US woman in 2019 and 41,760 were predicted to high-mobility group (HMG) proteins that were found from die from it (1). Breast cancer has a characteristic of therapy- their high mobility characteristics during polyacrylamide targeting receptors: hormone receptors (HR) that are electrophoresis of non-histone chromatin-associated estrogen receptor [ER: human ERα protein (NCBI protein proteins (3). -
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. -
The Biomarkers of Key Mirnas and Target Genes Associated with Acute Myocardial Infarction
The biomarkers of key miRNAs and target genes associated with acute myocardial infarction Qi Wang1, Bingyan Liu2,3, Yuanyong Wang4, Baochen Bai1, Tao Yu3 and Xian–ming Chu1,5 1 Department of Cardiology, The Affiliated hospital of Qingdao University, Qingdao, China 2 School of Basic Medicine, Qingdao University, Qingdao, China 3 Institute for Translational Medicine, Qingdao University, Qingdao, China 4 Department of Thoracic Surgery, Affiliated Hospital of Qingdao University, Qingdao, China 5 Department of Cardiology, The Affiliated Cardiovascular Hospital of Qingdao University, Qingdao, China ABSTRACT Background. Acute myocardial infarction (AMI) is considered one of the most prominent causes of death from cardiovascular disease worldwide. Knowledge of the molecular mechanisms underlying AMI remains limited. Accurate biomarkers are needed to predict the risk of AMI and would be beneficial for managing the incidence rate. The gold standard for the diagnosis of AMI, the cardiac troponin T (cTnT) assay, requires serial testing, and the timing of measurement with respect to symptoms affects the results. As attractive candidate diagnostic biomarkers in AMI, circulating microRNAs (miRNAs) are easily detectable, generally stable and tissue specific. Methods. The Gene Expression Omnibus (GEO) database was used to compare miRNA expression between AMI and control samples, and the interactions between miRNAs and mRNAs were analysed for expression and function. Furthermore, a protein-protein interaction (PPI) network was constructed. The miRNAs identified in the bioinformatic analysis were verified by RT-qPCR in an H9C2 cell line. The miRNAs in plasma samples from patients with AMI (n D 11) and healthy controls (n D 11) were used to construct Submitted 23 December 2019 receiver operating characteristic (ROC) curves to evaluate the clinical prognostic value Accepted 14 April 2020 of the identified miRNAs. -
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid Leukemia Cells Supported Only by Exogenous Cytokines Is Associated with a Patient Subset with Adverse Outcome Annette K. Brenner, Elise Aasebø, Maria Hernandez-Valladares, Frode Selheim, Frode Berven, Ida-Sofie Grønningsæter, Sushma Bartaula-Brevik and Øystein Bruserud Supplementary Material S2 of S31 Table S1. Detailed information about the 68 AML patients included in the study. # of blasts Viability Proliferation Cytokine Viable cells Change in ID Gender Age Etiology FAB Cytogenetics Mutations CD34 Colonies (109/L) (%) 48 h (cpm) secretion (106) 5 weeks phenotype 1 M 42 de novo 241 M2 normal Flt3 pos 31.0 3848 low 0.24 7 yes 2 M 82 MF 12.4 M2 t(9;22) wt pos 81.6 74,686 low 1.43 969 yes 3 F 49 CML/relapse 149 M2 complex n.d. pos 26.2 3472 low 0.08 n.d. no 4 M 33 de novo 62.0 M2 normal wt pos 67.5 6206 low 0.08 6.5 no 5 M 71 relapse 91.0 M4 normal NPM1 pos 63.5 21,331 low 0.17 n.d. yes 6 M 83 de novo 109 M1 n.d. wt pos 19.1 8764 low 1.65 693 no 7 F 77 MDS 26.4 M1 normal wt pos 89.4 53,799 high 3.43 2746 no 8 M 46 de novo 26.9 M1 normal NPM1 n.d. n.d. 3472 low 1.56 n.d. no 9 M 68 MF 50.8 M4 normal D835 pos 69.4 1640 low 0.08 n.d. -
An Ontogenetic Switch Drives the Positive and Negative Selection of B Cells
An ontogenetic switch drives the positive and negative selection of B cells Xijin Xua, Mukta Deobagkar-Lelea, Katherine R. Bulla, Tanya L. Crockforda, Adam J. Meadb, Adam P. Cribbsc, David Simsc, Consuelo Anzilottia, and Richard J. Cornalla,1 aMedical Research Council Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; bMedical Research Council Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; and cMedical Research Council, Weatherall Institute of Molecular Medicine, Centre for Computational Biology, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom Edited by Michael Reth, University of Freiburg, Freiburg, Germany, and approved January 6, 2020 (received for review September 3, 2019) + Developing B cells can be positively or negatively selected by self- BM HSCs increased CD5 B-1a B cell development (15), while antigens, but the mechanisms that determine these outcomes are expression of let-7b in FL pro-B cells blocked the development of incompletely understood. Here, we show that a B cell intrinsic B-1 B cells (17). These findings support the notion of hard-wired switch between positive and negative selection during ontogeny differences during ontogeny, but possibly downstream of the HSC is determined by a change from Lin28b to let-7 gene expression. commitment stage. Ectopic expression of a Lin28b transgene in murine B cells restored Several lines of evidence also suggest that B-1 B cells can un- the positive selection of autoreactive B-1 B cells by self-antigen in dergo positive selection, which is linked to their B cell receptor adult bone marrow. -
Comparison of Orthologs Across Multiple Species by Various Strategies
COMPARISON OF ORTHOLOGS ACROSS MULTIPLE SPECIES BY VARIOUS STRATEGIES BY HUI LIU DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biophysics and Computational Biology in the Graduate College of the University of Illinois at Urbana-Champaign, 2014 Urbana, Illinois Doctoral Committee: Professor Eric Jakobsson, Chair, Director of Research Professor Gene E. Robinson Associate Professor Saurabh Sinha Assistant Professor Jian Ma Abstract Thanks to the improvement of genome sequencing technology, abundant multi-species genomic data now became available and comparative genomics continues to be a fast prospering filed of biological research. Through the comparison of genomes of different organisms, we can understand what, at the molecular level, distinguishes different life forms from each other. It shed light on revealing the evolution of biology. And it also helps to refine the annotations and functions of individual genomes. For example, through comparisons across mammalian genomes, we can give an estimate of the conserved set of genes across mammals and correspondingly, find the species-specific sets of genes or functions. However, comparative genomics can be feasible only if a meaningful classification of genes exists. A natural way to do so is to delineate sets of orthologous genes. However, debates exist about the appropriate way to define orthologs. It is originally defined as genes in different species which derive from speciation events. But such definition is not sufficient to derive orthologous genes due to the complexity of evolutionary events such as gene duplication and gene loss. While it is possible to correctly figure out all the evolutionary events with the true phylogenetic tree, the true phylogenetic tree itself is impractical to be inferred. -
Supplementary Table S2
1-high in cerebrotropic Gene P-value patients Definition BCHE 2.00E-04 1 Butyrylcholinesterase PLCB2 2.00E-04 -1 Phospholipase C, beta 2 SF3B1 2.00E-04 -1 Splicing factor 3b, subunit 1 BCHE 0.00022 1 Butyrylcholinesterase ZNF721 0.00028 -1 Zinc finger protein 721 GNAI1 0.00044 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 GNAI1 0.00049 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 PDE1B 0.00069 -1 Phosphodiesterase 1B, calmodulin-dependent MCOLN2 0.00085 -1 Mucolipin 2 PGCP 0.00116 1 Plasma glutamate carboxypeptidase TMX4 0.00116 1 Thioredoxin-related transmembrane protein 4 C10orf11 0.00142 1 Chromosome 10 open reading frame 11 TRIM14 0.00156 -1 Tripartite motif-containing 14 APOBEC3D 0.00173 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3D ANXA6 0.00185 -1 Annexin A6 NOS3 0.00209 -1 Nitric oxide synthase 3 SELI 0.00209 -1 Selenoprotein I NYNRIN 0.0023 -1 NYN domain and retroviral integrase containing ANKFY1 0.00253 -1 Ankyrin repeat and FYVE domain containing 1 APOBEC3F 0.00278 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F EBI2 0.00278 -1 Epstein-Barr virus induced gene 2 ETHE1 0.00278 1 Ethylmalonic encephalopathy 1 PDE7A 0.00278 -1 Phosphodiesterase 7A HLA-DOA 0.00305 -1 Major histocompatibility complex, class II, DO alpha SOX13 0.00305 1 SRY (sex determining region Y)-box 13 ABHD2 3.34E-03 1 Abhydrolase domain containing 2 MOCS2 0.00334 1 Molybdenum cofactor synthesis 2 TTLL6 0.00365 -1 Tubulin tyrosine ligase-like family, member 6 SHANK3 0.00394 -1 SH3 and multiple ankyrin repeat domains 3 ADCY4 0.004 -1 Adenylate cyclase 4 CD3D 0.004 -1 CD3d molecule, delta (CD3-TCR complex) (CD3D), transcript variant 1, mRNA. -
HMGA2 Promotes Adipogenesis by Activating C/EBP&Beta
CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector Biochemical and Biophysical Research Communications 472 (2016) 617e623 Contents lists available at ScienceDirect Biochemical and Biophysical Research Communications journal homepage: www.elsevier.com/locate/ybbrc HMGA2 promotes adipogenesis by activating C/EBPb-mediated expression of PPARg * Yang Xi a, Wanjing Shen a, Lili Ma a, Ming Zhao a, Jiachen Zheng a, Shizhong Bu a, , ** Shinjiro Hino b, Mitsuyoshi Nakao b, c, a Diabetes Center, and Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, School of Medicine, Ningbo University, Ningbo 315211, China b Department of Medical Cell Biology, Institute of Molecular Embryology and Genetics, Kumamoto University, Kumamoto, 860-0811, Japan c Core Research for Evolutional Science and Technology (CREST), Japan Agency for Medical Research and Development, Tokyo, Japan article info abstract Article history: Adipogenesis is orchestrated by a highly ordered network of transcription factors including peroxisome- Received 1 March 2016 proliferator activated receptor-gamma (PPARg) and CCAAT-enhancer binding protein (C/EBP) family Accepted 6 March 2016 proteins. High mobility group protein AT-hook 2 (HMGA2), an architectural transcription factor, has been Available online 8 March 2016 reported to play an essential role in preadipocyte proliferation, and its overexpression has been impli- cated in obesity in mice and humans. However, the direct role of HMGA2 in regulating the gene Keywords: expression program during adipogenesis is not known. Here, we demonstrate that HMGA2 is required for Adipogenesis C/EBPb-mediated expression of PPARg, and thus promotes adipogenic differentiation. We observed a HMGA2 C/EBPb transient but marked increase of Hmga2 transcript at an early phase of differentiation of mouse 3T3-L1 PPARg preadipocytes. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
The Expression of HMGA Genes Is Regulated by Their 3Оutr
Oncogene (2001) 20, 4537 ± 4541 ã 2001 Nature Publishing Group All rights reserved 0950 ± 9232/01 $15.00 www.nature.com/onc The expression of HMGA genes is regulated by their 3'UTR Lars Borrmann1, S Wilkening1 and J Bullerdiek*,1 1Center for Human Genetics, University of Bremen, Leobenerstr. ZHG, 28359 Bremen, Germany Many benign mesenchymal tumors are characterized by binding by HMGA proteins leads to a conformational chromosomal abnormalities of the regions 12q15 or change in DNA modulating the environment for the 6p21.3 leading to aberrant expression of either HMGA2 binding of transcription factors. (formerly HMGIC) or HMGA1 (formerly HMGIY). Whereas HMGA2 is almost exclusively expressed in The proteins of both genes belong to the HMGA proliferating undierentiated cells during embryogen- (formerly HMGI(Y)) family of architectural transcrip- esis and in benign and malignant tumors, HMGA1 can tion factors. As a rule, aberrant HMGA transcripts also be detected at very low levels in dierentiated cells found in a variety of benign tumors have intact coding (Chiappetta et al., 1996; Zhou et al., 1995; Busse- regions at least for the DNA binding domains with a makers et al., 1991; Abe et al., 2000). An increased truncation of their 3' untranslated regions. Adding this to HMGA1 gene expression has been considered as a the ®nding that an altered HMGA protein level is not general diagnostic marker for neoplastic transforma- always correlated with an increased amount of corre- tion (Goodwin et al., 1985; Giancotti et al., 1987, 1989) sponding mRNA indicates a posttranscriptional expres- and the metastatic potential of malignant neoplasms sion control mediated by regulatory elements within the (Bussemakers et al., 1991; Tamimi et al., 1993; 3'UTR. -
Supplementary Table 1
Supplementary Table 1 gene p_val avg_logFC pct.1 pct.2 p_val_adj cluster gene gene p_val avg_logFC pct.1 pct. -
Dynamics of H3k27me3 Modification on Plant Adaptation To
plants Review Dynamics of H3K27me3 Modification on Plant Adaptation to Environmental Cues Qingwen Shen , Yisheng Lin, Yingbo Li and Guifeng Wang * National Key Laboratory of Wheat and Maize Crops Science, CIMMYT-China (Henan) Joint Research Center of Wheat and Maize, Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China; [email protected] (Q.S.); [email protected] (Y.L.); [email protected] (Y.L.) * Correspondence: [email protected]; Tel.: +86-371-56990324 Abstract: Given their sessile nature, plants have evolved sophisticated regulatory networks to confer developmental plasticity for adaptation to fluctuating environments. Epigenetic codes, like tri- methylation of histone H3 on Lys27 (H3K27me3), are evidenced to account for this evolutionary benefit. Polycomb repressive complex 2 (PRC2) and PRC1 implement and maintain the H3K27me3- mediated gene repression in most eukaryotic cells. Plants take advantage of this epigenetic machinery to reprogram gene expression in development and environmental adaption. Recent studies have uncovered a number of new players involved in the establishment, erasure, and regulation of H3K27me3 mark in plants, particularly highlighting new roles in plants’ responses to environmental cues. Here, we review current knowledge on PRC2-H3K27me3 dynamics occurring during plant growth and development, including its writers, erasers, and readers, as well as targeting mechanisms, and summarize the emerging roles of H3K27me3 mark in plant adaptation to environmental stresses. Citation: Shen, Q.; Lin, Y.; Li, Y.; Wang, G. Dynamics of H3K27me3 Keywords: H3K27me3; epigenetics; environmental cues; polycomb repressive complex 2; polycomb Modification on Plant Adaptation to repressive complex 1; demethylase; recruitment Environmental Cues.