Significant Modules and Biological Processes Between Active Components of Salvia Miltiorrhiza Depside Salt and Aspirin
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Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
View of HER2: Human Epidermal Growth Factor Receptor 2; TNBC: Triple-Negative Breast Resistance to Systemic Therapy in Patients with Breast Cancer
Wen et al. Cancer Cell Int (2018) 18:128 https://doi.org/10.1186/s12935-018-0625-9 Cancer Cell International PRIMARY RESEARCH Open Access Sulbactam‑enhanced cytotoxicity of doxorubicin in breast cancer cells Shao‑hsuan Wen1†, Shey‑chiang Su2†, Bo‑huang Liou3, Cheng‑hao Lin1 and Kuan‑rong Lee1* Abstract Background: Multidrug resistance (MDR) is a major obstacle in breast cancer treatment. The predominant mecha‑ nism underlying MDR is an increase in the activity of adenosine triphosphate (ATP)-dependent drug efux trans‑ porters. Sulbactam, a β-lactamase inhibitor, is generally combined with β-lactam antibiotics for treating bacterial infections. However, sulbactam alone can be used to treat Acinetobacter baumannii infections because it inhibits the expression of ATP-binding cassette (ABC) transporter proteins. This is the frst study to report the efects of sulbactam on mammalian cells. Methods: We used the breast cancer cell lines as a model system to determine whether sulbactam afects cancer cells. The cell viabilities in the present of doxorubicin with or without sulbactam were measured by MTT assay. Protein identities and the changes in protein expression levels in the cells after sulbactam and doxorubicin treatment were determined using LC–MS/MS. Real-time reverse transcription polymerase chain reaction (real-time RT-PCR) was used to analyze the change in mRNA expression levels of ABC transporters after treatment of doxorubicin with or without sulbactam. The efux of doxorubicin was measures by the doxorubicin efux assay. Results: MTT assay revealed that sulbactam enhanced the cytotoxicity of doxorubicin in breast cancer cells. The results of proteomics showed that ABC transporter proteins and proteins associated with the process of transcription and initiation of translation were reduced. -
Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
Variation in FCN1 Affects Biosynthesis of Ficolin-1 and Is Associated With
Genes and Immunity (2012) 13, 515–522 & 2012 Macmillan Publishers Limited All rights reserved 1466-4879/12 www.nature.com/gene ORIGINAL ARTICLE Variation in FCN1 affects biosynthesis of ficolin-1 and is associated with outcome of systemic inflammation L Munthe-Fog1, T Hummelshoj1, C Honore´ 1, ME Moller1, MO Skjoedt1, I Palsgaard1, N Borregaard2, HO Madsen1 and P Garred1 Ficolin-1 is a recognition molecule of the lectin complement pathway. The ficolin-1 gene FCN1 is polymorphic, but the functional and clinical consequences are unknown.The concentration of ficolin-1 in plasma and FCN1 polymorphisms in positions À 1981 (rs2989727), À 791 (rs28909068), À 542 (rs10120023), À 271 (rs28909976), À 144 (rs10117466) and þ 7918 (rs1071583) were determined in 100 healthy individuals. FCN1 expression by isolated monocytes and granulocytes and ficolin-1 levels in monocyte culture supernatants were assessed in 21 FCN1-genotyped individuals. FCN1 polymorphisms were determined in a cohort of 251 patients with systemic inflammation. High ficolin-1 plasma levels were significantly associated with the minor alleles in position À 542 and À 144. These alleles were also significantly associated with high FCN1 mRNA expression. The level of ficolin-1 in culture supernatants was significantly higher in individuals homozygous for the minor alleles at positions À 542 and À 144. Homozygosity for these alleles was significantly associated with fatal outcome in patients with systemic inflammation. None of the other investigated polymorphisms were associated with FCN1 and ficolin-1 expression, concentration or disease outcome. Functional polymorphic sites in the promoter region of FCN1 regulate both the expression and synthesis of ficolin-1 and are associated with outcome in severe inflammation. -
Comprehensive Analyses of 723 Transcriptomes Enhance Genetic and Biological Interpretations for Complex Traits in Cattle
Downloaded from genome.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press Resource Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle Lingzhao Fang,1,2,3,4,8 Wentao Cai,2,5,8 Shuli Liu,1,5,8 Oriol Canela-Xandri,3,4,8 Yahui Gao,1,2 Jicai Jiang,2 Konrad Rawlik,3 Bingjie Li,1 Steven G. Schroeder,1 Benjamin D. Rosen,1 Cong-jun Li,1 Tad S. Sonstegard,6 Leeson J. Alexander,7 Curtis P. Van Tassell,1 Paul M. VanRaden,1 John B. Cole,1 Ying Yu,5 Shengli Zhang,5 Albert Tenesa,3,4 Li Ma,2 and George E. Liu1 1Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA; 2Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA; 3The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom; 4Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom; 5College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; 6Acceligen, Eagan, Minnesota 55121, USA; 7Fort Keogh Livestock and Range Research Laboratory, Agricultural Research Service, USDA, Miles City, Montana 59301, USA By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biol- ogy, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis- specific genes evolve fastest). -
Crystal Structure of Human Gadd45 Reveals an Active Dimer
Protein Cell 2011, 2(10): 814–826 Protein & Cell DOI 10.1007/s13238-011-1090-6 RESEARCH ARTICLE Crystal structure of human Gadd45 reveals an active dimer 1,2,3* 1* 4 4 1 1 3 Wenzheng Zhang , Sheng Fu , Xuefeng Liu , Xuelian Zhao✉ , Wenchi Zhang✉ , Wei Peng , Congying Wu , Yuanyuan Li3, Xuemei Li1, Mark Bartlam1,2, Zong-Hao Zeng1 , Qimin Zhan4 , Zihe Rao1,2,3 1 National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 2 Tianjin Key Laboratory of Protein Science, College of Life Sciences, Nankai University, Tianjin 300071, China 3 Laboratory of Structural Biology, Tsinghua University, Beijing 100084, China 4 State Key Laboratory of Molecular Oncology, Cancer Institute, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China ✉ Correspondence: [email protected] (Z.-H. Zeng), [email protected] (Q. Zhan) Received August 23, 2011 Accepted September 19, 2011 ABSTRACT INTRODUCTION The human Gadd45 protein family plays critical roles in The human Gadd45 family of growth arrest and DNA DNA repair, negative growth control, genomic stability, damage-inducible proteins has three members, Gadd45α, cell cycle checkpoints and apoptosis. Here we report the -β, and -γ, grouped together on the basis of their amino acid crystal structure of human Gadd45, revealing a unique sequences and functional similarities (Vairapandi et al., 1996; dimer formed via a bundle of four parallel helices, Takekawa and Saito, 1998; Nakayama et al., 1999). The involving the most conserved residues among the genes encoding the α, β and γ isoforms of Gadd45 are Gadd45 isoforms. -
Decreased Plasma Concentrations of Apolipoprotein M in Sepsis And
Kumaraswamy et al. Critical Care 2012, 16:R60 http://ccforum.com/content/16/2/R60 RESEARCH Open Access Decreased plasma concentrations of apolipoprotein M in sepsis and systemic inflammatory response syndromes Sunil B Kumaraswamy1, Adam Linder2, Per Åkesson2 and Björn Dahlbäck1* Abstract Introduction: Apolipoprotein M (apoM) is present in 5% of high-density lipoprotein (HDL) particles in plasma. It is a carrier of sphingosine-1-phosphate (S1P), which is important for vascular barrier protection. The aim was to determine the plasma concentrations of apoM during sepsis and systemic inflammatory response syndrome (SIRS) and correlate them to levels of apolipoprotein A-I (apoA1), apolipoprotein B (apoB), HDL-, and low-density lipoprotein (LDL)-cholesterol. Methods: Plasma samples from patients with (1), severe sepsis with shock (n = 26); (2), severe sepsis without shock (n = 44); (3), sepsis (n = 100); (4), infections without SIRS (n = 43); and (5) SIRS without infection (n = 20) were analyzed. The concentrations of apoM, apoA1, and apoB were measured with enzyme-linked immunosorbent assays (ELISAs). Total, HDL-, and LDL-cholesterol concentrations were measured with a commercial HDL/LDL cholesterol test. Results: ApoM concentrations correlated negatively to acute-phase markers. Thus, apoM behaved as a negative acute-phase protein. Decreased values were observed in all patient groups (P < 0.0001), with the most drastic decreases observed in the severely sick patients. ApoM levels correlated strongly to those of apoA1, apoB, HDL, and LDL cholesterol. The HDL and LDL cholesterol levels were low in all patient groups, as compared with controls (P < 0.0001), in particular, HDL cholesterol. ApoA1 and apoB concentrations were low only in the more severely affected patients. -
13-Van Lieshout TOORTHJ
Send Orders for Reprints to [email protected] The Open Orthopaedics Journal, 2015, 9, (Suppl 1: M13) 367-371 367 Open Access Multiple Infectious Complications in a Severely Injured Patient with Single Nucleotide Polymorphisms in Important Innate Immune Response Genes Maarten W.G.A. Bronkhorst1, Peter Patka2 and Esther M.M. Van Lieshout*,1 1Trauma Research Unit Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands 2Department of Accident & Emergency, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands Abstract: Trauma is a major public health problem worldwide. Infectious complications, sepsis, and multiple organ dysfunction syndrome (MODS) remain important causes for morbidity and mortality in patients who survive the initial trauma. There is increasing evidence for the role of genetic variation in the innate immune system on infectious complications in severe trauma patients. We describe a trauma patient with multiple infectious complications caused by multiple micro-organisms leading to prolonged hospital stay with numerous treatments. This patient had multiple single nucleotide polymorphisms (SNPs) in the MBL2, MASP2, FCN2 and TLR2 genes, most likely contributing to increased susceptibility and severity of infectious disease. Keywords: Complications, genetic variation, infection, multiple organ dysfunction syndrome, single nucleotide polymorphism, systemic inflammatory response syndrome, trauma. INTRODUCTION differences between humans These differences are known as ‘polymorphisms’. The coding regions of DNA contain the Trauma is a major public health problem worldwide, approximately 20,000 human protein-coding genes. The ranking as the fourth leading cause of death. In 2010, there coding regions take up less than 2% of all DNA. More than were 5.1 million deaths from injuries and the total number of 98% of the human genome is composed of non-coding DNA deaths from injuries was greater than the number of deaths of which the function is partly unknown. -
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. -
Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer
Published OnlineFirst March 27, 2013; DOI: 10.1158/1078-0432.CCR-12-3851 Clinical Cancer Imaging, Diagnosis, Prognosis Research Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer Ye Xu1,4, Qinghua Xu1,6,7, Li Yang1,4, Xun Ye6,7, Fang Liu6,7, Fei Wu6,7, Shujuan Ni1,2,3,5, Cong Tan1,2,3,5, Guoxiang Cai1,4, Xia Meng6,7, Sanjun Cai1,4, and Xiang Du1,2,3,5 Abstract Purpose: The early detection of colorectal cancer (CRC) is crucial for successful treatment and patient survival. However, compliance with current screening methods remains poor. This study aimed to identify an accurate blood-based gene expression signature for CRC detection. Experimental Design: Gene expression in peripheral blood samples from 216 patients with CRC tumors and 187 controls was investigated in the study.Wefirstconductedamicroarrayanalysistoselect candidate genes that were significantly differentially expressed between patients with cancer and con- trols. A quantitative reverse transcription PCR assay was then used to evaluate the expression of selected genes. A gene expression signature was identified using a training set (n ¼ 200) and then validated using an independent test set (n ¼ 160). Results: We identified an 18-gene signature that discriminated the patients with CRC from controls with 92% accuracy, 91% sensitivity, and 92% specificity. The signature performance was further validated in the independent test set with 86% accuracy, 84% sensitivity, and 88% specificity. The area under the receiver operating characteristics curve was 0.94. The signature was shown to be enriched in genes related to immune functions. Conclusions: This study identified an 18-gene signature that accurately discriminated patients with CRC from controls in peripheral blood samples. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
2020 Program Book
PROGRAM BOOK Note that TAGC was cancelled and held online with a different schedule and program. This document serves as a record of the original program designed for the in-person meeting. April 22–26, 2020 Gaylord National Resort & Convention Center Metro Washington, DC TABLE OF CONTENTS About the GSA ........................................................................................................................................................ 3 Conference Organizers ...........................................................................................................................................4 General Information ...............................................................................................................................................7 Mobile App ....................................................................................................................................................7 Registration, Badges, and Pre-ordered T-shirts .............................................................................................7 Oral Presenters: Speaker Ready Room - Camellia 4.......................................................................................7 Poster Sessions and Exhibits - Prince George’s Exhibition Hall ......................................................................7 GSA Central - Booth 520 ................................................................................................................................8 Internet Access ..............................................................................................................................................8