Modulating Hallmarks of Cholangiocarcinoma
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Bilateral Gene Interaction Hierarchy Analysis of the Cell Death Gene
White et al. BMC Genomics (2016) 17:130 DOI 10.1186/s12864-016-2412-0 RESEARCH ARTICLE Open Access Bilateral gene interaction hierarchy analysis of the cell death gene response emphasizes the significance of cell cycle genes following unilateral traumatic brain injury Todd E. White1, Monique C. Surles-Zeigler1, Gregory D. Ford2, Alicia S. Gates1, Benem Davids1, Timothy Distel1,4, Michelle C. LaPlaca3 and Byron D. Ford1,4* Abstract Background: Delayed or secondary cell death that is caused by a cascade of cellular and molecular processes initiated by traumatic brain injury (TBI) may be reduced or prevented if an effective neuroprotective strategy is employed. Microarray and subsequent bioinformatic analyses were used to determine which genes, pathways and networks were significantly altered 24 h after unilateral TBI in the rat. Ipsilateral hemi-brain, the corresponding contralateral hemi-brain, and naïve (control) brain tissue were used for microarray analysis. Results: Ingenuity Pathway Analysis showed cell death and survival (CD) to be a top molecular and cellular function associated with TBI on both sides of the brain. One major finding was that the overall gene expression pattern suggested an increase in CD genes in ipsilateral brain tissue and suppression of CD genes contralateral to the injury which may indicate an endogenous protective mechanism. We created networks of genes of interest (GOI) and ranked the genes by the number of direct connections each had in the GOI networks, creating gene interaction hierarchies (GIHs). Cell cycle was determined from the resultant GIHs to be a significant molecular and cellular function in post-TBI CD gene response. -
The Title of the Dissertation
UNIVERSITY OF CALIFORNIA SAN DIEGO Novel network-based integrated analyses of multi-omics data reveal new insights into CD8+ T cell differentiation and mouse embryogenesis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Kai Zhang Committee in charge: Professor Wei Wang, Chair Professor Pavel Arkadjevich Pevzner, Co-Chair Professor Vineet Bafna Professor Cornelis Murre Professor Bing Ren 2018 Copyright Kai Zhang, 2018 All rights reserved. The dissertation of Kai Zhang is approved, and it is accept- able in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California San Diego 2018 iii EPIGRAPH The only true wisdom is in knowing you know nothing. —Socrates iv TABLE OF CONTENTS Signature Page ....................................... iii Epigraph ........................................... iv Table of Contents ...................................... v List of Figures ........................................ viii List of Tables ........................................ ix Acknowledgements ..................................... x Vita ............................................. xi Abstract of the Dissertation ................................. xii Chapter 1 General introduction ............................ 1 1.1 The applications of graph theory in bioinformatics ......... 1 1.2 Leveraging graphs to conduct integrated analyses .......... 4 1.3 References .............................. 6 Chapter 2 Systematic -
Rule Mining on Microrna Expression Profiles For
Faculty of Engineering and Information Technology University of Technology, Sydney Rule Mining on MicroRNA Expression Profiles for Human Disease Understanding A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy by Renhua Song July 2016 CERTIFICATE OF AUTHORSHIP/ORIGINALITY I certify that the work in this thesis has not previously been submitted for a degree nor has it been submitted as part of requirements for a degree except as fully acknowledged within the text. I also certify that the thesis has been written by me. Any help that I have received in my research work and the preparation of the thesis itself has been acknowledged. In addition, I certify that all information sources and literature used are indicated in the thesis. Signature of Candidate i Acknowledgments First, and foremost, I would like to express my gratitude to my chief supervisor, Assoc. Prof. Jinyan Li, and to my co-supervisors Assoc. Prof. Paul Kennedy and Assoc. Prof. Daniel Catchpoole. I am extremely grateful for all the advice and guidance so unselfishly given to me over the last three and half years by these three distinguished academics. This research would not have been possible without their high order supervision, support, assistance and leadership. The wonderful support and assistance provided by many people during this research is very much appreciated by me and my family. I am very grateful for the help that I received from all of these people but there are some special individuals that I must thank by name. A very sincere thank you is definitely owed to my loving husband Jing Liu, not only for his tremendous support during the last three and half years, but also his unfailing and often sorely tested patience. -
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. -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence After Radical Prostatectomy
Int. J. Mol. Sci. 2015, 16, 3856-3869; doi:10.3390/ijms16023856 OPEN ACCESS International Journal of Molecular Sciences ISSN 1422-0067 www.mdpi.com/journal/ijms Article Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence after Radical Prostatectomy Chinyere Ibeawuchi 1, Hartmut Schmidt 2, Reinhard Voss 3, Ulf Titze 4, Mahmoud Abbas 5, Joerg Neumann 6, Elke Eltze 7, Agnes Marije Hoogland 8, Guido Jenster 9, Burkhard Brandt 10 and Axel Semjonow 1,* 1 Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 2 Center for Laboratory Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 3 Interdisciplinary Center for Clinical Research, University of Muenster, Albert-Schweitzer-Campus 1, Gebaeude D3, Domagkstrasse 3, Muenster D-48149, Germany; E-Mail: [email protected] 4 Pathology, Lippe Hospital Detmold, Röntgenstrasse 18, Detmold D-32756, Germany; E-Mail: [email protected] 5 Institute of Pathology, Mathias-Spital-Rheine, Frankenburg Street 31, Rheine D-48431, Germany; E-Mail: [email protected] 6 Institute of Pathology, Klinikum Osnabrueck, Am Finkenhuegel 1, Osnabrueck D-49076, Germany; E-Mail: [email protected] 7 Institute of Pathology, Saarbrücken-Rastpfuhl, Rheinstrasse 2, Saarbrücken D-66113, Germany; E-Mail: [email protected] 8 Department -
Involvement of DPP9 in Gene Fusions in Serous Ovarian Carcinoma
Smebye et al. BMC Cancer (2017) 17:642 DOI 10.1186/s12885-017-3625-6 RESEARCH ARTICLE Open Access Involvement of DPP9 in gene fusions in serous ovarian carcinoma Marianne Lislerud Smebye1,2, Antonio Agostini1,2, Bjarne Johannessen2,3, Jim Thorsen1,2, Ben Davidson4,5, Claes Göran Tropé6, Sverre Heim1,2,5, Rolf Inge Skotheim2,3 and Francesca Micci1,2* Abstract Background: A fusion gene is a hybrid gene consisting of parts from two previously independent genes. Chromosomal rearrangements leading to gene breakage are frequent in high-grade serous ovarian carcinomas and have been reported as a common mechanism for inactivating tumor suppressor genes. However, no fusion genes have been repeatedly reported to be recurrent driver events in ovarian carcinogenesis. We combined genomic and transcriptomic information to identify novel fusion gene candidates and aberrantly expressed genes in ovarian carcinomas. Methods: Examined were 19 previously karyotyped ovarian carcinomas (18 of the serous histotype and one undifferentiated). First, karyotypic aberrations were compared to fusion gene candidates identified by RNA sequencing (RNA-seq). In addition, we used exon-level gene expression microarrays as a screening tool to identify aberrantly expressed genes possibly involved in gene fusion events, and compared the findings to the RNA-seq data. Results: We found a DPP9-PPP6R3 fusion transcript in one tumor showing a matching genomic 11;19-translocation. Another tumor had a rearrangement of DPP9 with PLIN3. Both rearrangements were associated with diminished expression of the 3′ end of DPP9 corresponding to the breakpoints identified by RNA-seq. For the exon-level expression analysis, candidate fusion partner genes were ranked according to deviating expression compared to the median of the sample set. -
Preclinical Evaluation of Protein Disulfide Isomerase Inhibitors for the Treatment of Glioblastoma by Andrea Shergalis
Preclinical Evaluation of Protein Disulfide Isomerase Inhibitors for the Treatment of Glioblastoma By Andrea Shergalis A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Medicinal Chemistry) in the University of Michigan 2020 Doctoral Committee: Professor Nouri Neamati, Chair Professor George A. Garcia Professor Peter J. H. Scott Professor Shaomeng Wang Andrea G. Shergalis [email protected] ORCID 0000-0002-1155-1583 © Andrea Shergalis 2020 All Rights Reserved ACKNOWLEDGEMENTS So many people have been involved in bringing this project to life and making this dissertation possible. First, I want to thank my advisor, Prof. Nouri Neamati, for his guidance, encouragement, and patience. Prof. Neamati instilled an enthusiasm in me for science and drug discovery, while allowing me the space to independently explore complex biochemical problems, and I am grateful for his kind and patient mentorship. I also thank my committee members, Profs. George Garcia, Peter Scott, and Shaomeng Wang, for their patience, guidance, and support throughout my graduate career. I am thankful to them for taking time to meet with me and have thoughtful conversations about medicinal chemistry and science in general. From the Neamati lab, I would like to thank so many. First and foremost, I have to thank Shuzo Tamara for being an incredible, kind, and patient teacher and mentor. Shuzo is one of the hardest workers I know. In addition to a strong work ethic, he taught me pretty much everything I know and laid the foundation for the article published as Chapter 3 of this dissertation. The work published in this dissertation really began with the initial identification of PDI as a target by Shili Xu, and I am grateful for his advice and guidance (from afar!). -
Serum Albumin OS=Homo Sapiens
Protein Name Cluster of Glial fibrillary acidic protein OS=Homo sapiens GN=GFAP PE=1 SV=1 (P14136) Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 Cluster of Isoform 3 of Plectin OS=Homo sapiens GN=PLEC (Q15149-3) Cluster of Hemoglobin subunit beta OS=Homo sapiens GN=HBB PE=1 SV=2 (P68871) Vimentin OS=Homo sapiens GN=VIM PE=1 SV=4 Cluster of Tubulin beta-3 chain OS=Homo sapiens GN=TUBB3 PE=1 SV=2 (Q13509) Cluster of Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 (P60709) Cluster of Tubulin alpha-1B chain OS=Homo sapiens GN=TUBA1B PE=1 SV=1 (P68363) Cluster of Isoform 2 of Spectrin alpha chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTAN1 (Q13813-2) Hemoglobin subunit alpha OS=Homo sapiens GN=HBA1 PE=1 SV=2 Cluster of Spectrin beta chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTBN1 PE=1 SV=2 (Q01082) Cluster of Pyruvate kinase isozymes M1/M2 OS=Homo sapiens GN=PKM PE=1 SV=4 (P14618) Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 Clathrin heavy chain 1 OS=Homo sapiens GN=CLTC PE=1 SV=5 Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4 Cytoplasmic dynein 1 heavy chain 1 OS=Homo sapiens GN=DYNC1H1 PE=1 SV=5 Cluster of ATPase, Na+/K+ transporting, alpha 2 (+) polypeptide OS=Homo sapiens GN=ATP1A2 PE=3 SV=1 (B1AKY9) Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 Dihydropyrimidinase-related protein 2 OS=Homo sapiens GN=DPYSL2 PE=1 SV=1 Cluster of Alpha-actinin-1 OS=Homo sapiens GN=ACTN1 PE=1 SV=2 (P12814) 60 kDa heat shock protein, mitochondrial OS=Homo -
Anti-Inflammatory Role of Curcumin in LPS Treated A549 Cells at Global Proteome Level and on Mycobacterial Infection
Anti-inflammatory Role of Curcumin in LPS Treated A549 cells at Global Proteome level and on Mycobacterial infection. Suchita Singh1,+, Rakesh Arya2,3,+, Rhishikesh R Bargaje1, Mrinal Kumar Das2,4, Subia Akram2, Hossain Md. Faruquee2,5, Rajendra Kumar Behera3, Ranjan Kumar Nanda2,*, Anurag Agrawal1 1Center of Excellence for Translational Research in Asthma and Lung Disease, CSIR- Institute of Genomics and Integrative Biology, New Delhi, 110025, India. 2Translational Health Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India. 3School of Life Sciences, Sambalpur University, Jyoti Vihar, Sambalpur, Orissa, 768019, India. 4Department of Respiratory Sciences, #211, Maurice Shock Building, University of Leicester, LE1 9HN 5Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia- 7003, Bangladesh. +Contributed equally for this work. S-1 70 G1 S 60 G2/M 50 40 30 % of cells 20 10 0 CURI LPSI LPSCUR Figure S1: Effect of curcumin and/or LPS treatment on A549 cell viability A549 cells were treated with curcumin (10 µM) and/or LPS or 1 µg/ml for the indicated times and after fixation were stained with propidium iodide and Annexin V-FITC. The DNA contents were determined by flow cytometry to calculate percentage of cells present in each phase of the cell cycle (G1, S and G2/M) using Flowing analysis software. S-2 Figure S2: Total proteins identified in all the three experiments and their distribution betwee curcumin and/or LPS treated conditions. The proteins showing differential expressions (log2 fold change≥2) in these experiments were presented in the venn diagram and certain number of proteins are common in all three experiments. -
Klf5 Is Involved in Self-Renewal of Mouse Embryonic Stem Cells
Short Report 2629 Klf5 is involved in self-renewal of mouse embryonic stem cells Silvia Parisi1,2,*, Fabiana Passaro1,3,*, Luigi Aloia1,2, Ichiro Manabe4, Ryozo Nagai5, Lucio Pastore1,3 and Tommaso Russo1,3,‡ 1CEINGE Biotecnologie Avanzate, 80145 Napoli, Italy 2European School of Molecular Medicine, SEMM, 80145 Napoli, Italy 3Dipartimento di Biochimica e Biotecnologie Mediche, Università di Napoli Federico II, 80131 Napoli, Italy 4Nano-Bioengineering Education Program and 5Department of Cardiovascular Medicine, The University of Tokyo Graduate School of Medicine, 7-3-1 Hongo, Bunkyo, Tokyo 113-8655, Japan *These authors contributed equally to this work ‡Author for correspondence (e-mail: [email protected]) Accepted 15 May 2008 Journal of Cell Science 121, 2629-2634 Published by The Company of Biologists 2008 doi:10.1242/jcs.027599 Summary Self-renewal of embryonic stem cells (ESCs) is maintained by undifferentiated state by Klf5 is, at least in part, due to the a complex regulatory mechanism involving transcription factors control of Nanog and Oct3/4 transcription, because Klf5 directly Oct3/4 (Pou5f1), Nanog and Sox2. Here, we report that Klf5, a binds to the promoters of these genes and regulates their Zn-finger transcription factor of the Kruppel-like family, is transcription. involved in ESC self-renewal. Klf5 is expressed in mouse ESCs, blastocysts and primordial germ cells, and its knockdown by RNA interference alters the molecular phenotype of ESCs, Supplementary material available online at thereby preventing their correct differentiation. The ability of http://jcs.biologists.org/cgi/content/full/121/16/2629/DC1 Klf5 to maintain ESCs in the undifferentiated state is supported by the finding that differentiation of ESCs is prevented Key words: Differentiation, Kruppel-like factors, Nanog, Oct3/4, when Klf5 is constitutively expressed. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).