Table SI. Primer List of Genes Used for Reverse Transcription‑Quantitative PCR Validation
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Combination of Photodynamic Therapy with Fenretinide and C6
Wayne State University Wayne State University Theses 1-1-2015 Combination Of Photodynamic Therapy With Fenretinide And C6-Pyridinium Ceramide Enhances Killing Of Scc17b Human Head And Neck Squamous Cell Carcinoma Cells Via The eD Novo Sphingolipid Biosynthesis And Mitochondrial Apoptosis Nithin Bhargava Boppana Wayne State University, Follow this and additional works at: https://digitalcommons.wayne.edu/oa_theses Part of the Medicinal Chemistry and Pharmaceutics Commons Recommended Citation Boppana, Nithin Bhargava, "Combination Of Photodynamic Therapy With Fenretinide And C6-Pyridinium Ceramide Enhances Killing Of Scc17b Human Head And Neck Squamous Cell Carcinoma Cells Via The eD Novo Sphingolipid Biosynthesis And Mitochondrial Apoptosis" (2015). Wayne State University Theses. 431. https://digitalcommons.wayne.edu/oa_theses/431 This Open Access Thesis is brought to you for free and open access by DigitalCommons@WayneState. It has been accepted for inclusion in Wayne State University Theses by an authorized administrator of DigitalCommons@WayneState. COMBINATION OF PHOTODYNAMIC THERAPY WITH FENRETINIDE AND C6-PYRIDINIUM CERAMIDE ENHANCES KILLING OF SCC17B HUMAN HEAD AND NECK SQUAMOUS CELL CARCINOMA CELLS VIA THE DE NOVO SPHINGOLIPID BIOSYNTHESIS AND MITOCHONDRIAL APOPTOSIS by NITHIN BHARGAVA BOPPANA THESIS Submitted to the Graduate School of Wayne State University, Detroit, Michigan in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE 2015 MAJOR: PHARMACEUTICAL SCIENCES Approved By: ________________________________ Advisor Date © COPYRIGHT BY NITHIN BHARGAVA BOPPANA 2015 All Rights Reserved DEDICATION Dedicated to my mom Rekha Vasireddy for always believing in me and helping me in becoming the person who I am today. ii ACKNOWLEDGEMENTS I am grateful to my advisor, Dr. Duska Separovic for her invaluable mentorship throughout the project. -
Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
Cell Reprogramming Technologies for Treatment And
CELL REPROGRAMMING TECHNOLOGIES FOR TREATMENT AND UNDERSTANDING OF GENETIC DISORDERS OF MYELIN by ANGELA MARIE LAGER Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Thesis advisor: Paul J Tesar, PhD Department of Genetics and Genome Sciences CASE WESTERN RESERVE UNIVERSITY May 2015 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Angela Marie Lager Candidate for the Doctor of Philosophy degree*. (signed) Ronald A Conlon, PhD (Committee Chair) Paul J Tesar, PhD (Advisor) Craig A Hodges, PhD Warren J Alilain, PhD (date) 31 March 2015 *We also certify that written approval has been obtained from any proprietary material contained therein. TABLE OF CONTENTS Table of Contents……………………………………………………………………….1 List of Figures……………………………………………………………………………4 Acknowledgements……………………………………………………………………..7 Abstract…………………………………………………………………………………..8 Chapter 1: Introduction and Background………………………………………..11 1.1 Overview of mammalian oligodendrocyte development in the spinal cord and myelination of the central nervous system…………………..11 1.1.1 Introduction……………………………………………………..11 1.1.2 The establishment of the neuroectoderm and ventral formation of the neural tube…………………………………..12 1.1.3 Ventral patterning of the neural tube and specification of the pMN domain in the spinal cord……………………………….15 1.1.4 Oligodendrocyte progenitor cell production through the process of gliogenesis ………………………………………..16 1.1.5 Oligodendrocyte progenitor cell to oligodendrocyte differentiation…………………………………………………...22 -
ONLINE SUPPLEMENTARY TABLE Table 2. Differentially Expressed
ONLINE SUPPLEMENTARY TABLE Table 2. Differentially Expressed Probe Sets in Livers of GK Rats. A. Immune/Inflammatory (67 probe sets, 63 genes) Age Strain Probe ID Gene Name Symbol Accession Gene Function 5 WKY 1398390_at small inducible cytokine B13 precursor Cxcl13 AA892854 chemokine activity; lymph node development 5 WKY 1389581_at interleukin 33 Il33 BF390510 cytokine activity 5 WKY *1373970_at interleukin 33 Il33 AI716248 cytokine activity 5 WKY 1369171_at macrophage stimulating 1 (hepatocyte growth factor-like) Mst1; E2F2 NM_024352 serine-throenine kinase; tumor suppression 5 WKY 1388071_x_at major histocompatability antigen Mhc M24024 antigen processing and presentation 5 WKY 1385465_at sialic acid binding Ig-like lectin 5 Siglec5 BG379188 sialic acid-recognizing receptor 5 WKY 1393108_at major histocompatability antigen Mhc BM387813 antigen processing and presentation 5 WKY 1388202_at major histocompatability antigen Mhc BI395698 antigen processing and presentation 5 WKY 1371171_at major histocompatability antigen Mhc M10094 antigen processing and presentation 5 WKY 1370382_at major histocompatability antigen Mhc BI279526 antigen processing and presentation 5 WKY 1371033_at major histocompatability antigen Mhc AI715202 antigen processing and presentation 5 WKY 1383991_at leucine rich repeat containing 8 family, member E Lrrc8e BE096426 proliferation and activation of lymphocytes and monocytes. 5 WKY 1383046_at complement component factor H Cfh; Fh AA957258 regulation of complement cascade 4 WKY 1369522_a_at CD244 natural killer -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
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. -
CD Markers Are Routinely Used for the Immunophenotyping of Cells
ptglab.com 1 CD MARKER ANTIBODIES www.ptglab.com Introduction The cluster of differentiation (abbreviated as CD) is a protocol used for the identification and investigation of cell surface molecules. So-called CD markers are routinely used for the immunophenotyping of cells. Despite this use, they are not limited to roles in the immune system and perform a variety of roles in cell differentiation, adhesion, migration, blood clotting, gamete fertilization, amino acid transport and apoptosis, among many others. As such, Proteintech’s mini catalog featuring its antibodies targeting CD markers is applicable to a wide range of research disciplines. PRODUCT FOCUS PECAM1 Platelet endothelial cell adhesion of blood vessels – making up a large portion molecule-1 (PECAM1), also known as cluster of its intracellular junctions. PECAM-1 is also CD Number of differentiation 31 (CD31), is a member of present on the surface of hematopoietic the immunoglobulin gene superfamily of cell cells and immune cells including platelets, CD31 adhesion molecules. It is highly expressed monocytes, neutrophils, natural killer cells, on the surface of the endothelium – the thin megakaryocytes and some types of T-cell. Catalog Number layer of endothelial cells lining the interior 11256-1-AP Type Rabbit Polyclonal Applications ELISA, FC, IF, IHC, IP, WB 16 Publications Immunohistochemical of paraffin-embedded Figure 1: Immunofluorescence staining human hepatocirrhosis using PECAM1, CD31 of PECAM1 (11256-1-AP), Alexa 488 goat antibody (11265-1-AP) at a dilution of 1:50 anti-rabbit (green), and smooth muscle KD/KO Validated (40x objective). alpha-actin (red), courtesy of Nicola Smart. PECAM1: Customer Testimonial Nicola Smart, a cardiovascular researcher “As you can see [the immunostaining] is and a group leader at the University of extremely clean and specific [and] displays Oxford, has said of the PECAM1 antibody strong intercellular junction expression, (11265-1-AP) that it “worked beautifully as expected for a cell adhesion molecule.” on every occasion I’ve tried it.” Proteintech thanks Dr. -
HCC and Cancer Mutated Genes Summarized in the Literature Gene Symbol Gene Name References*
HCC and cancer mutated genes summarized in the literature Gene symbol Gene name References* A2M Alpha-2-macroglobulin (4) ABL1 c-abl oncogene 1, receptor tyrosine kinase (4,5,22) ACBD7 Acyl-Coenzyme A binding domain containing 7 (23) ACTL6A Actin-like 6A (4,5) ACTL6B Actin-like 6B (4) ACVR1B Activin A receptor, type IB (21,22) ACVR2A Activin A receptor, type IIA (4,21) ADAM10 ADAM metallopeptidase domain 10 (5) ADAMTS9 ADAM metallopeptidase with thrombospondin type 1 motif, 9 (4) ADCY2 Adenylate cyclase 2 (brain) (26) AJUBA Ajuba LIM protein (21) AKAP9 A kinase (PRKA) anchor protein (yotiao) 9 (4) Akt AKT serine/threonine kinase (28) AKT1 v-akt murine thymoma viral oncogene homolog 1 (5,21,22) AKT2 v-akt murine thymoma viral oncogene homolog 2 (4) ALB Albumin (4) ALK Anaplastic lymphoma receptor tyrosine kinase (22) AMPH Amphiphysin (24) ANK3 Ankyrin 3, node of Ranvier (ankyrin G) (4) ANKRD12 Ankyrin repeat domain 12 (4) ANO1 Anoctamin 1, calcium activated chloride channel (4) APC Adenomatous polyposis coli (4,5,21,22,25,28) APOB Apolipoprotein B [including Ag(x) antigen] (4) AR Androgen receptor (5,21-23) ARAP1 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 1 (4) ARHGAP35 Rho GTPase activating protein 35 (21) ARID1A AT rich interactive domain 1A (SWI-like) (4,5,21,22,24,25,27,28) ARID1B AT rich interactive domain 1B (SWI1-like) (4,5,22) ARID2 AT rich interactive domain 2 (ARID, RFX-like) (4,5,22,24,25,27,28) ARID4A AT rich interactive domain 4A (RBP1-like) (28) ARID5B AT rich interactive domain 5B (MRF1-like) (21) ASPM Asp (abnormal -
Supplementary File 2A Revised
Supplementary file 2A. Differentially expressed genes in aldosteronomas compared to all other samples, ranked according to statistical significance. Missing values were not allowed in aldosteronomas, but to a maximum of five in the other samples. Acc UGCluster Name Symbol log Fold Change P - Value Adj. P-Value B R99527 Hs.8162 Hypothetical protein MGC39372 MGC39372 2,17 6,3E-09 5,1E-05 10,2 AA398335 Hs.10414 Kelch domain containing 8A KLHDC8A 2,26 1,2E-08 5,1E-05 9,56 AA441933 Hs.519075 Leiomodin 1 (smooth muscle) LMOD1 2,33 1,3E-08 5,1E-05 9,54 AA630120 Hs.78781 Vascular endothelial growth factor B VEGFB 1,24 1,1E-07 2,9E-04 7,59 R07846 Data not found 3,71 1,2E-07 2,9E-04 7,49 W92795 Hs.434386 Hypothetical protein LOC201229 LOC201229 1,55 2,0E-07 4,0E-04 7,03 AA454564 Hs.323396 Family with sequence similarity 54, member B FAM54B 1,25 3,0E-07 5,2E-04 6,65 AA775249 Hs.513633 G protein-coupled receptor 56 GPR56 -1,63 4,3E-07 6,4E-04 6,33 AA012822 Hs.713814 Oxysterol bining protein OSBP 1,35 5,3E-07 7,1E-04 6,14 R45592 Hs.655271 Regulating synaptic membrane exocytosis 2 RIMS2 2,51 5,9E-07 7,1E-04 6,04 AA282936 Hs.240 M-phase phosphoprotein 1 MPHOSPH -1,40 8,1E-07 8,9E-04 5,74 N34945 Hs.234898 Acetyl-Coenzyme A carboxylase beta ACACB 0,87 9,7E-07 9,8E-04 5,58 R07322 Hs.464137 Acyl-Coenzyme A oxidase 1, palmitoyl ACOX1 0,82 1,3E-06 1,2E-03 5,35 R77144 Hs.488835 Transmembrane protein 120A TMEM120A 1,55 1,7E-06 1,4E-03 5,07 H68542 Hs.420009 Transcribed locus 1,07 1,7E-06 1,4E-03 5,06 AA410184 Hs.696454 PBX/knotted 1 homeobox 2 PKNOX2 1,78 2,0E-06