DOCSLIB.ORG

What Is New and Hot in Genetics of Human Atopic Dermatitis: Shifting Paradigms in the Landscape of Allergic Skin Diseases

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
What Is New and Hot in Genetics of Human Atopic Dermatitis: Shifting Paradigms in the Landscape of Allergic Skin Diseases Acta Dermatovenerol Croat 2014;22(4):313-315 LETTER TO THE EDITOR What is New and Hot in Genetics of Human Atopic Dermatitis: Shifting Paradigms in the Landscape of Allergic Skin Diseases The immunologic abnormalities in patients with of the most prominent genes responsible for barrier allergic skin diseases occur as a consequence of pri- defect. FLG has been identified as a major locus caus- mary defects residing within the epidermis, suggest- ing skin barrier deficiency; however, not all patients ing an association between skin barrier dysfunction with AD have this mutation, so AD cannot be ex- and immune abnormalities (1). The skin barrier is plained by FLG mutation (3,4). Support for barrier de- located in the uppermost layers of the epidermis, ficiency initiating AD came from flaky tail mice, which the stratum corneum, with important elements: in- have frameshift mutation in FLG and also carry an tracellular keratin filaments, intercellular lipids, and unknown gene, the Matt gene, causing a matted hair a cornified cell envelope. It plays a vital role in all ter- phenotype (1,4,5). This phenotype in flaky tail mice is restrial forms of life, due to prevention of fluid loss due to a mutation in the Tmem79/Matt gene, with no and protection from microbial and allergen invasion. expression of the encoded protein mattrin in the skin Functional lack of epidermal enzymes and structural of mutant mice. Sasaki et al. and Saunders et al. re- skin proteins compromises skin barrier integrity and port successful delineation of the genetic basis of the function. These deficiencies can even induce local flaky tail mouse phenotype (1,4,5). Flaky tail mice dis- changes in the expression of various inflammatory play a matted hair phenotype and have spontaneous mediators, suggesting the direct immunologic role dermatitis under pathogen-free conditions; and have of the epidermis in the pathogenesis of allergic skin been used over the years as a model for AD (1). These diseases (1). Primary isolated epidermal defects can mice arose spontaneously as the result of crosses result in allergy. Filaggrin (FLG), involucrin, and lo- between mice carrying a recessive mutation named ricrin are among the most important structural pro- matted (ma), and have been since maintained as teins. Also, lipids play very important role, as well as double mutants (maft) (1). It has recently been found some enzymes, such as serine proteases. Netherton that flaky tail mice carry a deletion in the mouse FLG syndrome is classic example of autosomal recessive gene, suggesting that FLG deficiency might explain disorder due to loss-of-function mutations in SPINK5, their propensity to have dermatitis, analogous with the gene encoding the SP inhibitor lymphoepithelial the situation in some human patients with AD (not Kazal-type trypsin inhibitor (LEKTI) (2). Most impor- all patients with AD have FLG mutation). Genetically tantly, mutations of filaggrin (FLG) gene, an essential engineered FLG-deficient mice display impaired bar- component of the skin barrier, are associated with rier function, but lack the propensity of spontane- ichthyosis vulgaris and atopic dermatitis (AD). AD is ous skin inflammation of flaky tail mice. Matted mice inflammatory skin disease caused by inherited skin spontaneously develop dermatitis and atopy caused barrier deficiency, with mutations in FLG predispos- by a defective skin barrier, with mutant mice having ing to development of AD. AD has highly heritable systemic sensitization after cutaneous challenge with complex trait; however, environmental influences house dust mite allergens. The matted phenotype also play a role in triggering the atopic diathesis (3,4). was found to be due to a loss-of-function mutation Genome-wide association studies in AD have identi- in Tmem79 (4,5). Unexpectedly, the Tmem79 muta- fied several susceptibility loci; however, the major and tion, rather than the deletion in FLG, was found to only functionally characterized genetic factor is FLG, be associated with the development of dermatitis in which encodes skin barrier protein FLG (4). FLG is one mice (1). Moreover, exogenous Tmem79 expression ACTA DERMATOVENEROLOGICA CROATICA 313 Letter to the editor Acta Dermatovenerol Croat 2014;22(4):313-315 was able to rescue both the hair and the dermatitis OR10A3-NLRP10, GLB1, CCDC80, CARD11, ZNF365, phenotype in flaky tail mice (1). These studies have and CYP24A1-PFDN4) (15). However, the causal vari- elucidated the relative contributions of the FLG and ants at all loci except FLG are unknown (6). Matt mutations in DM mice (1). These data indicate In conclusion, we can state that FLG has been, and that the DM mouse is not a true model of FLG defi- still remains the major susceptibility gene in patients ciency-associated AD-like skin (3). Tmem79 is mainly with AD, but genetic pathways in atopic patients are expressed in the granular layers of the epidermis, complex and influenced by the environment, includ- where its absence correlates with abnormal function ing multiple genes involved in skin barrier, as well of lamellar granules (1,5). Those lamellar granules are as proteins, lipids, and enyzmes interacting with im- Golgi-derived specialized organelles, responsible for mune system. Therefore, we have many future lessons transferring lipids and proteases to the upper part of to learn from the genetics of atopic diseases. the epidermis (5). Therefore, Mattrin could be a link between protein and lipid interaction in etiopatholo- References gy of AD. Meta-analysis of 4.245 AD cases and 10.558 1. Sprecher E, Leung DY. Atopic dermatitis: Scrat- population-matched control patients showed that a ching through the complexity of barrier dysfunc- missense SNP, rs6694514, in the human Matt gene tion. J Allergy Clin Immunol 2013;132:1130-1. has a small but significant association with AD (3). Expression quantitative trait locus analysis showed 2. PM Elias. Skin barrier function. Curr Allergy Asth- that Matt is in a network of proteins expressed late in ma Rep 2008;8:299-305. epidermal differentiation, with an expression quanti- 3. Palmer CN, Irvine AD, Terron-Kwiatkowski A, Zhao tative trait locus profile closely matching that of Rhbg Y, Liao H, Lee SP, et al. Common loss-of-function (transporter protein) and Rab25 (membrane traffick- variants of the epidermal barrier protein filaggrin ing) (4). Mattrin shows distant sequence homology are a major predisposing factor for atopic derma- to the membrane- associated proteins in eicosanoid titis. Nat Genet 2006;38:441-6. and glutathione metabolism (MAPEG) protein family 4. Saunders SP, Goh CS, Brown SJ, Palmer CN, Por- (4). Matt mutation results in defective expression of ter RM, Cole C, et al. Tmem79/Matt is the matted the transmembrane protein mattrin, which is highly mouse gene and is a predisposing gene for atopic expressed in the upper granular layer of epidermal dermatitis in human subjects. J Allergy Clin Im- keratinocytes, with a predicted role in lipid homeo- munol 2013;132:1121-9. stasis. It is interesting to mention that authors noted 5. Sasaki T, Shiohama A, Kubo A, Kawasaki H, Ishida- that FLG mutation has a neonatal influence, whereas Yamamoto A, et al. A homozygous nonsense mu- Matt mutation shows progressive influence with age. tation in the gene for Tmem79, a component for This indicates the polygenic nature of the DM mouse the lamellar granule secretory system, produces as an AD model and indicates the differential influ- spontaneous eczema in an experimental mo- ence of both the FLG and Matt mutations (4). del of atopic dermatitis. J Allergy Clin Immunol Recently, four new susceptibility loci for AD were 2013;132:1111-20. identified and previous associations were replicated, 6. Ellinghaus D, Baurecht H, Esparza-Gordillo J, Rod- which brings the number of AD-risk loci reported in ríguez E, Matanovic A, Marenholz I, et al. High- individuals of European ancestry to 11 (7). It is esti- density genotyping study identifies four new mated that together, these susceptibility loci account susceptibility loci for atopic dermatitis. Nat Genet for 14.4% of the heritability for AD (7). Genome-wide 2013;45:808-12. association studies (GWAS) have shown remarkable overlap across immune-mediated diseases (7). Two 7. Zhernakova, A., van Diemen, C.C. & Wijmenga, C. Detecting shared pathogenesis from the shared European GWAS on AD established four susceptibil- genetics of immune-related diseases. Nat Rev Ge- ity loci (C11orf30, OVOL1, ACTL9 and RAD50-IL13- net 2009;10:43-55. KIF3A) in addition to FLG (4-6). At C11orf30, the same allele also confers risk to asthma and Crohn’s disease 8. Esparza-Gordillo J, Weidinger S, Fölster-Holst (5,9-11). For RAD50-IL13, locus agonistic effects were R, Bauerfeind A, Ruschendorf F, Patone G, et al. observed for asthma, and locus antagonistic effects A common variant on chromosome 11q13 is were observed for psoriasis (6,12,13). Two further loci associated with atopic dermatitis. Nat Genet were reported in a Chinese GWAS (TNFRSF6B-ZGPAT 2009;41:596-601. and TMEM232-SLC25A46) (14). All loci were confirmed 9. Paternoster L, Standl M, Chen CM, Ramasamy in a recent Japanese GWAS, which additionally re- A, Bønnelykke K, Duijts L, et al. Meta-analysis of ported eight new loci (IL1RL1-IL18R1-IL18RAP, MHC, genome-wide association studies identifies th- 314 ACTA DERMATOVENEROLOGICA CROATICA Letter to the editor Acta Dermatovenerol Croat 2014;22(4):313-315 ree new risk loci for atopic dermatitis. Nat Genet 15. Hirota T, Takahashi A, Kubo M, Tsunoda T, Tomita 2012;44:187-92. K, Sakashita M, et al. Genome-wide association 10. Marenholz I, Bauerfeind A, Esparza-Gordillo J, study identifies eight new susceptibility loci for Kerscher T, Granell R, Nickel R, et al. The eczema atopic dermatitis in the Japanese population. Nat risk variant on chromosome 11q13 (rs7927894) Genet 2012;44:1222-6.
Load more

Recommended publications
  • 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
    [Show full text]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]
  • An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors
    Ecology and Evolutionary Biology 2021; 6(3): 53-77 http://www.sciencepublishinggroup.com/j/eeb doi: 10.11648/j.eeb.20210603.11 ISSN: 2575-3789 (Print); ISSN: 2575-3762 (Online) An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors Miguel Angel Fuertes*, Carlos Alonso Department of Microbiology, Centre for Molecular Biology “Severo Ochoa”, Spanish National Research Council and Autonomous University, Madrid, Spain Email address: *Corresponding author To cite this article: Miguel Angel Fuertes, Carlos Alonso. An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors. Ecology and Evolutionary Biology. Vol. 6, No. 3, 2021, pp. 53-77. doi: 10.11648/j.eeb.20210603.11 Received: April 24, 2021; Accepted: May 11, 2021; Published: July 13, 2021 Abstract: Capturing conserved patterns in genes and proteins is important for inferring phenotype prediction and evolutionary analysis. The study is focused on the conserved patterns of the G protein-coupled receptors, an important superfamily of receptors. Olfactory receptors represent more than 2% of our genome and constitute the largest family of G protein-coupled receptors, a key class of drug targets. As no crystallographic structures are available, mechanistic studies rely on the use of molecular dynamic modelling combined with site-directed mutagenesis data. In this paper, we hypothesized that human-mouse orthologs coding for G protein-coupled receptors maintain, at speciation events, shared compositional structures independent, to some extent, of their percent identity as reveals a method based in the categorization of nucleotide triplets by their gross composition. The data support the consistency of the hypothesis, showing in ortholog G protein-coupled receptors the presence of emergent shared compositional structures preserved at speciation events.
    [Show full text]
  • Sean Raspet – Molecules
    1. Commercial name: Fructaplex© IUPAC Name: 2-(3,3-dimethylcyclohexyl)-2,5,5-trimethyl-1,3-dioxane SMILES: CC1(C)CCCC(C1)C2(C)OCC(C)(C)CO2 Molecular weight: 240.39 g/mol Volume (cubic Angstroems): 258.88 Atoms number (non-hydrogen): 17 miLogP: 4.43 Structure: Biological Properties: Predicted Druglikenessi: GPCR ligand -0.23 Ion channel modulator -0.03 Kinase inhibitor -0.6 Nuclear receptor ligand 0.15 Protease inhibitor -0.28 Enzyme inhibitor 0.15 Commercial name: Fructaplex© IUPAC Name: 2-(3,3-dimethylcyclohexyl)-2,5,5-trimethyl-1,3-dioxane SMILES: CC1(C)CCCC(C1)C2(C)OCC(C)(C)CO2 Predicted Olfactory Receptor Activityii: OR2L13 83.715% OR1G1 82.761% OR10J5 80.569% OR2W1 78.180% OR7A2 77.696% 2. Commercial name: Sylvoxime© IUPAC Name: N-[4-(1-ethoxyethenyl)-3,3,5,5tetramethylcyclohexylidene]hydroxylamine SMILES: CCOC(=C)C1C(C)(C)CC(CC1(C)C)=NO Molecular weight: 239.36 Volume (cubic Angstroems): 252.83 Atoms number (non-hydrogen): 17 miLogP: 4.33 Structure: Biological Properties: Predicted Druglikeness: GPCR ligand -0.6 Ion channel modulator -0.41 Kinase inhibitor -0.93 Nuclear receptor ligand -0.17 Protease inhibitor -0.39 Enzyme inhibitor 0.01 Commercial name: Sylvoxime© IUPAC Name: N-[4-(1-ethoxyethenyl)-3,3,5,5tetramethylcyclohexylidene]hydroxylamine SMILES: CCOC(=C)C1C(C)(C)CC(CC1(C)C)=NO Predicted Olfactory Receptor Activity: OR52D1 71.900% OR1G1 70.394% 0R52I2 70.392% OR52I1 70.390% OR2Y1 70.378% 3. Commercial name: Hyperflor© IUPAC Name: 2-benzyl-1,3-dioxan-5-one SMILES: O=C1COC(CC2=CC=CC=C2)OC1 Molecular weight: 192.21 g/mol Volume
    [Show full text]
  • Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib
    Supplementary Online Content Chen G, McQuade JL, Panka DJ, et al. Clinical, molecular and immune analysis of dabrafenib-trametinib combination treatment for metastatic melanoma that progressed during BRAF inhibitor monotherapy: a phase 2 clinical trial. JAMA Oncology. Published online April 28, 2016. doi:10.1001/jamaoncol.2016.0509. eMethods. eReferences. eTable 1. Clinical efficacy eTable 2. Adverse events eTable 3. Correlation of baseline patient characteristics with treatment outcomes eTable 4. Patient responses and baseline IHC results eFigure 1. Kaplan-Meier analysis of overall survival eFigure 2. Correlation between IHC and RNAseq results eFigure 3. pPRAS40 expression and PFS eFigure 4. Baseline and treatment-induced changes in immune infiltrates eFigure 5. PD-L1 expression eTable 5. Nonsynonymous mutations detected by WES in baseline tumors This supplementary material has been provided by the authors to give readers additional information about their work. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eMethods Whole exome sequencing Whole exome capture libraries for both tumor and normal samples were constructed using 100ng genomic DNA input and following the protocol as described by Fisher et al.,3 with the following adapter modification: Illumina paired end adapters were replaced with palindromic forked adapters with unique 8 base index sequences embedded within the adapter. In-solution hybrid selection was performed using the Illumina Rapid Capture Exome enrichment kit with 38Mb target territory (29Mb baited). The targeted region includes 98.3% of the intervals in the Refseq exome database. Dual-indexed libraries were pooled into groups of up to 96 samples prior to hybridization.
    [Show full text]
  • Supplementary Data
    SUPPLEMENTARY METHODS 1) Characterisation of OCCC cell line gene expression profiles using Prediction Analysis for Microarrays (PAM) The ovarian cancer dataset from Hendrix et al (25) was used to predict the phenotypes of the cell lines used in this study. Hendrix et al (25) analysed a series of 103 ovarian samples using the Affymetrix U133A array platform (GEO: GSE6008). This dataset comprises clear cell (n=8), endometrioid (n=37), mucinous (n=13) and serous epithelial (n=41) primary ovarian carcinomas and samples from 4 normal ovaries. To build the predictor, the Prediction Analysis of Microarrays (PAM) package in R environment was employed (http://rss.acs.unt.edu/Rdoc/library/pamr/html/00Index.html). When more than one probe described the expression of a given gene, we used the probe with the highest median absolute deviation across the samples. The dataset from Hendrix et al. (25) and the dataset of OCCC cell lines described in this manuscript were then overlaid on the basis of 11536 common unique HGNC gene symbols. Only the 99 primary ovarian cancers samples and the four normal ovary samples were used to build the predictor. Following leave one out cross-validation, a predictor based upon 126 genes was able to identify correctly the four distinct phenotypes of primary ovarian tumour samples with a misclassification rate of 18.3%. This predictor was subsequently applied to the expression data from the 12 OCCC cell lines to determine the likeliest phenotype of the OCCC cell lines compared to primary ovarian cancers. Posterior probabilities were estimated for each cell line in comparison to the following phenotypes: clear cell, endometrioid, mucinous and serous epithelial.
    [Show full text]
  • Us 2018 / 0305689 A1
    US 20180305689A1 ( 19 ) United States (12 ) Patent Application Publication ( 10) Pub . No. : US 2018 /0305689 A1 Sætrom et al. ( 43 ) Pub . Date: Oct. 25 , 2018 ( 54 ) SARNA COMPOSITIONS AND METHODS OF plication No . 62 /150 , 895 , filed on Apr. 22 , 2015 , USE provisional application No . 62/ 150 ,904 , filed on Apr. 22 , 2015 , provisional application No. 62 / 150 , 908 , (71 ) Applicant: MINA THERAPEUTICS LIMITED , filed on Apr. 22 , 2015 , provisional application No. LONDON (GB ) 62 / 150 , 900 , filed on Apr. 22 , 2015 . (72 ) Inventors : Pål Sætrom , Trondheim (NO ) ; Endre Publication Classification Bakken Stovner , Trondheim (NO ) (51 ) Int . CI. C12N 15 / 113 (2006 .01 ) (21 ) Appl. No. : 15 /568 , 046 (52 ) U . S . CI. (22 ) PCT Filed : Apr. 21 , 2016 CPC .. .. .. C12N 15 / 113 ( 2013 .01 ) ; C12N 2310 / 34 ( 2013. 01 ) ; C12N 2310 /14 (2013 . 01 ) ; C12N ( 86 ) PCT No .: PCT/ GB2016 /051116 2310 / 11 (2013 .01 ) $ 371 ( c ) ( 1 ) , ( 2 ) Date : Oct . 20 , 2017 (57 ) ABSTRACT The invention relates to oligonucleotides , e . g . , saRNAS Related U . S . Application Data useful in upregulating the expression of a target gene and (60 ) Provisional application No . 62 / 150 ,892 , filed on Apr. therapeutic compositions comprising such oligonucleotides . 22 , 2015 , provisional application No . 62 / 150 ,893 , Methods of using the oligonucleotides and the therapeutic filed on Apr. 22 , 2015 , provisional application No . compositions are also provided . 62 / 150 ,897 , filed on Apr. 22 , 2015 , provisional ap Specification includes a Sequence Listing . SARNA sense strand (Fessenger 3 ' SARNA antisense strand (Guide ) Mathew, Si Target antisense RNA transcript, e . g . NAT Target Coding strand Gene Transcription start site ( T55 ) TY{ { ? ? Targeted Target transcript , e .
    [Show full text]
  • A CRISPR Screen to Identify Combination Therapies of Cytotoxic
    CRISPRi Screens to Identify Combination Therapies for the Improved Treatment of Ovarian Cancer By Erika Daphne Handly B.S. Chemical Engineering Brigham Young University, 2014 Submitted to the Department of Biological Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biological Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2021 © 2020 Massachusetts Institute of Technology. All rights reserved. Signature of author………………………………………………………………………………… Erika Handly Department of Biological Engineering February 2021 Certified by………………………………………………………………………………………… Michael Yaffe Director MIT Center for Precision Cancer Medicine Department of Biological Engineering and Biology Thesis Supervisor Accepted by………………………………………………………………………………………... Katharina Ribbeck Professor of Biological Engineering Chair of Graduate Program, Department of Biological Engineering Thesis Committee members Michael T. Hemann, Ph.D. Associate Professor of Biology Massachusetts Institute of Technology Douglas A. Lauffenburger, Ph.D. (Chair) Ford Professor of Biological Engineering, Chemical Engineering, and Biology Massachusetts Institute of Technology Michael B. Yaffe, M.D., Ph.D. (Thesis Supervisor) David H. Koch Professor of Science Prof. of Biology and Biological Engineering Massachusetts Institute of Technology 2 CRISPRi Screens to Identify Combination Therapies for the Improved Treatment of Ovarian Cancer By Erika Daphne Handly B.S. Chemical Engineering Brigham Young University, 2014 Submitted to the Department of Biological Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biological Engineering ABSTRACT Ovarian cancer is the fifth leading cause of cancer death for women in the United States, with only modest improvements in patient survival in the past few decades. Standard-of-care consists of surgical debulking followed by a combination of platinum and taxane agents, but relapse and resistance frequently occur.
    [Show full text]
  • Explorations in Olfactory Receptor Structure and Function by Jianghai
    Explorations in Olfactory Receptor Structure and Function by Jianghai Ho Department of Neurobiology Duke University Date:_______________________ Approved: ___________________________ Hiroaki Matsunami, Supervisor ___________________________ Jorg Grandl, Chair ___________________________ Marc Caron ___________________________ Sid Simon ___________________________ [Committee Member Name] Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Neurobiology in the Graduate School of Duke University 2014 ABSTRACT Explorations in Olfactory Receptor Structure and Function by Jianghai Ho Department of Neurobiology Duke University Date:_______________________ Approved: ___________________________ Hiroaki Matsunami, Supervisor ___________________________ Jorg Grandl, Chair ___________________________ Marc Caron ___________________________ Sid Simon ___________________________ [Committee Member Name] An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Neurobiology in the Graduate School of Duke University 2014 Copyright by Jianghai Ho 2014 Abstract Olfaction is one of the most primitive of our senses, and the olfactory receptors that mediate this very important chemical sense comprise the largest family of genes in the mammalian genome. It is therefore surprising that we understand so little of how olfactory receptors work. In particular we have a poor idea of what chemicals are detected by most of the olfactory receptors in the genome, and for those receptors which we have paired with ligands, we know relatively little about how the structure of these ligands can either activate or inhibit the activation of these receptors. Furthermore the large repertoire of olfactory receptors, which belong to the G protein coupled receptor (GPCR) superfamily, can serve as a model to contribute to our broader understanding of GPCR-ligand binding, especially since GPCRs are important pharmaceutical targets.
    [Show full text]
  • Cellular Features Predicting Susceptibility to Ferroptosis: Insights from Cancer Cell-Line Profiling
    Cellular features predicting susceptibility to ferroptosis: insights from cancer cell-line profiling Vasanthi Sridhar Viswanathan Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2015 © 2015 Vasanthi Sridhar Viswanathan All rights reserved ABSTRACT Cellular features predicting susceptibility to ferroptosis: insights from cancer cell-line profiling Vasanthi Sridhar Viswanathan Ferroptosis is a novel non-apoptotic, oxidative form of regulated cell death that can be triggered by diverse small-molecule ferroptosis inducers (FINs) and genetic perturbations. Current lack of insights into the cellular contexts governing sensitivity to ferroptosis has hindered both translation of FINs as anti-cancer agents for specific indications and the discovery of physiological contexts where ferroptosis may function as a form of programmed cell death. This dissertation describes the identification of cellular features predicting susceptibility to ferroptosis from data generated through a large-scale profiling experiment that screened four FINs against a panel of 860 omically-characterized cancer cell lines (Cancer Therapeutics Response Portal Version 2; CTRPv2 at http://www.broadinstitute.org/ctrp/). Using correlative approaches incorporating transcriptomic, metabolomic, proteomic, and gene-dependency feature types, I uncover both pan-lineage and lineage-specific features mediating cell-line response to FINs. The first key finding from these analyses implicates high expression of sulfur and selenium metabolic pathways in conferring resistance to FINs across lineages. In contrast, the transsulfuration pathway, which enables de novo cysteine synthesis, appears to plays a role in ferroptosis resistance in a subset of lineages. The second key finding from these studies identifies cancer cells in a high mesenchymal state as being uniquely primed to undergo ferroptosis.
    [Show full text]
  • Online Supporting Information S2: Proteins in Each Negative Pathway
    Online Supporting Information S2: Proteins in each negative pathway Index Proteins ADO,ACTA1,DEGS2,EPHA3,EPHB4,EPHX2,EPOR,EREG,FTH1,GAD1,HTR6, IGF1R,KIR2DL4,NCR3,NME7,NOTCH1,OR10S1,OR2T33,OR56B4,OR7A10, Negative_1 OR8G1,PDGFC,PLCZ1,PROC,PRPS2,PTAFR,SGPP2,STMN1,VDAC3,ATP6V0 A1,MAPKAPK2 DCC,IDS,VTN,ACTN2,AKR1B10,CACNA1A,CHIA,DAAM2,FUT5,GCLM,GNAZ Negative_2 ,ITPA,NEU4,NTF3,OR10A3,PAPSS1,PARD3,PLOD1,RGS3,SCLY,SHC1,TN FRSF4,TP53 Negative_3 DAO,CACNA1D,HMGCS2,LAMB4,OR56A3,PRKCQ,SLC25A5 IL5,LHB,PGD,ADCY3,ALDH1A3,ATP13A2,BUB3,CD244,CYFIP2,EPHX2,F CER1G,FGD1,FGF4,FZD9,HSD17B7,IL6R,ITGAV,LEFTY1,LIPG,MAN1C1, Negative_4 MPDZ,PGM1,PGM3,PIGM,PLD1,PPP3CC,TBXAS1,TKTL2,TPH2,YWHAQ,PPP 1R12A HK2,MOS,TKT,TNN,B3GALT4,B3GAT3,CASP7,CDH1,CYFIP1,EFNA5,EXTL 1,FCGR3B,FGF20,GSTA5,GUK1,HSD3B7,ITGB4,MCM6,MYH3,NOD1,OR10H Negative_5 1,OR1C1,OR1E1,OR4C11,OR56A3,PPA1,PRKAA1,PRKAB2,RDH5,SLC27A1 ,SLC2A4,SMPD2,STK36,THBS1,SERPINC1 TNR,ATP5A1,CNGB1,CX3CL1,DEGS1,DNMT3B,EFNB2,FMO2,GUCY1B3,JAG Negative_6 2,LARS2,NUMB,PCCB,PGAM1,PLA2G1B,PLOD2,PRDX6,PRPS1,RFXANK FER,MVD,PAH,ACTC1,ADCY4,ADCY8,CBR3,CLDN16,CPT1A,DDOST,DDX56 ,DKK1,EFNB1,EPHA8,FCGR3A,GLS2,GSTM1,GZMB,HADHA,IL13RA2,KIR2 Negative_7 DS4,KLRK1,LAMB4,LGMN,MAGI1,NUDT2,OR13A1,OR1I1,OR4D11,OR4X2, OR6K2,OR8B4,OXCT1,PIK3R4,PPM1A,PRKAG3,SELP,SPHK2,SUCLG1,TAS 1R2,TAS1R3,THY1,TUBA1C,ZIC2,AASDHPPT,SERPIND1 MTR,ACAT2,ADCY2,ATP5D,BMPR1A,CACNA1E,CD38,CYP2A7,DDIT4,EXTL Negative_8 1,FCER1G,FGD3,FZD5,ITGAM,MAPK8,NR4A1,OR10V1,OR4F17,OR52D1,O R8J3,PLD1,PPA1,PSEN2,SKP1,TACR3,VNN1,CTNNBIP1 APAF1,APOA1,CARD11,CCDC6,CSF3R,CYP4F2,DAPK1,FLOT1,GSTM1,IL2
    [Show full text]
  • Impact of Non-Thermal Plasma on Cell Signaling in Keratinocytes
    Impact of non-thermal plasma on cell signaling in keratinocytes Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) der Mathematisch-Naturwissenschaftlichen Fakultät der Ernst-Moritz-Arndt-Universität Greifswald vorgelegt von Annemarie Barton geboren am 12.04.1986 in Bielefeld Greifswald, Dezember 2013 Dekan: Prof. Dr. Klaus Fesser 1. Gutachter: Prof. Dr. Ulrike Lindequist 2. Gutachter: Prof. Dr. David Graves Datum der Verteidigung: 24.04.2014 Contents 1 Introduction 5 1.1 Plasma . .5 1.2 Human Skin . .7 1.3 Wound Healing . .8 1.3.1 Acute wound . .8 1.3.2 Chronic wound . 11 1.4 Plasma medicine . 13 1.5 Aim of the work . 14 2 Materials and Methods 15 2.1 Materials . 15 2.1.1 Chemicals and solutions . 15 2.1.2 General laboratory equipment . 16 2.1.3 Kits . 16 2.1.4 Instruments . 17 2.1.5 Software . 18 2.1.6 Buffers and solutions . 19 2.2 Methods . 19 2.2.1 Cell culture . 19 2.2.2 Plasma source . 20 2.2.3 Plasma treatment . 22 2.2.4 Preparation of conditioned medium . 23 2.2.5 Co-culture with keratinocytes and monocytes . 24 2.2.6 Cell survival . 25 2.2.7 Gene expression analysis . 26 2.2.8 Protein expression analysis . 32 3 Results 34 3.1 Impact of plasma on HaCaT cells . 34 3.1.1 Cell survival . 34 3.1.2 Transcription profile . 36 3.1.3 Secretion profile . 44 3.2 Impact of the shielding gas . 48 3.2.1 Cell survival .
    [Show full text]