Astra ZenecaJan07.ppt

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Published on November 24, 2008

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Expression of genes involved in oxidative stress responses in airway epithelial cells of COPD smokers : Expression of genes involved in oxidative stress responses in airway epithelial cells of COPD smokers Per Broberg Biological Sciences AstraZeneca R&D Lund Outline : Outline AstraZeneca Introduction to Chronic Obstructive Pulmonary Disease (COPD; KOL = Kronisk Obstruktiv Lungesygdom), disease classification, pathobiology. Comparison of Affymetrix studies on epithelial brushings. A set of genes induced by smoke. Transcription factors. Slide 3: David R Brennan, Chief Executive Officer Employees around the world 2004 : Employees around the world 2004 TOTAL 64,000 R&D 12,000 Sales and marketing 31,000 Other 6,000 Production 15,000 Slide 5: Top 10 pharmaceutical companiesSales (MUSD) Source: IMS Health, IMS MIDAS, 46 countries MAT/Qtr4 2004 Slide 6: Sales(MUSD) Sales per therapeutic area : Sales per therapeutic area Respiratory andInflammation 12% Other 6% Gastrointestinal 28% Cardiovascular 22% Oncology 16% Neuroscience 16% Slide 8: Sales by therapeutic area(MUSD) Neuroscience +19% Oncology +16% Respiratory and Inflammation Gastrointestinal -4% Cardiovascular +17% Infection +7% +8% % growth CER The Gastric Proton Pump - Losec : The Gastric Proton Pump - Losec Nexium ® : Nexium ® The first acid pump inhibitor to show superiority over Losec ® Effective healing and fast symptom relief of reflux oesophagitis Healing of duodenal ulcers after one week Sales of major products 2004(MUSD) : Sales of major products 2004(MUSD) Losec/Prilosec -30% Seloken +6% Nexium +15% Seroquel +33% Zoladex -1% Crestor >100% Pulmicort +4% Casodex +11% Atacand +10% Arimidex +48% % growth CER Slide 12: R&D expenditures(MUSD) Expenditures as % of sales 17.2% 18.3% 17.7% Our research areas : Our research areas Gastrointestinal Cardiovascular Neuroscience CNS Pain Control/Anaesthesia Oncology Respiratory and Inflammation Infection The path to a new medicine : The path to a new medicine Years 1 16 2 3 4 5 6 7 8 9 10 11 12 13 14 15 No. of compounds Up to 1,000,000 10-15 First patent application Clinical trial application Product licenceapplication Drug Discovery Drug Development Target and leadidentification Leadoptimisation Concept testing Developmentfor launch Launch Clinical Development Phase I50-150people Phase II100-200people Phase III500-5,000people Phase IV studies continue Product lifecycle support Toxicology and pharmacokinetic studies (absorption, distribution, metabolism, excretion) Pharmaceutical and analytical development Process chemistry and manufacturing Registration and regulatory affairs Sales and marketing (preparation, promotion, advertising and selling) 1-8 1-3 1 The R&D process : Preclinical studies Clinical studies CHEMISTRY/ PHARMA-COLOGY IND* PHASE I PHASE II PHASE III NDA** PHASE IV Search for active substances Toxicology, efficacy studies on various types of animals Regulatory review Efficacy studies on healthy volunteers Clinical studies on a limited scale Comparative studies on a large number of patients Regulatory review Continued comparative studies *Investigational New Drug Application for permission to administer a new drug to humans 50–150persons 100–200patients 500–5,000patients Registration, market introduction **New Drug Application Application for permission to market a new drug KNOWLEDGELEVEL KNOWLEDGELEVEL 2–4 yrs. 2–6 mos. 3–6 yrs. 1–3 yrs. Approximately 10 years from idea to marketable drug TIME SPAN Discovery Development The R&D process Future Global Mortality : Future Global Mortality Ischaemic heart disease Cerebrovascular disease Lower respiratory infection Diarrhoeal disease Perinatal disorders COPD Tuberculosis Measles Road traffic accidents Lung cancer Stomach cancer HIV Suicide Murray & Lopez: WHO/World Bank Global Predictions Nat Med 1998 1990 2020 Prevalence COPD – smoking habits : Prevalence COPD – smoking habits Males Stang P. Chest 2000; 117:354S Slide 20: FVC FEV1 = how much you can exhale in 1 sec. FEV1/FVC = how large proportion you can exhale- Measures obstruction. Slide 21: Fletcher & Peto, BMJ, 1977 COPD: lung function decline Slide 22: GOLD Management guidelines of COPD GOLD workshop report update 2003 Slide 23: A “typical” COPD patient ? Slide 24: Pathophysiological changes in COPD small airways COPD pathobiology andcurrent treatment hypotheses : COPD pathobiology andcurrent treatment hypotheses Barnes and Hansel, Lancet, 2004 Airway epithelial cell function is dysregulated in COPD : Airway epithelial cell function is dysregulated in COPD Barrier function Mucus hyperplasia/metaplasia Proliferation, differentiation and repair Inflammatory mediator production Interactions with inflammatory cells AZ - U. of Southampton collaboration(Holgate, Djukanovic, Davies, Wilson, Richter, O´Donnell, Angco)Aims of the study : AZ - U. of Southampton collaboration(Holgate, Djukanovic, Davies, Wilson, Richter, O´Donnell, Angco)Aims of the study Investigate airway epithelial gene expression in non-smokers, healthy smokers and smokers with COPD in relation to clinical phenotype Establish relevant in vitro cell models to study in detail the effects of cigarette smoke on epithelial cells Increase understanding of molecular mechansisms underlying epithelial pathophysiology in COPD and provide novel targets or pathways for therapeutic intervention Cellular Composition of Brush Biopsies : Cellular Composition of Brush Biopsies N = 79 Subject characteristics : Subject characteristics N = 70 (9 samples excluded because of impurities) Affymetrix U133A,B microarray analysis : Affymetrix U133A,B microarray analysis 70 samples assayed Software ZAM: low level analysis, in-house SAGx: differential expression, Bioconductor Clustering and visualisation: Spotfire, Dchip Contrast normalisation RMA type of index Penalised t-test to compare subject categories Close to 45000 probesets Gene Sets from KEGG and Biocarta Roughly 150 clinical variables Penalised t-test and FDR : Penalised t-test and FDR Low expressed genes less accurately assayed: higher risk of false positives Solution: add a penalty to the denomimator of the t-test statistica To control false positive rate: estimate False Discovery Rate and threshold Oxidative stress related genes go up in Smokers and further increase in COPD : Oxidative stress related genes go up in Smokers and further increase in COPD PCA based on oxidative stress related genes : PCA based on oxidative stress related genes NS HS COPD Expression of Oxidative Stress related genes : Expression of Oxidative Stress related genes High Figure produced in Gene Data Viewer Principal Components Analysis (PCA) Slide 35: ES = enrichment score MES = maximum ES Gene Set Enrichment Analysis schematically From Mootha et al (2003) Calculation of MES 1) Order genes by expression difference 2) For each gene set: Calculate running sum of ES along all genes. Add to sum if gene belongs to gene set, otherwise subtract 3) Take maximum (partial) sum Slide 36: Gene Set Enrichment Analysis Implemented in R based on Mootha et al. (2003) Gene sets related to oxidative stress ranked high Transcription Factor Binding Sites(TFBSs) : Transcription Factor Binding Sites(TFBSs) A transcription factor (TF) is a protein that mediates the binding of RNA polymerase and the initiation of transcription TRANSFAC is a database on eukaryotic TFs, their genomic binding sites and DNA-binding Which TFBSs are overrepresented in a set of regulated genes? Elkon et al. (2003) presents an algorithm to score upstream regions in terms of TF binding affinity From Jayneway et al. Position weight matrix : Position weight matrix Sequence logo representation of the binding specificity of the transcription factor Elk-1, copied from the Jaspar web site , Roepcke, S. et al. Nucl. Acids Res. 2005 33:W438-W441; doi:10.1093/nar/gki590 Denote by p(i, j) the frequency of base i at position j in the PWM P Given a promoter subsequence s1s2 ... sl, define its similarity to P as follows: sim(P, s1s2…sl) > some large T(P) will be called a ‘hit’ Slide 39: Over-representation of Transcripion Factor Binding Sites From Elkon et al. (2003) Clustering of Genes with respect to TF binding sites : Clustering of Genes with respect to TF binding sites Correspondance between cell cultures and humans : Correspondance between cell cultures and humans Healthy Smokers/Nonsmokers Cells treated with Cigarette smoke extract resp vehicle Link between gene expression and clinical variables : Link between gene expression and clinical variables PLS analysis Validation : Validation RT-PCR Genetic Association studies in separate cohorts Cell and other models Localisation in disease tissue Protein References : References Pierrou, S., Broberg, P., O'Donnell, R., Pawlowski, K., Virtala, R., Lindqvist, E., Richter, A., Wilson, S., Angco, G., Möller, S., Bergstrand, H., Koopmann, W., Wieslander, E., Strömstedt, P.-E., Holgate, S., Davies, D., Lund, J., Djukanovic, R. (2006) Expression of genes involved in oxidative stress responses in airway epithelial cells of COPD smokers, AJRCCM Jayneway et al., Immunobiology Elkon, R., Linhart, C., Sharan, R., Shamir, R., and Shiloh, Y., Genome-wide In-silico Identification of Transcriptional Regulators Controlling Cell Cycle in Human Cells, Genome Research, Vol. 13(5), pp. 773-780, 2003 Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstrale M, Laurila E, Houstis N, Daly MJ, Patterson N, Mesirov JP, Golub TR, Tamayo P, Spiegelman B, Lander ES, Hirschhorn JN, Altshuler D, Groop LC, PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes, Nat Genet. 2003 Jul;34(3):267-73

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