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Gabriel Teku...Is Lucris.Pdf Computational analysis on the effects of variations in T and B cells. Primary immunodeficiencies and cancer neoepitopes Teku, Gabriel Ndipagbornchi 2017 Document Version: Peer reviewed version (aka post-print) Link to publication Citation for published version (APA): Teku, G. N. (2017). Computational analysis on the effects of variations in T and B cells. Primary immunodeficiencies and cancer neoepitopes. Lund University: Faculty of Medicine. Total number of authors: 1 Creative Commons License: Unspecified General rights Unless other specific re-use rights are stated the following general rights apply: Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Read more about Creative commons licenses: https://creativecommons.org/licenses/ Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. LUND UNIVERSITY PO Box 117 221 00 Lund +46 46-222 00 00 Computational analysis on the effects of variations in T and B cells 1 2 Computational analysis on the effects of variations in T and B cells Primary immunodeficiencies and cancer neoepitopes Gabriel Ndipagbornchi Teku DOCTORAL DISSERTATION by due permission of the Faculty of Medicine, Lund University, Sweden. To be defended at Segerfalksalen BMC, Lund. On Saturday September 30 at 09:00. Faculty opponent Professor Olli Yli-Harja 3 Organization Document name LUND UNIVERSITY DOCTORAL DISSERTATION Date of issue September 30th, 2017 Author Sponsoring organization Gabriel Ndipagbornchi Teku Title and subtitle Computational analysis on the effects of variations in T and B cells: Primary immunodeficiencies and cancer neoepitopes Abstract Computational approaches are essential to study the effects of inborn and somatic variations. Results from such studies contribute to better diagnosis and therapies. Primary immunodeficiencies (PIDs) are rare inborn defects of key immune response genes. Somatic variations are main drivers of most cancers. Large and diverse data on PID genes and proteins can enable systems biology studies on their dynamic effects on T and B cells. Amino acid substitutions (AASs) are somatic variations that drive cancers. However, AASs also cause cancer-associated antigens that are recognized by lymphocytes as non-self, and are called neoantigens. Detail analysis these neoantigens can be performed due to the availability of cancer data from many consortia. The purpose of this thesis was to investigate the effects of PIDs on T and B cells and to explore features of neoepitopes in cancers. The object of the first study was to detect the central T cell-specific protein network. The purpose of the second and third studies were to reconstruct the T and B cell network model and simulate the dynamic effects of PID perturbations. The aim of the fourth study was to characterize neoepitopes from pan-cancer datasets. The immunome interactome was reconstructed, and the links weighed with gene expression correlation of integrated, time series data (Paper I). The significance of the weighted links were computed with the Global Statistical Significance (GloSS) method, and the weighted interactome network was filtered to obtain the central T cell network. Next, the T cell network model was reconstructed from literature mining and the core T cell protein interaction network (Paper II). The B cell network model was reconstructed by mining the literature for central B cell interactions (Paper III). The normalized HillCube software was used to study the dynamic effects of PID perturbations in T and B cells. Proteome-wide amino AASs on putatively derived 8-, 9-, 10-, and 11-mer neoepitopes in 30 cancer types were analyzed with the NetMHC 4.0 software (Paper IV). The interconnectedness of the major T cell pathways are maintained in the central T cell PPI network. Empirical evidence from Gene Ontology term and essential genes enrichment analyses were in support for the central T cell network. In the T and B cell simulations for several knockout PIDs correspond to previous results. In the T cell model, simulations for TCR, PTPRC, LCK, ZAP70 and ITK indicated profound disruption in network dynamics. BCL10, CARD11, MALT1, NEMO and MAP3K14 simulations showed significant effects. In B cell, the simulations for LYN, BTK, STIM1, ORAI1, CD19, CD21 and CD81 indicated profound changes to many proteins in the network. Severe effects were observed in the BCL10, IKKB, knockout CARD11, MALT1, NEMO, IKKB and WIPF1 simulations. No major effects were observed for constitutively active PID proteins. The most likely epitopes are those which are detected by several macromolecular histocompartibility complexes (MHCs) and of several peptide lengths. 0.17% of all variants yield more than 100 neoepitopes. Amino acid distributions indicate that variants at all positions in neoepitopes of any length are, on average, more hydrophobic compared to the wild-type. The core T cell network approach is general and applicable to any system with adequate data. The T and B cell models enable the understanding of the dynamic effects of PID disease processes and reveals several novel proteins that may be of interest when diagnosing and treating immunological defects. The neoepitope characteristics can be employed for targeted cancer vaccine applications in personalized therapies. Key words Classification system and/or index terms (if any) Supplementary bibliographical information Language: English ISSN and key title: 1652-8220 ISBN: 978-91-7619-533-8 Recipient’s notes Number of pages Price Security classification I, the undersigned, being the copyright owner of the abstract of the above-mentioned dissertation, hereby grant to all reference sources permission to publish and disseminate the abstract of the above-mentioned dissertation. Signature Date 2017-08-28 4 Computational analysis on the effects of variations in T and B cells Primary immunodeficiencies and cancer neoepitopes Gabriel Ndipagbornchi Teku 5 Coverphoto by Gabriel Ndiagbornchi Teku Copyright (Gabriel Ndipagbornchi Teku) Faculty of Medicine Department of Experimental Medical Science Lund University, Faculty of Medicine Doctoral Dissertation Series 2017:150 ISBN 978-91-7619-533-8 ISSN 1652-8220 Printed in Sweden by Media-Tryck, Lund University, Lund 2017 6 To my wife, Dibo, and kids, Naseem and Oben for your love, care, support and immense sacrifice. 7 8 Contents Papers included in this thesis ..................................................................................11 Abstract ..................................................................................................................13 Abbreviations .........................................................................................................15 Thesis at a glance ....................................................................................................17 General introduction ...............................................................................................19 Networks ......................................................................................................19 Complex networks ...............................................................................22 Biological networks .............................................................................22 Reducing biological network complexity ............................................23 Cell-type specific network model reconstruction ................................24 Overview of the immune system, variations and diseases ...........................25 The innate immune system ..................................................................25 The adaptive immune system ..............................................................25 The effects of variations on the immune system .................................27 Primary immunodeficiency .................................................................28 Cancer immunogenicity .......................................................................28 Disease diagnosis, therapy, and prognosis ..........................................29 Research questions .................................................................................................31 Overview of methods .............................................................................................33 Protein-protein interaction network reconstruction ......................................33 Gene expression data, preprocessing and analysis .......................................34 Protein network filtering ..............................................................................34 Robustness of the T cell PPI network ..........................................................35 Gene Ontology term enrichment, over-representation, and semantic similarity analysis ...................................................................36 Analysis of essential genes ...........................................................................36
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