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Elaboration of Protein Microarrays for Rapid Screening and Quantification of Breast Cancer Biomarkers Liu Shi

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Elaboration of Protein Microarrays for Rapid Screening and Quantification of Breast Cancer Biomarkers Liu Shi Elaboration of protein microarrays for rapid screening and quantification of breast cancer biomarkers Liu Shi To cite this version: Liu Shi. Elaboration of protein microarrays for rapid screening and quantification of breast cancer biomarkers. Other. Ecole Centrale de Lyon, 2015. English. NNT : 2015ECDL0024. tel-01290891 HAL Id: tel-01290891 https://tel.archives-ouvertes.fr/tel-01290891 Submitted on 18 Mar 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Thèse de l’Université de Lyon délivrée par l’Ecole Centrale de Lyon Soutenue publiquement le 28/09/2015 Par Mlle Liu SHI Préparée à l’Institut des Nanotechnologies de Lyon Elaboration of protein microarray for rapid screening and quantification of breast cancer biomarkers Ecole Doctorale d’Electronique, Electrotechnique, Automatique Spécialité: Micro et Nanotechnologies Composition du jury : Professeur, PR-PHU, MAUDELONDE Thierry CHU Montpellier RAPPORTEUR PhD-HDR, CR CNRS, ROUPIOZ Yoann CEA Grenoble RAPPORTEUR Professeur, PR-PHU, GUEYFFIER François UCB Lyon EXAMINATEUR PhD- HDR, CR CNRS, TREVISIOL Emmanuelle LAAS - Toulouse EXAMINATRICE PhD-HDR, DR CNRS, SOUTEYRAND Eliane Ecole Centrale de Lyon, Directrice de Thèse PhD-HDR LAURENCEAU Emmanuelle Maitre de Conférences, ECL Co Directrice de Thèse PhD – HDR LAMBERT Claude CHU St- Etienne Invité Acknowledgements It was a great pleasure for me to make a thesis in the team of chemistry and nanobiotechnology in Lyon Institute of Nanotechnology (INL), and I want to thank a lot of people for these three years. Firstly, I want to thank my supervisor Dr Eliane Souteyrand and my co-supervisor Dr Emmanuelle Laurenceau. They helped me defining the structure of my thesis as well as giving me a lot of support and encouragement during last three years. Furthermore, I learned a lot from my bosses on how to organize time, how to resolve the problems, how to be a good researcher. All these are invaluable experience for me and make me benefit all my life. Then I want to thank all the colleagues in my team. Thanks Dr. Yann Chevolot for revising my publications and for discussing the problems that I have confronted during my thesis. Thanks Dr. Thomas Gehin for spotting, it’s fundamental because I cannot do anything without it. I also much appreciate Dr Virginie Monnier, Dr Magali Phaner-Goutorbe, Dr Jean- Pierre Cloarec, Isabel Nabeth and Maryline Diserio, we passed excellent coffee time almost every day. Also, great thanks to all doctors (Alice Goudot, Amandine Cornillon, Salome Ansanay-Alex and Francisco Palazon) and future doctors (Lucie Dupin, Francesca Zuttion, Maxime Boksebeld, Mathieu Caillau and Feixiong Chen). It’s amazing that we had created such a good and relaxed working environment. I would also appreciate the collaboration with the Montpellier Research Cancer Institute (IRCM). Thanks Dr. Jérôme Solassol and Dr. Alain Mangé for giving us samples and helping us analyzing data. Of course I greatly appreciate the PhD fellowship from China Scholarship Council (CSC) which gave me financial support to do my thesis. Also, I want to thank all my Chinese friends: Xianqing Meng, Huanhuan Liu, Tianli Huang, Kai Zhang, He Ding, Yu Bai, Zhen Lei, Xuchen Liu, Xingrong Huang, Yu Fan, Changwei Zhou, Xiangkun Sun, Wei Chen and Bingxue Zhang. I can not cite all but I keep all of you in my mind. Finally, I want to thank my family and my boyfriend. Thank you. 1 2 Abstract Breast cancer becomes the most common cancer among women. In order to improve women's chances of survival and life quality, to be diagnosed at an early stage and to receive correct treatment are the most promising ways. In this context, we aim at developing an antigen microarray for screening serological biomarkers to diagnose breast cancer patients as early as possible. Among numerous potential biomarkers, recent researches showed that antibodies against heat shock proteins (HSPs) are associated with tumor genesis and would be good diagnostic and prognostic biomarkers for breast cancer. Therefore, we used customized antigen microarray to screen anti-HSP antibodies in 50 breast cancer patients and 26 healthy controls. Our results indicated clearly that combining multiplex detection of anti-HSPs antibodies could discriminate breast cancer patients from healthy controls with sensitivity 86% and specificity 100%. Then, we elaborated an antibody microarray to detect the concentration of urokinase type plasminogen activator (uPA) in 16 cytosolic extracts of breast tummor tissue. uPA is good prognostic and predictive biomarker for breast cancer, low levels of uPA ( ≤3 ng/mg of protein) is associated with low risk of recurrence and no benefit of chemotherapy for breast cancer patients, and vice versa. Our results showed that the results obtained from our antibody microarray were surface dependent compared with the results obtained from ELISA. Furthermore, the use of our antibody microarray requires 25 times less sample volume compared with ELISA kit, thus solving the main limitations of ELISA. Finally, we determined and optimized the parameters which affected the performances of protein microarray, e.g. microarray surface chemistry, experimental duration, the concentration of solutions, etc. Furthermore, we studied the storage conditions for both chemically functionalized microarray surface as well as printed protein microarray. Results showed that our protein microarrays retain efficient biological activity for at least 3 month of storage. Key words : protein microarray, autoantibodies, breast cancer diagnosis, predictive biomarkers, storage 3 4 Abbreviations AAbs Autoantibodies APDMES (3-aminopropyl) dimethylethoxysilane ASCO American society of clinical oncology AUC Area under receiver operating characteristic curve BC Breast cancer BSA Bovine serum albumin Car Sodium carbonate buffer CMD Carboxymethyl dextran COOH Carboxylic acid surface Cy3 Cyanine 3 Cy5 Cyanine 5 DCIS Ductal carcinoma in situ DIC N, N’-diisopropylcarbodiimide DI water Deionized water EGTM European Group on Tumor Markers ELISA Enzyme-linked immunosorbent assay ER Estrogen receptor FI Fluorescence intensity FLISA Fluorescence-linked immunosorbent assay GRP Glucose-regulated protein HC Healthy controls HER-2 Human epidermal growth factor receptor 2 HSPs Heat shock proteins IHC Immunohistochemical MAMVE Maleic anhydride-alt-methyl vinyl ether MES 2-(N-morpholino) ethanesulfonic MRI Magnetic image resonance NHS N-hydroxysuccinimide ODN Oligonucleotide OFAT One-factor-at-a-time p53 Tumor protein 53 PAI-1 Plasminogen activator inhibitor-1 PBS Phosphate-buffered saline PMT Photomultiplier tubes PR Progesterone receptor ROC Receiver operating characteristic curve SD Standard deviation SNR Signal-to-noise ratio Strep Streptavidin TAA Tumor associated antigen TDSUM Tert-butyl-11-(dimethylamino)silylundecanoate uPA Urokinase plasminogen activator 5 6 Table of contents Acknowledge 1 Abstract 3 Abbreviations 5 Table of contents 7 General introduction 11 Chapter 1 State of the art 13 1.1 Breast cancer: Key data and detection techniques 17 1.2 Tumor biomarkers 20 1.2.1 Indicators of biomarker value and data analysis 21 1.2.2 Serum biomarkers used in clinic 24 1.2.3 Tissue biomarkers used in clinic 27 1.3 Autoantibodies (AAbs)- Diagnostic and prognostic value 32 1.3.1 Heat shock proteins (HSPs) and AAbs against HSPs 33 1.3.2 Autoantibodies against other TAAs than HSPs 38 1.4 Protein microarray 49 1.4.1 Surface chemistry 52 1.4.2 Commercial protein microarray 55 1.4.3 Optimization of assay conditions 62 1.4.4 Storage conditions of protein microarray 63 1.5 Aims of this thesis 65 References 67 Chapter 2 Anti-heat shock proteins autoantibodies profiling in breast cancer serum using customized protein microarrays 85 2.1 Introduction 89 2.2 Materials and methods 90 2.2.1 Materials 90 2.2.2 Serum samples 91 2.2.3 Surface functionalization of glass slides 91 2.2.4 Design of protein immobilization on flat glass slides 92 2.2.5 Multiplex immunoassays on micro-structured protein microarray 93 7 2.2.6 Fluorescence scanning 95 2.2.7 Data analysis 95 2.3 Results 95 2.3.1 Optimization of tumor antigen microarray conditions 95 2.3.2 Detection of autoantibodies against HSPs and P53 in breast cancer sera by multiplex immunoassays on antigen microarray 100 2.4 Discussion and Conclusions 106 References 109 Chapter 3 Antibody microarray for the quantification of uPA and PAI-1 in breast tumor tissue 113 3.1 Introduction 117 3.2 Experiments 118 3.2.1 Materials 118 3.2.2 Biological samples 118 3.2.3 Surface functionalization of microstructured glass slides 119 3.2.4 Design and Optimization of antibody microarray 119 3.2.5 Evaluation of the biological activity of antibodies against uPA and PAI-1 with ELISA 121 3.2.6 Quantification of uPA from breast tumor tissue extracts on antibody microarrays 122 3.2.7 Fluorescence scanning and data analysis 123 3.3 Results and discussion 124 3.3.1 Optimization of antibody microarray conditions 124 3.3.2 Quantification of uPA in breast tumor tissues extracts 134 3.4 Conclusions 145 References 147 Chapter 4 Optimization of protein
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