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Development of a protein microarray platform for the multiplex analysis of biomarkers associated with rheumatoid arthritis

Urbanowska, Teresa. Development of a protein microarray platform for the multiplex analysis of biomarkers associated with rheumatoid arthritis. 2004, Doctoral Thesis, University of Basel, Faculty of Science.

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Official URL: http://edoc.unibas.ch/diss/DissB_6955

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Abstract

Currently in the drug development process there is a growing awareness of the need to utilise a biomarker strategy which would allow compounds to be developed in a more efficient way with improved safety and pharmacology. Technologies which can evaluate, validate and monitor biomarkers in a cost effective and efficient manner are a necessity if such a biomarker strategy is to be properly implemented. In this thesis the development, validation and implementation of a protein microarray for quantitative and simultaneous analysis of proteins is described. In order to demonstrate the feasibility of this approach, Rheumatoid arthritis (RA) was chosen as a model for proof of concept. Based on the current literature, seven proteins thought to be associated with the development and progression of RA were selected. Initially, a protein microarray was developed on a glass chip treated either with a self assembled monolayer (SAM) of octadecyl phosphoric acid ester (ODP) or with polyL-lysine. SAM showed its superiority over poly-L-lysine by generating more homogenous and less variable spots. However, the process of coating the chip with the SAM was time consuming and expensive. Moreover, assay processing was entirely performed manually and could not be automated without a significant investment of time and resources. As a result, high inter-chip variability was observed preventing sensitive, quantitative and reproducible analysis to be performed. An attempt was, therefore, undertaken to develop an alternative microarray platform. The appearance on the market of long neck tips for antibody printing devices, provided the option of using established polystyrene 96-well plates as the solid support for developing a fully automated microarray format. The development process involved reagent selection, printing protocol optimization, matrix investigation, assay protocol establishment, and detection system evaluation. The robustness and reproducibility of the methodology was investigated using the Food and Drug Administration (FDA) regulatory guidelines for pharmacokinetic assay validation, in which a spike-recovery validation test was elaborated and run overdays. The method was shown to be both quantitative and reproducible, with an assay accuracy between 70-130%, and assay precision less than 30%. Importantly, the working range for each assay covered the relevant physiological concentrations. In addition, protein microarray performance was compared with the classical ELISA approach. Sera collected from a total of 78 individuals representing either rheumatic or healthy patients were measured using both approaches. Correlation coefficients (R2) between the two technologies was calculated for each analyte giving: 0.90 for A, 0.60 for B, 0.93 for C, 0.96 for D, 0.94 for E and 0.95 for F. Finally, the developed protein microarray was used to compare the analyte concentration levels between patients with RA and other rheumatic diseases. Significant differences in the serum concentration of B (p<0.0022), C (p<0.0107), E (p<0.0024) and F (p<0.0057) between RA and other arthritic patients were observed. In conclusion, the obtained results demonstrate the applicability of the developed protein microarray for quantitative and simultaneous analysis of the selected RA-related proteins in clinical samples. It is anticipated that miniaturized and multiplexed immunoassays which allow for the rapid evaluation of multiple analytes in a single sample, will represent a valuable tool for validating and monitoring biomarkers in the drug development process.
Advisors:Meyer, Urs Albert
Committee Members:Legay, F. and Primig, Michael
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:6955
Thesis status:Complete
Bibsysno:Link to catalogue
Number of Pages:109
Language:English
Identification Number:
Last Modified:23 Feb 2018 11:40
Deposited On:13 Feb 2009 14:59

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