<p>In this thesis, methods to study gene and protein expression in cells and tissues were developed and utilized in combination with protein-specific antibodies, with the overall objective to attain greater understanding of protein function.</p><p>To analyze protein expression in <i>in vitro</i> cultured cell lines, a cell microarray (CMA) was developed, facilitating antibody-based protein profiling of cell lines using immunohistochemistry (IHC). Staining patterns in cell lines were analyzed using image analysis, developed to automatically identify cells and immunohistochemical staining, providing qualitative and quantitative measurements of protein expression. Quantitative IHC data from CMAs stained with nearly 3000 antibodies was used to evaluate the adequacy of using cell lines as models for cancer tissue. We found that cell lines are homogenous with respect to protein expression profiles, and generally more alike each other, than corresponding cancer cells <i>in vivo</i>. However, we found variability between cell lines in regards to the level of retained tumor phenotypic traits, and identified cell lines with a preserved link to corresponding cancer, suggesting that some cell lines are appropriate model systems for specific tumor types. </p><p>Specific gene expression patterns were analyzed in vitiligo vulgaris and malignant melanoma. Transcriptional profiling of vitiligo melanocytes revealed dysregulation of genes involved in melanin biosynthesis and melanosome function, thus highlighting some mechanisms possibly involved in the pathogenesis of vitiligo. Two new potential markers for infiltrating malignant melanoma, Syntaxin-7 and Discs large homolog 5, were identified using antibody-based protein profiling of melanoma in a tissue microarray format. Both proteins were expressed with high specificity in melanocytic lesions, and loss of Syntaxin-7 expression was associated with more high-grade malignant melanomas.</p><p>In conclusion, the combination of antibody-based proteomics and microarray technology provided valuable information of expression patterns in cells and tissues, which can be used to better understand associations between protein signatures and disease.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:uu-8680 |
| Date | January 2008 |
| Creators | Strömberg, Sara |
| Publisher | Uppsala University, Department of Genetics and Pathology, Uppsala : Acta Universitatis Upsaliensis |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, text |
| Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, 1651-6206 ; 344 |
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