Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 178-195).

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2009.

Uveal melanoma is the most common primary intraocular malignant tumour in adults. Despite improvements in the diagnosis and treatment of the primary tumour, patients continue to have the same mortality rate as several decades ago, reflecting our poor understanding of the mechanisms behind the formation of metastases in this disease. The purpose of this study was therefore to characterize an animal model of uveal melanoma and use this model to study the transcriptional changes that cells undergo from culture to intraocular tumour, to circulation and finally to the formation of a metastatic nodule. / Using microarrays we identified 314 changes in transcript abundance between the intraocular tumour and metastatic lesions. Principal Components Analysis was used to cluster these transcripts into four distinct groups. A further 61 gene transcripts showed statistically significant changes between re-cultured cells isolated from the model, with the circulating malignant cells representing an intermediate step between cells isolated from intraocular tumours and metastatic lesions. We have produced a detailed analysis of the molecular changes that take place as human uveal melanoma cells evolve from a primary tumour to metastasis in an animal model, including the decrease in expression of specific melanoma markers. These changes were verified using quantitative real time polymerase chain reaction and three different functional assays. / In addition we sought to describe the genetic changes that are present in these cells. Using comparative genomic hybridization arrays we were able to successfully describe the deletions and amplifications that are present in genomic DNA extracted from paraffin embedded sections of the primary tumour. This represents the first time that archival tissue has successfully been used for this sort of analysis in uveal melanoma. We identified several genomic amplifications and deletions including an area of amplification of Wnt2, which is involved in beta-catenin regulation and C-Met, which plays a role in tumour cell homing to the liver in patients. / To the best of our knowledge, this is the first time that a detailed genetic analysis has been carried out on the progression of uveal melanoma from intraocular tumour, to circulation, to the formation of metastases.

The sequencing of the human genome revealed that the number of genes does not explain why humans are different from other organisms like mice and dogs. Instead, it is how genes interact with each other and the environment that separates us from other organisms. This motivates the study of genetic networks and, consequently, my research. My work delves into the roles that simple genetic networks play in a cell and explores the biotechnological aspects of how to uncover such genes and their interactions in experimental models. / Cells must respond to the extracellular environment to contract, migrate, and live. Cells, however, are subject to stochastic fluctuations in protein concentrations. I investigate how cells make important decisions such as gene transcription based on noisy measurements of the extracellular environment. I propose that genetic networks perform Bayesian inference as a way to consider the probabilistic nature of these measurements and make the best decision. With mathematical models, I show that allosteric repressors and activators can correctly infer the state of the environment despite fluctuating concentrations of molecules. Viewing transcriptional networks as inference modules explains previous experimental data. I also discover that the particular inference problem determines whether repressors or activators are better. / Next, I explore the genetic underpinnings of two canine models of atrial fibrillation: atrial tachypacing and ventricular tachypacing. Using Affymetrix microarrays, I find that the genetic signatures of these two models are significantly different both in magnitude and in class of genes expressed. The ventricular tachypacing model has thousands of transcripts differentially expressed with little overlap between 24 hours and 2 weeks, suggesting independent mechanisms. The atrial tachypacing model demonstrates an adaptation as the number of genes found changed decreases with increasing time to the point that no genes are changed at 6 weeks. I use higher level analysis to find that extracellular matrix components are among the most changed in ventricular tachypacing and that genes like connective tissue growth factor may be responsible. / Finally, I generalize the main problem of microarray analysis into an evaluation problem of choosing between two competing options based on the scores of many independent judges. In this context, I rediscover the voting paradox and compare two different solutions to this problem: the sum rule and the majority rule. I find that the accuracy of a decision depends on the distribution of the judges' scores. Narrow distributions are better solved with a sum rule, while broad distributions prefer a majority rule. This finding motivates a new algorithm for microarray analysis which outperforms popular existing algorithms on a sample data set and the canine data set examined earlier. A cost analysis reveals that the optimal number of judges depends on the ratio of the cost of a wrong decision to the cost of a judge.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 4 uppsatser.

Diss. (sammanfattning) Stockholm : Stockholms universitet, 2007. / Härtill 4 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2005. / Härtill 6 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 4 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 4 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2006. / Härtill 4 uppsatser.