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Cancer therapy operates by inflicting damage in malignant cells. The most lethal target is the genomic DNA. As a single double strand DNA break has the potential to kill the cell, mechanisms have evolved to detect and block propagation of the damage. Genes and their products function in a highly connected network-structure with ample cross-talk between different pathways. This interplay can be studied by genome-wide experiments, such as expression profiling. The aim of this thesis is to study the cellular effects of DNA damaging agents.

A theoretical framework is explored to improve understanding of expression profiling results. To analyse large datasets, computational methods were developed to model the data. Further, the response to DNA damage was investigated in different cellular systems. As late radiation toxicity is a severe limitation of radiotherapy of cancer patients, patients were enrolled in a study to search for a molecular signature to identify high-risk patients. Ex vivo irradiation of lymphocytes revealed a signature of functionally related gene sets that were capable to separate patients with regard to toxicity status.

The gene set analysis was also applied to a dataset where mouse embryonic stem cells had been exposed to various doses of cisplatin. At several time-points after administration of the drug, expression profiles were determined. In addition to the expected increase of genes related to apoptosis and cell cycle progression, damaged cells also seemed to have embarked upon a p53-dependent differentiation programme. Finally, in a study of cardiac rodent cells, the genotoxic treatment with irradiation was compared to the mechanical stress induced in heart tissue.

In conclusion, this thesis presents evidence for the advantage of using functionally related sets of genes in analysis and interpretation of genome-wide experiments. This strategy may improve clinical understanding of the effects of DNA damaging agents used for cancer therapeutics.