The ability of cancer cells to acquire simultaneous resistance to different drugs is a significant obstacle to successful chemotherapy. Today there are no clinically useful predictive markers of a patient's response to chemotherapy. The use of gene express ion patterns of well-defined chemotherapy-resistant and sensitive cancer cell lines and assaying their potential for predicting the response to chemotherapy in conjunction with the prognosis on a pre-characterised set of cancer patients can increase the ef fectiveness in searching for new prediction models. During my Marie-Curie fellowship we have identified genes associated with the resistance against 12 anticancer drugs. For example we were able to construct a predictive model for doxorubicin resista nce identifying the 80 genes with highest impact on the resistance. First, we will validate these already identified genes by an independent method. The validation will enable the fine-tuning of the prediction model, the selection of a gene list for cust om DNA chips and stem-cell investigations. About 51% of the already identified genes are EST¿s, where the biological function of the gene is unknown. These genes represent novel gene candidates responsible for chemotherapy resistance. Our aim is to perfo rm functional investigations in order to describe the function of these genes. This combines genome-wide expression profiling after RNA interference and stable transfection in order to detect pathways associated with these genes. Our major aim is to estab lish the prediction model for various cancer types. We plan to perform predictive analysis for lung, colon, breast and stomach cancer. This objective includes the build-up of a new tumour-bank focused on drug resistance and testing of self-synthesised cust om chips based on the prediction models. The results of the resistance pattern can allow the development of custom cDNA arrays to test drug resistance, thus reducing unnecessary treatment.
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