DONMFCCRP · Development of new models for cancer chemotherapy response prediction
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2005-01-01 → 2005-12-31
- EU contribution
- €40,000
- Participants
- 1
- Scheme
- ERG
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Results in brief
Final Activity Report Summary - DONMFCCRP (Development of new models for cancer chemotherapy response prediction)
Up to date clinical tests for predicting cancer chemotherapy response are not available and individual markers have shown little predictive value. Today, the only used factor in clinical decisions is staging, which reflects tumour size and spread. The need for an individual-tailored cancer therapy is great, since it could significantly increase the patient survival. In our first study we applied gene expression signatures derived from chemotherapy-resistant and -sensitive cell lines to effectively predict clinical survival after doxorubicin monotherapy. Our approach demonstrated the significance of in vitro experiments in the development of new strategies for cancer chemotherapy response prediction. In another study we focused on the resistance at the in vivo concentrations, and constructed predictive gene expression signatures for 11 anticancer agents. We have set up a new biobank focused on cancer chemotherapy resistance. We collected more than 250 lung- brain- ovarian- and colon cancer specimens in six different locations in Budapest, Hungary. We have constructed a low-density microarray to predict clinical response against two different anticancer agents simultaneously. Identifying gene expression signatures associated with resistance is only the first step in an effective therapy against cancer. To decipher the regulatory networks responsible for a common change in a set of co-regulated transcripts, we have conducted an in silico comparative promoter analysis. Using bioinformatics approaches we have set up putative regulatory networks, which provide insight into the mechanisms of resistance. In summary, we have developed technologies which can be used for predicting cancer chemotherapy response. Moreover, we have identified genes and transcription factors as new therapy targets for future anticancer agents.
Data: CORDIS, © European Union
Project objective
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.
Original text from CORDIS.
Participants
- 2ND DEPARTMENT OF MEDICINE, SEMMELWEISS UNIVERSITY · BUDAPESTCoordinatorCity levelHungary
Links
Data: CORDIS, © European Union