Each year more than 63,000 new cases of kidney cancer are diagnosed in the European Union. Approx. 50% of all patients have metastasized renal cell cancer (mRCC) at presentation or develop metastases during follow-up. 5-year relative survival of mRCC has been extremely poor: between 5 and 10%. In the past few years, so-called targeted therapies that suppress angiogenesis have changed the clinical practice for patients with mRCC dramatically. Both response and toxicity to these expensive drugs is, however, extremely variable. With an increasing number of compounds becoming available, choice of compounds and sequence is becoming extraordinary challenging. Classical patient and tumor characteristics appear to have poor predictive ability. The aim of this project is to identify germline genetic markers that predict response and toxicity (by the use of high-resolution whole genome SNP arrays in groups of hundreds of patients treated with different agents), identify expression and epigenetic markers in tumors that predict response (by comparing expression and methylome arrays and kinase profiles in frozen tumor tissue from groups of patients who do (N=30) and do not (N=30) respond to different agents), to integrate these data from different platforms by means of bioinformatics and to conduct focused functional studies on the results in order to improve understanding of the critical molecular and resistance pathways involved. A large European consortium that has recruited and will recruit large numbers of patients ensures that the new markers identified in a first discovery phase can be tested in a subsequent replication phase. We have the ambition to define new validated risk stratification criteria to be used in personalized patient management. These criteria allow prediction of individual therapy response and resistance and will enable the monitoring of successful treatment outcome while reducing unnecessary drug use and expense.
Field of science
- /medical and health sciences/clinical medicine/cancer
Call for proposal
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