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PREDICT

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Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics

Coordinator: Zoltan SZALLASI
Project Number: 259303
EC contribution: 5,841,009.20
Project website: http://www.predictconsortium.eu/

The strategic development of accurate biomarkers to predict response to therapy in cancer medicine will enhance clinical outcome and reduce the health economic impact of drug resistant disease. The PREDICT consortium will identify and validate predictive biomarkers for two drugs which have direct anti-tumour cell and anti-angiogenic activity and for which no established predictive biomarkers of tumour response exist: sunitinib, a multi-targeted tyrosine kinase inhibitor, and everolimus, an mTOR pathway inhibitor. Renal cell carcinoma (RCC), a disease sensitive to these agents, will serve as the model tumour type to identify predictive response biomarkers suitable for widespread application across diverse tumour types. PREDICT?s biomarker discovery approach is based on the integration of genomics data from pre-operative RCC therapeutic clinical trials with novel personalised functional genomic screen datasets. We will systematically collect tumour tissue from monotherapy pre-operative window RCC clinical trials of 240 patients treated with everolimus or sunitinib and determine expression profiles, copy number aberrations, and genome-wide exon sequences of tumours before and after drug treatment. We will perform two types of RNA interference drug- and hypoxia-resistance screens: one using reverse transfection of commercial siRNA libraries into previously established RCC cell lines, and one using a novel approach through personalised tumour cDNA derived-shRNA library transduction of ex-vivo cultured autologous tumour cell lines. Bioinformatics integration of these complementary individualised clinical and experimental datasets will enable the rapid and cost efficient identification of predictive biomarkers and simultaneously define molecular mechanisms contributing to intrinsic and acquired drug resistant disease in vivo, yielding additional targets for therapeutic intervention.

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