PREDICT

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

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 Obiettivo del progetto (Objective)

'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.'

Introduzione (Teaser)

Understanding how cancer responds to therapy is central for continuing the same or pursuing a different treatment to ensure a better clinical outcome. European researchers are working on developing tools to predict patient response to therapy.

Descrizione progetto (Article)

Renal cell carcinoma has a dismal prognosis with nearly 50 % of patients succumbing to the disease. Although removal of the kidney is curative for a significant proportion of patients, the cancer metastasises and is resistant to cytotoxic chemotherapy.

Significant progress has been made with the development of innovative drugs targeting VEGF and mTOR signalling, namely sunitinib and everolimus. However, there are no biomarkers to date for predicting patient response to these drugs. The EU-funded http://www.predictconsortium.eu/ (PREDICT) (Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics) project has been designed to address this issue.

The consortium is collecting tumour biopsies from renal cell carcinoma patients to perform genomic profiling and obtain cellular models for further experimentation. Several novel bioinformatics tools have also been developed during PREDICT.

The experimental tools were combined with RNAi technology to identify and validate potential biomarkers. These model systems are being used to investigate the role of mutations described during the course of the project. These tools should also prove useful in identifying genes that confer hypoxia sensitivity in renal cancer.

A significant finding of the study so far is the discovery that renal tumours are heterogeneous at the genetic and transcriptomic level. This has led scientists to conclude that cancer evolves and creates clones that contain heterogeneous somatic events. They realised that therapeutic strategies should be targeted to common mutations or molecules present in the trunk of the cancer phylogenetic tree. The biomarker discovery efforts of PREDICT partners have thus shifted towards that direction.

The observations of the PREDICT work are now being considered within national and international drug approval agencies when implementing next generation sequencing into clinical trial analyses.