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COLTHERES

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Modelling and predicting sensitivity to targeted therapies in colorectal cancers

Coordinator: Alberto BARDELLI
Project Number: 259015
EC contribution: 5,999,300.00
Project website: http://www.coltheres.eu/

Effective and long term treatment of cancer is now in sight, but will ultimately require an increasingly 'personalised' approach where the 'right' combination of drugs will be administered to the 'right' patients, based on a detailed understanding of their genetic background and their co-associated sensitivity or resistance 'biomarkers'. Efforts are specifically required to identify validated risk and patient-response stratification criteria, which can then be used to rationally develop companion diagnostic assays and more stream-lined clinical trials. COLTHERES will address these key issues by:

  1. Molecularly profiling colon cancer patient samples using multiple 'omics based technologies for co-segregating lesions that could impart resistance to existing and emerging targeted therapies
  2. The building and screening of predictive in vitro models based on this data, to enable the rapid and empirical determination of drug resistance biomarkers
  3. The use of these models and of the clinical studies to prospectively screen for genes mediating resistance and sensitivity to targeted therapies in CRCs
  4. The building of new algorithms to significantly accelerate the design of rational therapies, by integrating more predictive models, assays and biomarkers into all phases of drug discovery; including novel phase-0 (xenopatients) studies
  5. The design of innovative and focused biomarker driven phase II trials based on knowledge gathered within the project

COLTHERES has assembled a unique consortium, from both academia and industrial SMEs, of world- experts in the areas of;

  • clinical design of innovative biomarker trials and improved therapeutic strategies
  • 'omics technologies including genomic, transcriptomic, epigenomic and proteomic profiling
  • Functional genomic and disease model-generation
  • Bio-informatics and data analysis, to handle and interrogate the complexity of the data generated through the various approaches

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