Objective
We propose here an exhaustive analysis of the genome, exome, methylome and transcriptome of primary tumours and metastases from patients with colon carcinoma, based on a combination of deep sequencing and chip based techniques. Dependent on their availability, we shall also perform analyses of tumor stem cells, circulating tumor cells, free tumor DNA in serum and xenografts derived from the same patients. This will be complemented by the development and application of highly sensitive techniques to identify individual mutations, transcripts and proteins/protein complexes both in-situ in pathology slides as well as in patients’ blood or serum. The integration of these results will allow us to address the heterogeneity of the tumor samples, to deduce the genome/epigenome/transcriptome of the different cell types making up or originating from the tumor (e.g. circulating tumor cells, tumour stem cells or xenografts), to establish models able to predict suitable candidates for further biomarker development, and also to predict the effects and side effects of drugs in the treatment of genetically defined groups of patients. Available biomarkers, as well as biomarkers predicted from the work within the project will be validated in patient derived xenograft models and stem cell cultures, and ultimately transferred into a point of care (POC) diagnostic format. In parallel we will explore the use of the global genome and methylome information, e.g. derived from the analysis of free tumor DNA in the serum of the patient, as the ‘ultimate’ biomarker, to model the biology of the tumor (possibly even before any tumor has been localised), and as an independent route to predict clinically relevant parameters. Though sequencing/methylation analysis of the genome of the tumor through free DNA is currently still too costly for use as a routine diagnostic, this is likely to change over the period covered by the grant, due to the extremely rapid progress in the development of large scale sequencing techniques.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesmedical biotechnologycells technologiesstem cells
- medical and health sciencesbasic medicinepathology
- natural sciencesbiological sciencesgeneticsgenomes
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Call for proposal
IMI-JU-02-2009
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Coordinator
13353 Berlin
Germany
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Participants (21)
80539 Munchen
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751 05 Uppsala
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WC1E 6BT London
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69006 Lyon
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12489 Berlin
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91405 ORSAY CEDEX
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13125 Berlin
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10117 Berlin
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8010 Graz
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01069 Dresden
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Participation ended
80333 Muenchen
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151 85 Sodertaelje
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55218 Ingelheim
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2340 Beerse
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64293 Darmstadt
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CT13 9NJ Sandwich
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4070 Basel
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RG21 4FA Basingstoke
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10691 Stockholm
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08035 Barcelona
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14195 Berlin
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