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A systems approach to preventing drug resistance in colon cancer

Colon cancer (CC) is a major cause of death. Current treatment involves chemotherapy combined with anti-EGFR or VEGF drugs and radiotherapy. Screening for biomarkers can indicate whether EGFR-inhibitors will be effective in patients, but otherwise biomarkers for personalizing patient treatment are scarce. First-line combinations of chemotherapy and EGFR-inhibitors for patients being RAS wild-type have led to an increase in overall survival to more than 30 months. However, most patients develop RAS mutations under anti-EGFR therapy, or do not respond to EGFRi for unknown reasons. The majority of patients develop resistance and succumb to the disease. We still have a poor understanding of how gene networks drive cancer, how they modulate response, and how they induce resistance to treatment. Good disease models that provide insight are simply lacking. With the availability of large public data resources, our unique collection of patient samples and patient-derived models and with computational and experimental approaches becoming mature, the COLOSYS consortium aims to develop in silico therapy response predictors. These will allow precision medicine, based on patient-specific driver and resistance mechanisms. We will identify new CC tumor driver genes by integration of multiple data types from large public tumor data repositories. A high quality, open repository of data and knowledge (knowledge commons) will be assembled and used to construct multi-scale computer models of the molecular networks that underlie cancerous cell proliferation. Logic model simulations will predict the effect of drugs in cancer cell lines and patient tumors. We will test these predictions on cell lines as well as patient-derived cell cultures, organoids and mouse xenografts, and perform preliminary testing in patients. The combined computational, experimental and clinical testing will provide a thorough understanding of resistance mechanisms, and allow personalised treatment of colon cancer.

Acronym (Reference Number) COLOSYS (10)
Duration 01/05/2016 - 30/04/2019
Project Topic Oncology/therapy/

Project partner

Number Short Name Name Role Country
1 NTNU Norwegian University of Science and Technology Coordinator Norway
2 Charité Berlin Charité University Medicine Berlin Partner Germany
3 Institut Curie Institut Curie Partner France
4 CNIO Spanish National Center for Cancer Research (CNIO) Observer Spain
5 NKI Netherlands Cancer Institute Partner Netherlands