Objective
Recent research suggests that the hypoxic micro-environment of tumours is one of the major drivers of metastatic spread of cancer. Furthermore, hypoxic tumour micro-environments may result in treatment resistance of cancer cells, therefore causing a double effect of reducing the potential of a successful treatment of the cancer patient. This project seeks to clarify the roles and functions of the hypoxic tumour micro-environment in relation to the survival of solid tumours likely to metastasise. We will gain new knowledge about molecular mechanisms behind hypoxia-driven metastasis, like the epithelial-mesenchymal transition (EMT) by several routes: (a): mechanisms related to cell growth- and cell proliferation (UPR, mTOR, CA9, HIF, Notch, and VHL), (b): angiogenesis and lymphangiogenesis, (c): metabolism and pH-regulation (d): the handling of reactive oxygen species (ROS). We will generate animal models for the study of the role of hypoxia in metastases and develop a bio-bank of tumour and blood samples for molecular diagnostic studies. We will identify and develop advanced imaging techniques and biomarkers and identify micro-metastases in bone marrow of patients to assist in the selection of appropriate stratification of the actual primary tumour’s and metastases’ micro-environmental conditions. We will also create a machine-learning based classifier of tumour hypoxia. The consortium has the necessary expertise to perform proof-of-principle clinical testing of new treatment strategies. We will thus perform clinical tests of new drugs developed to attack the regulatory mechanisms selected from the pre-clinical work and possible synergisms of combined treatments. We will also test new radiotherapy strategies for treatment of primary as well as metastatic tumours. Cancer types chosen for clinical studies are non-small-cell lung carcinoma, squamous cell carcinoma of the larynx, prostate cancer, primary breast cancer and rectal cancer.
Fields of science
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Keywords
Call for proposal
FP7-HEALTH-2007-B
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Funding Scheme
CP-IP - Large-scale integrating projectCoordinator
0313 Oslo
Norway
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Participants (20)
6229 ET Maastricht
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EH8 9YL Edinburgh
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6525 XZ Nijmegen
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OX1 2JD Oxford
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8200 Aarhus
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1337 SANDVIKA
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M13 9PL Manchester
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50121 Florence
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17177 Stockholm
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28049 Madrid
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80636 Munich
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75794 Paris
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79098 Freiburg
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79110 FREIBURG IM BREISGAU
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DK-8000 Aarhus
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WC1E 6BT LONDON
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84505 BRATISLAVA
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01513 Vilnius
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6200 MD Maastricht
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0450 Oslo
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