Objective
Cancer heterogeneity is reflected in the multitude of phenotypes found in the clinic, with different proliferation statuses and metastatic potentials. These features cannot be assessed with the molecular imaging methods commonly available for diagnosis and monitoring. The main goal of this proposal is to develop a molecular imaging methodology based on endogenous contrast – CHyMERA – and demonstrate its feasibility to image hotspot areas of active proliferation and metastatic potential. The approach is based on the concept of cancer metabolic plasticity, does not require contrast agents or radioactive tracers, and should ultimately provide more specificity to cancer diagnosis and treatment planning than other imaging methods currently available. We propose to use animal models of human cancer, a glucose-enhanced imaging method, and an objective analysis of regional metabolic responses to controlled, reversible changes in the tumour microenvironment (perturbations), such as transient hypoxia. Specifically, we will (i) develop and validate CHyMERA at ultra-high magnetic fields, to monitor the metabolic kinetics of glucose and lactate in the tumour microenvironment. This methodology will be (ii) applied in vivo to two immunocompetent mouse model of GBM (allograft and genetically engineered models), to image vascular permeability/perfusion and hotspots of glioma proliferation. Finally, we will (iii) carry out a pilot study with two isogenic mouse models breast of cancer, metastatic and non-metastatic, to generate hotspots maps of proliferation and metastatic potential. All in vivo results will be validated post-mortem by immunohistochemistry. If successful, this methodology has a strong potential for clinical translational, which the host institution is ideally suited to test.
Field of science
- /medical and health sciences/clinical medicine/cancer
Programme(s)
Call for proposal
H2020-MSCA-IF-2018
See other projects for this call
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
1400-038 Lisboa
Portugal
