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Mapping Tumor Metabolic Aggressiveness with hybrid PET/MR Shift Reagents In Vivo

Subject Area Nuclear Medicine, Radiotherapy, Radiobiology
Inorganic Molecular Chemistry - Synthesis and Characterisation
Term since 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 516238665
 
The age-adjusted survival rate of cancer patients increased only 5% since the 1950s, despite substantial advances in early detection technologies. As such, there is an urgent need to develop reliable biomarkers and personalized diagnostic tools that enable clinicians to predict, non-invasively, the natural history and plasticity of tumor masses. Using sensors capable of detecting specific extracellular events in cancer, we can evaluate metabolic profiles detailed to each tumor type—virtually in vivo non-invasive biopsies of the tumor stroma. Exciting preliminary data from the team show that a novel extracellular lactate sensor used together with advanced biomedical imaging can detect extracellular lactate as a reliable biomarker for cancer aggressiveness without significant interference from other endogenous biomolecules. To our knowledge, this is the first-time extracellular lactate produced by cancer cells could be detected in vivo. Since overproduction of extracellular lactate is a hallmark of cancer, via the Warburg effect - we propose a direct strategy to detect the stages of tumor aggressiveness by utilizing novel hybrid metabolic sensors (SRs*), state-of-art hybrid imaging, multiparametric data analysis, and quantitative metabolic imaging. The success of the proposed work plan will lay the foundation for further research in: Design of probes detecting metabolic and functional events in the microenvironment; accurate tumor phenotypic profiling with hybrid probes; personalized and specialized diagnostic with multimodal approaches; detection of disease progression (i.e. aggressiveness, staging); quantitative metabolic imaging by the use of optimized hybrid PET/MRI sensors aimed at translational studies; advanced multiparametric analysis. This will ultimately lead to a holistic understanding of cancer progression, metastasis, the associated cancer aggressiveness, heterogeneity, and metabolic modulation in solid tumors.
DFG Programme Research Grants
 
 

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