Keywords: Biology, Models, Methods, Cancer, oncology
Motivation: Instead of focusing on the heavily-studied glycolysis in cancer, novel imaging tools that report on unexplored metabolic pathways are in need to enrich oncologic molecular imaging.
Goal(s): We developed Fluorine Metabolic Imaging (FMI), a novel MRI-based metabolic imaging platform, which utilizes 3FDGal to concurrently report and map sugar oxidation and reduction by cancer cells.
Approach: We in vitro exposed different cell lines and in vivo exposed tumor model mice to 3FDGal, followed by 19F-NMR and MRI experiments.
Results: FMI successfully differentiated cancer types based on their unique 3FDGal metabolic fingerprints, revealing distinct metabolic behaviors irrespective to glycolytic flux.
Impact: FMI with 3FDGal as an 19F-MRI tracer represents a revolutionary shift in oncologic imaging. By concurrently mapping sugar oxidizing/reducing enzymes, tumor categorization becomes available at the molecular level, regardless of glycolysis-dependence, opening up new frontiers in cancer research and detection.
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