Metabolic differences among and within tumors can be an important determinant in cancer treatment outcome. However, methods for determining these differences non-invasively in vivo is lacking. Using pancreatic ductal adenocarcinoma as a model, we demonstrate that tumor xenografts with a similar genetic background can be distinguished by their differing rates of the metabolism of 13C labeled glucose tracers, which can be imaged without hyperpolarization by using newly developed techniques for noise suppression. Using this method, cancer subtypes that appeared to have similar metabolic profiles based on steady state metabolic measurement can be distinguished from each other. The metabolic maps from 13C-glucose imaging localized lactate production and overall glucose metabolism to different regions of some tumors. Such tumor heterogeneity would not be not detectable in FDG-PET.
Digital Object Identifier (DOI)
National Cancer Institute 1ZIASC006321-39: James Mitchell
National Cancer Institute Intramural Research Program: Murali C Krishna
Shared Resource(s) of the University of Kentucky Markey Cancer Center P30CA177558: Andrew N. Lane and Teresa W. M. Fan
Glucose imaging data and related files have been deposited to Dataverse at https://doi.org/10. 7910/DVN/XU9XH9.
Kishimoto, Shun; Brender, Jeffrey R.; Crooks, Daniel R.; Matsumoto, Shingo; Seki, Tomohiro; Oshima, Nobu; Merkle, Hellmut; Lin, Penghui; Reed, Galen; Chen, Albert P.; Ardenkjaer-Larsen, Jan Henrik; Munasinghe, Jeeva; Saito, Keita; Yamamoto, Kazutoshi; Choyke, Peter L.; Mitchell, James; Lane, Andrew N.; Fan, Teresa W. M.; Linehan, W. Marston; and Krishna, Murali C., "Imaging of Glucose Metabolism by 13C-MRI Distinguishes Pancreatic Cancer Subtypes in Mice" (2019). Center for Environmental and Systems Biochemistry Faculty Publications. 9.