Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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  • Author: Kishimoto, Shun

    National Institutes of Health, United States

  • Author: Brender, Jeffrey R.

    National Institutes of Health, United States

  • Author: Crooks, Daniel R.

    National Institutes of Health, United States

  • Author: Matsumoto, Shingo

    Hokkaido University, Japan

  • Author: Seki, Tomohiro

    National Institutes of Health, United States

  • Author: Oshima, Nobu

    National Institutes of Health, United States

  • Author: Merkle, Hellmut

    National Institutes of Health, United States

  • Author: Lin, Penghui

    University of Kentucky, United States

  • Author: Reed, Galen

    GE Healthcare, United States

  • Author: Chen, Albert P.

    GE Healthcare, United States

  • Author: Ardenkjaer-Larsen, Jan Henrik

    Magnetic Resonance, Department of Health Technology, Technical University of Denmark, Ørsteds Plads, 2800, Kgs. Lyngby, Denmark

  • Author: Munasinghe, Jeeva P.

    National Institutes of Health, United States

  • Author: Saito, Keita

    National Institutes of Health, United States

  • Author: Yamamoto, Kazutoshi

    National Institutes of Health, United States

  • Author: Choyke, Peter L.

    National Institutes of Health, United States

  • Author: Mitchell, James B.

    National Institutes of Health, United States

  • Author: Lane, Andrew N.

    University of Kentucky, United States

  • Author: Fan, Teresa Wm

    University of Kentucky, United States

  • Author: Linehan, W. Marston

    National Institutes of Health, United States

  • Author: Krishna, Murali C.

    National Institutes of Health, United States

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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.

Original languageEnglish
Article numbere46312
JournaleLife
Volume8
Number of pages29
ISSN2050-084X
DOIs
Publication statusPublished - 13 Aug 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Cancer biology, Imaging, Magnetic resonance spectroscopy, Metabolism, Metabolomics, Mouse, MRI, Tumor microenvironment

ID: 194761301