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

ABSTRACT: 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.

SUBMITTER: Kishimoto S

PROVIDER: S-EPMC6706239 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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

Kishimoto Shun S Brender Jeffrey R JR Crooks Daniel R DR Matsumoto Shingo S Seki Tomohiro T Oshima Nobu N Merkle Hellmut H Lin Penghui P Reed Galen G Chen Albert P AP Ardenkjaer-Larsen Jan Henrik JH Munasinghe Jeeva J Saito Keita K Yamamoto Kazutoshi K Choyke Peter L PL Mitchell James J Lane Andrew N AN Fan Teresa Wm TW Linehan W Marston WM Krishna Murali C MC

eLife 20190813

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 noi ...[more]

PMID: 31408004

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Project description:Transcriptomic studies have attempted to classify glioblastoma (GB) into subtypes that predict survival and that have different therapeutic vulnerabilities. Here we identified three metabolic subtypes: glycolytic, oxidative and a mixed glycolytic/oxidative by mass spectrometry imaging of rapidly excised tumour sections from two GB patients infused with [U-13C]glucose and from spatial transcriptomic analysis of contiguous sections. The phenotypes did not correlate with microenvironmental features, including proliferation rate, immune cell infiltration, and vascularisation, were retained when patient-derived cells were grown in vitro, or as orthotopically implanted xenografts, and were robust to changes in oxygen concentration, demonstrating their cell intrinsic nature. The spatial extent of the regions occupied by cells displaying these distinct metabolic phenotypes are large enough to be detected using clinically applicable metabolic imaging techniques. A limitation of the study is that it is based on only two patient tumours, albeit on multiple sections, and therefore represents a proof-of-concept study. Glioblastoma is the most common primary adult brain cancer. Transcriptomic analyses have attempted to classify GB into subtypes that could predict treatment response, with a recent study that used a pathway-based classification defining metabolism-associated subtypes with distinct therapeutic vulnerabilities. These included a mitochondrial subtype, which is associated with a more favourable clinical outcome and that is sensitive to inhibitors of oxidative phosphorylation, and a glycolytic/plurimetabolic subtype that is resistant to multiple treatment types. An important question is the extent to which the metabolism displayed by tumour cells in vivo are cell intrinsic and how much they are defined by the tumour microenvironment. We have addressed this question using mass spectrometry imaging of rapidly excised tumour sections from GB patients infused with [U-13C]glucose immediately prior to surgery to image tumour cell metabolic fluxes in vivo and from a spatial transcriptomic analysis of adjacent sections. To our knowledge, this is the first report demonstrating high resolution imaging of metabolic fluxes in a human tumour in vivo.

Dataset Information

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

Publications

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

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