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

Shun Kishimoto, Jeffrey R. Brender, Daniel R. Crooks, Shingo Matsumoto, Tomohiro Seki, Nobu Oshima, Hellmut Merkle, Penghui Lin, Galen Reed, Albert P. Chen, Jan Henrik Ardenkjaer-Larsen, Jeeva Munasinghe, Keita Saito, Kazutoshi Yamamoto, Peter L. Choyke, James Mitchell, Andrew N. Lane, Teresa Wm Fan, W. Marston Linehan, Murali C. Krishna

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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.

Original languageEnglish
Article numbere46312
JournaleLife
Volume8
Number of pages29
ISSN2050-084X
DOIs
Publication statusPublished - 13 Aug 2019

Keywords

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

Cite this

Kishimoto, S., Brender, J. R., Crooks, D. R., Matsumoto, S., Seki, T., Oshima, N., ... Krishna, M. C. (2019). Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice. eLife, 8, [e46312]. https://doi.org/10.7554/eLife.46312
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 Wm ; Linehan, W. Marston ; Krishna, Murali C. / Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice. In: eLife. 2019 ; Vol. 8.
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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.",
keywords = "Cancer biology, Imaging, Magnetic resonance spectroscopy, Metabolism, Metabolomics, Mouse, MRI, Tumor microenvironment",
author = "Shun Kishimoto and Brender, {Jeffrey R.} and Crooks, {Daniel R.} and Shingo Matsumoto and Tomohiro Seki and Nobu Oshima and Hellmut Merkle and Penghui Lin and Galen Reed and Chen, {Albert P.} and Ardenkjaer-Larsen, {Jan Henrik} and Jeeva Munasinghe and Keita Saito and Kazutoshi Yamamoto and Choyke, {Peter L.} and James Mitchell and Lane, {Andrew N.} and Fan, {Teresa Wm} and Linehan, {W. Marston} and Krishna, {Murali C.}",
year = "2019",
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Kishimoto, S, Brender, JR, Crooks, DR, Matsumoto, S, Seki, T, Oshima, N, Merkle, H, Lin, P, Reed, G, Chen, AP, Ardenkjaer-Larsen, JH, Munasinghe, J, Saito, K, Yamamoto, K, Choyke, PL, Mitchell, J, Lane, AN, Fan, TW, Linehan, WM & Krishna, MC 2019, 'Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice', eLife, vol. 8, e46312. https://doi.org/10.7554/eLife.46312

Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice. / 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 Wm; Linehan, W. Marston; Krishna, Murali C.

In: eLife, Vol. 8, e46312, 13.08.2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice

AU - Kishimoto, Shun

AU - Brender, Jeffrey R.

AU - Crooks, Daniel R.

AU - Matsumoto, Shingo

AU - Seki, Tomohiro

AU - Oshima, Nobu

AU - Merkle, Hellmut

AU - Lin, Penghui

AU - Reed, Galen

AU - Chen, Albert P.

AU - Ardenkjaer-Larsen, Jan Henrik

AU - Munasinghe, Jeeva

AU - Saito, Keita

AU - Yamamoto, Kazutoshi

AU - Choyke, Peter L.

AU - Mitchell, James

AU - Lane, Andrew N.

AU - Fan, Teresa Wm

AU - Linehan, W. Marston

AU - Krishna, Murali C.

PY - 2019/8/13

Y1 - 2019/8/13

N2 - 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.

AB - 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.

KW - Cancer biology

KW - Imaging

KW - Magnetic resonance spectroscopy

KW - Metabolism

KW - Metabolomics

KW - Mouse

KW - MRI

KW - Tumor microenvironment

U2 - 10.7554/eLife.46312

DO - 10.7554/eLife.46312

M3 - Journal article

VL - 8

JO - eLife

JF - eLife

SN - 2050-084X

M1 - e46312

ER -

Kishimoto S, Brender JR, Crooks DR, Matsumoto S, Seki T, Oshima N et al. Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice. eLife. 2019 Aug 13;8. e46312. https://doi.org/10.7554/eLife.46312