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Investigating the metabolism of brain tumours using hyperpolarized magnetic resonance imaging

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  • Full or part time
    Prof K M Brindle
  • Application Deadline
    Applications accepted all year round

Project Description

Patients with similar tumour types can show markedly different responses to the same therapy. The development of new treatments would benefit, therefore, from the introduction of imaging methods that allow an early assessment of treatment response in individual patients, allowing rapid selection of the most effective treatment [1].

We have been developing methods for detecting the early responses of tumours to therapy, including magnetic resonance (MR) imaging of tumour cell metabolism using hyperpolarized 13C-labelled cell metabolites. Nuclear spin hyperpolarization can increase sensitivity in the MR experiment by >10,000x. This has allowed us to image the location of labelled cell substrates in vivo and, more importantly, their metabolic conversion into other metabolites. These substrates include pyruvate [2], lactate [3], glutamine [4], glutamate [5], fumarate [6], bicarbonate [7] and ascorbate [8] and glucose [9]. Reviewed in [10]. Exchange of hyperpolarized 13C label between lactate and pyruvate can be imaged in models of lymphoma and glioma and this flux is decreased post-treatment [2,11]. Hyperpolarized [1,4-13C]fumarate can be used to detect tumour cell necrosis post treatment in lymphoma [6] and both the polarized pyruvate and fumarate experiments detected early evidence of treatment response in a breast tumour model [12] and also early responses to anti-vascular [13] and anti-angiogenic drugs [14]. Tissue pH can be imaged from the ratio of the signal intensities of hyperpolarized H13CO3¯ and 13CO2 following intravenous injection of hyperpolarized H13CO3¯ [7] and tumour redox state can be determined by monitoring the oxidation and reduction of [1-13C]ascorbate and [1-13C]dehydroascorbate respectively [8]. Tumour glycolysis can be monitored by measuring the conversion of hyperpolarized [U-2H, U-13C]glucose to lactate and this flux was shown to decrease post-treatment [9]. More recently we have shown that we can follow, using hyperpolarized [1-13C]pyruvate, the progression of pancreatic precursor lesions, in a genetically engineered mouse model of the disease, which potentially could be used clinically to guide earlier intervention [15].

We also have used hyperpolarized [1-13C]pyruvate to investigate glycolytic metabolism in patient derived xenograft (PDX) models of glioblastoma (unpublished). These measurements have shown considerable heterogeneity between tumours derived from different patients, which we have evidence is related to underlying oncogenic mutations. Earlier this year we conducted our first study in a patient using this technique (the first outside North America) and will shortly conduct further studies in glioblastoma patients. The aim of this studentship is to use these PDX models to understand the factors responsible for this heterogeneity and then to use this information to gain a greater understanding of what the clinical imaging is telling us about an individual patient’s tumour. Our hypothesis is that these images will have prognostic value and may also predict treatment outcome. The student will learn a variety of techniques, including magnetic resonance imaging and spectroscopy; metabolic biochemistry, particularly as it relates to oncology and tumour cell and molecular biology.





References

References

1. Brindle, K., Nature Rev Cancer, 8, 94-107 (2008)
2. Day, S.E., et al., Nature Med, 13, 1382-1387 (2007)
3. Kennedy, B.W.C., et al., J Am Chem Soc, 134, 4969−4977 (2012)
4. Gallagher, F., et al., Magn. Reson. Med., 60, 253-257 (2008)
5. Gallagher, F., et al., Magn Reson Med, 66, 18-23 (2011)
6. Gallagher, F.A., et al., Proc Natl Acad Sci U S A, 106, 19801-19806 (2009)
7. Gallagher, F., et al., Nature, 453, 940-943 (2008)
8. Bohndiek, S.E., et al., J Am Chem Soc, 133, 11795-11801 (2011)
9. Rodrigues, T.B., et al., Nat Med, 20, 93-97 (2014)
10. Brindle, K.M., J. Amer. Chem. Soc., 137, 6418-6427 (2015)
11. Day, S.E., et al., Magn Reson Med, 65, 557-563 (2011)
12. Witney, T.H., et al., Brit. J. Cancer, 103, 1400-1406 (2010)
13. Bohndiek, S.E., et al., Molecular Cancer Therapeutics, 9, 3278-3288 (2010)
14. Bohndiek, S.E., et al., Cancer Research, 72, 854-864 (2012)
15. Serrao, E.M., et al., Gut, 65, 465–475 (2016)

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FTE Category A staff submitted: 189.63

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