New NMR cancer model: Tracking progress

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  • Published: Oct 15, 2013
  • Author: David Bradley
  • Channels: NMR Knowledge Base
thumbnail image: New NMR cancer model: Tracking progress

No modelling opportunity

The sum of 128 dynamic 13C spectra from representative in vitro (top) and in vivo (bottom) data acquired after injection of hyperpolarized [1-13C]pyruvate. Credit: Hill et al/PLOS One)

A new modelling technique for real-time tracking of metabolic reactions in tumours has been developed by UK researchers. The system based on a simplified computer model of nuclear magnetic resonance spectra could allow oncologists to assess how well their prescribed treatment, whether chemotherapy, radiotherapy or an immunological treatment is progressing without surgical intervention nor the need for regular biopsies.

The research was carried out by a team from The Institute of Cancer Research, in London, UK and was published in the journal PLOS One. The new approach reduces the complexity of analyses but nevertheless allows researchers to probe the rates of metabolic chemical reactions in living cells using dynamic nuclear polarization nuclear magnetic resonance (DNP-NMR spectroscopy). DNP-NMR gives a much-needed 10000-fold boost to the NMR signals but the data that emerges rely on computer modelling of the particular reaction being investigated making interpretation a more complicated and time-consuming process than it ought to be.

To simplify the process and give the technique wider utility, the ICR team - Deborah Hill, Matthew Orton, Erika Mariotti, Jessica Boult, Rafal Panek, Maysam Jafar, Harold Parkes, Yann Jamin, Maria Falck Miniotis, Nada Al-Saffar, Mounia Beloueche-Babari, Simon Robinson, Martin Leach, Yuen-Li Chung and Thomas Eykyn - have developed a new mathematical method for DNP-NMR - which compares the intensity ratios of the chemicals being studied, called the area under the curve (AUC). They refer to their method as a model free approach to kinetic analysis.

Pyruvate proving principle

Eykyn, who works in the Cancer Research UK and EPSRC Cancer Imaging Centre at ICR explains: "The ability to see chemical reactions taking place in live cells in real time is very exciting because it could help researchers developing cancer treatments assess their response. DNP-NMR is a promising technique, but previously it required a lot of complicated computer modelling which limited its uses. Our new method takes away the complications of using these models, simplifying DNP-NMR. We found that we could make the analysis much more straightforward which means this scan could be used more widely in the future, providing real benefits to doctors treating patients or to assess therapeutics entering the clinic."

Proof of principle was demonstrated by injecting the metabolite pyruvate into laboratory cancer cells and observing the effect of the enzyme lactate dehydrogenase on this compound as it rapidly converts it to lactate. The team found that their new AUC ratio accurately revealed the rates of interconversion of pyruvate and lactate. This data corroborated the results prediction from conventional reaction rate models. The team had similar success with several other cancer cell types and also in colon tumour models in mice.

Anticancer kinetics

The next step was to see how the results would change with the addition of an anticancer drug - dichloroacetate - to the equation. This experimental compound is used in laboratory tests but is not being mooted as a cancer drug for use in people. Nevertheless, it blocks upstream signalling pathways that influence pyruvate to lactate exchange. This led to a fall in the AUC ratio, which the team explains reflects a decrease in the reaction rate calculated from the old model.

"This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized carbon-13 metabolic imaging in humans, where measurement of the input function can be problematic," the team concludes.

"We plan to apply these techniques now to better understand how novel therapies currently in development affect cancer metabolism and thereby use our techniques to assess how these treatments are working," Eykyn told SpectroscopyNOW.

Related Links

Plos One 2013, 8(9): e71996: "Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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