MRS – Response to Therapy

Altered metabolism is now considered an emerging hallmark of cancer ¹. The rapid proliferation rate of cancer cells is associated with specific metabolic demands. The cells have to adapt to a hostile microenvironment with restricted supply of nutrients, and further they need to convert nutrients into biomass while at the same time maintaining sufficient energy production². The cancer-specific metabolic phenotype with increased glucose consumption and aerobic lactate production, a phenomenon known as the Warburg effect is well established. In addition, abnormal phospholipid metabolism and shunting of metabolites from the glycolysis into the pentose phosphate pathway is also commonly associated with cancer^{3, 4}. Further, some tumors show a high demand of glutamine to sustain tumor proliferation⁵. Several oncogenes and tumor suppressors are closely linked with metabolic processes, and cancer therapy is known to affect metabolism. Hence, the abnormal metabolism in cancer is increasingly recognized as a potential target for treatment in itself, but also as a source for novel biomarkers that can be used for diagnosis, treatment stratification, and prediction and monitoring of treatment response. Since response and resistance to chemotherapy or targeted drugs cannot be accurately predicted using current traditional biomarkers, individual monitoring of respo nse to therapy is an integral part of most cancer treatments. Early assessment of response can identify non-responders and allow rapid discontinuation or change of drug regimen.

Magnetic resonance spectroscopy (MRS) can be used to determine the concentration of various metabolites in vivo as well as ex vivo in biofluids, cell extracts and intact tissue specimens. MRS is therefore well suited for identification of relevant biomarkers for monitoring and prediction of response to therapy. This lecture will give an update on the current status on the use of in vivo MRS in clinical trials of response to cancer therapy, and further discuss applications of ex vivo MRS as a complementary tool to this. Emphasis will be put on the motivation and rationale for such work, the potential challenges and pitfalls, and finally analytical strategies for quantification and data handling.