Cancer metabolism in a snapshot: MRS(I)

다국어 초록 (Multilingual Abstract)

The contribution of MRS(I) to the in vivo evaluation of cancer‐metabolism‐derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by 13C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1‐13C] pyruvate (Pyr). Hot‐spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr 13C‐labelled ratio with respect to untreated or non‐responding tumour. For therapeutic agents inducing tumour hypoxia, the 13C‐labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. 31P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2‐hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N‐acetylaspartate (plain ratio or CNI index)) or the whole 1H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.
The role of MRSI(I) for cancer metabolism assessment, mostly since 2016, is reviewed. Strategies include the following: (1) quantification of single oncometabolite content such as 2HG; (2) selected metabolite ratios such as total Cho to NAA in gliomas, ratios related to Cho, Cr, citrate and polyamines in prostate cancer or Lac/Pyr in hyperpolarized 13C MRSI; and (3) the whole 1H MRSI(I) pattern, through pattern recognition analysis, allowing detection of response to therapy in preclinical brain tumours before detectable volume changes.