Deconvolving metabolic intratumoral heterogeneity in clear cell renal carcinoma with hyperpolarized 13C-pyruvate MRI

Background Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous cancer requiring a large number of biopsies to correctly characterize the tumor. Multiple biopsies are rarely feasible in the clinical setting, and therefore imaging methods offer the potential to evaluate the whole tumor non-invasively. For example, metabolic imaging offers the potential to probe the altered metabolism and metabolic heterogeneity that is characteristic of ccRCC. In this study we have explored and validated the use of hyperpolarized carbon-13 MRI (HP- ¹³ C-MRI) as a non-invasive clinical tool to probe metabolic heterogeneity in ccRCC patients and to more accurately identify which metabolic pathways are altered in vivo . Methods 58 tumor and healthy tissues biopsies were acquired postoperatively from 6 ccRCC patients imaged following injection of hyperpolarized [1- ¹³ C]pyruvate. MRI parameters were correlated with the metabolomic (146 metabolites) and transcriptomic (2523 metabolic genes) data obtained from these biopsies, split across 34 metabolic pathways. The results were used to generate metabologram projections as a visual representation of these metabolic differences. For each metabolic pathway, we generated a novel metabolic consensus scoring system for the identification of key altered metabolic pathways in ccRCC and their relationship to the imaging parameters. Results We show that the apparent exchange constant between pyruvate and lactate ( k _PL ) and the lactate to pyruvate ratio (LP _r ) on MRI can be used to measure differential metabolic pathways: they correlated positively with glycolysis and the pentose phosphate pathway, negatively with the TCA cycle, while also correlating with other pathways. Dichotomizing the imaged signal based on high and low k _PL measurements was sufficient to discriminate metabolic distinct regions on biopsy and this could be a simple tool to assess metabolism clinically. Furthermore, metabolic heterogeneity increased in regions with a higher k _PL and could be used to assess metabolic divergence. Conclusion This work validated the role of HP- ¹³ C-MRI to measure not only glycolysis, but also a range of other altered metabolic pathways in ccRCC. This could improve tumor stratification and provide novel methods to monitor treatment response. Metabolic imaging can also be used to guide biopsy acquisition based on metabolic alterations, and therefore could improve tumour characterization.