Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification

Abstract

Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and down-regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS)-based metabolomics. HCC was characterized by ∼2-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism.

Conclusion: Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process.

Fig. 1

Total fatty acid (free and esterified) content of 31 paired tumor (T) and uninvolved (N) tissues. Ordinates are relative concentrations (peak area/internal standard peak area/mg tissue). NS means difference not statistically significant.

Fig. 2

GCMS tissue metabolomics of 31 paired HCC tumors and uninvolved liver. (A) PLS-DA scores plot showing almost complete separation of tumors (red) and uninvolved liver tissues (green). (B) Validation of the PLS-DA model by 50 permutations of the data showing degradation of R2 to below 0.3 and Q2 to below 0. (C) OPLS-DA loadings S-plot showing downregulated metabolites (red) in tumor tissue that were significantly correlated to the OPLS-DA model. These metabolites comprised glucose, glycerol 3-phosphate, glycerol 2-phosphate, malate, alanine, and myo-inositol.

Fig. 3

Univariate statistical analysis of six metabolites identified as downregulated in HCC tumor tissues by PLS-DA analysis. Abscissae are relative concentrations (peak area/internal standard peak area/mg tissue). Red and green symbols represent tumor and unaffected tissue samples, respectively. Red and green dotted lines represent median values for tumor and unaffected tissue samples, respectively. Data were analyzed using Wilcoxon matched pairs test.

Fig. 4

OPLS-DA loadings S-plots for 59 HCC tissues typed as transcriptomic subgroups G1 to G6 and analyzed by GCMS. Of the 15 possible S-plots for G1 to G6, eight are shown for comparisons of G1 to G2, G4, G5, and G6, together with comparisons of G3 with G2, G4, G5, and G6. Abscissa units of p[1] are proportional to concentration and ordinate units of p(corr)[1] are a measure of the correlation of any loading (metabolite) to the OPLS-DA model. Red symbols correspond to the monoacylglycerols 1-palmitoylglycerol and 1-stearoylglycerol, which were elevated in G2, G4, G5, and G6 relative to G1 with similar comparisons shown for G3.

Fig. 5

Univariate statistical analysis for 10 metabolites in HCC tumor samples according to transcriptomic groups G1 to G6. Note no statistically significant differences in tissue lactate, glucose, glycerol 3-phosphate, malate, alanine, myo-inositol, and stearic acid across groups G1 to G6. Group G1 displayed significantly lower (P< 0.05) levels of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid than certain other groups (shown in green). Data were analyzed by Kruskal-Wallis with Dunn’s correction for multiple comparisons.

Fig. 6

Univariate statistical analysis for four metabolites in HCC tumor tissue transcriptomic group G1 versus all other groups G2-G6 combined. NS means difference not statistically significant. Data analyzed by two-tailed Mann-Whitney U test.