Metabolic profiling reveals potential metabolic markers associated with Hypoxia Inducible Factor-mediated signalling in hypoxic cancer cells

Abstract

Hypoxia inducible factors (HIFs) plays an important role in oxygen compromised environments and therefore in tumour survival. In this research, metabolomics has been applied to study HIFs metabolic function in two cell models: mouse hepatocellular carcinoma and human colon carcinoma, whereby the metabolism has been profiled for a range of oxygen potentials. Wild type cells have been compared to cells deficient in HIF signalling to reveal its effect on cellular metabolism under normal oxygen conditions as well as low oxygen, hypoxic and anoxic environments. Characteristic responses to hypoxia that were conserved across both cell models involved the anti-correlation between 2-hydroxyglutarate, 2-oxoglutarate, fructose, hexadecanoic acid, hypotaurine, pyruvate and octadecenoic acid with 4-hydroxyproline, aspartate, cysteine, glutamine, lysine, malate and pyroglutamate. Further to this, network-based correlation analysis revealed HIF specific pathway responses to each oxygen condition that were also conserved between cell models. From this, 4-hydroxyproline was revealed as a regulating hub in low oxygen survival of WT cells while fructose appeared to be in HIF deficient cells. Pathways surrounding these hubs were built from the direct connections of correlated metabolites that look beyond traditional pathways in order to understand the mechanism of HIF response to low oxygen environments.

Figure 1. Principal components analysis (PCA) scores plots of PC 1 versus PC 2 for intracellular FT-IR metabolic fingerprints of HEPA-1 wild type (WT) (left) and C4 (right) cells exposed to 21% oxygen, 1%, 5% and 0% oxygen.

In both cell lines, intracellular profiles from 21% and 5% oxygen group and separate from 1% and 0% highlighting the similarity between 21% and 5%.

Figure 2. Principal components analysis (PCA) on all HCT 116 metabolic profiles analysed using gas chromatography-mass spectrometry (GC-MS).

The quality control (QC) samples formed from pooling small quantities from each sample displayed on the plot fall approximately in the middle. WT = wild type; DN = dominant negative.

Figure 3. Canonical variates analysis (CVA) scores plots for (a) HCT 116 wild type (WT), (b) HEPA-1 WT, (c) HCT 116 dominant negative (DN) and (d) HEPA-1 C4 samples comparing all 3 oxygen conditions.

Each CVA model was built using 8 principal components (PCs) collectively accounting for between 80% and 90% of the total explained variance from each analysis. In all cases the greatest separation in the data was between normoxic samples and low oxygen samples in canonical variate (CV) 1.

Figure 4. Canonical variates analysis (CVA) of hypoxic (1% oxygen) samples in the HCT 116 (a,b) and HEPA-1 (c,d) cell models.

In each case the CVA models were built using principal components (PCs) 1–12 accounting for approximately 90% or the total explained variance. The distributions of samples in canonical variate (CV) 1 for each cell model are represented as bar charts (a,c) where the number of samples per bin is shown. The loadings for CV 1 for each cell model are shown (b,d). The peak number refers to unique metabolites and follows the same order as in Table 1 of supplementary information.

Figure 5. Network-based correlation analysis for HCT 116 and HEPA-1 cell models.

Conserved correlation differences between normoxia, hypoxia and anoxia were mapped onto the EHMN reconstruction using a shortest path analysis described previously. Pathways are coloured according to which oxygen levels correlation differences occurred and are presented for a) WT cells and b) HIF-1 deficient cells of both models. KEGG compound and reaction identifiers are indicated. Tyrosine and tyramine are contained in a box to denote that this metabolite was not definitively identified in the GC-MS analysis.

Figure 6. The interaction between pyruvate, 2-oxoglutarate and 2-hydroxyglutarate and central carbon metabolism.

2-hydroxyglutarate dehydrogenase (KEGG enzyme 1.1.99.2) catalyses a reversible reaction between 2-oxoglutarate and 2-hydroxyglutarate. All 3 metabolites feed into the tricarboxylic acid (TCA) cycle.

Figure 7. Fatty acid (FA) biosynthesis.

Hexadecanoic acid and octadecenoic acid are two of the end points of FA biosynthesis that metabolises acetyl-coA via malonyl-coA. Acetyl-CoA carboxylase alpha (KEGG enzyme 6.4.1.2).