Skip to main content
Download PDF

Mutant IDH and non-mutant chondrosarcomas display distinct cellular metabolomes

Cancer & Metabolism volume 9, Article number: 13 (2021) Cite this article

Abstract

Background

Majority of chondrosarcomas are associated with a number of genetic alterations, including somatic mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes, but the downstream effects of these mutated enzymes on cellular metabolism and tumor energetics are unknown. As IDH mutations are likely to be involved in malignant transformation of chondrosarcomas, we aimed to exploit metabolomic changes in IDH mutant and non-mutant chondrosarcomas.

Methods

Here, we profiled over 69 metabolites in 17 patient-derived xenografts by targeted mass spectrometry to determine if metabolomic differences exist in mutant IDH1, mutant IDH2, and non-mutant chondrosarcomas. UMAP (Uniform Manifold Approximation and Projection) analysis was performed on our dataset to examine potential similarities that may exist between each chondrosarcoma based on genotype.

Results

UMAP revealed that mutant IDH chondrosarcomas possess a distinct metabolic profile compared with non-mutant chondrosarcomas. More specifically, our targeted metabolomics study revealed large-scale differences in organic acid intermediates of the tricarboxylic acid (TCA) cycle, amino acids, and specific acylcarnitines in chondrosarcomas. Lactate and late TCA cycle intermediates were elevated in mutant IDH chondrosarcomas, suggestive of increased glycolytic metabolism and possible anaplerotic influx to the TCA cycle. A broad elevation of amino acids was found in mutant IDH chondrosarcomas. A few acylcarnitines of varying carbon chain lengths were also elevated in mutant IDH chondrosarcomas, but with minimal clustering in accordance with tumor genotype. Analysis of previously published gene expression profiling revealed increased expression of several metabolism genes in mutant IDH chondrosarcomas, which also correlated to patient survival.

Conclusions

Overall, our findings suggest that IDH mutations induce global metabolic changes in chondrosarcomas and shed light on deranged metabolic pathways.

Background

Over the past decade, reprogramming of cellular metabolism has gained attention as an emerging hallmark of cancer [1], but metabolic studies of bone and cartilage tumors have been limited. Chondrosarcomas are the most common malignancy of cartilage. They are associated with a number of genetic alterations including somatic mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 [2, 3]. IDH mutations have been identified in 38–70% of chondrosarcoma cases [4] and for this reason, IDH has been identified as a potential driver mutation. However, 52–87% of the benign precursor lesion, enchondromas, also harbor IDH mutations [4], suggesting that the abnormal IDH genes could potentially orchestrate early events in chondrosarcoma formation. These mutations are also found in several neoplasms including gliomas, glioblastomas, and acute myeloid leukemia [3].

IDH1 and IDH2 are located in the cytosol and mitochondria respectively, and catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) [5]. The mutant enzyme loses its ability to convert isocitrate to α-KG, and instead gains a neomorphic function to produce D-2-hydroxyglutarate (D-2HG), which has been referred to as an “oncometabolite” [6]. IDH mutations have been reported to be involved in epigenetic remodeling [7], stabilization of hypoxia-inducible factor 1a (HIF1α) [8], and regulation of alternative energetic pathways such as fatty acid metabolism [9].

Here, we have utilized a targeted metabolomics approach [10] to uncover potential metabolic differences between mutant IDH and non-mutant chondrosarcomas. Specifically, we compared metabolomic profiles of 4 IDH non-mutant chondrosarcomas with 8 mutant IDH1 and 5 mutant IDH2 chondrosarcomas (Table 1) using targeted gas chromatography-mass spectrometry (GC/MS) and flow-injection tandem mass spectrometry (MS/MS) methods [10]. By measuring a large number of metabolites, profiles of chondrosarcoma tissues were constructed to comprehensively cover a number of biological processes and metabolic pathways. This approach has been used by others to identify novel metabolic biomarkers and mechanisms in cancer, stem cells, and healthy tissues [10,11,12,13]. Our results highlight a number of metabolomic alterations and differentially regulated metabolic pathways in mutant IDH compared with non-mutant chondrosarcomas.

Table 1 Sequence results and clinicopathological information of chondrosarcomas used for metabolomics analysis
Full size table

Methods

The aim of this study was to assess the metabolic differences between mutant IDH and non-mutant chondrosarcomas. To identify and quantify metabolites in patient-derived chondrosarcoma xenograft tissue extracts, we performed targeted GC/MS or flow-injection MS/MS methods.

Patient-derived xenograft establishment

All human chondrosarcoma samples were handled according to the ethical guidelines of the host institutions. With institutional review board (IRB) approval, human chondrosarcoma tumor samples were obtained fresh from surgery. Within 24 h, tumors were cut into 2-mm3 pieces in sterile conditions and were subcutaneously implanted into the flank region of interleukin-2 receptor gamma chain (gamma)-null NOD/SCID (NSG) mice. Tumors were excised once maximal tumor capacity of 2.5 cm was reached. An important consideration in studying tumor metabolomics in patients is variability due to differences in diet, time of surgery, and the presence of medical comorbidities. To control for these patient-specific factors, we established patient-derived chondrosarcoma xenografts in immunodeficient mice. This allowed us to study chondrosarcoma tumor metabolism by eliminating these confounding factors.

Sequencing

Chondrosarcoma xenograft tumors were genotyped by extracting genomic DNA using the DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer’s protocol. Sanger sequencing was performed to analyze the samples for IDH1 and IDH2 mutations after PCR amplification on exon 4 of IDH1 and IDH2 (Table 1). Sequencing results were analyzed on 4Peaks software to confirm mutational status of each tumor.

Metabolite profiling

To prepare tumors for metabolomics analysis, tumors were pulverized using a prechilled cell crusher in liquid nitrogen. Approximately 50 mg of tumor tissue was added into a prechilled vial and homogenizing solvent (50% aqueous acetonitrile containing 0.3% formic acid) was added to achieve the desired tissue concentration of 50 mg/ml. Mini-BeadBeater Zirconia-Silicate Beads (BioSpec Products), 0.5 mm, were added to the vial to aid with homogenization. Samples were homogenized using Mini-BeadBeater (BioSpec Products) set to a frequency of 30 oscillations/s for 2 min. Metabolic quantification was performed by gas chromatography-mass spectrometry (GC/MS) or flow-injection tandem mass spectrometry (MS/MS) as described previously [14, 15]. Amino acids, acylcarnitines, and organic acids were analyzed using the stable isotope dilution technique. Amino acids and acylcarnitine measurements were made by flow-injection tandem mass spectrometry using sample preparation methods described previously [16, 17]. The data were acquired using a Waters TQD mass spectrometer equipped with an AcquityTM UPLC system and controlled by MassLynx 4.1 operating system (Waters, Milford, MA). Organic acids were quantified using methods described previously [18] employing Trace Ultra GC coupled to ISQ MS operating under Xcalibur 2.2 (Thermo Fisher Scientific, Austin, TX). Data analysis of metabolites was performed using Student’s t-test (p < 0.05).

UMAP analysis

To evaluate relative similarities between each chondrosarcoma, data was processed using Uniform Manifold Approximation and Projection [19] (UMAP) for dimensional reduction and visualization. In total, 7 organic acids, 17 amino acids, and 45 acylcarnitines were screened and separate UMAP projections were performed for each metabolite group (i.e., three groups with 17 tumors and 7, 17, or 45 dimensions). First, data was pre-processed by scaling the mean and variance (μ = 0 and σ = 1). Then, UMAP was performed for 2D visualization (R version 4.0.0 [20]); Package “Seurat” (Stuart, Butler, Hoffman, et al., 2019)-function RunUMAP; nearest neighbors: 15, minimum distance: 0.7, distance metric: Euclidean). After UMAP projection, tumors were labeled based on their genotype and evaluated qualitatively.

Carbon isotope labeling

Chondrosarcoma cells were cultured in DMEM with 1000mg/L 13C6-Glucose in 6-cm cell culture plates for 6 h. A total of 500 μL methanol was used to extract metabolites from each plate. After centrifuging at 12000 rpm for 15 min, supernatant was dried at 37 °C. The dried residues were resuspended in 25 μL of methoxylamine hydrochloride (2% (w/v) in pyridine) and incubated at 40 °C for 1.5 h in a heating block. After brief centrifugation, 35 μL of MTBSTFA + 1% TBDMS was added, and the samples were incubated at 60 °C for 30 min. The derivatized samples were centrifuged for 5 min at 20,000×g, and the supernatants were transferred to GC vials for GC-MS analysis. A modified GC-MS method was employed [21]. The injection volume was 1 μL, and samples were injected in splitless mode. GC oven temperature was held at 80 °C for 2 min, increased to 280 °C at 7°C/min, and held at 280 °C for a total run time of 40 min. GC-MS analysis was performed on an Agilent 7890B GC system equipped with a HP-5MS capillary column (30 m, 0.25 mm i.d., 0.25-μm phase thickness; Agilent J&W Scientific, Santa Clara, CA), connected to an Agilent 5977A Mass Spectrometer operating under ionization by electron impact (EI) at 70 eV. Helium flow was maintained at 1 mL/min. The source temperature was maintained at 230 °C, the MS quad temperature at 150 °C, the interface temperature at 280 °C, and the inlet temperature at 250 °C. Mass spectra were recorded in mass scan mode with m/z from 50 to 700.

13C-based stable isotope analysis

M0, M1, …, Mn refers to the isotopologues containing n heavy atoms in a molecule. The stable isotope distribution of individual metabolites was measured by GC-MS as described above. The isotopologue enrichment or labeling in this work refers to the corrected isotope distribution [22, 23]. To determine the flux from citrate/isocitrate to α-ketoglutarate, we normalized the % of 13C-α-ketoglutarate to the percentage of 13C-citrate/isocitrate.

Gene expression profiling data analysis

Chondrosarcoma gene expression data was previously published by another group in their identification of genes that determine disease progression [24]. Their mRNA microarray data and chondrosarcoma sample information [25] E-MTAB-7264 (https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-7265/) were downloaded from the European Bioinformatics Institute database [26] [PMID: 31604924]. Microarray data was normalized using the RMA algorithm with the “oligo” package [PMID: 20688976]. Gene expression data was further scaled for the generation of heatmaps. For survival analysis, samples were grouped into high/low expression based on median gene expression and plotted using the “survminer” package.

Results

Mutant IDH1 and IDH2 chondrosarcomas display an elevation of glycolytic and TCA cycle intermediates compared with non-mutant chondrosarcomas

To examine whether mutant IDH chondrosarcomas display metabolomic differences in comparison with non-mutant chondrosarcomas, we used gas chromatography/mass spectrometry (GC/MS) to profile 7 organic acids generated by glycolysis and the TCA cycle. Mutant IDH1 and IDH2 chondrosarcomas displayed a 3.5-fold elevation of lactate (Fig. 1b), coupled with a trend for increase of pyruvate (Fig. 1a), suggestive of enhanced glycolytic metabolism of glucose in mutant IDH chondrosarcomas.

Fig. 1
figure 1

Organic acid quantification of non-mutant, mutant IDH1, and mutant IDH2 chondrosarcoma tissue by gas chromatography/mass spectrometry (GC/MS). Quantification of glycolytic a pyruvate, b lactate and TCA cycle metabolites c citrate, d ⍺-ketoglutarate, e succinate, f fumarate, g malate, of non-mutant, mutant IDH1, and mutant IDH2 chondrosarcoma tissue. p-value = Student’s t-test p < 0.05, *: significant p-value

Full size image

Five TCA cycle intermediates were also quantified to determine if differences may exist in mitochondrial carbon cycling. Three intermediates generated in the latter part of the TCA cycle, succinate, fumarate, and malate were increased in mutant IDH1 and IDH2 chondrosarcomas compared with non-mutant chondrosarcomas (Fig. 1e–g). A different and more complex profile was found for the early TCA cycle intermediates—citrate and α-KG trended to increase in mutant IDH1 but decrease in mutant IDH2 chondrosarcomas (Fig. 1c, d). These differences may reflect the role of IDH1 in the cytosol as a source of NADPH for de novo lipogenesis [27] and other biosynthetic pathways, whereas IDH2 participates both in oxidative flux of α-ketoglutarate to the later TCA cycle intermediates, as well as reductive carboxylation of α-ketoglutarate to isocitrate and citrate in the mitochondria [28, 29].

Activation of reductive TCA cycle metabolism of glutamine and glutamate via conversion to α-ketoglutarate by the glutamate dehydrogenase reaction and flux to citrate via IDH2 has been invoked as a pathway for synthesis of biomass in growing cancer cells [29,30,31]. If IDH2 mutation impairs reductive flux of glutamine to citrate in chondrocytes, this may help to explain why citrate and α-ketoglutarate are depleted in mutant IDH2 chondrosarcomas (Fig. 1c, d; Supplemental Figure 2). Perhaps related, it has been suggested that citrate and α-ketoglutarate levels are influenced by multiple events limiting entry of carbon into the TCA cycle [30, 32, 33] including reduced mitochondrial NAD+/NADH ratio [30], reduced glutamine metabolism [30, 33], and inactivation of pyruvate dehydrogenase in hypoxic tumors [32].

To examine how mutant IDH alters flux through the TCA cycle, we traced [13C6]-labeled glucose. 13C α-KG labeling was reduced at 6 h in mutant IDH1 and IDH2 chondrosarcoma cells based on measurements of citrate (M2) and pyruvate (M3) labeling (Supplemental Figure 2). This result clarifies that carbon flux through mutant IDH is impaired, explaining depleted α-KG levels (Fig. 1d) in mutant IDH2 chondrosarcomas.

We next performed UMAP clustering analysis [19] on our metabolite dataset to examine if relative similarities exist between each chondrosarcoma genotype group (Supplemental Figure 1). UMAP projections performed on 7 organic acids revealed distinct clustering patterns in non-mutant and mutant IDH chondrosarcomas (Supplemental Figure 1A). Although organic acids in mutant IDH1 and mutant IDH2 chondrosarcomas did not cluster separately from one another, they clustered separately from the non-mutant group (Supplemental Figure 1A). UMAP projections reveal that chondrosarcomas of identical genotypes exhibit similar organic acid profiles. Taken together, our data is consistent with the notion that mutant IDH chondrosarcomas not only display high glycolytic and TCA cycle intermediates for energy production and maintenance but also display a distinct organic acid profile in comparison with non-mutant chondrosarcomas.

Global elevation of amino acids in mutant IDH chondrosarcomas in comparison with non-mutant chondrosarcomas

We next measured levels of 17 amino acids by MS/MS and constructed amino acid profiles of each patient tumor. We aimed to characterize overlapping and/or distinct patterns of expression in mutant IDH and non-mutant chondrosarcomas. Irrespective of mutational status, glycine (Gly), glutamate (Glu), glutamine (Gln), and alanine (Ala) were the most abundant amino acids in chondrosarcomas (Fig. 2a–c). This observation is supported by the sharp peak concentrations as indicated from radar profiles of chondrosarcoma tissues (Fig. 2a–c).

Fig. 2
figure 2

Amino acid profiles of non-mutant, mutant IDH, and mutant IDH2 chondrosarcoma tissue quantified by mass spectrometry (MS/MS) display a global elevation in mutant IDH chondrosarcomas. Radar profiles of a non-mutant chondrosarcomas, b mutant IDH1 chondrosarcomas, c mutant IDH2 chondrosarcomas, d scatter plot of amino acids in each genotype of chondrosarcoma. p-value = Student’s t-test p < 0.05, *: significant p-value

Full size image

A broad elevation of amino acids was observed in mutant IDH chondrosarcomas compared with non-mutant tumors (Table 2, Fig. 2d). Twelve of the 17 amino acids measured (Val, Met, His, Gly, Pro, Ser, Asn, Ala, Leu/Ile, Phe, Tyr, and Orn) were significantly elevated in mutant IDH1 chondrosarcomas. These same 12 amino acids exhibited clear trends to increase in mutant IDH2 chondrosarcomas, although only 5 of these (Gly, Gln, Pro, Ser, and Asp) achieved statistical significance (Table 2, Fig. 2d). Mechanisms for this broad increase in amino acids are not revealed by our data, but two possibilities are that mutant IDH may activate autophagy [34,35,36] or protein degradation [37, 38]. We used UMAP clustering analysis to determine if mutant IDH chondrosarcomas displayed distinct amino acid profiles compared with non-mutant chondrosarcomas (Supplemental Figure 1B). Although amino acid profiles of mutant IDH chondrosarcomas clustered together, two mutant IDH1 tumors clustered closely to the non-mutant cluster group (Supplemental Figure 1B).

Table 2 Fold change analysis reveals global elevation of amino acids in mutant IDH chondrosarcomas in comparison with non-mutant chondrosarcomas
Full size table

Amino acids involved in neoplastic energy-yielding pathways are elevated in mutant IDH chondrosarcomas

An abundant supply of amino acids is essential for tumors to sustain their proliferation through energy generation, nucleoside synthesis, protein synthesis, and cellular redox homeostasis [38]. For this reason, specific amino acids are coupled to neoplastic metabolic pathways [39]. Anaplerotic metabolism of amino acids regenerates key TCA cycle and glycolytic intermediates that enable carbon flow and ATP production in neoplastic cells. Further examination of our data suggests that several amino acids elevated by IDH mutations are critical anaplerotic substrates.

Glutamine (Gln) and glutamate (Glu) are involved in glutamine metabolism to fuel reductive and oxidative TCA carbon cycling. Gln and Glu are converted to α-ketoglutarate by the glutamate dehydrogenase reaction or by glutamate transamination. Gln levels trended to increase by 2.8-fold in mutant IDH1 chondrosarcomas and achieved statistical significance in mutant IDH2 chondrosarcomas (Table 2). Glu trended to increase by 3.2-fold and 4.3-fold in mutant IDH1 and mutant IDH2 tumors respectively (Table 2). Additionally, proline (Pro), another critical amino acid metabolized via conversion to glutamate and was found to be elevated in mutant IDH chondrosarcomas (Table 2). This suggests that mutant IDH chondrosarcomas possess a greater reliance of glutamine metabolism.

Alanine (Ala), glycine (Gly), and serine (Ser), which are broadly elevated in mutant IDH chondrosarcomas (Fig. 2d, Table 2), enter pathways of energy production via pyruvate, which in turn can be oxidized via pyruvate dehydrogenase or used as an anaplerotic substrate to generate oxaloacetate via pyruvate carboxylase. Aspartate (Asp) and asparagine (Asn), which are also elevated in mutant IDH tumors (Fig. 2d, Table 2), act as anaplerotic substrates via their conversion to oxaloacetate by aspartate transaminase. A previous study identified that elevated Asp levels serve as an endogenous metabolite, supporting tumor growth via conversion of Asn to Asp by asparaginase activity [40] and maintenance of Asp pools by electron acceptor activity was found to support cell proliferation [41]. Interestingly, our profile suggests that Asn and Asp are crucial substrates for TCA cycle fueling in mutant IDH chondrosarcomas.

Finally, the branched-chain amino acids (BCAAs), valine (Val), leucine (Leu), and isoleucine (Ile), have been implicated in metabolic reprogramming of neoplastic cells to promote cancer growth [42]. Individual Val and Leu/Ile levels were significantly elevated in mutant IDH1 chondrosarcomas and trended to increase in mutant IDH2 chondrosarcomas (Table 2). The increase in Val and Leu/Ile in mutant IDH chondrosarcomas is associated with similar increases in their transamination by-products Glu and Gln (Fig. 2a–d, Table 2).

Acylcarnitine species are elevated in mutant IDH chondrosarcomas

Acylcarnitines are generated by metabolism of fatty acids, glucose, and amino acids, and serve as cognate metabolites to acyl-CoAs generated in the mitochondria and cytosol [14]. We measured 45 independent acylcarnitine species ranging from 2 to 22 carbons in length, and with varying degrees of saturation by MS/MS. Even chain species ranging in length from C6 to C22 arise from fatty acid oxidation [14]. Odd chain species such as C3 (propionylcarnitine) and C5 (isovalerylcarnitine) are produced by amino acid catabolism, whereas C4 (butyrylcarnitine) can be derived from fatty acids or amino acids [14]. Acetylcarnitine (C2) is derived from acetyl-CoA, a common degradation product for many metabolic substrates. As in other tissues, acetylcarnitine (C2) is the most abundant acylcarnitine species in chondrosarcomas.

Interestingly, a number of long-chain lipid-derived acylcarnitines were found to be elevated in mutant IDH chondrosarcomas compared with non-mutant tumors, including oleate (C18:1), palmitate (C16:0), linoleate (C18:2), and stearate (C18:0) (Fig. 3c, Table 3). Consistent with a profile of increased fatty acid oxidation was the increase in C4-OH acylcarnitine (beta-hydroxy butyryl AC) in mutant IDH chondrosarcomas (Fig. 3a, Table 3). C3, C4, and C5 acylcarnitines derived from amino acid catabolism also trended higher in mutant IDH chondrosarcomas (Fig. 3a, Table 3).

Fig. 3
figure 3

Acylcarnitine profiles of non-mutant, mutant IDH1, and mutant IDH2 chondrosarcoma tissues, quantified by mass spectrometry (MS/MS) display an elevation of species in mutant IDH chondrosarcomas. Acylcarnitines classified according to increasing carbon chain length: a short-chain acylcarnitines, b medium-chain acylcarnitines, c long-chain acylcarnitines, d very-long-chain acylcarnitines. p-value = Student’s t-test p < 0.05, *: significant p-value

Full size image
Table 3 Fold change analysis reveals elevated levels of acylcarnitine species in mutant IDH chondrosarcomas
Full size table

To examine relative differences in acylcarnitine metabolism between mutant IDH and non-mutant chondrosarcomas, we compared means of acylcarnitine species in mutant IDH tumors to non-mutant tumors and calculated concentration fold changes (Table 3). From this analysis, we found medium- and long-chain lipid-derived acylcarnitines, C10, C16, and C16:1-OH/C14:1-DC significantly elevated in mutant IDH1 chondrosarcomas compared with non-mutant chondrosarcomas (Table 3). The amino acid-derived acylcarnitines, C5:1 and C4-OH were significantly elevated in mutant IDH2 chondrosarcomas compared with non-mutant tumors (Table 3).

UMAP clustering analysis of 45 acylcarnitines revealed weak clustering of mutant IDH and non-mutant chondrosarcomas (Supplemental Figure 1C). Although majority of mutant IDH chondrosarcomas clustered away from the non-mutant group, these clusters were spatially weak clusters (Supplemental Figure 1C). Although there may be some similarities in acylcarnitine profile in mutant IDH chondrosarcomas, these similarities are not as pronounced as clustering similarities noted in organic acid and amino acid profiles (Supplemental Figure 1A-C). Clustering analysis of the complete dataset of 69 metabolites revealed distinct clustering of mutant IDH chondrosarcomas from non-mutant tumors (Supplemental Figure 1D), emphasizing the notion that mutant IDH chondrosarcomas display a distinct metabolome in comparison with non-mutant chondrosarcomas.

Expression of genes regulating metabolism correlates with prognosis in chondrosarcomas

To determine the significance of our findings in a second chondrosarcoma patient cohort, we explored the expression levels of regulatory genes of metabolic pathways from previously published gene expression and patient survival data [24, 25]. Using normalized microarray gene expression data [24, 25], we found a number of genes involved in various metabolic processes to be elevated in mutant IDH tumors (Supplemental Figure 3A). For instance, genes involved in the regulation of glutamine metabolism, GLS and GLUD1; a biomarker of glycolysis, LDHA; and genes involved in TCA cycle regulation, PDK1, PDHB, MDH1, and SHMT2; were all significantly elevated in mutant IDH chondrosarcomas compared with non-mutant tumors (Supplemental Figure 3A).

The expression levels of a number of these genes significantly correlated with patient survival when analyzed using Kaplan-Meier survival analysis (Supplemental Figure 3B-H). Interestingly, chondrosarcomas with high expression levels of two regulators of acylcarnitine metabolism, CPT1A and FASN, displayed worse patient outcome (Supplemental Figure 3B-C). High expression of regulatory genes of the TCA cycle (SDHAF2, MDH1, MDH2, and PDHB) and glutamine metabolism (GLUD1), were also predictive of patient outcome (Supplemental Figure 3E-H, D). Taken together, these data are constant with the notion that specific metabolites and their associated regulatory genes are critical in chondrosarcoma metabolomics, drive tumor aggressiveness, and are predictive of patient survival.

Discussion

Here we report metabolic differences between mutant IDH chondrosarcomas and non-mutant chondrosarcomas across a spectrum of organic acids, amino acids, and acylcarnitines measured by targeted GC/MS and MS/MS mass spectrometry. Mutant IDH chondrosarcomas display metabolomes enriched for lactate, late-stage TCA cycle intermediates, multiple amino acids, and a subset of acylcarnitine species. Interestingly, UMAP projection analysis of our metabolite dataset revealed that organic acids and amino acids displayed spatially strong and distinct clustering patterns in accordance with each chondrosarcoma genotype. Upon analysis of all 69 metabolites by UMAP, this revealed spatially distinct clustering in mutant IDH chondrosarcomas and non-mutant chondrosarcomas. Thus, from our complete dataset, we were also able to conclude that mutant IDH chondrosarcomas display a distinct metabolic profile compared with non-mutant chondrosarcomas.

Metabolic changes can be cell type dependent, and although other studies show metabolic changes due to IDH mutations in other cell types, data from these studies do not extend to all cell types. Metabolic changes in cell culture may not reflect changes seen in vivo. This is a particular issue in certain tumor types like chondrosarcomas, where the cell phenotype changes in vitro. Indeed, differences in diet, time of surgery, and the presence of medical comorbidities will cause metabolic changes in tumors. To control for these factors while still analyzing tumors in vivo, we studied xenografts, allowing us to control for various external factors. Thus, our approach allows an analysis of chondrosarcoma tumor metabolism eliminating confounding factors of cell culture and patient variability.

We found an elevation of lactate in mutant IDH chondrosarcomas. Conversion of glucose carbon to lactate by the lactate dehydrogenase (LDHA) enzyme is a classic signature of cancer metabolism [43]. More importantly, lactate is not only a metabolic by-product of active glycolysis but has many other consequential effects on cancer bioenergetics and carcinogenesis [43]. Glycolytic tumors that produce lactate create an acidic tumor microenvironment which supports metastasis, angiogenesis, and immunosuppression [44]. It has also been demonstrated that neoplastic cells possess the ability to import lactate into the mitochondria to fuel energy production [45]. While a prior study showed elevated LDHA activity in chondrosarcomas, our data shows that genotype alters the level of lactate, and as such genotype should be taken into account when considering strategies to target this pathway [46].

Hypoxic tumors that have the ability to thrive in low oxygen environments are associated with lactate accumulation [43, 47]. Interestingly, it has been reported that glucose metabolism and hypoxia-inducible factor (HIF1a) levels are elevated in chondrosarcomas and correlated with a higher pathological grade and lower patient survival rate [48]. This suggests that mutant IDH chondrosarcomas possess a greater dependence on glycolysis for energy and are metabolically more active compared with non-mutant chondrosarcomas.

Another metabolic alteration caused by a mutated IDH enzyme was the broad elevation of amino acids. Specifically, amino acid profiling from our study revealed that glutamine and glutamate were abundant amino acids in chondrosarcomas and were elevated in mutant IDH chondrosarcomas, suggesting that there is increased dependence on glutaminolysis. This metabolic alteration has been identified in mutant IDH solid tumors [4, 37,38,39] and has led to two clinical trials targeting inhibition of glutaminolysis. Thus, our amino acid profile of mutant IDH chondrosarcomas confirms elevated levels of glutamine and glutamate and the notion that a greater dependence on glutaminolysis is required to support energy production in chondrosarcoma.

Similar to our findings in chondrosarcomas, mutant IDH gliomas also show a global elevation of free amino acids and lipid precursors [49]. While findings in gliomas show depletion of the late-stage TCA cycle intermediates, fumarate and malate [49], we did not observe this in chondrosarcoma. This finding could be a result of enhanced amino acid metabolism aiding in the replenishment of late-stage TCA cycle intermediates and maintenance of carbon cycling in mutant IDH chondrosarcomas. Fumarate is replenished by phenylalanine and tyrosine, both of which are amino acids elevated in IDH mutant chondrosarcomas, and malate is derived from pyruvate, an organic acid which also showed a trend for increase in mutant IDH chondrosarcomas. Moreover, opposing metabolic findings from Reitman et al. may be explained due to a different cell type being profiled and the in vitro conditions of their study [49].

We found distinct acylcarnitine derangements in mutant IDH versus non-mutant chondrosarcomas. Our analysis suggested that lipid and amino acid-derived acylcarnitine species were elevated in mutant IDH chondrosarcomas. This could suggest that in response to mutation of the IDH enzyme, chondrosarcomas resort to a greater dependence on fatty acid oxidation and amino acid metabolism to maintain tumor cell energetics. Studies in skeletal muscle reported that accumulation of mitochondrial acylcarnitine species can also be a signature of mitochondrial lipid overload or ineffective mitochondrial lipid catabolism [14]. Thus, it remains unclear if the abundant acylcarnitine levels in mutant IDH chondrosarcomas are a signature of enhanced influx of acylcarnitines in the mitochondria from increased mitochondrial fatty acid catabolism or from “incomplete” fatty acid oxidation. To investigate this phenomenon more comprehensively, a future point of interest would be to assess mutant IDH chondrosarcoma mitochondria β-oxidative capacity and acylcarnitine flux metabolism by carbon isotope labeling.

Future directions of study include addressing the elevation of specific amino acid species and their associated roles in neoplastic biochemical pathways. For instance, glycine was the most abundant amino acid in chondrosarcomas and was elevated in mutant IDH chondrosarcomas. Serine was also found in elevated levels in mutant IDH chondrosarcomas. Glycine and serine are biosynthetically linked and aid in the synthesis of proteins, nucleic acids, and lipids crucial to cancer cell growth [50, 51]. Investigation of the association of serine and glycine with tumorigenesis and malignancy [50, 51] is an attractive candidate for future studies in mutant IDH chondrosarcomas.

Our study also revealed elevated BCAAs (valine, leucine, and isoleucine) levels in mutant IDH chondrosarcomas. BCAAs were recently found to be a source of carbon for fatty acid biosynthesis in neoplastic proliferation, and suppression of BCAA metabolism led to a reduction in fatty acid levels [42, 52]. This interesting interplay between BCAA metabolism and fatty acid metabolism is another attractive candidate for further investigation in mutant IDH chondrosarcomas.

Conclusions

Our metabolomics profiling of 17 human chondrosarcomas reveals a number of distinct alterations in mutant IDH chondrosarcomas including differences in glycolytic intermediates, TCA cycle intermediates, amino acids, and acylcarnitines levels. This study revealed that mutant IDH chondrosarcomas are metabolically more active tumors compared with IDH non-mutant chondrosarcomas. While there are conflicting data on IDH mutational status and associated clinical outcome in chondrosarcomas [53, 54], our metabolomic profiling shows that mutant IDH chondrosarcomas are metabolically distinct and more active than non-mutant chondrosarcomas, giving rise to the potential that IDH mutational state alters cell behavior. The global elevation of amino acids, lactate accumulation, and elevation of acylcarnitines and eventual metabolic dependence of these metabolites for neoplastic energetics is a signature of IDH mutant chondrosarcomas. In support of our metabolomics findings, our analysis of previously published mRNA microarray data [24, 25] revealed increased gene expression levels of specific metabolism genes in mutant IDH chondrosarcomas, which was also found to correlate to poor patient survival.

Availability of data and materials

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

Abbreviations

IDH1:

Isocitrate dehydrogenase 1

IDH2:

Isocitrate dehydrogenase 2

UMAP:

Uniform Manifold Approximation and Projection

TCA:

Tricarboxylic acid

α-KG:

α-Ketoglutarate

D-2HG:

D-2-Hydroxyglutarate

HIF1α:

Hypoxia-inducible factor 1a

GC/MS:

Gas chromatography-mass spectrometry

MS/MS:

Mass spectrometry

IRB:

Institutional review board

BCAAs:

Branched-chain amino acids

LDHA:

Lactate dehydrogenase

References

  1. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74. https://doi.org/10.1016/j.cell.2011.02.013.

    Article  CAS  PubMed  Google Scholar 

  2. Hirata M, Sasaki M, Cairns RA, Inoue S, Puviindran V, Li WY, Snow BE, Jones LD, Wei Q, Sato S, Tang YJ, Nadesan P, Rockel J, Whetstone H, Poon R, Weng A, Gross S, Straley K, Gliser C, Xu Y, Wunder J, Mak TW, Alman BA. Mutant IDH is sufficient to initiate enchondromatosis in mice. Proc Natl Acad Sci. 2015;112(9):2829–34. https://doi.org/10.1073/pnas.1424400112.

    Article  CAS  PubMed  Google Scholar 

  3. Amary MF, Bacsi K, Maggiani F, Damato S, Halai D, Berisha F, Pollock R, O'Donnell P, Grigoriadis A, Diss T, Eskandarpour M, Presneau N, Hogendoorn PCW, Futreal A, Tirabosco R, Flanagan AM. IDH1 and IDH2 mutations are frequent events in central chondrosarcoma and central and periosteal chondromas but not in other mesenchymal tumours. J Pathol. 2011;224(3):334–43. https://doi.org/10.1002/path.2913.

    Article  CAS  PubMed  Google Scholar 

  4. Peterse EFP, Niessen B, Addie RD, de Jong Y, Cleven AHG, Kruisselbrink AB, van den Akker BEWM, Molenaar RJ, Cleton-Jansen AM, Bovée JVMG. Targeting glutaminolysis in chondrosarcoma in context of the IDH1/2 mutation. Br J Cancer. 2018;118(8):1074–83. https://doi.org/10.1038/s41416-018-0050-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Turkalp Z, Karamchandani J, Das S. IDH mutation in glioma: New insights and promises for the future. JAMA Neurol. 2014;71(10):1319–25. https://doi.org/10.1001/jamaneurol.2014.1205.

    Article  PubMed  Google Scholar 

  6. Borger DR, Goyal L, Yau T, et al. Circulating Oncometabolite 2-Hydroxyglutarate Is a Potential Surrogate Biomarker in Patients with Isocitrate Dehydrogenase-Mutant Intrahepatic Cholangiocarcinoma. Clin Cancer Res. 2014;20(7):1884–90. https://doi.org/10.1158/1078-0432.CCR-13-2649.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Parker SJ, Metallo CM. Metabolic consequences of oncogenic IDH mutations. Pharmacol Ther. 2015;152:54–62. https://doi.org/10.1016/j.pharmthera.2015.05.003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kickingereder P, Sahm F, Radbruch A, Wick W, Heiland S, Deimling A, Bendszus M, Wiestler B. IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma. Sci Rep. 2015;5(July):1–9. https://doi.org/10.1038/srep16238.

    Article  CAS  Google Scholar 

  9. Metallo CM, Gameiro PA, Bell EL, Mattaini KR, Yang J, Hiller K, Jewell CM, Johnson ZR, Irvine DJ, Guarente L, Kelleher JK, Vander Heiden MG, Iliopoulos O, Stephanopoulos G. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature. 2012;481(7381):380–4. https://doi.org/10.1038/nature10602.

    Article  CAS  Google Scholar 

  10. Newgard CB. Metabolomics and Metabolic Diseases: Where Do We Stand? Cell Metab. 2017;25(1):43–56. https://doi.org/10.1016/j.cmet.2016.09.018.

    Article  CAS  PubMed  Google Scholar 

  11. Dai C, Arceo J, Arnold J, Sreekumar A, Dovichi NJ, Li J, Littlepage LE. Metabolomics of oncogene-specific metabolic reprogramming during breast cancer. Cancer Metab. 2018;6(1):1–17. https://doi.org/10.1186/s40170-018-0175-6.

    Article  Google Scholar 

  12. Fujisawa K, Takami T, Okada S, Hara K, Matsumoto T, Yamamoto N, Yamasaki T, Sakaida I. Analysis of Metabolomic Changes in Mesenchymal Stem Cells on Treatment with Desferrioxamine as a Hypoxia Mimetic Compared with Hypoxic Conditions. Stem Cells. 2018;36(8):1226–36. https://doi.org/10.1002/stem.2826.

    Article  CAS  PubMed  Google Scholar 

  13. Moreno P, Jiménez-Jiménez C, Garrido-Rodríguez M, Calderón-Santiago M, Molina S, Lara-Chica M, Priego-Capote F, Salvatierra Á, Muñoz E, Calzado MA. Metabolomic profiling of human lung tumor tissues – nucleotide metabolism as a candidate for therapeutic interventions and biomarkers. Mol Oncol. 2018;12(10):1778–96. https://doi.org/10.1002/1878-0261.12369.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Koves TR, Ussher JR, Noland RC, Slentz D, Mosedale M, Ilkayeva O, Bain J, Stevens R, Dyck JRB, Newgard CB, Lopaschuk GD, Muoio DM. Mitochondrial Overload and Incomplete Fatty Acid Oxidation Contribute to Skeletal Muscle Insulin Resistance. Cell Metab. 2008;7(1):45–56. https://doi.org/10.1016/j.cmet.2007.10.013.

    Article  CAS  PubMed  Google Scholar 

  15. Bain JR, Stevens RD, Wenner BR, Ilkayeva O, Muoio DM, Newgard CB. Metabolomics applied to diabetes research: Moving from information to knowledge. Diabetes. 2009;58(11):2429–43. https://doi.org/10.2337/db09-0580.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. An J, Muoio DM, Shiota M, Fujimoto Y, Cline GW, Shulman GI, Koves TR, Stevens R, Millington D, Newgard CB. Hepatic expression of malonyl-CoA decarboxylase reverses muscle, liver and whole-animal insulin resistance. Nat Med. 2004;10(3):268–74. https://doi.org/10.1038/nm995.

    Article  CAS  PubMed  Google Scholar 

  17. Ferrara CT, Wang P, Neto EC, et al. Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling. PLoS Genet. 2008;4(3). https://doi.org/10.1371/journal.pgen.1000034.

  18. Jensen MV, Joseph JW, Ilkayeva O, Burgess S, Lu D, Ronnebaum SM, Odegaard M, Becker TC, Sherry AD, Newgard CB. Compensatory responses to pyruvate carboxylase suppression in islet β-cells: Preservation of glucose-stimulated insulin secretion. J Biol Chem. 2006;281(31):22342–51. https://doi.org/10.1074/jbc.M604350200.

    Article  CAS  PubMed  Google Scholar 

  19. McInnes L, Healy J, Melville J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. arXiv e-prints. 2018.

  20. Team R. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; 2020.

    Google Scholar 

  21. Wang Y, Christopher BA, Wilson KA, Muoio D, McGarrah RW, Brunengraber H, Zhang GF. Propionate-induced changes in cardiac metabolism, notably CoA trapping, are not altered by l-carnitine. Am J Physiol Endocrinol Metab. 2018;315(622-633):E622–33. https://doi.org/10.1152/ajpendo.00081.2018.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fernandez CA, Des Rosiers C, Previs SF, David F, Brunengraber H. Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J Mass Spectrom. 1996;31(3):255–62. https://doi.org/10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3.

    Article  CAS  PubMed  Google Scholar 

  23. Tomcik K, Ibarra RA, Sadhukhan S, Han Y, G.P. Tochtrop GFZ. Isotopomer enrichment assay for very short chain fatty acids and its metabolic applications. Anal Biochem. 2011;410(1):110–7. https://doi.org/10.1016/j.ab.2010.11.030.

    Article  CAS  PubMed  Google Scholar 

  24. Nicolle R, Ayadi M, Gomez-Brouchet A, Armenoult L, Banneau G, Elarouci N, Tallegas M, Decouvelaere AV, Aubert S, Rédini F, Marie B, Labit-Bouvier C, Reina N, Karanian M, le Nail LR, Anract P, Gouin F, Larousserie F, de Reyniès A, de Pinieux G. Integrated molecular characterization of chondrosarcoma reveals critical determinants of disease progression. Nat Commun. 2019;10(1):1–11. https://doi.org/10.1038/s41467-019-12525-7.

    Article  CAS  Google Scholar 

  25. Nabila E. E-MTAB-7265 - High-throughput sequencing of miRNA of cartilage tumors. 2018. https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-7265/.

    Google Scholar 

  26. European Bioinformatics Institute database (EMBL-EBI).

  27. Badur M, Muthusamy T, Parker S, et al. Oncogenic R132 IDH1 Mutations Limit NADPH for De Novo Lipogenesis through (D)2-Hydroxyglutarate Production in Fibrosarcoma Cells. Cell Rep. 2018;25(4).

  28. Zhang Y, Lv W, Li Q, et al. IDH2 compensates for IDH1 mutation to maintain cell survival under hypoxic conditions in IDH1-mutant tumor cells. Spandidos Publ. 2019;20(2).

  29. Jiang L, Shestov AA, Swain P, et al. Reductive carboxylation supports redox homeostasis during anchorage-independent growth. Nature. 2016;7598(532). https://doi.org/10.1530/ERC-14-0411.Persistent.

  30. Fendt SM, Bell EL, Keibler MA, Olenchock BA, Mayers JR, Wasylenko TM, Vokes NI, Guarente L, Heiden MGV, Stephanopoulos G. Reductive glutamine metabolism is a function of the α-ketoglutarate to citrate ratio in cells. Nat Commun. 2013;4(1):1–11. https://doi.org/10.1038/ncomms3236.

    Article  CAS  Google Scholar 

  31. Mullen AR, Wheaton WW, Jin ES, et al. Reductive carboxylation supports growth in tumor cells with defective mitochondria. Nature. 2012;481(7381):385–8. https://doi.org/10.1038/nature10642.Reductive.

    Article  CAS  Google Scholar 

  32. Raimundo N, Baysal BE, Shadel GS. Revisiting the TCA cycle: Signaling to tumor formation. Trends Mol Med. 2011;17(11):641–9. https://doi.org/10.1016/j.molmed.2011.06.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yang C, Ko B, Hensley CT, Jiang L, Wasti AT, Kim J, Sudderth J, Calvaruso MA, Lumata L, Mitsche M, Rutter J, Merritt ME, DeBerardinis RJ. Glutamine oxidation maintains the TCA cycle and cell survival during impaired mitochondrial pyruvate transport. Mol Cell. 2014;56(3):414–24. https://doi.org/10.1016/j.molcel.2014.09.025.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kimmelman AC, White E. Autophagy and Tumor Metabolism. Cell Metab. 2017;25(5):1037–43. https://doi.org/10.1016/j.cmet.2017.04.004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Mathew R, Karantza-Wadsworth V, White E. Role of autophagy in cancer. Nat Rev Cancer. 2007;7(December):961–7. https://doi.org/10.1038/nrc2254.Role.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Russell RC, Yuan HX, Guan KL. Autophagy regulation by nutrient signaling. Cell Res. 2014;24(1):42–57. https://doi.org/10.1038/cr.2013.166.

    Article  CAS  PubMed  Google Scholar 

  37. Bonfili L, Cecarini V, Cuccioloni M, et al. Essential amino acid mixtures drive cancer cells to apoptosis through proteosome inhibition and autophagy activation. 2017;38(1):42–9. https://doi.org/10.1111/ijlh.12426.

  38. Vettore L, Westbrook RL, Tennant DA. New aspects of amino acid metabolism in cancer. Br J Cancer. 2019;(June). https://doi.org/10.1038/s41416-019-0620-5.

  39. Hiraoka N, Toue S, Okamoto C, Kikuchi S, Ino Y, Yamazaki-Itoh R, Esaki M, Nara S, Kishi Y, Imaizumi A, Ono N, Shimada K. Tissue amino acid profiles are characteristic of tumor type, malignant phenotype, and tumor progression in pancreatic tumors. Sci Rep. 2019;9(1):1–14. https://doi.org/10.1038/s41598-019-46404-4.

    Article  CAS  Google Scholar 

  40. Sullivan LB, Luengo A, Danai LV, Bush LN, Diehl FF, Hosios AM, Lau AN, Elmiligy S, Malstrom S, Lewis CA, Vander Heiden MG. Aspartate is an endogenous metabolic limitation for tumour growth. Nat Cell Biol. 2018;20(7):782–8. https://doi.org/10.1038/s41556-018-0125-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sullivan LB, Gui DY, Hosios AM, Bush LN, Freinkman E, Vander Heiden MG. Supporting Aspartate Biosynthesis Is an Essential Function of Respiration in Proliferating Cells. Cell. 2015;162(3):552–63. https://doi.org/10.1016/j.cell.2015.07.017.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ananieva EA, Wilkinson AC. Branched-chain amino acid metabolism in cancer. Curr Opin Clin Nutr Metab Care. 2018;21(1):64–70. https://doi.org/10.1097/MCO.0000000000000430.

    Article  CAS  PubMed  Google Scholar 

  43. San-Millán I, Brooks GA. Reexamining cancer metabolism: Lactate production for carcinogenesis could be the purpose and explanation of the Warburg Effect. Carcinogenesis. 2017;38(2):119–33. https://doi.org/10.1093/carcin/bgw127.

    Article  CAS  PubMed  Google Scholar 

  44. de la Cruz-López KG, Castro-Muñoz LJ, Reyes-Hernández DO, García-Carrancá A, Manzo-Merino J. Lactate in the Regulation of Tumor Microenvironment and Therapeutic Approaches. Front Oncol. 2019;9(November). https://doi.org/10.3389/fonc.2019.01143.

  45. Kane DA. Lactate oxidation at the mitochondria: A lactate-malate-aspartate shuttle at work. Front Neurosci. 2014;8(OCT):1–6. https://doi.org/10.3389/fnins.2014.00366.

    Article  Google Scholar 

  46. Hua G, Liu Y, Li X, Xu P, Luo Y. Targeting glucose metabolism in chondrosarcoma cells enhances the sensitivity to doxorubicin through the inhibition of lactate dehydrogenase-A. Oncol Rep. 2014;31(6):2727–34. https://doi.org/10.3892/or.2014.3156.

    Article  CAS  PubMed  Google Scholar 

  47. Jiang B. Aerobic glycolysis and high level of lactate in cancer metabolism and microenvironment. Genes Dis. 2017;4(1):25–7. https://doi.org/10.1016/j.gendis.2017.02.003.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Chen C, Zhou H, Wei F, Jiang L, Liu X, Liu Z, Ma Q. Increased levels of hypoxia-inducible factor-1α are associated with Bcl-xL expression, tumor apoptosis, and clinical outcome in chondrosarcoma. J Orthop Res. 2011;29(1):143–51. https://doi.org/10.1002/jor.21193.

    Article  CAS  PubMed  Google Scholar 

  49. Reitman ZJ, Jin G, Karoly ED, Spasojevic I, Yang J, Kinzler KW. Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome; 2011. https://doi.org/10.1073/pnas.1019393108/-/DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1019393108.

    Book  Google Scholar 

  50. Amelio I, Cutruzzolá F, Antonov A, Agostini M, Melino G. Serine and glycine metabolism in cancer. Trends Biochem Sci. 2014;39(4):191–8. https://doi.org/10.1016/j.tibs.2014.02.004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Braun JE, Huntzinger E, Fauser M, et al. Metabolite Profiling Identifies a Key Role for Glycine in Rapid Cancer Cell Proliferation. Science. 2012;(May):1040–5.

  52. Lee JH, Cho Y r, Kim JH, et al. Branched-chain amino acids sustain pancreatic cancer growth by regulating lipid metabolism. Exp Mol Med. 2019;51(11). https://doi.org/10.1038/s12276-019-0350-z.

  53. Cleven AHG, Suijker J, Agrogiannis G, Briaire-de Bruijn IH, Frizzell N, Hoekstra AS, Wijers-Koster PM, Cleton-Jansen AM, Bovée JVMG. IDH1 or -2 mutations do not predict outcome and do not cause loss of 5-hydroxymethylcytosine or altered histone modifications in central chondrosarcomas. Clin Sarcoma Res. 2017;7(1):1–10. https://doi.org/10.1186/s13569-017-0074-6.

    Article  CAS  Google Scholar 

  54. Zhu GG, Nafa K, Agaram N, Zehir A, Benayed R, Sadowska J, Borsu L, Kelly C, Tap WD, Fabbri N, Athanasian E, Boland PJ, Healey JH, Berger MF, Ladanyi M, Hameed M. Genomic profiling identifies association of IDH1/IDH2 mutation with longer relapse-free and metastasis-free survival in high-grade chondrosarcoma. Clin Cancer Res. 2020;26(2):419–27. https://doi.org/10.1158/1078-0432.CCR-18-4212.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Qingxia Wei for the generation of xenografts from patient chondrosarcoma tissues. We also thank our funding sources: NIH R01 AR066765 and CIHR: MOP-37913 for funding this study.

Funding

NIH R01 AR066765, CIHR: MOP-37913

Author information

Authors and Affiliations

  1. Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, ON, Canada

    Sinthu Pathmanapan & Adrian Kwan Ho Loe

  2. Institute of Medical Science, University of Toronto, Toronto, ON, Canada

    Sinthu Pathmanapan

  3. Department of Pharmacology & Cancer Biology, Duke University, Durham, NC, USA

    Olga Ilkayeva & Christopher B. Newgard

  4. Sarah W. Stedman Nutrition and Metabolism Center and Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA

    Olga Ilkayeva, Guo-Fang Zhang & Christopher B. Newgard

  5. Department of Orthopaedic Surgery, Duke University, 311 Trent, Durham, NC, 27710, USA

    John T. Martin, Hongyuan Zhang & Benjamin A. Alman

  6. Lunenfeld-Tanenbaum Research Institute, and the University Musculoskeletal Oncology Unit, Mount Sinai Hospital, Toronto, ON, Canada

    Jay S. Wunder

Authors
  1. Sinthu Pathmanapan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olga Ilkayeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John T. Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adrian Kwan Ho Loe
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hongyuan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guo-Fang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Christopher B. Newgard
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jay S. Wunder
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Benjamin A. Alman
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SP, BAA, CBN, and JSW conceived the idea of the study and designed the study. SP, OI, AKHL, HHZ, GZ, and CBN acquired the data from the study. SP and CBN analyzed and interpreted data from the study. JTM analyzed a portion of the data from the study. SP, BAA, CBN, and JSW drafted and revised the work. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Benjamin A. Alman.

Ethics declarations

Ethics approval and consent to participate

The following study (01-0138-U) has received continued approval from the Mount Sinai Hospital Research Ethics Board for the usage of human samples for research. Human samples were handled and animal work complied with the IRB guidelines.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplemental Figure 1

. UMAP clustering analysis of metabolites from mutant IDH and non-mutant chondrosarcomas display strong spatial clustering in organic acid and amino acid groups but weak spatial clustering in acylcarnitine species. UMAP analysis was performed in each metabolite group A) 7 organic acids (5 TCA cycle and 2 glycolytic intermediates, B) 17 amino acids, C) 45 acylcarnitines, D) total 69 metabolites

Additional file 2: Supplemental Figure 2

. 13C α-KG labelling is reduced in mutant IDH1 and IDH2 chondrosarcoma cells based on measurements of citrate and pyruvate labelling. 13C isotope labelling of α-KG was achieved by 6 hours [13C6] labelling of glucose. Data normalized from citrate (M2) and pyruvate (M3) labelling display effects of mutated IDH1 and IDH2 enzymes A) reduction of α-KG carbon labelling from M2 citrate in mutant IDH chondrosarcoma cells B) reduction of α-KG carbon labelling from M3 pyruvate in mutant IDH chondrosarcoma cells

Additional file 3: Supplemental Figure 3

. Expression of genes regulating metabolism correlates with prognosis in chondrosarcomas. A number of metabolism genes were found to be A) elevated in mutant IDH1 and/or mutant IDH2 chondrosarcomas and B-H) were predicative of patient survival

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pathmanapan, S., Ilkayeva, O., Martin, J.T. et al. Mutant IDH and non-mutant chondrosarcomas display distinct cellular metabolomes. Cancer Metab 9, 13 (2021). https://doi.org/10.1186/s40170-021-00247-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40170-021-00247-8

Keywords

Cancer & Metabolism

ISSN: 2049-3002