Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes
© Fan et al; licensee BioMed Central Ltd. 2008
Received: 11 May 2008
Accepted: 21 October 2008
Published: 21 October 2008
The functional status of a cell is expressed in its metabolic activity. We have applied stable isotope tracing methods to determine the differences in metabolic pathways in proliferating Rhabdomysarcoma cells (Rh30) and human primary myocytes in culture. Uniformly 13C-labeled glucose was used as a source molecule to follow the incorporation of 13C into more than 40 marker metabolites using NMR and GC-MS. These include metabolites that report on the activity of glycolysis, Krebs' cycle, pentose phosphate pathway and pyrimidine biosynthesis.
The Rh30 cells proliferated faster than the myocytes. Major differences in flux through glycolysis were evident from incorporation of label into secreted lactate, which accounts for a substantial fraction of the glucose carbon utilized by the cells. Krebs' cycle activity as determined by 13C isotopomer distributions in glutamate, aspartate, malate and pyrimidine rings was considerably higher in the cancer cells than in the primary myocytes. Large differences were also evident in de novo biosynthesis of riboses in the free nucleotide pools, as well as entry of glucose carbon into the pyrimidine rings in the free nucleotide pool. Specific labeling patterns in these metabolites show the increased importance of anaplerotic reactions in the cancer cells to maintain the high demand for anabolic and energy metabolism compared with the slower growing primary myocytes. Serum-stimulated Rh30 cells showed higher degrees of labeling than serum starved cells, but they retained their characteristic anabolic metabolism profile. The myocytes showed evidence of de novo synthesis of glycogen, which was absent in the Rh30 cells.
The specific 13C isotopomer patterns showed that the major difference between the transformed and the primary cells is the shift from energy and maintenance metabolism in the myocytes toward increased energy and anabolic metabolism for proliferation in the Rh30 cells. The data further show that the mitochondria remain functional in Krebs' cycle activity and respiratory electron transfer that enables continued accelerated glycolysis. This may be a common adaptive strategy in cancer cells.
Rhabdomyosarcomas are a serious childhood cancer that arise from a primitive muscle cell, the "rhabdomyoblast", and fail to differentiate into striated muscle cells. These tumors account for about 5–8% of all childhood cancers, with a peak incidence in the 1–5 age group. Overall, 50% of the children diagnosed with rhabdomyosarcoma survive 5 years. There are two main forms of the sarcoma, alveolar and the less severe embryonic form. Although there is considerable information about the origin and progression of these tumors [1–5], much less is known about the biochemical phenotype of these sarcomas and how it differs from the primary myocytes of the nearby tissue. Such information would be of great value not only for understanding the basic biochemistry of these transformed cells, but also for developing new therapeutics. Here we report a study of the biochemical phenotype of rhabdomyosarcoma cells of the embryonic variety, Rh30, in comparison with primary myocytes, using a 13C-isotopomer-based metabolomic approach.
Rapidly dividing cancer cells in culture show numerous differences from the differentiated primary cells of a comparable type [6–8]. In order to divide, the cell must traverse the cell cycle repeatedly, with a concomitant doubling of macromolecular content during the S and G2 phases. This requires considerable biosynthetic resources and an energy demand far in excess of the basal rate. Biosynthesis of proteins, nucleic acids, lipids and complex carbohydrates involves coupling to the hydrolysis of nucleoside triphosphates (e.g. ATP and GTP in protein biosynthesis, CTP and UTP in lipid and carbohydrate biosynthesis), as well as the incorporation of carbon and nitrogen from metabolic precursors. For cells in culture, many of these precursors are readily available in the medium, including essential amino acids, fatty acids and glucose. In contrast, the precursors of nucleotides, complex carbohydrates and phospholipids are absent from the medium, and so must be synthesized de novo.
There is a hierarchy of ATP-consuming reactions in cellular function . As might be expected, maintenance of ion gradients across membranes for transport and various macromolecular repair processes involved in cell survival are the highest priority reactions and account for a large fraction of the ATP consumed in quiescent (G0/G1) cells [9–11]. Upregulating macromolecule biosynthesis in preparation for cell division requires additional ATP equivalents to be made. Many cancer cells have a tendency to increase glucose uptake  and glycolytic flux even under aerobic conditions, while secreting a large fraction of the glucose carbon as lactate [13, 14]. This implies a bypass to oxidative phosphorylation, such that glycolysis alone may account for a substantial fraction of the ATP production. This enhanced aerobic glycolysis is known as the Warburg effect [15–17]. A more efficient means for energy production under aerobic conditions is to increase the flux of acetylCoA derived from the oxidation of glucose, amino acids and fatty acids into the Krebs' cycle. Moreover, to sustain the Krebs cycle activity, it is necessary to upregulate anaplerotic reactions that replenish carbon diverted for biosynthesis.
Skeletal muscle uses both glycolysis and oxidative phosphorylation for providing energy for contraction. Under conditions of hard exercise, glycogen stores are rapidly depleted, and oxidative phosphorylation of fuels such as fatty acids cannot keep up with demand. The muscle resorts to a greatly increased rate of glycolysis (> 100 fold ) and the production of lactate. Lactate, and to some extent Ala, is exported from the myocytes into the blood, when they are transported the liver for resynthesis into glucose via gluconeogenesis (cf. Figure 1). These comprise the Cori and alanine cycles [19, 20]. Thus, myocytes have the capacity to make and secrete large amounts of lactate. The secretion of lactate via the monocarboxylate transporter is often accompanied by a proton symport [21, 22]. Moreover, most cells can actively export protons via various exchangers, such as the H+/Na+ antiporter , Many cancer cells pump prodigious quantities of H+ into the extracellular environment, which may offer survival advantages, particularly in the light of their accelerated glycolysis [24, 25].
Thus questions arise as to the metabolic differences between a transformed cell and a primary (untransformed) cell. Here we have used 13C quantitative isotopomer analysis to follow the fate of individual carbon atoms derived from glucose, as outlined in Figure 1, in both rhabdomyosarcoma cells (Rh30) and primary myocytes, grown under the same conditions to probe their biochemical phenotypes. This approach enabled changes in turnover through individual pathways to be followed, which is not generally possible by concentration-based metabolite profiling alone. Furthermore, the use of 13C-edited 1H NMR techniques allowed identification of major phosphorylated sugars that are otherwise difficult to detect in crowded 1H NMR spectra. Clear differences between the myocytes and the Rh30 cells were evident, consistent with heightened energy and anabolic metabolism in Rh30 cells.
Results and discussion
Under the growth conditions of these experiments, the Rh30 cells double in about 24 h in the presence of serum. The growth rate in the absence of serum (0.5% BSA) was about 30% slower, indicating only a weak dependence on growth factors. In contrast, the primary myocytes grew much more slowly, with a doubling time of approximately 50 h in the presence of serum growth factors. This suggests that the cancer cells have an overall net higher demand for metabolic energy to drive macromolecular biosynthesis as the cells proliferate. This is in addition to the normal basal cell metabolic requirements.
Glucose uptake and lactate secretion
Quantification of labeled metabolites in the media by 1H NMR analysis.
[13C Lac] mM
[13C Ala] mM
Rh30 (24 h)
4.8 ± 0.6
83 ± 1
0.35 ± .03
67 ± 4
6.1 ± 0.6
4.6 ± .6
52 ± 7.5
1.2 ± 0.2
64 ± 2
4.8 ± .5
5.9 ± .5
10 ± 1.4
The consumption of [U-13C]-glucose by the Rh30 cells at 24 h was comparable to the consumption by the primary myocytes in 48 h, reflecting the slower growth rate of the latter. The amount and degree of 13C enrichment in lactate secreted was very much higher for the Rh30 cells than the primary myocytes (Table 1 and Figure 4). Since the dry weight of the myocytes at 48 h was comparable to that of the Rh30 cells at 24 h, this implies an 8-fold higher lactate production rate in the Rh30 cells than the myocytes. The amount and degree of 13C enrichment of Ala in the Rh30 medium was also much higher than measured in the myocyte medium, although Ala secretion constituted a smaller fraction of the labeled glucose consumption (Table 1 and Figure 4). Thus, the Rh30 cells converted a much higher fraction, F (cf. Eq. 2 and Table 1) of the 13C glucose consumed into lactate (50%) than the myocytes (10%). We have observed that typically 30–50% of the glucose consumed was converted to lactate by various epithelial derived cancer cell lines, (A.N. Lane, T. WM Fan, unpublished data). This is in contrast to a recent report on glioblastoma cells, in which more than 95% of the glucose consumed was converted to lactate and Ala . The high rate of production of labeled lactate in Rh30 and other cancer cells indicates that the pyruvate kinase (PK) step in glycolysis (Fig. 1) must be active, in contrast with the reports of defective PK in some tumor cells .
The high degree of lactate labeling in Rh30 cells indicates that the major source of carbon in lactate and Ala was indeed glucose. However, the fraction of 13C Ala labeling in the myocyte was essentially at natural abundance, reflecting its primary origin from the 10% FCS present in the medium. Thus, not only did the Ala labeling pattern in myocytes differ from that in Rh30 cells but also it was distinct from the lactate labeling pattern in both cell lines. As the immediate precursor to Ala and lactate is pyruvate, these differences in labeling patterns could indicate the presence of distinct intracellular pools of pyruvate as observed in other cells [39, 40] and see below. Moreover, a significant fraction of glucose taken up by Rh30 (48%) and myocytes (90%) was converted to metabolites other than lactate (cf. Table 1). The fate of some of the remaining glucose carbon was traced in the cellular components is described below
Glucose-dependent cell metabolism
Quantification of 13C enrichment in cellular metabolites by 1H NMR analysis: Glycolysis.
74 ± 2
86 ± 2
2.9 ± 0.3
6.7 ± 0.3
73 ± 2
3.2 ± 0.3
44 ± 2
82 ± 2
0.7 ± 0.1
6.8 ± 0.3
Krebs' cycle activity
It is clear from Figure 7 that the Rh30 cells had a much higher buildup of the different 13C isotopomers of Glu (than the myocytes. This implicates a higher turnover of the Krebs cycle and specifically a higher capacity for anaplerotic pyruvate carboxylation, as evident by the enhanced buildup of 13C-4,5-Glu and 13C-2,3-Glu, respectively.
Malate and aspartate also showed substantial 13C enrichment (Figure 3B) in both doubly and triply labeled mass isotopomers based on the GC-MS analysis. The positional isotopomer of the triply labeled malate was deduced from the 2-D HSQC analysis, as shown in Figure 7. The doublet of C3 or β-malate and the triplet of C2 or α-malate indicate the prevalence of [13C-1,2,3]-malate. The doubly labeled malate isotopomers can be [13C-2,3]-malate, [13C-1,2]-malate, and/or [13C-3,4]-malate, the abundance of which could not be ascertained with the present data. By comparing Rh30 cells with myocytes in terms of the 13C-malate isotopomer patterns in Fig. 3B and 7, it is clear that Rh30 cells synthesized a much higher amount of doubly and triply labeled malate, the latter of which was identified as [13C-1,2,3]-malate. Similar considerations apply to Asp i.e. the doubly and triply labeled ([13C-1,2,3]-Asp) isotopomers were more abundant in Rh30 cells than in myocytes (Figure 3B).
According to the schemes in Figs 1 and 10B, [13C-1,2,3]-malate and [13C-1,2,3]-Asp can only be synthesized from [U-13C]-pyruvate via anaplerotic pyruvate carboxylation (PC). PC can also lead to the synthesis of the doubly labeled [13C-2,3]-malate or Asp after one turn of the Krebs cycle, as outlined in Fig. 10B. In contrast, the doubly labeled malate species (as [13C-1,2]- and [13C-3,4]-malate) or Asp should derive from the normal Krebs' cycle sequence with input of [U-13C]-pyruvate, as illustrated in Fig. 10A, or the doubly labeled [13C-2,3]-malate from pyruvate carboxylation, as outlined in Fig. 10B. Thus, the combined GC-MS and NMR determination of malate and Asp isotopomers not only revealed an enhanced activity of the Krebs' cycle but also activation of pyruvate carboxylation in the Rh30 cells over the primary myocytes. Such anaplerotic reactions are essential for actively dividing cells, as the production of important metabolites such as pyrimidine nucleobases and reduced glutathione deplete Krebs' cycle intermediates (Fig. 1 and see below), which must be replenished.
Krebs cycle intermediates may also be replenished via glutaminolysis [30, 38, 48], which has been shown to be activated in glioblastoma cells, based on the production of labeled lactate derived from labeled Gln . The role of glutaminolysis in anaplerosis in Rh30 cells could not be ascertained here for lack of carbon tracing from labeled Gln. However, the comparable production of unlabeled lactate by Rh30 cells and myocytes (Figures 1, 4 and see above) suggests a minor role for glutaminolysis in activating anaplerosis in Rh30 cells.
The sustained activity of the Krebs' cycle in the Rh30 cells requires a functional respiratory chain to regenerate NAD+ and FAD in the mitochondria. The same chain also reoxidizes cytosolic NADH produced by glycolysis, and transported into the mitochondria via the malate-aspartate shuttle (cf. Fig. 1), that is not involved in reducing pyruvate to lactate (and see above).
Furthermore, transformed Rh30 cells were much more active in de novo GSH synthesis than the primary myocytes. GSH was labeled in the Glu residue in Rh30 cells and the extent of this labeling was much stronger in Rh30 cells than in the myocytes (cf. Figs. 7 and 8), just as the case for its precursor Glu (Table 4). Although the cysteine supply can be rate limiting in GSH synthesis, in this case the medium contained an adequate supply of cystine (0.2 mM). The incorporation of labeled glutamate indicates a substantial rate of de novo GSH synthesis in the Rh30 cells.
Quantification of 13C enrichment in cellular metabolites by 1H NMR analysis: Pentose phosphate and pyrimidine biosynthesis
95 ± 2
80 ± 2
50 ± 3(26 ± 2)a
82 ± 2
88 ± 2
45 ± 2(21 ± 2)a
Quantification of 13C enrichment in cellular glutamate by 1H NMR analysis.
% 12C or
46 ± 3
11 ± 2
14 ± 2
29 ± 3
63 ± 3
2.5 ± .5
6.7 ± 1
28 ± 2
54 ± 3
16 ± 2
30 ± 3
78 ± 4
9 ± 1
13 ± 1
71 ± 3
9 ± 1
12 ± 2
7 ± 1
As Asp is derived from the transamination of the Krebs' cycle intermediate, OAA, increased diversion of Asp to pyrimidine ring biosynthesis would ultimately deplete OAA, which must be replenished to sustain the Krebs' cycle activity. As described above, this can occur by enhanced anaplerosis via pyruvate carboxylation in Rh30 cells. Furthermore, labeled Asp synthesized in the mitochondria is presumably transported to the cytoplasm for pyrimidine biosynthesis via the Asp/malate shuttle (Fig. 1). The enhanced rate of pyrimidine synthesis in Rh30 cells may well reflect an increased Asp/malate shuttle activity. This shuttle also facilitates the transfer of NADH produced in the cytoplasm to the mitochondrion for ATP production via oxidative phosphorylation. Although pyrimidine biosynthesis is mainly cytoplasmic, one step occurs within the mitochondrion and involves coupling to the electron transfer chain. Collectively these all point to metabolically functional mitochondria in the cancer cells.
The higher capacity for pyrimidine synthesis in Rh30 cells is corroborated by the13C labeling data in the ribose moiety of 5'-UXP, where all five carbons of the ribose residue were uniformly labeled in 13C. This was evident from the TOCSY 13C satellite patterns of the 5'-UXP cross-peaks (e.g. Fig. 9B for H1' → H2' of 5'-UXP) and 13C spin coupling patterns of C1' to C4' of ribose in 5'-UXP (Fig. 8). The abundance of [U-13C-ribose]-UXP (Fig. 9B) and % 13C enrichment (Table 3) were much higher in Rh30 cells than in myocytes, consistent with an enhanced rate of 5'-UXP synthesis. Also evident in Fig. 8 is the higher rate of synthesis for purine nucleotides (i.e. 5'-AXP and 5'-GXP), as shown by the higher abundance of [U-13C-ribose]-5'-AXP and 5'-GXP. This difference in 13C labeling of nucleotides is consistent with a higher metabolic demands for macromolecular (e.g. RNA) biosynthesis for the transformed cells compared with slowly dividing primary cells (also see below).
It should also be noted that the 1H NMR resonances of 5'-AXP and 5'-UXP in Fig. 8 were in fact mixtures of 3 resonances, which correspond to the tri, di and mono phosphates species, with intensities in the order 5'-ATP > 5'-ADP > 5'-AMP and similarly for 5'-UTP, 5'-UDP and 5'-UMP (data not shown).
Intracellular glucose-6-phosphate and glycogen synthesis
Free glucose is not expected to be present in cells where the activity of hexokinase exceeds that of glucose transport . The 1D proton spectra (Fig. 5A) show that the concentrations of glucose and G6P were negligible in the Rh30 cells which indicates that the steps downstream of G6P in glycolysis are not flux limiting. The low concentration of free glucose is a feature of cancer cells which together with the low level of G6P reflects the high glycolytic flux, making glucose transport rate limiting , despite derepression of GLUT4 expression by mutated p53. In contrast, the concentration of G6P in the myocytes was significant (Fig 7A), which suggests that for these cells, the uptake of glucose or hexokinase was not limiting glycolysis in these cells. Rather, a step downstream of G6P, such as PFK1, limits flux leading to an accumulation of G6P. This is consistent with typical estimates of intracellular G6P in skeletal muscle (ca. 200–400 μM). The much higher demand from glycolysis and the PPP (see above) in Rh30 cells, compared with the myocytes, may well be limiting glycogen synthesis, which competes for the same glucose precursor. This may underlie the lack of newly synthesized glycogen in Rh30 cells versus its significant presence in the myocytes (cf. Fig. 11).
Finally, the extent of 13C labeling in lactate, Ala, and pyrimidine nucleotides was higher in Rh30 cells grown in fetal calf serum (FCS) than cells grown in BSA (Table 3). The low enrichment of the intracellular Ala may be related to differences in pyruvate production from sources other than glucose between the FCS-stimulated and unstimulated Rh30 (BSA) cells (see above). For Glu, the two growth conditions gave a comparable extent of 13C labeling, which was significantly higher than that for the myocytes. Thus, even without the influence of the growth factor in FCS, Rh30 cells grown in BSA still exhibited a greater turnover of [U-13C]-glucose through glycolysis, Krebs' cycle, and pyrimidine nucleotide biosynthesis than the primary myocytes.
Using [U-13C]-glucose as tracer and isotopomer-based metabolomic analysis, we have demonstrated major distinctions in central energy and anabolic metabolism between the primary myocyte and transformed Rh30 cell lines. A major advantage of this approach is the ability to follow the fate of individual atoms simultaneously into many metabolites, and thereby to characterize the interrelationships among multiple biochemical pathways. Our data show that relative to the myocytes, glycolysis, Krebs' cycle, pentose phosphate pathway, and nucleotide biosynthesis (cf. Fig. 1) were coordinately enhanced in Rh30 cells, presumably to meet the demand of accelerated growth. The coordination between energy production (including the Warburg effect [15, 17, 52]) and generation of biosynthetic precursors in Rh30 cells may well be mediated via an activation of anaplerotic carboxylation and the malate/Asp shuttle which facilitates the transfer of NADH hydride from the cytoplasm to the mitochondrion for oxidative phosphorylation [7, 48], thereby sustaining accelerated glycolysis. The role of glutaminolysis as another anaplerotic input to the Krebs cycle is unclear but is likely to be less significant in accounting for the distinction between Rh30 cells and myocytes.
It is therefore evident that mitochondria of transformed Rh30 cells are active, both in citric acid cycling and respiratory electron transport. Since these processes are essential to cell proliferation, it is reasonable to postulate that they may be fundamental in the transformation of primary to malignant cells.
The human RMS cell line Rh30 (established at St. Jude Hospital), and human primary myocytes were cultured in pyruvate and glucose-free RPMI 1640 (Invitrogen, 11879-020), supplemented with 100 IU/ml penicillin, 10 μg/ml streptomycin, and 50 μg/ml neomycin (Life Technologies, Inc., Grand Island, NY) in the presence of 10% heat-inactivated FCS (Life Technologies) and 0.2% glucose. The medium thus contained 0.17 mM 12C alanine and 0.5 mM unlabeled lactate and 0.56 mM unlabeled glucose from the FCS. The cells were cultured in a humidified atmosphere at 5% CO2, 37°C at an initial cell density of 2.5 × 104 cells/flask (Corning) and the media were changed every 48 h. Prior to 13C labeling the cells were grown in 0.5% bovine serum albumin (BSA), without FCS to partially synchronize the culture. Control experiments were also run under otherwise identical conditions in which 0.5% BSA was used in place of FCS during the labeling phase. The dry weight of cells was measured for normalizing metabolite concentrations.
[U-13C]-glucose (99% 13C) was purchased from Cambridge Isotope Laboratories, MA and used without further purification. A stock solution (20%) was prepared in phosphate buffered saline and sterile filtered through a 0.2 μm filter. The appropriate quantity of the stock solution was added to glucose-free RPMI medium to a final concentration of 10.7 mM (excluding the 0.54 mM unlabeled glucose from the FCS).
Initial experiments were carried out with unlabeled glucose, followed by full metabolite profile experiments using [U-13C]-glucose. In one experiment, both the Rh30 and myocytes were cultured for 24 h in labeled glucose. In a second experiment to account for the differences in cell doubling rates, the Rh30 cells were cultured for 24 h, and the myocytes for 48 h in the labeled glucose. In this work, 13C atoms in various metabolites deriving exclusively from [U-13C]-glucose were monitored by NMR or mass spectrometry, which represented de novo metabolic transformations originating from glucose. Growth rates and viability were measured by direct cell counting on a hemocytometer using 0.4% Trypan Blue.
n is the number of moles of the compound in parentheses.
The factor of 2 accounted for the fact that one molecule of glucose gives rise to two molecules of lactate or Ala.
1-F then represents the glucose carbon that enters other metabolites and macromolecules in the cell mass or otherwise not accounted for. The fractions were not been corrected for the small (5%) contribution from unlabeled glucose present in the medium.
NMR spectra were recorded at either 14.1 T or 18.8 T on Varian Inova NMR spectrometers at 20°C using a 90° excitation pulse. One-dimensional NMR spectra were recorded with an acquisition time of 2 sec and a relaxation delay of 3 sec. Under these conditions, the protons were essentially full relaxed, as determined by independent measurements of the spin-lattice relaxation time, T1. For identifying metabolites in the extracts and determining the positional enrichment with 13C we used a suite of 2D experiments including TOCSY (or DQ COSY), HSQC, HCCH-TOCSY and HSQC-TOCSY as previously described [35–37, 53]. The latter two experiments make use of the isotope editing function. HCCH-TOCSY specifically selects for those molecules in which at least two adjacent carbon atoms are 13C whereas HSQC or HSQC-TOCSY detects protons directly attached to 13C. The TOCSY experiments were recorded with a spectral width of 6000 Hz in F2, 0.341 s acquisition time in t2 and 0.05 s in t1, 1.9 s interpulse delay, 50 ms mixing time, and an 8 kHz B1 field strength. The HSQC-TOCSY experiments were recorded with an acquisition time of 0.12 s in t2 and 12 ms in t1 using a 50 ms proton spin lock at a strength of 8 kHz. For the HCCH-TOCSY experiments, the acquisition times were 0.12 s in t2, 0.05 s in t1 using an 8 kHz 13C spin lock field centered in the aliphatic region of the spectrum for a duration of 12 ms.
Metabolites were assigned based on their 1H chemical shift, TOCSY connectivity patterns and correlation with 13C, using our in-house database as described previously [36, 54]. All metabolites except choline, sugars and the nucleotides were quantified from GC-MS data  whereas choline was quantified from the peak at 3.22 ppm in the 1-D NMR spectra, as described previously .
NMR analysis of 13C enrichment
Where M(true) is the corrected area, M(obs) is the observed area, and t is the recycle time. As the relaxation during the spin lock has the opposite effect on peak intensities, this correction was small . Effective T1 values were determined on standards recorded under the same solvent conditions.
Following NMR analysis, an aliquot (50–100 μl) of the NMR sample was re-equilibrated with H2O and lyophilized to remove any deuteration, then silylated with 25–50 μl 1:1 (v/v) acetonitrile:MTBSTFA (N-methyl-N-[tert-butyldimethylsilyl]trifluoroacetamide, (Regis Chemical, Morton Grove, IL) by 3 h of sonication followed by standing overnight [57, 58]. The solution was directly analyzed on a PolarisQ GC-ion trap MSn (ThermoFinnigan, Austin, TX) using a 0.5 μl injection volume. The column was 0.15 mm i.d. × 50 m fused silica open-tubular, coated with 0.2 μm BPX-5 (5% phenyl-methylsiloxane). The following conditions were employed for GC-MS. Injector at 280°C, column at 60°C for 2 min, followed by a 20°C/min ramp to 150°C, then 6°C/min to 300°C, splitless vent held for 1.5 min, He carrier gas velocity 30 cm/s at 60°C, transfer line = 280°C, electron energy = 70 eV, source heated to 190°C, automatic gain control target value = 50, maximum inject time = 25 ms, He damping gas = 0.3 ml/min, full scan acquisition from 140 to 650 m/z at a rate of five spectra/s which were averaged into one, and mass calibration preformed byperfluorotributylamine.
Metabolites were identified and quantified automatically using Xcalibur software (ThermoFinnigan), based on their GC retention times and mass fragmentation patterns matched against an in-house database and external standards. Identities were also verified by manual inspection. GC-MS quantification of total abundance of metabolites was accomplished by comparing the m/z 147 ion response for each metabolite in the samples with that for the corresponding standard of known concentration. The m/z 147 ion was chosen for quantification of labeled amino acids because this ion fragment did not contain 13C as it originated entirely from the silyl moiety. Conversely, for 13C isotopomers, the pseudo-molecular ion clusters of authentic standards were used to obtain the empirical ion ratios as the basis of the calculation for label abundance, as described in detail previously .
This work was supported by the Brown Foundation, Kentucky Challenge for Excellence (to ANL), NIH Grant RR018733 from the National Center for Research Resources, National Cancer Institute Grants 1 R01CA101199-01 and 1R01CA118434-01A2 to TWMF, NIH R01 CA106281-01 to MZR, NSF EPSCoR grant EPS-0132295 for the 18.8 T NMR spectrometer, and EPSCoR grant EPS-0447479 to TWMF for the development of isotopomer-based metabolomic analysis.
- Jankowski K, Kucia M, Wysoczynski M, Reca R, Zhao D, Trzyna E, Trent J, Peiper S, Zembala M, Ratajczak J: Both hepatocyte growth factor (HGF) and stromal-derived factor-1 regulate the metastatic behavior of human rhabdomyosarcoma cells, but only HGF enhances their resistance to radiochemotherapy. Cancer Research. 2003, 63: 7926-7935.PubMedGoogle Scholar
- Libura J, Drukala J, Majka M, Tomescu O, Navenot JM, Kucia M, Marquez L, Peiper SC, Barr FG, Janowska-Wieczorek A, Ratajczak MZ: CXCR4-SDF-1 signaling is active in rhabdomyosarcoma cells and regulates locomotion, chemotaxis, and adhesion. Blood. 2002, 100: 2597-2606.View ArticlePubMedGoogle Scholar
- Wysoczynski M, Miekus K, Jankowski K, Wanzeck J, Bertolone S, Janowska-Wieczorek A, Ratajczak J, Ratajczak MZ: Leukemia inhibitory factor: A newly identified metastatic factor in rhabdomyosarcomas. Cancer Research. 2007, 67: 2131-2140.View ArticlePubMedGoogle Scholar
- Scotlandi K, Picci P: Targeting insulin-like growth factor 1 receptor in sarcomas. Current Opinion in Oncology. 2008, 20: 419-427.View ArticlePubMedGoogle Scholar
- Baer C, Nees M, Breit S, Selle B, Kulozik AE, Schaefer KL, Braun Y, Wai D, Poremba C: Profiling and functional annotation of MRNA gene expression in pediatric rhabdomyosarcoma and Ewing's sarcoma. Int J Cancer. 2004, 110 (5): 687-694.View ArticlePubMedGoogle Scholar
- Rarnanathan A, Wang C, Schreiber SL: Perturbational profiling of a cell-line model of tumorigenesis by using metabolic measurements. Proceedings of the National Academy of Sciences of the United States of America. 2005, 102: 5992-5997.View ArticleGoogle Scholar
- Telang S, Lane AN, Nelson KK, Arumugam S, Chesney JA: The oncoprotein H-RasV12 increases mitochondrial metabolism. Mol Cancer. 2007, 6: 77-PubMed CentralView ArticlePubMedGoogle Scholar
- Telang S, Yalcin A, Clem AL, Bucala R, Lane AN, Eaton JW, Chesney J: Ras transformation requires metabolic control by 6-phosphofructo-2-kinase. Oncogene. 2006, 25: 7225-7234.View ArticlePubMedGoogle Scholar
- Buttgereit F, Brand MD: A Hierarchy of ATP-Consuming Processes in Mammalian-Cells. Biochem J. 1995, 312: 163-167.PubMed CentralView ArticlePubMedGoogle Scholar
- Schmid D, Burmester GR, Tripmacher R, Kuhnke A, Buttgereit F: Bioenergetics of human peripheral blood mononuclear cell metabolism in quiescent, activated, and glucocorticoid-treated states. Bioscience Reports. 2000, 20: 289-302.View ArticlePubMedGoogle Scholar
- Buttgereit F, Burmester GR, Brand MD: Therapeutically targeting lymphocyte energy metabolism by high-dose glucocorticoids. Biochemical Pharmacology. 2000, 59: 597-603.View ArticlePubMedGoogle Scholar
- Schwartzenberg-Bar-Yoseph F, Armoni M, Karnieli E: The tumor suppressor p53 down-regulates glucose transporters GLUT1 and GLUT4 gene expression. Cancer Research. 2004, 64: 2627-2633.View ArticlePubMedGoogle Scholar
- Wehrle JP, Ng CE, McGovern KA, Aiken NR, Shungu DC, Chance EM, Glickson JD: Metabolism of alternative substrates and the bioenergetic status of EMT6 tumor cell spheroids. NMR in Biomedicine. 2000, 13: 349-360.View ArticlePubMedGoogle Scholar
- Lanks KW, Li PW: End Products of Glucose and Glutamine Metabolism by Cultured Cell Lines. Journal of Cellular Physiology. 1988, 135: 151-155.View ArticlePubMedGoogle Scholar
- Garber K: Energy boost: The Warburg effect returns in a new theory of cancer. Journal of the National Cancer Institute. 2004, 96: 1805-1806.View ArticlePubMedGoogle Scholar
- Werle M, Jahn L, Kreuzer J, Hofele J, Elsasser A, Ackermann C, Katus HA, Vogt AM: Metabolic control analysis of the Warburg-effect in proliferating vascular smooth muscle cells. Journal of Biomedical Science. 2005, 12: 827-834.View ArticlePubMedGoogle Scholar
- Warburg O: On the origin of cancer cells. Science. 1956, 123: 309-314.View ArticlePubMedGoogle Scholar
- Fell D: Understanding the Control of Metabolism. 1997, London: Portland Press.Google Scholar
- Ganong WF: Excitable Tissue: Muscle. Review of Medical Physiology. 2003, New York: McGraw-Hill.Google Scholar
- Perriello G, Jorde R, Nurjhan N, Stumvoll M, Dailey G, Jenssen T, Bier DM, Gerich JE: Estimation of Glucose-Alanine-Lactate-Glutamine Cycles in Postabsorptive Humans – Role of Skeletal-Muscle. Am J Physiol. 1995, 269 (3 Pt 1): E443-E450.PubMedGoogle Scholar
- Enerson BE, Drewes LR: Molecular features, regulation, and function of monocarboxylate transporters: Implications for drug delivery. Journal of Pharmaceutical Sciences. 2003, 92: 1531-1544.View ArticlePubMedGoogle Scholar
- Halestrap AP, Price NT: The proton-linked monocarboxylate transporter (MCT) family: structure, function and regulation. Biochemical Journal. 1999, 343: 281-299.PubMed CentralView ArticlePubMedGoogle Scholar
- Moolenaar WH: Regulation of Cytoplasmic Ph by Na+/H+ Exchange. Trends in Biochemical Sciences. 1986, 11: 141-143.View ArticleGoogle Scholar
- Gatenby RA, Gillies RJ: Why do cancers have high aerobic glycolysis?. Nature Reviews Cancer. 2004, 4: 891-899.View ArticlePubMedGoogle Scholar
- Gillies RJ, Gatenby RA: Adaptive landscapes and emergent phenotypes: why do cancers have high glycolysis?. Journal of Bioenergetics and Biomembranes. 2007, 39: 251-257.View ArticlePubMedGoogle Scholar
- Christofk HR, Heiden Vander MG, Harris MH, Ramanathan A, Gerszten RE, Wei R, Fleming MD, Schreiber SL, Cantley LC: The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature. 2008, 452: 230-U274.View ArticlePubMedGoogle Scholar
- Mazurek S, Boschek CB, Hugo F, Eigenbrodt E: Pyruvate kinase type M2 and its role in tumor growth and spreading. Seminars in Cancer Biology. 2005, 15: 300-308.View ArticlePubMedGoogle Scholar
- Mazurek S, Grimm H, Boschek CB, Vaupel P, Eigenbrodt E: Pyruvate kinase type M2: A crossroad in the tumor metabolome. British Journal of Nutrition. 2002, 87: S23-S29.View ArticlePubMedGoogle Scholar
- Mazurek S, Grimm H, Oehmke M, Weisse G, Teigelkamp S, Eigenbrodt E: Tumor M2-PK and glutaminolytic enzymes in the metabolic shift of tumor cells. Anticancer Research. 2000, 20: 5151-5154.PubMedGoogle Scholar
- Mazurek S, Eigenbrodt E: The tumor metabolome. Anticancer Research. 2003, 23: 1149-1154.PubMedGoogle Scholar
- Moreno-Sanchez R, Rodriguez-Enriquez S, Marin-Hernandez A, Saavedra E: Energy metabolism in tumor cells. Febs Journal. 2007, 274: 1393-1418.View ArticlePubMedGoogle Scholar
- Elbers JRJ, Vanunnik JAM, Rijksen G, Vanoirschot BA, Roholl PJM, Oosting J, Staal GEJ: Pyruvate-Kinase Activity and Isozyme Composition in Normal Fibrous Tissue and Fibroblastic Proliferations. Cancer. 1991, 67: 2552-2559.View ArticlePubMedGoogle Scholar
- Lane AN, Fan TW-M, Higashi RM: Stable isotope assisted metabolomics in cancer research. IUBMB Life. 2008, 60: 124-129.View ArticlePubMedGoogle Scholar
- Lane AN, Fan TW, Higashi RM: Isotopomer-based metabolomic analysis by NMR and mass spectrometry. Methods Cell Biol. Edited by: John J, Correia HWD. 2008, 84: 541-588. San Diego: Academic Press.Google Scholar
- Lane AN, Fan TW: Quantification and identification of isotopomer distributions of metabolites in crude cell extracts using 1H TOCSY. Metabolomics. 2007, 3: 79-86.View ArticleGoogle Scholar
- Fan TW, Lane AN: Structure-based profiling of Metabolites and Isotopomers by NMR. Progress in NMR Spectroscopy. 2008, 52: 69-117.View ArticleGoogle Scholar
- Fan T, Bandura L, Higashi R, Lane A: Metabolomics-edited transcriptomics analysis of Se anticancer action in human lung cancer cells. Metabolomics. 2005, 1: 1-15.View ArticleGoogle Scholar
- DeBerardinis RJ, Mancuso A, Daikhin E, Nissim I, Yudkoff M, Wehrli S, Thompson CB: Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proceedings of the National Academy of Sciences of the United States of America. 2007, 104: 19345-19350.PubMed CentralView ArticlePubMedGoogle Scholar
- Zwingmann C, Richter-Landsberg C, Leibfritz D: C-13 isotopomer analysis of glucose and alanine metabolism reveals cytosolic pyruvate compartmentation as part of energy metabolism in astrocytes. Glia. 2001, 34: 200-212.View ArticlePubMedGoogle Scholar
- Lu D, Mulder H, Zhao P, Burgess SC, Jensen MV, Kamzolova S, Newgard CB, Sherry AD: 13C NMR isotopomer analysis reveals a connection between pyruvate cycling and glucose-stimulated insulin secretion (GSIS). Proceedings of the National Academy of Sciences of the United States of America. 2002, 99: 2708-2713.PubMed CentralView ArticlePubMedGoogle Scholar
- Lean CL, Bourne R, Thompson JF, Scolyer RA, Stretch J, Li LXL, Russell P, Mountford C: Rapid detection of metastatic melanoma in lymph nodes using proton magnetic resonance spectroscopy of fine needle aspiration biopsy specimens. Melanoma Research. 2003, 13: 259-261.View ArticlePubMedGoogle Scholar
- Eliyahu G, Kreizman T, Degani H: Phosphocholine as a biomarker of breast cancer: Molecular and biochemical studies. Int J Cancer. 2007, 120 (8): 1721-1730.View ArticlePubMedGoogle Scholar
- Glunde K, Jie C, Bhujwalla ZM: Molecular causes of the aberrant choline phospholipid metabolism in breast cancer. Cancer Research. 2004, 64: 4270-4276.View ArticlePubMedGoogle Scholar
- Katz-Brull R, Seger D, Rivenson-Segal D, Rushkin E, Degani H: Metabolic markers of breast cancer: enhanced choline metabolism and reduced choline-ether-phospholipid synthesis. Cancer Research. 2002, 62: 1966-1970.PubMedGoogle Scholar
- Glunde K, Jacobs MA, Bhujwalla ZM: Choline metabolism in cancer: implications for diagnosis and therapy. Expert Review of Molecular Diagnostics. 2006, 6: 821-829.View ArticlePubMedGoogle Scholar
- Swanson MG, Zektzer AS, Tabatabai ZL, Simko J, Jarso S, Keshari KR, Schmitt L, Carroll PR, Shinohara K, Vigneron DB, Kurhanewicz J: Quantitative analysis of prostate metabolites using H-1 HR-MAS spectroscopy. Magnetic Resonance in Medicine. 2006, 55: 1257-1264.View ArticlePubMedGoogle Scholar
- Lloyd SG, Zeng HD, Wang PP, Chatham JC: Lactate isotopomer analysis by H-1 NMR spectroscopy: Consideration of long-range nuclear spin-spin interactions. Magnetic Resonance in Medicine. 2004, 51: 1279-1282.View ArticlePubMedGoogle Scholar
- Mazurek S, Eigenbrodt E, Failing K, Steinberg P: Alterations in the glycolytic and glutaminolytic pathways after malignant transformation of rat liver oval cells. Journal of Cellular Physiology. 1999, 181: 136-146.View ArticlePubMedGoogle Scholar
- Kong X, Manchester J, Salmons S, Lawrence JCJ: Glucose transporters in single skeletal muscle fibers. Relationship to hexokinase and regulation of contractile activity. J Biol Chem. 1994, 269: 12963-12967.PubMedGoogle Scholar
- Artemov D, Bhujwalla ZM, Pilatus U, Glickson JD: Two-compartment model for determination of glycolytic rates of solid tumors by in vivo C-13 NMR spectroscopy. NMR in Biomedicine. 1998, 11: 395-404.View ArticlePubMedGoogle Scholar
- Villar-Palasi C, Guinovart JJ: The role of glucose-6-phosphate in the control of glycogen synthase. FASEB J. 1997, 11: 544-558.PubMedGoogle Scholar
- Robey IF, Lien AD, Welsh SJ, Baggett BK, Gillies RJ: Hypoxia-inducible factor-1 alpha and the glycolytic phenotype in tumors. Neoplasia. 2005, 7: 324-330.PubMed CentralView ArticlePubMedGoogle Scholar
- Fan TWM, Higashi RM, Lane AN: Integrating metabolomics and transcriptomics for probing Se anticancer mechanisms. Drug Metabolism Reviews. 2006, 38: 707-732.View ArticlePubMedGoogle Scholar
- Fan TW-M: Metabolite profiling by one- and two-dimensional NMR analysis of complex mixtures. Progress in Nuclear Magnetic Resonance Spectroscopy. 1996, 28: 161-219.View ArticleGoogle Scholar
- Gradwell MJ, Fan TWM, Lane AN: Analysis of phosphorylated metabolites in crayfish extracts by two-dimensional H-1-P-31 NMR heteronuclear total correlation spectroscopy (heteroTOCSY). Analytical Biochemistry. 1998, 263: 139-149.View ArticlePubMedGoogle Scholar
- Fan TWM, Colmer TD, Lane AN, Higashi RM: Determination of metabolites by proton NMR and GC: Analysis for organic osmolytes in crude tissue extracts. Analytical Biochemistry. 1993, 214: 260-271.View ArticlePubMedGoogle Scholar
- Fan TWM, Higashi RM, Lane AN, Jardetzky O: Combined Use of H-1-Nmr and Gc-Ms for Metabolite Monitoring and Invivo H-1-Nmr Assignments. Biochimica Et Biophysica Acta. 1986, 882: 154-167.View ArticlePubMedGoogle Scholar
- Fan TWM, Higashi RM, Frenkiel TA, Lane AN: Anaerobic nitrate and ammonium metabolism in flood-tolerant rice coleoptiles. Journal of Experimental Botany. 1997, 48: 1655-1666.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.