Mass Spectrometry-Based Method to Study Inhibitor-Induced Metabolic Redirection in the Central Metabolism of Cancer Cells

Cancer cells often respond to chemotherapeutic inhibitors by redirecting carbon flow in the central metabolism. To understand the metabolic redirections of inhibitor treatment on cancer cells, this study established a 13C-metabolic flux analysis (13C-MFA)-based method to evaluate metabolic redirection in MCF-7 breast cancer cells using mass spectrometry. A metabolic stationary state necessary for accurate 13C-MFA was confirmed during an 8–24 h window using low-dose treatments of various metabolic inhibitors. Further 13C-labeling experiments using [1-13C]glucose and [U-13C]glutamine, combined with gas chromatography-mass spectrometry (GC-MS) analysis of mass isotopomer distributions (MIDs), confirmed that an isotopic stationary state of intracellular metabolites was reached 24 h after treatment with paclitaxel (Taxol), an inhibitor of mitosis used for cancer treatment. Based on these metabolic and isotopic stationary states, metabolic flux distribution in the central metabolism of paclitaxel-treated MCF-7 cells was determined by 13C-MFA. Finally, estimations of the 95% confidence intervals showed that tricarboxylic acid cycle metabolic flux increased after paclitaxel treatment. Conversely, anaerobic glycolysis metabolic flux decreased, revealing metabolic redirections by paclitaxel inhibition. The gap between total regeneration and consumption of ATP in paclitaxel-treated cells was also found to be 1.2 times greater than controls, suggesting ATP demand was increased by paclitaxel treatment, likely due to increased microtubule polymerization. These data confirm that 13C-MFA can be used to investigate inhibitor-induced metabolic redirection in cancer cells. This will contribute to future pharmaceutical developments and understanding variable patient response to treatment.


INTRODUCTION
Various metabolic inhibitors are used as medications or chemotherapeutic agents for a wide variety of conditions, including cancer. 1) Exposure to these inhibitors o en a ects cell viability by directly or indirectly a ecting metabolic homeostasis. 2) In response to these changes, mammalian cells respond in-turn by redirecting carbon ow in the central metabolism. is supplies a required amount of raw materials and essential cofactors for adaptation to adverse conditions. 1,2) It is expected that a better understanding of cytotoxicity and the cellular mechanisms that underlie drug resistance can be achieved by analyzing the metabolic changes that occur a er inhibitor exposure. To this end, ux analyses using stable isotope-labeled tracers have been developed and widely employed to investigate ux and metabolic redirections in cancer cells. 3,4) For example, cancer cells and tissues have been successfully cultured in medium containing a 13 C-labeled carbon source that is subsequently incorporated into metabolites ( 13 C-labeling experiments). 5) By measuring 13 C labeling patterns in intracellular metabolites, or by examining mass isotopomer distributions (MIDs) using mass spectrometry, ux ratios at various metabolic branch points can be established. 6) ese MID analyses have revealed various cancer-speci c metabolic pathways that contribute to disease, such as reductive glutamine and C1 metabolism. 3,[7][8][9][10] In addition to the MID analyses, 13 C-metabolic ux analysis ( 13 C-MFA) is a promising method to perform a more thorough investigation of inhibitor-induced metabolic redirection in central metabolism. 11,12) Using this tool, metabolic ux distributions in the central metabolism have been estimated from MIDs and carbon uptake and lactate production rates. [13][14][15][16] Despite several applications of 13 C-MFA for mammalian cells [17][18][19][20][21][22] as well as preliminary analyses of the estradiol stimulated MCF-7 cells and verapamil treated HL-1 cardiomyocytes, 23) it remains unclear whether 13 C-MFA could be applied to investigate the e ects of metabolic inhibitors in cancer cells. It is because the 13 C-MFA requires two stationary states. 24,25) Firstly, cells need to be maintained and examined at a metabolic stationary state during exponential growth. Secondly, the MIDs of intracellular metabolites must be measured and compared at an isotopically stationary state under which these MIDs have reached a plateau. 24,25) e modern 13 C-MFA methodology strictly requires the two stationary states for statistically acceptable ux estimation with 95% con dence intervals (CIs) by a direct MID measurement of many intracellular metabolites. us, an analysis of dynamic metabolic events a er inhibitor treatment is still challenging for 13 C-MFA.
is study optimized a 13 C-MFA method to evaluate metabolic redirection in cancer cells a er treatment with various inhibitors used for cancer treatment. MCF-7 breast cancer cell line treated with the mitosis inhibitor paclitaxel (Taxol) was selected as a model for further investigation and model development. Paclitaxel is a chemotherapeutic agent used for many types of cancer, including breast carcinomas. 26) Further experiments using this model established that the metabolic and isotopic stationary states required for 13 C-MFA could be achieved, occurring during within an 8-24 h window a er low-dosage inhibitor treatment. Finally, ux redirection in the central metabolism of paclitaxel-treated MCF-7 cells was successfully evaluated by the developed method. is analysis indicates that 13 C-MFA is indeed suitable for investigating inhibitor-induced metabolic redirection in cancer cells. is will contribute to developing future pharmaceuticals and understanding patient responses to treatment.

MCF-7 culture
MCF-7 human breast carcinoma cells (3.6×10 5 cells) were seeded in 5 mL Dulbecco's modi ed Eagle's medium (DMEM) containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (Wako) in 60-mm (diameter) plates and cultured for 15 h at 37°C with 5% CO 2 . For the 13 C-labeling experiments, cells were cultured in 5 mL DMEM without glucose, L-glutamine, phenol red, sodium pyruvate, and sodium bicarbonate (Sigma-Aldrich, St. Louis, MO, USA), and supplemented with 20 mM [1-13 C]glucose, 2 mM [U-13 C] glutamine (Cambridge Isotope Laboratories, Andover, MA, USA, over 99% purity), 3.7 g/L sodium bicarbonate, and 10% dialyzed FBS (Life Technologies, Gaithersburg, MD, USA). Cultured medium (1 mL) was sampled for the analysis of extracellular metabo-lites. For 13 C-labeling experiments, cells were cultured on 20 plates in parallel, and 10 plates were used for sampling of intracellular metabolites of cells cultured in DMEM containing [1-13 C] glucose, and the other 10 plates containing [U-13 C] glutamine at 9, 12, 16, 20, and 24 h from the start of 13 C-labeling. e live cells were counted with trypan blue dye and a TC20 automated cell counter (BIO-RAD, Hercules, CA, USA). Trypsin was added to the plates and activated in 37°C for 1 min. A er collecting the cells, the live cells were counted with TC20. For extracellular metabolite measurements, culture medium (1.0 mL) was collected, mixed with an equal volume of 20 mM pimelate solution (internal standard), and ltered through a lter cartridge (0.45-µm pore size). Extracellular metabolite concentrations were determined by the previously described methods. 25)

Metabolite extraction and derivatization
Intracellular metabolites were extracted using methanol/ water/chloroform. 25) e medium was removed, and cells were rinsed with PBS. Next, 800 µL of −80°C methanol containing 5 µM ribitol (internal standard) was added to quench metabolism. Both solution and cells were collected via scraping. Cell lysates were transferred to fresh sample tubes, and 800 µL of cold chloroform and 320 µL of cold water were added. A er vortexing and centrifugation, the top aqueous layer was collected and dried under air ow. Dried metabolites were dissolved in 50 µL of 40 mg/mL methoxyamine hydrochloride in pyridine and held at 30°C for 90 min. Finally, 50 µL of MTBSTFA containing 1% TBDMCS was added and held at 60°C for 30 min.

Gas chromatography/mass spectrometry analysis
Gas chromatography/mass spectrometry (GC/MS) analysis was performed using an Agilent 7890 GC with DB-5MS capillary column (Agilent Technologies) connected to an Agilent 5975 MSD. e GC/MS was operated under electron impact (EI) ionization at 70 electron volts (eV). In splitless mode, a 1 µL sample was injected at 250°C, using helium as the carrier gas at a ow rate of 1 mL/min. For the analysis of central metabolites derivatives, the GC oven temperature was held at 70°C, increased to 280°C at a rate of 3°C/min for a total run time of approximately 75 min. e MS source and quadrupole were held at 230°C and 150°C, respectively, and the detector was operated in the selected ion monitoring mode. e m/z values for the 13 C-labeling of each metabolite are shown in the Supplementary Data S1.

C-Metabolic ux analysis
MFA was performed using a metabolic model of Homo sapiens similar to that used in the previous studies. [17][18][19][20][21] e model includes 85 reactions and 81 metabolites in the pathways for glycolysis, pentose phosphate, TCA cycle, anaplerosis, and lipid biosynthesis, as well as the metabolic branch from 3-phosphoglyceric acid (PGA) to serine biosynthesis and C1 pathway (Supplementary Data S1). In order to avoid rank de ciency during the calculation, metabolic ux levels of the output reactions for Asn and lactate were tted to the measured values by calculating the RSS values. e metabolic ux levels of the two output reactions were estimated by the 13 C-MFA, since the metabolic ux levels toward the C1 metabolism (PGA→C1 metabolism) and fatty acid biosynthesis (AcCoA_c→fatty acid biosynthesis) were not experimentally determined in this study. e metabolic branch was included because it has been reported that a signi cant amount of PGA is supplied to the C1 metabolic pathway and is degraded into CO 2 , regenerating NADPH. 8) In addition, intracellular compartmentalization between the cytosol and mitochondria was ignored for pyruvate, citrate, and α-ketoglutarate (αKG) as introducing intracellular compartmentalization failed to improve model tting (data not shown), since, similar simpli cation has also been performed in previous 13 C-MFA studies. 17,19,21,27) e metabolic ux levels of the other input and output reactions were xed to the observed values, and not used for the residual sum of squares (RSS) calculation. Fluxes for biomass of MCF-7 were calculated from the precursor and dry cell weight data. 28) All data analysis for the 13  e e ect of naturally occurring isotopes was removed from the raw mass spectrometry data. Metabolic ux levels were estimated by minimizing the RSS between experimentally measured and simulated MIDs using the sequential least squares programming (SLSQP) function implemented in PyOpt 1.2 30) :

RESULTS e e ects of inhibitor treatment on culture proles and material balance in MCF-7 cells
In order to identify the exponential growth of MCF-7 human breast carcinoma cells, culture pro les and growth curves were rst investigated (Fig. 1a).
is analysis indicated that MCF-7 cells were under exponential growth from 6-24 h a er initial seeding. Suitable concentrations for subsequent inhibitor treatment analysis were then evaluated using dose-response analyses. In particular, the number of live MCF-7 cells numbers at 24 h a er paclitaxel treatment showed that growth inhibition occurred in a dose-dependent manner (data not shown). As cells maintained in an exponential growth phase are essential for the 13 C-labeling experiment, a paclitaxel concentration that elicited 50% inhibition (10 nM) was employed for subsequent study.
E ect of paclitaxel treatment on the culture pro le was determined by the addition of paclitaxel. A growth curve analysis revealed that MCF-7 cell numbers decreased from 0-6 h a er treatment (Fig. 1b). is acute response is supported by previous studies indicating increased cell apoptosis at these concentrations of paclitaxel. 32) A er this initial period of cell death, the remaining cells then increased in number in a time-dependent manner. ese results indicate that exponential growth (or a metabolic stationary phase) occurred from 6-24 h (Fig. 1b). Furthermore, the recovery in growth suggests that MCF-7 cells have adapted to paclitaxel treatment and we hypothesized that this was likely due to changes in metabolic ux distribution.
In addition to paclitaxel, similar analyses were performed for several other metabolic inhibitors, including dichloroacetate (an inhibitor of the pyruvate dehydrogenase kinase), rotenone (a mitochondrial complex I inhibitor), 6-aminonicotinamide (an inhibitor of NADP + -dependent 6-phosphogluconate dehydrogenase), and 2-deoxyglucose (glycolytic inhibitor) (Figs. 1c-1f). e culture pro les of each of these inhibitors were similar to paclitaxel-treated cells, reaching an exponential growth phase between 8-24 h. ese results demonstrate that the exponential growth (or pseudo-metabolic stationary) state required for accurate 13 C-MFA can likely be attained for many inhibitors by selecting a dose that leads to partial inhibition of cell growth. However, for this study, paclitaxel was selected as the model compound for further development.
In order to obtain the material balance data required for 13 C-MFA, cell culture was repeated to determine the speci c growth rates of MCF-7 cells during the identi ed metabolic stationary phase (9-24 h) (Fig. 2). e speci c growth rates were determined to be 0.033 h −1 for control cells (Fig. 2a) and 0.014 h −1 for paclitaxel-treated cells (approximately 43% of the control; Fig. 2b). Further analysis of the culture medium showed that the concentrations of extracellular glucose and lactate had either decreased or increased in a time-dependent manner, respectively (Fig.  2a). e speci c rates for glucose consumption and lactate production in control cells were determined from the time course data to be 858±351 and 1451±26 nmol (10 6 cells) −1 h −1 , respectively (Table 1). ese data suggested that paclitaxel treatment a ected the material balance of MCF-7 cells due to the fact that the speci c rates of glucose consumption (673±164 nmol [10 6 cells] −1 h −1 ) and lactate production (821±53 nmol [10 6 cells] −1 h −1 ) were 78 and 56% of the control rates, respectively (Table 1). e consumption and production rates for amino acids were also determined from the medium component analysis (Table 1).

Con rmation of an isotopic stationary state
Next, an isotopic stationary state was con rmed using a 13 C-labeling experiment. To achieve this, cell media were exchanged with DMEM containing either [1-13 C] glucose or [U-13 C] glutamine at the 0 h timepoint. Intracellular free metabolites were extracted and 13 C-labeling determined by gas chromatography-mass spectrometry following derivatization with tert-butyldimethylsilyl (TBDMS) ethers ( Supplementary Fig. S1).  (Figs. 3e-3h). Similar results were observed for each of the measured metabolites ( Supplementary Fig. S2). Although more comprehensive 13 C-labeling would have provided accurate ux analysis, a longer cell cultivation time was determined to not be feasible under the current experimental conditions because an exponential cell growth phase could not be maintained.
is was due to cell con uency being reached at 30-36 h (data not shown). erefore, only MID data 24 h a er labeling were employed for ux estimation since an isotopically stationary state was almost attained.
Subsequent MID data showed that 13 C-labeling of metabolites in MCF-7 cells was a ected by paclitaxel treatment. Speci cally, for cells cultured in [1-13 C] glucose, the relative abundances of the m+1 signal of [M−85] + Ala were 0.440 (Fig. 3a) and 0.405 (Fig. 3b) at 24 h in control and paclitaxeltreated cells, respectively. For [1-13 C] glucose, equal amounts of unlabeled and [3-13 C]-labeled Ala were produced via the Embden-Meyerhof-Parnas (EMP) pathway. Conversely, only unlabeled Ala molecules were produced via the oxidative pentose phosphate (oxPP) pathway as the 13 C atom was discarded.
us, the branching ratios of metabolic ux between the oxPP and EMP pathways (oxPP/EMP) could be estimated from the labeling patterns of Ala. 12) If this branching ratio increases, metabolic change would be observed as a decrease in the relative intensities of mass signals derived from the m+1 signal of [M−85] + Ala. ese data suggest that paclitaxel treatment increases the oxPP/EMP branching ratios of MCF-7 cells (Figs. 3a and 3b).

Estimation of metabolic ux distribution using 13 C-MFA
As both metabolic and isotopic stationary states were es-  Table 1. All data are mean±standard deviations of three independent cultures.
tablished, it was con rmed that 13 C-MFA could be applied to examine the e ects of paclitaxel treatment in MCF-7 cells (Figs. 1 and 3). In addition to stationary states, 13 C-MFA also requires a direct MID measurement of many intracellular metabolites. For the purpose, a parallel labeling method was employed to increase MID measurement for a better estimation of metabolic ux using an experimental design shown in Supplementary Fig. S1. 27,[33][34][35] In this case, MCF-7 cells were cultured in parallel with media containing (a) [1-13 C] glucose and unlabeled glutamine or (b) unlabeled glucose and [U-13 C] glutamine. A er 24 h, two sets of MID data were obtained from these MCF-7 cells (Supplementary Data S1). Next, the metabolic distributions of control and paclitaxel-treated MCF-7 cells were determined from material balances 24 h a er labeling (Table 1) and from MID data ( Fig. 4 and Supplementary Data S1). e metabolic model used in this study was based on prior 13 C-MFA studies using cancer cells 21,27) and included glycolysis, the pentose phosphate pathway, the TCA cycle, anaplerotic reactions, fatty acid biosynthesis, and the metabolic branch from 3-phopshoglycerate (PGA) to the C1 metabolic pathway (PGA→C1 metabolism; Fig. 4 and Supplementary Data S1). As the studied system was over-determined, goodness of t could be validated by χ 2 tests. 36) Although the threshold residual sum of squares (RSS) was 47.4, the RSS of control and paclitaxel-treated cells were 36.9 and 42.1, respectively (Supplementary Data S2). is 13 C-MFA highlighted various facets of the cancerspeci c metabolism of MCF-7 cells, such as an active anaerobic glycolysis pathway due to the Warburg e ect. [37][38][39] In control MCF-7 cells, the metabolic ux of the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) reaction in glycolysis was 1,669 nmol (10 6 cells) −1 h −1 .
is was 10-fold greater than that of the TCA cycle and the oxidative pentose phosphate pathway. In addition, a large amount of α-ketoglutaric acid (αKG; 102 nmol [10 6 cells] −1 h −1 ) was also supplied from glutamine (Gln) and arginine (Arg). is was 11.8% of the glucose uptake rate and αKG was primarily catabolized via oxidative TCA reactions and malic enzyme (malate dehydrogenase) to produce lactate.

Metabolic redirection a er paclitaxel treatment
Although it has been shown that paclitaxel treatment inhibits tubulin polymerization, blocks cell replication, arrests cells in G2/M, and induces apoptosis, 32) the e ects on central metabolism are unclear.
is is because metabolic pro ling of paclitaxel treatment using immortalized human pancreatic cell lines showed no signi cant changes in central metabolism. 40) However, a comparison of estimated metabolic ux distributions in this study clearly indicated that paclitaxel treatment reduced metabolic ux into the EMP pathway that converts glucose into lactate for anaerobic glycolysis (blue arrows in Fig. 4b). For example, metabolic ux into the entry reaction of the EMP pathway (PGI) in control cells was 742 nmol (10 6 cells) −1 h −1 . ese levels decreased by 27% in paclitaxel-treated cells (547 nmol [10 6 cells] −1 h −1 ). However, the metabolic ux levels of the oxPP pathway in control and paclitaxel-treated cells were similar to each other (114 and 125 nmol [10 6 cells] −1 h −1 , respectively). is indicates that the branching ratio of oxPP/EMP had increased from 0.15 to 0.23 a er paclitaxel treatment.
is observed metabolic redirection at the EMP/oxPP branch point is consistent with the previously observed MID shi s in [M−85] + Ala (Figs. 3a and 3b). e paclitaxel-induced increase in metabolic ux was observed in reactions found in the lower half of the TCA cycle and two reactions in the anaplerotic pathway, malate dehydrogenase (MAE) and pyruvate carboxylase (PYC) (red arrows in Fig. 4b). For the case of the αKG dehydrogenase (αKGDH) reaction, the metabolic ux level in the paclitaxel-treated sample (123 nmol [10 6 cells] −1 h −1 ) was 1.5-fold higher than that of the control sample (81 nmol [10 6 cells] −1 h −1 ). As the αKG supply from Gln and Arg in the paclitaxel-treated sample (102 nmol [10 6 cells] −1 h −1 ) was similar to that of the control cells (100 nmol [10 6 cells] −1 h −1 ), this increase in αKGDH ux was derived from the redirection of metabolic ux in the isocitrate dehydrogenase (IDH) reaction. Indeed, the metabolic ux of the IDH reaction was altered from being reversed (reductive, −21 nmol [10 6 cells] −1 h −1 ) to forward (oxidative, 23 nmol [10 6 cells] −1 h −1 ) in the paclitaxel-treated sample (Fig. 4).

Cofactor balance
Finally, the metabolic reactions responsible for the regeneration and consumption of various cofactors (ATP, NADH, and NADPH) were characterized in the central metabolic network (Fig. 4b). is allowed an investigation of a balance between cofactor regeneration and consumption rates. Figure 5a summarizes the NADH balance in control and paclitaxel-treated cells. For control cells, the NADH regeneration rate was determined to be 2,237 nmol (10 6 cells) −1 h −1 (Fig. 5a), with 75 and 22% of NADH regenerated by the GAPDH reaction of glycolysis and reactions in the TCA cycle, respectively. On the other hand, the NADH consumption explained in the central metabolic network was 1,664 nmol (10 6 cells) −1 h −1 (Fig. 5a). e primary consumer of NADH was found to be the lactate dehydrogenase (LDH) reaction, consuming 87% of the NADH regenerated by GAPDH. e gap between total NADH regeneration and consumption was determined to be 573 nmol (10 6 cells) −1 h −1 and the 95% CI for this gap was calculated to be 467-689 nmol (10 6 cells) −1 h −1 (Supplementary Data S1, 95% CI of r107_OxPHOS). e gap indicates that excess NADH was consumed as an electron donor in the electron transport system of oxidative phosphorylation (OxPHOS).
is is approximately 1.8-fold higher than control cells (Fig. 5a).
is increase was ascribed to decreased NADH consumption by LDH and increased NADH regeneration by the TCA cycle (Fig. 5a). For NADPH, the estimated NADPH balance was deemed unreliable due to a large 95% CI of C1 metabolism and fatty acid biosynthesis ux (Fig.  5b).
ATP balance was also estimated from the OxPHOS rate calculated from NADH balance and the metabolic ux of . e ux levels used in this study are shown in the metabolic model. Each panel with numbers represents a best-t estimation of metabolic ux with lower and upper 95% con dence intervals (CIs). Dotted arrows represent reactions where metabolic ux levels were determined from a medium component analysis (Table 1). e red and blue arrows in panel (b) show reactions where metabolic ux levels were either increased or decreased by paclitaxel treatment. Signi cance was indicated by non-overlapping 95% CIs between any two conditions. e blue labels indicate reaction names. All abbreviations are de ned in Supplementary Data S3. Cofactors in the reactions are shown in panel (b). reactions responsible for ATP regeneration and consumption. Figure 5c shows that the ATP regeneration rate in control cells was 4,660 nmol (10 6 cells) −1 h −1 and the ratio between ATP regeneration by substrate phosphorylation (GAPDH and pyruvate kinase [PYK]) and by OxPHOS was established as 70 : 28. Of this regenerated ATP, 36% was consumed during the phosphorylation of glucose by hexokinase (HXK) and phosphofructokinase (PFK) during glycolysis. e gap between total regeneration and consumption was 2,983 nmol (10 6 cells) −1 h −1 , with a 95% CI of 2,782-3,249 nmol (10 6 cells) −1 h −1 (Supplementary Data S1, 95% CI of r108_ATPx). ese results suggest that ATP is being used for various cell functions, including cell component biosynthesis and cell division.
e ATP regeneration rate in paclitaxel-treated cells was 4,996 nmol (10 6 cells) −1 h −1 . is was similar to levels found in control cells (Fig. 5c). However, the contribution ratio between substrate level phosphorylation and OxPHOS was 49 : 49, suggesting that ATP regeneration was more dependent on OxPHOS and the mitochondrial electron transport system. As ATP consumption during glycolysis was reduced, the regeneration rate of excess ATP was elevated to 3627 nmol (10 6 cells) −1 h −1 , with a 95% CI of 3,234-4,123 nmol (10 6 cells) −1 h −1 (Fig. 5c).

DISCUSSION
is study has demonstrated that 13 C-MFA can be used to investigate metabolic redirection in inhibitor-treated cancer cells using paclitaxel-treated MCF-7 cells as a model. Since both metabolic and isotopic stationary states are required to apply 13 C-MFA, 24,25) an important outcome of this study is therefore a con rmation that MCF-7 cells reach two stationary states a er 10 nM paclitaxel treatment ( Figs. 1 and 3). In particular, it was shown that MCF-7 cells were in a metabolic stationary state 8-24 h a er paclitaxel treatment as an exponential growth phase was observed. Further measurements of intracellular metabolites by mass spectrometry revealed that MIDs had reached a plateau within this period, indicating an isotopically stationary state. Using these two stationary states, the overall distribution of ux in the central metabolism of untreated and paclitaxel-treated MCF-7 cells was successfully determined by 13 C-MFA of an over-determined metabolic system by direct MID measurement of intracellular metabolites in the parallel labeling experiment, the goodness-of-t analysis by the χ 2 statistics, and the estimation of 95% CIs (Figs. 3 and  4). 34,36,41) Using this newly established 13 C-MFA system, various aspects of the metabolism in MCF-7 cells and response to inhibitor treatment were revealed. A cancer-speci c metabolism such as the Warburg e ect was clearly observed in control cells since the metabolic ux of glycolysis was 10-fold larger than the TCA cycle (Fig. 4). In addition, glutamine was largely catabolized via oxidative TCA reactions and malate dehydrogenase to produce lactate. ese trends were similar to a recent study using 13 C-MFA to investigate lung cancer cells (A549) 27) and B-cells. 21) However, the result is inconsistent with another 13 C-MFA study examining MCF-7 cells, probably because of di erences in culture conditions and experimental design. 23) e result of this study also revealed that some αKG was converted into citrate (Cit) by the reversed reaction of isocitrate dehydrogenase (IDH) (Fig. 4). e reductive glutamine metabolism has been observed in various cancer cells and tissues and is therefore likely a marker of cancer-speci c metabolism. 3,7) In addition, the 13 C-MFA suggested that MCF-7 cells adopted a paclitaxel-treated condition by reducing their dependency on cancer-speci c metabolism. Moreover, metabolic ux levels of other cancer-speci c metabolic pathways such as MAE and PYC were upregulated by the paclitaxel treatment suggesting roles in the cancer metabolism. [42][43][44] A purpose of the metabolic redirection could be estimated from the quantitative determination of metabolic ux levels. e cofactor balance data (Fig. 5) indicated that excess ATP regeneration was elevated in paclitaxel-treated MCF-7 cells. e results suggested that the metabolic redirection is for the activation of ATP dependent microtubulin polymerization and for the ATP dependent excretion of paclitaxel. 32) However, the culture pro les and 13 C-labeling kinetic data ( Figs. 1 and 3) suggest some limitations in experimental design. e rst limitation is that 13 C-MFA cannot presently be applied to the study of organs as the method , and ATP (c) were obtained from best-t metabolic ux distributions (Fig. 4). Gaps between regeneration and consumption rates, with their 95% con dence intervals (CIs), are shown. It was hypothesized that excess NADH was used for ATP regeneration in the oxidative phosphorylation (OxPHOS) pathway with a P/O ratio of 2.3. requires detailed material balance data, including carbon uptake and lactate production rates (Table 1). is currently limits the technique to cells or tissues cultured in media. A second limitation is that the inhibitor dose range is quite limited as a relatively prolonged metabolic stationary state is required a er treatment to perform 13 C-MFA. erefore high-dose treatments that induce acute cell death would be unsuitable. irdly, the time points used for the analysis were limited since the metabolic state of MCF-7 cells changed in a time-dependent manner a er 10 nM paclitaxel treatment (Fig. 1b). While, paclitaxel-induced cell death was observed between 6-9 h (Fig. 1b), the remaining cells entered an exponential growth phase a er the cell death phase, indicating that MCF-7 cells may have adapted to paclitaxel treatment. is allowed metabolic ux distribution a er the metabolic adaptation to be evaluated by 13 C-MFA. A similar adaptation and exponential growth phase was observed for other metabolic inhibitors during the 8-24 h period, suggesting that 13 C-MFA could be applied to analyze metabolic redirection induced by other inhibitors. A nal limitation was the incomplete isotopically stationary states measured during the study (Fig. 3). Since longer cultivation times for more complete isotopically stationary states could con ict with the exponential growth required to establish a metabolic stationary state, culture conditions should be optimized for each unique experiment using di erent inhibitors and cell lines. If isotopically stationary states cannot be assumed, dynamic or isotopically non-stationary (INST)-MFAs using 13 C-labeling time-course data have been developed that could be applied for mammalian cell analysis. 19,21,45,46) e INST-MFA requires additional data concerning the intracellular concentration of all intermediates in the metabolic network, as well as more computational time to estimate metabolic ux distributions.
In summary, this study demonstrate that 13 C-MFA can be successfully applied to investigate metabolic redirection in the cancer cells due to inhibitor treatments. Using the validated metabolic and isotopic stationary states, 13 C-MFA was used to evaluate redirection of central metabolism in paclitaxel-treated MCF-7 cells, revealing the importance of metabolic ux into the TCA cycle and anaerobic glycolysis in the adaptation process. Although this study has provided validation of the 13 C-MFA method, more acute metabolic responses (<12 h) should be investigated for a more detailed understanding of the metabolic adaptation process. is would reveal where the metabolic state was transiently changed during the early response to inhibitor treatment. In addition, any regulatory mechanisms responsible for metabolic redirection cannot be estimated from the metabolic ux data alone. 12,47,48) erefore, a more comprehensive analysis of dynamic metabolic adaptation mechanisms due to drug treatment could be revealed using 13 C-based analysis in combination with other metabolic data. e present study suggests that 13 C-MFA is suitable for investigating inhibitor-induced metabolic redirection in cancer cells. is will aid the development of better targeted pharmaceuticals and understanding di erent patient responses to treatment. 49)