NMR Metabolomics Analysis of the Effects of 5-Lipoxygenase

Article pubs.acs.org/jpr

NMR Metabolomics Analysis of the Effects of 5‑Lipoxygenase Inhibitors on Metabolism in Glioblastomas Pier Jr Morin,† Dean Ferguson,† Luc M. LeBlanc,† Martin J. G. Hébert,† Aurélie F. Paré,† Jacques Jean-François,† Marc E. Surette,† Mohamed Touaibia,*,† and Miroslava Cuperlovic-Culf*,†,‡ †

Department of Chemistry and Biochemistry, Université de Moncton, Moncton, Canada National Research Council of Canada, Moncton, Canada

‡

S Supporting Information *

ABSTRACT: Changes across metabolic networks are emerging as an integral part of cancer development and progression. Increasing comprehension of the importance of metabolic processes as well as metabolites in cancer is stimulating exploration of novel, targeted treatment options. Arachidonic acid (AA) is a major component of phospholipids. Through the cascade catalyzed by cyclooxygenases and lipoxygenases, AA is also a precursor to cellular signaling molecules as well as molecules associated with a variety of diseases including cancer. 5-Lipoxygenase catalyzes the transformation of AA into leukotrienes (LT), important mediators of inflammation. High-throughput analysis of metabolic profiles was used to investigate the response of glioblastoma cell lines to treatment with 5-lipoxygenase inhibitors. Metabolic profiling of cells following drug treatment provides valuable information about the response and metabolic alterations induced by the drug action and give an indication of both on-target and off-target effects of drugs. Four different 5-lipoxygenase inhibitors and antioxidants were tested including zileuton, caffeic acid, and its analogues caffeic acid phenethyl ester and caffeic acid cyclohexethyl ester. A NMR approach identified metabolic signatures resulting from application of these compounds to glioblastoma cell lines, and metabolic data were used to develop a better understanding of the mode of action of these inhibitors. KEYWORDS: Drug discovery, NMR Metabolomics, Caffeic acid phenethyl ester, 5-lipoxygenase inhibitors, Glioblastoma multiforme, Antioxidant and antiradical activity

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INTRODUCTION Glioblastoma multiforme (GBM) is the most prevalent form of primary brain tumor in adults and one of the most lethal forms of cancer. Currently available treatments can foster a 2 year survival rate in only 13−27% of patients, which is significantly lower than for the majority of other cancers.1,2 The problems in prolonging survival of GBM patients are late diagnosis, local infiltrative growth within the brain, and the lack of subtypespecific treatment options. Subtyping of GBMs and the development of new treatments that take into consideration molecular characteristics of the diseases are urgently needed. Cancer metabolic phenotype provides an extremely interesting treatment option with a range of enzymes currently explored as drug targets.3 Metabolic changes are increasingly viewed as one of the hallmarks of carcinogenesis4−6 with many key oncogenic signaling pathways and epigenetic events converging in order for cells to adapt to an altered metabolism. At the same time, metabolic profiles in GBMs can help discriminate between tumor subtypes7 and can be explored as markers for tumors’ responses to treatment and treatment planning. Metabolism of polyunsaturated fatty acids is closely linked to carcinogenesis with major upregulation of de novo fatty acid synthesis and altered fatty acid utilization and processing both © 2013 American Chemical Society

as building blocks of biological systems and as signaling molecules. Polyunsaturated fatty acids are substrates for three different enzyme pathways: cyclooxygenase (COX), lipoxygenase (LO), and epoxygenase.8 A member of the lipoxygenase pathways, 5-lipoxygenase (5-LO) is the key enzyme in the conversion of arachidonic acid (AA) to leukotrienes (LTs).9 LTs are important lipid mediators of inflammation with a significant role in a number of diseases including cancers.10,11 The first two steps in LT biosynthesis catalyzed by 5-LO convert arachidonic acid into 5-hydroperoxyeicosatetraenoic acid (5-HPETE), followed by dehydration to the unstable epoxide LTA4. These initial oxygenation/dehydration steps are aided in the cellular environment by the 5-LO-activating protein (ALOXAP or FLAP), which acts as substrate transfer/ supply protein for 5-LO at the nuclear membrane. LTA4 is rapidly converted to either LTB4 by LTA4 hydrolase or to LTC4 by LTC4 synthases. LT signals are transduced via specific receptors, resulting in several distinct biological activities.12 Thus, inhibition of 5-LO has been considered as an avenue for treatment of various conditions with many Received: January 10, 2013 Published: April 5, 2013 2165

dx.doi.org/10.1021/pr400026q | J. Proteome Res. 2013, 12, 2165−2176

Journal of Proteome Research

Article

Scheme 1a

a Reagents and conditions: (i) NaOH, AcO2, 1 h, 85%; (ii) SOCl2, reflux, 4 h, pyridine, CH2Cl2, HOCH2CH2Phenyl or HOCH2CH2Cyclohexyl rt, 12 h, 5 (83%), 6 (80%); (iii) guanidinium chloride/Et3N in CH2Cl2/MeOH (1:1, v/v), rt, 4 h, 1 (84%), 2 (82%).

acid (4). The conversion of 4 into the corresponding carboxylic chloride was achieved by the Vilsmeier−Haack adduct derived from thionyl chloride (SOCl2) and DMF as catalyst. Baseinduced de-O-acetylation in 5 or 6 to afford CAPE (1)17,20 and the cyclohexyl analogue (MT30) (2) was accomplished with guanidinium chloride/triethyl amine in methanol and dichloromethane (Scheme 1).

natural products and derivatives showing potential as 5-LO inhibitors.13 Several reports show significance of 5-LO for tumor progression with 5-LO expressed in number of glioblastoma subtypes and observation of partial suppression of glioblastoma growth with 5-LO inhibition.14 Inhibition of 5LO in glioblastoma cell line expressing 5-LO induced apoptosis suggesting 5-LO inhibitors are possibly promising drugs for GBM.15,16 Zileuton is the only clinically approved 5-LO inhibitor, however, with possibly serious side effects as well as indications of off-target effects13 the search for novel drugs is justified. Recently, the effect of caffeic acid phenethyl ester (CAPE, compound 1 in Scheme 1), a component of propolis from honeybee hives, was tested as free radical scavenger, antioxidant, and 5-LO inhibitor.17 Boudreau et al.17 showed that CAPE is a potent inhibitor of LT biosynthesis through concurrent inhibition of 5-LO catalysis and AA release from membrane phospholipids. Contrary to the belief that polyphenols solely inhibit 5-LO through their antioxidant properties, these results showed that the ester functional group in CAPE influences 5-LO inhibition. In fact, CAPE was proven to be a superior inhibitor of LT biosynthesis compared to both amide and cinnamic acid analogues of caffeic acid as well as caffeic acid, which acts only as an antioxidant. Inhibition of LT biosynthesis and AA release as well as the antioxidant action of CAPE are expected to result in metabolic changes in cells. Thus, this work explores the metabolic changes in glioblastoma cells following treatment with caffeic acid phenethyl ester (CAPE) and caffeic acid cyclohexethyl ester (MT30) (Scheme 1). All metabolic changes are compared with the effects of the standard inhibitor of 5-LO, zileuton, as well as the unesterified caffeic acid. The metabolic changes were analyzed using NMR metabolomics profiling of lipophilic and hydrophilic cellular extracts. High content screening of drugs with metabolomics analysis provides molecular measurements closely related to drug targets.19 Many 5-LO inhibitors affect related 12-LO, 15-LO, and COX enzymes as they share the same substrate and a somewhat conserved binding site. This possible off-target effect can lead to significant changes in cells regardless of endogenous 5-LO levels. In addition, metabolomics analysis is explored as an initial screen for possible offtarget effects. As a result of the major metabolic changes induced by these four compounds in three GBM cell lines expressing different levels of 5-LO, a model of dominant action for four drugs was proposed.

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Cell Lines and in Vitro Culture Conditions

Human glioma cells A172, Hs683, and U373 were maintained in DMEM supplemented with 10% FBS (fetal bovine serum) and antibiotics (Invitrogen). All cell lines were a kind gift of Adrian Merlo (Laboratory of Molecular Neuro-oncology, University of Basel, Basel, Switzerland). Hydrophilic Phase Metabolite Isolation

Hydrophilic metabolites isolation was performed as described previously.7 Briefly, 1 × 106 cells were seeded in quadruplicate in 10 cm culture dishes, treated with 10 μM CAPE, 10 μM MT30, 10 μM caffeic acid, or 10 μM zilueton, and incubated for 72 h at 37 °C and 5% CO2. All compounds were dissolved in DMSO and metabolites isolated from cells treated with DMSO alone or not treated at all were also collected using the same protocol. Cells were harvested by scraping and rinsed with 5 mL of PBS. The mixture was centrifuged at 4,000 RCF (relative centrifugal force) for 1 min. Supernatant was discarded and the cell pellet was rinsed with 5 mL of PBS. Following another centrifugation at 4,000 RCF for 1 min, cell pellets were kept on ice for 5 min before being resuspended in 1 mL of ice-cold 50% acetonitrile. Cell suspensions were kept on ice for 10 min before centrifugation at 16,000 RCF for 10 min at 4 °C. The aqueous acetonitrile extract supernatants were dried down under a stream of N2. Lipophilic Phase Metabolite Isolation

Procedure for lipophilic metabolites isolation followed a previously published protocol.21 Cells were seeded, treated, and incubated as described in the previous section. Cells were then harvested in the culture medium and centrifuged at 1,000 rpm for 5 min at 4 °C. Pellets were subsequently washed twice with 4 mL of PBS followed by two centrifugation steps of 1,000 rpm. Cold methanol (7.4 mL/pellet) and cold water (2.2 mL/ pellet) were added to resuspend the pellets. Samples were sonicated in an ice bath for three 1-min cycles interspersed with 1-min wait periods. The homogenates were transferred to glass tubes, cold chloroform was added (3.7 mL/pellet), and the tubes were sealed. Homogenates were stored overnight at 4 °C. The following day, cold chloroform and cold water (3.7 mL/g pellet each) were added to the tubes, and samples were vortexed for 30 s. Homogenates were centrifuged at 1,000 rpm for 5 min at 4 °C. The lower phase containing the lipophilic metabolites was recuperated and dried down under a stream of N2.

MATERIALS AND METHODS

Compounds Synthesis

The synthesis of CAPE (1) as well the cyclohexyl analogue (2) is summarized in Scheme 1. The two esters were synthesized from 2-phenyl or 2-cyclohexylethanol with acetylated caffeic 2166



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NMR Experimentation and Preprocessing

mM NaCl, 0.05% v/v Tween 20) with 5% w/v powdered skim milk. Membranes were then incubated overnight at 4 °C with polyclonal rabbit anti-human 5-LO antibodies (New England Biolabs) at a 1:1000 v/v dilution in TBST. Subsequently, membranes were incubated with HRP-linked anti-rabbit IgG secondary antibody (1:2000 v/v dilution) in TBST for 1 h and then blots were developed using chemiluminescent reagents. Bands at ∼75 kDa corresponding to the expected molecular weight of 5-LO were visualized using an Alpha Innotech gel imager.

The residue obtained after drying was dissolved in 0.6 mL of deuterium oxide (Aldrich, 99.96 atom % 2H) and pipetted into a 5 mm NMR tube for NMR analysis. All 1H NMR measurements were performed on a Bruker Avance III 400 MHz spectrometer at 298 K. 1D spectra were obtained using a gradient water presaturation method22 with 512 scans. Standard parameters were used with gradient duration of 1 ms and recovery delay after the gradient of 100 μs. NMR spectra were processed using Mnova with exponential apodization (exp 1); global phase correction; Berstein-Polynomial baseline correction; Savitzky-Goley line smoothing and normalization using total spectral area as provided in Mnova. Spectral regions from 0 to 9 ppm were included in the normalization and analysis. Data preprocessing including data organization, removal of undesired areas, and binning as well as data presentation was performed with Matlab vR2010b (Matworks). Minor adjustments in peak positions (alignment) between different samples were performed using in-house alignment software (GASP) as well as Icoshift.23 The qualitative analysis of the major variances in the spectra were performed by using principal component analysis (PCA) as well as fuzzy K-means cluster analysis using Matlab platform as described previously.7,24 Feature selection was done with the significance analysis for microarrays (SAM) method.25

Antioxidant Activity Measurement

The antioxidant assay was performed as previously described by Liégeois et al.29 Briefly, a 5 mM phosphate-buffered solution (pH 7.4) containing 0.05% Tween 20 (Sigma-Aldrich) and 0.16 mM linoleic acid (Cayman Chemical) was preheated at 40 °C. The oxidation reaction, performed under a constant temperature of 37 °C, was initiated with the addition of 50 μL of 2,2′azobis(2-amidinopropane) dihydrochloride (AAPH) solution (10 mg mL−1) (Cayman Chemical) to 1 mL of the above solution in the presence of the test compounds or their diluent. The rate of lipid oxidation was determined by measuring the absorbance at 234 nm with a Thermo Varioskan UV visible spectrophotometer at every 5 min for 3 h. Inhibition of linoleic acid oxidation was calculated as followed: (%) = (1 − rate absorbance change with test compound/rate of absorbance change with solvent control) × 100.

Hydrophilic Phase Metabolite Quantification

Peak assignment was performed using several methods developed in our group and elsewhere and was based on metabolic NMR databases.7,26−28 Spectra for 40 metabolites used in quantification were obtained from the Human Metabolomics Database (www.hmdb.ca) or Biological Magnetic Resonance Databank (www.bmrb.wisc.edu) and were further analyzed visually and compared to the obtained spectra. An automated method for quantification based on multivariable linear regression of spectra with appropriately aligned metabolite data from databases was previously described in detail7 and used in this study. The assumption behind this approach is that the spectrum of a mixture is the same as the combination (sum) of spectra of individual components measured under the same conditions. Relative metabolite concentrations were estimated using nonlinear curve fitting with the multivariate least-squares approach. The linear regression result was used as the starting point, and the model was constrained to concentrations c ≥ 0. NMR spectra of the mixtures (samples) are modeled as a sum of spectra for components (metabolites) in the mixture. Lipophilic phase metabolite quantification is performed for peak areas as peaks represent groups that can be present in multiple metabolites measured in this phase. Assignment of specific peak positions is based on literature information.

Antiradical Activity Measurement

The radical scavenging activity of test compounds was measured as previously described using 2,2-diphenyl-1picrylhydrazyl (DPPH) as a stable radical25 with slight modifications. Particular care was taken in the preparation of the control (DPPH reagent + ethanol as a diluent without test compounds). Controls with OD of 0.350−0.360 at 520 nm were deemed as acceptable to avoid variations in IC50 calculations. One millilier of DPPH in ethanol (60 mM) was mixed with 1 mL of the test compounds at the indicated concentrations or their diluent (ethanol). Each mixture was then shaken vigorously and held in the dark for 30 min at room temperature. The absorbance of DPPH at 520 nm was then measured. The radical scavenging activity was expressed in terms of % inhibition of DPPH absorbance: % inhibition = [(Acontrol − Atest)/Acontrol)] × 100, where Acontrol is the absorbance of the control (DPPH solution without test compound), and Atest is the absorbance of the test sample (DPPH solution plus compound). IC50 Calculations. All data are expressed as means of three experiments;, each experiment being performed in triplicate. IC50 values were calculated from a sigmoidal concentration− response curve-fitting model with a variable slope on a GraphPad Prism 5 software (GraphPad Software, San Diego, CA).

SDS-PAGE and Immunoblotting

GBM cells were trypsinized, centrifuged, and resuspended in 800 μL of NP-40 lysis buffer (1% Nonidet-P40, 50 mM TrisHCl pH 7.6, 150 mM NaCl, 2 mM EDTA and a single protease inhibitor cocktail tablet (Roche)) followed by 200 μL of 5X SDS buffer (100 mM Tris-base, 10% SDS w/v, 20% glycerol, 0.2% bromophenol blue, 10% 2-mercaptoethanol) at 4 °C. Aliquots containing an equal amount of total protein were loaded into each lane. Electrophoresis and transfer to PVDF membranes (PALL Life Sciences) was carried out as described previously.29 Following transfer, the PVDF membrane was blocked for 30 min in TBST (50 mM Tris-HCl pH 6.8, 150

Chemistry

All chemicals used were purchased from Aldrich (CA). TLC was performed on Kieselgel 60 F254 plates from Merck. Detection was carried out under UV light or by molybdate solution followed by heating. Separations were carried out on silica gel (7749 Merck) using circular chromatography (Chromatotron, model 7924, Harrison Research). Melting points were obtained using a MEL-TEMP (model 1001D) melting point apparatus. NMR spectra were recorded on a Bruker Avance III 400 MHz spectrometer. Accurate mass 2167



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measurements were performed on a MicrOTOF instrument from Bruker Doltonics’ in positive electrospray. Either protonated ions (M + H)+ or sodium adducts (M + Na)+ were used for empirical formula confirmation. Compound 6. White solid (82%); mp 90−91 °C. 1H NMR (400 MHz, CDCl3, 25 °C) δ (ppm): 7.63 (d, J = 16 Hz, 1H,  CHCar), 7.43 (d, J = 8.4 Hz, 1H, Har), 7.38 (s, 1H, Har), 7.24 (d, J = 8.4 Hz, 1H, Har), 6.40 (d, 1H, 16 Hz, CHCO), 4.26 (t, J = 6.8 Hz, 2H, CH2CH2cycloHexyl), 2.33 (s, 6H, 2 × OAc), 1.78−1.59 (m, 7H, CH2CH2cycloHexyl, CH2CH2cycloHexylH), 1.43 (br s, 1H, CH2CH2cycloHexylH), 1.32−1.13 (m, 3H, CH2CH2cycloHexylH), 1.02−0.93 (m, 2H, CH2CH2cycloHexylH). 13C NMR (101 MHz, CDCl3, 25 °C) δ (ppm): 168.10, 168.02, 166.71, 143.41, 142.57, 142.41, 133.39, 126.40, 123.91, 122.70, 119.54, 63.01, 36.04, 34.58, 33.19, 26.50, 26.21, 20.68, 20.64. Compound 2 (MT30). White solid (82%); mp 147−148 °C. 1H NMR (400 MHz, DMSO-d6, 25 °C) δ (ppm): 9.61 (br s, 1H, OH), 9.16 (br s, 1H, OH), 7.46 (d, J = 15.8 Hz, 1H, =CHCar), 7.05 (s, 1H, Har), 7.01 (d, J = 8.1 Hz, 1H, Har), 6.76 (d, J = 8.1 Hz, 1H, Har), 6.26 (d, J = 15.8 Hz, 1H, =CHCO), 4.15 (t, J = 6.5 Hz, 2H, CH2CH2cycloHexyl), 1.72−1.60 (m, 5H, CH2CH2cycloHexylH), 1.52 (q, J = 6.5 Hz, 2H, CH2CH2cycloHexyl), 1.36 (br s, 1H, CH2CH2cycloHexylH), 1.25−1.11 (m, 3H, CH2CH2cycloHexylH), 0.96−0.88 (m, 2H, CH2CH2cycloHexylH). 13C NMR (101 MHz, DMSO-d6, 25 °C) δ (ppm): 167.07, 148.83, 146.01, 145.48, 125.95, 121.81, 116.18, 115.29, 114.48, 62.25, 36.13, 34.48, 33.07, 26.49, 26.15. HRMS-ESI: m/z [M + 1]+ calcd for C17H23O4 291.1596, found 291.1579.

Table 1. Antiradical and Antioxidant Properties of the Tested Compoundsa compound caffeic acidb Zileutonb MT-30 CAPEb

free radical scavenging IC50 (μM) mean CI mean CI mean CI mean CI

13.2 9.76−17.9 >100 n.i.b 13.2 12.3−14.1 21.9 15.2−31.4

antioxidant assay IC50 (μM) mean CI mean CI mean CI mean CI

2.01 1.68−2.42 0.79 0.59−1.06 2.71 1.89−3.87 1.09 0.77−1.54

a

Values are means from 3 independent experiments, each performed in triplicate. bData from refs 17 and 18.

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Figure 2. Sum of lipophilic phase spectra for three cell lines including untreated and treated cells. Sums for each cell type are presented as three colored areas. Spectral regions represent spectra from lipophilic metabolites with: 1, CH3 (cholesterol); 2, CH3CH2 (cholesterol); 3, CH2 (lipid, cholesterol); 4, residual signal from water; 5, CH2CH CH (lipid); 6, CH2COO (lipid); 7, CHCH2CH; 8, N(CH3) (phosphatidylethanolamine, phosphatidylcholine); 9, CH2OCOR, CH2OPO2; 10, CHOCOR (lipid); 11, HCCH (lipid, cholesterol); 12, Ar−H; 13, Ar−H (assignments based on previous work45).

RESULTS AND DISCUSSION Three distinct GBM cell lines, A172, Hs683, and U373, expressing different levels of 5-LO were used to analyze the

Figure 1. Western blot analysis of expression levels of 5-LO in studied cell lines. Shown are relative exposure levels from three different experiments. Expression level of 5-LO is relative to the corresponding β-actin level.

effects of the investigated treatments on cellular metabolism. Endogenous 5-LO protein levels in these cells lines, determined by Western blot analysis (Figure 1), were A172 > Hs683 > U373, in agreement with previously shown levels for some of these cell types.15 Cells were treated with the same amounts of structurally related compounds CAPE, MT30 (compound 2 in Scheme 1), zileuton, and caffeic acid. DMSO was also used to monitor the solvent effects on metabolism. Concentration of 10 μM was selected on the basis of the results from previous work17 as a concentration that, for all compounds, shows over 50% 5-LO inhibition as well as antioxidant and antiradical activity in vitro while not inducing cell death. Two inhibitors, CAPE and MT30 (Schema 1), were synthesized using the

Figure 3. Average spectra of hydrophilic extracts of cell lines studied in this work from three cell lines.

procedure developed by our group (see Materials and Methods). CAPE and MT30 are all redox-active 5-LO inhibitors that act by keeping active site iron in the ferrous state. Due to their high redox activity, they are likely to interfere with other biological redox systems. Caffeic acid is an antioxidant with little or no inhibitory effect toward 5-LO.14 Zileuton is an iron ligand inhibitor that chelates iron in the active site while at the same 2168



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Figure 4. PCA and fuzzy C-means analysis of hydrophilic profiles (spectra) of three cell lines following DMSO or drug treatment. (A) PCA shows plots for PC1 and PC2 including the percentage of represented variation. (B) Fuzzy C-means clusters indicate relative membership values where blue is membership value of 0, no belonging to cluster, and red shows membership of 1, indicating strong belonging to cluster. In fuzzy clustering all samples can belong to all clusters allowing for non-strict grouping.

metabolites are included (Supplementary Figure 2B and C). Concentrations were determined for the 40 metabolites listed in Supplementary Figure 1. Of more interest, however, is the change in metabolic profiles following drug treatments and controls for each cell lines shown in Figure 4. Presented are results of PCA and fuzzy clustering analysis for hydrophilic metabolites for tree cell lines including samples treated with drugs and controls. Analysis of lipophilic metabolites gives comparable result (data not shown). General trends shown by PCA agree with the result of true clustering with Fuzzy C-means (FCM) method. Major metabolic changes induced by caffeic acid and zileuton treatments are comparable in all three cell lines regardless of the 5-LO expression levels. On the other hand CAPE and MT30 treatments lead to comparable metabolic shift in A172 cells only. In U373 cells the effect of CAPE is indistinguishable from the control cells, and similarly in Hs683 cells the effect of MT30 cannot be separated from the effect of the solvent. Quantitative metabolic data (i.e., relative concentrations of metabolites) obtained from spectra provide for more informative determination of major changes caused by stimulation. In addition, obtaining information about the affected metabolites, rather than only spectral positions leads to the possibility for biological interpretation and application of results. Preservation of major features in the data following the quantification of metabolites is shown through fuzzy clustering analysis of spectral and quantitative data for hydrophilic metabolites shown in Supplementary Figure 3.

time having weak reducing properties. Antiradical and antioxidant characteristics of these four compounds are shown in Table 1. For comparison, ascorbic acid showed free radical scavenging activity with an IC50 value of 75 μM.14 CAPE was previously shown to be a very effective inhibitor of 5-LO products biosynthesis and of AA release from membranes.17 All tested compounds exhibit significant antioxidant and radical scavenging activity with the exception of zileuton, which is not a strong free radical scavenger17,18 (Table 1). The metabolic effects of treatments were measured using 1H NMR spectroscopy with separate analysis of lipophilic and hydrophilic cellular extracts. Measurements were performed on all three cell lines (A172, Hs683, and U373), in untreated cells as well as cells treated with DMSO (solvent), CAPE, MT30, zileuton, and caffeic acid. The sum of lipophilic phase spectra with assignment of spectral regions is shown in Figure 2. An equivalent figure for hydrophilic region is shown inFigure 3. Spectra of the reference metabolites used in quantification relative to the sample spectra are shown in Supporting Information. PCA of lipophilic and hydrophilic spectra for all cell lines and all treatments (Supplementary Figure 2) show clear separation of nontreated cells from those treated with compounds or even only solvent. As a sideline, metabolic profiles are also significantly different for the three cell lines tested. Concentrations of metabolites in the hydrophilic phase were obtained using the multivariate linear regression method described in Materials and Methods and in greater detail previously.7 Both spectral and quantitative metabolic data were used for analyses. Data obtained by analysis of relative concentrations of 2169



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Figure 5. SAM determination of major metabolic differences between samples for three cell lines. Plots in panel A show major metabolic differences between cells treated with DMSO as group 1 and CAPE, MT30, and zileuton as group 2 representing 5-LO inhibitors. Panel B shows major metabolic differences between samples treated with DMSO and those treated with CAPE, MT30, or caffeic acid representing antioxidants. Plots show data following scaling across samples for improved visualization.

PCA of control samples (treated with DMSO) and samples treated with each compound included in the study are shown in Supplementary Figure 4A for hydrophilic metabolites (using spectra and relative metabolite concentrations) and lipophilic metabolites (Figure 4B) and shows agreement with the analysis shown in Figure 4. The effect of all three 5-LO inhibitors is largest in A172 cells with clear separation of treated and control samples based on profiles of hydrophilic and lipophilic metabolites. Caffeic acid and also zileuton alter metabolic profiles in cells regardless of the expression of 5-LOin three cell cultures, possibly through their antioxidant function. In fact results suggest more significant effect of zileuton and caffeic acid as antioxidants on the cell metabolism than is the effect of 5-LO inhibition. This is indicated by more closely related metabolic change caused by zileuton and caffeic acid compared to the other two drugs in all three cell types. The most significantly altered metabolites for all four treatments relative to DMSO-treated cells are determined using SAM method (Figure 5). With compounds causing metabolic changes through both an effect

on 5-LO as well as an antioxidant effect, it is of interest to determine metabolites that are affected by 5-LO inhibition and, conversely, those resulting from the antioxidant properties of the tested compounds. Out of the four compounds, CAPE and MT30 are 5-LO inhibitors and antioxidants with free radical scavenging activity, zileuton is both a 5-LO inhibitor and an antioxidant, and caffeic acid is an antioxidant with free radical scavenging activity (Table 1). The most differentially concentrated metabolites between groups of CAPE, MT30, and caffeic acid (as radical scavengers and antioxidants) versus DMSO and CAPE, MT30 and zileuton (5-LO inhibitors and antioxidants) versus DMSO were determined in the three cell cultures (Figure 5A and B). Result of this analysis is closely linked to the sample separation observed in PCA (Figure 4). In A172 cells all treatments induced metabolic profile change relative to DMSO, with similar metabolites experiencing the largest change with all four treatments. Clustering of MT30 with caffeic acid in the analysis in Figure 7B (A172) and its clustering away from CAPE and zileuton in Figure 7A (A172) possibly indicates a 2170



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Figure 6. Loadings plots (for PC1) obtained by performing PCA comparison of DMSO-treated cells and cells treated with each of the four inhibitors. Included in the legend is information about the percentage of variability represented by PC1. Peaks positions are assigned equivalently to Figure 2 and represent: 1, CH3 (cholesterol); 2, CH3CH2 (cholesterol); 3, CH2 (lipid, cholesterol); 5, CH2CHCH (Lipid); 6, CH2COO (lipid); 8, N(CH3) (phosphatidylethanolamine, phosphatidylcholine); 11, HCCH (lipid, cholesterol); 12, Ar−H; 13, Ar−H (assignments based on published work45).

and caffeic acid lead to observable metabolic shifts. Loading plots (Figure 6) obtained from PCA of different groups of lipophilic samples present discriminatory spectral regions for different treatments. Figure 6 shows loadings for PC1 as well as percentage of total variability explained with PC1 for each cell type. Figure highlights regions of the spectra that are contributing to the observed PC1 grouping of samples. Concentrations of lipophilic metabolites were significantly affected by the treatments. Affected positions are assigned to cholesterol and other lipid groups (listed in Figure 6). In the lipid spectrum, the same locations are most significant for PCA results in all groups of data explored. In A172 cells, inhibition of 5-LO leads to major changes in lipid groups concentrations. This is not surprising given the potent action of 5-LO products in cell activation and functional responses such as chemotaxis.30 The effect of four compounds are clearly distinct in the three cell lines tested here with different levels of metabolic changes resulting from four treatments and with different metabolites being the most affected. Hs683, A172, and U373 cells show

more significant antioxidant or radical scavenging effect of MT30 relative to the other 5-LO inhibitors. In Hs683 cells, zileuton and caffeic acid lead to the largest change in metabolic profiles, likely through their antioxidant effect and impact on AA release (for zileuton). In U373 cells, CAPE does not induce significant change in the observed metabolite concentrations either through 5-LO inhibition nor through the antioxidant function as it clusters with DMSO-treated samples in both analyses (Figure 4). MT30 and zileuton-treated samples once again group with those treated with caffeic acid (Figure 5B). PCA analysis of lipophilic spectra shows results comparable to the those obtained for hydrophilic samples (Figure 6 and Supplementary Figure 4). Once again, lipophilic metabolites are significantly altered with any of the four treatments in A172 cells. In Hs683 cells, zileuton and caffeic acid lead to major separation of samples, although some grouping of treated samples is visible for cells exposed to MT30 and CAPE. In U373 cells, CAPE treatment does not induce significant metabolic change (according to PCA), but MT30, zileuton, 2171



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Figure 7. (A) Logarithmic values of relative gene expression levels for genes involved in AA metabolism. Values are obtained from Broad CCLE database.31 (B) Schematic representation of major, initial steps in AA metabolism.

studies.32 Hs683 cells show relative overexpression of cPLA2 (suggesting high release of AA) and PTGS1, thus suggesting replacement of LT production in these cells by production of prostaglandin E2 (PGE2). PGE2 promotes cell proliferation at least in part via the stimulation of β-catenin, which leads to a number of carcinogenic changes including metabolic changes.33 15-LO and 12-LO branches lead to production of HPETEs, which are implicated in the activation of peroxisome proliferator-activated receptors (PPARs).34 PPAR activation leads to number of metabolic changes and ultimately apoptosis. In addition, 15(S)-HPETE is also a substrate for glutathione Stransferase further promoting metabolic transformation. Inhibition of AA and lipid pathways can have both direct and indirect effects on hydrophilic metabolites. Analysis of major differentially concentrated metabolites in the hydrophilic phase spectra are shown in Figure 5 and Figure 8. In A172 cells, four treatments lead to changes in concentrations of (Figure 5) succinic acid, adenine, aspartate, myoinositol, and adenosine indicating possible changes in glutathione/glutamine/proline (Glut/Gln/Pro) metabolism, methionine metabolism (adenosine, adenine), or purine pathway (adenosine, aspartate, adenine). Dissimilar responses of A172 and Hs683 to the 5LO inhibitors is also clear from the analysis of major metabolic changes following treatments in these two cell lines (Figure 8A). Major metabolic differences between Hs683 and A172 cells prior to 5-LO inhibition are determined from the analysis of samples treated with DMSO (Figure 8A). Although metabolic differences between glioblastoma subtypes are interesting, it is

dissimilar expression levels of genes involved in six pathways of AA metabolism. AA metabolism is initiated by PLA2G4A (cPLA2), a calcium-dependent, cytosolic phospholipid-binding protein that catalyzes AA release from phosphatidylcholine (most commonly). AA is then transformed through one of six different avenues (according to KEGG metabolic pathways database). Figure 7A presents logarithmic values of relative expression levels for: PLA2 (PLA2G4A), 5-LO, 5-lipoxygenase activation protein (ALOXAP), leukotriene A4 hydrolase (LTA4H), LTC 4 synthases (LTC4S), cyclooxygenase (PTGS1), cytochrome P450 (CYP2B6), 15-lipoxygenase (15b-LO), and 12-lipoxygenase (12b-LO and 12-LO). Values are obtained from Broad-Novartis Cancer Cell Line Encyclopedia (CCLE).31 Values for 5-LO are in agreement with Western blot measurements shown in Figure 1. PLA2GA4 is highly expressed in Hs683 cells, suggesting substantial AA release in these cells. The initial steps of six separate avenues for AA metabolism are catalyzed by (1) PTGS1, (2) CYP2B6, (3) 15-LOB, (4) 12-LO, (5) 12b-LO, and (6) 5-LO, and all lead to distinct metabolic products. 5-LO is activated by ALOXAP (i.e., FLAP or 5-LOAP) and subsequent steps toward leukotriene generation are catalyzed by LTA4H and LTC4S (Figure 9B), all of which are overexpressed in A172 cells. PTGS1 and CYP2B6 branches are up-regulated in Hs683 cells. U373 cells, also known as U251MG, under-express all of the genes listed relative to the two other cell lines, suggesting reduced significance of AA metabolism in this cell type. Gene expression data are clearly consistent with LTs production in the A172 cell line, in agreement with previous 2172



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Figure 8. SAM determination of the most significantly different metabolites between Hs683 and A172 cells treated with (A) DMSO; (B) CAPE, MT30, or zileuton (5-LO inhibitors); and (C) caffeic acid as an antioxidant. Outlined are metabolites that are different only in control cells (red), in control and inhibitor-treated cells (green), only treated cells (dark red), control and antioxidant-treated cells (blue), and metabolites that are only different in one group of treatments (underlined).

acid, an antioxidant, also leads to dissimilar metabolic changes in two cell lines. Once again, levels of L-proline, glutamate, and glycerol-3-phosphate become comparable. Following antioxidant treatment, however, choline, leucine, oxidized glutathione, and phenylalanine concentrations are significantly altered. This analysis thus emphasizes the distinct effects of 5-LO inhibitors and antioxidants on selected GBM cells. Following this analysis it can be hypothesized that 5-LO inhibition leads to changes in concentrations of methionine, succinate, alanine, and phosphocholine. Antioxidant treatment leads to additional changes in concentrations of L-proline, glutamate, glycerol-3-phosphate, and choline (altered to the baseline in all treatments) and glutathione, phenylalanine, and leucine (unique to caffeic acid treatment). 5-LO (directly influences several major oncogenes or cell regulators. 5-LO inhibitors have been previously shown to reduce TNF levels. 35 TNF significantly stimulates the

not the focus of this work. Metabolic differences for DMSOtreated cells provide however a baseline for the analysis of treated cells. Major metabolites with dissimilar concentrations in Hs683 and A172 cells treated with 5-LO inhibitors (CAPE, MT30, and zileuton) are shown in Figure 8B. In this group, glycine, myoinositol, taurine, and lactate remain dissimilar as they were in the control samples (Figure 8A) (shown in green in the figure). However, concentration levels of L-proline, glutamate, and glycerol-3-phosphate change with addition of inhibitors, and although in control cells they were significantly different in Hs683 and A172 cells, they are no longer dissimilar in the two treated cell cultures. Therefore L-proline, glutamate, and glycerol-3-phosphate (shown in red in the figure) are differentially affected by treatment in the two cell cultures. Finally, addition of inhibitors to the two cell lines leads to different changes in concentration levels of methionine, succinate, phosphocholine, and choline. Treatment with caffeic 2173



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and reduced production of LTs. Previous computational analysis of the AA pathway has shown that blocking 5-LO can lead to activation of 15-LO.38 The 15-LO pathway products stimulate PPAR signaling, and this, in addition to the changes in LTs concentrations, leads to significant metabolic changes. In Hs683 cells, PTGS1 is significantly overexpressed while 5LO as well as 15-LO and related genes are down-regulated, suggesting that in Hs683 the PTGS1 branch of the AA pathway is the most active. Treatment with 5-LO inhibitors CAPE and MT30 of Hs683 cells leads only to minor changes in lipophilic and hydrophilic profiles, possibly through off-target inhibition of PTGS1 or AA release or through antioxidant activity of the compounds. At the same time, zileuton influences AA release,13 and caffeic acid acts as an antioxidant. Both compounds are possibly affecting other less characterized enzymes leading to clearly apparent metabolic effects. The majority of genes involved in AA metabolism are under-expressed in U373 cells; however, treatment of cells with MT30, zileuton, and caffeic acid still induces changes in metabolism. One possible target in this case is lamin γ1. Lamin γ1 is known to be highly expressed in U373 cells and absent in Hs683 cells and is the target of molecular structures designed for PTGS1 inhibition in glioblastomas.43,44 Inhibition of lamin γ1 could lead to observed changes, particularly in choline metabolites due to its role in cell wall binding. Analysis of specific off-target effects of these compounds as well as further analysis of avenues for the observed metabolic change will be undertaken in the future.

Figure 9. Pathway Studio analysis of the shortest path connecting metabolites phosphocholine, succinate, methionine, and alanine (that were affected differentially by tested compounds in A172 and Hs683 cells) and 5-LO (as the target for inhibitors). Gene colors indicate expression levels in Hs683 relative to A172 (wild type, not treated) with blue indicating overexpression in Hs683 and red in A172. For metabolites, yellow indicates overexpression in Hs683 and blue in A172 cells. Arrows indicate metabolite concentration changes in A172 cells treated with 5-LO inhibitors relative to A172 cells treated with antioxidant. Microarray data were obtained from GEO23806 and was provided by Schulte et al.46 Network shows connection between the four metabolites and 5-LO through number of known oncogenes (e.g., TNF, TGFβ) and oncosuppressors (P53), several with different expression in the two cell lines.

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CONCLUSIONS In this work we have tested the effect of 5-LO inhibitors on the metabolism of three types of glioblastoma cell lines. Metabolic profiling was performed on the lipophilic and hydrophilic extracts of cells with 1H NMR spectroscopy, followed by metabolite quantification. The addition of inhibitors leads to distinct changes in metabolic profiles in three cell lines. In cells expressing 5-LO, it was possible to observe changes in metabolism consistent with a switch to the 15-LO branch of AA metabolism. The analysis of cell lines that express 5-LO at lower levels has shown that inhibitors of the AA pathway still lead to metabolic changes in cells, possibly through their action as antioxidants or through inhibition of other enzymes. This analysis is a significant step toward a better understanding of 5LO’s role in cancer and also in furthering the application of NMR metabolomics in drug discovery and testing. Both ontarget and off-target effects can be observed with metabolomics making this technique a highly versatile approach for obtaining high throughput molecular data for drug testing.

formation of phosphocholine,35−37 therefore suggesting that phosphocholine levels in 5-LO inhibition are affected through TNF. Deregulated levels of TNF oncogene has an effect on other major proteins such as HIF1A38 and HDAC3, which in turn activates expression of 5-LO.39 5-LO is also related to the function of several caspases.40 Through the network of interacting proteins it is possible to relate 5-LO inhibition and observed concentration changes for phosphorylcholine, methionine, alanine, and succinate as well as other metabolites. Figure 9 compares transcript levels stemming from microarray studies performed on untreated Hs683 and A172 cells (where genes shown in blue are overexpressed in Hs683 cells and red in A172 cells).The inhibition of 5-LO will through these types of networks impact concentrations of a number of metabolites with major changes according to our measurement of a small subset of four metabolites shown in Figure 9. A positive relationship between 5-LO activity and phosphorylcholine is clear from the effect of 5-LO inhibitors, which lead to the reduction of concentration of phosphorylcholine likely through the deactivation of TNF. In the case of succinate we have observed increase in concentration following 5-LO inhibition possibly through the negative regulation by TNF that was previously suggested.41 Inhibition of 5-LO leads to downconcentration of alanine possibly through the negative regulation by TGFb1 indicated in the literature.42 Finally, methionine concentration increases with 5-LO inhibition possibly through indicated protein network. Detailed analysis of each of these relationships requires further experimentation. . From metabolic data obtained here as well as previously measured gene expression values in the three cell lines, it is possible to hypothesize a model of action for the inhibitors. 5LO and related enzymes are highly expressed in A172 cells, and thus treatment of these cells leads to 5-LO pathway inhibition

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ASSOCIATED CONTENT

S Supporting Information *

Supplementary Figures 1−4. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*(M.C.-C.) Tel: 506 861-0952. Fax: 506 851-3630. E-mail: [email protected]. (M.T.) Tel: 506 858-4493. Fax: 506 8584541. E-mail: [email protected]. Notes

The authors declare no competing financial interest. 2174



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ACKNOWLEDGMENTS P.J.M. is funded by the Beatrice Hunter Cancer Research Institute, the Brain Tumour Foundation of Canada, and the New Brunswick Health Research Foundation. Authors would like to thank M. Monette (Bruker Canada) for her help in setting up NMR experiments. M.T. acknowledges the contribution of the Canadian Foundation for Innovation (CFI), the New Brunswick Innovation Foundation (NBIF), New Brunswick Health Research Foundation, and Université de Moncton. M.T. would also like to acknowledge the support of the CFI for the funding of a portion of operating costs and maintenance for the NMR instrument through the Infrastructure Operating Fund (IOF). M.E.S. acknowledges support from the Canada Research Chairs Program.

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NMR Metabolomics Analysis of the Effects of 5-Lipoxygenase

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