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Leiden/Amsterdam Center for Drug Research, Divisions of Molecular Toxicology (S.M.v.L., J.K., N.P.E.V.) and Biomolecular Analysis (W.M.A.N., H.I.), Vrije Universiteit Amsterdam, The Netherlands; and Kiadis B.V., Groningen, The Netherlands (D.E.v.E., H.I.)
(Received March 29, 2006; accepted June 16, 2006)
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Abstract |
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) affinity assay. P450-derived metabolites of the SERMs were generated in the bioreactor, subsequently trapped on-line with solid phase extraction, and finally separated with gradient HPLC. Upon elution, the metabolites were screened on affinity for ER with an on-line HRS assay. With this HRS system, we were able to follow, in a time-dependent manner, the formation of ER-binding metabolites of tamoxifen and raloxifene. By analyzing the bioaffinity chromatograms with liquid chromatography-tandem mass spectrometry, structural information of the pharmacologically active metabolites was obtained as well. For tamoxifen, 15 active and 6 nonactive metabolites were observed, of which 5 were of primary, 10 of secondary, and 6 of an as yet unknown order of metabolism. Raloxifene was biotransformed in three primary and three secondary metabolites. MS/MS analysis revealed that three of the observed active metabolites of raloxifene were not described before. The present automated on-line HRS system coupled to a P450-containing bioreactor and an ER-affinity detector proved very efficient, sensitive, and selective in metabolic profiling of SERMs.
(ER) plays a crucial role in the development of breast cancer (Ali and Coombes, 2000
) and osteoporosis in postmenopausal women (Spelsberg et al., 1999). Therefore, selective estrogen receptor modulators (SERMs) are extensively used in treatment and prophylaxis of these disorders. Tamoxifen (TAM) is the most commonly used SERM in the treatment of postmenopausal, hormone-sensitive, advanced breast cancer. TAM can also halve the threat of breast cancer in women at high risk for this disorder (Morello et al., 2002; O'Regan and Jordan, 2002). Raloxifene (RAL), on the other hand, is generally used in the prevention of osteoporosis in postmenopausal women. A beneficial effect of the treatment with RAL is that it also reduces the risk of breast cancer (Martino et al., 2004). In addition, RAL has a protective effect on the cardiovascular system by reducing levels of low-density lipoprotein-cholesterol and homocysteine (Morello et al., 2002).
It is now well known that most SERMs, like other drugs and xenobiotics, are metabolized by membrane-bound cytochrome P450 enzymes (P450s) (Evans and Relling, 1999; Notley et al., 2002). For TAM it has been shown that P450s in endometrial tissue play a role in the formation of DNA-reactive -hydroxytamoxifen, possibly causing endometrial cancer (Sharma et al., 2003). RAL is metabolized by P450s into three possible quinones with alkylating properties toward macromolecules (Yu et al., 2004). Alternatively, both for TAM and RAL, it has been shown that their metabolites can also have affinity for ER (Lim et al., 1999; Fura, 2006). Biotransformation of both TAM and RAL is mainly catalyzed by CYP3A4 (Chen et al., 2002; Desta et al., 2004). Polymorphisms in P450s or drug-drug interactions at the level of P450s can cause altered pharmacological effects in humans (Ingelman-Sundberg and Rodriguez-Antona, 2005). Hence, efficient and sensitive screening methods for detection and identification of pharmacologically active metabolites are desirable.
Generation of metabolites and subsequent analysis of metabolite mixtures is usually performed by off-line incubation, extraction, and HPLC separation, coupled to various on- or off-line detection techniques. The methods used are usually based on time-consuming manual operations (Roy et al., 2005). However, we recently developed and validated a novel bioanalytical system which is based on the hyphenation of a small-scale (500 µl) P450-containing bioreactor to solid phase extraction (SPE) and gradient HPLC (van Liempd et al., 2005). This system proved very efficient in the formation, trapping, and separation of P450-generated metabolites. If this method could be combined with a postcolumn bioaffinity detection system, generated metabolites could be screened instantaneously on selected pharmacological properties. At present, there are several of these so called high-resolution screening (HRS) detection systems available. Recently, for example, a P450 inhibition and a phosphodiesterase inhibition HRS detection system were developed (Schenk et al., 2003; Kool et al., 2005). Both methods are based on enzymatic conversion of model substrates in highly fluorescent products. When this reaction is inhibited by substrates or inhibitors, less fluorescent product will be formed and a negative peak in the assay baseline is observed. For the present study, we made use of an HRS assay for the detection of ER-binding compounds (Oosterkamp et al., 1996; Schobel et al., 2001; Kool et al., 2006). This HRS bioaffinity assay is based on the increase of fluorescent signal of the tracer compound coumestrol upon binding to the ER ligand-binding domain. When coumestrol is displaced by a compound with ER affinity that elutes from the HPLC column, it is seen as a negative peak in the baseline of the bioassay.
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affinity of on-line generated metabolites of SERMs. Metabolites were generated in an adapted version of a recently developed on-line P450 bioreactor, coupled to SPE and gradient HPLC (van Liempd et al., 2005). For the biotransformation of TAM, easily available P450-containing pig liver microsomes were used. Especially CYP1A2, CYP3A4, and CYP2E1 activities of these microsomes show great resemblance to those in human liver (Zuber et al., 2002). For the biotransformation of RAL, phenobarbital (PB)-induced rat liver microsomes were used, because they contain high levels of CYP2A and 3A subtypes (Gokhale et al., 1997). By coupling the P450 bioreactor to an HRS ER affinity detection system, it is possible to screen the on-line metabolites for ER affinity in a postcolumn detection mode. By analyzing the detected active metabolites with LC-MS/MS, structural features of these metabolites could be resolved. |
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Biomaterials. P450 reaction buffer consisted of 100 mM potassium phosphate (pH = 7.4), 10 mM MgCl2, 16.0 mg/ml BSA, and 2 mM EDTA. The buffer used in the HRS ER affinity assay consisted of 10 mM KPi (pH = 7.4) and 150 mM NaCl (EB). The regenerating system (RS) for the P450 reaction contained 10 mM NADPH, 30 mM G6P, and 3 u/ml GDH dissolved in P450 reaction buffer. TAM and RAL were dissolved in 0.1% AA upon injection. Pig liver microsomes (LMs) were prepared as described by Kool et al. (2006) and contained 20 µM P450, as determined according to Omura and Sato (1964). PB-induced rat LMs were prepared according to the method of Yenes et al. (2004) and contained 11 µM P450. The ER ligand-binding domain (LBD) was produced with recombinant Escherichia coli BL21(DE3)-expressing His6-ER_LBD according to the method of Eiler et al. (2001). The concentration of ER_LBD was measured by determination of estradiol binding ability in a saturation radioligand binding assay described by Eiler et al. (2001) and yielded 250 nM.
SPE-HPLC-coupled P450 Bioreactor. Formation and separation of metabolites took place in a slightly modified model (Fig. 1) of a recently developed and validated on-line bioreactor, coupled to SPE and HPLC (van Liempd et al., 2005). All pumps used in the system were Knauer K-500 HPLC pumps. Injections were performed with a Gilson 234 autoinjector (50-µl injection loop) equipped with a Rheodyne six-port injection valve (Gilson, Villagers-le-Bel, France). Autoinjector, pumps, and switch valves were operated by ScreenControl software (Kiadis, Groningen, The Netherlands). The HPLC columns, SPE columns, and reaction coils were thermostated with a Shimadzu CTO-10AC column oven. Superloops were purchased from GE Healthcare (Roosendaal, The Netherlands). Knitted 1/16 inch x 0.75 mm polytetrafluoroethylene reaction coils, PEEK tubing, six-way dead-end switch valves and two-position six-port switch valves were obtained from VICI Jour (Amstelveen, The Netherlands). Flow splitters were made of 1/16 inch x 0.5 mm PEEK tubing with 50 µm i.d. x 375 µm o.d. fused silica inserts. Polyethersulfone (PES) 0.22-µm membrane filters were purchased from Sterlitech (Kent, WA). The filter was embedded between PEEK inserts with pore size of 150 µm to fixate the flexible PES membrane. Filter and inserts were enclosed by a PEEK filter holder, described in a preceding publication (van Liempd et al., 2005). The inserts and filter holder were manufactured in-house. SPE cartridges were prepared in-house. A slurry of 100 mg/ml SPE material in MeOH was prepared. SPE materials used were Luna C18(2) 10-µm (Bester, Amstelveen, The Netherlands), StrataX (Bester), and C8 Bakerbond (J. T. Baker, Deventer, The Netherlands). The slurry was transferred in a 10 x 3mm column by applying underpressure at the end of the column. The bottom was sealed with a 0.2-µm stainless steel screen. When the column was filled, the top was sealed with a similar screen.
Optimization of the P450 Bioreactor. Since different substrates were used in this bioreactor setup compared with the one previously developed (van Liempd et al., 2005), the reactor had to be revalidated. First, absorption of RAL and TAM to flow path components (tubing, reaction coil, filter unit) was evaluated. Therefore, the filter outlet was directly coupled to the UV detector. Next, the substrate (50 µl, 500 µM) or control was injected and mixed with P450 reaction buffer (without microsomes) in the reaction coil. The flow path was then emptied through the UV detector with water or with 0.1% (v/v) acetic acid. The obtained signals were subtracted from controls and compared with the signal obtained by direct injection of substrates in the detector. Subsequently, properties of various SPE materials were assessed. SPE materials were tested on breakthrough volumes with a method described previously (van Liempd et al., 2005). During separation, the SPE column is placed in series with the HPLC column; therefore, the effect of the SPE material on separation had to be determined. For this purpose, peak widths of substrate peaks were compared for different SPE materials, i.e., Strata-X, Luna C18(2) 10 µm, and C8 Bakerbond.
On-line Metabolite Formation and Separation. The SPE-HPLC-coupled P450 bioreactor can be divided into a P450 reactor unit and a chromatographic unit (Fig. 1). In the bioreactor unit, the actual P450 reaction takes place, whereas in the chromatographic unit, analytes are trapped and separated. For the present study, we applied a few alterations in both the bioreactor and the chromatographic unit. For the reactor unit, this included incorporation of three extra reaction coils with accompanying switch valve (SV2). In addition, in the chromatographic unit, three extra SPE cartridges, a switch valve (SV5), and an SPE wash pump (P4) were introduced.
In more detail, the bioreactor unit consisted of a pump (P1), switch valves (SV1–SV3), an autoinjector, reaction coils, a filter unit, and 50-ml superloops. A superloop (SL) is a hydraulic-driven syringe that can introduce various solutions in the system. SL 1 was filled with P450-containing microsomes and SL 2 contained RS. Both SL 1 and 2 were kept on ice. During filling of the reaction coil, the flow of P1 was split between the autoinjector, SL 1, and SL 2 in a 1:8:1 ratio. Control runs were carried out by blocking the RS flow by means of a manually operated switch valve (not indicated in Fig. 1) between SL 3 and the seven-way junction. The total reaction volume amounted to 500 µl. After incubation, analytes were applied to the SPE column with a degassed 0.1% AA solution from SL 4. All parts in the reactor unit were connected with 1/16 inch x 0.5 mm i.d. PEEK tubing.
The bioreactor and the chromatographic unit were separated by a filter unit containing a 0.22-µm polyethersulfone (PES) filter to remove microsomes that otherwise could clog the SPE and HPLC columns. After reconcentration of analytes on the SPE column, the filter unit and reaction coil were rinsed by a series of cleaning steps. First, the filter was back-flushed with water at a flow rate of 1 ml/min for 1 min, followed by a solution of 250 mM NaOH/0.5% SDS (SL 4) at the same flow rate for 1 min. Finally, the system was rinsed with water at a rate of 1 ml/min for 3 min, which proved to be sufficient for total removal of the washing solution (pH went back to 7).
Chromatography. Before HPLC separation, the SPE column, containing Luna C18(2) 10-µm particles, was washed with 2 ml of a 5% MeOH solution. Next, the compounds were separated in the chromatographic unit, which consists of gradient pumps (P2, P3), an SPE wash pump (P4), switch valves (SV4, SV5), SPE columns, and an HPLC column. For TAM and its P450-generated metabolites, a linear gradient from 50% MeOH to 90% MeOH in 40 min, constant for 20 min, and back to 30% MeOH in 10 min was applied. RAL and its metabolites were separated with a gradient from 30% MeOH to 80% MeOH in 40 min, constant for 20 min, and back to 30% MeOH in 10 min. For both gradients, organic and aqueous phases contained 10 mM ammonium acetate. All separations were carried out on a 150 x 4.6 mm i.d. Luna C18(2) column protected with a 2.0 x 5.0 mm i.d. C18 guard column (Phenomenex, Amstelveen, The Netherlands). The HPLC flow rate for all separations was 250 µl/min. After the HPLC column, the eluent was split in a 9 to 1 ratio to, respectively, an Agilent 1100 series UV detector (Agilent Technologies, Amstelveen, The Netherlands) and the on-line ER affinity assay. The UV detector was set to 280 nm when TAM was used as a substrate and to 254 nm when RAL was used. The HPLC column and SPE cartridges were thermostated at 37°C and 22°C, respectively. All parts in the chromatographic unit were connected with 1/16 inch x 0.13 mm i.d. PEEK tubing.
Reaction Conditions. For one reaction procedure with one control run and three reaction runs, the first coil (a) was filled only with microsomes and substrate (TAM or RAL) at a flow rate of 0.5 ml/min (Table 1). The other coils (b–d) were filled with microsomes, substrate, and RS. The final coil concentrations in the reaction runs with TAM were 50 µM TAM, 1.6% (v/v) pig LMs (360 nM), 1.0 mM NADPH, 3.0 mM G6P, and 0.3 u/ml GDH in a total volume of 500 µl. Coil concentrations for RAL incubations were 25 µM RAL and 8% (v/v) rat LMs (880 nM), whereas all the other components were kept the same as in TAM incubations. Reaction coils were thermostated at 37°C. Next, the coils were emptied one after another, starting with d and ending with a. The mixture in the reaction coils was applied to corresponding SPE columns (e.g., coil a to SPE column a) with 0.1% (v/v) AA from SL 4 at a flow rate of 1.0 ml/min. The injection and coil-emptying procedures were programmed such that incubation times in the different coils were 7, 15, and 24 min. When all coils were emptied on SPE columns, the trapped compounds were further separated on an HPLC column.
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HPLC and Mass Spectrometry. To identify metabolites, reaction or control mixtures were trapped on the SPE columns as described. Subsequently, the SPE columns were transferred to the LC-MS/MS setup and placed in front of the HPLC column. The same gradients were used as in the on-line ER affinity assay. For both TAM and RAL, MS was performed on an LCQ Deca mass spectrometer (Thermo Finnigan, Breda, The Netherlands) in full-scan (m/z 100–800) and positive electrospray ionization mode. The most abundant ion was selected for collision-induced dissociation (CID). Eluent from the HPLC column was sprayed into the mass spectrometer at +4.5 kV. The temperature of the heated capillary was set at 240°C; sheath and auxiliary gas flows were 10 and 50, respectively. A UV detector was placed in series with the MS. By aligning UV spectra obtained with the bioassay setup and those obtained before MS, masses could be appointed to compounds responsible to ER affinity signals.
Estrogen Receptor Affinity Assay. The present homogeneous ER affinity detection assay was performed according to the method of Kool et al. (2006). The ER affinity detection system is based on the competition of a fluorescent tracer compound (coumestrol) with HPLC-eluted compounds for the ligand-binding domain (LBD) of ER. When coumestrol is bound to the receptor, fluorescence is enhanced. When binding of coumestrol is decreased because of competition of an eluting ER ligand, fluorescence intensity decreases. This decrease is a measure of affinity of the ligand toward ER. A setup was used that consisted of makeup pumps (P5, P6), superloops (SL 5, 6), reaction coils (1/16 inch x 0.25 mm i.d., Tefzel), and an Agilent 1100 series fluorescence detector (Agilent Technologies) (Fig. 2). The HPLC eluent was split in a 1:10 ratio where one tenth of the flow (25 µl/min) was directed to the assay. In the four-way junction, this flow was combined with the ER solution (10 nM ER in EB, SL 5) flow of 150 µl/min and a makeup flow. One tenth of the total makeup flow was directed to the assay (135 µl/min). The makeup flow consisted of an opposite H2O/MeOH gradient compared with the HPLC gradient to keep the MeOH concentration in the assay constant at 15%. ER and eluted compounds were allowed to bind in the first reaction coil (25 µl). This mixture was combined with the flow of coumestrol solution (0.43 µM in EB, SL 6) of 150 µl/min. The final equilibrium between ER, ligand, and coumestrol was established in the second reaction coil (50 µl). Detection took place directly after the second coil with a fluorescent detector set to 
ex = 340 nm and em = 410 nm.
Data Analysis. For both substrates, three consecutive reaction procedures including HPLC separation and on-line ER affinity screening were performed to measure metabolite formation in time. Areas of negative peaks in the baselines of the ER affinity assay, caused by eluted, active metabolites and corresponding UV traces, were integrated with ACD/SpecManager 6.0 (Advanced Chemistry Development Inc., Toronto, ON, Canada). A signal-to-noise ratio threshold of >3 was applied for appointing negative peaks. For obtaining the relative ER affinity, all integrated areas of all ER affinity traces were expressed as a percentage of the largest area (parent compound excluded). Relative affinities of corresponding signals were averaged and relative standard deviations (RSDs) were calculated with Prism 3.0 (GraphPad Software Inc., San Diego, CA). Deviations of ER affinity signals after 24-min incubations from controls were checked on significance with a two-tailed t test. LC-MS data of the metabolites were processed with Xcalibur/Qual Browser v 1.2 (Thermo Finnigan).
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affinity. To that end, two recently developed and validated methodologies, i.e., an on-line bioreactor (van Liempd et al., 2005) (Fig. 1) and an on-line ER affinity bioassay (Oosterkamp et al., 1996) (Fig. 2), were combined into one hyphenated system. The metabolites generated in the multicoil P450-bioreactor could be trapped on-line with a SPE unit and separated with gradient HPLC. Subsequently, the separated metabolites were screened for ER affinity with the on-line ER affinity bioassay. Overall, this approach resulted in the generation and detection of 15 ER-binding and 6 nonbinding metabolites for TAM (Fig. 3). Moreover, the multicoil P450-containing bioreactor was able to produce metabolites of RAL or TAM in a time-dependent way (Fig. 5). For RAL, six binding and two nonbinding metabolites were detected (Fig. 4). The concentration of all metabolites of both TAM and RAL increased in time except for metabolites TM6 and TM15, which decreased after 7 min of incubation. The m/z values of most metabolites formed could be determined by analyzing the SPE-trapped compounds with mass spectrometry. For identification, subsequent MS-MS spectra provided further information about the structure of the metabolites (see below).
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), where HPLC gradients of 70 min were applied. The newly developed bio-reactor system with multiple reaction coils and multiple SPE units was optimized for two SERM substrates. To that end, we tried to diminish adsorption of substrates and metabolites to flow path components of the bioreactor and the SPE unit as much as possible. Flow path flushing with MilliQ water only resulted in a recovery of 75% for both TAM and RAL, whereas flushing with 0.1% (v/v) acetic acid resulted in a recovery of >99% of both substrates (data not shown). During reaction coil flushing in the presence of liver microsomes, the pressure over the filter increased from 0 to 10 bars when a 2% (v/v) pig LM solution was used and from 0 to 20 bars when a 10% (v/v) rat LM solution was used. When the filter membrane was cleaned with MilliQ water and NaOH/SDS solution, the pressure returned to normal. Evaluation of SPE materials showed that all materials tested, i.e., Luna C18(2), C8 Bakerbond, and Strata-X, were able to trap both TAM and RAL (50 µl, 500 µM) and could trap both substrates completely. However, only Luna C18(2) 10-µm material did not alter peak widths during HPLC separation when compared with the same separation without SPE column. The use of other SPE materials resulted in wider peaks for TAM and RAL, i.e., 1.6 times for Strata-X and 1.9 times for C8 Bakerbond.
After the optimization, the SPE-HPLC combination coupled to the P450-bioreactor could be used for the metabolic conversion of the two substrates. This resulted in the generation of 21 metabolites of TAM and 7 for RAL. Besides the unchanged substrates, many metabolites with affinity for ER were eluting from the HPLC column and causing negative peaks in the baseline of the ER affinity trace (Figs. 3B and 4B). Tamoxifen was metabolized by pig LMs in 15 ER-binding metabolites (TM1–TM15, Fig. 3) and 6 non-ER-binding metabolites (TM16–TM20). Relative ER affinity progress curves showed that the formation of ER-binding metabolites was time-dependent (Fig. 5). We arbitrarily distinguished ER-binding metabolites in highly active (TM6, TM8, TM11, TM12, and TM13, Fig. 5A), moderately active (TM5, TM9, TM10, and TM14, Fig. 5B) and low active metabolites (TM1–TM4, TM7, and TM15, Fig. 5C) according to their relative affinity for ER after 24 min of incubation in the bioreactor. Relative ER affinities for the strong binding metabolites varied from 97 ± 5% for TM11 to 15 ± 4% for TM12. The four moderately active metabolites showed affinities varying from 8.4 ± 1.4% to 5.6 ± 3.0%. The low active metabolites possessed activities from 4.0 ± 1.2% to as little as 1.6 ± 0.9%. When the five TAM metabolites with high relative ER affinities were taken into account, the total RSD of the data points amounted to 28%. For metabolites with moderate ER affinity, a RSD of 37% was calculated, whereas for slightly active metabolites, the RSD was 43%. After 24 min of incubation of TAM with pig LMs, all active metabolites showed a significant rise in activity compared with control incubations (p < 0.05). Moreover, from the relative ER affinity progress curves (Fig. 5), upward trends of ER affinity in time, indicative of increasing production of active metabolites, were obvious. Biotransformation of RAL by rat LMs resulted in the formation of six active metabolites (RM1–RM6) and one nonactive metabolite (RM7) (Fig. 3B). The pooled RSD of all six active RAL metabolites was 18%. Again, upward trends in the formation of ER-binding metabolites were evident (Fig. 5D).
Identification of Tamoxifen and Raloxifene Metabolites. In Fig. 6, a provisional scheme of the metabolism of TAM by P450 enzymes is presented. Not all TAM metabolites detected by UV and the ER affinity assay were detected by LC-electrospray ionization-MS. The minor metabolites TM1 to TM4, TM6, and TM7 were all visible on the ER affinity traces but could not be detected with LC-MS. Masses of the protonated molecules of metabolites TM5, TM8 to TM21 were subsequently determined by LC-MS (Table 2). Structural properties of the TAM metabolites formed based on CID mass spectra are discussed in the next section. The ER-binding metabolite TM5 is a dihydroxylated secondary metabolite, as is indicated by the m/z value of 404. The m/z value of 374 for ER-binding metabolites TM8, TM9, and TM10 indicates a secondary oxygenated N-desmethyl species. The ER-binding metabolites TM11, TM12, TM14, and TM15 were identified as primary monohydroxy-TAM metabolites according to a protonated molecule with m/z 388. Based on m/z 358, TM13 was identified as a primary N-desmethyl-TAM metabolite that also showed significant binding to ER. TM16 to TM19 were all identified as dihydroxy-TAM metabolites, which, however, did not show any traceable affinity in the ER affinity assay. The protonated molecule at m/z 374 for TM20 was assigned to an oxygenated N-desmethyl metabolite. According to the protonated molecule mass of 402, TM21 was a quinone. In Fig. 7 the metabolic scheme of the metabolism of RAL by rat LMs is depicted. We were able to measure protonated molecule masses from six ER-binding and one non-ER-binding metabolite of RAL. The first three metabolites eluting (RM1–RM3), are all dihydroxy-RAL species according to the protonated molecules at m/z 506. RM4 to RM6 at m/z 480 are primary, monohydroxylated RAL metabolites. The protonated molecule at m/z 472 implies that RM7 is probably one of the two quinones recently described in the literature (Yu et al., 2004).
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affinity of P450-generated metabolites of SERMs. The P450-bioreactor on-line, coupled to SPE-HPLC, enabled us to generate and swiftly trap and separate a substantial amount of P450-generated metabolites of both TAM and RAL. The metabolites were trapped very efficiently on SPE columns and, isolated from air and light, they stayed protected from oxidation or UV degradation. In addition, because the incubation of the drugs took place before HPLC runs, microsomes were directly used, which reduced degradation of P450 enzymes to a minimum. P450 enzymes are known to degrade to some extent, even when stored on ice (Yamazaki et al., 1997). For the detection of ER-binding metabolites, we made use of a previously developed and optimized on-line HRS ER affinity assay. Displacement of coumestrol from the ER ligand-binding domain results in a decreased fluorescence intensity of coumestrol (Oosterkamp et al., 1996; Schobel et al., 2001). From the HPLC column eluting TAM and RAL, metabolites with affinity for the ER caused clear and reproducible negative peaks in the baseline of the bioaffinity trace (Figs. 3B and 4B). The peak height depends on the concentration of the eluting compound and its ER affinity. According to the upward trends in the ER progress curves (Fig. 5, A–C), TAM was metabolized in a time-dependent manner by pig liver microsomes in 15 ER-binding metabolites (Fig. 3B). The ER affinity detection system proved to be very sensitive, according to the response signals of TM1 to TM4, TM6, and TM7, since these metabolites were only detected by their ER affinity response and not by UV. The high relative standard deviations of the ER affinity signals with these low and moderate ER-binding metabolites can be explained by the fact that variations between ER affinity signals tend to increase when the respective bioaffinity signals are decreasing (Fig. 5, B and C). When bioaffinity signals approach the lowest level of detection, noise is obviously becoming a prominent factor, leading to increased standard deviations and, as a consequence, higher RSDs. Biotransformation of RAL in the P450-bioreactor by rat liver microsomes resulted in the formation of six ER-binding metabolites (RM1–RM6, Fig. 4B). Again, upward trends in the formation of ER-binding metabolites were evident (Fig. 5D). Consequently, the present bioanalytical method is useful not only for the screening and identification of individual metabolites in mixtures, but also for measuring the time-dependent formation of P450-generated ER-binding metabolites of compounds like TAM and RAL.
Metabolic Profiling of Tamoxifen. Interpretation of the MS-MS spectra of the metabolites was performed using the profile group concept proposed by Kerns et al. (Mayol et al., 1994). Of the 21 TAM metabolites observed, 5 were identified as primary metabolites (TM11–TM15) (Table 2; Fig. 6). Leveling of ER affinity progress curves (Fig. 5) can be explained by primary metabolites reaching steady-state conditions as they are further metabolized into secondary metabolites. The primary metabolite, TM13, was identified as N-desmethyl-TAM which, in humans, is catalyzed by CYP3A4 (Desta et al., 2004). On the basis of UV data (not shown) it appeared to be the most abundant metabolite of TAM. According to their MS-MS spectra TM11 and TM12 were monohydroxylated on the aromatic 3- or 4-position (Table 2; Fig. 6) which are known to be catalyzed in humans by CYP3A4 (3-position) or CYP2D6 (4-position) (Crewe et al., 2002; Desta et al., 2004). TM11 and TM12 are the second most abundant metabolites according to UV data. Considering the high relative affinity of TM11 for ER, this metabolite is likely to be 4-hydroxy-TAM since previous studies showed that this metabolite of TAM is 30 to 100 times more potent than TAM itself (Fura, 2006). The CID mass spectrum of TM14 did not provide structural information. TM15 was identified as TAM-N-oxide by its MS-MS spectrum (Table 2; Fig. 6) and is mainly formed by flavin-containing monooxygenases (Mani et al., 1993). The abundance of this metabolite was comparable to that of TM12; however, its ER affinity was very low (Figs. 3 and 5). The decreasing slope of its ER affinity progress curve can be explained by reduction of the N-oxide by P450 enzymes, which is in line with the suggestion that N-oxide-TAM is a storage form of TAM in vivo (Mani et al., 1993).
Several primary metabolites of TAM are further metabolized into the secondary metabolites TM5, TM8 to TM10, and TM16 to TM21. The MS-MS spectrum of the dihydroxylated metabolite TM5 revealed hydroxylation in the a-ring and b-ring of TAM (Table 2; Fig. 6A), respectively, yielding 4 (or 3), 4' (or 3')-dihydroxy-TAM. TM5 probably originates from TM11/TM12 and is catalyzed in humans by CYP3A (Desta et al., 2004). The MS-MS spectra of the oxygenated N-desmethyl metabolites TM8 and TM10 point to hydroxylation either in the a-ring of TAM (3- or 4-position) or on the -position of the ethylene moiety. Since the amount of TM8 formed is 150 times as low as TAM, whereas its relative ER affinity is high, this metabolite is most likely endoxifen, which is known to be as potent as 4-hydroxy-TAM (Johnson et al., 2004). The MS-MS spectrum of TM9 did not provide additional structural information. The CID spectrum of the dihydroxylated metabolite TM17 suggested that besides the ethyl moiety, the c-ring or ether linkage (e) in TAM is also hydroxylated, which is an observation hitherto not described. CID spectra of the dihydroxylated metabolites TM16, TM18, and TM20 did not reveal the positions of the hydroxyl group introduced. For the dihydroxylated metabolite TM19, we could identify hydroxylation of the ethyl moiety (d). The MS-MS spectrum of TM21 suggested that this metabolite is a diquinone of TAM, a species also known to be produced by P450s (Fan and Bolton, 2001). Finally, the fast elution times of the ER-binding metabolites at the beginning of the chromatogram (TM1–TM4) indicate that these are most likely tertiary metabolites. Introduction of additional hydroxyl groups or cleavage of methyl groups increase polarity and therefore shorten retention times in reversed phase chromatography.
To unambiguously substantiate the suggested structures of TAM metabolites, additional experiments should be carried out. For example, standards of the suggested metabolites should be synthesized and their retention times and MS-MS spectra could be compared with those obtained with the present bioanalytical system. Furthermore, preparative HPLC and subsequent NMR analysis of the metabolites could provide more definite structural information.
Metabolic Profiling of Raloxifene. The metabolic profile of RAL is less complex than that of TAM. Only four primary and three secondary metabolites were observed when incubated with rat liver microsomes (Fig. 7). Formation of several ER-binding metabolites showed clear upward trends according to Fig. 5D. Interpretation of the MS-MS spectra of the monohydroxylated RAL metabolites RM4 and RM5 lead to the conclusion that hydroxyl groups were introduced in either the a- or b-ring of RAL, as expected, upon biotransformation by P450s (Lim et al., 1999) (Table 3; Fig. 7). The fragments at m/z 405 and 269 suggest that RM6 is hydroxylated on the aromatic c-ring. This metabolite has not yet been described previously, despite the fact that P450s are very well capable of hydroxylating aromatic moieties. MS-MS spectra of the dihydroxy-RAL species RM2 and RM3 also provided structural information. For RM2, fragments at m/z 363 and 269 point to hydroxylation in the piperidinic d-ring (Fig. 7) and aromatic c-ring. The m/z 389, 269, and especially m/z 144 fragments of RM3 strongly indicate that the d-ring is dihydroxylated. Both RM2 and RM3 have not yet been described in the literature. The ion at m/z 472 implies that RM7 is likely one of the two quinine-metabolites recently described in the literature (Yu et al., 2004). Interestingly, except for the diquinone, all observed metabolites show significant ER affinity, which may have consequences for the in vivo effect of RAL. Additional experiments should be performed to find definite proof.
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affinity assay. The system was validated with the two clinically used SERMs as model compounds, namely, tamoxifen and raloxifene. The present bioanalytical method was able to provide simultaneously information about the time-dependent formation as well as about the ER affinity of P450-generated metabolites of TAM and RAL. For TAM, we were able to identify 15 ER-binding metabolites and 6 non-ER-binding metabolites varying from trace amounts of tertiary metabolites to major primary ones. Among the ER-binding metabolites, we identified 4-hydroxy-TAM, N-oxide-TAM, N-desmethyl-TAM, and the recently characterized, very potent endoxifen. We also could identify potentially carcinogenic -hydroxy-TAM species. By analyzing RAL with the presented sytem, we were able to identify six ER-binding metabolites, of which there were three novel ones and one nonbinding metabolite. These RAL metabolites include species that are hydroxylated on the piperidine ring. Overall, biotransformation of the SERMs analyzed yields a very complex profile of ER-binding and non-ER-binding metabolites which might have considerable consequences for the pharmacological properties of these drugs. The hyphenated and fully automated bioanalytical system presented here could be very useful for elucidation of convoluted metabolic profiles and. by inference, could become a novel tool in active metabolite screening, e.g., for the purpose of drug discovery and development and for safety assessment research. |
Acknowledgments |
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affinity detector were kindly provided by Kiadis B.V. (Groningen, The Netherlands). The ER LBD expressing E. coli cells were a kind gift of Dr. Marc Ruff and Dr. Dino Moras. |
Footnotes |
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Article, publication date, and citation information can be found at http://dmd.aspetjournals.org.
ABBREVIATIONS: ER, estrogen receptor ; P450, cytochrome P450 enzyme; HRS, high resolution screening, PES, polyethersulfone; RAL, raloxifene; SERM, selective estrogen receptor modulator; SPE, solid phase extraction; TAM, tamoxifen; HPLC, high-performance liquid chromatography; PB, phenobarbital; LC-MS, liquid chromatography-mass spectrometry; MS/MS, tandem mass spectrometry; G6P, glucose 6-phospate; GDH, glucose-6-phosphate dehydrogenase; AA, amino acid; EB, 10 mM KPi (pH = 7.4) and 150 mM NaCl; RS, regenerating system; LM, liver microsome; LBD, ligand-binding domain; PEEK, polyetheretherketone; MeOH, methanol; SL, superloop; CID, collision-induced dissociation; RSD, relative standard deviation; TIC, total ion chromatogram.
Address correspondence to: Prof. Dr. N. P. E. Vermeulen, LACDR-Section of Molecular Toxicology, Department of Chemistry and Pharmacochemistry, Vrije Universiteit, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. E-mail: npe.vermeulen{at}few.vu.nl
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