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Vol. 293, Issue 3, 761-770, June 2000
College of Pharmacy, Ohio State University, Columbus, Ohio
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Abstract |
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The intracellular pharmacokinetics of paclitaxel is closely related to its pharmacodynamics. Although drug transport across the cell membrane and extracellular and intracellular drug binding have been shown to affect intracellular drug accumulation, their quantitative relationship is unknown. This study was designed to establish a mathematical model for computing the intracellular paclitaxel pharmacokinetics. As a starting point, the model assumes drug transport into and out of cells via passive diffusion. Experimental data on the intracellular pharmacokinetics of [3H]paclitaxel were obtained using monolayer cultures of human breast MCF7 tumor cells, which have negligible expression of the mdr1 P-glycoprotein. The results indicate that, in addition to drug binding and microtubule concentration, changes in cell number due to cell growth and drug effects also affected intracellular drug accumulation. A kinetic model was developed to describe several concomitant processes: 1) saturable drug binding to extracellular proteins, 2) saturable and nonsaturable drug binding to intracellular components, 3) time- and concentration-dependent drug depletion from culture medium, 4) cell density-dependent drug accumulation, and 5) time- and drug concentration-dependent enhancement of tubulin concentration. The model was validated by the close prediction (<7% deviation) of the effects of extracellular-to-intracellular concentration gradient and cell density on the kinetics of drug accumulation and efflux. This model was used to predict the effects of changing several parameters (number and binding affinity of intracellular binding sites, free fraction, and concentration of drug in extracellular fluid) on intracellular drug accumulation. In conclusion, the computational model of intracellular paclitaxel pharmacokinetics provides the means to predict drug concentration in cells.
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Introduction |
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Paclitaxel,
one of the most important anticancer drugs developed in the past two
decades, is active against multiple types of human solid tumors
(Rowinsky, 1993
). Paclitaxel enhances tubulin polymerization, promotes
microtubule assembly, binds to microtubules, stabilizes microtubule
dynamics, induces mitotic block at the metaphase/anaphase transition,
and induces apoptosis (Parness and Horwitz, 1981
; Manfredi et al.,
1982
; Jordan et al., 1993
, 1996
; Derry et al., 1995
). The intracellular
concentration of paclitaxel is critical for its pharmacological effect.
Drug resistance in several resistant sublines is correlated with
reduced intracellular drug accumulation compared with the sensitive
parent cell lines (Lopes et al., 1993
; Bhalla et al., 1994
; Jekunen et
al., 1994
; Riou et al., 1994
; Speicher et al., 1994
).
One of the challenges regarding the clinical use of paclitaxel is
the identification of optimal treatment schedules; multiple treatment
schedules with different infusion duration (1, 3, 24, and 96 h)
and different treatment frequency (daily, weekly, and every 3 weeks)
are under evaluation in patients. The difficulty is in part due to the
lack of a precise understanding of the pharmacodynamics of paclitaxel,
i.e., drug effect as a function of drug concentration and treatment
duration. For example, the importance of treatment duration on the
antitumor effect of paclitaxel has been controversial; some studies in
cultured cells indicate that prolonging the treatment duration did not
enhance the drug effect (Cohen and Duke, 1984
; Roberts et al., 1990
),
whereas other studies indicate the opposite (Rowinsky et al., 1988
;
Liebmann et al., 1993
; Lopes et al., 1993
; Milas et al., 1995
). We have
shown that this controversy is likely due to the delayed cytotoxicity
of paclitaxel that is exhibited after termination of treatment. The
delayed effect is due in part to the slow manifestation of apoptosis
and in part to the slow release of paclitaxel from its intracellular
binding sites (Au et al., 1998
). These findings indicate that
the elucidation of paclitaxel pharmacodynamics requires a better
understanding of its intracellular pharmacokinetics on a quantitative
level. For example, the intracellular drug concentration-time profile
is needed to predict the drug effect at various time intervals during and after drug administration.
Several laboratories, including ours, have studied various aspects of
intracellular pharmacokinetics of paclitaxel in cultured cells, such as
the binding of paclitaxel to extracellular and intracellular
macromolecules (Manfredi et al., 1982
; Jordan et al., 1993
; Song et
al., 1996
) and the effect of overexpression of the multidrug resistance
of P-glycoprotein (Pgp) on drug efflux (Bhalla et al., 1994
; Speicher
et al., 1994
). Although these studies have led to a better
understanding of the determinants of intracellular paclitaxel
pharmacokinetics on a conceptual level, they do not provide the means
to depict quantitatively how changes in these determinants will alter
intracellular pharmacokinetics. For example, it is known that: 1)
changes in tubulins alter drug binding and accumulation in cells (Haber
et al., 1995
; Dumontet et al., 1996
; Dumontet and Sikic, 1999
); 2) the
presence of Cremophor micelles decreases the free fraction of
paclitaxel available to enter cells (Knemeyer et al., 1998
); and 3)
displacement of paclitaxel from plasma protein binding sites by other
highly protein-bound drugs such as cisplatin increases the free
fraction. However, because the quantitative relationship between these
determinants and intracellular drug accumulation is unknown, it is not
possible to design treatment schedules to accommodate changes in the determinants.
The goal of this study was to establish a computational model of
intracellular paclitaxel pharmacokinetics that could be used to
quantify the relative importance of various determinants. As a first
study, the model was developed for a system where drug efflux does not
involve active drug transport by the Pgp efflux pump, and the required
experimental data were obtained using human breast adenocarcinoma MCF7
cells, which have negligible Pgp expression (Fairchild et al., 1990
; Li
et al., 1998
).
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Materials and Methods |
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Chemicals and Reagents.
Paclitaxel was a gift from
Bristol-Myers Squibb Co. (Wallingford, CT) and the National Cancer
Institute (Bethesda, MD); 3"-[3H]paclitaxel
(specific activity, 19.3 Ci/mmol) from the National Cancer Institute;
and PSC833 from Novartis Inc. (Summit, NJ). 7-Epitaxol was purchased
from Hauser Chemicals (Boulder, CO); cefotaxime sodium from
Hoechst-Roussel (Somerville, NJ); gentamicin from Solo Pak Laboratories
(Franklin Park, IL); all other cell culture supplies including Versene
from Life Technologies (Grand Island, NY); Solvable tissue gel
solubilizer and Atomlight scintillation fluid from DuPont Biotechnology
Systems (Boston, MA); and all other chemicals and
-tubulin
monoclonal antibody from Sigma (St. Louis, MO). All chemicals
and reagents were used as received. 7-Epitaxol was >99.2% pure, as
determined by high pressure liquid chromatographic (HPLC) analysis.
Cell Culture. Human breast MCF7 tumor cells were a gift from Dr. Kenneth Cowan (National Cancer Institute). Cells were maintained in RPMI-1640, supplemented with 9% heat-inactivated fetal bovine serum, 2 mM glutamine, 90 µg/ml gentamicin, and 90 µg/ml cefotaxime sodium, in a humidified atmosphere at 37°C and 5% CO2. For experiments, cells were harvested from subconfluent cultures using trypsin and resuspended in fresh medium before plating. Cells with greater than 90% viability, as determined by trypan blue exclusion, were used. The doubling time of MCF7 cells, during the exponential growth phase, was 24 h.
Cell Volume Measurement.
The volume of MCF7 cells in
the exponential growth phase was determined using the Samba Image
Analyzer 4000 (Imaging Products International, Inc., Chantilly, VA).
Because the drug-induced reorganization of microtubules has no effect
on cell volume (Brown et al., 1985
; Mills, 1987
), cell volume was
determined using untreated cells. Cells were harvested with trypsin,
stained with toluidine blue (0.2% in 10% methanol), and diluted with
PBS. The Samba 4000 quantified the distance as the number of pixels,
i.e., 164 pixels per 200× microscopic field. The maximum
(L) and minimum (W) diameters of a cell, which
were determined by counting the number of pixels and converting the
value to micrometers, were used to calculate the cell volume. Equation 1 describes the calculation of the volume (V) of ellipsoid
cells. MCF7 cells in the log growth phase showed an average volume of
2.09 ± 0.431 µl/106 cells (mean ± S.D.; n = 232; median, 2.11 µl).
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(1) |
Uptake and Efflux of Paclitaxel.
Cells were plated at
densities of 105 to 106
cells/well in 1 ml of culture medium in six-well plates. One day after
seeding, the medium was replaced with 1 ml of medium containing
[3H]paclitaxel. Nonradiolabeled paclitaxel was
added when necessary. The final specific activity of
[3H]paclitaxel ranged from 0.04 to 19.3 Ci/mmol. Drug uptake experiments used drug concentrations (total
concentration) that are within the therapeutic range of 1 to 5000 nM
(Kearns et al., 1995
). To determine drug efflux, cells were treated
with 10 nM [3H]paclitaxel for 24 h, then
washed twice with 1 ml of ice-cold drug-free medium, followed by
incubation in drug-free medium with agitation every 15 min for 2 h
and every hour thereafter. For both uptake and efflux studies, aliquots
(100 µl) of medium were removed at predetermined times. After the
remaining medium was aspirated, cells were washed twice with 0.25 ml of
ice-cold Versene and then harvested as a suspension after
trypsinization. Cell number was measured by hemocytometer or by
Coulter Counter (Coulter Electronics Inc., Hialeah, FL) after a 20-fold
dilution with Isotone (Coulter Electronics Inc.). Samples
were dissolved in 0.5 ml of Solvable tissue gel solubilizer, mixed
with 10 ml of Atomlight, and processed by liquid scintillation counting.
Sample Extraction and Analysis.
Paclitaxel and its
reversible epimerization product, 7-epitaxol, were extracted using
ethyl acetate and ammonium acetate buffer (0.01 M, pH 5.0). The latter
was added to minimize epimerization (Leslie et al., 1993
). The organic
extract was evaporated to dryness. After being reconstituted with 16%
acetonitrile in ammonium acetate, the sample was loaded on BondElut CN
solid-liquid phase extraction cartridges (Varian, Harbor City, CA)
pre-equilibrated sequentially with 2 ml of acetonitrile, 2 ml of
methanol, and 3 ml of ammonium acetate buffer. After being washed with
2 ml of ammonium acetate buffer and 2 ml of 25% acetonitrile in the
same buffer, the analytes were eluted with 70% acetonitrile in water.
The eluent was evaporated to dryness and reconstituted in the HPLC
mobile phase (49% acetonitrile in water). The extraction recovery was
>90% for both culture medium and cell samples. An aliquot was
analyzed by HPLC using a reversed phase µBondapak C18 column (Waters
Association, Milford, MA) and UV absorbance at 229 nm. The flow rate of
the mobile phase was 1 ml/min, and the retention times for paclitaxel
and 7-epitaxol were 13.6 and 21.9 min, respectively. More than 95% of
the radioactivity recovered in the HPLC-eluting fractions corresponded
to paclitaxel and 7-epitaxol. 7-Epitaxol accounted for less than 10%
of the total radioactivity at 4 h. Because paclitaxel and
7-epitaxol together accounted for almost all of the recovered
radioactivity and because paclitaxel and 7-epitaxol are
pharmacologically equivalent, with identical microtubules binding
affinity and cytotoxicity (Ringel and Horwitz, 1987
), the total
recovered radioactivity was considered equivalent to paclitaxel without
further correction in subsequent studies.
Confirmation of Negligible Pgp-Mediated Paclitaxel Efflux in MCF7
Cells.
The MCF7 cells used in this study are known to have
negligible Pgp expression (Fairchild et al., 1990
). A separate study
using Western blot analysis confirmed that the Pgp level in these cells was barely detectable (Li et al., 1998
). To determine whether Pgp-mediated efflux significantly contributed to the efflux of paclitaxel, we compared the intracellular concentration-time profiles in the absence or presence of a known Pgp inhibitor, PSC833 (Boesch et
al., 1991
). A preliminary study showed that PSC833, at 0.5, 1, and 5 µg/ml, did not affect the growth of MCF7 cells for at least 2 days.
Subsequent studies used 1 µg/ml PSC833. In the uptake study, PSC833
was administered with paclitaxel. In the efflux study, cells were first
treated with paclitaxel for 24 h; the paclitaxel-loaded cells were
then placed in PSC833-containing medium.
Analysis of Total and Polymerized Tubulin.
Total (free plus
polymerized) and polymerized tubulin were analyzed as previously
described (Thrower et al., 1991
), with the exception that cells were
lysed by four to five cycles of freezing, thawing, and vortexing. More
than 90% of the cells were lysed, as indicated by the uptake of trypan
blue dye. Tubulin was analyzed by an enzyme-linked immunoadsorbent
assay using a monoclonal antibody to
-tubulin (IgG, Tub2.1). Bovine
brain tubulin was used as the tubulin standard due to the
unavailability of human tubulin. Hence, we were not able to determine
the absolute concentration/amount of tubulin in human cells.
Accordingly, changes in the tubulin concentration/amount were reported
as changes relative to the control value.
Model Development.
We constructed an intracellular
pharmacokinetic model to describe the factors that determine the
kinetics of paclitaxel uptake, binding, and efflux from cells. The
model included: 1) saturable binding of paclitaxel to proteins in the
extracellular compartment (Song et al., 1996
), 2) saturable and
nonsaturable binding of paclitaxel to cellular components (Manfredi et
al., 1982
), 3) time- and concentration-dependent changes in microtubule
mass (Jordan et al., 1993
; Derry et al., 1995
), and 4) time- and
concentration-dependent changes in cell number (see
Results). We assumed that a) drug uptake is by passive
diffusion because sodium azide treatment, which depletes ATP, has
minimal effect on intracellular drug accumulation (Manfredi et al.,
1982
); b) drug efflux is by passive diffusion because Pgp-mediated drug
efflux was insignificant in MCF7 cells (see Results); and c)
only free drug participates in the uptake and efflux processes.
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(2) |
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(3) |
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(4) |
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(5) |
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(6) |
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(7) |
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(8) |
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(9) |
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Ctotal,m and B = (1 + NSB) · Kd,c + Bmax,c,initial · (1 + kBmax,c · t)
Ctotal,c.
Equations 8 and 9 were used with the numerical integration
method of WINNONLIN (SCI Software, Lexington, KY) to simulate the intracellular and extracellular drug concentration-time profiles.
Determination of Model Parameters.
Several model parameters
were determined experimentally, as follows:
Bmax,m and
Kd,m were determined by analyzing our
previously published data on paclitaxel binding to proteins in cell
culture medium (Song et al., 1996
) using eq. 5;
kcell number was calculated for each
initial Ctotal,m as the slope of the log-linear
plot of [cell number] versus [time]; and
kBmax,c was calculated for each
initial Ctotal,m as the slope of the plot of
[concentration of total tubulin] versus [time].
Validation of the Kinetic Model. The intracellular pharmacokinetic model was used to predict the effect of cell density on drug accumulation and the effect of the intracellular-to-extracellular concentration gradient on drug efflux. The model-predicted data were then compared with experimental results to evaluate the validity of the model.
Application of Intracellular Pharmacokinetic Model. The intracellular pharmacokinetic model was used to demonstrate the effects of changing several parameters (i.e., number and dissociation constant of intracellular binding sites, free fraction of drug in extracellular fluid, and extracellular drug concentrations) on intracellular drug concentrations. These simulations were accomplished by altering the values of Bmax,c, Kd,c, Bmax,m-to-Kd,c ratio, and initial Ctotal,m, respectively. Simulations were conducted for initial cell density of 106 cells/ml of medium volume.
Computer Simulation. For model fitting and simulations, we used WINNONLIN with 1/concentration as the weight.
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Results |
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Verification of Model Assumption.
Paclitaxel is a substrate
for Pgp but not for multidrug resistance-associated protein,
another drug efflux membrane protein (Breuninger et al., 1995
). The
assumption of a negligible Pgp-mediated drug transport in MCF7 cells
was verified with an inhibitor study. Treatment of MCF7 cells with the
Pgp inhibitor PSC833 at 1 µg/ml did not alter the intracellular
accumulation of paclitaxel. For the control and the PSC833-treated
cells, the areas under the intracellular concentration-time profiles
were 79 ± 8 and 84 ± 7 µM · h, respectively
(mean ± S.D., n = 3). A separate study showed
that PSC833 at this concentration completely inhibited the Pgp-mediated
efflux in the mdr1-transfected subline of the MCF7 cells
(i.e., BC19 cells), which showed a 9-fold higher Pgp expression and
60% lower drug accumulation (Jang et al., 1998
; Li et al., 1998
).
These data rule out significant Pgp-mediated efflux and support the
assumption that paclitaxel is removed from MCF7 cells by passive diffusion.
Kinetics of Paclitaxel Accumulation and Binding.
Figure
1 shows the kinetics of paclitaxel
accumulation in MCF7 cells. The extensive drug accumulation in cells,
indicated by the high intracellular-to-extracellular concentration
ratios (Table 1), resulted in significant
depletion of paclitaxel from the medium, i.e., >70% depletion at 1 and 10 nM and ~40% depletion at 1000 nM. The depletion occurred even
though the volume of the drug-containing medium was more than 500 times
the cell volume, a condition that is commonly used in cell culture
studies. The intracellular concentration increased with time and
approached plateau levels between 1 and 4 h, with the longest time
to reach plateau levels at the lowest extracellular concentration. The intracellular-to-extracellular concentration ratio at 4 h
decreased 13-fold when the extracellular concentration increased from 1 to 1000 nM. However, when the extracellular concentration was further
elevated to 2000 and 5000 nM, the intracellular-to-extracellular concentration ratio remained relatively constant at ~75. As shown below, these concentration-dependent changes in concentration ratios
are due to the saturation of the saturable binding sites at higher
extracellular drug concentrations and to the linear increase of
nonsaturable binding with extracellular concentration.
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Effect of Paclitaxel Treatment on Tubulins/Microtubules.
In
untreated cells, the polymerized tubulin represented ~75% of total
tubulin. Treatment with 1 and 10 nM paclitaxel did not increase the
total tubulin nor the extent of polymerization, whereas treatments with
100 and 1000 nM paclitaxel significantly enhanced the polymerization
(Table 4). Treatment with 1000 nM
paclitaxel for 24 h further increased the amount of total tubulin,
whereas shorter treatments with 1000 nM or treatments with lower drug concentrations did not. This indicates the induction of tubulin production over time at high paclitaxel concentration. The increase in
tubulin polymerization at 1000 nM paclitaxel occurred within 1 h
or before significant tubulin production was detected. This indicates a
rapid polymerization of pre-existing tubulin by paclitaxel in MCF7
cells and confirms that this drug effect, previously observed in a
cell-free system (Derry et al., 1995
), also occurs in intact cells.
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Development and Validation of a Computational Intracellular Paclitaxel Pharmacokinetic Model. Figure 1 shows the model-simulated intracellular and extracellular drug concentration-time profiles, which superimposed the experimental data points. Table 3 lists the model parameters.
To evaluate the validity of the model, we compared the model-predicted data with the subsequently obtained experimental data. Based on the uptake and efflux data, we expected that the intracellular kinetics of paclitaxel would be affected by cell density and intracellular-to-extracellular concentration gradient. Our model predicted that the extensive drug accumulation in tumor cells would deplete the drug in medium, ranging from a 21% depletion for a cell density of 0.08 × 106 cells/ml to a 90% depletion at a cell density of 2 × 106 cells/ml when cells were treated with 10 nM initial extracellular concentration. The depletion of drug in the medium would in turn result in a lower drug accumulation in cells plated at a high density. This prediction was experimentally verified; the model-predicted and the experimentally determined intracellular concentration, obtained at several cell densities ranging from 0.13 to 1.3 × 106 cells/ml, deviated by 7.5 ± 3.2% (range, 2-11%; Fig. 2). A practical solution for reducing drug depletion while maintaining a desired plating density would be to increase the volume of culture medium. Our model predicted that increasing the medium volume by 10-fold would reduce the extent of drug depletion in the medium, ranging from 2.5% depletion at a cell density of 0.08 × 106 cells/10 ml to 41% depletion at 2 × 106 cells/10 ml. This, again, was experimentally confirmed (Fig. 2).
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Examples of Application of a Computational Intracellular Paclitaxel Pharmacokinetic Model. The computational intracellular pharmacokinetic model can be used to depict changes in intracellular drug concentration as a function of extracellular concentration, time, number and binding affinity of binding sites, and cell density. To demonstrate its use, we performed the following simulations.
Drug resistance is related to altered expression of tubulins (Haber et al., 1995
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100 nM, or
before saturation of the saturable intracellular binding that
constitutes the major mode of drug binding at this concentration range,
intracellular drug concentration increased linearly with extracellular
concentration. At extracellular concentrations between 100 and 1000 nM,
when the saturable intracellular binding approaches saturation,
intracellular drug concentration increased nonlinearly with
extracellular concentration. Finally, at the higher concentrations
above 1000 nM, when the nonsaturable binding becomes the major mode of
intracellular drug binding, intracellular drug concentration increased
linearly with extracellular concentration.
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Discussion |
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Relationship Between Cell Density, Tubulin Polymerization/Production, and Drug Accumulation. The intracellular concentration-time profiles, depicted in Fig. 1, showed two unusual features. First, the intracellular paclitaxel concentration attained at 1 and 10 nM extracellular concentrations reached a maximum value at 4 h and subsequently declined by 23 and 10%, respectively, by 24 h (Table 1). Second, the intracellular concentrations attained at 100 and 1000 nM extracellular concentrations continued to increase with time by about 20 and 50% between 4 and 24 h, respectively (Table 1). These profiles differ from the more commonplace situation where intracellular drug concentration increases with time to reach and remain at a plateau level. This study showed that the decrease in intracellular drug accumulation with time at low drug concentration was due to an increase in cell number as cell proliferation continued (i.e., cell number increased by 36 and 23% over 24 h at 1 and 10 nM, respectively, see Table 1), whereas the increase in drug accumulation with time at high drug concentration was due to paclitaxel-induced increases in total tubulin (Table 4).
Comparison of Paclitaxel Accumulation Data in MCF7 Cells with
Previous Data in Other Cells.
To determine whether the
intracellular pharmacokinetic model is applicable to human cancer cells
in general or only to the MCF7 cells, we compared the accumulation of
paclitaxel and drug-induced changes in tubulin polymerization and
production in MCF7 cells with the results of an earlier study in HeLa
cells (Jordan et al., 1993
). The unusually high drug accumulation in
MCF7 cells is similar to the finding in HeLa cells; the
intracellular-to-initial medium concentration ratios in MCF7 cells,
attained at 10 to 1000 nM initial medium concentrations, ranged from
115 to 464 at 24 h (calculated from data in Table 1), whereas the
same ratios in HeLa cells ranged from 111 to 480 at 20 h. In both
cell lines, prolonged treatment (20-24 h) with paclitaxel at
higher concentrations (
100 nM) induced tubulin production and
polymerization and increased microtubule concentration. The enhancement
in microtubule concentration in MCF7 cells was lower than in HeLa
cells, i.e., a 2-fold enhancement at an initial extracellular
concentration of 1000 nM in MCF7 cells versus a 5-fold enhancement in
HeLa cells. This 2.5-fold greater enhancement is mainly due to the
higher concentration of pre-existing free tubulin available for
polymerization in the HeLa cells; free tubulin represents 67% of total
tubulin in HeLa cells (Jordan et al., 1991
; Thrower et al., 1991
) and
25% in MCF7 cells (Table 4). Correction for this factor showed that
the enhancement in total tubulin was almost identical in the two cell
lines, i.e., 1.8-fold in MCF7 for 24 h versus 1.7-fold in HeLa
cells for 20 h (calculated from the literature data; Jordan et
al., 1991
, 1993
; Thrower et al., 1991
).
Conclusions. The intracellular pharmacokinetic model of paclitaxel described here takes into account the known determinants of drug accumulation in Pgp-negative cells, and therefore can be used to depict intracellular drug concentration-time profiles. As shown in this study, a computational intracellular pharmacokinetic model has the versatility to predict the kinetics of paclitaxel uptake, binding, and efflux in cells under various conditions. The ability to predict intracellular drug concentrations as a function of extracellular drug concentrations such as those in plasma enables the comparison of intracellular concentrations attained at different treatment schedules, e.g., a long infusion that delivers a low plasma concentration for a long duration versus a shorter infusion that delivers a higher plasma concentration for a shorter duration. The ability to predict intracellular drug accumulation as a function of extracellular drug binding enables the evaluation of drug-drug interaction due to alteration of free fraction of paclitaxel in plasma by the presence of Cremophor or cisplatin. The ability to relate the intracellular bound concentrations to changes in microtubules enables us to quantify the effects of changes in tubulins on the kinetics of drug accumulation and efflux in cells. Our long-term goal is to develop a model that links the intracellular pharmacokinetics with pharmacodynamics and allows the antitumor effects of selected treatment schedules to be depicted.
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Acknowledgments |
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We thank Dr. Kenneth Cowan for providing the MCF7 cells, Dr. Dalia Cohen for providing PSC833, and Dr. Jean R. Weaver for help with writing an image analysis program for cell volume determination.
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Footnotes |
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Accepted for publication February 15, 2000.
Received for publication November 2, 1999.
1 This work was partially supported by research Grants R37CA49816 and R01CA63363 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. Dr. Kuh was partially supported by a Presidential Fellowship awarded by the Ohio State University.
2 Current address: Catholic Research Institutes of Medical Science, Catholic University of Korea, 505 Banpo-dong, Seocho-ku Seoul 137-701, Korea.
Send reprint requests to: Dr. Jessie L.-S. Au, College of Pharmacy, 500 West 12th Ave., Columbus, OH 43210. E-mail: au.1{at}osu.edu
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Abbreviations |
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Pgp, P-glycoprotein; Ctotal,c and Ctotal,m, total (i.e., free plus bound) drug concentrations in cells and medium, respectively; Cfree,c and Cfree,m, free drug concentrations in cells and medium, respectively; Vc and Vm, volumes of cells and medium, respectively; CLf, clearance of free drug by passive diffusion; Bmax,c and Bmax,m, maximum drug-binding capacity in cells and medium, respectively; Kd,c and Kd,m, dissociation constants for drug binding to saturable binding sites in cells and medium, respectively; NSB, proportionality constant of nonsaturable binding sites in cells; Vone cell, mean volume of a single cell; ICN, initial cell number at time 0; kcell number, rate constant for changes in cell number; kBmax,c, rate constant for increase in Bmax,c; Bmax,c(t) and Bmax,c,initial, Bmax,c at time t and 0, respectively.
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