Effect of small-molecule modification on single-cell pharmacokinetics of PARP inhibitors

Article abstract of DOI:10.1158/1535-7163.MCT-13-0801

The heterogeneous delivery of drugs in tumors is an established process contributing to variability in treatment outcome. Despite the general acceptance of variable delivery, the study of the underlying causes is challenging, given the complex tumor microenvironment including intra- and intertumor heterogeneity. The difficulty in studying this distribution is even more significant for small-molecule drugs where radiolabeled compounds or mass spectrometry detection lack the spatial and temporal resolution required to quantify the kinetics of drug distribution in vivo. In this work, we take advantage of the synthesis of fluorescent drug conjugates that retain their target binding but are designed with different physiochemical and thus pharmacokinetic properties. Using these probes,wefollowed the drug distribution in cell culture and tumor xenografts with temporal resolution of seconds and subcellular spatial resolution. These measurements, including in vivo permeability of small-molecule drugs, can be used directly in predictive pharmacokinetic models for the design of therapeutics and companion imaging agents as demonstrated by a finite element model. Mol Cancer Ther; 13(4); 986-95.

Full text of DOI:10.1158/1535-7163.MCT-13-0801

Published OnlineFirst February 19, 2014; DOI: 10.1158/1535-7163.MCT-13-0801
Molecular
Cancer
Therapeutics
Models and Technologies
Effect of Small-Molecule Modification on Single-Cell
Pharmacokinetics of PARP Inhibitors
Greg M. Thurber1, Thomas Reiner1, Katherine S. Yang1, Rainer H. Kohler1, and Ralph Weissleder1,2
Abstract
The heterogeneous delivery of drugs in tumors is an established process contributing to variability in
treatment outcome. Despite the general acceptance of variable delivery, the study of the underlying causes is
challenging, given the complex tumor microenvironment including intra- and intertumor heterogeneity. The
difficulty in studying this distribution is even more significant for small-molecule drugs where radiolabeled
compounds or mass spectrometry detection lack the spatial and temporal resolution required to quantify the
kinetics of drug distribution in vivo. In this work, we take advantage of the synthesis of fluorescent drug
conjugates that retain their target binding but are designed with different physiochemical and thus pharma-
cokinetic properties. Using these probes, we followed the drug distribution in cell culture and tumor xenografts
with temporal resolution of seconds and subcellular spatial resolution. These measurements, including in vivo
permeability of small-molecule drugs, can be used directly in predictive pharmacokinetic models for the
design of therapeutics and companion imaging agents as demonstrated by a finite element model. Mol Cancer
Ther; 13(4); 986–95. ꢀ2014 AACR.
neity can be due to differences in MDR expression levels
Introduction
among different clones (20), mosaic tumors (17), differ-
ent cell states (18), nutrient supply (21), and acquired
drug resistances, among others. Ultimately, the final
distribution is determined by both these tumor char-
acteristics and the drug-specific properties, such as
molecular weight, charge, lipophilicity, target, and non-
target binding.
Heterogeneous drug distribution is a well-known
phenomenon in the delivery of therapeutics to tumors
(1–6), and the manipulation of delivery has a direct
impact on clinical treatment of tumors (7). Variable
delivery also has a pivotal but often less appreciated
role in the development of targeted imaging agents (8–
11). Despite the importance and impact of this hetero-
geneity on therapeutic outcome and imaging agent
design, the study of the underlying causes is compli-
cated by the complex and variable tumor microenvi-
ronment (4). At the whole tumor level, heterogeneous
vascularization and blood flow (12), gradients in oxygen
(13), nutrients (14), and waste products (15), multiple
cell types (16), genetic (17), and epigenetic (18) variabil-
ity in protein expression (19) all contribute to complex
patterns in distribution. At the cellular level, heteroge-
The study of small-molecule distribution has been
complicated by a lack of high spatial and temporal
resolution methods for tracking molecules in tumors.
The two most common ex vivo methods are autoradi-
ography of tritiated or other radiolabeled compounds
and organ-based detection using liquid chromatogra-
phy/mass spectrometry (LC/MS). Typically, these
experiments provide data over several hours with tissue
level distribution (6, 22–25) and an upper limit of
sampling rate of minutes with cellular resolution. The
relatively fast distribution of some drugs has required
that in vitro methods, such as multilayered cells or
tumor spheroids (26–30), be developed to measure
transport parameters. In vivo methods lack the high
spatial and temporal resolution necessary for many of
these drugs. Mathematical models have also played a
large role due to their ability to easily decouple the
drug- and tumor-specific effects and aid in experimen-
tal design (31–35). However, for small-molecule drugs,
the tissue, cellular, and subcellular experimental data
for mathematical model validation is often lacking,
providing a significant obstacle to the use of these
models.
Authors' Affiliations: 1Center for Systems Biology, Massachusetts Gen-
eral Hospital; and 2Department of Systems Biology, Harvard Medical
School, Boston, Massachusetts
Note: Supplementary data for this article are available at Molecular Cancer
Therapeutics Online (http://mct.aacrjournals.org/).
Current address for G.M. Thurber: Department of Chemical Engineering,
Department of Biomedical Engineering, University of Michigan, Ann Arbor,
Michigan; and current address for T. Reiner, Department of Radiology,
Memorial Sloan-Kettering Cancer Center, New York, New York.
Corresponding Author: Ralph Weissleder, Center for Systems Biology,
Massachusetts General Hospital, 185 Cambridge St, CPZN 5206, Boston,
MA 02114. Phone: 617-726-8226; Fax: 617-643-6133; E-mail:
rweissleder@mgh.harvard.edu
doi: 10.1158/1535-7163.MCT-13-0801
Given the challenges associated with studying small-
molecule distribution in tumors, in concert with the recent
ꢀ2014 American Association for Cancer Research.
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Single-Cell Pharmacokinetics of PARP Inhibitors
Materials and Methods
Synthesis of probes
technologic advances in intravital and preclinical tumor
biology research (36–38), we have been developing new
imaging techniques to follow drugs at higher spatial
and temporal resolution in the tumor microenviron-
ment. For example, we have derived therapeutic drug
precursors with BODIPY FL to develop companion
imaging drugs (39–41). This has led to new insight into
the pharmacokinetics of some drugs at the single cell
level in vivo. However, the attachment of the different
fluorochromes also offers the unique opportunity to
study variable pharmacokinetics given differences in
the physiochemical and fluorescent properties (Fig. 1).
In particular, using a relatively small footprint BODIPY
FL on one molecule and a larger BODIPY 650 fluoro-
phore on another, the two drugs can be used to study
molecular effects in the same tissue without complicat-
ing local environment factors.
In this article, we use two different PARP inhibitor
companion imaging drugs to investigate the specific
effects of molecular weight and lipophilicity on target
versus nontarget localization and tumor vessel perme-
ability. The physiochemical properties have a significant
effect on cellular uptake and wash-out kinetics, tumor
vessel permeability, and target versus off-target ratio. A
mathematical model is developed using a finite element
mesh to predict the distribution in the tissue with in vivo
imaging data used to validate the results.
Unless otherwise noted, all reagents were purchased
from Sigma-Aldrich and used without further purifica-
tion. BODIPY FL and BODIPY 650/665 succinimidyl ester
were purchased from Invitrogen. Olaparib (AZD2281)
was purchased from Selleck Chemicals. 4-[[4-Fluoro-3-
(piperazine-1-carbonyl)phenyl]methyl]-2H-phthalazin-
1-one and olaparib-BODIPY FL were synthesized
as described elsewhere (40-42). High-performance
liquid chromatography-electrospray—mass spectrome-
try (HPLC-ESI-MS) analyses and HPLC purifications
were performed on a Waters LC-MS system. For liquid
chromatography-electrospray—mass spectrometry (LC-
ESI-MS) analyses, a Waters XTerra C18 5 mm column was
used. For preparative runs, an Atlantis Prep T3 OBDTM 5
mm column was used. High-resolution ESI mass spectra
were obtained on a Bruker Daltonics APEXIV 4.7 Tesla
Fourier Transform mass spectrometer (FT-ICR-MS) in the
Department of Chemistry Instrumentation Facility at the
Massachusetts Institute of Technology (Boston, MA). Pro-
ton nuclear magnetic resonance (1H NMR) spectra were
recorded on a Varian AS-400 (400 MHz) spectrometer.
Chemical shifts for protons are reported in parts per
million (ppm) and are referenced against the dimethyl
sulfoxide lock signal (1H, 2.50 ppm). Data are reported
as follows: chemical shift, multiplicity (s ¼ singlet,
Figure 1. Molecular properties and cellular imaging. A, the measured inhibitory concentrations of the three PARP inhibitors with the structure shown in B. C, in
vitro images of olaparib-BODIPY FL and olaparib-BODIPY 650 show similar patterns of uptake. Before washing, the majority of the probe is located
in the perinuclear endoplasmic reticulum, and, after washing, the nuclear signal (with higher PARP concentrations in the nucleolus) is more prominent.
The kinetics of distribution are significantly different between the two probes, with the olaparib-BODIPY 650 rates around 10 times slower. The ratio of
uptake in the ER to the nucleus before washing is also much higher with the olaparib-BODIPY 650 probe. The contrast is identical for olaparib-BODIPY FL
before and after the wash, but the contrast was increased after 2 hours of washing to show the nuclear-specific staining, which is much lower than the
perinuclear signal before washing (Supplementary Fig. S2). Scale bar, 20 mm.
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Thurber et al.
d ¼ doublet, t ¼ triplet, m ¼ multiplet), coupling constants
Cell lines and imaging setup
(Hz), and integration.
For cell and xenograft experiments, HT-1080 cells
were purchased from American Type Culture Collec-
tion in February of 2006. Cells were resuscitated in
February of 2012 for experiments; no authentication
was done by the authors. The cells were grown in
Dulbecco’s modified Eagle medium supplemented
with nonessential amino acids, 10% FBS, and 1% pen-
icillin-streptomycin. These cells contain large nuclei and
highly vascularized xenografts ideal for measuring sub-
cellular distribution in vivo. Live cell imaging was done
using an inverted Deltavision deconvolution micro-
scope with a 40ꢂ objective (Applied Precision Instru-
ments) and equipped with a 37ꢁC heated stage and 5%
CO2 live cell imaging setup. Media and solutions with
probes were prewarmed to 37ꢁC before addition
through an access window. The appropriate dichroic
mirrors and filters were used for imaging BODIPY FL
and BODIPY 650 fluorescence.
Synthesis of olaparib-BODIPY 650
Triethylamine(11mL,78mmol)wasaddedtoasolutionof
BODIPY 650/665 succinimidyl ester (5.0 mg, 7.8 mmol) and
4-[[4-fluoro-3-(piperazine-1-carbonyl)phenyl]methyl]-2H-
phthalazin-1-one (5.7 mg, 15.6 mmol) in dimethyl sulfoxide
(500 mL). The reaction mixture was stirred for 2 hours at
room temperature and purified via HPLC to yield the title
compound as a blue solid (5.5 mg, 6.1 mmol, 78%). 1H NMR
(400 MHz, DMSO-d6) d ¼ 12.59 (s, 1H), 11.45 (s, 1H), 8.30–
8.25 (m, 1H), 8.11 (t, 3JHH ¼ 5.2, 1H), 7.95 (d, 3JHH ¼ 7.7, 1H),
3
3
7.88 (t, JHH ¼ 7.3, 1H), 7.82 (t, JHH ¼ 7.5, 1H), 7.58–7.04
(m, 16H), 6.37 (m, 1H), 4.52 (s, 2H), 4.32 (s, 2H), 3.62–3.12
(m, 10H), 2.34–2.23 (m, 2H), 1.51–1.43 (m, 4H), 1.29–1.22
(m, 2H); 19F NMR (376 MHz, DMSO-d6) d ¼ ꢀ120.2 (s,
1F), ꢀ142.3 (q, JBF ¼ 34 Hz, 2F); LC-ESI-MS(þ) m/z (%) ¼
875.5 [M-F]þ (100), 894.5 [MþH]þ (35), 917.5 [MþNa]þ (15);
LC-ESI-MS(ꢀ) m/z (%) ¼ 893.4 [M-H]ꢀ (100); HRMS-ESI
[MþH]þ m/z calculated for [C49H47BF3N8O5]þ 895.3709,
found 895.3732 [MþH]þ.
Mouse xenografts
Xenografts were imaged as previously described (40),
and all animal experiments were carried out in accor-
dance with guidelines from the Institutional Subcom-
mittee on Research Animal Care. Briefly, dorsal skin
window chambers were surgically implanted in 6- to 8-
week-old nude mice. Approximately 3 to 4 million cells
were suspended in a 50% Matrigel and 50% PBS solu-
tion and injected under the fascia and allowed to grow
for 1 to 2 weeks. When tumors were vascularized and
reached 1 to 2 mm in size, mice were anesthetized using
1% to 2% isoflurane in 2 L/min oxygen and a tail
vein catheter was inserted. The mouse was moved
to a heated microscope stage where the vital signs
were continuously monitored. Angiosense-750 (Perkin
Elmer) or 250 mg of 500-kDa amino-dextran labeled with
Pacific Blue NHS ester (Life Technologies) was injected
via tail vein and used to visualize the vasculature. Once
the region of interest was selected, a time-lapse imaging
sequence was initiated, followed by tail vein injection of
the probe. Seventy-five nanomoles of probe was formu-
lated in 30 mL of 1:1 dimethylacetamide:solutol solution
and 112.5 mL of PBS and sonicated.
Plasma protein binding
Plasma protein binding was measured using rapid
equilibrium dialysis plates from Pierce according to the
manufacturer’s instructions. Briefly, each probe was
diluted to a 10 mmol/L concentration in 300 mL of mouse
serum and allowed to equilibrate at 37ꢁC on a shaker for 4
hours with 100 mL of PBS. After equilibration, samples
from each compartment were mixed with additional
plasma or PBS so the final buffer was 50% PBS and 50%
plasma (to minimize protein binding effects on fluores-
cence). The fluorescence was measured using a Tecan
Safire plate reader.
PARP enzyme assay
PARP enzymatic activity was measured following
the manufacturer’s instructions for the universal PARP
colorimetric assay kit from Trevigen. Briefly, increasing
concentrations of olaparib, olaparib-BODIPY FL, or
olaparib-BODIPY 650 (0–4 mmol/L) were added to
histone-coated strip wells in a 96-well plate. Inhibitors
were then preincubated for 10 minutes at room tem-
perature with 0.5 U/well recombinant human PARP.
Wells were then incubated for 1 hour with PARP
cocktail and then washed twice with PBS containing
0.1% Triton X-100 and twice with PBS. Streptavidin-
HRP was then added to each well and incubated for 1
hour. Wells were again washed twice with PBS-0.1%
Triton X-100 and twice with PBS. The colorimetric
reaction was developed upon addition of TACS-Sap-
phire for 15 minutes, followed by reaction termination
with 0.2 mol/L hydrochloric acid (HCl). Absorbance
was measured on a TECAN Sapphire2 plate reader and
enzyme inhibition curves were fit using nonlinear
regression dose-response inhibition equations from
GraphPad (Prism).
Permeability measurements
Permeability measurements were taken using a single
vessel method (43). Briefly, a time-lapse imaging sequence
(sequential scans every 10 seconds) was started before
injection. After intravenous delivery of 75 nmol of both
probes, regions of interest inside the vessel and outside
the vessel were drawn to measure the plasma concentra-
tion and extravascular concentration over time. Taking
into account the plasma fraction and protein binding
(since the permeability is measured relative to the free
drug concentration in the plasma), the permeability was
calculated for each region. These measurements were
repeated at several locations within a field of view for a
minimum of 3 mice.
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Single-Cell Pharmacokinetics of PARP Inhibitors
Mathematical modeling
After validating target binding of the two agents, the
ability of the drugs to localize to the nucleus in vitro was
investigated. HT-1080 cells were incubated with 1
mmol/L of each drug in real time using an inverted
microscope and glass coverslip bottom dishes. Using an
epifluorescence microscope, images were acquired
every second to capture the rapid uptake (half-life 71
seconds for olaparib-BODIPY FL) and wash-out of the
small-molecule companion imaging drug. After the
drug accumulated within cells, they were washed twice
and incubated with fresh media (without drug). PARP1
is located in the nucleus with a higher concentration in
the nucleolus, enabling rapid identification of target
bound drug by drawing subcellular regions of
interest. Figure 1C shows the cells immediately after
the drug was removed (no wash). Both drugs accumu-
lated significantly in the perinuclear region, most likely
the endoplasmic reticulum. Within five minutes of
washing, the nonspecific staining of the endoplasmic
reticulum with the BODIPY FL drug disappeared, while
the target specific nuclear staining remained. However,
the larger BODIPY 650 version required over 2 hours of
washing to reduce the endoplasmic reticulum staining,
although the target-specific labeling remained. The
uptake and wash-out kinetics for the cells were mea-
sured and fit to uptake and clearance curves (Supple-
mentary Materials and Methods).
Details of the mathematical model can be found in the
supporting material, but briefly, the plasma concentration
was set to a biexponential decay as measured in vivo.
Because of high plasma protein binding, this concentra-
tion was held constant throughout the length of the
vessels in agreement with theoretical (3) and experimental
results (40). The product of the permeability and free drug
concentration gradient across the vessel wall wasset equal
to the diffusive flux in the tissue for the boundary condi-
tions. In the tissue, the rapid immobilization by nonspe-
cific protein binding and cellular uptake was assumed to
be linear, so the effective diffusion coefficient was adjust-
ed by the bound to free ratio (44). Free drug entered the
nucleus and bound the target at a rate equal to that
measured in cell culture. The wash-out kinetics were set
to those in cell culture. These rates are a combination of
transport to the target protein and binding/dissociation,
so they are not necessarily equal to the intrinsic associa-
tion/dissociation kinetics of the drug.
Results
Structure function studies during drug development
show tolerance for a large number of substitutions at the
cyclopropyl ring in olaparib (42). The charge neutral
BODIPY dyes were used to ensure membrane permeabil-
ity required to access the nuclear target protein. The
structure and properties of the drugs are listed in Fig. 1
and Table 1. Enzyme inhibition assays of olaparib-BOD-
IPY FL and olaparib-BODIPY 650 showed nmol/L IC50
values and expected decreasing affinities as cyclopropane
substitutions increase in bulk size (40).
On the basis of the target affinity and assuming passive
transport across the plasma membrane, a simple model
of nuclear versus endoplasmic reticulum uptake was
developed to capture the relative cellular uptake.
Specific nuclear uptake was saturable based on the affinity
and estimated nuclear concentration of PARP of 3 mmol/L
Table 1. Molecular, cellular, and in vivo properties
Molecule
Olaparib
Olaparib-BODIPY FL
Olaparib-BODIPY 650
MW (g/mol)
434
640
895
clogP
1.2
4.0
6.0
PARP EC50
Ex/Em (nm)
4.4 ꢃ 1.0 nmol/L
14 ꢃ 1.2 nmol/L
502/510
92 ꢃ 45 nmol/L
646/660
NA
Perinuclear uptake half-life (at 1 mmol/L)
Nuclear uptake half-life (at 1 mmol/L)
Perinuclear clearance half-life
Nuclear clearance half-life
Perinuclear/nuclear ratio (equilibrium at 1 mmol/L)
Mouse plasma clearance
1.18 minutes
1.14 minutes
ꢄ1.66 minutes
1.36 hours
21.2 minutes
8.27 minutes
ꢄ12.8 minutes
1.50 hours
6.0
130
C0 ¼ 7.0 mmol/L
A ¼ 0.77
C0 ¼ 22.8 mmol/L
A ¼ 0.91
t1/2,a ¼ 5.16 minutes
t1/2,b ¼ 85.7 minutes
99.23% (ꢃ0.11%)
t1/2,a ¼ 7.68 minutes
t1/2,b ¼ 92.5 minutes
99.22% (ꢃ0.66%)
Mouse plasma protein binding
NOTE: Top: molecular weight, calculated logP, enzyme affinity, and fluorescence properties of the three PARP inhibitors; middle,
cellular compartment uptake and clearance rates measured in vitro; bottom, plasma clearance of fluorescent probes. Clearance is
similar, although the 1 minute concentration of olaparib-BODIPY FL is significantly less even after injecting the same dose. Plasma
protein binding for both probes was high but similar.
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Thurber et al.
(Supplementary Table S1). Using the relative concentra-
tion of the nucleus and free drug concentration, a linear
(nonsaturable) uptake in the endoplasmic reticulum was
assumed, which is consistent with equilibrium models of
small molecules partitioning into lipid membranes (45,
46). From these estimates, low concentrations of the BOD-
IPY FL drug would specifically stain the nucleus, while
the BODIPY 650 version would not obtain a higher con-
centration in the nucleus at equilibrium based on the
higher uptake in the endoplasmic reticulum relative to
the lower affinity and specific binding. Because the BOD-
IPY FL version starts to wash out in seconds, cells were
imaged in the presence of drug in the media (no washing).
As the endoplasmic reticulum concentration is higher
than free drug in solution, it is still possible to obtain a
cellular image using wide-field microscopy under
these conditions (Fig. 2). As predicted by the cell kinetic
study, the 10 and 100 nmol/L concentrations gave a
higher nuclear signal for the BODIPY FL drug, but the
1 mmol/L concentration resulted in a higher endoplasmic
reticulum signal. The higher lipophilicity and ER uptake
and the lower affinity of the BODIPY 650 labeled drug
resulted in higher ER signal at all concentrations, even
though nuclear-specific staining could be obtained by
washing the cells. Note that the overall intensity of the
images varied dramatically, so the exposure times are
different, but the relative intensity behaved as expected.
Recent advances in intravital microscopy techniques
allow us to measure subcellular drug concentrations at
many frames per minute. This improvement in time
resolution prompted us to measure the distribution of
the BODIPY FL and BODIPY 650 conjugated olaparib after
intravenous injection. Vascular permeability is one of the
most important parameters determining the relationship
between tumor physiology and drug uptake, and this
value can vary by over 5 orders of magnitude between
large nanoparticles and small molecules such as oxygen
(3). Using intravital microscopy in dorsal window cham-
bers of HT-1080 xenografts, the permeability was mea-
sured simultaneously for both drugs in tumor blood
vessels. In all cases, the permeability of the BODIPY FL
drug was higher than the BODIPY 650 drug despite
similar plasma protein binding for both (Fig. 3A). Plotting
this data alongside a compilation of permeability for
proteins and nanoparticles (32), the olaparib-BODIPY
650 permeability (0.46 ꢃ 0.27 mm/s) follows the same
trend as these hydrophilic molecules that primarily
extravasate along a paracellular path (Fig. 3B). However,
the BODIPY FL version has a much higher permeability
(4.7 ꢃ 2.5 mm/s) than would be expected for this trend.
The molecular weight of these drugs only differs by 255
g/mol and plasma protein binding is not statistically
significantly different, but the permeability difference is
significant (P ¼ 0.001). Given the rapid cellular uptake and
wash-out kinetics of the BODIPY FL drug, we hypothesize
that the transcellular route for extravasation is significant
for a molecule of this size. For reference, oxygen is not
shown on the graph but has been estimated at 5 ꢂ 10ꢀ2
cm/s with a radius of approximately 0.3 nm. Plasma
clearance was qualitatively similar between the two
agents, although the peak concentration was higher for
the larger drug. The dose for both drugs was 75 nmol, so it
is likely that the rapid cellular uptake of BODIPY FL drug
(1.2 minutes half-life in vitro) lowered the concentration
before the initial 1 minute time point (Table 1).
Given the challenges of measuring drug distribution
within tumors, mathematical models play an important
role in predicting the impact of variability in drug prop-
erties and the tumor microenvironment (32, 47, 48). To
take advantage of the insight provided by this modeling,
Figure 2. Specific cell uptake. A, a simple equilibrium model derived from the kinetic data predicts that the olaparib-BODIPY FL yields a higher nuclear signal at
low concentrations and higher endoplasmic reticulum (ER) signal at high concentrations. The greater uptake in the endoplasmic reticulum for olaparib-
BODIPY 650 indicates that at equilibrium, the endoplasmic reticulum signal will always be higher than the nucleus. B, wide-field fluorescence images of the
cells in equilibrium with probe in the media are consistent with the equilibrium model. Note that the image contrast was changed between the different
concentrations due to the order of magnitude difference in signal intensity. Arrow points to lower uptake in nucleus. Scale bar, 20 mm.
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Single-Cell Pharmacokinetics of PARP Inhibitors
Figure 3. Tumor vessel
permeability. A, permeability
of olaparib-BODIPY FL and
olaparib-BODIPY 650 in HT-1080
xenografts. The olaparib-BODIPY
FL consistently resulted in an
approximately 10-fold higher
permeability than olaparib-
BODIPY 650. B, the two olaparib
derivatives, shown with open
diamonds, compared with a
variety of proteins and polymers
with varying size (hydrodynamic
radius). The black line is a
two-pore model fit for paracellular
transport (32).
we used a finite element model of drug distribution to
compare uptake of both drugs. For comparison with
experimental results, a vascular probe was injected to
define the vessels within the microscopic field of view
(Supplementary Fig. S1), and a Delaunay triangulation
algorithm was used to create a mesh in the extravascular
space. Because of the high plasma protein binding of these
drugs, the blood flow rate through each vessel has a
negligible impact (3), so the plasma concentration was
set equal to the systemic concentration. The experimen-
tally measured permeability, nonspecific uptake ratio,
and target binding were used in the simulations to predict
the distribution at various times after injection. The lower
nonspecific uptake and faster washout of the olaparib-
BODIPY FL is predicted to give nuclear-specific labeling
as seen in the in vivo microscope image after intravenous
injection of the companion imaging drug (Supplementary
Fig. S1). The higher nonspecific uptake and slower cellular
wash-out of the olaparib-BODIPY 650 is predicted to
result in higher nonspecific uptake at 218 minutes than
nuclear bound drug (Supplementary Fig. S1), which was
validated with the intravital image (Fig. 4). The experi-
mental results validate the model predictions, where the
nuclear target bound drug is less than the nonspecific
cellular uptake, even though wash-out in vitro was shown
to result in nuclear-specific labeling (Fig. 1).
The finite element simulation was able to capture the
differences in subcellular uptake seen with the in vivo
experiments at long time points after the diffusion gra-
dients had dissipated. To further validate the model, the
simulation results were compared at earlier times after
injection (Fig. 5). Minutes after injection, the drug diffuses
away from the vessels, and the olaparib-BODIPY FL
shows approximately equal nonspecific and nuclear tar-
geting at 8 minutes in both the simulation (top) and in vivo
microscope image (bottom). By 25 minutes, the nonspe-
cific uptake has cleared enough to identify individual
nuclei in the image. In contrast, the higher nonspecific
uptake of the olaparaib-BODIPY 650 results in poorer
distribution and much higher nonspecific uptake early
after injection. Because of the higher plasma signal (Table
1), the confocal microscope settings must be reduced to
not saturate the blood vessel signal, resulting in less
apparent signal in the tissue. However, the drug does not
penetrate as far as the olaparib-BODIPY FL in the exper-
imental image (bottom). By 25 minutes, the olaparib-
BODIPY 650 simulation shows increased penetration but
still a higher nonspecific signal than target signal (top). By
Figure 4. In vivo subcellular
distribution. Olaparib-BODIPY FL
shows predominantly nuclear and
nucleolus uptake after 218 minutes
while olaparib-BODIPY 650 is
located primarily in the perinuclear
region. Scale bar, 20 mm.
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Figure 5. Tumoral heterogeneity.
Finite element models of the probe
distribution (top) during the first half
hour show faster distribution for the
olaparib-BODIPY FL with nuclear-
specific staining apparent after
only 25 minutes. The higher
nonspecific immobilization of
olaparib-BODIPY 650 results in
more early time heterogeneity.
In vivo images for the olaparib-
BODIPY FL confirm the lack of
nuclear signal at 8 minutes but
presence of the signal by 25
minutes (bottom). Olaparib-
BODIPY 650 has low penetration
into the tissue at 8 minutes, and
perinuclear staining readily
apparent by 25 minutes. Scale bar,
100 mm.
this time, the blood signal has diminished enough to
distinguish the high perinuclear signal for olaparib-BOD-
IPY 650.
in permeability with decreasing size (51, 52). Taking
advantage of the fast sampling rate afforded by intravital
fluorescence microscopy, we were able to measure sig-
nificant differences in tumor vessel permeability given
small changes in the structure of companion imaging
drugs. These values are critical for predictive modeling
of therapeutics and imaging agent design, but there is a
paucity of data in the literature for in vivo small-molecule
drug permeability. While it is generally accepted that
macromolecules have limited uptake due to low perme-
ability and oxygen and some small-molecule drugs read-
ily cross the endothelium, the transition between these
two regimes (permeability limited versus diffusion or
blood flow limited uptake) is not well defined. Our data
here indicate that the transition between the two regimes
occurs for lipophilic small-molecule drugs between
500 and 1,000 Da, which has important implications for
combination therapies with angiogenesis inhibitors that
normalize the tumor vasculature (7). Our results here are
consistent with the hypothesis that drugs with slow
cellular uptake and washout have lower vascular perme-
ability. The permeability of olaparib–BODIPY 650
matches the predicted value based on a two-pore model
that only accounts for paracellular extravasation of macro-
molecules, while olaparib-BODIPY FL has a higher per-
meability and much faster cellular uptake and washout. In
addition, previous observations for olaparib-BODIPY FL
(40) show thatthe vascularpermeability ofthis moleculeis
the same in tumor vessels and mouse ear vessels. The
paracellular extravasation of macromolecules is increased
in tumors due to the action of VEGF and inflammatory
molecules that increase permeability, and the lack of
difference between these locations indicates that paracel-
lular transport is not significant for olaparib-BODIPY FL.
The olaparib scaffold is an ideal inhibitor for these
studies given the high target expression of PARP (typi-
cally 106 proteins per cell; ref. 53) and distinct subcellular
distribution pattern. Target expression is localized to the
Discussion
Heterogeneous delivery of imaging probes and thera-
peutics to tumors is a complex problem that limits
the design, development, and efficacy of these agents.
While significant progress has been made in understand-
ing the distribution of macromolecules and nanoparticles
(4, 32, 49, 50), the techniques for studying small-molecule
distribution lack the subcellular spatial resolution and
high sampling rate for directly observing the pertinent
rates in vivo. In this work, we take advantage of the
development of fluorescent drug conjugates that retain
their cellular specificity and enzyme inhibition (Fig. 1)
while allowing the simultaneous imaging of multiple
drugs with different physiochemical properties in vivo.
The different fluorophores enable the imaging of multiple
probes in the same tumor microenvironment, isolating
the effect of drug properties from highly variable tumor
physiology. This technique has allowed us to measure the
kinetics of two small-molecule drugs that bind their target
with unprecedented temporal and spatial resolution.
As one specific example, this methodology allows the
direct imaging of small-molecule drug permeability
across the tumor vasculature. Historically, this property
was measured in isolated perfused tissues to determine
the physiologic permeability surface area product. How-
ever, without a simultaneous estimate of surface area,
which can vary over an order of magnitude in tumors, the
results cannot be used for tumor predictions where the
permeability of tumor blood vessels is often higher than in
healthy tissue (43). Fluorescence imaging can overcome
this limitation by direct visualization of extravasation in
the relevant tumor microenvironment, and previous
results shed light on important trends, such as the increase
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Single-Cell Pharmacokinetics of PARP Inhibitors
nucleus while nonspecific uptake occurred in the peri-
nuclear region including the endoplasmic reticulum (Fig.
2). It is therefore easy to identify nonspecific versus target-
specific uptake. This pattern of nonspecific uptake is not
surprising for a lipophilic neutral molecule, which accu-
mulates in the membrane, but the method allowed us to
measure the in vivo kinetics of uptake into the different
subcellular compartments. The ER distribution is in con-
trast to weak bases that are trapped in lysosomes upon
protonation and positively charged small molecules that
accumulate in the mitochondria (45). Given the lipophilic
nature of these drugs, it was assumed that the nonspecific
uptake was nonsaturable and linear with concentration
(Fig. 2), and the resulting prediction of uptake agreed with
the cellular results. The observed subcellular distribution
is important for cellular transport and metabolism,
with p450 enzymes and transporters, such as p-glycopro-
tein, located within certain cellular compartments. The
complex interplay with charge, pKa, molecular weight,
and tissue physiology (e.g., anti-VEGF therapy) will be
explored in future work.
Understanding the impact of physiochemical proper-
ties on tumoral distribution is important for both drug and
imaging agent development. Empirical methods, such as
Lipinski’s rule of 5 (54) or limits on physiochemical
properties (e.g., using neural networks ref. 55) can provide
guidance, but outliers and counter examples exist (56). For
example, canertinib, an irreversible EGFR tyrosine kinase
inhibitor (TKI), obeys all the "rule of 5" criteria but failed in
clinical trials (57). The next generation variant, dacomiti-
nib, violates one of the rules but has shown better phase II
results (58, 59). A more precise method for predicting
pharmacokinetic and pharmacodynamic requirements is
needed.
An understanding of the transient changes in concen-
tration after dosing is even more important for the devel-
opment of imaging agents. While many therapeutics
benefit from continuous dosing, allowing a steady state
or pseudo–steady state to develop, imaging agents are
typically delivered as a single bolus dose. In several
studies of radiolabeled EGFR TKIs, 18F-gefitinib provided
insight into the distribution of this clinically approved
drug (9). However, it failed to localize based on EGFR
target expression. A more hydrophilic radiolabeled EGFR
TKI (60) did distribute differentially to higher expressing
tumors. Interestingly, the predicted logP of these com-
pounds (using the same software in all cases) is 5.6 for
gefitinib and 4.4 for the radiolabeled PEGylated EGFR
TKI. These are similar to the 6.0 value for olaparib-BOD-
IPY 650 and 4.0 for olaparib-BODIPY FL reported here,
which are also both able to hit their target but distribute
differently. Although these results cannot be extrapolated
to allagents, it may provide an"upper limit" around a logP
of ꢄ5 for target specific retention. The lower limit is not
explored in this work, although successful hypoxia imag-
ing agents have logP values around 0 to 1 (61) while
negative logP values, such as Oregon Green tetrazine
(39) cannot penetrate cells to reach their target. Clearly,
the molecular weight and hydrophilicity must be low
enough to allow access to intracellular targets. It is also
important to note in these examples that while some goals
of therapeutic and imaging agent development are
aligned (e.g., high affinity and specificity), others are at
odds (rapid systemic clearance of imaging agents to
reduce background versus sustained systemic levels of
therapeutics to reduce dosing).
A deeper understanding of drug distribution for both
small-molecule agents and biologics is required as the
lines between these two discrete fields become blurred.
For example, Navitoclax, a "small-molecule" inhibitor of
Bcl-2 family proteins is almost 975 Da in size, a molecular
weight likely required for its disruption of protein–pro-
tein interactions. Smaller biologics include imetelstat
(MW ¼ 4610), a telomerase inhibitor, and stapled peptides
(ꢄ2 kDa) such as BH3 domains (62), among many others.
These new agents may present complex pharmacokinetic
behavior that do not follow small molecule or biologic
drug development patterns. A better mechanistic under-
standing of distribution, including the influence of blood
flow, permeability, diffusion, cellular uptake, and target
binding (3) will enable more rapid development of these
types of drugs. Unfortunately, simple extrapolation of
some experiments, such as the permeability of molecules
less than 1 nm in Fig. 3B, can provide misleading results
since charge and protein binding can have a large effect on
the paracellular versus transcellular routes of extravasa-
tion. Future work is required to make better predictions of
drug uptake based on molecular properties.
Mathematical modeling will continue to play an
increasing role in predicting the distribution of novel drug
and imaging agents. With multiple simultaneous rates
occurring during experiments, including plasma clear-
ance, extravasation, diffusion, target binding, and metab-
olism, it becomes difficult to experimentally isolate the
effect of any one parameter; however, this can easily be
done with a validated model. This joint theoretical and
experimental approach helped elucidate the effect of
dose on antibody uptake (8), and the required timing
after injection of hypoxic imaging agents (63). Even the
clinically widespread fluorodeoxyglucose (FDG) agent
shows blood flow–dependent uptake at early times fol-
lowed by glucose metabolism dependent localization at
later times (64), an effect captured by mathematical mod-
els (3). The development of agents based on iterative
synthesis and animal experiments is labor and cost inten-
sive. Mathematical models provide a rapid and cost-
effective way of focusing synthesis on desirable molecular
properties to obtain sufficient uptake and distribution
for therapeutics or efficient target binding and clearance
for imaging agents. They can also be combined with
pharmacodynamic models for prediction of therapeutic
outcome. The mechanistic framework can be scaled to
humans by changing the plasma clearance rates and
concentration, thus providing insight into the distribu-
tion in the clinic, which is currently unobtainable
by other methods. Finally, mathematical modeling and
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993
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Published OnlineFirst February 19, 2014; DOI: 10.1158/1535-7163.MCT-13-0801
Thurber et al.
Acquisition of data (provided animals, acquired and managed patients,
provided facilities, etc.): G. Thurber, T. Reiner, K. Yang, R. Kohler
Analysis and interpretation of data (e.g., statistical analysis, biostatis-
tics, computational analysis): G. Thurber, T. Reiner, K. Yang, R.
Weissleder
Writing, review, and/or revision of the manuscript: G. Thurber, T. Reiner,
K. Yang, R. Kohler, R. Weissleder
Administrative, technical, or material support (i.e., reporting or orga-
nizing data, constructing databases): G. Thurber
simulations also help in interpretation of experimental
and clinical results.
In conclusion, a combination of novel fluorescent drug
conjugates and in vivo imaging experiments have provid-
ed insight into the cellular and tumoral heterogeneity of
small-molecule drugs. The lipophilic PARP inhibitors
studied here show a sharp transition in both cellular
uptake and permeability between a 640-Da probe with
a clogP of 4 and a 895-Da probe with clogP of 6. These
measurements can be used to develop predictive mathe-
matical simulations that help in understanding drug
distribution in vivo at the preclinical and clinical stage,
in designing better imaging agents and therapeutics, and
in interpreting experimental results.
Study supervision: R. Weissleder
Acknowledgments
This work was supported in part by NIH Grants P50 CA086355, R01
EB010011, and K01 DK093766.
Grant Support
This work was supported by NIH Grants P50 CA086355 (to R. Weis-
sleder), R01 EB010011 (to R. Weissleder), and K01 DK093766 (to G.M.
Thurber).
The costs of publication of this article were defrayed in part by the
payment of page charges. This article must therefore be hereby marked
advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate
this fact.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Authors' Contributions
Conception and design: G. Thurber, T. Reiner, R. Weissleder
Development of methodology: G. Thurber, T. Reiner, R. Kohler
Received October 1, 2013; revised January 23, 2014; accepted February 3,
2014; published OnlineFirst February 19, 2014.
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Effect of Small-Molecule Modification on Single-Cell
Pharmacokinetics of PARP Inhibitors
Greg M. Thurber, Thomas Reiner, Katherine S. Yang, et al.
Mol Cancer Ther 2014;13:986-995. Published OnlineFirst February 19, 2014.
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