Sensitivity of MRI Tumor Biomarkers to VEGFR Inhibitor Therapy in an Orthotopic Mouse Glioma Model

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DOI: 10.1371/journal.pone.0017228 · Source: PubMed
Abstract
MRI biomarkers of tumor edema, vascular permeability, blood volume, and average vessel caliber are increasingly being employed to assess the efficacy of tumor therapies. However, the dependence of these biomarkers on a number of physiological factors can compromise their sensitivity and complicate the assessment of therapeutic efficacy. Here we examine the response of these MRI tumor biomarkers to cediranib, a potent vascular endothelial growth factor receptor (VEGFR) inhibitor, in an orthotopic mouse glioma model. A significant increase in the tumor volume and relative vessel caliber index (rVCI) and a slight decrease in the water apparent diffusion coefficient (ADC) were observed for both control and cediranib treated animals. This contrasts with a clinical study that observed a significant decrease in tumor rVCI, ADC and volume with cediranib therapy. While the lack of a difference between control and cediranib treated animals in these biomarker responses might suggest that cediranib has no therapeutic benefit, cediranib treated mice had a significantly increased survival. The increased survival benefit of cediranib treated animals is consistent with the significant decrease observed for cediranib treated animals in the relative cerebral blood volume (rCBV), relative microvascular blood volume (rMBV), transverse relaxation time (T2), blood vessel permeability (K(trans)), and extravascular-extracellular space (ν(e)). The differential response of pre-clinical and clinical tumors to cediranib therapy, along with the lack of a positive response for some biomarkers, indicates the importance of evaluating the whole spectrum of different tumor biomarkers to properly assess the therapeutic response and identify and interpret the therapy-induced changes in the tumor physiology.

Figures

Sensitivity of MRI Tumor Biomarkers to VEGFR Inhibitor
Therapy in an Orthotopic Mouse Glioma Model
Christian T. Farrar
1
*
.
, Walid S. Kamoun
2.
, Carsten D. Ley
2.
, Young R. Kim
1
, Ciprian Catana
1
, Seon J.
Kwon
1
, Bruce R. Rosen
1
, Rakesh K. Jain
2
, A. Gregory Sorensen
1
1 Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America,
2 Edwin L. Steele Laboratory for Tumor Biology, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
Abstract
MRI biomarkers of tumor edema, vascular permeability, blood volume, and average vessel caliber are increasingly being
employed to assess the efficacy of tumor therapies. However, the dependence of these biomarkers on a number of
physiological factors can compromise their sensitivity and complicate the assessment of therapeutic efficacy. Here we
examine the response of these MRI tumor biomarkers to cediranib, a potent vascular endothelial growth factor receptor
(VEGFR) inhibitor, in an orthotopic mouse glioma model. A significant increase in the tumor volume and relative vessel
caliber index (rVCI) and a slight decrease in the water apparent diffusion coefficient (ADC) were observed for both control
and cediranib treated animals. This contrasts with a clinical study that observed a significant decrease in tumor rVCI, ADC
and volume with cediranib therapy. While the lack of a difference between control and cediranib treated animals in these
biomarker responses might suggest that cediranib has no therapeutic benefit, cediranib treated mice had a significantly
increased survival. The increased survival benefit of cediranib treated animals is consistent with the significant decrease
observed for cediranib treated animals in the relative cerebral blood volume (rCBV), relative microvascular blood volume
(rMBV), transverse relaxation time (T2), blood vessel permeability (K
trans
), and extravascular-extracellular space (n
e
). The
differential response of pre-clinical and clinical tumors to cediranib therapy, along with the lack of a positive response for
some biomarkers, indicates the importance of evaluating the whole spectrum of different tumor biomarkers to properly
assess the therapeutic response and identify and interpret the therapy-induced changes in the tumor physiology.
Citation: Farrar CT, Kamoun WS, Ley CD, Kim YR, Catana C, et al. (2011) Sensitivity of MRI Tumor Biomarkers to VEGFR Inhibitor Therapy in an Orthotopic Mouse
Glioma Model. PLoS ONE 6(3): e17228. doi:10.1371/journal.pone.0017228
Editor: Eric Bernhard, National Cancer Institute, United States of America
Received October 18, 2010; Accepted January 26, 2011; Published March 3, 2011
Copyright: ß 2011 Farrar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by the National Institutes of Health (P41-RR14075, P01-CA80124, R01-CA115767) and by AstraZeneca Pharmaceuticals.
CTF gratefully acknowledges support from the National Cancer Institute (T32-CA009502) and the National Institute on Aging (K25-AG029415). WSK gratefully
acknowledges support from the Susan G. Komen foundation. CDL gratefully acknowledges support from the Harboe Foundation, the A.P. Møller Foundation, and
the Dagmar-Marshall Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: AGS has advisory roles at Genentech, Regenero n, Millennium Pharmaceuticals , AstraZenca, Mitsubi shi Pharma , Merrimack
Pharmaceuticals, Olea Medical, Sie mens Medical Solutions, Lantheus, Biogen Idec, and Epix Pharmaceuticals. RKJ has advisory roles at AstraZeneca,Dyax,
Enlight, SynDevRx, Millennium (1 time), Genzyme (1 time), Morphosys (1 time), Astellas (1 time) and Regeneron (1 time), and received honoraria for giving lectures
at Pfizer and Genzyme. The other authors have declared that no competing interests exist. Some financial support was provided by AstraZeneca Pharmaceuticals.
The funders do not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials.
* E-mail: cfarrar@nmr.mgh.harvard.edu
. These authors contributed equally to this work.
Introduction
Early biomarkers of tumor response to anti-angiogenic therapy
are urgently needed to enable the rapid assessment and tailoring of
drug therapies. MRI biomarkers are increasingly being used to
assess the efficacy of tumor therapies. In particular, MRI methods
for characterizing the tumor vascular structure, including the
cerebral blood volume (CBV) [1], microvascular blood volume
(MBV: vascular volume pertaining only to relatively small
diameter vessels) [2,3], and vessel caliber index (VCI) [4,5] have
been developed and used to study changes in tumor vasculature
with therapeutic treatment [6–10]. In addition, the apparent
diffusion coefficient (ADC), determined from diffusion-weighted
images (DWI), and the transverse relaxation time (T2) have been
used as biomarkers of tumor edema [11,12]. Finally, Dynamic
Contrast Enhanced (DCE) MRI experiments [13–15] have been
employed to assess changes in both the permeability (K
trans
) of the
tumor vasculature to small Gd-based contrast agents, such as Gd-
DTPA, and the volume fraction of the extra-vascular extra-cellular
space (n
e
) [16–18].
However, as discussed in more detail below, these MRI
biomarkers typically each depend on a variety of physiological
factors that may all be influenced by tumor therapy, thereby
complicating the interpretation of the biomarker changes. The
sensitivity of a particular biomarker may vary greatly depending
on the particular tumor phenotype and what parts of the tumor
physiology are being effected by a given tumor therapy. In
addition, the models used to relate the biomarkers to the relevant
physiology may be inadequate or poorly characterized further
complicating interpretation of biomarker responses. Here we
examine in detail the sensitivity of these MRI tumor biomarkers to
treatment with cediranib (AstraZeneca Pharmaceuticals), a potent
inhibitor of vascular endothelial growth factor receptors (VEGFR)
[19]. The MRI biomarker responses are compared with both ex
vivo histology and in vivo optical microscopy studies performed
previously [20] in the same mouse tumor model to more directly
PLoS ONE | www.plosone.org 1 March 2011 | Volume 6 | Issue 3 | e17228
link the biomarkers to the relevant tumor physiology and validate
their sensitivity to anti-angiogenic therapy. The results reported
here provide insight into which of the MRI biomarkers are most
sensitive to changes in tumor morphology and predictive of tumor
response to anti-angiogenic therapy.
The VCI is increasingly being used in both clinical and animal
model studies as a biomarker of vessel normalization with anti-
angiogenic therapy [4,6–8,21–23]. The VCI is defined as the ratio
between the blood volume weighted for large diameter vessels
(CBV, cerebral blood volume) to the blood volume weighted for
small diameter vessels (MBV, microvascular blood volume) and is
proportional to the average blood vessel diameter [4,5]. Angio-
genesis driven tumor growth is typically associated with increased
vessel density and caliber and a disordered and tortuous
vasculature structure [24–26]. An increased VCI with therapy
has therefore typically been interpreted as a lack of a therapeutic
response. However, an accurate assessment of therapeutic efficacy
and interpretation of changes in the tumor vasculature is difficult
to obtain from changes in the average vessel diameter alone. For
example, if both the CBV and MBV decrease, suggesting a
positive therapeutic response, but the MBV decreases more than
the CBV then an increased VCI will be observed. Here we
examine the sensitivity of the VCI to changes induced by cediranib
therapy. The changes in VCI with therapy are compared with
histological and intravital optical microscopy (IVM) measurements
of the average tumor blood vessel diameter and CBV.
The water ADC has previously been shown to be correlated
with tumor cell density [27–29] and has been used to monitor
response to chemotherapy, where increased cell death (decreased
cellular volume fraction) was associated with increased ADC [30–
34]. However, anti-angiogenic therapies may have only anti-
edema effects and the role of ADC as a sensitive biomarker of
tumor edema is less well established. The ADC depends on a
number of factors including the intra- and extra-cellular water
diffusion coefficients and transverse relaxation times, the cellular
volume fraction, and the tortuosity of the extra-cellular space [35].
Since anti-angiogenic therapies may alter a number of these
parameters it is difficult to predict how the ADC will change. In
addition, some anti-angiogenic therapies may have both anti-
edema and anti-tumor effects that could lead to offsetting ADC
responses thereby masking changes in edema. Finally, ADC may
also correlate with glioma invasion [36], further complicating its
interpretation over time. Given all of these possibilities, it would be
helpful to explore the relationship of changes in ADC acutely after
anti-VEGF therapy to changes in tumor edema. The transverse
relaxation time, T2, has also been used as a biomarker of edema
[11,12]. Increased protein concentrations associated with de-
creased edema typically lead to decreased T2 relaxation times.
However, T2 is influenced by many other factors, such as water
compartmentalization and diffusion, hemorrhage, and necrosis.
These factors could all lead to therapy induced T2 changes
independent of changes in edema. Here we examine the sensitivity
of both ADC and T2 to cediranib therapy and validate the
sensitivity of these tumor edema biomarkers with ex vivo
measurements of tumor water content determined from wet and
dry tumor weights.
DCE experiments for assessing vascular permeability to low
molecular weight Gd-based contrast agents, such as Gd-DTPA,
require the use of an accurate arterial input function (AIF) to
properly model the tracer kinetics and extract permeability
parameters. However, obtaining an accurate AIF can be
complicated by many factors, including partial volume and
contrast agent induced T2* distortion of the measured AIF and
lack of an artery in the field of view from which to measure the
AIF. Here we compare the sensitivity of our DCE MRI
measurements of vascular permeability changes, made using a
fixed bi-exponential AIF model, with IVM measurements of
changes in vascular permeability to tetramethylrhodamine-labeled
bovine serum albumin (TMR-BSA).
Materials and Me thods
Mouse Brain Tumor Model
Green fluorescent protein expressing U87 (U87-GFP) tumor
cells (human glioblastoma) were grown in vitro (DMEM medium
with 10% serum, 37 degrees, 20% oxygen, 5% CO
2
), harvested,
resuspended in serum-free DMEM medium, and used for tumor
implantation in athymic (nu/nu genotype) mice. Injections
consisted of 3–5
ml of a cell suspension containing 1610
6
to
5610
6
cells/ml implanted with a 28-gauge microsyringe (10 ml,
Hamilton, Reno, NV). Injections were performed with the mouse
head fixed in a stereotaxic device (Small Animal Stereotaxic
Instrument with Mouse Adaptor, David Kopf Instruments,
Tujunga, CA). The needle tip was positioned at an angle of 55u
and depth of 1.75 mm, and cells were injected slowly over
1 minute. This injection technique ensures implantation of a
sufficient number of cells into the superficial mouse brain cortex.
When the arising tumor reaches approximately 363 mm, it was
harvested and divided into small fragments (,0.560.5 mm) for
implantation in the animals used for the MRI experiments. The
tumor fragments were implanted into the mice by dissecting the
skin from a small area of the skull, slightly anterior to the bregma
and lateral to the midline. A small portion of tumor tissue was
implanted with a 30-gauge needle in the exposed brain. Mice were
imaged 10–14 days following tumor implantation (day 0), when
tumors typically reached a diameter of 2–3 mm, and again 2–3
days later following cediranib treatment, which consisted of 3–
6 mg cediranib/kg bodyweight/day. Control animals were treated
with Tween. The Massachusetts General Hospital Subcommittee
on Research Animal Care approved all experiments (SRAC
protocol # 2004N000050).
Intravital Optical Mic roscopy (IVM)
Green fluorescent protein (GFP) expressing U87-GFP tumors
were implanted in athymic mice, as described above, with
previously implanted cranial windows [37,38]. When tumors
reached a diameter of 1.8–3.5 mm, animals were anaesthetized
and 3–6 locations per animal were imaged using a multi-photon
laser-scanning microscope. To visualize the vessels, 150
mlof
tetramethylrhodamine labeled dextran (MW 2 million, 10 mg/ml)
was injected intravenously. Stacks of 250
mm depth with 5 mmZ-
steps were acquired, and a virtual vascular cast was generated in
3D by custom image analysis software [39]. Length-weighted
average vessel diameter was calculated based on the virtual cast. A
relative Cerebral Blood Volume (rCBV
IVM
) was calculated from
the ratio of the tumor to contralateral cortex microvessel density
(MVD) determined from the IVM data.
For vascular permeability measurements, tetramethylrhoda-
mine labeled BSA (TMR-BSA) was injected intravenously and the
fluorescence signal in a single optical section containing a vessel of
interest was monitored, as described previously [25]. The
permeability P of a vessel of radius r was then calculated from
Equation 1, given below.
P~ lim
t?0
d
dt
Ð
?
r~R
FrðÞrdr
F
n
{F
i
ðÞ
R
ð1Þ
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 2 March 2011 | Volume 6 | Issue 3 | e17228
Here F
n
is the fluorescence intensity from the plasma in the vessel
and F
i
is the fluorescence intensity immediately outside the vessel.
The integral of F( r), the fluorescence intensity in the extravascular
space, was evaluated numerically along a line perpendicular to
the flow axis of the vessel. This derivation assumes that the
relationship between fluorescence signal and local concentration of
fluorophore is uniform across the line of interest and there is no
influx from adjoining vessels.
Magnetic Resonance Imaging
All experiments were performed on a 9.4 Tesla magnet
(Magnex Scientific Ltd, Oxford, UK) equipped with a 60 mm
inner diameter gradient coil (Resonance Research, Billerica, MA)
and interfaced with a Bruker MRI console (Bruker Biospin,
Billerica, MA). The gradient coil has a maximum strength of
1500 mT/m and a rise time of 100
ms. Images were acquired
using either a home built surface coil or a home built mouse head
bird-cage coil. Mice were positioned on a custom made mouse
cradle and anesthetized with 1.5% isoflurane in 50/50 O
2
/
medical air mixture with total flow rate of 1200 ml/min. Contrast
agent injections were performed using an intravenous tail vein
catheter.
For assessing the response of the U87 mouse brain tumor to
cediranib it was necessary to split the mice into two groups to
minimize the scanner time, since it was found that repeated long
exposure to anesthesia resulted in animal death. The imaging
protocol for the first group of animals was as follows: localizer
sequence, T2-weighted RARE sequence, multi-echo spin-echo
sequence (T2 map), multi-echo gradient-echo sequence (T2* map),
injection of 50
ml of SPION (8 mg Fe/ml or ,16 mg Fe/kg
bodyweight), multi-echo spin-echo sequence (T2 map), multi-echo
gradient-echo sequence (T2* map). The imaging protocol for the
second group of animals consisted of: localizer sequence, T2-
weighted RARE sequence, multi-echo spin-echo sequence (T2
map), spin-echo diffusion weighted sequence (DWI), DCE
sequence (100 repetitions) with injection of 50
ml of 100 mM
Gd-DTPA. Total scan time in each case was just under 1 hour.
T2-weighted RARE M RI
T2-weighted Rapid Acquisition with Refocused Echoes (RARE)
images were acquired to assess the tumor volume. The acquisition
parameters were: TE = 10, RARE factor = 16, TR = 3000 ms,
NA = 4, 11 image slices, 0.5 mm slice thickness, 150
mm in-plane
resolution. Tumor volume was determined from the T2
hyperintense tumor region of the brain.
Steady-State Susceptibility Contrast (SSC) MRI
T2 and T2* maps were generated from multi-echo spin-echo
and multi-echo gradient-echo images, respectively, using a custom
written MATLAB program for voxel-wise fitting of the T2 or T2*
relaxation times. Multi-echo spin-echo image acquisition param-
eters were: TE = 10 ms, 10 echoes with 10 ms increment,
TR = 2.5 s, 2 averages, FOV = 1.92 cm, matrix = 1286128 (in-
plane resolution 150
mm), slice thickness = 0.5 mm, 11 image
slices. Multi-echo gradient-echo image acquisition parameters
were: TE = 2.5 ms, 8 echoes with 2.5 ms increment, TR = 1.0 s, 4
averages, FOV = 1.92 cm, matrix = 1286128 (in-plane resolu-
tion = 150
mm), slice thickness = 0.5 mm, 11 image slices. Images
were acquired both before and after injection of SPION (16 mg
Fe/kg bodyweight, r2 = 40 mM
21
s
21
). The relative Cerebral
Blood Volume (rCBV) weighted for large diameter blood vessels
(DR2*) and relative microvascular blood volume (rMBV) weighted
for small diameter blood vessels (DR2) were determined from the
difference between the post- and pre-SPION R2* (1/T2*) and R2
(1/T2) maps respectively. A tumor relative VCI (rVCI) was
calculated using Equation 2 where the tumor VCI was normalized
to the normal contralateral cortex VCI. The value of the Apparent
Diffusion Coefficient (ADC) was taken from DWI measurements
(see below).
rVCI
linear
~
ADC
tumor
ADC
normal

1=2
DR2
=
DR2ðÞ
tumor
DR2
=
DR2ðÞ
normal
ð2Þ
Diffusion Weighted Imaging (DWI):
Spin-echo diffusion weighted images were acquired with 3
different b-values: 0, 756, 1506 s/mm
2
. Spin-echo acquisition
parameters were: TE = 13.8 ms, TR = 3 s, FOV = 1.92 cm, ma-
trix = 1286128 (in-plane resolution = 150
mm), 0.5 mm slice
thickness, 11 image slices. The apparent diffusion coefficient
(ADC) maps were generated using an in-house written MATLAB
program for fitting the natural log of the signal intensity as a
function of b-value.
Dynamic Contrast Enhanced (DCE) Imaging:
The DCE sequence consisted of a T1-weighted gradient-echo
sequence with TE = 2.5 ms, TR = 50 ms, Flip Angle = 35u,
FOV = 1.92 cm, matrix = 96696 (in-plane resolution = 200
mm),
0.5 mm slice thickness, 1 image slice, 70–100 repetitions, tem-
poral resolution = 4.8 s. 50–100
ml of 100 mM Gd-DTPA (0.2–
0.4 mmoles/kg) was injected approximately 30 s after commence-
ment of the DCE imaging sequence. The signal intensity in the
tumor ROI was analyzed using an in-house written MATLAB
program, which models the tumor signal enhancement using the
two-compartment model of Tofts et al [13–15], to extract the
volume fraction of the extra-vascular extra-cellular (EES) space
(n
e
), the volume transfer constant between the plasma and EES
(K
trans
), and the rate constant between the EES and the blood
plasma (k
ep
). Briefly, the time dependence of the tumor signal
intensity is fit to equation 3.
StðÞ~M
0
1{e
{TRR1 tðÞ

sin aðÞ
1{cos aðÞe
{TRR1 tðÞ
ð3Þ
where R1(t) is the longitudinal relaxation rate, a is the flip angle,
and TR is the repetition time. R1(t) depends on the contrast agent
relaxivity (r
1
), the pre-contrast longitudinal relaxation rate (R1(0)),
and the tissue concentration of the contrast agent tracer (C
t
(t))as
described by equation 4.
R1 tðÞ~R10ðÞzr1 C
t
tðÞ ð4Þ
In turn, C
t
(t) is derived from the arterial input function (AIF), C
p
(t),
as described by equation 5.
C
t
tðÞ~K
trans
:
D
:
a
1
:
e
{k
ep
:
t
{e
{k
1
:
t

k
1
{k
ep

z
a
2
:
e
{k
ep
:
t
{e
{k
2
:
t

k
2
{k
ep

"#
ð5Þ
C
p
tðÞ~D
:
a
1
:
e
{k
1
:
t
za
2
:
e
{k
2
:
t

The AIF is modeled as a bi-exponential function with parameters
a
1
and k
1
describing the fast equilibration between the plasma and
extracellular space, a
2
and k
2
describing the clearance of contrast
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 3 March 2011 | Volume 6 | Issue 3 | e17228
agent by the kidneys, and D is the contrast agent dose (mmoles
Gd/kg bodyweight) administered by intravenous injection [13].
We have used the AIF parameters determined empirically by
McGrath et al [40].
Histology
Tumor-bearing mice were perfusion fixed by infusion of 4%
paraformaldehyde through the left ventricle. For immunofluores-
cence analysis, mouse brains were post-fixed for 1 hour in 4%
formaldehyde in PBS followed by incubation in 30% sucrose in
PBS overnight at +4uC and subsequent mounting in freezing
media (OCT, Tissue-Tek). Brains were sectioned every 20
mm and
incubated for 2–4 hours at room temperature with anti-CD31
antibody (2.5
mg/ml, clone 2H8, Millipore Chemicon Interna-
tional) in 0.2% Triton-X100 and 5% normal horse serum (NHS)
in PBS. After several washes in PBS, tissue sections were incubated
for 1 hour at room temperature with 1:400 dilutions of Cy5-
conjugated anti-armenian hamster antibody in 0.2% Triton-X100
and 5% NHS in PBS. After several washes in PBS, tissues were
post-fixed in formaldehyde and mounted with DAPI containing
mounting media (Vectashield, VectorLabs) for confocal micros-
copy. Quantification of the stained area was performed using
an in-house segmentation algorithm (coded using MATLAB,
Mathworks).
Ex Vivo Tumor Water Content Analysis
Anesthetized mice were euthanized by cervical dislocation and
the brains were collected. Brains were dissected into several
compartments: Tumor, ipsilateral hemisphere, contralateral
hemisphere and midbrain. Tissues were weighed immediately
and dried in a vacuum for up to 2 weeks. Weights were collected
throughout the drying period until the final dry weight was
established. Water content was calculated as following:
Water content~ wet weight{dry weightðÞ=wetweight:
Statistical Analysis
Comparisons of changes in the MRI biomarkers between the
cediranib and control groups were performed using analysis of
variance (ANOVA) calculations and statistical significance was
defined by a p-value of ,0.05.
Results
Tumor volume was determined from the T2-weighted hyper-
intense region on day 0 and day 2–3 following commencement of
treatment. An increased tumor volume was observed over time for
both cediranib (194635%) and control (230633%) animals with
no statistically significant difference between groups (Figure 1, left).
This is in agreement with previous IVM measurements of tumor
volume, which observed no difference in tumor growth rate
between cediranib and control animals [20].
Similarly, an increased rVCI was observed on day 2–3 for both
cediranib (33.261.9%) and control (33.863.1%) animals with no
significant difference between treatment groups (Figure 1, right).
This result is in good agreement with previous histology measures
of the average tumor blood vessel diameter [20], which saw no
differences between control (9.460.3
mm) and cediranib
(9.560.4
mm) treated animals in the average vessel diameter of
the tumor core after 2 days of treatment.
While the rVCI increased equally for cediranib and control
groups, the increase occurred for different reasons. As shown in
Figure 2 (left panel), cediranib treatment lead to a decrease in both
rCBV (216.562.2%) and rMBV (239.265.8%). The larger drop
in rMBV compared to rCBV lead to the increased rVCI observed
in Figure 1. In contrast, the control group observed an increase in
rCBV (+14.162.3%) and a decrease in rMBV (220.662.1%),
again resulting an increased rVCI. A statistically significant
difference between control and cediranib groups was observed in
both the change over time of the rCBV (p,0.01) and of the rMBV
(p,0.05). As demonstrated in Figure 2 (right panel), there were no
statistically significant differences between MRI and IVM
measurements of the change over time in rCBV for either control
or cediranib treated animals.
While there was a statistically significant (p = 0.01) decrease in
ADC (26.262.5%) with cediranib treatment, the ADC also
decreased slightly for control animals (22.463.1%) with no
statistically significant difference between cediranib and control
groups (Figure 3, left). In contrast, a significant (p,0.01) difference
in the change over time of T2 (DT2) was observed between control
(1.661.3%) and cediranib (28.661.4%) treated animals (Figure 3,
right). The decreased T2 for cediranib treated animals is consistent
with the decreased water content measured ex vivo from the wet
and dry tumor weights on day 2 of treatment, where a 6.361.9%
decrease in tumor water content was observed between cediranib
and control animals [20]. This is in good agreement with the
8.560.2% difference in T2 observed on day 2 by MRI for control
(T2 = 52.8 ms) and cediranib (T2 = 48.3 ms) treated animals.
A statistically significant difference between cediranib and
control groups was observed in both the change over time of
K
trans
(p = 0.04) and n
e
(p = 0.03). A 34.3610.1% decrease in
K
trans
(6SEM) was observed over time for cediranib treated
animals, while a 6.3615.8% increase in K
trans
was observed for
control animals (Figure 4, left). Similarly, changes over time in n
e
(6SEM) of 231.664.3% and 22.8613.6% were observed for
cediranib and control groups, respectively (Figure 4, middle). The
changes in vascular permeability to Gd-DTPA (K
trans
) observed by
MRI are in good agreement with the changes in permeability to
tetramethylrhodamine-labeled bovine serum albumen (TMR-
BSA) observed previously [20] by IVM (Figure 4, right), where a
decreased permeability (DP=262.3619.2%) for the cediranib
group and an increased permeability (DP = 8.863.5%) for the
control group were observed on day 2.
Discussion
While many MRI biomarkers of anti-angiogenic therapy
response have been proposed, the sensitivity of these biomarkers
to anti-VEGF therapy has not been examined in detail [41]. In
particular, these biomarkers typically each depend on a number of
physiological factors that when altered by tumor therapy may lead
to opposing effects on the biomarker response, thereby minimizing
the biomarker sensitivity to therapy. A recent clinical study of 30
recurrent glioblastoma patients treated with a single dose of
cediranib (AstraZeneca Pharmaceuticals), a potent VEGF recep-
tor-targeted kinase inhibitor, did observe a strong correlation
between changes in the MRI biomarkers K
trans
and microvascular
blood volume (MBV) and the duration of overall and/or
progression-free survival [42]. In addition, recent IVM and MRI
studies in a U87 mouse brain tumor model demonstrated that
cediranib significantly prolongs survival despite persistent tumor
growth, where the survival benefit was primarily attributed to
decreased vascular permeability and reduction of edema [20].
Here we extend these studies by examining the response of
multiple MRI tumor biomarkers, including CBV, MBV, VCI,
K
trans
, n
e
, T2, and ADC, to cediranib therapy and comparing
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 4 March 2011 | Volume 6 | Issue 3 | e17228
them to previously reported [20] histology and IVM measure-
ments of the tumor physiology, including tumor water content,
average blood vessel diameter, blood volume, and vascular
permeability. These studies therefore help to identify the
biomarkers that are most sensitive to changes induced by anti-
angiogenic therapy and to more directly link the biomarker
responses to changes in the relevant tumor physiology.
Recent studies have shown that the vascular models used to
derive the relationship between the average blood vessel diameter
and the MRI measured CBV (DR2*) and MBV (DR2) may be
inadequate for modeling the very abnormal tumor vasculature
[43,44]. The vasculature is typically modeled as a random
uniformly distributed collection of perfect cylinders [45,46]. Not
only may this vascular model be inadequate for tumors, but also it
is unclear how anti-angiogenic tumor therapies that normalize the
tumor vasculature will affect the appropriateness of such a fixed
vascular model. Here we find that the increased rVCI observed for
both control and cediranib treated animals (Figure 1) is consistent
with histology measurements of the average vessel diameter [20],
which observed no difference in vessel diameter between control
and cediranib treated animals after 2 days of treatment. This
suggests that despite the simplistic static vascular model used, the
VCI does accurately reflect changes in the average blood vessel
diameter.
Cediranib treated mice have been shown to have a significantly
increased survival rate compared to controls [20]. Evaluation of
the rVCI alone therefore might mistakenly suggest that cediranib
has no therapeutic benefit as the VCI increased significantly for
both cediranib and control animals. However, analysis of changes
in the rCBV and rMBV indicates that the increased rVCI for
control and cediranib groups occurred for quite different reasons
(Figure 2). While the rCBV and rMBV both decreased
significantly for cediranib treated animals, the rMBV decreased
more than the rCBV resulting in an increased rVCI. In contrast,
Figure 1. Cediranib therapy does not affect tumor growth or vessel caliber. (left) Percent change after 2–3 days of treatment in the (left)
tumor volume and (right) rVCI for cediranib and control treated animals. A significant increase over time in tumor volume and rVCI was observed for
both cediranib and control animals with no statistically significant difference between treatment groups.
doi:10.1371/journal.pone.0017228.g001
Figure 2. Cediranib therapy decreases tumor blood volume. (left) After 2–3 days of treatment, a statistically significant (p,0.01) difference in
the rCBV (6SEM) was observed between cediranib and control groups with a 16.562.2% decrease for cediranib treated animals and a 14.162.3%
increase for control animals. In contrast, after 2–3 days of treatment, the rMBV decreased for both cediranib (239.265.8%) and control ( 220.662.1%)
groups. (right) The changes over time in rCBV measured by MRI and IVM are in excellent agreement, with a large decrease in rCBV for cediranib
treated animals and a large increase in rCBV for control animals observed by both imaging modalities.
doi:10.1371/journal.pone.0017228.g002
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 5 March 2011 | Volume 6 | Issue 3 | e17228
for control animals the rCBV increased while the rMBV decreased,
again resulting in an increased rVCI. The larger decrease over
time in the MBV compared to the CBV observed for cediranib
treated animals suggests that cediranib is preferentially pruning
smaller caliber, less mature tumor blood vessels and has a smaller,
but still significant, effect on the larger blood vessels. In contrast,
the increased CBV and decreased MBV observed over time for
control mice would be consistent with an increasingly avascular
tumor with vessel regression in the tumor core and fewer, but
larger, blood vessels. Such progression to an avascular phenotype
for the core of large tumors is not uncommon and has, for
example, been observed previously in a rat glioma model [47].
The change in rCBV measured by MRI is in excellent
agreement with that measured by IVM (Figure 2). In addition,
the strong response of the rCBV and rMBV to cediranib therapy is
consistent with a previous clinical study where cediranib treatment
lead to a significant decrease in both rCBV and rMBV [7]. While
the clinical study did observe a transient decrease in rVCI that was
not observed in our mouse brain tumor model, this might simply
reflect somewhat different relative responses of the rMBV and
rCBV in the clinical subjects, where a greater decrease is observed
for the rCBV than rMBV. Finally, in contrast to the VCI, the
decreased rMBV measured after only one treatment in the clinical
study was strongly correlated with the duration of overall and/or
progression-free survival [42]. These results therefore suggest that
the CBV and MBV may be better gauges of therapeutic response
than the VCI.
Changes in the T2-weighted signal intensity of tumors are
frequently taken as evidence of changes in tumor edema [11].
Here we quantified tumor T2 relaxation times and compared the
changes in T2 with changes in tumor water content measured ex
vivo. A significant difference between cediranib and control groups
is observed in the T2 response (Figure 3). In particular, cediranib
treated animals had an 8.560.2% lower T2 on day 2 than control
animals, which is in good agreement with the 6.361.9% decreased
tumor water content measured ex vivo after 2 days of cediranib
therapy [20]. This suggests that T2 is a sensitive and quantitative
biomarker of changes in tumor edema. However, care must be
Figure 3. Cediranib therapy decreases tumor T2, but does not affect ADC. (left) While a significant decrease in ADC was observed for
cediranib treated mice (p = 0.01) after 2–3 days of treatment, no statistically significant difference was observed between cediranib and control
groups for the change over time of ADC. (right) In contrast, the decreased T2 observed after 2–3 days of treatment for cediranib animals was
significantly (p,0.01) different from the increased T2 observed for control animals.
doi:10.1371/journal.pone.0017228.g003
Figure 4. Cediranib therapy decreases tumor vascular permeability and extravascular-extracellular space. A significant decrease in
both K
trans
(left) and n
e
(middle) was observed after 2–3 days of treatment with cediranib. A statistically significant decreased vascular permeability to
BSA (DP) was also observed by IVM after 2 days of cediranib treatment (right), consistent with the decreased permeability over time observed by MRI
(K
trans
).
doi:10.1371/journal.pone.0017228.g004
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 6 March 2011 | Volume 6 | Issue 3 | e17228
taken when analyzing tumors with regions of necrosis and
hemorrhage. While the U87 tumor model studied here displayed
no sign of necrosis, hypointense regions consistent with hemor-
rhage were evident in some cases, particularly along the periphery
of the tumor. It is therefore important to define tumor regions-of-
interest that do not contain hemorrhage as this will result in
significantly decreased T2 values. In addition, therapies that
induce large changes in water compartmentalization (i.e. due to
necrosis and/or changes in the extravascular-extracellular space)
and diffusion could also complicate interpretation of T2 changes.
Changes in water compartmentalization and water diffusion
would, however, be reflected in the ADC. For the U87 tumor
model studied here, only very small changes in ADC were
observed with therapy (Figure 3).
The ADC is also frequently used as a biomarker of tumor
edema. While the ADC did decrease significantly over time for
cediranib treated animals, the ADC also decreased slightly for
control animals leading to no significant differences in the ADC
response to treatment between cediranib and control groups
(Figure 3). In contrast, tumor edema determined from tumor T2
and from ex vivo wet-dry tumor weights [20] showed a significant
decrease in tumor edema over time for cediranib treated animals
compared to controls. The ADC depends on a large number of
factors including the intra- and extra-cellular water diffusion
coefficients and transverse relaxation times, the cellular volume
fraction, and the tortuosity of the extra-cellular space [35]. The
significant decrease in ADC for cediranib treated animals likely
resulted from a combination of decreased edema and decreased
extravascular-extracellular space (increased cellular volume frac-
tion), observed by DCE MRI (Figure 4). In contrast, the slight
decrease in ADC for control animals likely resulted from an
increase in tumor edema, which would lead to an increased ADC,
being offset by the decrease in the tumor extravascular-
extracellular space (Figure 4), which leads to a decreased ADC.
The decreased extravascular-extracellular space for control
animals may be a result of the increased tumor blood volume
(Figure 2) and an increased tumor cell volume induced by
increased intra-cellular water content. This illustrates that
offsetting responses in different parts of the tumor physiology
can compromise the sensitivity of the ADC to changes in tumor
edema. Thus, for this tumor model, T2 is a more sensitive gauge of
changes in tumor edema than ADC. This is in agreement with a
previous clinical study, which found T2 to be more sensitive and
‘‘useful’’ than ADC for differentiating contrast-enhancing tumor
and immediate edema regions [11], though it conflicts with clinical
experience with cediranib where early changes were seen on ADC
before they were seen on T2-weighted images [7]. The
dependence of the MRI biomarkers on a number of physiological
factors points to the need to consider the biomarker changes in
relation to one another to properly interpret the therapy induced
changes. Only by considering the ADC, T2, and n
e
responses
together, for example, can insight be obtained into the likely
changes in tumor physiology that are occurring for cediranib and
control groups. In general, the sensitivity of a particular MRI
biomarker may vary greatly depending on which physiological
factors are being altered most by a given therapy for a particular
tumor.
Finally, DCE experiments using low molecular weight Gd-
based contrast agents, such as Gd-DTPA, are routinely performed
for assessing changes in vascular permeability (K
trans
) in response
to anti-angiogenic therapy. However, accurate measurement of
K
trans
requires the use of an accurate arterial input function (AIF)
to properly model the tracer kinetics. Obtaining an accurate AIF is
complicated by many factors, including partial volume and
contrast agent induced T2* distortion of the measured AIF and
lack of an artery in the field of view from which to measure the
AIF. In particular, for mouse brain images obtained with a surface
RF coil, no arteries are typically visible from which to measure an
AIF. Using a reference tissue, such as scalp tissue, to calibrate the
tumor DCE curves can in principle allow the tracer kinetic
parameters to be determined without the need for a direct AIF
measurement [48]. However, in practice using a reference tissue
calibration is complicated by B
1
field inhomogeneities associated
with surface coils and B
0
field inhomogeneity present at air-tissue
interfaces, such as the scalp. Recent studies suggest that given the
large potential errors in measurement of the AIF, it is better to use
an assumed, fixed AIF model for all subjects [49]. The validity of
such an approach, however, remains unclear. The AIF is sensitive
to blood flow velocity (linked to body weight), blood pressure
(dependent on anesthesia dose and body temperature), and the
amount of contrast agent injected (variable due to manual
injection method typically used for animal studies), all parameters
that are difficult to assess with great accuracy and likely vary from
subject to subject. While in theory an accurate measure of AIF
could help reduce all of these sources of subject-to-subject
variability, in practice measurement of the AIF may itself add
uncertainty, rather than reduce it, and thus these uncertainties in
many of the kinetic tracer model input parameters may lead to
large uncertainties in the assessment of the vessel permeability
parameters K
trans
and n
e
. A previous study of a subcutaneous flank
tumor model in rats, where an AIF was directly measured and
compared with a variety of AIF models, suggests that errors
introduced by using a fixed bi-exponential AIF model are less than
5% [40]. However, others have suggested that the use of a fixed
AIF model can lead to large systematic errors in the determination
of permeability parameters [13,50]. The agreement between
permeability parameters extracted using experimentally measured
and fixed models is likely to be highly variable depending on the
tumor model and reproducibility of the experimental techniques
used (i.e. anesthesia, contrast agent injection technique, etc.). The
decreased permeability to Gd-DTPA induced by cediranib
observed in this study (Figure 4), as quantified by K
trans
,is
consistent with the decreased permeability to BSA observed
previously by IVM [20]. The IVM measurement of permeability
involves a much simpler and more straightforward analysis of the
fluorescent signal intensity in the vascular and extravascular
spaces, with no complicated kinetic modeling or need for an
accurate AIF. The good agreement between DCE and IVM
permeability measurements therefore suggests that the simple,
fixed bi-exponential AIF model can be adequate for assessing
changes in vascular permeability. The strong response of K
trans
to
cediranib therapy is again in agreement with a previous clinical
study, which saw a significant decrease in K
trans
for cediranib
treated subjects [7] that was correlated with the duration of overall
and/or progression-free survival [42].
In summary, the MRI biomarkers T2, K
trans
, n
e
, rCBV, and
rMBV all decreased significantly in response to cediranib therapy.
The decreased T2 was correlated with decreased tumor water
content measured ex vivo, indicating that T2 is a sensitive
biomarker of tumor edema. In contrast, the ADC was not
sensitive to changes in tumor water content in this tumor model.
The decreased K
trans
was consistent with IVM measurements of
vascular permeability. The changes in rCBV were in good
agreement with IVM measures of tumor blood volume changes.
In addition, the biomarker responses observed here are consistent
with a previous clinical study that observed a strong decrease in
K
trans
, rCBV and rMBV with cediranib treatment [7]. These
findings indicate that T2, K
trans
, rCBV, and rMBV are sensitive
Sensitivity of MRI Tumor Biomarkers to Therapy
PLoS ONE | www.plosone.org 7 March 2011 | Volume 6 | Issue 3 | e17228
biomarkers of tumor response to anti-angiogenic therapy in this
tumor model. The fact that the VCI and ADC were not sensitive
to cediranib therapy in our mouse brain tumor model, in contrast
to the clinical cediranib study [7], suggests that the sensitivity of a
particular MRI biomarker varies depending on which physiolog-
ical factors are being altered most by a given therapy for a
particular tumor. It also indicates the importance of measuring the
whole spectrum of MRI tumor biomarkers and examining their
changes in relation to one another in order to properly assess the
therapeutic response and identify and interpret the therapy
induced changes in the tumor physiology.
Acknowledgments
We would like to thank Sylvie Roberge for her technical assistance.
Author Contributions
Conceived and designed the experiments: CTF WSK CDL BRR RKJ
AGS. Performed the experiments: CTF WSK CDL. Analyzed the data:
CTF WSK CDL CC SJK YRK. Wrote the paper: CTF WSK YRK BRR
AGS.
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    • "This produces a measurable increase in the transverse relaxation rates of spin echo and gradient echo MRI signals (R 2 = 1/T 2 and R Ã 2 ¼ 1=T Ã 2 , respectively) [13], which can then be exploited to compute in vivo biomarkers of vascular morphology [14– 16]. This method has been used to monitor tumor response to anti-angiogenic treatments in various preclinical cancer models17181920212223. The potential for clinical translation of SSC-MRI has been enhanced by the availability of ferumoxytol (Feraheme Ò , AMAG Pharmaceuticals, Inc., Lexington , MA), an FDA-approved drug that can also be used as a superparamagnetic MRI contrast agent. "
    [Show abstract] [Hide abstract] ABSTRACT: Translational vasculature-specific MRI biomarkers were used to measure the effects of a novel anti-angiogenic biomimetic peptide in an orthotopic MDA-MB-231 human triple-negative breast cancer model at an early growth stage. In vivo diffusion-weighted and steady-state susceptibility contrast (SSC) MRI was performed pre-treatment and 2 weeks post-treatment in tumor volume-matched treatment and control groups (n = 5/group). Treatment response was measured by changes in tumor volume; baseline transverse relaxation time (T 2); apparent diffusion coefficient (ADC); and SSC-MRI metrics of blood volume, vessel size, and vessel density. These vasculature-specific SSC-MRI biomarkers were compared to the more conventional, non-vascular biomarkers (tumor growth, ADC, and T 2) in terms of their sensitivity to anti-angiogenic treatment response. After 2 weeks of peptide treatment, tumor growth inhibition was evident but not yet significant, and the changes in ADC or T 2 were not significantly different between treated and control groups. In contrast, the vascular MRI biomarkers revealed a significant anti-angiogenic response to the peptide after 2 weeks—blood volume and vessel size decreased, and vessel density increased in treated tumors; the opposite was seen in control tumors. The MRI results were validated with histology—H&E staining showed no difference in tumor viability between groups, while peptide-treated tumors exhibited decreased vascularity. These results indicate that translational SSC-MRI biomarkers are able to detect the differential effects of anti-angiogenic therapy on the tumor vasculature before significant tumor growth inhibition or changes in tumor viability.
    Full-text · Article · Nov 2014
    • "On immunoblot analysis, increase of both γH2AX and caspase signals were dose- and time-dependent with respect to pyruvate/TH-302 treatment (Figure S5 in File S1), suggesting that both DNA damage and subsequent apoptotic cell death are induced by TH-302. As shown in Figure 6E, both γH2AX and caspase signals increased one day after treatment of tumors on days 7, 8 and 12, which also correlated with the decrease in the T2 intensity on the same days reflecting decreased water content (Figure 6F, Figure S6 in File S1) [31]. Taken together, these data support the notion that the 2-nitroimidazole trigger in TH-302 is reduced under hypoxia for Br-IPM release and elicit DNA damage and tumor cell death in SCCVII tumor tissues 24 h after combination pyruvate/TH-302, which is consistent with the EPR and MR imaging data. "
    [Show abstract] [Hide abstract] ABSTRACT: BackgroundTH-302 is a hypoxia-activated prodrug (HAP) of bromo isophosphoramide mustard that is selectively activated within hypoxic regions in solid tumors. Our recent study showed that intravenously administered bolus pyruvate can transiently induce hypoxia in tumors. We investigated the mechanism underlying the induction of transient hypoxia and the combination use of pyruvate to potentiate the anti-tumor effect of TH-302.Methodology/ResultsThe hypoxia-dependent cytotoxicity of TH-302 was evaluated by a viability assay in murine SCCVII and human HT29 cells. Modulation in cellular oxygen consumption and in vivo tumor oxygenation by the pyruvate treatment was monitored by extracellular flux analysis and electron paramagnetic resonance (EPR) oxygen imaging, respectively. The enhancement of the anti-tumor effect of TH-302 by pyruvate treatment was evaluated by monitoring the growth suppression of the tumor xenografts inoculated subcutaneously in mice. TH-302 preferentially inhibited the growth of both SCCVII and HT29 cells under hypoxic conditions (0.1% O2), with minimal effect under aerobic conditions (21% O2). Basal oxygen consumption rates increased after the pyruvate treatment in SCCVII cells in a concentration-dependent manner, suggesting that pyruvate enhances the mitochondrial respiration to consume excess cellular oxygen. In vivo EPR oxygen imaging showed that the intravenous administration of pyruvate globally induced the transient hypoxia 30 min after the injection in SCCVII and HT29 tumors at the size of 500–1500 mm3. Pretreatment of SCCVII tumor bearing mice with pyruvate 30 min prior to TH-302 administration, initiated with small tumors (∼550 mm3), significantly delayed tumor growth.Conclusions/SignificanceOur in vitro and in vivo studies showed that pyruvate induces transient hypoxia by enhancing mitochondrial oxygen consumption in tumor cells. TH-302 therapy can be potentiated by pyruvate pretreatment if started at the appropriate tumor size and oxygen concentration.
    Full-text · Article · Sep 2014
  • [Show abstract] [Hide abstract] ABSTRACT: Nuclear Magnetic Resonance (MR) based imaging has become an integrated domain in today's oncology research and clinical management of cancer patients. MR is a unique imaging modality among numerous other imaging modalities by providing access to anatomical, physiological, biochemical and molecular details of tumour with excellent spatial and temporal resolutions. In this review we will cover established and investigational MR imaging (MRI) and MR spectroscopy (MRS) techniques used for cancer imaging and demonstrate wealth of information on tumour biology and clinical applications MR techniques offer for oncology research both in preclinical and clinical settings. Emphasis is given not only to the variety of information which may be obtained but also the complementary nature of the techniques. This ability to determine tumour type, grade, invasiveness, degree of hypoxia, microvacular characteristics, and metabolite phenotype, has already profoundly transformed oncology research and patient management. It is evident from the data reviewed that MR techniques will play a key role in uncovering molecular fingerprints of cancer, developing targeted treatment strategies and assessing responsiveness to treatment for personalized patient management, thereby allowing rapid translation of imaging research conclusions into the benefit of clinical oncology.
    Article · Oct 2011
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