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Development and Intratumoral Distribution of Block Copolymer Micelles as Nanomedicines for the Targeted
Delivery of Chemotherapy to Solid Tumors
by
Andrew S. Mikhail
A thesis submitted in conformity with the requirements for the degree of doctor of philosophy
Department of Pharmaceutical Sciences and the Institute of Biomaterials and Biomedical Engineering
University of Toronto
© Copyright by Andrew S. Mikhail 2013
ii
Development and Intratumoral Distribution of Block Copolymer
Micelles as Nanomedicines for the Targeted Delivery of
Chemotherapy to Solid Tumors
Andrew S. Mikhail
Doctor of philosophy
Department of Pharmaceutical Sciences and the Institute of Biomaterials and Biomedical Engineering
University of Toronto
2013
Abstract
Recent advancements in pharmaceutical technology based on principles of
nanotechnology, polymer chemistry, and biomedical engineering have resulted in the
creation of novel drug delivery systems with the potential to revolutionize current
strategies in cancer chemotherapy. In oncology, realization of significant improvements
in therapeutic efficacy requires minimization of drug exposure to healthy tissues and
concentration of the drug within the tumor. As such, encapsulation of chemotherapeutic
agents inside nanoparticles capable of enhancing tumor-targeted drug delivery is a
particularly promising innovation. Yet, initial investigations into the intratumoral fate of
nanomedicines have suggested that they may be heterogeneously distributed and
achieve limited access to cancer cells located distant from the tumor vasculature. As
such, uncovering the determinants of nanoparticle transport at the intratumoral level is
iii
critical to the development of optimized delivery vehicles capable of fully exploiting the
therapeutic potential of nanomedicines.
In this work, the chemotherapeutic agent, docetaxel (DTX), was incorporated into nano-
sized, biocompatible PEG-b-PCL block copolymer micelles (BCMs). Encapsulation of
DTX in micelles via chemical conjugation or physical entrapment resulted in a dramatic
increase in drug solubility and customizable drug release rate. The use of multicellular
tumor spheroids (MCTS) was established as a viable platform for assessing the efficacy
and tumor tissue penetration of nanomedicines in vitro. A series of complementary
assays was validated for analysis of DTX-loaded micelle (BCM+DTX) toxicity in
monolayer and spheroid cultures relative to Taxotere®. Cells cultured as spheroids were
less responsive to treatment relative to monolayer cultures due to mechanisms of drug
resistance associated with structural and microenvironmental properties of the 3-D
tissue. Computational, image-based methodologies were used to assess the spatial and
temporal penetration of BCMs in spheroids and corresponding human tumor xenografts.
Using this approach, the tumor penetration of micelles was found to be nanoparticle-
size-, tumor tissue type- and time- dependent. Furthermore, spheroids were found to be
a valuable platform for the prediction of trends in nanoparticle transport in vivo. Overall,
the results reported herein serve to demonstrate important determinants of nanoparticle
intratumoral transport and to establish computational in vitro and in vivo methodologies
for the rational design and optimization of nanomedicines.
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Acknowledgments
Firstly I would like to thank my supervisor Dr. Christine Allen for the opportunity to
undertake a doctoral research project in her lab. It has been a privilege and a pleasure
to work under her guidance and I am truly grateful for her continued support and belief
in my abilities. I am very lucky to have worked under the leadership of such a caring
individual and inspiring researcher. She has made this experience both enjoyable and
deeply rewarding and I would like to sincerely thank her for all that she has done for me.
I am also deeply appreciative of my advisory committee members: Dr. Yu-Ling
Cheng, Dr. Robert Macgregor and Dr. Ian Tannock. Receiving constructive ideas and
critical input from such esteemed investigators was truly one of the greatest privileges of
being a doctoral student. I extend to them my deepest gratitude for finding time in their
busy schedules to support my research. I valued their input tremendously. In particular, I
am very grateful for the scientific guidance provided by Dr. Tannock and the members
of his laboratory and the advice and support of Dr. Macgregor.
I would also like to thank all of my colleagues who have helped me along the way
and who have made this experience enjoyable. A special thanks to Sina Eetezadi for his
efforts in what turned out to be a very productive, and fun, collaboration. Thank you also
to Dr. David Dubins for making my experience as a teaching assistant so enjoyable. I’d
also like to acknowledge Dr. Kazunori Kataoka and Dr. Horacio Cabral for providing me
the opportunity to work at the University of Tokyo.
I am also blessed with great friends in my life who have supported me and with
whom I share so many great memories from this period of my life. There are too many
to list here, but I would be remiss to not acknowledge my great friend Derek Watkins,
who is like a brother to me. Words are not enough to thank you for your support. As this
journey comes to a close and a new one begins, I humbly remember friends of mine
and of my family who have been affected by or lost their lives to cancer.
Finally, with all of my heart, I would like to thank my family for everything they
have done for me. Their unconditional support through thick and thin is what made this
accomplishment possible. To my parents I am forever indebted for all that they have
sacrificed and put second to my well-being and happiness. None of this was possible
without them. I dedicate this accomplishment to my father, Shaheer Mikhail, who is my
greatest mentor and who inspired me to pursue higher learning.
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Table of Contents
Acknowledgments ........................................................................................................ iv
Table of Contents ........................................................................................................... v
List of Tables .................................................................................................................. x
List of Figures ............................................................................................................... xi
List of Abbreviations .................................................................................................. xiv
CHAPTER 1. Introduction .............................................................................................. 1
1.1 Overview ............................................................................................................... 3
1.2 Whole body transport and macrodistribution ......................................................... 5
1.3 Thermodynamic and kinetic stability of block copolymer micelles in vivo .............. 6
1.4 Drug retention in vivo ............................................................................................ 7
1.5 Pharmacokinetics and whole body distribution of block copolymer micelles ....... 10
1.6 Influence of blood proteins and MPS clearance .................................................. 11
1.7 Passive tumor accumulation via the EPR effect .................................................. 12
1.8 Tumor physiology and its role in nanoparticle delivery ........................................ 13
1.8.1 Vascular density (density of functional vessels) ....................................... 13
1.8.2 Vascular permeability ............................................................................... 13
1.8.3 Interstitial fluid pressure and transport in the interstitium .......................... 14
1.9 Active targeting ................................................................................................... 16
1.10 Microdistribution: transport within an organ or tissue…………………………….17
1.11 3-D tissue culture and the multicellular tumor spheroid model .......................... 22
1.12 Transport at the cellular level……………………………………………………….23
1.13 Docetaxel .......................................................................................................... 25
1.14 . Summary……………………………………………………………………………...26
1.15 Rationale………………………………………………………………………………27
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1.16 Hypotheses…………………………………………………………………………...28
1.17 Objectives……………………………………………………………………………..28
1.18 Overview of Thesis Chapters……………………………………………………….29
CHAPTER 2. Poly(ethylene glycol)-b-poly(ε-caprolactone) Micelles Containing Chemically Conjugated and Physically Entrapped Docetaxel: Synthesis, Characterization, and the Influence of the Drug on Micelle Morphology ........... 30
2.1 Abstract ............................................................................................................... 32
2.2 Introduction ......................................................................................................... 33
2.3 Experimental Section .......................................................................................... 34
2.3.1 Materials ................................................................................................... 34
2.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) Copolymers ..................... 34
2.3.3 Addition of Carboxylic Acid Group to PCL Block of PEG-b-PCL Copolymers .............................................................................................. 35
2.3.4 Conjugation of DTX to PEG-b-PCL-COOH Copolymers .......................... 35
2.3.5 Characterization of Copolymers and Copolymer-Drug Conjugates .......... 36
2.3.6 Micellization and Measurement of Critical Micelle Concentration (CMC) . 36
2.3.7 Transmission Electron Microscopy (TEM) Analysis .................................. 37
2.3.8 Determination of Micelle Size ................................................................... 37
2.3.9 Evaluation of Drug Loading and Release ................................................. 38
2.3.10 Statistical Analysis .................................................................................... 38
2.4 Results and Discussion ....................................................................................... 38
2.4.1 Synthesis of PEG-b-PCL Copolymer and PEG-b-PCL-DTX Copolymer-Drug Conjugate ........................................................................................ 38
2.4.2 Physico-Chemical Properties of PEG-b-PCL and PEG-b-PCL-DTX Copolymer and Copolymer-Drug Conjugates ........................................... 41
2.4.3 Characterization of the Copolymer-Drug Conjugate and Drug-Loaded Micelles. ................................................................................................... 43
2.4.4 Micelle Morphology ................................................................................... 43
2.4.5 Drug Loading ............................................................................................ 46
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2.4.6 Drug Release............................................................................................ 47
2.5 Conclusions ......................................................................................................... 49
2.6 Acknowledgements ............................................................................................. 50
CHAPTER 3. Cytotoxicity and Growth Inhibitory Effect of Docetaxel-loaded Block Copolymer Micelles and Taxotere® in Monolayer and Spheroid Cultures .......... 51
3.1 Abstract ............................................................................................................... 53
3.2 Introduction ......................................................................................................... 54
3.3 Materials and Methods ........................................................................................ 56
3.3.1 Materials ................................................................................................... 56
3.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) and Alexa Fluor 488-PEG-b-PCL (AF488-PEG-b-PCL) copolymers .................................................. 56
3.3.3 Preparation and characterization of BCMs ............................................... 57
3.3.4 Sizing of BCM+DTX ................................................................................. 57
3.3.5 Transmission Electron Microscopy (TEM) ................................................ 57
3.3.6 Drug Release............................................................................................ 57
3.3.7 Tissue culture and growth of MCTS ......................................................... 58
3.3.8 Immunohistochemical analysis of MCTS .................................................. 58
3.3.9 Measurement of MCTS Growth ................................................................ 59
3.3.10 Cytotoxicity in Monolayer and Spheroid Tissue Culture ........................... 59
3.3.11 Growth Inhibition of MCTS ....................................................................... 60
3.3.12 Clonogenic Survival Assay ....................................................................... 60
3.4 Results ................................................................................................................ 61
3.4.1 Characterization of BCM+DTX ................................................................. 61
3.4.2 Growth of MCTS ....................................................................................... 62
3.4.3 Cytotoxicity in monolayer and MCTS culture ............................................ 63
3.4.4 Inhibition of MCTS growth ........................................................................ 64
3.4.5 Immunohistochemistry .............................................................................. 66
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3.4.6 Clonogenic Survival .................................................................................. 68
3.5 Discussion ........................................................................................................... 69
3.6 Conclusions ......................................................................................................... 73
CHAPTER 4. Image-based Analysis of the Time-dependent Penetration of Polymeric Micelles in Multicellular Tumor Spheroids and Tumor Xenografts ... 74
4.1 Abstract ............................................................................................................... 76
4.2 Introduction ......................................................................................................... 77
4.3 Methods .............................................................................................................. 79
4.3.1 Materials ................................................................................................... 79
4.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) and Alexa Fluor® 488-PEG-b-PCL (AF488-PEG-b-PCL) copolymers .................................................. 79
4.3.3 Preparation and characterization of BCMs ............................................... 80
4.3.4 Transmission electron microscopy (TEM) ................................................ 80
4.3.5 Tissue culture and growth of MCTS ......................................................... 81
4.3.6 Penetration of BCMs in MCTS ................................................................. 81
4.3.7 Animals and growth of tumor xenografts .................................................. 81
4.3.8 Penetration of BCMs in tumor xenografts ................................................. 82
4.3.9 Computational analysis of BCM distribution in tumor sections ................. 83
4.4 Results ................................................................................................................ 83
4.4.1 Synthesis and characterization of PEG-b-PCL copolymers and BCMs .... 83
4.4.2 Growth of MCTS ....................................................................................... 84
4.4.3 Penetration of BCMs in MCTS ................................................................. 85
4.4.4 Penetration of BCMs in tumor xenografts ................................................. 86
4.5 Discussion ........................................................................................................... 92
4.6 Conclusions ......................................................................................................... 96
4.7 Acknowledgements ............................................................................................. 97
ix
CHAPTER 5. Summary and Future Directions .......................................................... 98
5.1 Conclusions and Summary of Findings ............................................................... 98
5.2 Future Directions ............................................................................................... 100
5.2.1 Improving drug retention and tumor-specific drug delivery ..................... 100
5.2.2 Therapeutic efficacy and the intratumoral fate of DTX ............................ 101
5.2.3 Overcoming transport barriers by modulating the tumor microenvironment…………………………………………………………….102
References.................................................................................................................. 104
Appendix 1: Chapter 3 Supplemental Data .............................................................. 140
Appendix 2: Chapter 4 Supplemental Data .............................................................. 143
x
List of Tables
Table 2.1 Melting Temperature (Tm), Critical Micelle Concentration (CMC), Morphology,
Diameter, Molecular Weight (Mn), and Polydispersity (Mw/Mn) of Copolymers
and Copolymer-Drug Conjugate. ........................................................................... 40
Table 2.2. GPC Retention Times (Rt) of the Copolymers and Copolymer-Drug
Conjugate .................................................................................................................. 41
Table 4.1. Composition of block copolymers and properties of BCMs. ............................. 84
xi
List of Figures
Figure 1.1. Micelle transport at the whole body, tissue and cellular levels. ........................ 5
Figure 1.2. Molecular simulation of DTX surrounded by PEG-b-PCL ................................. 9
Figure 1.3. Biodistribution and intratumoral distribution of 111In-PEG-b-PCL micelles. .. 21
Figure 1.4. Cellular uptake of EGF-conjugated PEG-b-PVL micelles . ............................. 19
Figure 2.1. Synthesis of PEG-b-PCL, PEG-b-PCL-COOH, and PEG-b-PCL-DTX ......... 39
Figure 2.2. 1H NMR of PEG-b-PCL copolymers and copolymer-DTX conjugates. ......... 40
Figure 2.3. GPC chromatograms of copolymers and copolymer-DTX conjugates.. ....... 41
Figure 2.4. Diameter and stability of PEG-b-PCL-DTX micelles . ...................................... 42
Figure 2.5 TEM images showing the morphology of micelles containing physically
and/or chemically conjugated docetaxel in different molar ratios. ................. 45
Figure 2.6. Drug loading of BCMs by physical entrapment of DTX at various copolymer
and copolymer-drug conjugate concentrations………………………….....…47
Figure 2.7. Release of chemically conjugated DTX from PEG-b-PCL-DTX micelles. .... 48
Figure 2.8. Release of physically entrapped DTX from PEG2000-b-PCL1000 BCMs and
BCM-DTX................................................................................................................ 49
Figure 3.1. 3-D cultures as an intermediary platform between monolayer cultures and
animal models ........................................................................................................ 55
Figure 3.2. Schematic representation of assays used for analysis of formulation efficacy
in spheroids. ........................................................................................................... 56
Figure 3.3. TEM and size distribution as determined by DLS of BCM+DTX... ................. 61
Figure 3.4. Release of DTX from BCMs (PEG5000-b-PCL5000) and Taxotere® .................. 62
xii
Figure 3.5. Cell packing density and growth of HeLa and HT29 MCTS ............................ 62
Figure 3.6. Cytotoxicity of Taxotere® and BCM+DTX and BCMs in monolayer and
MCTS cultures as measured using the APH assay. ........................................ 64
Figure 3.7. Growth inhibition of HeLa and HT29 MCTS by BCM+DTX and Taxotere® .. 65
Figure 3.8. Immunohistochemical staining of HeLa and HT29 MCTS cross-sections with
H&E, Ki67 (proliferation) and EF5 (hypoxia). .................................................... 66
Figure 3.9. Ki67 positive signal distribution in HeLa and HT29 MCTS .............................. 67
Figure 3.10. Spatial distribution of features of HeLa and HT29 MCTS
microenvironments. ............................................................................................... 67
Figure 3.11. Clonogenic survival of HeLa and HT29 cells following treatment with
BCM+DTX or Taxotere® as monolayers, disaggregated MCTS and intact
MCTS. ..................................................................................................................... 68
Figure 4.1. Schematic representation of tumor and MCTS cross-sections ...................... 78
Figure 4.2. TEM images of PEG5000-b-PCL5000 and PEG2000-b-PCL1000 BCMs. .............. 84
Figure 4.3. Schematic representation of MCTS growth using the liquid overlay
method. ................................................................................................................... 85
Figure 4.4. H&E immunohistochemical staining of HT29 and HeLa xenografts and
MCTS ...................................................................................................................... 86
Figure 4.5. BCM penetration in HeLa and HT29 MCTS following incubation with BCM-
15 and BCM-55 for 1 h and 24 h ......................................................................... 87
Figure 4.6. Area-normalized distribution of BCM-15 and 55 HeLa and HT29 MCTS
following 1 h and 24 h exposures. ...................................................................... 88
Figure 4.7. Representative computational image-based analysis of BCM penetration in
tumor xenografts .................................................................................................... 89
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Figure 4.8. Interstitial penetration of BCMs relative to tumor blood vesselsin HeLa and
HT29 tumor xenografts. ........................................................................................ 90
Figure 4.9. Mean fluorescence pixel intensities of BCM-15 and BCM-55 at 100 µm from
the nearest blood vessel in tumor xenografts at 1, 6, and 24 h p.i. ............... 91
Figure 4.10. Potential influence of micelles on the intratumoral distribution of the drug. 96
xiv
List of Abbreviations
APH Acid phosphatase assay
AUC Area under the curve
BCM(s) Block copolymer micelle(s)
BCM-15 15 nm block copolymer micelles
BCM-55 55 nm block copolymer micelles
CL Caprolactone
CMC Critical micelle concentration
Da Daltons
DLS Dynamic light scattering
DOX Doxorubicin (adriamycin)
DTX Docetaxel
Glu Glutamic acid
GPC Gel permeation chromatography
HLB Hydrophilic-lipophilic balance
HPLC High-performance liquid chromatography
IC50 Half maximal inhibitory concentration
i.v. Intravenous
MCTS Multicellular tumor spheroids
MDR Multi-drug resistant
Mn Number average molecular weight
mPEG Methoxy-poly(ethylene oxide)
MPS Mononuclear phagocytic system
Mw Weight average molecular weight
NMR Nuclear magnetic resonance
PBS Phosphate buffered saline
PCL Poly(ε-caprolactone)
pKb Base dissociation constant
PPO Poly(propylene oxide)
PTX Paclitaxel
PAsp Poly(aspartic acid)
xv
PEG Poly(ethylene glycol)
P85 Pluronic® P85
PK Pharmacokinetics
SF Surviving fraction
t1/2,α Distribution half-life
t1/2,β Elimination half-life
TAX Taxotere®
TEM Transmission electron microscopy
Tyr Tyrosine
1
1 Chapter 1. Introduction
Chapter 1. Introduction
2
This chapter is a reprint with modification of: “Andrew S. Mikhail and Christine Allen.
Block copolymer micelles for delivery of cancer therapy: Transport at the whole body,
tissue and cellular levels.” Journal of Controlled Release 138 (2009) 214–223; with
permission from Elsevier.
This chapter was written by AS. Mikhail with editing by Dr. C. Allen.
3
1.1 Overview
The use of block copolymer micelles (BCMs) for the targeted delivery of
chemotherapeutics has proven to be a promising approach for improving the
therapeutic efficacy of drug therapy. Acceleration of the translation of nanomedicines
from the fundamental stages of pre-clinical development to clinical use requires a
greater understanding of the transport mechanisms that influence the fate of nano-
carriers at the whole body, tissue, and cellular levels (Figure 1.1). New imaging-based
techniques to evaluate the intratumoral distribution and tumor penetration of BCMs and
other nanosystems have the potential to revolutionize our understanding and current
approach to drug delivery in this field.
The therapeutic efficacy of conventional chemotherapeutic agents is often limited
by the drug's poor aqueous solubility and systemic toxicity. Side effects resulting from
toxicity to healthy tissues commonly constrain the dose and frequency of chemotherapy
and thus compromise the effectiveness of treatment [1]. Although the use of small
molecule surfactants as excipients in commercial formulations has helped to improve
the solubility of hydrophobic drugs, these chemicals are also intrinsically toxic [2].
Incorporation of drugs within biocompatible and/or biodegradable block copolymer
micelles (BCMs) has been shown to reduce systemic toxicity while increasing drug
solubility and site-specific tumor accumulation [3–7].
BCMs are self-assembled nano-sized aggregates of amphiphilic copolymers. The
hydrophobic micelle core, which acts as a drug reservoir, is surrounded by a hydrophilic
corona that provides a protective interface between the core and the external
environment [8, 9]. A number of other polymer and lipid-based colloidal carriers have
also been explored for improving the solubility and efficacy of various drugs [10–13].
However, an important advantage of micellar drug delivery vehicles is the unique ability
to customize both their core and coronal properties. Alterations to the composition of the
constituent copolymers can influence important performance related parameters
including micelle size, core-drug compatibility, drug loading capacity, drug release
kinetics and stability thus permitting the manipulation of the encapsulated drug's
pharmacokinetic profile and tissue distribution [14–16]. As a result of growing interest in
this promising drug delivery platform over the past two decades, several BCM-based
4
drug formulations are now in various stages of clinical evaluation with many others in
pre-clinical development [17–21]. The current status of micellar drug delivery vehicles in
clinical trial development has recently been reviewed by Matsumura [22] and Yokoyama
[23]. These achievements along with a survey of the literature using the Scopus™
database (Elsevier B.V.) that reveals more than 10000 publications on BCMs for drug
delivery necessitates reflection on our current state of knowledge and the next steps
required to truly achieve revolutionary advances in this field.
The concept of the “magic bullet”, proposed by Paul Ehrlich in 1906, envisioned a
delivery system that could “bring therapeutically active groups to the organ in question”
[24]. Due to the toxic and non-specific nature of chemotherapeutic agents, this concept
is particularly relevant to the field of cancer therapy. Certainly in oncology,
achievements of the most significant improvements in therapeutic efficacy require
minimization of drug exposure to healthy tissues and concentration of the drug at the
tumor site. In essence, realization of Ehrlich's vision would require the design of delivery
vehicles capable of carrying large quantities of poorly soluble chemotherapeutic drugs
with drug release only occurring once the vehicle has reached the target tumor.
Although the emergence of nanomedicines has served to reduce treatment-
related side effects by improving the tumor-specific delivery of chemotherapy,
corresponding improvements in therapeutic efficacy have often been modest. One
important reason for this is that they may be poorly distributed in tumors resulting in
limited exposure of cancer cells to therapeutically relevant concentrations of drug. Many
systemically administered therapeutic agents remain highly concentrated in the
periphery of the tumor and are confined to perivascular tissue due to their
heterogeneous intratumoral distribution and limited penetration through the tumor
interstitial space [25]. Enlarged intervascular distances become host to gradients in drug
concentration that may promote drug resistance and spare distant cells from treatment
that can subsequently repopulate the tumor [26]. Therapeutic efficacy is further impeded
by resistance associated with properties of the tumor microenvironment including the
presence of gradients in cell proliferation in which quiescent cells are less sensitive to
therapy, and regions of hypoxia in which cellular changes can result in drug resistance
and a more aggressive phenotype [27]. As such, there is an increasing demand for the
establishment of in vitro tissue models that more accurately replicate the complex
5
transport barriers and resistance mechanisms associated with the microenvironment of
native tumors. Three dimensional (3-D) tissue cultures, such as multicellular tumor
spheroids (MCTS), have the potential to bridge the gap between traditional in vitro and
in vivo models while providing a high-throughput platform for the rapid assessment of
therapeutic candidates [28–30]. Moreover, this approach is highly relevant in the field of
nanomedicine where the rational design and optimization of nanocarrier properties is
critical in expediting the translation of advanced drug delivery systems from conception
to clinical application.
Figure 1.1. Block copolymer micelle transport at the whole body, tissue and cellular
levels. Micelles circulate throughout the body and accumulate in tumor tissues where
they may be taken up by cancer cells.
1.2 Whole body transport and macrodistribution
Encapsulation of a drug in BCMs can increase the drug's circulation lifetime following
systemic administration, allow for site-specific drug delivery, and reduce undesirable
drug distribution to healthy tissues and organs. A thorough understanding of how the
physico-chemical properties of micelles influence the pharmacokinetics (PK) and
biodistribution of encapsulated drugs in vivo is critical to the design of new formulations
with enhanced therapeutic efficacy. It is important to note that the ability of micelle
Endosomal escape
Micelle disassembly
Endocytosis/receptor
mediated cell uptake
Extracellular drug release
6
delivery vehicles to alter the in vivo disposition and distribution of a drug is dependent
on the extent to which the drug remains encapsulated in the micelle following
administration. Micelles that function primarily as solubilizers increase the aqueous
solubility of the drug but have poor stability and/or limited drug retention following i.v.
injection. As a result, the pharmacokinetic profile and biodistribution of the drug remain
largely unchanged when compared to conventional formulations [31, 32]. In contrast,
the longer the drug remains encapsulated within the micelle, the greater the influence of
the micelle carrier on the drug's fate in vivo [33–35]. In general, the ability of a micelle
delivery system to function as a solubilizer or a true carrier depends on the stability of
the micelles in vivo and drug retention in the presence of blood components.
1.3 Thermodynamic and kinetic stability of block copolymer micelles in vivo
Micelle stability is a function of both thermodynamic and kinetic parameters and has
been discussed extensively elsewhere [15]. Briefly, the concentration at which
amphiphilic copolymer chains are thermodynamically driven to self-assemble in solution
to form micelles is known as the critical micelle concentration (CMC). Above the CMC,
the copolymer exists as micelles in equilibrium with a small population of single chains
while below the CMC, the copolymer exists in solution as single copolymer chains
referred to as unimers. Therefore, the dilution that occurs following intravenous (i.v.)
administration of micelles can present a significant challenge in terms of achieving
adequate thermodynamic stability of the delivery system in vivo. However, it has been
demonstrated that micelles can remain kinetically stable for extended periods of time
below the CMC depending on several properties of the core-forming block including its
glass transition temperature and melting temperature (if any) [36, 37].
To date, radiolabeling of micelles has been the most common method used to
investigate the influence of micelle stability on copolymer fate in vivo, though the
number of studies remains limited and merits further investigation [32, 38–40].
Batrakova et al. recently examined the pharmacokinetics and biodistribution of
radioactively labeled Pluronic® P85 (P85) administered intravenously to mice at
copolymer concentrations that, following dilution in vivo, were above and below the
7
CMC [41]. The results revealed that the circulation half-life of P85 (t1/2=60–90 h) was
dependent on the concentration of copolymer administered and thus the aggregation
state of the copolymers in vivo. The concentration of copolymer also influenced
copolymer uptake in the liver with the lowest AUC/dose ratio in the liver occurring
following administration of an intermediate copolymer concentration. Therefore, the
presence of Pluronic® copolymers as either micelles or unimers in vivo plays an
important role in determining their biodistribution. In another study, Liu et al. explored
the influence of micelle stability on the pharmacokinetics of radiolabeled PEG-b-poly(ε-
caprolactone) (PEG-b-PCL) block copolymers above and below the CMC [37]. The
pharmacokinetic profile obtained for copolymer administered i.v. below the CMC
revealed rapid elimination of the copolymer from the circulation (t1/2β=10.2 h) and a high
volume of distribution (Vd=7.6 mL). The plasma clearance profile for copolymer
administered above the CMC followed a two compartment model with a rapid
distribution phase (t1/2α=1.5 h) followed by a relatively slow elimination phase (t1/2β=30.8
h). In addition, administration of copolymer as intact micelles, yet at a concentration that
following dilution in the plasma would reach levels below the CMC (i.e.
thermodynamically unstable micelles), resulted in a more rapid distribution phase
(t1/2α=0.8 h) and elimination phase (t1/2β=16.7 h) when compared to micelles
administered above the CMC. The presence of intact micelles was observed up to 24 h
postadministration of both thermodynamically stable and unstable micelles confirming a
high degree of kinetic stability for this system likely imparted by the hydrophobic and
semi-crystalline PCL core. This study demonstrates that the selection of a core-forming
block that provides a high degree of kinetic stability is an important component in the
preparation of micelles that act as true drug carriers and remain intact for prolonged
periods in vivo. However, at high drug to material ratios the drug itself may become an
influential component of the micelle core and alter the nature and/or state of the core as
well as formulation stability.
1.4 Drug retention in vivo
Retention of hydrophobic drugs within the core of stable BCMs is critical to the
development of true site-specific delivery vehicles. The capacity of a micellar system to
solubilize and retain a drug within its core is determined by the compatibility between
8
the drug and the core-forming polymer block. The miscibility and/or degree of interaction
between the polymer and the drug affects many of the performance related
characteristics of the delivery system including stability, drug loading capacity, drug
loading efficiency, and drug release kinetics [42].
Due to the vast array of drugs each with its own unique chemical structure, no
single core forming block will be suitable for maximizing the loading and retention of all
drugs. Therefore, it is unlikely that a single micelle system can serve as a universal
delivery vehicle for all drugs. Instead, a drug should be matched with compatible
copolymer micelles containing a core–forming block tailored to the specific chemical
properties of the drug [43]. For example, Carstens et al. found that the presence of an
aromatic end group on the core-forming block improved the loading and stability of
taxanes [44]. Paclitaxel (PTX) and docetaxel (DTX) were loaded into mPEG750-b-
oligo(ε-caprolactone)5 micelles containing a hydroxyl (OH), benzoyl (Bz) or naphthoyl
(Np) group at the terminus of the polycaprolactone block. Micelles formed from
copolymers with a hydroxyl terminated core-forming block and encapsulating PTX or
DTX were the least stable and demonstrated rapid drug release compared to micelles
containing aromatic end groups. The improved performance of the copolymer micelles
containing the aromatic end groups was attributed to π–π interactions between the
taxanes and the micelle core resulting in improved core-drug compatibility. Similarly, a
micelle formulation of PTX, known as NK105, that has now reached Phase II clinical
development is composed of copolymers with PEG as the hydrophilic block and
modified poly(aspartic acid) (PAsp) as the core-forming block [45]. The PAsp block is
conjugated with 4-phenyl-1-butanol to increase core-drug compatibility and as a result,
the micelles have a drug loading capacity of 23% (w/w). Alternatively core-drug
compatibility may be improved by covalent attachment of drug molecules to the core-
forming block of the copolymer. This principle was demonstrated by Yokoyama et al.
who found that the conjugation of doxorubicin to the core forming block of (PEG-b-
P(Asp)) micelles led to greater physical encapsulation of doxorubicin in comparison to
micelles formed from the PEG-b-P(Asp) copolymer alone [46].
In order to expedite the selection of highly compatible polymer-drug pairs,
Dwan'Isa et al. demonstrated the ability to use predictive computational approaches for
estimating drug solubility and compatibility in hydrated copolymer micelles [47].
9
Copolymers of PEG and random copolyesters of ε-caprolactone (CL) and trimethylene
carbonate (TMC) were considered for the assessment of polymer-drug compatibility
using the Flory-Huggins interaction parameter (χsp). A comparison of the experimental
solubilities for 8 model drugs in 10% w/v PEG-b-P(CL-co-TMC) micelle solutions with
the predicted polymer-drug compatibilities demonstrated good agreement between the
experimental and theoretical results. This technique may offer a promising approach for
the rapid screening of drugs suitable for delivery by a specific micelle system or,
conversely, of polymers suitable for formulation of a specific drug. As illustrated in
Figure 1.2, the application of such theoretical or computational models to formulation
design may eliminate the trial and error approach that is commonly used to select
suitable material-drug pairs [42, 48].
Figure 1.2. Docetaxel molecule (yellow) surrounded by PCL2-b-PEG19 copolymer (PCL
in white, PEG in blue). Oxygen atoms are in red. Potential hydrogen bond interaction is
indicated by a dashed green line.
10
1.5 Pharmacokinetics and whole body distribution of block copolymer micelles
The PK and biodistribution of BCMs can be influenced by many factors including the
chemical nature of the copolymer materials (i.e. nature of hydrophobic and hydrophilic
blocks), characteristics of the copolymer (e.g. polydispersity, CMC), their physico-
chemical characteristics (e.g. size, size distribution, morphology, surface charge) and
stability [14–16, 49]. To some extent, variations in copolymer properties and preparation
as well as differences between animal models make it challenging to identify the
underlying criteria that may be used to predict the biodistribution of all micelle systems
[50]. Changes to any number of these properties can significantly alter the in vivo
performance of BCMs. Yamamoto et al. demonstrated the potential for long circulating
PEG-b-poly(D,L-lactide) (PEG-b-PDLLA) copolymer micelles by introducing a slight
anionic charge on the micelle surface through the conjugation of charged peptides and
selection of an appropriate micelle size with a narrow size distribution (diameter ≈30
nm) [51]. The pharmacokinetic profiles of 125I labeled Tyr and Tyr-Glu-PEG-b-PDLLA
micelles in mice were biphasic with elimination half-lives (T1/2) of 18.8 h and 17.7 h,
respectively. The biodistribution of micelles containing an anionic charge (Tyr-Glu)
displayed a significantly lower uptake into the liver and spleen when compared to
neutral Tyr-conjugated micelles suggesting the importance of the slight anionic surface
charge on non-specific organ uptake. Most notably, 25% of the total injected copolymer
dose, for both the 125I labeled Tyr and Tyr-Glu-PEG-b-PDLLA micelle formulations
remained in circulation after 24 h and only 9% in the liver and spleen compared to ~20–
30% for similar systems [52, 53]. The copolymers used in this study were synthesized
by anionic ring opening polymerization resulting in materials with a narrow
polydispersity (Mw/Mn=1.10) consequently yielding micelles having a narrow and
unimodal size distribution. This study highlights the need to prepare or select the
copolymers to be used as building blocks of micelle systems with care in order to
ensure the micelles have a narrow, monomodal size distribution and are resistant to
self-aggregation.
11
1.6 Influence of blood proteins and MPS clearance
Immediately following intravenous injection, various plasma proteins may adhere to the
delivery vehicle in a process known as opsonization. Not only may opsonization lead to
the extraction of the drug from the micelle [54], but it may also result in the elimination of
the micelles by the mononuclear phagocytic system (MPS). The MPS is comprised
primarily of the Kupffer cells and hepatocytes of the liver and the macrophages of the
spleen. These phagocytotic cells have the ability to rapidly remove micelles from the
bloodstream by recognizing specific proteins (opsonins) bound to their surface. The
susceptibility of circulating polymeric micelles to clearance via the MPS is determined
primarily by the size and surface properties of the micelle that influence the extent of
opsonization. In general, the smaller the circulating colloidal carrier, the greater is its
accumulation and uptake in the liver by hepatocytes likely due to the diameter of the
sinusoidal endothelial fenestrations which range from 100 to 150 nm [55–57]. Larger
particles (>200 nm) or particle aggregates may be removed from the circulation by the
spleen [12].
The properties of the corona-forming block also strongly influence the biodistribution
and clearance of BCMs. Various properties of the corona including the thickness,
density, charge, presence of functional groups, and surface bound targeting moieties
may impact the extent of opsonization and clearance. Presence of a non-ionic, steric
stabilizing hydrophilic polymer, such as polyethylene glycol (PEG) [58], as the corona-
forming block has been shown to prolong the circulation time of BCMs by avoiding
opsonization and subsequent clearance by the MPS [52, 59, 60]. PEG has also been
shown to reduce self-aggregation of lipid-based colloidal carriers, extending their
circulation longevity [61]. Colloidal carriers that avoid clearance by the MPS are
eventually excreted in the urine by the kidneys [32, 41, 62, 63] and/or undergo
hepatobiliary excretion in the feces [51]. For materials to be eliminated from circulation
by glomerular filtration in the kidneys, they must generally have a molecular weight of
less than 50,000 g/mol [64, 65] and have a diameter of less than approximately 5.5 nm
[66]. Since the total molecular weight and size of micelles is typically higher than this, it
may be assumed that only individual copolymer chains and free drug are eliminated via
renal excretion.
12
1.7 Passive tumor accumulation via the EPR effect
BCMs have been shown to increase drug accumulation at solid tumor sites via passive
targeting. Passive targeting relies on the enhanced permeation and retention (EPR)
effect defined by the leaky vasculature and poor lymphatic drainage commonly
associated with solid tumors that enables the extravasation and accumulation of nano-
sized delivery systems at these sites [67, 68]. Importantly an extended circulation
lifetime is required for exploitation of the EPR effect. Therefore, passive targeting relies
primarily on the size of the delivery system but is also indirectly influenced by other
physico-chemical characteristics (e.g. surface properties) that may influence the
circulation lifetime of the BCMs. Indeed, passive targeting of drugs to tumors using
colloidal systems has been reported to result in as much as a 10–50 fold increase in
drug accumulation in tumors relative to normal tissues [69]. For example, Kwon and
Kataoka reported that the PEG-b-PAsp doxorubicin conjugated micelle system
increased the tumor accumulation of doxorubicin from 0.9% of the total injected dose
per gram of tumor for free DOX to 10% for the polymer-drug conjugated micelles 24 h
following i.v. administration in tumor bearing mice [70]. Recently, Kataoka and
coworkers also reported that polymeric micelles incorporating (1,2-
diaminocyclohexane)platinum(II) (DACHPt) resulted in accumulation of 10% of the total
injected dose per gram of tumor at 24 h p.i. in an orthotopic gastric cancer model (6-fold
higher than that achieved following administration of oxaliplatin) [71]. In addition,
elevated accumulation was observed in metastatic lymph nodes (15% total injected
dose per gram of tissue) resulting in a reduction in metastatic tumor growth.
There are several physiological factors that are responsible for determining the
extent of extravasation of colloidal carriers via the EPR effect including the density,
permeability and perfusion of the tumor vasculature as well as the interstitial fluid
pressure [72, 73]. Therefore, the delivery of drugs encapsulated in colloidal carriers
depends not only on the properties of the carrier itself, but also on the physiological
features of the tumor. It should be noted, however, that tumor physiology is highly
heterogeneous on an intra- and inter-tumor basis as well as within an animal or patient
population [74, 75]. These differences can have a profound effect on the efficacy of
EPR-mediated therapies and other forms of tumor-targeted therapies [74, 76–78].
13
1.8 Tumor physiology and its role in nanoparticle delivery
1.8.1 Vascular density (density of functional vessels)
Since micelle delivery vehicles arrive at the tumor via the circulatory system, tumor
vascularization is an important factor in determining their initial distribution and ability to
exploit the EPR effect. The vascular density within a tumor is heterogeneous, with
vascular growth, perfusion or function often limited to specific regions [79]. As a result,
colloidal delivery vehicles may only be distributed to well-perfused compartments of the
tumor. In accordance with this phenomenon, Yuan et al. showed that following systemic
administration of fluorescently labeled liposomes in tumor bearing mice, the liposomes
preferentially accumulated in certain regions of the tumor and were entirely absent from
others [80]. The impact of heterogeneous delivery vehicle distribution in a tumor on
therapeutic efficacy is likely to depend on the rate of drug release and the ability of the
drug to penetrate within the extravascular space in order to reach cells located in
avascular regions of the tumor.
The extent and nature of tumor vascularization depends on several factors
including the type of tumor, its location, and its growth rate [79]. For example, Fukumura
et al. compared the microcirculation of a colon adenocarcinoma metastasized to the
liver with that of the same tumor grown subcutaneously [81]. They found that tumors
that had metastasized to the liver had significantly lower vessel density particularly in
the necrotic center in comparison to the subcutaneous tumors. The aforementioned
variations in tumor physiology may have important implications when comparing the
efficacy of formulations studied in different animal models and in the translation of
therapies from pre-clinical animal models to humans.
1.8.2 Vascular permeability
The permeability of tumor vasculature is an important determinant of BCM transport into
the tumor interstitium [82]. Extravasation of colloidal carriers from the blood into the
interstitial space occurs primarily via diffusion and convection through endothelial
fenestrae which may range in size from 200 nm to 1.2 um depending on the tumor type
[83]. A study by Dreher et al. showed that the tumor vascular permeability of
macromolecular carriers (i.e. dextrans) with molecular weights of 3.3, 10, 40, 70 kDa
14
and 2 MDa was inversely correlated with their molecular size [84]. The potential
modulation of vascular permeability as a means of increasing the extravasation of
colloidal carriers was demonstrated by Monsky et al. using vascular endothelial growth
factor (VEGF) [85]. Injection of various nanoparticles combined with the topical
administration of VEGF (10 ng/ml) to the tumor via a dorsal skin chamber was found to
double the maximum pore size (from 400 to 800 nm) in human colon carcinoma
xenografts resulting in the extravasation of larger nanoparticles when compared to
controls. Similarly, Ogawara et al. demonstrated that the degree of in vivo accumulation
of radiolabeled PEG liposomes containing DOX was greater in tumors secreting higher
quantities of vascular endothelial growth factor (VEGF), independent of the extent of
vascularization [86]. Therefore the extent of BCM tumor accumulation will be influenced
by the unique vascular permeability associated with a specific tumor model or cancer.
As a result, BCMs of appropriate size should be selected for drug delivery based in part
on the vascular permeability of the tumor in order to maximize BCM transvascular
transport via the EPR effect [83, 84, 87]. Alternatively, modulation of tumor vascular
permeability may be an effective strategy to enhance tumor-specific drug delivery and to
overcome heterogeneity associated with EPR-mediated transvascular transport [68].
1.8.3 Interstitial fluid pressure and transport in the interstitium
Interstitial fluid pressure is elevated in tumors due to an increase in fluid and plasma
protein transport into the interstitial space resulting from the highly permeable nature of
tumor vessels and the absence of adequate lymphatic drainage [88]. The resulting
reduction in hydrostatic and oncotic pressure differences across the vessel wall
presents a barrier to the transport of colloidal carriers into the interstitium [89].
Furthermore, interstitial fluid pressure may be elevated in the center of the tumor
relative to the periphery resulting in reduced extravasation of macromolecules in the
center and a convective flow which forces macromolecules towards the tumor periphery
[90, 91]. The high cell density, presence of certain extracellular matrix components and
interactions with cells also decreases the diffusion of delivery systems in the tumor
interstitial compartment [92–94]. Indeed, colloids must be below a certain size in order
to achieve significant penetration from the vascular surface into the tumor interstitium
[84]. The study by Dreher et al., introduced above, also evaluated the three-dimensional
15
penetration of differently sized (i.e. 3.3, 10, 40 and 70 kDa and 2 MDa) and
fluorescently labeled dextrans in mice bearing solid tumors using the dorsal skin fold
window chamber model and intravital laser scanning microscopy. The 10 kDa dextrans
were found to reach the same level of deep penetration as the 3 kDa dextrans but in a
longer period of time while the penetration of the 40 and 70 kDa dextrans were reported
to be similar in their penetration heterogeneity throughout the 30 minute study. Although
the permeability of larger macromolecules was decreased, the associated reduction in
the rate of clearance combined with a greater vascular AUC resulted in optimal
macromolecule molecular weights of 40 and 70 kDa with respect to total tumor
accumulation. The 2 MDa dextran was only detected in appreciable amounts up to 5 μm
from the vascular surface. The molecular weights of the dextrans (3.3, 10, 40, 70 kDa
and 2 MDa) used in this study were reported to correspond to hydrodynamic diameters
of about 4, 6, 11, 15 and 49 nm, respectively. Recently, Kataoka and coworkers
demonstrated that sub-100 nm micelles had no size dependent limitations on
penetration in tumors with a highly permeable structure, while only micelles smaller than
50 nm were capable of penetrating the interstitium of hypovascular tumors with low
structural permeability [95]. The limited transport of delivery systems away from tumor
entry sites may indeed preclude further entry of particles into the tumor [75]. Also, since
intervascular distances and avascular regions within tumors can be significant, the
limited penetration of a delivery system may prevent the eradication of cells distant from
the tumor vasculature; however this will also be dependent on the release and
distribution properties of the drug.
Importantly, in the selection of the size of a delivery system, a balance must be
achieved between optimizing blood residence time and tumor penetration. An extended
circulation lifetime is required for the delivery system to fully exploit the EPR effect: in
mice and rats it has been reported that the “area under the time-concentration curve
(AUC) must remain high for >6 h” [69]. In general, an increase in the molecular size or
hydrodynamic diameter of macromolecules or colloidal delivery systems is known to
increase their residence time in the bloodstream [66, 84, 96]. Yet, beyond a certain size,
significant uptake and accumulation in MPS organs such as the liver and spleen tends
to occur [97, 98]. Also, larger sized particles (>30–45 kDa) are retained within the tumor
tissue longer than small molecules which rapidly clear by diffusion [99, 100]. Therefore
16
the size of the nano-carrier should be adjusted accordingly in order to balance the
advantage of passive uptake at the tumor via the EPR effect with undesirable uptake in
other tissues such as the liver and spleen and tumor penetration. Achieving this balance
and selecting an optimal size may be confounded by the differences in physiology
between animals and humans that may significantly alter the observed performance of a
colloidal carrier system, such as BCMs, in humans. Some of the most promising
preclinical results for a BCM formulation were reported by Hamaguchi et al. using
NK105, a PEO-b-poly(4-phenyl-1-butanoate-L-aspartamide) [PEO-b-PPBA] block
copolymer micelle [34]. Micelles containing physically entrapped PTX were
administered to C26 tumor bearing CDF1 mice resulting in a 90-fold increase in PTX
plasma AUC and a 25-fold increase in its tumor AUC relative to free PTX. The treatment
resulted in complete tumor regression following a single injection of a PTX-equivalent
dose of 100 mg/kg. However, in phase I clinical trials, the increase in plasma AUC
following administration of NK105 was significantly less in humans (~15 fold increase)
when compared to the results of the preclinical animal studies. Translation of
formulations from pre-clinical animal models to humans is challenging owing to
differences in their MPS activity, vascular characteristics at the tumor site and tumor
physiology. Discrepancies between the physiology of animal tumor xenografts and the
physiology of native human tumors are likely to profoundly influence the performance of
colloidal delivery systems. These same differences may exist between individual
patients and highlight the need to work towards the implementation of personalized
therapies.
1.9 Active targeting
BCMs may be actively targeted by incorporating surface grafted recognition moieties
that impart an affinity for cellular receptors or components that are present on and/or
upregulated by tumor cells [101]. Ligands that have been pursued for active targeting of
BCMs to different cancers include sugar moieties such as galactose [102], epidermal
growth factor [103], folate [104], antibodies [105], and peptides [106]. In vitro cell culture
studies have demonstrated that coupling of targeting moieties to the micelle surface
results in their selective accumulation in target cells via receptor-mediated endocytosis
[104, 105, 107]. Furthermore, in vitro studies have shown that active targeting can also
17
overcome multidrug resistance and direct delivery systems to specific subcellular
compartments [108–110]. Drug formulations relying on actively targeted BCMs and
other colloidal systems have also been shown to result in significant improvements in
efficacy in pre-clinical animal models, in comparison to the non-targeted drug
formulations [111–115]. However, few studies have examined the influence of active
targeting on the cellular uptake of delivery systems within tumors in vivo [99, 116–118].
In one example, Mamot et al. demonstrated that anti-EGFR immunoliposomes
achieved a 6-fold increase in cellular uptake at the tumor site compared to nontargeted
liposomes 24 h following i.v. administration [113]. The influence of the presence of a
targeting moiety on the pharmacokinetics, biodistribution and tumor accumulation of
nanosystems is controversial [99]. In some cases active targeting of a delivery system
has been shown to increase tumor accumulation while in others the degree of tumor
accumulation remains constant [99]. For example, Kirpotin et al. showed that active
targeting of liposomes using the anti-HER2 monoclonal antibody did not result in
increased tumor localization in mice bearing HER2-overexpressing breast cancer tumor
xenografts but did lead to a greater degree of cellular internalization at the tumor site
and an increase in efficacy [117]. Similarly, Bae et al. found no significant difference in
tumor accumulation between folate-targeted and non-targeted micelles suggesting that
the EPR effect is the primary factor in tumor localization [119]. In contrast, Hussain et al.
found that the tumor accumulation of liposomes was 2 fold greater for epithelial cell
adhesion molecule targeted liposomes compared to non-targeted liposomes [114].
Overall, the influence of a targeting moiety on the in vivo pathway and fate of delivery
systems is dependent on the nature of the targeting moiety as well as its density at the
surface of the vehicle and biological factors such as tumor physiology [119]. However,
further studies are needed to fully elucidate the influence of active targeting on BCMs in
vivo. It is likely that although passive targeting is the primary mechanism for tumor
accumulation via the EPR effect, active targeting may promote retention of nano-
carriers in the tumor interstitium and increase cellular internalization.
1.10 Microdistribution: transport within an organ or tissue
Traditionally, the primary goal of drug delivery is to increase the concentration of a
therapeutic agent at the tumor site while limiting systemic exposure and toxicity to non-
18
target tissues and organs. However, in order for chemotherapeutic drugs to be effective,
they must be capable not only of reaching the tumor but also of penetrating it sufficiently
in order to expose all constituent tumor cells to a therapeutically relevant dose. There is
increasing evidence that tumor repopulation following treatment is not only mediated by
cellular mechanisms of drug resistance but also by a drug's limited penetration and
distribution within the tumor which results in insufficient elimination of malignant cells
[25, 26, 120, 121]. For chemotherapy to be curative, the drug should have access to all
cells in the tumor in lethal quantities, as certain cells that remain following treatment
may be capable of initiating tumor recurrence [25]. Due to limited tumor vascular
density, a drug may be required to penetrate > 100 µm from the nearest blood vessel to
reach distant cells [122]. This is in contrast to normal tissues in which cells usually
remain within a few cell diameters from a vessel [122]. Therefore, the extent of
penetration within the interstitial space of tumors is critical in determining the dose of
drug received by cells distant from the tumor vasculature.
The transport of drugs within the extravascular space of solid tumors is
influenced by both tumor physiology and the physicochemical properties of the drug.
Several excellent reviews on the penetration of drugs and nanomedicines in tumors can
be found elsewhere [73, 122, 123]. In general, the supply of drug to a tumor depends on
the injected dose, the drug's pharmacokinetic profile and biodistribution, tumor
vascularization, and, in the case of drugs encapsulated within colloidal delivery vehicles,
the extent of extravasation via the EPR effect. Once in the interstitium, drugs may be
transported by convection and/or diffusion [73, 124]. Convection in the interstitial space
is determined by the pressure gradient established according to intravascular hydraulic
pressure, transvascular fluid flow and the rate of resorption into the lymphatic vessels.
However, due to the lack of functional lymphatic drainage in tumors, fluid accumulates
in the interstitial space resulting in increased interstitial pressure and limited convective
flow and interstitial transport [123]. The rate and extent of diffusion through the tumor
interstitium is determined by properties of the drug including its size, charge and
structure, the extent of its cellular uptake and binding, as well as the structure and
composition of the interstitial compartment (refer to section 1.8.3 for further details) [92,
124–126].
19
Transport of the free drug through the tumor tissue occurs through extracellular
or trans-cellular pathways depending on the drug's relative aqueous and lipid solubility.
Consumption of the drug due to cellular metabolism or intra-cellular binding at the site of
action (e.g. microtubules, DNA) will reduce drug penetration [122]. In many cases, these
factors act to minimize the transport of drugs away from the vasculature, minimizing
access of the drug to distant cells.
Figure 1.3. (a) EGF-conjugated PEG-b-PVL micelles labeled with a hydrophobic
fluorescent probe, CM-DiI, via physical encapsulation. (b) Fluorescent confocal
microscopy images of EGFR-overexpressing breast cancer cells (MDA-MB-468)
incubated with non-targeted and targeted micelles for two hours at 37°C. (c) MDA-MB-
468 cells were incubated with EGFR-targeted micelles, and were subsequently counter-
stained with Hoechst 33258 for visualization of the cell nuclei. The white arrows
indicate localization of the EGFR-targeted micelles in the nucleus. (b) and (c) are taken
from Zeng et al. [108].
20
A significant limitation associated with the current methodology for assessing the
accumulation of drugs and/or delivery systems in solid tumors in vivo is the assumption
that their tumor distribution is homogeneous. For example, biodistribution studies are
commonly performed by excising and processing the entire tumor for quantitative
analysis of tumor accumulation using radioactively labeled drugs or drug delivery
vehicles. Although this kind of analysis may provide important information regarding
total tumor accumulation, it provides no insight into the spatial distribution of a drug or
carrier within the tumor. As a result, image-based methodologies have recently been
employed in order to improve our understanding of drug and drug delivery vehicle
distribution within tumors in vivo. For example, intravital laser-scanning confocal
microscopy has been used in murine tumor xenograft models via a dorsal skin fold
window chamber to assess penetration of fluorescently labeled macromolecules from
the vascular surface into the tumor interstitium [127]. Using this technique, Yuan et al.
showed that fluorescently labeled liposomes between 86 and 90 nm in size remained
near the vasculature with minimal penetration through the interstitium [80]. Following
extravasation, the liposomes formed clusters that were not significantly transported into
the interstitial space. Recently, Kataoka and coworkers have implemented an intravital
confocal microscopy technique that permits real-time analysis of the tissue penetration
and distribution of micelles in tumors and other organs [95, 129, 130]
In addition, studies by Zheng et al. have used computed tomography (CT) to
track the biodistribution and tumor accumulation of liposomes with an average diameter
of 80 nm in rabbit models [131, 132]. The CT-based assessment enabled noninvasive
and real-time visualization of the heterogeneous intratumoral distribution of the
liposomes at submillimeter resolution in VX-2 sarcoma bearing New Zealand White
rabbits [131]. As well Hoang et al. employed both the traditional method and
microSPECT/CT imaging to quantify the biodistribution of an 111Indium-labeled (111In)
PEG-b-PCL copolymer micelle formulation [132]. The 111In-copolymer was administered
intravenously to healthy and MDA-MB-231 tumor-bearing mice as micelles with an
average hydrodynamic diameter of 58 nm. Data obtained by traditional evaluation of
biodistribution was found to correlate well with data acquired using non-invasive image-
based analysis. Moreover, the intratumoral distribution of the micelles in vivo was
revealed by microSPECT/CT imaging. As shown in Figure 1.4, the intratumoral
21
Figure 1.4. a) MIP and saggital image of tissue accumulation of 111In-PEG-b-PCL
micelles 48 h p.i in an athymic BALB/c mouse bearing an MDA-MB-231 tumor xenograft
after i.v. administration of 111In-micelles. Clear visualization of the liver, spleen, bladder
and tumor was observed. b) Tissue distribution of 111In-micelles acquired via
conventional methodology and MicroSPECT/CT ROI analyses in MDA-MB-231 tumor-
bearing mice at 48 h p.i. c) Transversal slices of tumor accumulation illustrating non-
homogeneous distribution of 111In-micelles. Taken from Hoang et al. [132].
a) b)
c)
22
distribution of the micelles was found to be heterogeneous and limited primarily to the
tumor periphery. This information is critical for the development of drug delivery vehicles
with improved distribution and penetration in tumors and is otherwise unavailable
through traditional evaluation of biodistribution.
In general, there remains a limited understanding of the independent fate of drugs
and colloidal carriers in tumors. It is likely that following extravasation, rapid release of
the drug from the colloidal carrier would result in a similar distribution of drug within the
tumor as would be observed for freely administered drug. Carriers that demonstrate a
sustained release effect but remain confined to certain tumor compartments may act as
drug reservoirs that deliver the drug within the tumor over extended periods of time
even following a reduction in plasma concentration. In this scenario, the efficacy of
treatment may be highly dependent on the ability of the drug itself to penetrate within
the tumor tissue. Drug delivery vehicles that strongly retain the drug and do not
distribute within the tumor may inhibit drug penetration and treatment efficacy. For drugs
that display poor penetration in tissues, encapsulation within delivery vehicles that
enhance transport would be ideal, though this possibility has yet to be examined.
1.11 3-D tissue culture and the multicellular tumor spheroid model
Evaluating penetration in relevant 3-D in vitro models can be useful for the systematic
analysis of the influence of drug or delivery vehicle properties on tissue transport. To
date, 3-D in vitro tumor tissue models have served to enhance our understanding of
biological processes associated with tumor growth and resistance to treatment. Several
models with varying degrees of biological complexity have been implemented including
multicellular layers [133–135], natural and synthetic tissue scaffolds [136–138], and
multicellular tumor spheroids [29, 139, 140]. Of these models, spheroids, which are
growing spherical aggregates of tumor cells, are particularly appealing for their potential
use in high-throughput screening protocols and the ability to measure their growth in
response to treatment. The use of spheroids for evaluating anti-cancer therapies was
largely pioneered by Sutherland et al. via a series of systematic studies investigating
their response to radiotherapy in the early 1970’s [141–143]. The spheroid model has
also been applied in evaluating the influence of the tumor microenvironment on
fundamental cellular processes such as proliferation, metabolism, differentiation,
23
invasion and metastasis [144–146]. Furthermore, mechanisms of resistance to
chemotherapy and limitations in drug penetration have also been revealed in spheroid
cultures [147–149]. Yet, to date, the application of spheroids in the design and
evaluation of nanomedicines has been limited [150–152].
In general, spheroids contain a gradient in cellular proliferation from the surface to
the core with a greater proportion of proliferating cells located closer to the spheroid
periphery and quiescent cells located centrally. This structural organization reflects the
radial distribution of tissues surrounding tumor blood vessels in which proliferative cells
reside proximally and less metabolically active cells reside distally. In addition,
spheroids possess an extensive extracellular matrix as well gradients in pH and pO2
reflective of the acidic and hypoxic microenvironment of solid tumors and avascular
tumor nodules [153]. Together, these characteristics serve to approximate conditions of
the tumor microenvironment enabling better prediction of therapeutic response in vivo
relative to conventional 2-D cultures. In addition, the symmetrical, spherical morphology
of spheroids makes them a useful platform for evaluating the transport of drugs and
nano-carriers by assessing their penetration from the spheroid surface towards the core
[154].
1.12 Transport at the cellular level
Following extravasation of drug loaded micelles into the tumor interstitium, hydrophobic
drugs may be transported into cancer cells by diffusion following their release from
intact or disassembled micelles or by cellular internalization of the drug-loaded micelle
[155–158]. The transport of hydrophobic molecules across the cell membrane is
governed by the difference in drug concentration between the interstitial fluid and the
intracellular compartment. Therefore, the rate of release of the drug from the micelle
can be expected to influence the rate of diffusion and intracellular drug accumulation.
Alternatively, drug loaded micelles may undergo cellular internalization prior to drug
release. However, unlike small hydrophobic drug molecules, BCMs cannot diffuse
through the cell membrane but rather are internalized by endocytosis. Following cell
uptake, micelles are contained within acidic endosomes and may follow various
transport pathways including endosomal fusion with lysosomes or exocytosis
24
(recycling). Detailed reviews of the endocytotic pathways and endocytosis of
nanosystems have been recently published [159–162].
BCMs have been shown to alter the subcellular distribution of drugs. To date,
studies examining the subcellular distribution of the components of block copolymer-
based formulations (i.e. drug and copolymer) have primarily relied upon confocal
microscopy in combination with fluorescently labeled drug and/or copolymer and various
organelle specific stains [116, 163–166]. Rapoport et al. demonstrated that fluorescently
labeled Pluronic® micelles internalized by fluid phase endocytosis can alter the
distribution of a drug between acidic vesicles and the cytosol [109]. When administered
in PBS, the drug ruboxyl was not found in the nuclei of multi-drug resistant (MDR) cells,
whereas following administration of ruboxyl in Pluronic P-105 micelles, significant
accumulation was observed in the nuclei due to drug release from cytosolic vesicles.
They suggested that the permeabilization of acidic vesicle membranes by the Pluronic®
copolymer surfactant resulted in the release of the drug into the cytoplasm. The
subcellular distribution of micelles and their cargo has also been shown to be altered by
the addition of a targeting moiety to the surface of the delivery system. As shown in
Figure 1.3, Zeng et al. demonstrated that conjugation of epidermal growth factor (EGF)
to the surface of PEG-b-PVL micelles resulted in preferential perinuclear and nuclear
localization of the micelles in the epidermal growth factor receptor overexpressing cell
line MDA-MB-468 [108].
Stimuli-responsive BCMs containing surface-bound active targeting moieties have
been developed to specifically target the acidic environment of endosomes. For
example, BCMs containing drugs conjugated to the hydrophobic core by pH-labile
chemical linkers have been developed to release the drug when exposed to the acidic
environment of endosomes [167–170]. In another approach, BCMs composed of
polymers containing ionizable groups have been designed such that the micelle is
destabilized following polymer charge conversion in response to acidic conditions [107,
[171, 172]. Furthermore, some cationic polymers have demonstrated the ability to
disrupt the endosomal membrane based on the “proton sponge effect” whereby
ionizable groups become protonated and therefore act to resist the natural acidification
of endosomes leading to further influx of cytosolic protons, accompanying Cl- ions and
osmotically-driven swelling and membrane rupture [173–178]. Kataoka's group has
25
developed a polyplex triblock copolymer micelle system for the delivery of DNA to solid
tumors containing an endosomal disrupting segment composed of a poly(aspartamide)
derivative, (PAsp(DET)). The highly efficient transfection achieved by this system was
attributed to the change in protonation of (PAsp (DET)) in the acidic environment of
endosomes and subsequent disruption of the endosomal membrane and release of
DNA into the cytoplasm [173]. Notably, BCM systems have also demonstrated particular
effectiveness against MDR cell lines [171, 179]. Bae's group has developed a mixed
micelle system composed of poly(L-histidine)-block-poly(ethylene glycol) (PolyHis-b-
PEG) and poly(L-lactic acid) (PLLA)-b-PEG-folate that undergoes protonation of polyHis
below its pKb and deprotonation above its pKb. As a result, micelles are formed at high
pH, and are destabilized in acidic environments due to the increase in hydrophilicity of
the micelle core. PolyHis-b-PEG unimers induce disruption of the endosomal membrane
resulting in enhanced drug release into the cytoplasm and greater cytotoxicity towards
ovarian MDR carcinoma cells compared to pH insensitive micelles [110]. Intracellular
accumulation of drugs in resistant cancer cell lines was also increased in the presence
of Pluronic® polymers. Specifically, Kabanov's research has shown that Pluronic®
copolymers, with HLB values b19 and intermediate lengths for the PPO blocks, are
effective drug efflux modulators [180]. Burt's group also showed that PEG-b-PCL
copolymers were capable of increasing the accumulation of a P-gp substrate in Caco-2
cells [181].
1.13 Docetaxel
DTX is an anti-mitotic agent, currently administered as Taxotere® (Sanofi-Aventis) or as
a generic (Hospira), belonging to the taxane family of drugs and is approved for
treatment of cancers of the breast, prostate, lung, head and neck, and stomach [182].
DTX, like its sibling paclitaxel, has been shown to exert an anti-cancer effect primarily
by impeding mitosis via stabilization of microtubules [183]. Microtubules are an
important cellular component involved in several essential cell processes including
intracellular transport and cell division. DTX binds to the microtubule subunit β-tubulin,
inducing hyperstabilization that leads to cell-cycle arrest and apoptosis [184]. DTX has
demonstrated greater efficacy than paclitaxel in preclinical and clinical studies due to its
improved cellular uptake and increased binding and stabilization of microtubules [185].
26
In a randomized phase III study comparing docetaxel to paclitaxel in patients with
advanced breast cancer, the median overall survival, median time to progression and
overall response rate were greater for patients receiving docetaxel [186]. DTX has also
demonstrated superior response rates and median time to progression in anthracycline
and alkylating-agent resistant metastatic breast cancer relative to doxorubicin and high
activity as first-line chemotherapy [187–189].
Following i.v. administration, it has been reported that 92% of docetaxel binds with
plasma proteins [190]. Elimination occurs primarily by metabolism in the liver and
excretion into the feces via the bile [185]. Clearance from systemic circulation is
biphasic (for doses up to 70 mg/m2) with associated plasma half-lives of 5.4 minutes
and 1.4 hours following a 1 hour infusion at a dose of 70 mg/m2 in humans [185, 191].
Docetaxel is also associated with serious toxicities, most commonly neutropenia, that in
certain cases require dose reduction [192]. Taxotere® is comprised of docetaxel
dissolved in polysorbate 80 (Tween® 80), a non-ionic surfactant which has been linked
to hypersensitivity reactions [1]. In light of its poor solubility, toxicity and rapid plasma
clearance, docetaxel is an ideal candidate for encapsulation in BCMs.
1.14 Summary
BCMs have proven to be a viable and versatile platform for the development of novel
chemotherapeutic formulations with the potential to significantly improve cancer
treatment outcomes. However, effective development of BCM-based drug formulations
from pre-clinical evaluation to clinical application requires the use of improved in vitro
models which mimic mechanisms of drug resistance associated with the tumor
microenvironment. The use of 3-D tissue cultures such as multicellular tumor spheroids
for the rational design and optimization of nanosystems will serve to expedite the
translational process. Establishment of advanced techniques for evaluating the
intratumoral transport of nanosystems is required in order to better understand the
complex relationships between nano-carrier properties, intratumoral penetration and
therapeutic efficacy in the context of the tumor microenvironment. Integration of
computational, imaging-based methodologies within the field of drug delivery research
promises to provide powerful and unique insight into the transport and fate of
nanosystems in vivo with the ultimate goal of realizing their full therapeutic potential.
27
1.15 Rationale
According to the World Health Organization (WHO), cancer accounts for more than 7.6
million deaths worldwide every year [193]. In Canada, it is estimated that approximately
40% of women and 45% of men will develop cancer during their lifetimes and 1 in every
4 Canadians will die from this disease [194]. Chemotherapy is a critical component of
most cancer treatment strategies. However, its efficacy hinges on the ability of the
therapeutic agent to selectively harm cancer cells while inflicting as little damage as
possible to healthy tissues and organs. Since the primary selective mechanism of many
current cytostatic drugs relies upon their inherent capacity to exert toxicity to rapidly
proliferating cells, collateral damage to dividing cells throughout the body which are
non-cancerous is inevitable. This limits the maximum tolerable dose or may result in
side effects that necessitate dose reductions that hinder treatment efficacy or in some
cases may require discontinuation of therapy [193, 194].
Encapsulation of chemotherapeutic agents in nanoparticles such as block
copolymer micelles (BCMs) has proven to be a promising approach for reducing toxicity
to healthy tissues and organs and improving therapeutic efficacy. As such, there are
now seven BCM-based formulations undergoing clinical trial evaluation [23]. While
some of these formulations serve primarily to enhance the solubility of the drug,
advances in nanoengineering have led to the development of carrier vehicles capable of
tumor-targeted drug delivery. Yet, despite achieving increased tumor-specific drug
accumulation, realization of commensurate improvements in therapeutic efficacy has
proven elusive. Indeed, recent evidence suggests that nanoparticles may be
heterogeneously distributed in tumors, potentially limiting the exposure of cancer cells to
encapsulated drugs. For chemotherapy to be most effective the drug must be
distributed throughout a tumor in lethal quantities so as to minimize the survival of
clonogenic cells capable of initiating tumor repopulation. Therefore, the focus of this
research was to elucidate critical determinants of nanoparticle intratumoral transport
using novel in vitro and in vivo computational methodologies with the ultimate goal of
establishing rational design criteria for the development of nanomedicines with
enhanced intratumoral distribution and efficacy.
28
1.16 Hypotheses
1) The 3-D tumor microenvironment imposes substantial obstacles which limit the
effective transport and therapeutic efficacy of nanomedicines. The penetration of
nanoparticles in tumor tissues is a dynamic process wherein the rate and extent
depend on nanoparticle physicochemical properties, such as particle size, and
physiological properties of the tumor tissues.
2) Multicellular tumor spheroids can be used to evaluate the transport and
therapeutic efficacy of nanomedicines in vitro and to facilitate prediction of their
interstitial penetration and performance in vivo.
1.17 Objectives
In accordance with the hypotheses described above, the specific research objectives
were as follows:
Objective 1: To synthesize a polymeric nanomedicine containing docetaxel and to
characterize its physicochemical properties including drug loading capacity, release
kinetics and morphology.
Objective 2: To establish a 3-D tissue model and corresponding in vitro methodologies
for evaluating the performance of the nanomedicine and Taxotere®.
Objective 3: To implement computational, image-based methodologies for evaluating
the spatio-temporal penetration of nanoparticles in 3-D tissue cultures (spheroids) and
human tumor xenografts.
Objective 4: To assess the role of nanoparticle size and tumor tissue properties on the
spatio-temporal distribution of nanoparticles in spheroids and corresponding tumor
xenografts and to evaluate the “in vivo” predictive capacity of the spheroid model.
29
1.18 Overview of Thesis Chapters
The studies addressing the specific aims of this research, described above, are
described in Chapters 2 - 4 of the thesis. Chapter 2 describes the preparation and
physico-chemical characterization of PEG-b-PCL micelles as well as two methods of
incorporating DTX into the micelles, namely, physical entrapment and chemical
conjugation. This chapter also demonstrates the release kinetics of DTX from the
micelles and examines micelle morphology. Specifically, the influence of chemical
conjugation of DTX to the micelle core on drug release and micelle morphology was
reported and potential implications for drug delivery were discussed. Chapter 3
describes the performance of DTX-loaded PEG-b-PCL BCMs relative to Taxotere®
using a 3-D in vitro tumor model. Multicellular tumor spheroids were grown using colon
and cervical cancer cell lines and characterized in terms of their growth rate, cell
packing density, and tissue architecture. The cytotoxicity of BCM+DTX was compared in
monolayer and spheroid cultures in order to assess the influence of the 3-D
microenvironment on resistance to therapy. The ability of BCM+DTX and Taxotere® to
inhibit the growth of MCTS over a 30 day period was also evaluated. Resistance of
MCTS to treatment was assessed with respect to cell line-specific differences in MCTS
microenvironment and tissue structure. Chapter 4 describes the evaluation of BCM
penetration in tumor tissues using both in vitro and in vivo tumor models. A
computational methodology was developed for quantifying the relative distribution of
fluorescently labeled micelles following incubation with MCTS. In addition, a
computational procedure was established for the evaluation of BCM interstitial tissue
penetration in tumor xenografts following systemic administration. The influence of
micelle size and structural properties of the tumor tissues on micelle penetration was
evaluated. Chapter 5 summarizes the main findings of this research, presents
conclusions, and outlines potential future research.
30
2 Chapter 2
Poly(ethylene glycol)-b-poly(ε-caprolactone) Micelles Containing
Chemically Conjugated and Physically Entrapped Docetaxel:
Synthesis, Characterization, and the Influence of the Drug on
Micelle Morphology
Chapter 2
31
This chapter is a reprint of: “Andrew S. Mikhail and Christine Allen. Poly(ethylene
glycol)-b-poly(ε-caprolactone) Micelles Containing Chemically Conjugated and
Physically Entrapped Docetaxel: Synthesis, Characterization, and the Influence of the
Drug on Micelle Morphology.” Biomacromolecules 2010, 11, 1273–1280; with
permission from the American Chemical Society.
All experiments were performed by AS. Mikhail.
This chapter was written by AS. Mikhail and edited by Dr. C. Allen.
32
2.1 Abstract
Docetaxel was coupled to the hydrophobic block of poly(ethylene glycol)-b-poly(ε-
caprolactone) (PEG-b-PCL) copolymers synthesized by metal free ring-opening
polymerization. Synthesis of the copolymers and the copolymer-drug conjugate (PEG-b-
PCL-DTX) were confirmed by 1H NMR and GPC analyses. The PEG-b-PCL-DTX
conjugates had a ∼1:3 drug/copolymer ratio (w/w) and a low critical micelle
concentration in aqueous solution (14 mg/L). Encapsulation of DTX in PEG-b-PCL-DTX
micelles resulted in an 1840-fold increase in the aqueous solubility of the drug. Release
of physically encapsulated DTX from PEG-b-PCL-DTX micelles was slower than drug
release from PEG-b-PCL micelles due to the improved compatibility between DTX and
the micelle core. Core-conjugated DTX was released over the course of one week
indicating that PEG-b-PCL-DTX micelles have the capacity for sustained drug release in
the absence of physically encapsulated drug. Importantly, conjugation of DTX to the
core-forming block had a profound effect on the morphology of the copolymer
aggregates.
33
2.2 Introduction
The use of block copolymer micelles (BCMs) as nano-sized drug delivery vehicles is a
viable and versatile strategy for improving the toxicity profile and efficacy of
chemotherapeutic agents [197]. However, effective design of advanced delivery
systems of this nature demands a thorough understanding of how the physicochemical
properties of BCMs influence their performance as drug delivery vehicles [198].
Alterations to the composition of the constituent copolymers allows for the manipulation
of important properties such as the compatibility between the drug and the carrier. Good
compatibility between the drug and the core-forming block of the micelle affords high
drug-loading levels [199], improved drug solubility [47], and sustained release of the
encapsulated drug [200]. Several strategies have been employed to improve core-drug
compatibility, including optimization of the structure [34, 201, 202] and end group [44] of
the hydrophobic block and chemical conjugation of drug molecules to the core [203].
Recently, BCM morphology has been identified as an important determinant of
their performance as drug delivery vehicles [204, 205]. Specifically, the morphology of
BCMs has been shown to influence their drug-loading capacity and drug release profile
[206]. In addition, Christian et al. showed that administration of the anticancer drug
paclitaxel in filamentous block copolymer aggregates, called filomicelles, resulted in a
higher maximum tolerated dose for the drug and more sustained tumor shrinkage in
comparison to administration of the drug in spherical micelles [207]. Discher’s group has
also demonstrated that the shape of the micelle can influence delivery vehicle transport
and their interactions with phagocytic cells [208]. Therefore BCM morphology must be
carefully considered in the design and evaluation of copolymer-based drug formulations.
In many of the published studies performed to date, the morphology of BCM-
based drug formulations is largely ignored or simply assumed to be spherical. As such,
there remains a limited understanding of the factors that control the morphology of
copolymer aggregates formed from biocompatible and biodegradable copolymer
materials [209, 210]. If greater morphological control is achieved, efforts may be made
to more clearly elucidate the influence of BCM morphology on drug delivery vehicle
biodistribution and transport in vivo. In the work presented herein, the physicochemical
characteristics of biocompatible BCMs comprised of poly(ethylene glycol)-b-poly(ε-
34
caprolactone) (PEG-b-PCL) and a novel micelle-forming copolymer-drug conjugate
(PEG-b-PCL-DTX) containing docetaxel (DTX) are reported. The copolymer-drug
conjugate contains DTX that is chemically conjugated to the hydrophobic PCL core of
the micelle in order to improve the compatibility between the core and physically
entrapped DTX. The influence of chemical conjugation of DTX on drug loading, drug
release, and morphology of the micelles is evaluated. Importantly, the conjugation of the
drug to the core-forming block is not only found to have a profound effect on drug
loading but also on the morphology of the copolymer aggregates. As well, the chemical
entrapment of a drug into BCMs is shown to alter their morphology.
2.3 Experimental Section
2.3.1 Materials
α-Methoxy-ω-hydroxypoly(ethylene glycol) (CH3O-PEGOH, Mn = 2000, Mw/Mn = 1.06,
as determined by SEC) was obtained from Sigma-Aldrich (Oakville, ON, Canada) and
dried by azeodistillation of toluene. ε-Caprolactone and dichloromethane were
purchased from Sigma-Aldrich and were dried using calcium hydride. Hydrogen chloride
(1.0 M in diethyl ether), 1,6-diphenyl-1,3,5-hexatriene (DPH), succinic anhydride, N,N-
dicyclohexylcarbodiimide (DCC), 4-dimethylaminopyridine (DMAP), N,N-
dimethylformamide (DMF), diethyl ether, hexane, and acetonitrile were also purchased
from Sigma-Aldrich and used without further purification. Anhydrous docetaxel was
purchased from Jari Pharmaceutical Co. (Jiangsu, China) and 3H-labeled docetaxel was
purchased from American Radiolabeled Chemicals (St. Louis, MO).
2.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) Copolymers
PEG-b-PCL copolymers were prepared by metal-free cationic ring-opening
polymerization of ε-CL using CH3O-PEG-OH as macroinitiator in the presence of HCl,
as previously reported [37]. Typically, 2.0 g of CH3O-PEG-OH (1 mmol, Mn) 2000,
Mw/Mn ) 1.06) was added to a flame dried flask, dried by toluene azeodistillation, and
dissolved in 12 mL of dichloromethane. ε-Caprolactone (1.0 or 2.0 g; 8.76 or 17.52
35
mmol, distilled over calcium hydride) was added, followed by 3 mL of hydrogen chloride
(0.003 mmol, 1.0 M in diethyl ether). The reaction solution was stirred for 24 h at room
temperature prior to termination upon the addition of triethylamine (0.5 mL). Finally, the
triethylamine hydrochloride salt was removed by filtration, and the copolymer was
collected via precipitation in diethyl ether and hexane (50:50, v/v%) and dried under
vacuum at room temperature.
2.3.3 Addition of Carboxylic Acid Group to PCL Block of PEG-b-PCL Copolymers
PEG-b-PCL block copolymers were modified by reaction with succinic anhydride to
generate carboxyl-terminated PEG-b-PCL (PEG-b-PCL-COOH) copolymers [211].
Specifically, 0.5 g of PEG-b-PCL was placed in a flame-dried flask containing 50x molar
excess of succinic anhydride. The reactants were dissolved in 10 mL of pyridine and
heated to 60 °C for 4 h before being cooled to room temperature and allowed to stir for
20 h. Pyridine was removed in vacuo and the polymer was dissolved in acetonitrile,
dialyzed against water for 3 days, and lyophilized. The reaction yield was 72%.
2.3.4 Conjugation of DTX to PEG-b-PCL-COOH Copolymers
Conjugation of DTX to PEG-b-PCL-COOH copolymers was conducted by reaction with
equimolar equivalents of 4-dimethylaminopyridine (DMAP) and N,N′-
dicyclohexylcarbodiimide (DCC) in dry dichloromethane. The copolymer was first placed
in a flame-dried flask and dried by azeodistillation with toluene. DCC and DMAP were
then added and the reaction flask was purged with N2 prior to the addition of
dichloromethane. The flask and its contents were then cooled to 0 °C in an ice bath for
2 h and subsequently stirred for 22 h at room temperature. The reaction solution was
then filtered to remove the N,N′-dicyclohexylurea precipitate and dried under vacuum to
recover the product. Free DTX was removed by washing thoroughly in diethyl ether.
Successful conjugation of DTX to the copolymer was confirmed using gel permeation
chromatography (GPC), high performance liquid chromatography (HPLC), and nuclear
magnetic resonance (1H NMR) analyses.
36
2.3.5 Characterization of Copolymers and Copolymer-Drug Conjugates
1H NMR spectra were obtained on an Oxford 400 spectrometer (400 MHz) using CDCl3
as the solvent. Chemical shifts were reported in ppm. GPC measurements were
performed using a Waters 590 liquid chromatography system equipped with three
Waters Styragel HR 4E columns and a 410 differential refractometer detector. THF with
1% triethylamine was used as the mobile phase at a flow rate of 1.0 mL/min through the
columns at 40 °C. Narrow polystyrene standards (Polysciences Inc., Warrington, PA)
were used to generate a GPC calibration curve. The data obtained were recorded and
assessed using the Windows-based Millenium 2.0 software package (Waters Inc.,
Milford, MA). The amount of DTX conjugated to the copolymer was determined using
HPLC (Agilent series 1200) connected to a UV detector (Waters 2487).
Chromatographic separation of PEG-b-PCLDTX and DTX was achieved using an
XTerra C18 reverse phase column and acetonitrile/water (51/49, v/v%) as the mobile
phase with UV detection at 227 nm. To determine the efficiency of DTX conjugation to
the copolymer, a sample of PEG-b-PCL-DTX before and after the removal of free DTX
was dissolved in acetonitrile and the elution peak of DTX in the sample was quantified
using a calibration curve generated from a series of DTX samples of known
concentration. The extent of DTX conjugation was also determined by scintillation
counting (Beckman Coulter, LS 6500) following the conjugation of 3H-DTX to the
copolymer.
2.3.6 Micellization and Measurement of Critical Micelle Concentration (CMC)
Micelles were prepared from PEG-b-PCL copolymers of various molecular weights and
the PEG-b-PCL-DTX copolymer-drug conjugate using a dry-down method. Copolymer
or copolymer-drug conjugate was dissolved in DMF and allowed to stir overnight.
Following evaporation of DMF under N2 and vacuum, polymer films were heated to 60
°C in a water bath. Hot filtered distilled water or buffer (PBS, pH 7.4) was subsequently
added to vials containing the polymer films and thoroughly vortexed. Resulting micelle
solutions were stirred for 3 days. The CMCs of the copolymers and copolymer-drug
conjugate were determined by an established fluorescence-based method [212]. Briefly,
an aliquot of a 1,6-diphenyl-1,3,5-hexatriene (DPH) stock solution prepared in
37
chloroform was added to a series of glass vials such that the final concentration of DPH
in each solution was 1.175 mg/L. Copolymer or copolymer-drug conjugate stock
solutions were generated in chloroform and added to the vials resulting in copolymer or
copolymer-drug concentrations ranging from 0.125 to 500 mg/L. The samples were
vortexed and dried thoroughly under nitrogen. Once the films had dried, the vials were
heated to 60 °C, and 1 mL of double-distilled water, also at 60 °C, was added to each
vial. The hydrated samples were protected from light and stirred at 60 °C for 2 h and
then at room temperature overnight. The fluorescence emission of the samples was
measured at 350 nm (λex) and 430 nm (λem) with a dual-scanning microplate
spectrofluorometer (Spectra GeminiXS, Molecular Devices, Sunnyvale, CA).
2.3.7 Transmission Electron Microscopy (TEM) Analysis
Micelle morphology was observed using TEM with a Hitachi 7000 microscope operating
at an acceleration voltage of 75 kV (Schaumburg, IL). The micelle solutions (10 mg/mL)
were diluted in double-distilled water immediately prior to analysis and negatively
stained with a 1% uranyl acetate (UA) solution. The negative stain provided an electron-
dense layer resulting in reverse-contrast, negative-electron images. The samples mixed
with UA were deposited on copper grids that had been pre-coated with carbon and
negatively charged (Ted Pella Inc., Redding, CA). The final copolymer concentration on
the grid was 0.5 mg/mL. The copper grids were briefly left to stand to allow the solvent
to evaporate.
2.3.8 Determination of Micelle Size
The average hydrodynamic diameter of spherical micelles was determined by DLS
using a 90Plus Particle Size Analyzer (Brookhaven Instruments Corp., Holtsville, NY) at
an angle of 90° and temperature of 25 °C. The samples were diluted to 0.5 mg/mL prior
to DLS measurement. The effective mean diameter was obtained using the 90Plus
Particle Sizing Software. For aggregates with nonspherical morphologies the mean
micelle diameters were obtained by analysis of TEM images. The average diameters of
the copolymer aggregates in the TEM images were obtained using SigmaScan Pro
software (Jandel Scientific). Representative images were selected and the diameters of
a minimum of 20 spherical aggregates were recorded.
38
2.3.9 Evaluation of Drug Loading and Release
The level of physically entrapped and chemically conjugated DTX was quantified using
3H-DTX (0.001% (w/w) of total DTX) with subsequent analysis of samples by scintillation
counting. For drug-loading studies, DTX was stirred with the copolymer or copolymer-
drug conjugate (1:10 free DTX to copolymer or copolymer-drug conjugate containing
24% conjugated DTX (w/w)) in DMF prior to formation of the copolymer film as
described above. The micelle solutions were centrifuged (Eppendorf 5804R) at 2000
rpm for 5 min to remove drug crystals prior to determination of drug content. For the
drug release studies and evaluation of copolymer-drug conjugate hydrolysis a dialysis
method was employed. Briefly, 1 mL aliquots of micelle samples were placed in dialysis
bags (molecular weight cutoff = 1 kDa) at a copolymer concentration of 10 mg/mL and
dialyzed against 500 mL of buffer (PBS, 0.01 M, pH 7.4) that was replaced at 1, 3, 8,
and 24 h and every 24 h thereafter. At selected time intervals, 10 μL samples were
withdrawn from the dialysis bag for scintillation counting. The volume in the dialysis bag
was also measured at each time point by withdrawing and replacing the micelle solution
using a micropipette to account for changes in total sample volume.
2.3.10 Statistical Analysis
All results were obtained from data groups of n ≥ 4 and are expressed as mean ±
standard deviation (SD). A two sample t-test was used to measure statistical
significance between pairs of results, and p < 0.05 was considered to be significant.
2.4 Results and Discussion
2.4.1 Synthesis of PEG-b-PCL Copolymer and PEG-b-PCL-DTX Copolymer-Drug Conjugate
Synthesis of the diblock copolymer, PEG-b-PCL, was achieved via metal-free cationic
ring-opening polymerization. PEG-b-PCL copolymers containing two different PCL block
molecular weights of 1000 g/mol (PEG-b-PCL(2k1k)) and 2000 g/mol (PEG-b-
PCL(2k2k)) were generated by altering the ratio of ε-CL to CH3O-PEG-OH in the
reaction solution. Following polymerization of PEG-b-PCL(2k1k), the PCL block was
functionalized by attachment of a carboxylic acid terminal group to facilitate conjugation
39
of DTX. Carboxyl-terminated PEG-b-PCL (PEG-b-PCL-COOH) copolymers were then
conjugated with DTX using a well-established coupling mechanism described above
and previously reported [213]. The synthetic procedures employed for the preparation of
PEG-b-PCL copolymers and the PEG-b-PCL-DTX conjugate are outlined in Figure 2.1.
Figure 2.2 includes the 1H NMR spectra for the copolymer, DTX, and the PEG-b-PCL-
DTX copolymer-drug conjugate with corresponding peak assignments. As has been
reported for PTX, a taxane similar in structure to DTX, hydroxyl groups at the 2′, 7, and
10 positions are suitable sites for conjugation [214, 215]. However, reaction occurs
preferentially at the 2′ position due to the limited reactivity of the 7 and 10 positions
[216, 217]. The disappearance of the resonance at δ = 4.62 ppm in the DTX spectrum
corresponds to a change in resonance of the proton at the carbon 2′ position, confirming
successful conjugation of the drug to the copolymer.
Figure 2.1. Synthesis of (a) PEG-b-PCL, (b) PEG-b-PCL-COOH, and (c) PEG-b-PCL-
DTX
40
Figure 2.2. 1H NMR spectra and corresponding peak assignments for PEG-b-PCL (a)
and PEG-b-PCL-COOH (b) copolymers. 1H NMR spectra of DTX (c) and PEG-b-PCL-
DTX (d).
Table 2.1 Melting temperature (Tm), critical micelle concentration (CMC), morphology,
diameter, molecular weight (Mn), and polydispersity (Mw/Mn) of copolymers and
copolymer-drug Conjugate.
aDiameter of spherical micelles as determined by TEM measurements. bDiameter
determined by DLS as an average of five measurements over a 7 day period (n = 3).
41
Table 2.2. GPC retention times (Rt) of the copolymers and copolymer-drug conjugate
The resonance of this proton is likely shifted to 5.3 ppm. The chemical shift and peak
assignments are as follows: peaks at 1.38 ppm (2H, CO-CH2-CH2-CH2-CH2-CH2), 1.6
ppm (4H, CO-CH2-CH2-CH2-CH2-CH2), 2.3 ppm (2H, CO-CH2-CH2-CH2-CH2-CH2), and
4.1 ppm (2H, CO-CH2-CH2-CH2-CH2-CH2) were assigned to the PCL block, whereas the
peaks at 3.38 ppm (3H, CH3-O), and 3.65 ppm (4H, O-CH2-CH2-O) were assigned to
the PEG block. The appearance of a peak at 2.65 ppm (4H, CO-CH2-CH2-COOH)
indicates the successful addition of the carboxylic acid functional group to the PCL
block. Ratios of the hydrophobic block to the hydrophilic block were determined from the
relative intensities of the PCL proton signal at 2.3 ppm and the PEG proton signal at
3.65 ppm.
Figure 2.3. GPC chromatograms of (a) PEG-b-PCL(2k1k); (b) PEG-b-PCL(2k1k)-DTX;
(c) PEG-b-PCL(2k2k).
2.4.2 Physico-Chemical Properties of PEG-b-PCL and PEG-b-PCL-DTX Copolymer and Copolymer-Drug Conjugates
The CMC represents the concentration at which micellization occurs in aqueous
solution and provides an indication of the thermodynamic stability of the micelles. The
CMC of the PEG-b-PCL copolymer was reduced from 20.6 to 14.0 mg/L following the
Retention time (Rt), min
42
conjugation of DTX. Because the micelles are subjected to significant dilution in the
blood, a low CMC is important to promote stability following i.v. administration.
However, several other factors contribute to maintaining micelle stability at
concentrations below the CMC [15]. Table 2.1 includes a summary of the physical and
thermal properties of the copolymers and copolymer-drug conjugate.
Dynamic light scattering at a fixed scattering angle (90°) cannot be used to
determine the diameter of non-spherical micelles since the correlation function analysis
is based on the assumption that the particles are spherical. Therefore, the diameter of
spherical micelles in samples containing both spheres and rods was determined by
analysis of TEM images. DLS measurements are reported for micelle solutions that
contain only spherical aggregates.
Figure 2.4. Mean diameter of PEG-b-PCL(2k1k)-DTX micelles at a concentration of 10
mg/mL (equivalent to 2.5 mg/mL DTX), as measured by DLS over a period of one week.
Successful conjugation of DTX to the copolymer was also confirmed by GPC. The
reduction in retention time (Rt) and shift in the GPC chromatogram of the PEG-b-
PCL(2k1k)-DTX conjugate relative to the chromatogram of the PEG-b-PCL(2k1k)
copolymer indicates an increase in the copolymer molecular weight (Mn) following the
attachment of DTX (Table 2.2. GPC retention times (Rt) of the copolymers and
copolymer-drug conjugate, Figure 2.3). Both PEG-b-PCL copolymers and PEG-b-
PCL(2k1k)-DTX copolymer-drug conjugate possess a monomodal molecular weight
distribution and low polydispersity (Mw/Mn; Table 1). The stability of PEG-b-PCL(2k1k)-
DTX micelles was assessed by DLS over a period of one week (Figure 2.4). No
43
significant change in the mean diameter of the micelles was observed indicating good
stability and an absence of secondary particle aggregation.
2.4.3 Characterization of the Copolymer-Drug Conjugate and Drug-Loaded Micelles.
Docetaxel was conjugated to the PCL block of PEG-b-PCL(2k1k). HPLC analysis
revealed that 89% of PEG-b-PCL(2k1k) was coupled to DTX (mol %). Unreacted PEG-
b-PCL(2k1k) was not removed. The final product contained 24% DTX (wt%). It was
determined that <1% (w/w) unreacted DTX remained following purification of the
copolymer-drug conjugate. Although copolymer micelle concentrations of up to 50
mg/mL (equivalent to ∼12 mg/mL docetaxel) were generated, a 10 mg/mL PEG-b-
PCL(2k1k)-DTX concentration (equivalent to ∼2.4 mg/mL docetaxel) was selected for
further investigation based on results demonstrating the stability of the micelles formed
from the copolymer-drug conjugate at this concentration over one week (i.e., clear
solution, constant particle size, Figure 2.4)). This concentration represents an ∼480-fold
increase in the water solubility of DTX (DTX aqueous solubility: 5.0 μg/mL [218]).
2.4.4 Micelle Morphology
The morphology of BCMs in aqueous solution is controlled by a number of properties
including the nature of the copolymer blocks, ratio of hydrophobic to hydrophilic block
length, and total copolymer molecular weight [219]. A general model describing the free
energy of a copolymer molecule in a micelle, as put forth by Halperin and Alexander
[220], includes the following three components: interfacial tension (Fint), steric repulsions
between adjacent coronal polymer chains (Fcorona), and core chain deformation (Fcore).
These terms may be combined to approximate the free energy per chain in a single
micelle (Fmicelle = Fint + Fcorona + Fcore). This model has been used to explain the
morphologies produced in aqueous solution by block copolymers of varied compositions
[209, 221, 222].
In the present study, the morphology of aggregates formed from the PEG-b-PCL
copolymers and the PEG-b-PCL(2k1k)-DTX copolymer-drug conjugate were observed
by TEM (Figure 2.5). The PEG-b-PCL(2k1k) copolymer formed spherical aggregates
∼10 nm in diameter and rod-like aggregates ranging in length from 0.3 to 1.8 μm. In
44
contrast, the PEG-b-PCL(2k1k)-DTX copolymer-drug conjugate formed only spherical
aggregates. The rod to sphere transition was also apparent when aggregates formed
from varying ratios of PEG-b-PCL(2k1k) and PEG-b-PCL(2k1k)-DTX were found to
contain a larger population of spheres when the PEG-b-PCL(2k1k)-DTX content was
increased. Interestingly, similar to PEG-b-PCL(2k1k) but in contrast to PEG-b-
PCL(2k1k)-DTX micelles, aggregates of PEG-b-PCL(2k2k) contained rod-like
morphologies, suggesting that the molecular weight of the hydrophobic block alone
(both PEG-b-PCL(2k2k) and PEG-b-PCL(2k1k)-DTX have similar Mn values) was not
responsible for generating the pure spherical morphology of the PEG-b-PCL(2k1k)-DTX
micelles. Furthermore, the morphology of PEG-b-PCL(2k1k) and PEG-b-PCL(2k2k)
copolymer micelles (a mixed population of rods and spheres) was not significantly
altered following physical entrapment of DTX in the micelle core. Therefore, only when
DTX was chemically conjugated to the micelle core was an alteration in micelle
morphology observed.
The morphology of copolymer aggregates containing a crystalline core is
determined by the balance of entropic forces that arise from the stretching of corona
chains and an enthalpic component associated with core chain folding [223, 224]. In the
case of brush micelles where the corona forming block is longer than the core forming
block, spherical micelles are generally favored due to the larger area available per
corona chain relative to rod or lamellar aggregate morphologies. However, an increase
in the number of crystalline folds in the core leads to a reduction in corona chain
crowding thus favoring rod-like and lamellar aggregate morphologies. For example, Du
et al. examined the influence of systematically increasing the PCL block length and,
presumably, the amount of core chain folding in PEG-b-PCL micelles while maintaining
a constant PEG chain length and observed the formation of spherical, cylindrical, worm-
like, and lamellar aggregates, respectively [225]. In a study by Zhang et al., the
crystallization tendency of the core forming block in copolymer micelles containing PEG
as the hydrophilic block and either crystalline poly(caprolactone-b-L-lactide) (P(CL-LLA))
or amorphous poly(caprolactone-b-D,L-lactide) (P(CL-DLLA)) as the hydrophobic core
forming block was demonstrated to be an important determinant of micelle morphology
[226].
45
Figure 2.5 TEM images of micelles formed from PEG-b-PCL(2k1k)-DTX and PEG-b-
PCL(2k1k) in molar ratios of 9:1 (a), 7:3 (b), 3:7 (c), 1:9 (d), and PEG-b-PCL (2k2k) (e).
Micelles containing physically entrapped DTX (2% w/w): PEG-b-PCL(2k1k) + DTX (f),
PEG-b-PCL(2k2k) + DTX (g), and PEG-b-PCL(2k1k)-DTX + DTX (h). The concentration
of all copolymers and the copolymer-drug conjugate was 10 mg/mL.
The authors suggested that the high enthalpy of crystallization of the P(CL-LLA) core-
forming block was the driving force for the observed sphere to rod transition. In the
present study, PEG-b-PCL(2k1k) micelles were found to undergo a rod to sphere
transition upon chemical conjugation of DTX to the core forming block of the micelle. It
is postulated that the conjugation of the drug to the micelle core disrupts the
semicrystalline structure of PCL, thereby inhibiting core chain folding and leading to the
formation of spherical aggregates as opposed to the mixed sphere and rod
morphologies of the PEG-b-PCL(2k1k) micelles. However, further examination of the
state of the micelle core is required to support this mechanism. In agreement with the
current study, Elsabahy et al. did not observe a DTX-induced transition in the
46
morphology of the PEG-b-PCL aggregates when DTX was loaded into PEG-b-
poly(butylene oxide) (PEG-b-PBO) and PEG-b-poly(styrene oxide) (PEG-b-PSO)
micelles [227]. A spherical morphology was observed for the PEG-b-PBO micelles and
a rod morphology for the PEG-b-PSO micelles before and after drug loading.
2.4.5 Drug Loading
DTX loading capacity of PEG-b-PCL(2k1k), PEG-b-PCL(2k2k), and PEG-b-PCL(2k1k)-
DTX micelles was compared. The highest drug-loading capacity was observed for PEG-
b-PCL(2k1k)-DTX micelles at all copolymer and copolymer-drug conjugate
concentrations (Figure 2.6).
The superior drug-loading capacity of PEG-b-PCL(2k1k)-DTX micelles reflects an
improvement in core-drug compatibility following conjugation of DTX to the PCL block.
This phenomenon may be attributed to the significant increase in core hydrophobicity
and the presence of π-π interactions between the core-conjugated drug and the free
drug [201]. This is in agreement with a study by Carstens et al. that found the presence
of an aromatic end group on the core-forming block of mPEG750-b-oligo(ε-
caprolactone)5 improved the loading capacity of DTX in the micelles [44]. Similarly,
Yokoyama et al. found that the conjugation of doxorubicin to the core forming block of
(PEG-b-P(Asp)) micelles led to greater physical encapsulation of doxorubicin in
comparison to micelles formed from the PEG-b-P(Asp) copolymer alone [46].
The length of the core forming block also influenced drug loading at a high
copolymer concentration (30 mg/mL) as the PEG-b-PCL(2k2k) copolymer displayed a
higher loading capacity than PEG-b-PCL(2k1k). Chemical and physical entrapment of
DTX in PEG-b-PCL(2k1k)-DTX copolymer-drug conjugate micelles resulted in a total
drug-loading capacity of 3.15 mg/mL DTX equiv. (0.75 mg/mL physically entrapped DTX
+ 2.4 mg/mL chemically conjugated DTX) at a PEG-b-PCL(2k1k)-DTX concentration of
10 mg/mL and up to 9.2 mg/mL DTX equiv. (2 mg/mL physically entrapped DTX + 7.2
mg/mL chemically conjugated DTX) at a PEG-b-PCL(2k1k)-DTX concentration of 30
mg/mL. Therefore, this formulation strategy affords a 630- to 1840-fold increase in the
aqueous solubility of DTX.
47
Figure 2.6. Physical entrapment of DTX in BCMs formed from PEG-b-PCL(2k1k), PEG-
b-PCL(2k2k), and PEG-b-PCL(2k1k)-DTX at various copolymer and copolymer-drug
conjugate concentrations (n = 5). *Denotes statistically significant difference (p < 0.05).
2.4.6 Drug Release
Drug release from PEG-b-PCL(2k1k)-DTX micelles containing only chemically
conjugated DTX is expected to occur via hydrolysis of the ester bond joining DTX to the
PCL block. An initial rapid release of DTX was observed from the micelles followed by
sustained drug release over the course of one week (Figure 2.7). The apparent burst
release observed during the first 3 h represents the release of free DTX present as a
result of hydrolysis that occurred during the 3 days of stirring that is part of micelle
preparation. HPLC analysis revealed that 48.7% of the total conjugated DTX initially
present in the PEG-b-PCL(2k1k)-DTX micelles is cleaved from the copolymer during
this time (data not shown). Due to the large quantity of DTX solubilized by this system
(2.4 mg/mL), the copolymer-drug conjugate micelles may be capable of delivering
therapeutically relevant doses without the need for supplementary physical entrapment
of DTX. Because drug release occurs via hydrolysis, it is reasonable to suggest that the
rate of drug release will depend on the ability of water to penetrate the micelle core (i.e.,
the length and nature of the hydrophobic block) and the stability of the micelles in vivo.
Co
nce
ntr
atio
n o
f D
TX
, m
g/m
L
Polymer or polymer-drug conjugate concentration, mg/mL
48
Therefore, it may be possible to modulate the rate of drug release by altering the length
and chemical structure of the core-forming block.
The release of physically entrapped DTX from the micelles was assessed under
sink conditions (Figure 2.8). The drug release profile of all micelle solutions displayed
rapid initial release of DTX followed by extended release over a 24 h period. PEG-b-
PCL(2k1k)-DTX micelles displayed the slowest release of physically entrapped DTX
compared to PEG-b-PCL(2k2k) and PEG-b-PCL(2k1k) micelles likely due to superior
compatibility between free DTX and the micelle core containing chemically bound DTX.
Figure 2.7. Release of chemically conjugated DTX from PEG-b-PCL-DTX micelles at
10 mg/mL (2.4 mg/mL DTX equivalent) in PBS buffer (pH = 7.4), n = 4.
Because the PEG-b-PCL(2k1k)-DTX micelles were found to be stable (i.e., they did not
aggregate or degrade significantly based on size measurements by DLS) in PBS buffer
at pH 7.4 for at least one week, the release of DTX from the micelles is likely to occur
primarily by diffusion. Furthermore, a longer hydrophobic block may provide greater
protection against both hydrolysis of the ester bond between PCL and DTX and a
greater barrier against DTX diffusion, resulting in a slower rate of drug release.
Rele
ase
of
che
mic
ally
co
nju
ga
ted
DT
X,
%
Time, days
49
Figure 2.8. Drug release profile of physically entrapped DTX from copolymer micelles
formed from PEG-b-PCL(2k1k) ( ), PEG-b-PCL(2k2k) ( ), and PEG-b-PCL(2k1k)-
DTX ( ) at a concentration of 10 mg/mL (2% free DTX w/w of physically entrapped
DTX to copolymer or copolymer-drug conjugate). * and ** denote a statistically
significant difference (p < 0.05) between PEG-b-PCL(2k1k) and PEG-b-PCL(2k2k) and
PEG-b-PCL(2k1k)-DTX and both PEG-b-PCL(2k1k) and PEG-b-PCL(2k2k),
respectively. “Release of physically entrapped DTX” refers to the amount of DTX
released relative to the total physically entrapped DTX initially present and does not
include DTX released due to the hydrolysis of PEG-b-PCL(2k1k)-DTX during the
experiment.
2.5 Conclusions
DTX was coupled to the hydrophobic block of PEG-b-PCL copolymers synthesized by
metal free ring-opening polymerization. PEG-b-PCL(2k1k)-DTX copolymer-drug
conjugates formed micelles in aqueous solution at a CMC significantly lower than that of
PEG-b-PCL(2k1k). Analysis of drug loading via physical entrapment of DTX within the
copolymer-drug conjugate micelles revealed a maximum increase in DTX solubility of
1840-fold. Release of physically encapsulated DTX from PEG-b-PCL(2k1k)-DTX was
rapid, though slower than drug release from PEG-b-PCL(2k1k) micelles, suggesting that
this formulation may act primarily as a drug solubilizer. However, release of the core-
Rele
ase
of
ph
ysic
ally
en
trapp
ed
DT
X,
%
Time, h 25
50
conjugated drug was slower (90% released over 1 week), demonstrating the copolymer-
drug conjugate micelle’s capacity for sustained release of DTX. The morphologies of the
BCMs were influenced by the presence of chemically conjugated DTX in the micelle
core. Block copolymer aggregates adopted a spherical morphology following the
attachment of DTX to the PCL core forming block rather than a mixed population of rod-
and sphere-like aggregates as was observed for copolymer micelles in the absence of
core conjugated DTX. Finally, an increasing population of BCMs with a rod-like
morphology was observed as the ratio of copolymer to copolymer-drug conjugate was
increased. In light of recent evidence demonstrating the influence of BCM morphology
on drug loading, circulation longevity and tissue penetration, these findings demonstrate
the importance of characterizing the morphology of similar systems in the absence and
presence of drug.
2.6 Acknowledgements
This research is funded by an NSERC operating grant to C. Allen. A. Mikhail is also
grateful to NSERC for a post graduate scholarship.
51
3 Chapter 3
Cytotoxicity and Growth Inhibitory Effect of Docetaxel-loaded
Block Copolymer Micelles and Taxotere® in Monolayer and
Spheroid Cultures
Chapter 3
52
The following procedures were performed by AS Mikhail: Synthesis and characterization
of PEG-b-PCL copolymers, formulation of BCM+DTX, TEM imaging, drug release
assays, histological analyses, copolymer biocompatibility assay, the clonogenic assay,
portions of the APH assay validation, establishment of spheroid growth protocol and all
data analysis and writing.
The following procedures were performed by S. Eetezadi under the guidance of AS.
Mikhail: Measurement of spheroid packing density and growth rate, the APH assay,
growth inhibition assay and illustration of Figure 3.1 and Figure 3.2.
Immunohistochemical staining was performed by the Pathology Research Program
(PRP) at the University Health Network (Toronto, ON).
This chapter was written by AS. Mikhail and edited by Dr. C. Allen.
53
3.1 Abstract
While 3-D tissue models have received increasing attention over the past several
decades in the development of traditional anti-cancer therapies, their potential
application for the evaluation of advanced drug delivery systems such as
nanomedicines has been largely overlooked. In particular, new insight into drug
resistance associated with the 3-D tumor microenvironment has called into question the
use of monolayer cultures for prediction of in vivo anti-tumor activity. In this work, a
series of complementary assays was established for evaluating the in vitro efficacy of
docetaxel (DTX) -loaded block copolymer micelles (BCM+DTX) and Taxotere® in 3-D
multicellular tumor spheroid (MCTS) cultures. Spheroids were found to be significantly
more resistant to treatment than monolayer cultures in a cell line dependent manner.
Limitations in treatment efficacy were attributed to mechanisms of resistance associated
with properties of the spheroid microenvironment. DTX-loaded micelles demonstrated
greater therapeutic effect in both monolayer and spheroid cultures in comparison to
Taxotere®. Overall, this work demonstrates the use of spheroids as a viable platform for
the evaluation of nanomedicines in conditions which more closely reflect the in vivo
tumor microenvironment relative to traditional monolayer cultures. By adaptation of
traditional cell-based assays, spheroids have the potential to serve as intermediaries
between traditional in vitro and in vivo models for high-throughput assessment of
therapeutic candidates.
54
3.2 Introduction
Resistance to chemotherapy is not only facilitated by processes at the cellular level, but
also by mechanisms associated with the tumor microenvironment [228, 229]. In growing
tumors, the heterogeneous architecture of the vasculature, irregular blood flow, large
intervascular distances and nature of the extracellular matrix limit the access of cells to
oxygen, nutrients, and systemically administered therapies [122, 123]. Within the tumor
interstitium, gradients in the rate of cell proliferation are established wherein rapidly
dividing cells reside close to the tumor vasculature and quiescent cells are situated
deep within the extravascular space. However, many anti-neoplastic agents exert
limited toxicity against slowly- or non-proliferating cells and are less effective in the
hypoxic and acidic microenvironments of poorly perfused tissues [27, 230]. These
therapeutic limitations are exacerbated by high interstitial fluid pressure which inhibits
the penetration of chemotherapeutic agents through the tumor interstitium by limiting
convective transport [73]. As a result cells located far from blood vessels may be less
sensitive to treatment and also be exposed to sub-therapeutic drug concentrations.
The use of in vitro cell culture is critical for rapid identification of drug candidates
and for investigating mechanisms of drug efficacy at the cellular and molecular levels. In
contrast to in vivo tumor models, in vitro cultures are better suited for systematic studies
of formulation parameters in a highly controlled environment. However, cytotoxic effects
observed in monolayer cultures often fail to translate into similar effects in vivo [231,
232]. This is due to the inherent inability of conventional cultures to account for
mechanisms of drug resistance and transport restrictions associated with the 3-D tumor
microenvironment. As such, there is increasing interest in applying in vitro tissue models
that enable rapid, high throughput screening of drug formulations for selection of lead
candidates to move forward for evaluation in vivo [28, 139, 233].
As depicted in Figure 3.1, 3-D tissue cultures such as multlicellular tumor
spheroids (MCTS) serve as an intermediary between the oversimplified structure of
monolayer cultures and the highly complex nature of in vivo tumors. MCTS cultures
possess a complex network of cell-cell contacts and advanced extracellular matrix
development, as well as pH, oxygen, metabolic and proliferative gradients analogous to
the microenvironmental conditions in poorly vascularized and avascular regions of solid
55
tumors [234–236]. In general, a spheroid is comprised of an outer region of proliferating
cells which surrounds intermediate layers of quiescent cells and, if the spheroid is large
enough, a necrotic core. This arrangement parallels the radial organization of tissues
surrounding tumor blood vessels. To date, a variety of 3-D in vitro tissue models have
been applied for the study of anticancer therapies including natural and synthetic tissue
scaffolds [237, 238], multicellular layers [25, 125, 134, 239, 240], and multicellular tumor
spheroids [29, 135, 237]. MCTS are particularly relevant in the development of
nanomedicines since their penetration in 3-D tumor tissues may be restricted by
properties of the delivery vehicle. To date, however, there remain limited examples of
the use of MCTS for the evaluation of nanomedicines [150–152, 168, 241].
DTX is a potent chemotherapeutic agent that is currently administered as
Taxotere® (Sanofi-Aventis) and used for treatment of cancers of the breast, prostate,
lung, head and neck, and stomach [182]. However, Taxotere is known to be
associated with side effects that can require reductions to the administered dose [192].
Encapsulation of chemotherapeutic agents within biocompatible nanosystems such as
block copolymer micelles (BCMs) has proven to be a promising approach for mitigating
the burden of toxicity on normal tissues and increasing tumor-specific drug
accumulation [198]. In this study, traditional cell-based assays are adapted and applied
in a systematic and complementary manner for the evaluation of a DTX-loaded
nanomedicine and Taxotere® in both monolayer and MCTS cultures (Figure 3.2).
Figure 3.1. Intermediate in complexity, 3-D cultures permit the systematic, high-
throughput assessment of formulation properties in a controlled environment that
approximates important components of in vivo tumors in the absence of complex
parameters which may confound data interpretation.
56
Figure 3.2. Schematic representation of assays used for analysis of formulation efficacy
in spheroids.
3.3 Materials and Methods
3.3.1 Materials
Methoxy poly(ethylene glycol) (CH3O-PEG-OH; Mn = 5000, Mw/Mn = 1.06) was
obtained from Sigma-Aldrich (Oakville, ON, Canada). ε-Caprolactone and
dichloromethane (Sigma-Aldrich) were dried using calcium hydride prior to use.
Hydrogen chloride (HCl) (1.0 M in diethyl ether), N,N-dimethylformamide (DMF), diethyl
ether, hexane and acetonitrile were used without further purification. Alexa Fluor 488
(AF488) carboxylic acid succinimidyl ester was purchased from Molecular Probes
(Eugene, OR). The hypoxia marker, EF5, and Cy5-conjugated anti-EF5 antibody were
purchased from the Department of Radiation Oncology, University of Pennsylvania,
(Philadelphia, PA). DTX was purchased from Jari Pharmaceutical Co. (Jiangsu, China).
3.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) copolymers
PEG-b-PCL copolymer was prepared as previously described [242]. Briefly, CH3O-PEG-
OH was used to initiate the ring-opening polymerization of ε-CL in the presence of HCl.
The reaction was carried out for 24 h at room temperature prior to termination by
addition of triethylamine (TEA) and precipitation in diethyl ether and hexane (50:50,
v/v%). The product was dried under vacuum at room temperature.
57
3.3.3 Preparation and characterization of BCM+DTX
PEG-b-PCL copolymer and DTX were dissolved at a copolymer:drug weight ratio of
20:1 in DMF and stirred for 30 min. DMF was evaporated under N2 at 30oC and residual
solvent was removed under vacuum. Dry copolymer-drug films were then heated to 60
°C in a water bath prior to the addition of PBS buffer (pH 7.4) at the same temperature.
Resultant micelle solutions were vortexed, stirred for 24 h at room temperature and
finally sonicated (Laboratory Supplies Co., NY) for 1 h. Undissolved drug crystals were
removed by centrifugation at 4400 g for 12 min (Eppendorf 5804R). The final copolymer
concentration was 10 mg/mL. The amount of physically entrapped DTX in BCM
samples was determined by HPLC analysis (Agilent series 1200) with UV detection
(Waters 2487) at a wavelength of 227 nm. An XTerra C18 reverse phase column was
employed with ACN/water (60/40, v/v%) as the mobile phase. Drug loading was
quantified using a calibration curve generated from a series of DTX standards.
3.3.4 Sizing of BCM+DTX
The average hydrodynamic diameter of the BCMs was determined by dynamic light
scattering (DLS) using a 90Plus Particle Size Analyzer (Brookhaven Instruments Corp.,
Holtsville, NY) at an angle of 90° and temperature of 25 °C. The samples were diluted to
a copolymer concentration of 0.5 mg/mL prior to measurement. Analysis was performed
using the 90Plus Particle Sizing Software.
3.3.5 Transmission Electron Microscopy (TEM)
BCMs were observed by TEM using a Hitachi 7000 microscope operating at an
acceleration voltage of 75 kV (Schaumburg, IL). Samples were diluted in double distilled
water immediately prior to analysis and negatively stained with a 1 % uranyl acetate
(UA) solution. The final copolymer concentration was 0.5 mg/mL. The samples were
then deposited on copper grids that had been pre-coated with carbon and negatively
charged (Ted Pella Inc., Redding, CA) and briefly air-dried prior to analysis.
3.3.6 Drug Release
The release of DTX from BCMs and Taxotere® was analyzed using a dialysis method.
Aliquots (1 mL) of BCM+DTX, DTX in DMSO and Taxotere® were placed in individual
58
dialysis bags (MWCO 2 kDa, Spectra/Por, Rancho Dominguez, CA) and dialyzed
against 2 L of PBS at pH 7.4 in an incubator at 37oC ensuring that sink conditions were
maintained. At selected timepoints, 50 µL samples were withdrawn from the dialysis
bags and DTX content was measured by HPLC as described above. The volume in the
dialysis bags was also measured at each time point by withdrawing the samples,
measuring their mass and returning them in order to account for possible dilution or
concentration of the samples over time.
3.3.7 Tissue culture and growth of MCTS
Human cervical (HeLa) and colon (HT29) (ATCC, Manassas, VA) cancer cells were
incubated at 37 °C and 5% CO2 in DMEM containing 1% penicillin-streptomycin and
supplemented with 10% FBS. For growth of MCTS, cells were suspended using trypsin-
EDTA and seeded onto non-adherent 96-well round-bottomed Sumilon PrimeSurface™
plates (MS-9096U; Sumitomo Bakelite, Tokyo, Japan) in 200 µL of media per well.
During growth, 50% of the media was exchanged every other day. MCTS were grown
until they reached ~ 500 µm in diameter before use.
3.3.8 Immunohistochemical analysis of MCTS
MCTS were washed in PBS and transferred onto a vinyl specimen mold (Cryomold®,
Tissue-Tek, Sakura Finetek, CA) prior to addition of Tissue-Tek® O.C.T. compound
(Sakura Finetek, Torrance, CA). MCTS were then submersed in an isopentane bath
cooled by liquid nitrogen, cut into 5 μm thick sections using a microtome and mounted
on glass slides. Histological staining was conducted for the identification of cellular
proliferation (Ki67) and stained with hematoxylin and eosin (H&E). For identification of
hypoxic regions, MCTS were incubated with 0.5 mM EF5 and soaked in PBS prior to
cryosectioning. EF5 in the MCTS sections was identified by binding with cyanine-5-
conjugated mouse anti-EF5 (1/50) antibody. The positive signal distribution for Ki67 was
analyzed using a customized MATLAB® algorithm, as described previously [243].
Briefly, images containing Ki67-stained MCTS sections were thresholded for positive
color intensity. Using a distance map, signal intensities were summed within three
concentric regions of equidistant thickness, each equivalent to 1/3 of the MCTS radius:
59
periphery, intermediate and core. The distribution of Ki67 positive signal is expressed as
a percentage of total positive signal in the MCTS section.
3.3.9 Measurement of MCTS Growth
Spheroids were imaged using a light microscope with a 10x objective lens (VWR
VistaVision TM) connected to a digital camera (VWR DV-2B). The diameter and volume
of MCTS were determined by measuring their cross-sectional area using an automated
image analysis macro developed for use with the ImageJ software package (NIH,
Bethesda, MD, Version 1.44m). The automated method was validated by comparison to
manual determination of spheroid diameter and volume (Appendix 1, Figure A1). For
the automated method, images were converted into 8-bit greyscale and the perimeter of
an individual MCTS was recognized by an automated threshold function and the image
converted to a 2-D mask. The area of the spheroid mask was recorded, applying an
image of known scale as calibration. Finally, the volume of the MCTS was calculated by
assuming a spherical shape as follows: V=4/3*π*(d/2)3. Data was fit using the Gompertz
equation for tumor growth as follows: V(t)=V(0)exp(α/β(1−exp(−β∗t))) where V(t) is
volume at time t, V(0) the initial volume and α and β are constants [244].
3.3.10 Cytotoxicity in Monolayer and Spheroid Tissue Cultures
The cytotoxicity of BCM+DTX and Taxotere® in monolayer and spheroid cell cultures
was determined using the established acid phosphatase (APH) assay which is based on
quantification of cytosolic acid phosphatase activity [245]. For this assay, p-nitrophenyl
phosphate is added in cell culture and hydrolyzed in viable cells to p-nitrophenol via
intracellular acid phosphatase. Briefly, MCTS and monolayer cultures were treated with
Taxotere® or BCM+DTX for 24 h over a range of drug concentrations. Following
treatment, cells were washed three times with fresh media and cultured for an additional
48 h. Cells were washed with PBS buffer prior to the addition of reaction buffer (2 mg/ml
p-nitrophenyl phosphate (Sigma) and 0.1 % v/v Triton-X-100 in 0.1 M sodium acetate
buffer at pH 5.5). Following incubation for 2 h in the cell incubator, 1 M sodium
hydroxide was added to each well and acid phosphatase activity was determined by
measuring the UV absorbance at 405 nm using an automated 96-well plate reader
(SpectraMax Plus 384, Molecular Devices, Sunnyvale, CA). Results were normalized to
60
controls as follows: % viability = (Atreatment – Amedia)/(Acontrol – Amedia), where A = mean
absorbance. All experiments were performed in triplicate.
3.3.11 Growth Inhibition of MCTS
BCM+DTX or Taxotere® was administered to spheroids for 24 h at a DTX equivalent
concentration of 2, 20 or 200 ng/mL. The culture media was replaced following the
incubation period. Subsequently, half of the culture media was replaced in each well
every other day. Images of spheroids were captured using a light microscope with a 10x
objective lens (VWR VistaVisionTM) connected to a digital camera (VWR DV-2B).
Spheroid size was determined by measuring their 2-D cross-sectional area using the
automated image analysis method described previously. The data are reported as the
mean volume of six spheroids ± SD.
3.3.12 Clonogenic Survival Assay
The clonogenic assay was used to determine the ability of single cells to replicate and
form colonies (>50 cells) following exposure to BCM+DTX and Taxotere®. Single cell
suspensions derived from monolayers and disaggregated spheroids were diluted in
culture media and cells were plated in 6-well plates in desired numbers. MCTS were
disaggregated by incubation in trypsin-EDTA for 10 min, followed by gentle agitation.
Drug formulations were added immediately at a DTX equivalent concentration of 20
ng/mL. This concentration was selected due to its intermediate cytotoxicity and growth
inhibitory effect. After treatment for 24 h, cells were washed with PBS and 2 mL of fresh
media was added to each well. For treatment of intact spheroids, drug formulations
were added directly into wells containing individual MCTS. After 24 h, MCTS were
collected and rinsed in PBS, suspended as single-cell suspensions in fresh media
following trypsinization, and seeded onto 6-well plates. Cells were incubated for 14-16
days prior to fixation with methanol and staining with 1% crystal violet solution. Colonies
consisting of at least 50 cells were counted. The surviving fraction (SF) was expressed
as the number of colonies divided by the product of the number of cells plated and the
plating efficiency. The plating efficiency was determined by dividing the number of
colonies formed by the number of cells plated for untreated controls.
61
3.4 Results
3.4.1 Characterization of BCM+DTX
PEG-b-PCL copolymer micelles containing physically encapsulated DTX were
generated with a spherical morphology (Figure 3.3a). The size distribution of the
micelles was monomodal with an average hydrodynamic diameter of 54.6 ± 4.9 nm
(Figure 3.3b). Drug loading resulted in a final DTX equivalent concentration of 258.7 ±
35.5 µg/mL at a loading efficiency of 52.7 ± 7.1 %. Release of DTX from BCMs occurred
over the course of 24h with 74% of the drug released by 12 h. In contrast, the transport
of docetaxel from Taxotere® into the surrounding PBS release media was complete by
12h.
0 50 100
0
20
40
60
80
100
Hydrodynamic diameter (nm)
Re
lative
nu
mb
er
Figure 3.3. a) Transmission electron micrograph (Scale bar in represents 100 nm) and
b) size distribution of BCM+DTX as determined by DLS.
a) b)
62
Figure 3.4. Release of DTX from dialysis bags containing BCM+DTX, Taxotere®, and
DTX in DMSO, n = 3. The data is fit to a two-phase exponential association model.
3.4.2 Growth of MCTS
Spheroids were grown using a modified liquid overlay technique by seeding HT29 or
HeLa cells onto non-adherent U-bottom tissue culture wells without the use of an
agarose surface coating. MCTS were spherical, followed a sigmoidal growth profile, and
were grown until a diameter of ~ 500 µm was reached prior to use (Figure 3.5).
0 5.010 7 1.0108 1.510 80
110 0 4
210 0 4
310 0 4
410 0 4
510 0 4
HeLa
HT29
Volume per spheroid (µm3)
Cells
per
sphero
id
0 5 10 15 20 25 300
210 0 8
410 0 8
610 0 8
810 0 8
HT29
HeLa
Days
MC
TS
vo
lum
e (m
3)
Figure 3.5. a) Cell packing density (number of cells per spheroid) of HeLa and HT29
MCTS, n=12. Dashed line indicates the volume of MCTS used in studies. b) Growth of
HeLa and HT29 MCTS, n=6. Data was fit using the Gompertz equation for tumor
growth. The dashed lines indicate spheroid properties used in the studies.
a) b)
63
3.4.3 Cytotoxicity in monolayer and MCTS culture
The metabolic activity of cells following exposure to BCM+DTX or Taxotere® was
assessed using the APH assay (Figure 3.6). This assay was validated by assessing the
relationship between UV absorbance and cell number in both monolayer and spheroid
cultures. If the production of p-nitrophenol (i.e. the activity of acid phosphatase) is to be
used as a measure of cellular metabolic activity and, in this capacity reflect cell viability,
the UV absorption per cell must be independent of spheroid size and proliferative
activity (i.e. cell cycle distribution). As shown in Figure A2 (Appendix 1), a linear
relationship was observed between UV absorbance and spheroid diameter (i.e. cell
number). A well-established tetrazolium salt-based assay (WST-8) was also evaluated
and did not yield a similar correlation (Appendix 1, Figure A3). The NADH/NADPH-
dependent production of formazan per cell was reduced (i.e. a non-linear relationship
between UV absorbance and cell number was established) as the cell number per
spheroid increased.
Spheroid cultures were less sensitive to BCM+DTX and Taxotere® relative to
their monolayer counterparts. HeLa cells were less responsive to treatment with either
BCM+DTX or Taxotere® than HT29 cells in monolayer culture, while the opposite was
observed for cells grown as spheroids. The IC50 of HeLa and HT29 monolayer cultures
treated with BCM+DTX were 0.37+/-0.01 and 0.01+/-0.004 ng/mL, respectively. When
treated with Taxotere®, the IC50 of HeLa and HT29 monolayer cultures were 2.2+/-0.5
and 0.09+/-0.01 ng/mL, respectively. Only HeLa spheroids demonstrated a measurable
IC50 (1396 ± 198 ng/mL for BCM+DTX and 1558 ± 103 ng/mL for Taxotere®) whereas
HT29 MCTS maintained a viability above 80% at all drug concentrations.
64
10 - 6 10 - 4 10 - 2 10 0 10 2 10 4 1060
50
100 ML: BCM+DTX
ML: Taxotere
MCTS: Taxotere
MCTS: BCM+DTX
[DTX] (ng/ml)
Cell
surv
ival,
%
10 - 6 10 - 4 10 - 2 100 102 104 1060
50
100
ML: Taxotere
ML: BCM+DTX
MCTS: Taxotere
MCTS: BCM+DTX
[DTX] (ng/ml)
Cell
surv
ival,
%
1 10 100 1000 100000
50
100
HT29
HeLa
Concentration (mg/ml)
Cell
viabili
ty,
%
Figure 3.6. Cytotoxicity of Taxotere® and BCM+DTX in a) HeLa and b) HT29 monolayer
and MCTS cultures as measured using the APH assay. Data is expressed as the
percent viability relative to untreated controls and fit to the Hill equation. c) Cytotoxicity
of blank PEG-b-PCL micelles as a function of copolymer concentration. Each plot
represents the mean of three independent experiments ± SD (n=3).
3.4.4 Inhibition of MCTS growth
MCTS volume was plotted over a 30 day period following a 24 h incubation with 2, 20,
and 200 ng/mL BCM+DTX or Taxotere® (Figure 3.7). The growth of HeLa MCTS was
completely impeded following incubation with DTX concentrations of 20 and 200 ng/mL.
No significant difference in growth was observed following exposure to 2 ng/mL of DTX
relative to untreated controls. In the case of HT29 MCTS, incubation with 20 ng/mL of
BCM+DTX and Taxotere® only resulted in a partial reduction in MCTS volume.
Following re-treatment 14 days after the initial drug incubation, BCM+DTX
a) b)
c)
Cell
via
bili
ty, %
Cell
via
bili
ty, %
C
ell
via
bili
ty, %
65
Figure 3.7. a) Representative images of HeLa and HT29 MCTS following treatment with
BCM+DTX at a concentration of 20 ng/mL. Bars represent 100 µm. Growth inhibition of
HeLa and HT29 MCTS by BCM+DTX and Taxotere® at concentrations of 2, 20 and 200
ng/mL. Cells were re-treated after two weeks (arrow). Plots c) and e) are expanded
regions of plots b) and d). Data is expressed as the mean volume of six spheroids (n=6)
± SD. “*” represents a statistically significant difference, p < 0.05.
b) c)
d) e)
a)
66
demonstrated greater inhibition of HT29 MCTS growth than Taxotere® at a
concentration of 20 ng/mL. Similarly to HeLa MCTS, complete inhibition of growth was
observed following incubation with 200 ng/mL of drug.
3.4.5 Immunohistochemistry
Immunohistochemical analysis of MCTS cross-sections was performed in order to
identify regions of necrosis, cellular proliferation and hypoxia (Figure 3.8). Staining with
the proliferation marker Ki67 revealed a greater proportion of proliferative cells in HeLa
MCTS relative to HT29. Image analysis revealed that 88.6% of proliferating cells were
located within the periphery of HT29 MCTS (Figure 3.9).
Figure 3.8. HeLa (a-c) and HT29 (d-f) MCTS cross-sections stained with H&E (a, d),
Ki67 proliferation marker (b, e) and EF5 (c, f), a marker of hypoxia. Scale bars represent
100 µm.
a)
a
b)
a
d) a
e)
a
f)
a
c)
a
67
Figure 3.9. Ki67 positive signal distribution relative to radial position in a) HeLa and b)
HT29 MCTS as a percent of total positive stain, n=6.
Figure 3.10. Relative spatial distribution of features of HeLa and HT29 MCTS
microenvironments. “++”, “+” , and “-”, indicate high, intermediate and low levels of the
corresponding feature, respectively.
In contrast, only 51% of the total proliferating cells were located in the periphery of HeLa
MCTS and 25% and 24% were located in the intermediate region and core,
respectively. Signs of necrosis were visible following staining with H&E in HT29 MCTS.
Incubation of MCTS with EF5 allowed for identification of regions of hypoxia following
exposure to Cy5- conjugated anti-EF5 antibody. Hypoxic conditions were observed
a) a
b)
a
68
primarily in the core and intermediate regions of HT29 MCTS. In contrast, HeLa MCTS
did not demonstrate any regional hypoxia. The relative distributions of cellular
proliferation, hypoxia and necrosis in the MCTS are summarized in Figure 3.10.
3.4.6 Clonogenic Survival
The surviving fractions (SF) of HeLa and HT29 cells were determined following
treatment with BCM+DTX or Taxotere® as monolayer and MCTS cultures (Figure 3.11).
Figure 3.11. Clonogenic survival of HeLa and HT29 cells following 24 h treatment with
20 ng/mL of BCM+DTX or Taxotere® (TAX) as monolayers, disaggregated spheroids
and intact spheroids.
The SF was higher for all MCTS cultures relative to monolayers. HeLa cells were less
sensitive to treatment than HT29 when cultured as monolayers but more sensitive than
HT29 cells when the cells were exposed to treatment as MCTS. In all cases, the SF
was lower when treated with BCM+DTX compared to Taxotere®. Furthermore, cells
exposed to treatment immediately following MCTS disaggregation demonstrated
residual resistance to both BCM+DTX and Taxotere®.
69
3.5 Discussion
In recent years, the tumor microenvironment has been implicated in the coordination of
tumor growth, metastasis and resistance to anti-cancer therapies [246, 247]. Therefore,
effective evaluation of novel therapeutic agents requires the use of tissue models which
closely mimic native conditions within the intratumoral space. Yet, the vast majority of
chemotherapeutic agents are screened for cytotoxic effects in monolayer cultures which
do not account for critical mechanisms of drug resistance associated with the tumor
microenvironment. As a result, these models poorly predict a drug’s therapeutic efficacy
in vivo [231]. In contrast, 3-D MCTS better approximate the state of cancer cells in their
native environment and thus can be used to more accurately estimate a drug’s
therapeutic potential. A variety of methods have been used to grow MCTS for use in
cancer research including spinning culture flasks [248], hanging drops [249], liquid
overlay on agarose [250], micropatterned plates [251], and recently, using inter-cellular
linkers [252]. However, many of these techniques are impractical, time-consuming, and
involve delicate handling procedures, limiting the use of the MCTS model in drug
screening and development. In addition, practical application of traditional cell-based
assays in MCTS cultures remains poorly established. In the current study, the
performance of BCM+DTX and Taxotere® was evaluated in monolayer and MCTS
cultures using a straightforward and robust MCTS culture technique and by adaptation
of conventional cytotoxicity and survival assays.
MCTS grew according to sigmoidal growth patterns reflective of tumor growth in
vivo (Figure 3.5) and possessed histological features similar to those of the native tumor
microenvironment including gradients in cell proliferation and regions of hypoxia and
necrosis (Figure 3.8, Appendix 1 - Figure A4). Cells grown in spheroid cultures
demonstrated considerably greater resistance to treatment with BCM+DTX or Taxotere®
relative to cells grown in monolayer cultures. This may be a result of the limited
exposure of cells within MCTS to treatment due to poor penetration of DTX or BCMs,
the limited sensitivity of cells within MCTS to DTX due to a reduction in cellular
proliferation and/or resistance associated with 3-D cell adhesion (i.e. contact effect). In
a study by Kyle et al., the penetration half-depth (the depth from the surface at which
the amount of drug falls to half of its maximum concentration) of DTX in multicellular
70
layers was found to be < 25 µm following a 2h incubation at a concentration of 0.3 µM
[253]. Peak tissue levels did not increase proportionally following a 10-fold increase in
drug concentration although the depth of penetration was improved indicating partial
saturation of tissue binding. Therefore, it is likely that high intracellular binding and
consumption of DTX by peripheral cells in the MCTS limits the toxicity to cells distant
from the surface. For drugs which are rapidly consumed by cells, encapsulation in
BCMs which minimize interactions and uptake by cells may improve drug penetration
[254]. For example, Pun et al. reported ameliorated penetration of doxorubicin into
MCTS when encapsulated in poly(ethylene oxide)-b-poly[(R)-3-hydroxybutyrate]-b-
poly(ethylene oxide) (PEO-b-PHB-b-PEO) triblock copolymer micelles [150]. However,
BCMs which penetrate poorly through tissues may limit the penetration of the
encapsulated drug. Overall, the extent to which the BCMs influence drug penetration
will depend on the relative rates of drug release and BCM penetration in the MCTS. We
have previously demonstrated that 55 nm PEG-b-PCL BCMs can achieve a
homogeneous distribution in MCTS following a 24 h incubation [255].
In addition to potential limitations in MCTS penetration associated with the drug
and BCMs, the discrepancy between MCTS and monolayer cytotoxicity may also be a
result of drug resistance imparted by the MCTS microenvironment. A marked decrease
in the proportion of proliferating cells was observed in MCTS with increasing depth from
the surface (Figure 3.9). Since DTX exerts its therapeutic effect on cycling cells, cells
located near the MCTS surface will respond to treatment similarly to cells cultured as
monolayers. By contrast, quiescent cells that are located in the intermediate and core
regions of the MCTS will be less sensitive to treatment. This notion is supported by the
observation that cells exposed to treatment immediately following disaggregation of
MCTS demonstrated greater clonogenic survival than monolayer cells, but less than
cells treated as intact MCTS. Therefore, there exists a population of cells within the
MCTS that is more resistant to treatment than cells cultured as monolayers even in the
absence of any physical barrier to drug penetration. The limited sensitivity of MCTS to
treatment is likely a result of both restricted transport and mechanisms of drug
resistance associated with the MCTS microenvironment.
The extent to which culturing cells as MCTS influenced the therapeutic effect of
BCM+DTX and Taxotere® relative to monolayers was found to be cell-line specific. In
71
monolayer cultures, BCM+DTX and Taxotere® demonstrated greater cytotoxicity against
HT29 cells relative to HeLa cells. However, culturing cells as MCTS imparted a greater
enhancement in therapeutic resistance (i.e. greater increase in IC50) to HT29 cells than
to HeLa cells. We have previously shown significantly greater penetration of HeLa
MCTS than HT29 MCTS by BCMs due to the former’s lower cell packing density and
large intercellular channels [255]. In the current study, significant cell line-dependent
differences in MCTS microenvironment were observed. Limited permeability of HT29
MCTS and/or high consumption of nutrients and oxygen by peripheral cells was
reflected by the presence of central hypoxia and necrosis. Furthermore, HT29 MCTS
contained a greater proportion of non-proliferating cells relative to HeLa MCTS. It is
likely that some quiescent cells within the MCTS retained their clonogenic potential
following exposure to inadequate amounts of DTX and were capable of recommencing
proliferative activity when re-plated as monolayers. The greater clonogenic potential of
HeLa cells following disaggregation of MCTS relative to HT29 cells likely reflects the
greater sensitivity of HT29 monolayer cells to DTX rather than greater residual
resistance of MCTS-derived HeLa cells.
One of the important advantages of the MCTS model is that it allows for
treatment efficacy to be observed over an extended period of time. In order to evaluate
the potential of surviving cells to repopulate MCTS, the growth of MCTS following
treatment with BCM+DTX and Taxotere® was evaluated for 28 days with treatment re-
applied after 14 days. The results of this study demonstrate both dose- and time-
dependent changes in MCTS growth following incubation with the drug formulations.
Near complete elimination of HeLa MCTS was observed following treatment at 20
ng/mL or greater with either BCM+DTX or Taxotere®. In contrast, only partial growth
inhibition was observed in HT29 MCTS when exposed to the same concentration. This
observation is consistent with the results obtained from the cytotoxicity and clonogenic
assays in which HT29 MCTS demonstrated greater resistance to treatment relative to
HeLa MCTS. A slight inhibitory effect in HT29 MCTS following administration of DTX
formulations at 2 ng/mL was likely due to the cytotoxicity and shedding of surface cells,
consistent with the response of HT29 cells to treatment in monolayer cultures. In
addition, the apparent discrepancy between the limited cytotoxicity in HT29 spheroids
revealed using the APH assay (measured 2 days post drug incubation) and the marked
72
growth inhibition at 20 ng/mL is consistent with the observed 4 day delay in growth
inhibitory effect. Interestingly, little difference in spheroid growth inhibition was observed
between BCM+DTX and Taxotere® following initial treatment. It should be noted,
however, that following retreatment after 14 days of culture, BCM+DTX demonstrated a
greater growth inhibitory effect relative to Taxotere®.
Several factors may have contributed to the greater cytotoxicity of BCM+DTX
relative to Taxotere® in monolayer and MCTS cultures. It has been hypothesized that
DTX is taken up more rapidly by cells following release from BCMs in close proximity to
the cell membrane due to an increase in the local transmembrane concentration
gradient [256–258]. Slower efflux of BCM-encapsulated DTX relative to free DTX, by
avoidance of membrane efflux pumps, may also contribute to the greater therapeutic
effect of the DTX-loaded BCMs [111, 259, 260]. For instance, the level of expression of
certain genes and their associated transport proteins, such as P-glycoprotein (P-gp) or
multidrug resistance associated protein 7 (MRP7), for which docetaxel is a substrate,
may influence differences in cytotoxicity between free docetaxel and docetaxel
encapsulated within micelles. Furthermore, the level of expression of transporters may
vary over time, may change with repetitive exposure to a drug, or may be different when
cells are cultured as spheroids relative to monolayers [261, 262]. However, further
investigation is required to fully elucidate the mechanism of cytotoxicity that lead to
enhanced therapeutic effects of BCM+DTX relative to Taxotere® in vitro.
73
3.6 Conclusions
Overall, as outlined in Figure 3.2, the three assays employed in this study provide
complementary information on the therapeutic potential of drug formulations.
Importantly, comparison of results obtained in monolayer and spheroid cultures
demonstrated the important influence of the microenvironment and 3-D tissue structure
on formulation efficacy. Therefore, 3-D cultures such as MCTS may serve as important
tools for investigating the performance of nanomedicines in environments that more
closely mimic intratumoral conditions in vivo. However, while spheroids share several
important structural and microenvironmental properties with native tumors, there are
important differences which may limit the extent to which this in vitro model can be used
to predict drug efficacy in vivo. Notably, the MCTS model does not account for the
potential influence of convective flow or presence of stromal cells on drug and
nanoparticle transport. Despite these limitations, evaluation of formulation efficacy in
spheroids rather than monolayer cultures is expected to more accurately reflect
therapeutic performance in vivo.
74
4 Chapter 4
Image-based Analysis of the Time-dependent Penetration of
Polymeric Micelles in Multicellular Tumor Spheroids and Tumor
Xenografts
Chapter 4
75
This chapter is a copy of: “AS. Mikhail, S. Eetezadi, J. Stewart and C. Allen. “Image-
based Analysis of the Time-dependent Penetration of Polymeric Micelles in Multicellular
Tumor Spheroids and Tumor Xenografts”. Submitted, 2012.
All experiments and data analyses were performed by AS. Mikhail. J. Stewart wrote the
MATLAB® algorithms. S. Eetezadi illustrated Figure 4.1 and Figure 4.3.
Immunohistochemical staining was performed by the Pathology Research Program
(PRP) at the University Health Network (Toronto, ON).
This chapter was written by AS. Mikhail and edited by Dr. C. Allen.
76
4.1 Abstract
Although the selective tumor accumulation of systemically administered nanomedicines
has been well documented, corresponding improvements in therapeutic efficacy have
often been incommensurate. A significant reason for this is their heterogeneous
intratumoral distribution and poor interstitial penetration which limits the exposure of
cancer cells to therapy. In the present work, fluorescence-based methodologies were
used for the computational assessment of polymeric micelle penetration in multicellular
tumor spheroids (MCTS) and tumor xenografts originating from human cervical (HeLa)
and colon (HT29) cancer cells. The influence of micelle size on tissue penetration was
examined at multiple time points in vitro and in vivo. Penetration of 15 nm micelles in
MCTS was rapid and resulted in a homogeneous distribution from the periphery to the
core while 55 nm micelles underwent delayed, time-dependent penetration of MCTS.
Following i.v administration of micelles to mice bearing tumor xenografts, penetration of
55 nm micelles into the tumor interstitium was slow but progressive while 15 nm
micelles exhibited rapid penetration with visible clearance by 24 h post injection. Higher
concentrations of penetrating micelles in HeLa MCTS and tumor xenografts relative to
HT29 models were attributed to differences in tissue architecture. These results show
that micelle penetration is size-, tumor type- and time-dependent. Together, these
findings demonstrate the potential applicability of 3-dimensional MCTS models for the
high-throughput assessment of nanoparticle tissue transport in vitro.
77
4.2 Introduction
Poor penetration of chemotherapeutic agents in solid tumors has been recognized as
one of the major challenges limiting the efficacy of macromolecular and nanoparticle-
based cancer therapies [122]. The successful distribution of therapeutic agents
throughout a tumor remains a challenge due to the heterogeneous architecture of the
vascular network, abnormal blood flow, dense nature of the extracellular matrix and
interstitial hypertension [73, 122, 263]. Given that lymphatic drainage is compromised
throughout much of the tumor due to compression of lymphatic vessels by cancer cells
and leakage of excess fluid from the tumor vasculature, interstitial fluid pressure (IFP) is
elevated particularly within the tumor core [264]. Since high IFP levels can approach or
exceed intra-capillary pressure, diffusion is believed to be the primary mechanism of
transvascular and interstitial transport throughout much of the tumor mass [90].
Supramolecular assemblies of amphiphilic copolymers known as block
copolymer micelles (BCMs) constitute a promising class of nanoparticles for the
systemic delivery of chemotherapy [6, 22, 23, 198, 265, 266]. In contrast to conventional
small molecule surfactants that are commonly used as solubilizing excipients,
biocompatible copolymers such as poly(ethylene glycol)-b-poly(ε-caprolactone) (PEG-b-
PCL) result in micelles with a greater degree of thermodynamic and kinetic stability
[242]. Stable, long-circulating BCMs can accumulate preferentially within a tumor via the
enhanced permeability and retention (EPR) effect, resulting in tumor-specific delivery of
the encapsulated drug [69, 267].
Indeed, the systemic delivery of anti-cancer drugs via nanoparticle-encapsulation
has been shown to increase their tumor accumulation relative to conventional
chemotherapeutic agents [3, 6, 268, 269]. However, seminal research pertaining to the
intratumoral fate of macromolecules and nanoparticles suggests that they are
heterogeneously distributed and display limited penetration into avascular tumor
compartments [80, 84, 95, 120–122, 132]. While evaluating chemotherapeutic
nanomedicines in conventional tissue culture provides insight into therapeutic
responses at the cellular level, this approach often fails to accurately predict a
formulation’s efficacy in vivo. This is largely due to the simplified structure of monolayer
cultures which does not account for multicellular mechanisms of drug resistance and
78
transport restrictions commonly associated with 3-D tumor tissues. In contrast, 3-D
cultures such as multicellular tumor spheroids possess an extracellular matrix as well as
pH, oxygen, metabolic and proliferative gradients analogous to the microenvironment in
hypovascular and avascular regions of solid tumors [234–236]. MCTS are composed of
an outer layer of proliferating cells surrounding a quiescent cell layer and necrotic core,
mimicking the radial organization of tissues adjacent to a tumor blood vessel (Figure
4.1) [29]. As such, MCTS provide a useful platform for studying diffusion-based
transport of nanoparticles with respect to the structural and microenvironmental
heterogeneity commonly associated with solid tumors.
Figure 4.1. Schematic representation of tumor and MCTS cross-sections. MCTS are
composed of a peripheral region of proliferating cells surrounding an intermediate
region of quiescent cells and a nutrient deprived or necrotic core mimicking the radial
organization of tissues adjacent to a tumor blood vessel.
Herein we directly compare the spatial and temporal penetration of block copolymer
micelles using a 3-D in vitro tissue model and corresponding human tumor xenografts.
The influences of BCM size and tumor tissue type on interstitial transport are also
assessed. The capacity of the spheroid model to predict the in vivo tissue penetration
of BCMs is evaluated with the objective of validating its potential as a high-throughput in
79
vitro platform for optimization of nanoparticle transport properties. Computational image
analysis is used to assess BCM penetration in MCTS and tumor xenografts with the
ultimate goal of developing rational design criteria for improving the transport and
therapeutic efficacy of drug-loaded nanoparticles.
4.3 Methods
4.3.1 Materials
Methoxy poly(ethylene glycol) of different molecular weights (CH3O-PEG-OH; Mn =
5000, Mw/Mn = 1.06; Mn = 2000, Mw/Mn = 1.06) were obtained from Sigma-Aldrich
(Oakville, ON, Canada). ε-Caprolactone and dichloromethane were purchased from
Sigma-Aldrich and dried using calcium hydride prior to use. Hydrogen chloride (1.0 M in
diethyl ether), N,N-dimethylformamide (DMF), diethyl ether, hexane and acetonitrile
were also purchased from Sigma-Aldrich and used without further purification. Alexa
Fluor® 488 (AF488) carboxylic acid succinimidyl ester was purchased from Molecular
Probes (Eugene, OR).
4.3.2 Synthesis of CH3O-PEG-b-PCL (PEG-b-PCL) and Alexa Fluor® 488-PEG-b-PCL (AF488-PEG-b-PCL) copolymers
PEG-b-PCL copolymers were prepared by metal-free cationic ring opening
polymerization of ε-CL with CH3O-PEG-OH as macroinitiator in the presence of HCl
using an established method previously reported [242]. For the synthesis of
fluorescently labelled copolymer (AF488-PEG-b-PCL), NH2-PEG-OH was used in place
of CH3O-PEG-OH for polymerization. Alexa Fluor® carboxylic acid succinimidyl ester
(AF488) was then conjugated to NH2-PEG-b-PCL (2x molar excess with respect to
AF488) in DMSO with TEA (30x molar excess with respect to NH2-PEG-b-PCL) for 24 h
at room temperature. AF488-PEG-b-PCL was purified using a silica gel 100 C8- reverse
phase column (Sigma-Aldrich, Oakville, ON, CA) packed in 50/50 acetonitrile/water and
equilibrated with water prior to injection of the reaction mixture. Unbound AF488 was
eluted using water followed by elution of the AF488-PEG-b-PCL conjugate using a
90/10 solution of acetonitrile/water. The purity of the conjugate was assessed by high
performance liquid chromatography (HPLC) using a Styragel HR2 column (effective
molecular-weight range of 500 to 20,000; Waters, MA) connected to a fluorescence
80
detector (Agilent Technologies Inc., CA) with excitation and emission wavelengths of
λex=495 nm and λem=519 nm, respectively. Filtered HPLC grade DMF was used as the
mobile phase with a flow rate of 0.5 mL/min.
4.3.3 Preparation and characterization of BCMs
Micelles were prepared from PEG2000-b-PCL1000 or PEG5000-b-PCL5000 copolymers by
hydration of thin films. First, copolymers were dissolved in DMF and stirred overnight.
For generation of fluorescent BCMs, AF488-conjugated PEG2000-b-PCL1000 or PEG5000-
b-PCL5000 copolymers dissolved in DMF were added to the unlabeled copolymer in
order to achieve a final AF488 concentration of 1 µM for in vitro studies and 10 µM for in
vivo studies in each BCM sample. DMF was evaporated under N2 at 30oC and trace
solvent was removed under vacuum. Dry copolymer films were then heated to 60 °C in
a water bath prior to the addition of PBS buffer (pH 7.4) at the same temperature with
thorough vortexing. Resultant micelle solutions were stirred for 24 h and then sonicated
for 1 h (Laboratory Supplies Co., NY). The critical micelle concentration (CMC) of the
copolymers was determined by an established fluorescence-based method as
previously described [242].
4.3.4 Transmission electron microscopy (TEM)
The size and morphology of the BCMs were determined by TEM using a Hitachi 7000
microscope (Schaumburg, IL) operating at an acceleration voltage of 75 kV. BCM
solutions (10 mg/mL) were diluted in double distilled water immediately prior to analysis
and negatively stained with a 1 % uranyl acetate (UA) solution. The negative stain
provided an electron dense layer resulting in reverse-contrast, negative electron
images. The samples mixed with UA were deposited on copper grids (Ted Pella Inc.,
Redding, CA) that had been pre-coated with carbon and negatively charged. The final
copolymer concentration on the grid was 0.5 mg/mL. The copper grids were briefly left
to stand to allow the solvent to evaporate. The average sizes of BCMs were obtained by
measuring the diameter of a minimum of 20 BCMs using TEM images and SigmaScan
Pro software (Jandel Scientific).
81
4.3.5 Tissue culture and growth of MCTS
Human cervical (HeLa) and colon (HT29) cancer cells were cultured in DMEM
containing 1% penicillin-streptomycin solution supplemented with 10% FBS. Cells were
incubated at 37 °C and 5% CO2 and harvested by trypsinization with trypsin-EDTA. To
initiate growth of MCTS, monolayer cells were trypsinized and seeded onto non-
adherent 96-well round-bottomed Sumilon PrimeSurface™ plates (MS-9096U;
Sumitomo Bakelite, Tokyo, Japan). Following cellular aggregation and growth, each
well contained a single spheroid. During growth, 50% of the culture medium was
exchanged every other day.
4.3.6 Penetration of BCMs in MCTS
MCTS were incubated with 15 (BCM-15) or 55 (BCM-55) nm fluorescently labeled
BCMs in separate wells for 1 and 24 h at a copolymer concentration of 1 mg/mL in each
well. Following incubation with BCMs, MCTS were washed in PBS and transferred onto
a vinyl specimen mold (Cryomold®, Tissue-Tek, Sakura Finetek, CA). Samples were air-
dried for 5 minutes prior to the addition of Tissue-Tek® O.C.T. compound (Sakura
Finetek, Torrance, CA). MCTS were frozen by submersion in an isopentane bath cooled
by liquid nitrogen. MCTS samples were then cut into 5 μm thick sections and mounted
on glass slides. Images were acquired at 10x magnification using an Olympus BX50
upright fluorescence microscope (Olympus, PA) equipped with an EXFO fluorescence
illumination source and Semrock Quad Sedat filter set. A Photometrics CoolSnap HQ2
CCD camera was used to capture images with fixed exposure and contrast settings.
The fluorescence intensity per unit area was calculated with respect to the distance
from the MCTS surface using a custom MATLAB (MathWorks Inc., MA) algorithm. The
total area-normalized signal intensity in arbitrary units is then calculated within three
concentric regions of the MCTS: periphery, intermediate and core (Figure 4.1).
4.3.7 Animals and growth of tumor xenografts
Four week-old nude female CD1 mice (Charles River, MA) were housed at the Animal
Resource Centre of the University Health Network (Toronto, ON, Canada) where they
were given water and food ad libitum. All procedures were carried out under a protocol
approved by the Animal Care Committee of the University Health Network. HeLa
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(7.5x106) or HT29 (1.25x106) cells were suspended in DMEM medium and injected
subcutaneously into the right hind flank of the mice. The tumor volume was determined
using calipers to measure the diameter of each tumor and applying the formula of an
ellipsoid v = a x b2 / 2, where v is the tumor volume and a and b are the largest and
smallest diameters, respectively. Tumors were allowed to grow for two weeks until
reaching a size of ~ 60-80 mm3 prior to use of the animals in the studies outlined below.
4.3.8 Penetration of BCMs in tumor xenografts
Tumor-bearing animals were administered BCM-15 or BCM-55 formulations i.v.
(copolymer concentration of 10 mg/mL (10 µM conjugated AF488)) and sacrificed at 1,
6, or 24 h post injection. In order to identify perfused blood vessels within the tumors,
each animal received a 100 µL injection of Hoechst 33342 (10 mg/mL) (Sigma-Aldrich)
1 minute prior to sacrifice. Tumors were excised, embedded in Tissue-Tek® O.C.T.
compound and frozen immediately in a bath of isopentane cooled by liquid nitrogen
prior to tissue sectioning and analysis. Frozen tumor blocks were cut into 5 µm-thick
sections separated by 200 µm within each tumor. Fluorescence images were captured
as described above. Images of entire tumor sections were generated by tiling and
stitching using MetaMorph imaging software (Molecular Devices Inc., CA).
First, images identifying the distribution of BCMs and Hoechst were captured
using fluorescein isothiocyanate (FITC) and 4′,6-diamidino-2-phenylindole (DAPI) filter
sets, respectively. Sections were then stained for identification of both functional and
non-functional blood vessels using primary rat anti-CD31 and secondary Cy3-
conjugated goat anti-rat IgG antibodies (BD Biosciences, Toronto, Canada). Images
were subsequently captured using a rhodamine (TRITC) filter set. Composite images of
complete tumor sections containing fluorescence signals representing BCMs, blood
vessels, and blood perfusion were overlayed and registered (Image Pro PLUS, v6.0). In
preparation for image analysis, regions of necrosis and artifacts resulting from
sectioning and staining were excluded. Background tissue autofluorescence was
accounted for by subtraction of average intensity values from regions in the tumor
sections with no fluorescence signal. Mean pixel intensities at specific distances from
the nearest CD31-positive pixel (endothelial cell) within whole tumor sections were
determined using a custom MATLAB algorithm as described further below. Results were
83
reported as background-subtracted mean AF488 fluorescence pixel intensity at given
distances from CD31-positive pixels in a minimum of 4 tumor sections from 3 animals
+/- SD. The AUC was calculated by integration of mean pixel intensity vs. distance
curves using the trapezoid rule. Microvessel density was measured as the total area of
CD31-positive signal divided by the total surface area of the tumor section, n = 8 +/- SD.
Cell packing density was determined by measuring the total area of nuclear staining
divided by the total surface area in the field of view, n = 5 +/- SD.
4.3.9 Computational analysis of BCM distribution in tumor sections
A method was developed to determine the mean AF488 pixel intensity (BCMs) with
respect to distance from the nearest CD31-positive pixel (blood vessel) using a custom
MATLAB algorithm. Registered images of whole tumor sections stained for blood
vessels were thresholded in order to generate binarized images containing only CD31-
positive or CD31-negative pixels (Figure 4.7a). Binarized images were used to generate
distance maps (Figure 4.7b) in which gradients in pixel intensity surround each CD31-
positive pixel. In a distance map, the intensity of each pixel is analogous to its distance
from the nearest blood vessel. Using both a distance map and registered tumor section
image containing AF488-BCMs, the mean BCM pixel intensities with background
subtracted and associated distances from the CD31-positive pixels in bins of 5 µm
increments were calculated.
4.4 Results
4.4.1 Synthesis and characterization of PEG-b-PCL copolymers and BCMs
Synthesis of the diblock copolymer, PEG-b-PCL, was achieved via metal-free cationic
ring opening polymerization, as previously described [242]. Table 4.1 summarizes the
composition of the copolymers and the physicochemical properties of the resulting
BCMs. PEG-b-PCL copolymers comprised of different block lengths were generated by
altering the feed ratio of ε-CL to CH3O-PEG-OH used as starting materials. In the case
of fluorescently labeled copolymers, NH2-PEG-OH was used to initiate the
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polymerization resulting in the synthesis of NH2-PEG-b-PCL copolymers. Alexa Fluor
488 carboxylic acid succinimidyl ester was conjugated to the amino group of the
copolymer forming a stable amide bond. Complete separation of unconjugated AF488-
PEG-b-PCL was achieved using a silica gel 100 C8- reversed phase column.
Table 4.1. Composition of block copolymers and properties of block copolymer micelles.
BCMs generated from PEG2000-b-PCL1000 or PEG5000-b-PCL5000 had diameters of 15.8
+/- 2.2 nm (BCM-15) and 53.9 (+/- 5.1) nm (BCM-55), respectively, as measured by
TEM and were primarily spherical in shape with a few rod-like structures observed in the
BCM-15 samples (Figure 2).
Figure 4.2. TEM images of a) PEG5000-b-PCL5000 and b) PEG2000-b-PCL1000 BCMs.
4.4.2 Growth of MCTS
Individual MCTS were grown from HT29 or HeLa cells in non-adherent U-bottom well
plates using a modified liquid overlay technique (Figure 4.3) [270]. Both HeLa and HT29
cells formed spherical MCTS and demonstrated sigmoidal growth profiles (Chapter 3)
[271]. By appropriate selection of the initial number of cells seeded in each well, MCTS
a) b)
100 nm 100 nm
85
of both cell lines reached a volume of approximately 5x107 µm3 (~ 500 µm in diameter)
following 7 days of culture. No significant difference was found in collagen content
between the HeLa and HT29 spheroids (Appendix 2, Figure A1). However, examination
of spheroid microstructure by light microscopy revealed greater porosity in the HeLa
spheroids in comparison to the more tightly packed tissue architecture within the HT29
spheroids (Figure 4.4).
Figure 4.3. Growth of MCTS using the liquid overlay method. Images of growing
spheroids were captured using a light microscope and 10x objective lens. Scale bars
represent 200 µm.
4.4.3 Penetration of BCMs in MCTS
In this study, the diffusive transport of fluorescently labeled BCMs of different sizes was
examined in MCTS. Representative images of MCTS cross-sections following
incubation with 15 and 55 nm BCMs for 1 h and 24 h are shown in Figure 4.5 and
results of computational analysis are shown in
Figure 4.6. The signal intensity in HeLa MCTS was much greater at all radial positions
in comparison to HT29 MCTS after both 1 h and 24 h incubation periods. After
incubation for 1 h, computational image analysis confirmed that BCM-15 was distributed
homogeneously in the MCTS while BCM-55 demonstrated significantly less penetration
into the core of both HeLa and HT29 MCTS. By 24 h, both BCM-15 and BCM-55
achieved a homogeneous distribution throughout HeLa and HT29 MCTS, although
dramatically lower total fluorescence intensity was observed in HT29 MCTS.
a) b) c) d)
86
Figure 4.4. H&E staining of a) HT29 and b) HeLa xenografts as well as c) HT29 and d)
HeLa MCTS. Scale bars represent 100 µm in a) and b) and 50 µm in c) and d).
Transmitted light, cross-sectional images of e) HT29 and f) HeLa MCTS at 40x
magnification. Arrows indicate large intercellular channels. Scale bars represent 10 µm
in e) and f).
4.4.4 Penetration of BCMs in tumor xenografts
The penetration of BCMs in xenografts was evaluated by fluorescence imaging of
tumor cross-sections at 1, 6, and 24 h following i.v administration of fluorescently
labelled BCMs. Computational image analysis was conducted using a customized
algorithm to determine the mean fluorescence pixel intensity at a given distance from
the nearest tumor blood vessel (CD31-positive pixel) (Figure 4.7).
a)
e) f)
a) b) c) d)
87
Figure 4.5. BCM fluorescence in representative cross-sections of HeLa MCTS following
incubation of MCTS for 1 h with a) 15 nm and b) 55 nm BCMs; and 24 h with e) 15 nm
and f) 55 nm BCMs. HT29 MCTS cross-sections following incubation of MCTS for 1 h
with c) 15 nm and d) 55 nm BCMs; and 24 h with g) 15 nm and h) 55 nm BCMs. Scale
bars represent 100 µm.
Representative regions of HeLa and HT29 tumor xenograft cross-sections following
administration of BCM-15 and BCM-55 are shown in Figure 4.8 along with the results of
computational image analysis. The green, red, and blue signals correspond to
fluorescence of AF488-BCMs, blood vessels (anti-CD31), and blood vessel perfusion
(Hoechst), respectively. These results demonstrate that BCM-55 localized more closely
to the tumor vasculature relative to BCM-15 in both xenograft models. The areas under
the mean signal intensity curves (AUC) were lower in HT29 xenografts indicating lower
concentrations of penetrating BCMs relative to HeLa xenografts (Appendix 2, Table T1).
BCM-15
24h
HT29
BCM-55 BCM-55 BCM-15
1h
HeLa
a) b) c) d)
e) f) g) h)
88
Figure 4.6. Area-normalized distribution of 15 (BCM-15) and 55 (BCM-55) nm BCMs in
HeLa (top row) and HT29 (bottom row) MCTS following 1 or 24 h exposures. “*”
indicates statistically significant difference from unmarked groups (top left). “*” indicates
statistically significant differences between groups with the same mark (bottom left).
Bars indicate differences between groups marked “*” and “**”. In all cases, p < 0.05.
In addition, minimum and maximum mean fluorescent pixel intensities at a depth of 100
µm from the nearest blood vessel occurred at 24 h p.i. for BCM-15 and BCM-55,
respectively, indicating that the smaller micelles had begun to clear from the tumor
tissues when the larger micelles were reaching their maximum depth of penetration
(Figure 4.9). Hoechst staining identified vessel perfusion at the time of animal sacrifice
a) b)
BCM-55 BCM-15
* *
**
* *
HeL
a
HT
29
1 h 24 h
*
89
but not necessarily vessels that may have been perfused at an earlier time. In this study
Hoechst staining was only used for qualitative identification of perfused vessels. The
microvessel density of HeLa and HT29 tumor xenografts was 6.01+/-1.04 and 4.15+/-
1.17, respectively. The cell packing density of HT29 tumor xenografts was found to be
55.4 +/- 1.2 while HeLa tumor xenografts had a cell packing density of 36.3 +/- 3.1.
Figure 4.7. Computational image-based analysis was employed to determine the mean
fluorescence pixel intensity at a given distance from the nearest tumor blood vessel. a)
Representative binary image showing CD31-positive pixels obtained from a whole HT29
tumor section stained for blood vessels. b) Representative distance map (generated
from the CD-31 binary image) in which the distance of each pixel from the nearest blood
vessel is analogous to its intensity with black pixels being nearest to a blood vessel and
white pixels being farthest away. c) Overlay of CD31-positive and BCM-15 fluorescence
images pseudocoloured in red and green, respectively. Scale bar represents 500 µm.
a) b) c)
90
Figure 4.8. Representative images and corresponding fluorescence intensity profiles (p.
91) demonstrating the interstitial penetration of BCMs (green) relative to tumor blood
vessels (red) in HeLa and HT29 tumor xenografts. A perfusion marker (blue) was
injected immediately prior to animal sacrifice. Scale bars represent 50 µm.
BC
M-1
5
BC
M-5
5
BC
M-5
5
BC
M-1
5
HeL
a
HT
29
1 h 6 h 24 h
91
Figure 4.8 (continued from p. 90). Fluorescence intensity profiles.
Figure 4.9. Mean fluorescence pixel intensities in arbitrary units of 15 and 55 nm BCMs
at 5 µm (top left), 25 µm (top right), 50 µm (bottom left) and 100 µm (bottom right) from
the nearest blood vessel in HeLa and HT29 tumor xenografts at 1, 6, and 24 h p.i.
BCM-15 BCM-55
15 nm
HT
29
H
eL
a
HT29 BCM-15 HT29 BCM-55 HeLa BCM-55 HeLa BCM-15
92
4.5 Discussion
The heterogeneous intratumoral distribution of nano-scale drug delivery systems poses
a significant challenge to their successful application in the treatment of cancer. For
maximum efficacy, anticancer drugs delivered via the systemic circulation must travel
deep into the extravascular space in order to reach cancer cells located in regions of
limited vascular density or function [26]. It has been recognized that conventional
chemotherapeutic agents penetrate poorly within the tumor interstitium resulting in the
exposure of tumor cells to sub-therapeutic concentrations which may promote drug
resistance and tumor repopulation [272]. This problem is exacerbated by the presence
of quiescent cells which often reside within hypoxic regions of the tumor distant from
blood vessels and that are intrinsically less sensitive to chemotherapy [228]. As such,
many anticancer formulations which are shown to be highly cytotoxic in monolayer cell
cultures often elicit an unsatisfactory therapeutic response within the complex
microenvironment of solid tumors.
3-D tissue cultures are useful intermediates for bridging the gap between the
over-simplified structure of monolayer cultures and pre-clinical tumor models [29, 139,
233, 252, 273]. While 3-D cell cultures have been instrumental in exposing limitations in
the interstitial penetration of conventional chemotherapeutic agents, there remains
limited application of these models in the design of nanomedicines [150, 241, 274]. To
date, our understanding of nanoparticle intratumoral transport has been largely based
on assumptions drawn from studies which have evaluated the intratumoral fate of drugs
and other non-colloidal macromolecules. However, distinguishing properties of
nanoparticles, including their size, shape, and surface properties, are likely to limit the
precise application of these findings in the design of nanomedicines.
A recent study of micelle transport by Cabral et al. found that while polymeric
micelles below 50 nm in diameter could penetrate the extravascular space and inhibit
the growth of poorly permeable pancreatic tumor xenografts, larger micelles remained
concentrated in the perivascular space and exerted no therapeutic effect [95]. Similarly,
our group has reported that a reduction in nanoparticle size enhances BCM penetration
in breast tumor xenografts [275]. In the current study, both spatial and temporal
changes in micelle penetration are reported using in vitro and in vivo tumor models. It
should be noted that we have previously demonstrated the high thermodynamic and
93
kinetic stability of PEG-b-PCL micelles both in vitro and during extended circulation in
the blood [37]. Following a 1 h incubation with both HeLa and HT29 MCTS, the relative
accumulation of 55 nm micelles was greatest at the spheroid periphery while 15 nm
micelles were distributed homogeneously from the periphery to the core. However,
following a 24 h incubation with MCTS, 55 nm micelles achieved a homogeneous
distribution that paralleled that of 15 nm micelles. Similar size-dependent tissue
penetration profiles were observed in tumor xenografts at early time points following i.v
administration of BCMs. However, while the depth of penetration of 55 nm micelles
increased over time, the mean fluorescence intensity of 15 nm micelles appeared to
diminish in both HeLa and HT29 tumors by 24 h p.i presumably due to their limited
vascular supply and rapid tissue clearance (Figure 4.9). Although rod-like nanoparticles
have been shown to penetrate tumor tissues to a greater extent than spherical
nanoparticles, the influence of morphology on tissue transport in the present study is
limited due to the presence of only a small number of rod-like aggregated in the BCM-
15 sample [276]. Our group has previously demonstrated that block copolymer micelles
with diameters in the range of 15-25 nm have short circulation half-lives relative to 60
nm micelles [96], [275]. Therefore, the concentration gradient responsible for diffusion of
15 nm micelles within the tumor interstitium may diminish relatively quickly. By contrast,
larger, longer-circulating micelles with prolonged and elevated plasma concentrations
may undergo slower tumor accumulation and delayed penetration of the tumor
interstitium [100, 277, 278]. Furthermore, larger micelles are likely to be better retained
in the tumor tissue even following a decline in plasma concentration while smaller
micelles are susceptible to more rapid clearance [279].
At 24 h p.i., tumor xenograft sections demonstrated a somewhat heterogeneous,
punctate distribution of BCMs in agreement with previous reports of nanoparticle
intratumoral distribution [80]. This may be due to the internalization of BCMs by tumor
cells or sequestration by phagocytic cells of the immune system. In addition,
heterogeneous BCM extravasation is apparent as some blood vessels appear to not be
surrounded by BCMs while other vessels appear to have significant BCM accumulation
in the surrounding extravascular space. This phenomenon may be attributed to
differences in vascular permeability, particularly in the case of BCM-55, or due to
variations in vascular perfusion. In some cases, there is an absence of BCMs around
94
vessels which appear to be perfused based on the extravasation of Hoechst while other,
apparently non-perfused vessels, are surrounded by BCMs. This finding is in agreement
with the notion that tumor vascular perfusion is transient and therefore vessels which
are observed to be perfused at the time of animal sacrifice may not have been perfused
previously, and vice versa.
Irrespective of micelle size, higher fluorescence signal intensities were apparent
in MCTS composed of HeLa cells relative to those composed of HT29 cells. This
phenomenon is likely attributed to the presence of large intercellular channels in HeLa
MCTS (Figure 4.4f). Pun’s group has previously demonstrated that the penetration of
nanoparticles in spheroids was greater following treatment with collagenase primarily
due to an increase in spheroid porosity [280]. It is postulated that the lower cell density
and greater extracellular volume of HeLa MCTS relative to HT29 MCTS resulted in
significantly higher amounts of penetrating BCMs. Greater fluorescence signal
intensities were also observed in HeLa xenografts in comparison to the more densely
structured HT29 xenografts. This observation is consistent with several reports of
greater drug penetration in tumors with a higher proportion of interstitial fluid space and
in tumor tissues of low cell density [94, 135, 281, 282]. For example, McGuire et al.
recently demonstrated greater ex vivo penetration of dextrans into tumor tissue samples
with enlarged and interconnected interstitial channels following exposure to chemical
agents that reduce cellular volume or induce cytotoxicity [282].
The similarities in BCM penetration between MCTS and tumor xenograft models
serves to establish the capacity of the MCTS model to predict trends in nanoparticle
interstitial transport in vivo. Specifically, BCM penetration in both models was found to
depend on nanoparticle size, time and tumor or cell type. However, MCTS lack several
important components possessed by tumor xenografts which may limit the predictive
capacity of this in vitro model. Whereas MCTS are, in most cases, composed entirely of
a single epithelial cell line, some tumors contain a large proportion of stromal cells and
fibrous tissues. Although the extent of the influence of tumor stroma on tissue transport
may vary, it is likely that tumors with high stromal content may be better modeled by
MCTS cocultures or other multi-component platforms. In addition, the MCTS model
does not account for the clearance of nanoparticles from tumor tissues in vivo. As such,
the use of MCTS is most suitable for the prediction of trends in nanoparticle tumor
95
penetration during their accumulation in the tumor rather than at later stages following
significant influence by processes of nanoparticle retention or clearance.
Few methods have been reported for quantifying penetration of small molecules,
macromolecules or nanoparticles in solid tumors [26, 95, 275, 283, 284]. In the present
study, the distribution of fluorescently labeled BCMs relative to tumor blood vessels was
examined using an image-based computational methodology. In order to reduce
potential bias and to achieve a more comprehensive evaluation of tissue distribution, an
efficient procedure was implemented in which entire tumor cross-sections were
analyzed rather than selected sample regions within sections. However, the in vivo
computation of BCM penetration was limited to an analysis of 2-D images
representative of 3-D tumors. Therefore, the presence of out-of-plane vessels that could
potentially contribute to the accumulation of in-plane BCMs may serve to overestimate
the depth of penetration of the micelles. However, this effect, as well as any potential
influence of small differences in MVD between tumor models, was minimized by only
including data in the analysis acquired within a distance of 100 µm from the nearest
CD31-positive pixel.
Figure 4.10. Potential influence of micelles on the intratumoral distribution of the drug.
As illustrated in Figure 4.10, the influence of BCM intratumoral distribution on the
distribution of the drug will depend on the extent to which the drug remains associated
with the carrier. For slow release nanocarriers, the heterogeneous distribution of the
96
delivery system may negatively influence the distribution of the drug and treatment
efficacy. For drugs that are rapidly released following nanoparticle accumulation, the
distribution of the drug may depend strongly on its ability to penetrate within the tumor
interstitium. It is possible that the distribution of poorly penetrating drugs, due to
significant cellular uptake and binding, may be improved by encapsulation in
nanocarriers which demonstrate limited interaction with cells. Slow releasing
nanocarriers that are well retained in the tumor may also serve as drug depots which
can provide extended drug exposure and ameliorated penetration of the free drug by
establishing localized elevated drug concentrations that serve to drive diffusive transport
in the interstitium.
4.6 Conclusions
The in vitro assessment of BCM tissue penetration using MCTS provided a useful
prediction of relative BCM penetration in HeLa and HT29 tumor xenografts and the
influence of nanoparticle size on interstitial transport. Both in MCTS and tumor
xenografts, the amount of penetrating nanoparticles was limited in tissues with a high
cell packing density while the rate of penetration was promoted by a reduction in
nanoparticle size. Smaller nanoparticles achieved a more rapid penetration into tumor
tissues but began to clear by 24 h p.i while larger nanoparticles achieved slow but
similar depth of penetration and prolonged retention in the tumor. Therefore, the design
of effective delivery systems will require careful adjustment of nanoparticle properties,
such as size, in order to help circumvent the unique transport restrictions imposed by
tumor tissues and to optimize their performance for specific therapeutic applications.
97
4.7 Acknowledgements
A. Mikhail is the recipient of post-graduate scholarships from NSERC and the
Government of Ontario. S. Eetezadi is funded by the NSERC CREATE Biointerfaces
training program and holds an Ontario Trillium scholarship. The authors thank Dr. I.
Tannock’s Laboratory (Princess Margaret Hospital) and J. Jonkman (Advanced Optical
Microscopy Facility, University Health Network) for helpful discussions on image
analysis as well as P. Zahedi for technical assistance with animal studies.
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5 Chapter 5. Summary and Future Directions
5.1 Conclusions and Summary of Findings
This thesis has explored potential determinants of nanocarrier intratumoral penetration
and evaluated the influence of important properties of the 3-D tumor microenvironment
on the therapeutic efficacy of nanomedicines. The initial objective of this research was
to design, synthesize and characterize a model BCM-based drug delivery system for the
chemotherapeutic agent, DTX. Chapter 2 described the incorporation of DTX into PEG-
b-PCL BCMs by means of two methods of drug encapsulation: physical entrapment and
chemical conjugation. Physical entrapment of DTX resulted in > 90% drug release from
the BCMs over 12 h while chemical conjugation resulted in extended drug release over
the course of 7 days. Incorporation of DTX by both chemical and physical entrapment
resulted in significantly greater loading and slower release of the physically entrapped
drug relative to BCMs containing no chemically conjugated drug. This phenomenon was
attributed to improved compatibility between DTX and the core-forming block containing
conjugated DTX (PCL-DTX) relative to unmodified BCMs (PCL alone) and
demonstrated the potential to customize both drug loading and release properties of the
nanocarrier system. In addition, due to a high drug loading capacity, the BCMs were
capable of dramatically enhancing the solubility of DTX. Interestingly, it was also found
that chemical conjugation of DTX to the core of the micelles resulted in profound
changes in micelle morphology. In fact, conversions between spherical and rod-like
morphologies were controlled simply by altering the ratio of unmodified copolymer to
DTX-conjugated copolymer incorporated into the BCMs. This was an important finding
as the shape of nanocarriers has recently been shown to have significant implications in
drug delivery in terms of its influence on drug loading and circulation longevity. The role
of BCM morphology in determining intratumoral distribution and penetration is also of
great interest and warrants future investigation.
In the next phase of research, the therapeutic efficacy of the BCM+DTX
formulation was assessed in MCTS cultures as a means for evaluating the influence of
the 3-D tumor microenvironment on the performance of nanomedicines. Both
BCM+DTX and Taxotere® demonstrated significantly less cytotoxic activity against
Chapter 5. Summary and Future Directions
99
MCTS cultures relative to monolayers. The degree to which culturing cells as MCTS
increased their resistance to treatment relative to monolayers was different for each cell
line due to cell line-specific differences in MCTS structure and microenvironment. For
instance, culturing cells as MCTS imparted a greater enhancement in therapeutic
resistance to HT29 cells than to HeLa cells. Histological examination revealed that
HT29 MCTS contained fewer proliferating cells and a greater degree of hypoxia and
necrosis relative to HeLa MCTS. It was also found that cells treated immediately
following their recovery from disaggregated spheroids retained residual heightened drug
resistance relative to cells grown and treated as monolayers. These findings
demonstrated that drug resistance in 3-D tumor tissues is due in part to mechanisms of
resistance associated with properties of the tissue microenvironment. Interestingly, the
DTX-loaded micelles demonstrated greater cytotoxicity than Taxotere® both in
monolayer and spheroid cultures. Heightened in vitro cytotoxicity of nanoparticle-
encapsulated chemotherapies has been attributed elsewhere to differences in the rate
of cellular uptake and efflux relative to free drug, among other potential mechanisms
[256, 285–287]. This promising result warrants further study, including examination of
cellular uptake and efflux kinetics as well as comparative investigations of efficacy in
tumor xenograft models.
Having identified microenvironmental parameters which may limit the efficacy of
therapy, the focus of Chapter 4 was to investigate the ability of nanoparticles to
penetrate 3-D tumor tissues. A computational method was implemented for the direct
comparison of the spatial and temporal penetration of BCMs in both a 3-D in vitro tissue
model and human tumor xenografts. Specifically, the in vivo penetration of BCM-55 into
the tumor interstitium was found to be slower than BCM-15 and reached a maximum
depth of penetration at 24 h p.i. BCM-15 exhibited more rapid and greater interstitial
transport with its maximum signal intensity occurring at 6 h p.i. Furthermore, significant
clearance of BCM-15 from the tumors had occurred by 24 h post injection while BCM-55
was well retained. Greater permeability of HeLa MCTS and xenografts relative to HT29
were attributed to differences in cell packing density and the size of intercellular
channels. Overall it was determined that the penetration of nanocarriers in tumor tissues
was nanoparticle-size-, tumor tissue type-, and time-dependent. In the future this
method of analysis can be applied to track the independent fate of the drug and
100
nanocarrier with respect to cellular markers of toxicity in order to evaluate the influence
of nanoparticle properties on drug distribution and therapeutic efficacy.
This research has demonstrated potential limitations in the therapeutic efficacy of
nanomedicines due to both transport limitations associated with 3-D tumor tissues as
well as resistance associated with properties of the tumor microenvironment.
Importantly, a series of assays was established and validated for the comprehensive
evaluation of nanomedicines using a 3-D in vitro tissue model that approximates
important conditions associated with drug resistance in solid tumors. Computational,
image-based methods were successfully applied for evaluating nanoparticle penetration
in tumor tissues at the sub-micron level using both in vitro and in vivo tumor models.
Results obtained in MCTS cultures reflected trends in the tumor tissue penetration of
nanoparticles in vivo thus establishing the model as a valuable tool for optimizing
transport properties of nanomedicines in vitro. Future work will seek to evaluate the
predictive capacity of MCTS in terms of therapeutic efficacy in tumor xenografts.
5.2 Future Directions
5.2.1 Improving drug retention and tumor-specific drug delivery
The degree to which a nanoparticle can influence the in vivo disposition of a drug
depends upon the extent to which the drug is retained following administration. Drugs
that remain encapsulated within the nanoparticle will adopt the transport,
pharmacokinetics, and clearance properties of the delivery system [33–35, 288]. In
contrast, drugs that are rapidly released from the nanoparticle will acquire a similar in
vivo fate to that of free drug [31, 32, 289]. Ideally, the drug should remain encapsulated
until the nanoparticles have sufficiently accumulated in the tumor. In reality, drug
delivery systems must strike a balance between drug retention and the bioavailability of
the drug at the tumor site. This balance will require careful consideration of the
demands of a specific therapy which may benefit from more rapid or more sustained
release of the therapeutic agent. In some cases achieving significant improvements in
drug solubility by replacing toxic solubilizing excipients with inert synthetic copolymers is
sufficient to reduce the severity of side effects or allow for the implementation of a more
101
aggressive dosing strategy. However, truly tumor-specific drug delivery systems hold
the greatest promise in terms of achieving significant advancements in treatment
outcomes.
In the case of BCMs, efforts have been made to improve the retention of the drug
in the micelle core in order to increase tumor-specific drug delivery. Several BCM-based
formulations are undergoing clinical trial evaluation based on this research [197]. In this
thesis, chemical conjugation of the drug to the micelle core was demonstrated as one
possible approach for improving the retention of freely encapsulated drug due to an
improvement in core-drug compatibility. The conjugated drug itself was released very
slowly via hydrolysis of the ester linkage between DTX and the hydrophobic block of the
copolymer. In the future, it is worth exploring the development of so called “triggered
release” or “environmentally responsive” systems. In these systems, the drug is
released following exposure to environmental stimuli unique to the physiology of tumors.
Alternatively, exposure to externally applied stimuli, such as heat, ultrasonic waves and
magnetic fields may be applied to the tumor in order to trigger or guide drug release. In
the case of the BCM+DTX formulation developed in this thesis, inclusion of pH sensitive
or enzymatically cleavable chemical linkers may be an important next step for improving
the tumor-specific delivery of DTX.
5.2.2 Therapeutic efficacy and the intratumoral fate of DTX
Although the findings in this thesis provide important insight into the transport of BCMs
at the intratumoral level, the analysis was limited to assessment of delivery vehicle
distribution and did not report the fate of DTX itself. Yet, since we are ultimately
interested in the access of tumor cells to therapeutic concentrations of DTX rather than
to the carrier itself, evaluating the independent fate of DTX and the BCMs is an
important future direction for this research. For example, it is plausible that drug carriers
confined to the perivascular space may act as drug reservoirs for sustained release of
the drug over an extended period of time. In this scenario, the efficacy of treatment may
depend on the rate of release and interstitial penetration of the drug rather than solely
on the distribution of the delivery vehicle itself. The image-based methodology for
evaluating intratumoral penetration described in Chapter 4 can be used to analyze the
relative distribution of any two (or more) fluorescent (or chromogenic, autoradiographic)
102
signals in the tumor. Therefore, this procedure is expected to serve as the basis for
future investigations into the relationship between the intratumoral distribution of drug
and nanocarrier, the tumor microenvironment and therapeutic efficacy.
Since the response of tumor cells to a drug is highly dependent on conditions
within the local tumor microenvironment, it would be beneficial to evaluate the
intratumoral distribution of downstream markers of cytotoxic effects rather than directly
assessing the distribution of the drug. For example, identification of cleaved caspase-3
or gamma-H2AX, markers of apoptosis and DNA double-strand breaks, respectively,
would provide invaluable insight into therapeutic response within the context of the local
tumor microenvironment [26, 243]. This analysis can be correlated to therapeutic
efficacy observed in traditional growth delay experiments in mice bearing human tumor
xenografts. In fact, tumor sections can be analyzed at various time points throughout
the trial, providing insight into changes in the distribution of therapeutic activity in the
tumor that may occur during the course of treatment. Changes in important properties of
the tumor microenvironment (ex. hypoxia) or proliferative activity of cells can also be
evaluated following treatment with nanomedicines. It is also of particular interest to
apply these analyses following administration of tumor “modulators” [290, 291] in order
to investigate the potential to actively circumvent barriers to nanoparticle penetration
and therapeutic efficacy associated with the 3-D tumor microenvironment, discussed in
greater detail below.
5.2.3 Overcoming transport barriers by modulating the tumor microenvironment
Effective delivery of a chemotherapeutic agent from the site of administration to its
cellular target is a multi-step process that requires accumulation at the tumor, adequate
distribution via the tumor vascular network, extravasation and permeation of the
interstitial space. However, each of these steps is associated with a number of
physiological barriers which limit the transport of drugs at the intratumoral level, as
discussed in Chapters 3 and 4. Moreover, even if a therapeutic agent reaches its target,
the drug’s efficacy may be greatly diminished in regions of hypoxia and/or limited
cellular metabolic and proliferative activity. Therefore, future studies may include
attempts to circumvent these barriers by altering properties of the tumor
103
microenvironment for the purpose of improving the intratumoral distribution and
penetration of nanomedicines. For example, Kataoka`s group demonstrated an
enhancement in nanoparticle extravasation and penetration following administration of a
TGF-β inhibitor resulting in a reduction in tumor fibrosis and pericyte coverage of the
endothelium in a hypovascular, fibrotic pancreatic tumor model [292, 293]. Similarly,
Jain’s group demonstrated enhanced penetration and efficacy of a nanomedicine
following inhibition of collagen I synthesis by administration of losartan, a clinically
approved compound with recognized antifibrotic activity [294]. In another approach,
conjugation or coating of collagenase to nanoparticles induced ECM-penetrating
properties that enhanced their transport in ECM gels and tumor spheroids [295, 296].
Enhanced penetration in the spheroids was attributed to an increase in the accessible
space (volume fraction) and a decrease in frictional resistance to diffusion [296].
Alterations to the composition of the ECM have also been shown to facilitate
extravasation by altering tumor IFP. Eikenes et al. reported a reduction in tumor IFP
following intratumoral injection of hyaluronidase, an ECM-degrading enzyme, resulting
in an increase in the transcapillary pressure gradient which promoted the tumor
accumulation and penetration of Caelyx™ (liposomal doxorubicin) [297]. Modulators of
tumor vascular permeability and systemic blood pressure have also been investigated
for the purpose of enhancing transvascular transport and the EPR effect [68].
The theory of “vascular normalization”, largely advanced by Jain and coworkers,
describes the administration of anti-angiogenic therapies to return the leaky, tortuous
tumor vasculature to its more natural architecture [298, 299]. Consequently, normal IFP
is restored, enhancing convective flow in the interstitium resulting in improved transport
of therapeutic agents. However, this approach must be applied with care, as anti-
angiogenic agents are also known to reduce the density or permeability of tumor-
associated vessels leading to a potential reduction in the tumor uptake and penetration
of subsequently administered nanomedicines [300]. Recently, promising alternative
approaches for enhancing drug accumulation and penetration have been reported
including use of hyperthermia [301], high-intensity focused ultrasound [302] and
radiation [303]. The co-administration of nanomedicines and external modulators of the
tumor microenvironment remains an exciting potential area of research, worthy of
further investigation.
104
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Appendix 1: Chapter 3 Supplemental Data
Figure A1: a) Schematic representation of the analysis process using a macro
developed for ImageJ, version 1.44m. The volume was derived from the area of the
MCTS assuming a spherical shape: . b) Correlation between manual and
automated volume measurements of HeLa MCTS. 1000 cells were seeded and the
volume of the MCTS was determined every 2 days for 10 days by manually measuring
the diameter and automatically by image recognition using a macro for ImageJ.
Methods
MCTS were imaged at selected intervals of growth and their size was determined by
measuring their 2-D cross-sectional area using an automated image analysis macro
developed for use with the ImageJ software package (Version 1.44m). Images were
converted into 8-bit greyscale, the perimeter of an individual MCTS was recognized by
an automated threshold function and the area of the 2-D MCTS mask was recorded and
HeLa Volume
0 2.010 7 4.010 7 6.010 7
0
2.010 7
4.010 7
6.010 7
Volume of MCTS Manual Measure (m3)
Volu
me o
f M
CT
S A
uto
Measure
(m
3)
a)
b)
141
converted to μm2 by calibration using an image of known scale. Finally, the volume of
the MCTS was calculated by assuming a spherical shape as follows:
where V is the volume and A is the measured area. Growth curves were plotted as
mean spheroid volume of 30 MCTS vs. time and fit using the Gompertz growth equation
[243] .
0 5000 10000 15000 200000.0
0.2
0.4
0.6HT29
HeLa
Cells per well
OD
405
0 10000 20000 300000.0
0.5
1.0
1.5
2.0
2.5
HeLa
HT29
Cells per spheroid
OD
405
0 200 400 600 8000.0
0.5
1.0
1.5
2.0
2.5HT29
HeLa
Spheroid diameter
OD
405
Figure A2: Validation of the acid phosphatase assay (APH) for HeLa and HT29 cells
grown in monolayer (left) and spheroid culture (center and right) demonstrating a linear
relationship between cell number and UV absorption at 405 nm. Each data point
represents the mean of three independent experiments ± SD (n = 3)
Figure A3. WST-8 assay showing non-linear correlation between the number of cells
and OD450 in spheroid culture.
142
Figure A4. Fluroescence images of HT29 (a, b) and HeLa (c, d) tumor xenografts
displaying markers of hypoxia (EF5, blue) and blood vessels (CD31, red). Fluroescence
signal of 55 nm BCMs is shown in green at 1 h p.i. Scale bars represent 100 µm.
a) b)
c) d)
143
Appendix 2: Chapter 4 Supplemental Data
Table T1. Area under the curve (AUC), Dmean (mean penetration distance), and intensity
values for fluorescent BCMs in HeLa and HT29 tumor xenografts at selected distances
from the nearest blood vessel.
Cell Line Sample
Time post injection, h AUC
Dmean, µm
Fluorescence Intensity at 5 µm
Fluorescence Intensity at 50 µm
Fluorescence Intensity at 100 µm
HeLa BCM55 1 148.51 27.2 9.78 +/- 1.74 1.40 +/- 0.58 0.40 +/- 0.12
6 160.92 30.4 9.70 +/- 2.27 2.03 +/- 0.56 0.62 +/- 0.44
24 154.38 36.8 5.20 +/- 1.14 3.28 +/- 0.48 0.67 +/- 0.30
BCM15 1 176.09 33.9 9.76 +/- 0.98 2.16 +/- 0.39 1.11 +/- 0.12
6 150.72 40.2 6.00 +/- 1.17 2.59 +/- 0.64 1.33 +/- 0.61
24 117.38 37.2 4.19 +/- 0.62 1.90 +/- 0.46 0.32 +/- 0.03
HT29 BCM55 1 61.32 18.7 6.36 +/- 0.72 0.26 +/- 0.24 0.09 +/- 0.06
6 82.60 26.3 7.06 +/- 1.19 0.61 +/- 0.30 0.26 +/- 0.23
24 112.76 32.6 6.51 +/- 0.79 1.24 +/- 0.69 0.48 +/- 0.02
BCM15 1 142.37 35.9 6.31 +/- 1.48 1.83 +/- 0.51 0.86 +/- 0.06
6 134.68 37.8 5.65 +/- 1.37 1.83 +/- 0.95 0.81 +/- 0.31
24 68.89 29.3 5.24 +/- 0.69 0.41 +/- 0.22 0.17 +/- 0.09
0.00
0.05
0.10
0.15
0.20
HeLa
HT29
co
lla
ge
n
g/m
g w
et
tissu
e
Figure A1. Collagen content in HeLa and HT29 MCTS after 7 days of growth. Collagen
content is reported per mg of wet tissue ± SD.
144
Method
Collagen content was determined by first incubating MCTS in papain digest buffer (125
µg/ml papain, 0.1 M Na-Phosphate, 5 mM Na2EDTA and 5 mM Cystein-HCL) at 60 °C
overnight. Solubilized samples were hydrolyzed in 6 M HCL at 110 °C for 24 h prior to
evaporation of the acid at 65 °C and further drying under vacuum conditions. The
residue was dissolved and neutralized in a 1:10 dilution of the stock buffer (stock buffer:
18.08 g sodium acetate, 12.5 g citric acid, 3 ml glacial acetic acid, 8.5 g sodium
hydroxide in 250ml ddH2O; pH 6.5). Chloramine-T solution (70 mg chloroamine T in 1
ml of ddH2O, 1.5 ml Methyl cellosolve and 2.5 ml stock buffer) was added to the sample
and incubated for 20 min at RT. Following disintegration of chloroamine T by 3.15 M
perchloric acid, Ehrlichs reagent was added to the sample (200 mg of dimethyle-
aminobenzaldehyde dissolved in 1ml of Methyl cellosolve) and incubated 20 min at 60
°C. After cooling in cold water the absorbance was measured within 30 min using a UV
spectrometer (SpectraMax Plus 384, Molecular Devices, Sunnyvale, CA) at 560 nm.
Concentration of the hydroxyproline was determined from a standard curve and
collagen content was calculated assuming 13% hydroxyproline content.