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Imaging Biomarkers of Response to Radiation and Anti-angiogenic Agents
in Brain Tumors
by
Caroline Chung
A thesis submitted in conformity with the requirements for the degree of Masters of Science
Institute of Medical Science University of Toronto
© Copyright by Caroline CHUNG 2011
ii
Imaging Biomarkers of Response to
Radiation and Anti-angiogenic Agents in Brain Tumors
Caroline CHUNG
Masters of Science
Institute of Medical Science University of Toronto
2011
Abstract
There is mounting evidence to support combined therapy with radiation (RT) and anti-
angiogenic agents (AA) for the treatment of brain tumors. However, the therapeutic benefit of
this combined treatment hinges on the specific dose, schedule, and duration of each treatment.
Early biomarkers that reflect tumor physiological responses provide key information that could
guide these aspects of treatment. Pre-clinical tumor models are invaluable tools for identifying
potential biomarkers, their optimal timing for measurement and their ability to guide therapy in
clinical translation. This thesis demonstrates the feasibility and potential of serial MRI to guide
the design, delivery and measure of early response to combined AA and RT in a murine
intracranial glioma model. We identified promising biomarker changes reflecting early
treatment response that may ultimately facilitate individualized spatio-temporal delivery of
radiotherapy (RT) and anti-angiogenic agents (AA) for brain tumors.
iii
Acknowledgments
I wish to thank my supervisor Dr Cynthia Ménard for her valuable time, advice and mentorship
throughout my fellowship, research and ongoing career adventure. I would like to thank my Program
Advisory Committee for guiding me and helping me grow through the past 2 years. I would like to
express special gratitude to Dr. Michael Milosevic, who has dedicated exceptional time to guide the
development of this project, manuscript and thesis and who has provided an open door for
mentorship.
Thank you to the Brain Tumor Research Centre laboratory and all the members of the lab for
welcoming me in, especially Kelly Burrell for her time and support. Special thanks to Dr.
Gelareh Zadeh for her mentorship, guidance and support in the lab and ongoing research
collaborations.
Thank you to STTARR and the research team involved in the serial MRI protocol development
and experimental acquisition and data analysis: Debbie Squires for her tail vein expertise, Jesper
Kallehauge for his time and contribution to the diffusion MRI analysis and Petra Wildgoose for
her keen participation and assistance with serial MRI and urine acquisition. A special thank you
to Warren Foltz for all the hours of MRI imaging and data analysis, Patricia Lindsay for
facilitating the small animal irradiation and dosimetry calculations and Dr. Andrea Kassner for
her contribution as part of team who developed the DCE-MRI protocol used in this study.
Thanks to the UBC Clinical Investigator Program for their financial support and Dr. Sian Spacey for
her guidance and support throughout this experience.
Thanks to CARO and Astra Zeneca for the RAZCER grant funding to make this project possible and
to Pfizer for providing sunitinib for this project. Thanks to Anthony Brade for liaising with Pfizer
and assisting in generating drug support for this study.
To my parents, thank you so much for all your unconditional love, endless support and
encouragement and your confidence in me over all these years.
Finally, a special dedication to Dr. Barry Sheehan, who was not only my CIP supervisor but a true
mentor who lead my career into Radiation Oncology, encouraged me to pursue my research interests
and always reminded me to “Carpe Diem”.
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Table of Contents
Acknowledgments .......................................................................................................................... iii
Table of Contents ........................................................................................................................... iv
List of Tables ................................................................................................................................ vii
List of Figures .............................................................................................................................. viii
List of Appendices ......................................................................................................................... xi
Chapter 1 Introduction/Literature Review ...................................................................................... 1
1 Overview .................................................................................................................................... 1
1.1 Brain Tumor Vasculature and Angiogenesis ...................................................................... 1
1.1.1 Angiogenic Factors ................................................................................................. 3
1.2 Anti-angiogenic Agents and Brain Tumors ........................................................................ 5
1.2.1 Sunitinib .................................................................................................................. 7
1.3 Radiation and Brain Tumors ............................................................................................... 7
1.4 Anti-angiogenic Agents with Radiation .............................................................................. 8
1.4.1 Balance of Pro-angiogenic Factors ......................................................................... 8
1.4.2 Vascular Normalization .......................................................................................... 8
1.4.3 Endothelial Cell Death ............................................................................................ 9
1.4.4 Importance of Treatment Timing and Duration ...................................................... 9
1.5 Imaging Brain Tumors ...................................................................................................... 10
1.5.1 Current Standard for Imaging Response Measures .............................................. 11
1.5.2 Functional MRI Response Measures .................................................................... 12
1.6 Biomarkers ........................................................................................................................ 19
1.6.1 Imaging Biomarkers .............................................................................................. 19
1.6.2 Biofluid Biomarkers .............................................................................................. 20
1.7 Tumor Models for Brain Tumors ...................................................................................... 21
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1.8 Conclusion ........................................................................................................................ 21
Chapter 2 Aims/Hypotheses ......................................................................................................... 23
2 Thesis Hypothesis: ................................................................................................................... 23
2.1 Aim 1: ............................................................................................................................... 23
2.2 Aim 2: ............................................................................................................................... 24
2.3 Aim 3: ............................................................................................................................... 24
Chapter 3 Development of a Synchronized Tumor Model and Imaging Protocol ...................... 25
3 OVERVIEW ............................................................................................................................ 25
3.1 INTRODUCTION ............................................................................................................ 25
3.1.1 ANIMAL TUMOR MODELS .............................................................................. 25
3.1.2 PURPOSE ............................................................................................................. 27
3.2 METHODS & MATERIALS ........................................................................................... 27
3.3 RESULTS ......................................................................................................................... 32
3.3.1 MOUSE MODEL ................................................................................................. 33
3.4 DISCUSSION ................................................................................................................... 41
3.4.1 CONCLUSION ..................................................................................................... 44
Chapter 4 Imaging Biomarker Dynamics in Intracranial Murine Glioma Study of Radiation and Anti-angiogenic Therapy ................................................................................................... 45
4 Abstract .................................................................................................................................... 46
4.1 INTRODUCTION ............................................................................................................ 47
4.2 METHODS & MATERIALS ........................................................................................... 48
4.3 RESULTS ......................................................................................................................... 54
4.4 CONCLUSIONS ............................................................................................................... 70
Chapter 5 Towards Individualized Image-Guided Spatio-Temporal Delivery of Combined Cancer Therapeutics ................................................................................................................. 71
5 General Discussion ................................................................................................................... 71
5.1 Tumor Model and Experimental Design ........................................................................... 71
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5.2 Treatment Delivery ........................................................................................................... 72
5.3 Response Evaluation ......................................................................................................... 75
5.3.1 Imaging ................................................................................................................. 75
5.3.2 Biofluid ................................................................................................................. 80
5.4 Future Directions and Translation .................................................................................... 81
5.5 Conclusions ....................................................................................................................... 82
6 References ................................................................................................................................ 84
Appendices .................................................................................................................................. 100
vii
List of Tables
Table 1.1 Anti-angiogenic agents in brain tumors……………………………………6
Table 4.1Multiparametric MRI Protocol…………………………………………….52
viii
List of Figures
Figure 3.1 Relationship between standard deviation in ADC (%) and signal-to-noise (SNR)…31
Figure 3.2 Diagram highlighting the interaction and interdependence of the multiple factors
considered during the concurrent development of a tumor model and multiparametric MRI
protocol for experimentation with radiation and anti-angiogenic therapy. TV injection = tail-vein
injection protocol, highlighted in a red box, was developed over a series of injection studies to
determine the details of the gadolinium injection protocol MRI sequences included in the final
multiparametric MRI protocol are highlighted in blue………………………………………......32
Figure 3.3 Axial T2-weighted MR images of tumors at day 14 following IC injection with
1 x 106 cells of U87 glioma cell line (left) and MDA-MB231 breast cell line (right). The arrow
indicates a large area of intratumoral hemorrhage, which appears as a hypointensity on the T2-
weighted image due to susceptibility of deoxyhemoglobin………………………………….......34
Figure 3.4 Axial T2-weighted MR (left frame) and dynamic contrast-enhanced MR image (right
frames) for (a) U87 glioma tumor (b) MB-231 breast tumor at day 14 after IC injection into the
right frontal lobe. Heterogeneous enhancement with gadolinium contrast is visible in the U87
tumor (top) whereas no contrast enhancement is seen in the MB231 tumor
(bottom)…………………………………………………………………………………………..35
Figure 3.5 (a) Axial T1-weighted MR images of a mouse pre- and post-contrast to demonstrate
the posterior cerebral artery that was identifies as a reliable vessel for measurement of an arterial
input function. (b) Signal Intensity (SI) curve of the arterial input function (AIF) and tumor with
a 10µL injection of 20:1 Gd-DTPA:Hep-saline over 6 seconds…………………………………38
Figure 3.6 DCE-MRI Protocol Development Experiments…...………………………………....39
Figure 4.1 Timeline of the treatments and MRI imaging sessions. MRI on day 0 confirmed and
measured the volume of gross tumor at baseline. Sunitinib (SU) was delivered for 7 weekdays.
Radiation (RT) 8Gy in 1 fraction was delivered on day 1 of treatment, after the first dose of SU.
Multiparametric MRI was acquired bi-weekly on days 3, 7, 10, and 14………………………...49
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Figure 4.2 Flow Diagram Summarizing Experiment 1: Radiation and Sunitinib Study. Following
intracranial (IC) injection, mice were imaged for baseline tumor size at day 7 after which they
were randomized to the 4 treatment arms: placebo, placebo + radiation (RT), sunitinib (SU) and
SU + RT. For each treatment arm, a proportion of the mice were followed with serial
multiparametric MRI and the remaining mice were followed for survival analysis…………….50
Figure 4.3 (a) Representative intracranial tumors at baseline demonstrating the variability in size
and location (b) Representative images used for radiation planning and dose evaluation: (i) Axial
co-registered baseline T1-weighted gadolinium-enhanced MRI and treatment day cone-beam CT
(ii) Axial cone-beam CT image with radiation isodoses (10% orange, 90% red, 95% teal) around
the tumor (blue) and the isocentre at the centre of the 2 axes. The isocentre was placed using
visual estimation of the tumor location on the CBCT, using baseline MR
information……………………………………………………………………………………….55
Figure 4.4 (a) Survival curves. Median survival was 35 days for combined sunitinib and radiation
(SU+RT), 30 days for both radiation (RT) and sunitinib (SU) monotherapies, and 26 days for
placebo. (b) Tumor growth curve with mean relative tumor volume for each treatment group
shown on a logarithmic scale. Daily LN tumor growth rate increases in the non-radiation control
and SU groups (0.08 and 0.098, respectively) were greater than daily growth rate increases in the
SU+RT and RT groups (0.029 and 0.025, respectively), p<0.001. Error bars represent standard
deviation………………………………………………………………………………………….57
Figure 4.5 (a) Representative images of DCE-MRI with standard location of AIF and typical
tumor ROI. (b) Signal Intensity Curve for the mean AIF of all mice imaged in this experiment
with error bars representing the standard deviation……………………………………………...60
Figure 4.6 (a) Mean percent change in iAUC60 for each treatment arm over time from baseline
to day 14 (b) Mean percent change in iAUC60 of the ROI from baseline for each treatment arm
at treatment day 3 (c) Mean percent changes in iAUC60 of the AIF from baseline for each
treatment arm at treatment day 3. Error bars reflect standard deviation…………………………61
x
Figure 4.7 (a) Mean percent change in Ktrans for each treatment arm over time from baseline to
day 14. Percent change from baseline to treatment day 3 (D3) for each treatment arm: (b) Ktrans,
based on modified Tofts analysis (c) Kep, based on modified Tofts analysis (d) pre-contrast tumor
T1, demonstrating the wide inter and intra-group variability. (e) Ktrans based on modified Tofts
analysis using population mean T1 and individual T1 values. Error bars represent standard
deviation………………………………………………………………………………………….62
Figure 4.8 (a) Percent change in ADC tumor/ADC contralateral brain over time (b)
Representative T1-weighted gadolinium-enhanced images and apparent diffusion coefficient
(ADC) maps at baseline and on treatment day 3 (D3) for a mouse treated with radiation and
sunitinib (c) Relative changes in ADC (day 3/day 0) in each treatment arm, demonstrating a
greater increase in ADC for the two RT arms vs. non-RT arms in both for experiments 1 and 2.
Experiment 2 showed significant rises for SU+RT 2.35 (p=0.003) and RT 2.48 (p=0.045) vs.
control 1.33 (p=0.2) and SU 1.34(p=0.2) (d) Correlation of mean relative change in ADC for
each mouse from baseline to treatment day 3 versus Ln(tumor growth rate)…………………64
Figure 4.9 Summary of relative changes in candidate urine biomarkers from baseline to treatment
day 4 for placebo, sunitinib monotherapy (SU) and sunitinib + radiation (SURT) arms. From the
panel of biomarkers measured, this figure summarizes the candidate biomarkers that showed
notable changes with treatment. The radiation monotherapy arm could not be fully analyzed due
to limited sample volume……………………...…………………………………………………65
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List of Appendices
Appendix I: A Phase I Study of Stereotactic Radiosurgery Concurrent with Sunitinib in Patients
with Brain Metastases
Appendix II: Discovery of biomarkers to guide individualized therapy in patients with brain
metastasis receiving radiotherapy
1
Chapter 1 Introduction/Literature Review
1 Overview
Until recently, the treatment of brain tumors has been limited largely to surgery and radiation.
However, both of these local modalities have associated toxicities and challenges that limit the
ability to provide curative treatments in many cases. For surgery, the anatomical location can
limit the extent of resection. For radiotherapy, dose constraints to surrounding normal brain,
particularly to critical normal structures, can often limit our ability to deliver adequate curative
doses of radiation. There have been ongoing efforts to introduce systemic therapy in
combination with the local treatment modalities to maximize the therapeutic ratio. More
recently, the introduction of anti-angiogenic agents has raised the possibility of combining these
targeted agents with radiation to enhance treatment response. When combining multiple
therapies, there are several factors that may impact outcome, including dose, schedule and timing
of treatments, as well as appropriate patient selection. Early non-invasive biomarker measures of
physiological response to treatment that can be followed over time may help determine these
factors and thereby guide individualized multimodality treatment.
1.1 Brain Tumor Vasculature and Angiogenesis
Due to the limits of oxygen and nutrient diffusion, tumors can only grow to sizes of 1–2mm3
before their metabolic demands are restricted. In order to grow beyond this size, the tumor needs
to switch to an angiogenic phenotype.[1] However, other mechanisms for tumor vessel
development have been described more recently, including vessel co-option, vasculogenic
mimicry, and intussusception. [1] Vessel cooption is the use of pre-existing vessels in the
surrounding normal tissue by the tumor. [2] In various preclinical models of primary or
metastatic brain tumors, co-option of pre-existing vessels has been observed. [3] Vessel
intussusception involves the formation vascular tissue into the lumen of a pre-existing blood
vessel such that the vessel is split into two new vessels.[4] Vasculogenesis is the creation of new
blood vessels when there were no pre-existing ones. This is thought to involve the colonization
of circulating endothelial or other proangiogenic cells, primarily facilitated by bone marrow-
derived cells. [5]
2
Angiogenesis, also called sprouting angiogenesis, is the development of new vessels from pre-
existing ones, [6] and this process has been thought to be the primary mechanism of vessel
development in solid tumors. [7] The angiogenic process generally creates blood vessels that are
structurally and functionally abnormal and dysfunctional. The vessels are typically leaky,
dilated, tortuous and disorganized. [8] Functionally, these vessels are inefficient at delivering
oxygen, nutrients, as well as therapeutic agents, such as chemotherapy, to tumors. [9] Among all
solid tumors, glioblastoma is the most angiogenic with the highest degree of vascular
proliferation and endothelial cell hyperplasia.[10] Additionally, the presence of microvascular
proliferation is a histopathological hallmark of glioblastoma, which distinguishes this high-grade
astrocytoma from low-grade astrocytomas.[11]
When tumors undergo the processes involved in the angiogenic switch, in addition to the
development of new blood vessels, tumors have increased invasive and metastatic properties.
This likely reflects the upstream and downstream pathways common to all of these processes.
[12] The mechanism and molecular pathways involved in angiogenesis have been studied
extensively and the key players in these pathways are highlighted below. For an individual
tumor vessel, the complex interaction of these multiple growth factors involved in the angiogenic
process determines the final outcome regarding vessel growth. [13]
In gliomas, tumor vascularity has been correlated with both higher pathology grade and shorter
survival.[14, 15] Angiogenesis is thought to be the predominant mechanism of vascular
development in brain tumors.[16] It is thought to be driven by tumor hypoxia, which results in
chronic activation of the HIF pathway and increased production of vascular endothelial growth
factor (VEGF) and basic fibroblast growth factor (bFGF).[17] Genetic factors in gliomas can
also result in chronic activation of the hypoxia inducible factor (HIF) pathway via the
intracellular phosphatidylinositol 3-kinase or mitogen-activated protein (MAP) kinase
pathways.[18] Therefore, a growing number of studies are investigating the role of targeted
agents that would inhibit these pathways. As with several other solid tumors, vasculogenesis
has been suggested as an additional mechanism for vascular development in gliomas, based on
the presence of bone marrow endothelial progenitor cells (EPCs) in tumor. However, there have
been wide variability in the level of EPCs ranging from 0 – 50% and therefore the degree to
which this process occurs in gliomas is yet to be elucidated.[19] Recent studies show that the
role of vasculogenesis may be greater in the regrowth of glioblastoma following irradiation and
3
that there is greater potential for targeted therapies to inhibit tumor regrowth by inhibiting
vasculogenesis in this situation.[5]
1.1.1 Angiogenic Factors
A number of signaling pathways have been implicated in angiogenesis in brain tumors including
VEGF, platelet-derived growth factor (PDGF), bFGF, angiopoietins, epidermal growth factor
(EGF), hepatocyte growth factor (HGF) and a number of other cytokines.
Vascular endothelial growth factor is the most potent pro-angiogenic factor. [20] It activates
endothelial cell proliferation and increases the expression of matrix metalloproteinases and
plasminogen activators, which degrade the extracellular matrix and thereby facilitates endothelial
cell migration. [21] VEGF is also a potent factor that induces vasodilation and increases
permeability of the existing vessels by causing a loss of pericyte-endothelial integrity. [22, 23]
There are six members of VEGF family of growth factors: VEGF-A, VEGF-B, VEGF-C, VEGF-
D, VEGF-E and placental growth factor. These interact differentially with three cell surface
receptor tyrosine kinases called VEGF receptors (VEGF-R).[4] For sprouting angiogenesis, the
VEFG-A and VEGFR2 interaction plays a major role. Measured levels of VEGF generally have
been higher in tumors, particularly those with worse prognosis and with greater resistant to
conventional chemotherapy and radiation treatment, such as malignant gliomas and
melanomas.[24] In vivo treatment with antibody or small-molecule inhibitors of VEGF or
VEGF-R have shown effective inhibition in a number of tumor cell lines and suggest promising
treatments to overcoming treatment resistance. [20] Vascular endothelial growth factor is over-
expressed in GBM and the VEGF/VEGFR-2 pathway is the predominant mechanism for
angiogenesis in glioblastomas.[25, 26] However, attempts to inhibit this pathway with anti-
VEGF agents has resulted a wide variation of overall response and durability of responses,
suggesting that not all malignant gliomas are dependent on the VEGF-VEGFR pathway.[26]
Basic fibroblast growth factor, also known as FGF-2, stimulates all major steps in the
angiogenesis cascade. It is produced by macrophages, endothelial cells and tumor cells and
released in the extracellular matrix, initiating angiogenesis. In addition to angiogenesis, bFGF is
involved in endothelial cell proliferation and migration, and degradation of the extracellular
matrix. [27] In both mouse and human tumors, bFGF has been shown to be involved in tumor
growth and neovascularization [28]
4
Platelet-derived growth factor (PDGF) and its receptor, platelet-derived growth factor receptor
(PDGFR) are not directly pro-angiogenic. But all members of the PDGF family have strong
angiogenic effect indirectly stimulating proliferation of fibroblasts and vascular smooth muscle
cells. [29] As FGF2 potently stimulates EC proliferation but has almost no effect on chemotaxis
and PDGF induces endothelial cell migration but not proliferation, only when both systems
become activated does coordinated EC proliferation and migration occur, allowing for vessel
growth.[30]
Epidermal growth factor is a potent mitogenic factor for endothelial cells, therefore binding to
EGFR (ErbB-1, HER1) increases the proliferation of endothelial cells.[31] Furthermore EGF can
stimulate VEGF expression in gliomas, which can act in an autocrine or paracrine manner.[20]
In tumors with the mutant EGFRvIII, which is constitutively activated, VEGF expression is
induced through the Ras/MAPK and NF-κB pathways.[32-34] Expression of EGFRvIII has
been associated with faster rates of double strand repair and increased radioresistance.[35]
There are 3 members of the angiopoietin family of growth factors involved in angiogenesis:
angiopoietin-1 (Ang-1), angiopoietin-2 (Ang-2) and angiopoietin-4(Ang-4). These growth
factors all bind to the endothelial tyrosine kinase receptor Tie-2 but the binding of each ligand to
this receptor results in widely different effects.[4] When Ang-1 binds to Tie-2, it activates the
Tie-2 to increase endothelial cell migration and adhesion as well as recruitment of pericytes and
smooth muscle cells to stabilize vessels.[36] When Ang-2 binds to Tie-2, Tie-2 is inhibited
therefore vessels are de-stabilized by disruption of endothelial cells and perivascular cells.[37]
Ang-2 also increases the expression of matrix metalloproteinase (MMP)-2, and acts with VEGF
to promote angiogenesis.[38, 39] Glioblastomas are known to express Tie-2 and its ligands Ang-
1 and Ang-2. In human GBM, Tie-2 expression is restricted to blood vessels and the level of
expression and phosphorylation of Tie-2 has been associated with grade of glioma.[39, 40]
Finally, a recent study reports that Ang-4 also binds to Tie-2 resulting in very potent
proangiogenic activity and increased GBM cell survival.[41]
Cytokines that have been implicated in angiogenesis include hepatocyte growth factor/scatter
factor (HGF/SF), interleukin-6 (IL-6), interleukin-8 (IL-8) and tumor necrosis factor (TNF)-α.
Overexpresssion of HGF/SF and its receptor c-MET have been reported in both the tumor and
endothelial cells of GBM and higher levels of HGF/SF have been associated with increased
5
angiogenic activity, independent of VEGF.[42] IL-6 induces VEGF transcription and regulates
the VEGF promoter thereby contributes to glioma angiogenesis.[43] In contrast, IL-8 stimulates
angiogenesis through interaction with the C-X-C chemokine receptor 1(CXCR1), CXCR2 and
Duffy antigen receptor for cytokines and thereby can affect angiogenesis independent of
VEGF.[44] Tumor necrosis factor-α is an inflammatory cytokine that induces tumor
angiogenesis indirectly by upregulating other angiogenic factors including VEGF.[45, 46] This
cytokine is found in malignant gliomas, endothelial cells and infiltrating macrophages and its
receptor is expressed by glioma and endothelial cells.[47]
1.2 Anti-angiogenic Agents and Brain Tumors
A number of anti-angiogenic agents have been investigated as therapeutic agents for brain
tumors, including monoclonal antibodies to VEGF, receptor tyrosine kinase inhibitors directed at
the VEGFR and PDGFR, intracellular kinase inhibitors, immunomodulatory agents, endogenous
angiogenesis inhibitors and other new agents that inhibit targets involved in the angiogenic
pathway. [26, 48] Table 1.1 lists a number of the agents that have been or are currently being
investigated as treatment of brain tumors. Many of these agents are being evaluated as
monotherapy, as well as combined therapy with chemotherapy and/or radiation. Based on the
mechanism of anti-angiogenic agents, it has been widely recognized that the specific aim of
therapy should guide the dose, duration and schedule of anti-angiogenic agent administration.
For instance, if the goal is to completely deprive the tumor of its blood supply, the anti-
angiogenic agent should be continued until no functioning vasculature remains.[8] In primary
brain tumors, monotherapy treatment with an anti-angiogenic agent has yielded only modest
responses to-date and has failed to demonstrate long-term survival benefits.[26, 49, 50] But
recent reports of dramatic responses of renal cell carcinoma metastases, including brain
metastases, from sunitinib monotherapy have been encouraging.[51]
In contrast to anti-angiogenic monotherapy, combination therapy with anti-angiogenic agents
and cytotoxic systemic therapy has demonstrated more promising results. For example, the
combination of bevacizumab, a monoclonal antibody to VEGF, and several chemotherapeutic
agents have resulted in radiological response rates of 50-66% in patients with recurrent
glioblastoma.[52-54] When anti-angiogenic agents are administered in combination with
cytotoxic systemic therapy, one proposed mechanism is that the anti-angiogenic agent can
6
improve vascular efficiency, and thereby improve the accessibility of chemotherapy to the tumor
cells.[8] However, a great challenge is in determining the optimal dose and schedule required to
achieve the delicate balance between the endothelial cells and perciytes to improve the vascular
efficiency.[55] It has been demonstrated that delivering anti-angiogenic agents in a suboptimal
schedule with chemotherapy can result in worse outcomes due to antagonism between the
chemotherapeutic and anti-angiogenic agents.[56, 57] Biomarkers that can provide non-
invasive, repeatable measures of biological response can play a key role in the determining the
optimal dose, schedule and duration of anti-angiogenic agents.
Table 1.1 Anti-angiogenic agents in brain tumors
Category Agent Target Monoclonal Antibody Bevacizumab
Aflibercept VEGF VEGF
Receptor Tyrosine Kinase Inhibitor
Sorafenib Sunitinib Cediranib Pazopanib Vatalanib Vandetanib XL 184 Imatinib Dasatinib Tandutinib
VEGFR, PDGFR, c-kit, raf VEGFR, PDGFR, c-kit, FLT-3 VEGFR, PDGFR, c-kit VEGFR, PDGFR, c-kit VEGFR, PDGFR, c-kit, c-Fms VEGFR, EGFR VEGFR, c-met PGDFRa, c-kit, BCR-ABL PDGFR, Src, BCR-ABL PDGFR, c-kit, FLT-3
Intracellular kinase inhibitor
Temsirolimus Everolimus Bortezomib Enzastaurin
mTOR mTOR NF-κB PKCβ
Immunomodulatory Thalidomide Lenalidomide
Endogenous angiogenesis inhibitor
Celecoxib Rofecoxib
COX-2 COX-2
Other Cilengitide Prinomastat
αvβ3 and αvβ3
MMP-2, MMP-9, MMP-13, MMP-14
7
1.2.1 Sunitinib
Sunitinib is a tyrosine kinase receptor inhibitor that acts at VEGF receptors 1 and 2, PDGF
receptor, stem cell factor receptor (c-KIT), FLT3 and RET kinases. [58] As most malignant
tumors produce multiple angiogenic factors, an agent that inhibits multiple receptors like
sunitinib may be more effective at blocking tumor angiogenesis than an agent that blocks just
one receptor.[59] It has shown clinical efficacy as a monotherapeutic agent in renal carcinoma.
[60, 61] Pre-clinically, sunitinib maintenance after radiation treatment to subcutaneous tumors in
mice has demonstrated improved therapeutic effects beyond the additive effects of either
monotherapy.[62]
Sunitinib targets several receptor tyrosine kinases that are involved in GBM angiogenesis and
growth including PDGFR, stem cell growth factor receptor (KIT), FLT-3 and colony stimulating
factor-1 (CSF1-R).[63] In pre-clinical studies, sunitinib was associated with a reduction in
microvessel density (MVD) and increased tumor necrosis.[64] Sunitinib monotherapy or
following radiation treatment has been associated with improved survival in murine tumor
models.[62, 64] Clinically, sunitinib monotherapy in patients with recurrent glioblastoma
following chemotherapy and radiation failed to show effective response. However this study
administered sunitinib 37.5 mg daily, which is lower than the clinically administered dose of 50
mg daily in patients with metastatic renal cancer, for which impressive responses have been
observed.[65]
Pre-clinical pharmacokinetic studies have demonstrated that after oral administration of sunitinib
in solution or suspension form, the drug was readily absorbed systemically such that the time to
peak concentration was between 1 – 3 hours following a dose of 40 mg/kg. The plasma half-life
ranged between 2 – 4.6 hours following a single administration of 20 – 40 mg/kg orally.
However, sunitinib rapidly penetrated the blood-brain barrier such that brain concentrations were
greater than 5 fold higher than plasma concentrations up to 1 hour after administration in mice.
[66]
1.3 Radiation and Brain Tumors
The main biological effect of ionizing radiation is through the induction of free radicals that
cause DNA double strand breaks.[67] This can result in clonogenic cell death of tumor and
8
endothelial cells.[68] Radiation can also induce endothelial-cell apoptosis and programmed cell
death through ceramide pathways.[69] In the brain, endothelial cell death from radiation can
result in breakdown of the blood-brain barrier and increased vasogenic edema, ischemia and
hypoxia, which can drive upregulation of VEGF.[70] Furthermore, radiation can directly
upregulate VEGF secretion by glioma cells. As increased VEGF stimulates angiogenesis and
results in decreased apoptosis of both tumor and endothelial cells, upregulation of VEGF may
contribute to radioresistance by GBM.[67, 71] Based on this rationale, there is a growing
interest in combining anti-VEGF therapy with radiation for the treatment of GBM in order to
reduce radioresistance.
1.4 Anti-angiogenic Agents with Radiation
There is mounting preclinical and early clinical data suggesting that combining anti-VEGF
therapy with radiation may improve tumor response. [50, 62, 72-75] Several possible
mechanisms for this synergistic interaction are described below.
1.4.1 Balance of Pro-angiogenic Factors
Irradiation has been associated with rises in the expression of proangiogenic factors such as
VEGF and basic fibroblast growth factor.[76-78] This rise in VEGF and proangiogenic factors
can be via the mitogen-activated protein (MAP) kinase or HIF-1 induced pathway.[17, 77] which
may be responsible for the greater rate of metastatic disease that has been observed following
local irradiation of the primary tumor.[76, 79, 80] Therefore the addition of anti-angiogenic
therapy with radiation may counteract the rise in pro-angiogenic factors following radiation that
may be responsible for increased metastases. In a study of a subcutaneous murine model of
primary Lewis lung carcinoma, irradiation of the primary tumor in the right hind leg resulted in a
rise in the development of lung metastases; however, administration of angiostatin, an anti-
angiogenic agent, following radiation to the primary tumor prevented this metastatic growth. [81]
1.4.2 Vascular Normalization
Another potential mechanism that has been proposed by Jain et al. is that anti-angiogenic agents
can, at least transiently, normalize tumor vasculature to improve oxygen delivery and thereby
increase the cytotoxic effects of radiation in hypoxic tumor environments. [8, 75, 82]. This has
raised controversy as the mechanism of an anti-angiogenic agent would presumably reduce
9
vascular supply to the tumor and decrease tumor oxygenation. When changes in intratumoral
PO2 were monitored, a measurable transient decrease in PO2 preceded a subsequent increase in
tumor oxygenation.[83] Therefore treatment with anti-angiogenic agent prior to radiation may
improve tumor oxygenation and thereby improve radiation response.[84] Several studies have
attempted to evaluate changes in tumor vascular physiology in response to anti-angiogenic
agents in order to better characterize this vascular normalization process.[75, 85]
1.4.3 Endothelial Cell Death
Radiation can induce endothelial-cell apoptosis and programmed cell death through the
generation of ceramide, which activates the mitogen-activated protein kinase 8, mitochondrial
and death-receptor pathways. A recent study has demonstrated that ionizing radiation induces
early endothelial cell apoptosis in the brain, as early as 4 hours after irradiation.[86] Previous
studies have demonstrated that radiation-induced endothelial cell apoptosis is dose-dependent
and that one of the key anti-tumor effects of large-fraction (>8 Gy) radiotherapy is mediated by
the activation of these ceramide driven pathways. [76, 87, 88 ]. As anti-angiogenic agents can
also cause endothelial cell death, when large single fractions of radiation are delivered with anti-
angiogenic agents, these treatments may work through non-cross resistant mechanisms to
increase endothelial cell death.
1.4.4 Importance of Treatment Timing and Duration
Despite some of the compelling pre-clinical findings and proposed mechanisms of beneficial
interaction of anti-angiogenic agents and radiation, attempts to combine these two treatments in
the clinical and pre-clinical setting have been met with mixed responses overall. The reason for
this variable response may be that the benefit of combinatorial therapy is contingent on the
optimal timing and duration of anti-angiogenic therapy with radiation. The response to particular
timing and duration of treatment may also depend on the particular tumor type, oxygenation
status, and microenvironment, all of which can influence the optimal mechanistic aim for anti-
angiogenic therapy.[89, 90]
Several studies in murine subcutaneous xenograft tumors of squamous cell cancer have found
that anti-angiogenic therapy immediately after fractionated radiotherapy resulted in the best
outcome.[89, 90] In these cases, the proposed mechanism may involve continued endothelial
10
cell death after radiation delivery, as the anti-angiogenic agent targets tumor endothelial cells. A
murine intracranial glioma model demonstrated that maintenance sunitinib following concurrent
sunitinib and radiation therapy resulted in prolonged tumor growth delay beyond the combined
concurrent treatment only. In this same study, TUNEL staining was present only in endothelial
cells in tumors treated with combined radiation and sunitinib and absent in tumors treated with
either sunitinib or radiation monotherapy, suggesting that the primary mechanism of improved
response to combination therapy involved endothelial cell apoptosis.[62]
Jain et al. have suggested that the optimal timing may reflect the timing of “vascular
normalization” with anti-angiogenic therapy. [8] Winkler et al. has systematically evaluated
several treatment schedules for combining DC101, a VEGFR2-specific monoclonal antibody,
with radiation to treat murine orthotopic glioblastoma tumors and found that very different
responses in tumor growth delay resulted from the different schedules of DC101 and radiation.
This study also demonstrated that VEGFR2 inhibition temporarily normalized tumor blood
vessels but this period of vascular normalization was brief. [72, 75]
The precise mechanism of interaction of anti-angiogenic agents and radiation are yet unclear and
may be multifactorial. From the published studies, there is growing evidence that endothelial
cell death is one of these mechanisms and this may be quantified pathologically. However,
establishing early, non-invasive, reproducible, and quantitative biomarkers that reflect tumor
vascular changes and tumor response will facilitate serial measurements and characterization of
the dynamics of these responses. This may help determine the optimal dose, schedule and
duration of each treatment in combinatorial therapy and may facilitate early intra-treatment
adaptations to therapy. Finally, early biomarkers of response would enable individualized
adaptive approaches to therapy
1.5 Imaging Brain Tumors
Magnetic resonance imaging (MRI) is the imaging modality of choice for evaluating brain
tumors for diagnosis and evaluation of therapy response. The standard protocols for imaging
brain tumors usually include a fluid-attenuated inversion recovery (FLAIR) and a T1-weighted
image following administration of gadolinium.[91] It provides excellent soft tissue contrast, has
multiplanar capability and is a non-invasive imaging modality that does not expose the patient to
11
radiation.[92] In addition to the detailed anatomical information, MRI has the capability of
interrogating different aspects of tumor physiology by evaluating various parametric measures of
vascular permeability and perfusion, water diffusion, and spectroscopy.
1.5.1 Current Standard for Imaging Response Measures
Response assessment of brain tumors largely has been based on changes in the size of the
enhancing component of the tumor. In 1990, MacDonald et al. introduced criteria for response
assessment in gliomas that were based primarily on changes in the 2-dimensional measures of
the contrast-enhancing component of the tumor on CT or MRI, while incorporating steroid use
and changes in neurological status. [93] However, several limitations of the MacDonald criteria
have been identified. For example, meaningful 2-dimensional measurements are difficult as
tumors grow in 3 dimensions, are often irregularly shaped and contain cystic components. This
can be further complicated when there are multifocal tumors, for which the MacDonald criteria
lack guidance regarding an appropriate tumor measurement. Finally, as 2-dimensional tumor
measurements are defined manually, these measures are prone to interobserver variability. With
advances in MR analysis technology, automated delineation and measurement of tumor volume
are now possible. Thus far volumetric measurements have shown good concordance with the 2-
dimensional measurements and automated delineation would minimize interobserver variability.
[94-97] Regardless of how the tumor is measured, the MacDonald criteria only measure the
enhancing abnormality and uses changes in the enhancing component as a measure of treatment
response; however gadolinium-enhancement occurs where there is breakdown of blood-brain
barrier and increased vascular permeability, regardless of the etiology of increased permeability.
With the recent introduction of concurrent chemotherapy and radiation for high grade gliomas,
20-30% of patients have had increased contrast enhancement on their first post-radiation MRI.
This phenomenon has been called pseudoprogression and is thought to reflect a transient change
in vascular permeability following combined treatment. Many of these patients would meet the
MacDonald criteria for progressive disease, which could result in premature discontinuation of
effective therapies or premature intervention with additional therapy. In contrast, several new
anti-angiogenic agents have produced very dramatic reductions in the enhancing component of
tumors as early as 1-2 days after therapy initiation. This more likely reflects vascular
normalization and resulting reduction in vascular permeability as opposed to true tumor
regression. This phenomenon has been called pseudoresponse as there has been disparity
12
between the imaging response based on measures of change in the enhancing abnormality and
clinical outcome.[98]
The Response Assessment in Neuro-Oncology Working Group is an international
multidisciplinary group that has developed new standardized response criteria that attempts to
address the identified issues and limitations of the MacDonald criteria. Although this group
recognized the value of volume measurements, the new criteria use 2-dimensional tumor
measurements as there is a lack of a standardized approach for volume measurement at this time.
The new criteria include enlargement of non-enhancing tumor as evidence of tumor progression.
It has also defined time-frames for radiologic changes in order to address pseudoprogression and
pseudoresponse. For example, increased enhancement within the first 12 weeks of radiotherapy
is only defined to be disease progression if the majority of the enhancement is outside of the
radiation field or beyond the high-dose region. Decreased enhancement should persist for at
least 4 weeks before a true response is considered. Furthermore, the working group recognized
that advanced MRI techniques that evaluate tumor physiology are promising tools for predicting
eventual tumor response or differentiating tumor and other treatment-related MR changes that
should eventually be incorporated into future response criteria. However, at the present time
these advanced MRI measures were not incorporated into the response criteria because there are
still a number of uncertainties in the acquisition and analysis of these functional MRI studies that
make standardization of these measures difficult.
1.5.2 Functional MRI Response Measures
Several quantitative functional MRI measures of treatment response to both radiation and anti-
angiogenic agents have been reported. These include dynamic contrast-enhanced (DCE-MRI),
dynamic susceptibility (DSC-MRI), diffusion-weighted MR (DWI), and quantitative T1 or T2.
These functional MRI changes likely occur earlier in response to treatment than volume changes
and in some cases these changes may occur in the setting of stable tumor volume with anti-
angiogenic therapy or even increased tumor volume following radiation therapy. Therefore these
functional MRI measures are likely better early markers of treatment response that can be used to
guide individualized and early adaptive therapy as opposed to the conventional volume-based
imaging response criteria.
13
1.5.2.1 Dynamic contrast-enhanced (DCE) MRI
Dynamic contrast-enhanced MRI has been proposed as a method of imaging the physiology of
tumor microcirculation, including the perfusion and permeability of the microvasculature.
Typically it involves the administration of a low molecular weight contrast agent and tracking
the uptake and distribution of contrast into the feeding vessels and tissues over time with high
temporal and spatial resolution.[99] Changes in DCE-MRI findings are relevant to tumor
response to radiotherapy as microvascular damage and endothelial cell death is thought to play a
role in overall radiation response.[76, 90, 100] Changes in serial DCE-MRI can also evaluate the
vascular response of tumors to anti-angiogenic therapy.
Currently, DCE-MRI measures are the most promising biomarkers with the most consistent
findings in clinical trials of anti-angiogenic agents. Tumor response to therapy can be measured
by extracting measures of enhancement or applying pharmacokinetic models to extract modeled
values. Recently, Leach et al. have established recommendations for the appropriate MRI
methodology to use in Phase I/II clinical trials assessing antiangiogenic and antivascular
therapies. These recommendations state that at least one of two possible primary endpoints
should be used: initial area under the contrast agent time curve (iAUC) and/or Ktrans.[101]
However, it was recognized that there are a number of limitations and challenges in acquiring,
analyzing and interpreting these DCE-MRI measures.
The initial area under the contrast agent time curve (iAUC) measures both the gadolinium inflow
and the bulk perfusion of a tumor and it reflects multiple factors: blood flow, vascular
permeability, and the fraction of interstitial space. [102, 103] This measure is relatively simple
to acquire and does not require a pharmacokinetic model. It is commonly reported as a measure
of the area under the curve for the first 60 seconds of contrast uptake, called iAUC60. But the
range over which iAUC is taken is not important as long as it is large enough to ensure good
signal-to-noise and it is acquired consistently between studies so that changes in iAUC can
properly be measured.[102] There have been some promising studies in which both iAUC60
and the other recommended vascular measure, Ktrans, have decreased following anti-anti-
angiogenic therapy.[104] However, iAUC response measures have been quite variable
following anti-angiogenic therapy in pre-clinical and clinical studies. [101, 105-108] This likely
reflects the vascular factors of the tumor including blood flow, vascular permeability, and the
14
fraction of interstitial space and extra-tumoral factors that can impact the overall gadolinium
delivery such as the speed of the contrast injection, heart rate and systemic blood flow. Although
the arterial input function (AIF) is not required to derive the iAUC value, the AIF could be used
to help normalize the iAUC for the extra-tumoral factors that do not reflect tumor vascular
physiology.[109] Applying this concept, previous studies have shown that normalizing iAUC
measures to a reference muscle tissue have resulted in iAUC changes parallel to Ktrans changes
over a wide range of tissue input functions.[106]
Researchers have explored a number of different perfusion models in order to measure various
kinetic parameters that reflect tissue perfusion. In 1999, Tofts et al. introduced several standard
kinetic parameters to facilitate consistent measurements and meaningful comparison of perfusion
parameter findings across investigators: Ktrans, Kep and ve. These parameters were generated
using a model that considers the blood plasma (or intravascular space) and the extracellular
extravascular space (EES or interstitial space) as two compartments.
Ktrans is the rate constant of the movement of the contrast agent from the intravascular space to
the extravascular space. The most general definition of Ktrans is
Ktrans = (1 – e –PS/F(1-Hct)) F ρ (1-Hct) [102]
Where PS is the permeability surface area product per unit mass of tissue (ml min-1g-1), F is the
flow of blood per unit mass of tissue (ml min-1g-1), Hct is the hematocrit fraction and ρ is the
tissue density (g ml-1).
In the 2-compartment (Tofts or Modified Tofts) model, the transfer constant Ktrans has several
interpretations, depending on the relative capillary permeability and blood flow in the tissue of
interest. If vascular permeability is high, Ktrans reflects the blood plasma flow per unit volume of
tissue. If vascular permeability is low, Ktrans reflects the permeability surface area per unit
volume of tissue. Therefore, reductions in Ktrans with anti-angiogenic treatment could represent
either a change in tumor blood flow or a change in vascular permeability, both of which would
be useful to know. [110]
In both pre-clinical and clinical studies, Ktrans has been shown to decline following anti-
angiogenic therapy, reflecting an expected decrease in vascular permeability with these
15
agents.[85, 105, 111, 112] Ve is the volume of extravascular extracellular space per unit volume
of tissue. [110] Kep is the ratio of Ktrans to Ve and it reflects the efflux of the contrast agent from
the tumor back into the vasculature. Even when other measures of vascular response to anti-
angiogenic agents were observed, changes in Kep have been variable. [113]
Kep = Ktrans/ve
Although DCE-MRI has been explored much more extensively as a measure of response to anti-
angiogenic therapy, changes in DCE-MRI measures in response to radiation have also been
investigated. In patients with rectal cancer, DCE-MR images were acquired prior to surgical
resection for comparison of the imaging measures and pathological findings of tumor vascular
changes with pre-operative radiation. Patients treated with radiotherapy had a 77% decrease in
tumor KPS (p=0.03), the endothelial transfer coefficient reflecting microvessel blood flow,
compared with patients not treated with pre-operative radiation. Microvessel density was 37%
lower (-p=0.03) in patients who received a long course of pre-operative radiation with 25
fraction of 1.8Gy per fraction but not in the 3 patients who received short course radiotherapy
with 5 fractions of 5 Gy. [114] In the brain, changes in both vascular volume and permeability
measures on DCE-MRI have been correlated with the cumulative radiation doses and also
correlated with changes in verbal learning scores at 6 months after RT. [115] In addition,
several studies have reported short-term increases and medium to long-term decreases in Ktrans in
response to radiation therapy in normal brain, gliomas, and meningiomas.[116, 117] More
recently, both the fractional high-CBV tumor volume prior to RT and decreases in fractional
low-CBV tumor volume after 1 week of RT were predictive of better survival in patients with
high grade glioma. [118]
Early changes in DCE-MRI measures following concurrently combined anti-angiogenic agents
with radiation in brain tumor have not yet been investigated. As part of this process, preliminary
16
studies will investigate the various DCE-MRI parameters to develop an acquisition protocol that
is optimized for murine intracranial tumors. The extensive studies utilizing DCE-MRI to
evaluate tumors have not only identified a number of promising metrics to measure response but
have also revealed the multiple challenges of establishing a robust, reproducible acquisition
protocol, data analysis approach and endpoint measures. Because DCE-MRI exploits the
changes in T1 as the contrast agent, in our case Gd-DTPA, enters the tissue of interest, the
baseline T1 value prior to contrast injection and the consistency of contrast injection are both key
factors that can impact the results. The T1 value in tumor can change with treatment and has
been investigated as a potential measure of treatment response.[105, 119] As a result, T1 values
can vary at baseline prior to treatment and can change variably in response to treatment, all of
which can affect the DCE-MRI measures. A recent study demonstrated that applying population
mean AIF or individual AIF values into the Modified Tofts analysis can result in a 35.8%
difference in the mean Ktrans for the region of interest. [120] The AIF measurement has been
taken from various locations including a nearby large artery, the aorta, or a reference tissue.[121-
123] In this study, we aim to establish an intracranial vessel that could be consistently used as
the AIF for DCE-MRI analysis. In addition to the AIF and T1 measurement, additional
challenges of establishing a DCE-MRI protocol for murine intracranial tumor include achieving
adequate temporal resolution to capture the early uptake of the contrast into the AIF and tumor
while maintaining an adequate signal-to-noise ratio (SNR) and spatial resolution for evaluating
very small early tumors in this longitudinal study.
1.5.2.2 Dynamic susceptibility-weighted contrast-enhanced (DSC) MRI
An additional promising technique for investigating tumor vascular physiology that utilizes
dynamic contrast evaluation is T2*-weighted dynamic susceptibility-weighted contrast-enhanced
MRI, which enables the measurement of cerebral blood volume (CBV), peak height (PH) and
percentage of signal intensity recovery (PSR).[124, 125] Susceptibility refers to the loss of MR
signal caused by the magnetic field-distorting effects of paramagnetic substances, such as
gadolinium, which is greatest on T2*- and T2-weighted sequences. This technique requires a
high temporal resolution to capture the wash in and wash out of the contrast material, employing
rapid echo-planar imaging in conjunction with injection of contrast. As the contrast passes
17
through the vasculature and tissue, the signal decrease is monitored over time and integration of
the signal over time for each voxel can produce CBV maps.[126, 127]
The relative CBV (rCBV) has been associated with MVD and has been associated with
angiogenesis and glioma grade.[128-130] Several recent studies have correlated rCBV measures
with response to anti-angiogenic therapies, thalidomide and bevacizumab, in patients with
glioma. [131-133] Early reductions in rCBV have also been observed in gliomas following high-
dose radiotherapy and changes occurring as early as at the end of 1 week of radiotherapy have
been shown to be predictive for survival in low grade glioma. [117, 134] Recently, a potential
useful clinical application of rCBV as an early response biomarker has been demonstrated by
Tsien et al., who found that a significant reduction in rCBV during week 3 of chemoradiotherapy
for high-grade glioma was noted in patients with progressive disease compared with those with
pseudoprogression.[135]
The strengths of DSC include high temporal resolution and accurate measurement of CBV,
which has shown promise as a biomarker in brain tumors. However, limitations of this technique
include the limited spatial resolution, the need for a rapid injection of contrast and the
measurement of only relative values.[136] These limitations pose even greater challenge in
murine intracranial tumors as these are very small tumors and the mice have limited tolerances of
the volume and speed of contrast injection. Furthermore, rapid leakage of the contrast agent into
the extravascular space can result in falsely low rCBV estimates because the theoretical model
for DSC is based on the assumption that contrast agent remains within the intravascular
space.[137] There is ongoing work with newer larger paramagnetic contrast agents and
mathematical correction methods to account for this shift in rCBV.
1.5.2.3 Diffusion-weighted Imaging (DWI)
Diffusion-weighted imaging measures the Brownian motion of water molecules within tissue,
which is influenced by the underlying tumor morphology. [138] The apparent diffusion
coefficient (ADC) is a measure of water diffusion in tissue, which is sensitive to changes in
cellular size, extracellular volume and membrane permeability, as well as changes in the stromal
characteristics such as collagen content and presence of apoptosis. [138-140] Ellingson et al.
recently demonstrated that the ADC measurements within the precise region of stereotactic
18
biopsies of human gliomas were strongly inversely correlated with the cell density measurement
of the biopsy specimen with an R2=0.7933 (p<0.0001). Applying this new data, the concept of
creating “cellularity maps” that may allow for non-invasive estimation of cellular proliferation
and motility in human gliomas was introduced.[141]
Given that changes in ADC reflect changes in cellular density, it would be expected that ADC
changes will be observed in response to anticancer therapies. In animal models, changes in both
T2 and ADC have been reported to correlate with positive tumor response to various anticancer
therapies, [138, 139, 142-144] and in the case of certain chemotherapies, dose-dependent
changes in ADC have been observed. [143, 145, 146] Following cytotoxic treatment, increased
water diffusion has been consistently observed in tumors, likely reflecting processes involved in
cellular apoptosis and death. Chenevert et al. has reported that although changes in tumor T1, T2
and ADC could be used to measure changes in extracellular water content following cytotoxic
treatment, ADC rises were the most sensitive measure of cytotoxic therapy response. [143]
Recent clinical studies have suggested that ADC changes may be useful in distinguishing
treatment response from non-response when conventional imaging measures of response are not
helpful. For example radionecrosis and tumor necrosis is associated with a much higher ADC
than tumor recurrence although the appearance of both entities appears similar on conventional
MR imaging. [138, 139, 147-149] For high-grade gliomas, apparent diffusion coefficient (ADC)
histogram analysis on diffusion-weighted imaging has been shown to predict responses to both
bevacizumab therapy and radiation monotherapy. [52] Hamstra et al. demonstrated that ADC
response, when measured as the volume of tumor with increased ADC at week 3 of radiation
treatment was similar to the prognostic value of conventional radiologic response measured at 10
weeks after starting radiotherapy.[139] Similar rises in ADC in response to radiotherapy have
been observed in other tumor sites including the head and neck and liver cancers. [150-152]
Therefore, early ADC rises may be predictive of response to cytotoxic therapies such as radiation
treatment.
As ADC is a measure of water diffusion, it would be plausible that there would be a correlation
between ADC and DCE-MRI measures of volume of extravascular, extracellular fluid (Ve) and
Ktrans, which reflects vascular permeability. However, recent studies have demonstrated an
unclear relationship between ADC and these DCE-MRI measures. One study failed to show any
19
correlation between ADC and Ve in gliomas.[153] Another study evaluating changes in ADC
and DCE-MRI measures, Ve and Ktrans, in response to neoadjuvant chemotherapy in patients with
breast cancer reported an inverse relationship between ADC and Ve, contrary to the expected
positive correlation between these measures. [154] These finding suggest that these measures
may reflect different aspects of the tumor microenvironment.
1.6 Biomarkers
A biomarker is a distinct biological indicator of a process, event or condition. [Webster’s
Dictionary] There are different types of biomarkers including prognostic biomarkers, predictive
biomarkers and pharmacodynamic biomarkers. Prognostic biomarkers provide information
about the outcome of the patient, regardless of therapy. Predictive biomarkers provide an
estimate of response or outcome specific to a treatment. Pharmacodynamic biomarkers are
associated with modulation of a specific biological target by the specific treatment.[155]
Surrogate biomarkers need to fulfill two criteria: correlation with clinical outcome and reflect the
specific effect of the treatment.[156] Biomarkers can take the form of imaging modalities, direct
measurement of specific biologic characteristics such as oxygen concentration, biofluid measures
of proteins or pathological or genetic measures within the tumor tissue.
Although single point measures of some biomarkers have demonstrated predictive or prognostic
value, many biomarkers demonstrate both spatial and temporal heterogeneity. By measuring
biomarkers over time, the changes in biomarkers with response to treatment or tumor progression
can provide valuable information to help guide therapy. For example, measures of biomarker
change during treatment may provide guidance of the scheduling and timing for combinatorial
therapy and enable treatment adaptation based on individual responses. For repeated evaluation
of changes in biomarkers over time, minimally-invasive or non-invasive measures are preferred.
Therefore imaging biomarkers and biofluid biomarkers have been selected for investigation in
this study that aims to identify biomarkers of treatment response that can be evaluated serially in
patients with brain tumors.
1.6.1 Imaging Biomarkers
There are several quantitative, reproducible imaging methods that are promising predictive
biomarkers for radiation and anti-angiogenic agents. As described above, early changes in
20
several functional MRI measures have been associated with response to therapies and have
shown correlation with measures of the underlying mechanism of that therapy. For example,
rises in ADC have been associated with lower cellular density in gliomas and early rises in ADC
in response to radiotherapy have been correlated with better tumor control and outcome.[142,
143, 148, 157] Using DCE-MRI, early decreases in Ktrans have been associated with decreases in
microvessel density and have been associated with response to anti-angiogenic therapies.[85,
105-107, 111]
1.6.2 Biofluid Biomarkers
There is growing interest in measuring serum and urine biofluid biomarkers, both for early
detection of cancer and for monitoring treatment response. Early exploratory clinical studies
have suggested that urinary measures of angiogenic markers, VEGF and matrix
metalloproteinases may be useful biomarkers that predict clinical outcome in cancer patients
treated with radiotherapy. [158] Several angiogenic growth factors such as VEGF-A, PDGF,
basic fibroblast growth factor (bFGF), placenta growth factor (PlGF), hepatocyte growth factor
(HGF) and interleukin 8 (IL-8) have been detected in serum and may predict survival or response
to anti-angiogenic therapy. [74, 159, 160]
Attempts to measure serum VEGF levels in patients with glioblastoma have shown mixed
results. Several studies have reported that serum VEGF levels were significantly higher in
patients with malignant gliomas compared with healthy controls.[161] Takano et al on the other
hand found no difference between serum VEGF in patients with brain tumors and healthy
controls.[162] However, this may reflect the very small number of patients with glioblastoma
for which serum VEGF was evaluated in these studies. The largest of these studies by Reynes et
al, found a twofold higher serum VEGF level in patients with proven glioblastoma than healthy
controls.[163] Furthermore, in a phase I dose escalation study of the multi-targeted (VEGFR-2,
VEGFR-3, PDGFR-β, c-kit) tyrosine kinase inhibitor telatinib, serial plasma measures
demonstrated dose-dependent rises in VEGF and decreases in VEGF receptor-2 levels were
observed.[104] These findings suggest great promise in using biofluid biomarkers to evaluate
therapy response and potentially guide individualized treatment based on serial measures.
21
1.7 Tumor Models for Brain Tumors
Various in vivo tumor models of GBM have been investigated, including subcutaneous and
intracranial xenograft models as well as spontaneous tumor models. There are a number of
reasons why intracranial tumor models better reflect clinical tumor behavior than subcutaneous
tumor models. Gene expression profiles of different glioma cell lines and the histopathological
characteristics of the tumors these cell lines produce resemble each other and clinical glioma
tumors more when grown orthotopically than when grown subcutaneously or in vitro. [164, 165]
In addition, the delivery of systemic agents across the blood brain barrier and delivery of
radiotherapy to specific organ sites may be better reflected in orthotopic models and the location
of tumor implantation and growth may impact response to these treatments. [166] For example,
Lund et al. treated mice with GBM xenografts implanted subcutaneously in the thigh and
intracranially with radiation, TNP-470 or the combination. For the thigh tumors, a significant
enhancement of the anti-tumor effect was seen in the combination group. However, this was not
observed for the intracranial tumors.[167] This emphasizes the importance of selecting a tumor
model that best resembles the clinical tumor in order for efficient translation of the preclinical
findings, as the tumor microenvironment may greatly impact response to treatment.
1.8 Conclusion
With the introduction of targeted therapy such as anti-angiogenic agents and growing use of
combination therapy regimens for the treatment of brain tumors, there is a growing need for
biomarker measures to enable timely prediction of eventual clinical treatment response in order
to guide appropriate treatment selection, scheduling and adaptation. MRI has become the
preferred imaging modality for brain tumors as it provides superior anatomical detail and has
capability of multiparametric imaging to interrogate different aspects of tumor characteristics.
Functional MRI biomarkers may provide a non-invasive means for early determination of
outcome through measures that reflect physiological and microenvironmental responses to
therapy that warrant further investigation.
Based on all the rationale described above, we are investigating the effects of combining large
single fraction radiation with sunitinib, an anti-angiogenic agent, clinically in patients receiving
radiosurgery with sunitinib and pre-clinically in a murine orthotopic brain tumor model. Pre-
clinically judicious monitoring of potential early biomarkers was completed to allow for
22
translation of the promising biomarkers for further investigation in the clinical study. [Appendix
I]
23
Chapter 2 Aims/Hypotheses
2 Thesis Hypothesis:
There is mounting evidence and rationale that anti-angiogenic agents may enhance the effects of
radiation through a number of mechanisms. However, it has been recognized that the optimal
dose, schedule and timing of these treatments are critical to improving the outcomes of combined
therapy. Several multiparametric MR measures have shown promise as response biomarkers for
anti-angiogenic and radiation therapy. As MRI can provide information reflecting tumor
morphology and physiology, early MRI response biomarkers may guide individualized spatio-
temporal delivery of multimodality treatment. Longitudinal studies with frequent serial
multiparametric MRI would facilitate the exploration of early imaging biomarkers to determine
the specific promising biomarker changes and the timing of these changes. Pre-clinical animal
models of cancer, such as intracranial xenograft brain tumor models, are invaluable tools for
acquiring this early data about the effects of new therapies and in identifying candidate response
biomarkers that warrant further translation to clinical studies. However, pre-clinical
experimentation with combined modality treatment and investigation of biomarkers involves
numerous factors including the choice of an appropriate tumor model and selection and timing of
imaging biomarker measures in relation to treatment delivery. All of these aspects are critical to
identifying promising biomarkers that will be successful in clinical translation.
Thesis hypothesis: Imaging biomarker dynamics can be determined in murine intracranial tumor
investigation of radiation and anti-angiogenic therapy.
2.1 Aim 1:
To design a preclinical intracranial mouse model that allows for longitudinal imaging evaluation
of the effects of radiation and antiangiogenic therapy
Subaim 1: To establish an orthotopic brain tumor model that has overall survival and
tumor growth rate amenable for longitudinal MRI evaluation
24
Subaim 2: To establish a tumor model that demonstrates measurable vascular
permeability on DCE-MRI so that changes in vascular permeability can be measured
following anti-angiogenic therapy
Subaim 3: To develop a multiparametric MRI protocol that enables longitudinal
evaluation of murine intracranial tumors
2.2 Aim 2:
To guide the spatial and temporal delivery of radiation and antiangiogenic therapy using serial
MRI
Subaim 1: To use MRI to guide the spatial delivery of radiation
Subaim2: To use MRI to guide the temporal delivery of treatment once gross tumor is
confirmed
2.3 Aim 3: To evaluate tumor and candidate biomarker response to sunitinib and radiation
Subaim 1: To compare tumor growth delay and survival with each treatment: placebo,
sunitinib alone, radiation alone and sunitinib + radiation
Subaim 2: To evaluate the changes in multiparametric MRI measures including DCE-
MRI (iAUC60, Ktrans and Kep) and DWI (ADC) with each treatment
Subaim 3: To measure changes in urine biomarkers consistent with molecular responses
to anti-angiogenic therapy to confirm systemic delivery of sunitinib and a biologic effect
on molecular pathways involved in tumor angiogenesis.
25
Chapter 3 Development of a Synchronized
Tumor Model and Imaging Protocol
3 OVERVIEW
3.1 INTRODUCTION
Animal tumor models are instrumental in evaluating the effects of new therapies and in
identifying promising early measures of treatment response. However, selecting the appropriate
tumor model and the experimental design can impact the translational value of the experimental
findings. When designing a study that aims to measure imaging endpoints, it would be prudent
to consider the imaging factors and tumor model factors that can impact the feasibility and value
of the findings of the experiment.
3.1.1 ANIMAL TUMOR MODELS
For the purpose of investigating treatments for glioblastoma, it is accepted that intracranial tumor
models better reflect clinical tumor behavior than subcutaneous tumor models for several
reasons. When different glioma cell lines are grown orthotopically, their gene expression
profiles and histopathological characteristics resemble each other and resemble clinical glioma
tumors more than when they are grown subcutaneously or in vitro. [164, 165] In addition, the
delivery of systemic agents across the blood brain barrier and delivery of radiotherapy to specific
organ sites may be better reflected in orthotopic models. [166] However, intracranial tumor
model experiments are challenging because these tumors are not readily accessible for direct
measurement of tumor size or physiological response. Imaging plays a key role in the evaluation
of these tumors both in the clinical and pre-clinical scenario.
In this preliminary study, the process of selecting the appropriate intracranial model addressed
the key features that would facilitate experimentation with conformal radiation and anti-
angiogenic treatment and evaluation with longitudinal biomarker measures including
multiparametric MRI. Mouse survival would be long enough for longitudinal biomarker
26
measures and tumor growth rate would again be slow enough for multiple biomarker measures
over time but quick enough that the experiment would be completed within several months.
In addition to addressing the requirements of the pre-clinical experiment, the tumor model and
imaging measures were selected with consideration of the potential to translate the findings to
the clinical setting. In order to identify imaging biomarkers that could be translated to a clinical
phase I study of concurrent sunitinib and radiosurgery, the pre-clinical experiment was designed
to deliver concurrent sunitinib with a single high dose radiation treatment that was delivered
conformally to the tumor. In order to determine the potential benefit of adding sunitinib to
radiation, a moderate dose of 8 Gy in a single fraction was used in order to ensure that tumor
cure would not be achieved with radiation alone. To evaluate the effects of sunitinib and
radiation, a model with measurable vascular permeability was selected.
MRI PROTOCOL
Longitudinal imaging with MRI of intracranial tumors has been used for confirming gross tumor
at baseline and following tumor size over the course of the experiment as a measure of treatment
response. [168] However there is growing interest in identifying early measures of response to
therapy that may precede tumor volume changes. For example, rises in tumor ADC as early as 24
hours to 7 days after cytotoxic therapy have been measured, prior to any significant tumor
volume change. [139, 142, 143, 149, 169, 170] Measures of vascular response to anti-angiogenic
therapy can occur prior to or independent of changes in tumor morphology and volume.[105,
111] Therefore, longitudinal measurement of tumor vascular response and ADC change along
with morphological response would provide a more detailed evaluation of the effects of anti-
angiogenic and radiation therapy.
These MRI measures are sensitive to data acquisition and analysis. For example, pre-clinical
studies have demonstrated wide variability in vascular measures, such as Ktrans and iAUC, which
can occur by applying different T1 values and arterial input function (AIF) data into
analyses.[102, 120, 171] There are also ongoing efforts to determine the optimal approach to
DCE analysis including the optimal kinetic model, AIF measurement and optimal endpoint
measures that reflect clinical and pathological outcome. We attempted to design an MRI
protocol that would facilitate collection of individual T1 and AIF values for application in the
Modified Tofts Model, a widely accepted approach for DCE analysis.
27
In this study, we concurrently developed the MR protocol while selecting the appropriate tumor
model and experimental design to evaluate the effects of radiation and sunitinib. Development
of the MR protocol involved consideration of a number of factors including the spatial resolution
and tissue contrast, the particular quantitative data we were aiming to acquire and the specific
analysis approaches to be used, the total imaging time per mouse, as well as repeatability of these
measures. The MR images aimed to serve multiple purposes for our experimental design:
confirmation of the presence and location of gross tumor, measurement of tumor size and
assessment of changes in multiparametric MRI measures (DCE, DWI) over time.
3.1.2 PURPOSE
The purpose of this preliminary study was to concurrently develop a synchronized murine
intracranial tumor model and multiparametric MRI protocol that allows frequent, longitudinal
imaging evaluation of tumor response to radiation and antiangiogenic therapy.
3.2 METHODS & MATERIALS
Cell Cultures. Two cell lines were grown in 1X DMEM and 10% fetal bovine serum under
standard conditions (37 C in 5% CO2 and 95% room air).
(1) Human glioma cell line, U87 (Dr. Abhijit Guha’s lab) was selected because intracranial
tumors with angiogenic properties have been well-established using this cell line in NOD-SCID
mice. It expresses VEGF moderately. As a model for primary tumor, the intracranial model with
U87 has been criticized because it does not have the invasive properties of a primary brain
tumor. However, brain metastases typically grow as well-circumscribed tumors, more similar to
the growth pattern of an intracranial U87 tumor.
(2) Human breast cancer cell line, MDA-MB231-BR (gift from Kevin Camphausen, NCI) was
selected because breast cancer is one of the most common sources of brain metastases. There
was promise to establish this cell line as an intracranial model in NOD-SCID mice as it has been
established as intracranial tumors in nude mice at NCI.
Mouse Intracranial model. Six week-old NOD SCID mice were anesthetized with
intraperitoneal injection of 0.4-0.8 mL Avertin and positioned in a stereotactic frame. The
following number cells of each tumor cell line suspended in 10 μL PBS were injected
28
stereotactically using a 10-µL Hamilton syringe into the right frontal lobe (1mm anterior and
2mm lateral to the bregma at 3mm depth from the dura): (1) 1 x 106 cells, (2) 2 x 105 cells, and
(3) 1 x 105 cells. The technique of intracranial injection was provided by an instructional session
at Kevin Camphausen’s laboratory at the National Cancer Institute and additional instructional
sessions with Gelareh Zadeh at Mars animal facility. Although there is literature that SCID and
NOD-SCID mice have a generalized radiation repair defect, which results in a greater
radiosensitivity compared with wild type mice, NOD-SCID mice are a common strain used for
murine xenograft experiments evaluating the effects of radiation, with and without systemic
agents that may enhance tumor radiosensitivity.[172, 173] All animal care and studies were
carried out in accordance with institutional animal care guidelines.
The following criteria were used to evaluate each mouse model: (1) presence of measurable
intracranial tumor on MRI, (2) a tumor growth rate and overall survival that is amenable to serial
MRI measures, and (3) evidence of angiogenesis on MRI and/or changes in vascular
permeability.
MRI. A 7-Tesla Bruker BioSpec 70/30 with the B-GA12 gradient coil, 7.2cm linear volume
transmitter, murine slider bed, and murine head coil was used for serial imaging. For each MR
imaging session, mice were anesthetized with isoflurane and placed on the MR bed with a bite
block and water warming system to maintain body temperature at 38°C.[105] Respiration rate
was monitored using a pneumatic pillow (P-respTM, SAII) throughout the imaging session with
isoflurane adjustment to maintain a consistent respiratory rate of 35 to 45 breathes per second.
Serial imaging sessions were aimed to include:
(1) T2-weighted-Fast spin echo (FSE) anatomical imaging to confirm the presence of gross
tumor at baseline and stratify mice to treatment arms based on tumor size and document any
edema that developed with tumor growth and treatment. The T2 image was also used to
determine the slice prescription for all the images sequences acquired per imaging session.
(2) Diffusion-weighted imaging (DWI) to measure changes in tumor ADC in response to
treatment. ADC has been shown to be associated with tissue cellularity and can increase with
tumor response to cytotoxic treatment as a result of decreased cell density, apoptosis and tumor
necrosis.
29
(3) T1 quantification for the purpose of measuring individual T1 values for application in
Modified Tofts model analysis of DCE-MRI data.
(4) Contrast-enhanced T1-weighted-FSE anatomical imaging with matched slice prescription and
image resolution to the T2-weighted image set, started at 5-minutes post contrast injection for
tumor volume measurement over time.
(5) Dynamic contrast-enhanced MRI protocol development addressed two aspects of this
acquisition:
(a) MRI protocol that would satisfy a balance between signal-to-noise ratio and spatial
resolution for the small tumors at baseline and adequate temporal resolution for acquisition of
signal intensity data for the AIF and tumor
(b) Establishment of a reproducible, representative AIF for an intracranial murine tumor. The
following aspects of the injection protocol were investigated:
(i) Set-up of the contrast syringe and tail vein catheter for a reproducible injection
(ii) Amount of gadolinium that can be delivered by tail vein injection to achieve the
appropriate signal to measure the true AIF peak without signal saturation
(iii) Speed of contrast injection: Clinically, a bolus injection is used for DCE acquisition
and would be ideal in the pre-clinical setting as well. However, a bolus injection of the
volume of contrast mixture used may not be tolerated by mice with larger tumors. The
injection rate must balance feasibility in mice while approximating bolus conditions as
much as possible.
(iv) Arterial input function (AIF): As we were attempting to measure individual AIF for
Modified Tofts analysis, the DCE protocol needed to include an enhancing blood vessel
that could repeatedly be identified for AIF measurement. Measurements of AIF in mice
have been challenging and there are limited studies using an intracranial AIF for
Modified Tofts analysis. As part of the DCE protocol, we aimed to identify a large
intracranial vessel that was located close to the tumor so that it could be captured
simultaneously in the imaging volume of the tumor, was relatively easily identified in all
30
mice and had a repeatable signal intensity curve that was representative of a vascular
input function.
As meaningful measurement of MRI biomarker dynamics requires sufficiently high precision for
confident detection of changes in the particular MRI biomarkers, we applied the approach that a
biomarker response is considered detectable with sufficient confidence when the magnitude of
change is greater than twice the precision of that biomarker measure.[174, 175] Precision is
impacted by multiple method-dependent factors (i.e. motion for ADC analysis; temporal
resolution for DCE analysis), but all techniques display variability dependent on signal-to-noise
ratio (SNR). Signal-to-noise ratio is the ratio between the mean signal within a region of interest
(ROI) in an area of high signal intensity and the standard deviation of the background noise, and
it is a criterion for image quality.[176] The SNR is proportional to overall scan time and
inversely proportional to spatial resolution.
Fig. 3.1 displays the contribution of SNR to ADC standard deviation based on Monte Carlo
simulation (500 repetitions at each SNR: b= 0, 1000 s/mm); isotropic diffusion coefficient = 0.8
x10-3mm2/s). According to these simulation estimates, the ADC precision owing to thermal
noise is 5, 2.5, and 1% at SNR of 35, 70, and 150. The SNR of an ROI is a function of per voxel
SNR according to the formula:
SNRROI = SNRvoxel · √(no. of voxels)
Therefore by achieving a per voxel SNR of at least 70, suggesting ADC precision of 2.5% from
thermal noise, the ADC precision of an ROI will be at least 70.
31
Figure 3.1 Relationship between standard deviation in ADC (%) and signal-to-noise (SNR).
Monte Carlo simulations for 500 repetitions at each SNR applying the following assumptions were
used to generate this relationship: b = 0, 1000; isotropic diffusion coefficient = 0.8 x 10-3mm2/s.
32
3.3 RESULTS
The development of the tumor model and MRI protocol involved parallel progression of both the
tumor model and MRI protocol with consideration of a number of interdependent factors that are
summarized in Figure 3.2.
TV injection – limited to BI‐WEEKLY
EXPERIMENTAnti‐angiogenic and Radiation
Tumour control, Overall survival, Biomarkers
Tumour modelTumour vascular permeability
MRI protocolDCE‐MRI
Overall survival
Tumour growth rate
Baseline Tumour size Spatial resolution
Temporal resolution
AIF
qT1
DWI
T2wT1‐gad
Overall scan time
FOV
SNR
Figure 3.2 Diagram highlighting the interaction and interdependence of the multiple factors
considered during the concurrent development of a tumor model and multiparametric MRI protocol.
TV injection = tail-vein injection; AIF = arterial input function; FOV = field of view’ SNR = signal-
to-noise ratio. The TV injection protocol, highlighted in a red box, was developed over a series of
injection studies to optimize the Gd-DTPA injection protocol in order to achieve measurable Gd-
DTPA uptake in the tumor and AIF. MRI sequences included in the final multiparametric MRI
protocol are highlighted in blue. The overall scan time would directly impact the experimental
design, as this would limit the number of mice that can be imaged per day.
33
3.3.1 MOUSE MODEL
MOUSE SURVIVAL & TUMOR GROWTH RATE
As the survival needed to be long enough for at least three serial MRI acquisitions, the survival
required for this study was dependent on how frequently serial multiparametric MRI could be
acquired. The limiting factor for repeated contrast-enhanced MRI was the frequency of tail vein
access. Given that mice have 2 tail veins for access with catheters, studies evaluating a DCE at
only 2 time points, before and after treatment, have repeated tail vein injections in mice as soon
as 24 hours after treatment. [107] When more than 2 time points have been evaluated, successful
repeated tail vein injection of Gd-DTPA has been achieved as frequent as 3 injections within 1
week: at baseline, day 2 and day 7. [177] Based on these previous reports, we aimed to repeat
tail vein injections bi-weekly over this longitudinal study with the DCE acquisition at baseline,
treatment days 3, 7, 10 and 14.
Following IC injection of 1 x 106 cells of either U87 glioma or MDA-MB231 breast cell lines,
mice had a median survival of 15 days. Six days following IC injection of 1 x 106 U87 glioma
cells, 100% (5/5) mice developed tumors that were visible on baseline MRI and these tumors
grew by day 14. Six days following IC injection of 1 x 106 cells of MDA-MB231 breast cells,
0/5 mice had developed tumors visible on baseline MRI. However by day 14, 100% (5/5) mice
were symptomatic (decreased oral intake, seizures, loss of fur) and only 2 survived MRI, which
confirmed large hemorrhagic tumors. [Figure 3.3] On extraction of the brains of the other mice,
large hemorrhagic tumors were grossly visible in these mice.
When 2 x 105 cells were injected, mice injected with U87 glioma cells had a median survival of
19 days whereas mice injected with MDA-MB231 cells had a median survival of 15 days. On
imaging, 100% of mice had visible tumors 6 days after IC injection of U87 glioma cells but no
mice injected with MB231 cells had visible tumor. By day 14, U87 glioma tumors had grown in
size and MB231 tumors were again large and hemorrhagic.
In an effort to prolong survival of mice injected with MB231 tumor cells and find the optimal
window of tumor size without necrosis, an IC injection of 1 x 105 cells was also tested. Despite
the reduction in the number of cells, median survival remained at 15 days and mice died of
hemorrhagic, necrotic tumors.
34
Figure 3.3 Axial T2-weighted MR images of tumors at day 14 following IC injection with
1 x 106 cells of U87 glioma cell line (left) and MDA-MB231 breast cell line (right). The arrow
indicates a large area of intratumoral hemorrhage, which appears as a hypointensity on the T2-
weighted image due to susceptibility of deoxyhemoglobin.
EVIDENCE OF VASCULAR PERMEABILITY
Dynamic contrast-enhanced MR images are shown in Figure 3.4 for large volume U87 and
MB231 tumors. Dynamic uptake of gadolinium was observed in the U87 tumors, demonstrating
the potential for monitoring changes in vascular physiology in this model. In contrast, MB231
tumors failed to demonstrate contrast uptake and with serial imaging, 83% of tumors contained
areas of hemorrhage.
U87 MDA-MB231
35
(b) MB231
T2-w DCE
(a) U87
T2-w DCE
Figure 3.4. Representative images from day 14 (post-IC injection): axial T2-weighted MR (left
frame) and dynamic contrast-enhanced MR image (right frames) for (a) U87 glioma tumor – showing
heterogeneous tumor enhancement (b) MB-231 breast tumor – showing no contrast enhancement (c)
Signal intensity curves for U87 (left) and MB231 (right) show the respective changes in signal
intensity for tumor ROI and contralateral brain.
(c) Signal Intensity Curves
MB231
IF
CL Brain ROI
U87
ROI
CL Brain
IF
Non-enhancing Brain
36
TUMOR LOCATION
Given that the tumor model would be used to evaluate the effect of radiation, a model that
produces well-defined tumors in a predictable tumor location would facilitate delineation of the
tumor and conformal radiation delivery. The preliminary studies demonstrated that the
intracranial injection technique resulted in tumors that were well-defined and localized to the
right frontal lobe, at the location of the IC injection of tumor cells.
FINAL MODEL SELECTION
Based on the findings of this preliminary work, the U87 glioma cell line was selected for
establishment of a well-defined intracranial tumor that has the appropriate growth rate and
survival for serial multiparametric imaging studies and measurable vascular permeability for
evaluation with DCE-MRI.
MRI PROTOCOL
The MRI protocol was developed in a synchronized manner with the establishment of the tumor
model while considering the aims of our specific study to evaluate the effects of radiation and
anti-angiogenic agents and to identify early imaging biomarkers of response. As shown in
Figure 3.2, this involved finding a balance of multiple interdependent factors in the tumor model
and MRI protocol.
The limiting factor for the frequency of serial multiparametric MRI acquisitions was the feasible
frequency of repeated tail vein injections of gadolinium in NOD-SCID mice, which was
estimated conservatively to be bi-weekly based on previous reported experience of 3 injections
of gadolinium via tail vein at baseline, day 2 and day 7.[166] In addition to the timing of the tail
vein injections, the DCE-MRI protocol involved the greatest balance between the spatial and
temporal resolution and therefore this protocol influenced the spatial resolution and slice
prescription of the remainder of the multiparametric MRI protocol. Therefore the development of
the multiparametric MRI protocol involved a total of 58 hours of imaging time for a series of
injection studies for the DCE-MRI protocol and further development of the remaining MRI
sequences.
37
Dynamic contrast-enhanced (DCE) MRI protocol
The first challenge in development of our DCE protocol was establishing a method for
reproducible Gd-DTPA injections in mice that could be repeated longitudinally. Options
considered for vascular access for repeated contrast injection for DCE-MRI acquisition included
repeated tail vein puncture for temporary tail vein catheterization, placement of a long-term
indwelling intracarotid catheter and placement of a long-term indwelling tail vein catheter. The
indwelling intracarotid catheter would interfere with the MR acquisition as a surface head coil
was used and the mouse would be positioned prone in the scanner. Due to the size and fragility
of the tail vein in NOD-SCID mice, even small movements of the temporary indwelling catheter
resulted in loss of access to the tail vein. Therefore use of an indwelling tail vein catheter that
would be left in place throughout the duration of this longitudinal study was not feasible. Tail
vein catheterization was initially carried out in a tail vein catheterization immobilizing device
after which the mouse was transferred onto the MRI slider bed. However, the movement during
transfer resulted in frequent loss of access to the tail vein. Therefore, tail vein catheterization
was carried out on the MRI slider bed. Once this was established, comparison of syringes used
to deliver Gd-DPTA determined that the 50µL 27-G Hamilton gas-tight syringe was an MRI
compatible syringe that facilitated accurate manual injection of Gd-DTPA at the intended rate of
delivery. [Figure 3.6]
A series of injection studies was then performed to determine the optimal dose and speed of Gd-
DTPA injection while concurrently identifying a vessel near the tumor that could be consistently
identified in all mice. [Figure 3.6] The basal artery was identified as a large vessel located near
the tumor so that it could be concurrently captured within the field of view of the DCE
acquisition and consistently identified in all mice. The signal intensity curve was evaluated with
varying doses of Gd-DTPA and speeds of injection. In figure 3.5(a), this vessel is shown pre-
and post-injection of Gd-DTPA and its representative signal intensity curve is shown to
demonstrate that this vessel has an AIF curve with the expected steep rise in signal intensity,
peak and relatively quick washout. [Figure 3.5(b)]
Finally, further adjustments of the DCE protocol were made to establish the optimal balance in
sufficient signal-to-noise, spatial resolution, and temporal resolution with the field of view
required for the injection protocol and AIF that was established. A 250x250x500-µm voxel size
38
at 2.5 sec temporal resolution provided a decent SNR (noise standard deviation(sd) < 0.05
resulting in a per voxel SNR of > 70) in the endogenous contrast frames, and provided the best
possible trade-offs for temporal and spatial resolution and slice number using the murine head
coil.[178]
Pre-contrast Post-contrast
Figure 3.5 (a) Axial T1-weighted MR images of a mouse pre- and post-contrast to demonstrate
the basilar artery (indicated by arrows) that was identifies as a reliable vessel for measurement
of an arterial input function. (b) Signal Intensity (SI) curve of the arterial input function (AIF)
and tumor with a 10µL injection of 20:1 Gd-DTPA:Hep-saline over 6 seconds.
SI
Time (sec)
(a)
(b)
39
INJECTION PROTOCOL:
1. Concentration of Gd-DTPA: a. 50:50 Gd-DTPA:Hep-saline adequate
signal b. 20:1 Gd-DPTA:Hep-saline adequate
signal 2. Speed of injection:
a. Bolus: Two mice with large tumor died immediately after bolus injection. Signal became saturated in the arterial input function.
b. Over 6 seconds: All mice tolerated this rate of injection, even mice with large tumors. Signal saturation did not occur and the peak of AIF was captured.
Identification of the appropriate syringe for injection of Gd-DTPA
1. 1 cc syringe: Plunger was drawn in by the magnetic field so that Gd-DTPA was delivered as soon as the mouse was positioned in the MRI. Secondly, the volume of the syringe was too large to accurately deliver the small volume of Gd-DPTA into the mouse at a reproducible rate.
2. Fifty microlitre 27-G Hamilton gas-tight syringe: The gas-tight syringe along with fixation of the head of the plunger with tape prevented plunger movement and Gd-DTPA delivery prior to the DCE-MRI. The 50µL volume syringe allowed for adequate volume to flush the tail-vein catheter and deliver adequate volume of Gd-DTPA.
SPATIAL & TEMPORAL RESOLUTION:
1. Spatial Resolution: 125 x 125 x 500 µm was established for the high resolution T2 and T1-gad acquisitions
2. Temporal Resolution: A series of imaging session were completed to achieve the minimal temporal resolution of 2.5 seconds, while maintaining the spatial resolution
AIF:
1. Identification of vessel 2. Reproducible 3. Adequate temporal
resolution to capture the early phase of the AIF curve, including the upslope and peak
Figure 3.6 DCE-MRI Protocol Development Experiments
40
After the final DCE-MRI protocol was established, the DWI and T1 quantification was acquired
at the same spatial resolution and spatial registration, as summarized in the final multiparametric
imaging protocol below.
MR imaging was performed using a 7 tesla micro-MRI system (BioSpec 70/30 USR, Bruker,
Ettlingen, Germany), with the B-GA12 gradient coil, a 72 mm inner diameter linear volume
resonator for RF transmission, and anteriorly-placed head coil for RF reception from each
supinely oriented mouse. For each imaging session, mice were anesthetized with 1.8%
isoflurane and place on the MR bed with a bite block and water warming system to maintain
body temperature at at 38°C. Respiration rate was monitored using a pneumatic pillow (SA
Instruments, Stonybrook, NY) with isoflurane adjusted to maintain a consistent respiratory rate
between 35-45 breaths per second throughout the imaging session. Integrated water tubes within
the animal bed maintained temperature homeostasis at 38ºC. MR images were acquired utilizing
a stack of contiguous horizontal slices encompassing the injection site and surrounding brain.
Image slice prescription was matched for qT1, DWI and DCE over the acquired 5 slices. T2w
and T1w-RARE images were comprised of 12 slices to cover the entire brain, including the 5
slices, which were registered with the slices of the quantitative acquisitions.
(1) T2-weighted RARE (rapid acquisition relaxation enhancement): TE/TR=72/5000 ms, RARE
factor 16, 50 kHz readout bandwidth, 125 x 125 x 500-µm voxels using 128x128 matrix over 16
x 16 mm, 2 averages, total 80 sec scan time; Averages were re-ordered to improve motion
suppression.
(2) DWI: Segmented EPI (echo planar imaging, TE=24 ms; 9 segments, b=0, 1000 s/mm2, 3
directions,125 x 125 x 500-µm voxels, 250 kHz readout bandwidth, 128x128 matrix over 16x16
mm FOV, fat suppression. Experiment 1, used TR=3000 and 3 nex (7 min). Experiment 2 used
the respiratory interval as the TR (~ 1500ms) and 5 nex (~5 min) to improve motion insensitivity
of the segmented-EPI reconstruction. Segmented EPI was essential for a reasonable
approximation of geometric truth, compared to a single-shot EPI approach at 7 Tesla. Total scan
time was 7 min 12 sec for non-respiratory gated DWI acquisition.
(3) Variable-TR RARE for T1 quantification: TE = 7 ms, but effectively 14 ms using RARE
factor of 4 for some scan time acceleration, TR = 450, 700, 1000, 1500, 3000, and 5000 ms, 75
41
kHz readout bandwidth, 250 x 250 x 500-µm voxels using 64x64 matrix over 16x16mm FOV, 2
averages, total 4 min 40 sec scan time; Averages were re-ordered to improve motion suppression.
(4) DCE-MRI using 2D-FLASH: TE/TR = 2.3/39 ms, 35-deg flip angle, 81.5 kHz readout
bandwidth, 250 x 250 x 500-µm voxels using 64x64 matrix over 16x16 mm FOV, 2.5
seconds/repetition of 5-slices, 100 repetitions encompassing 4min 11 sec. The spatial resolution
and slice prescription matched to SR-RARE. Contrast delivery (0.38mmol/kg Gd-DTPA) by
manual injection over 6 seconds via a tail vein cannula, utilizing a precision 50μl-volume 27-G
Hamilton syringe, started after 6 baseline images
(5) Contrast-enhanced T1-weighted RARE (T1gad): TE/TR = 8/1200 ms, RARE factor of 4, 2
averages, 81.5 kHz readout bandwidth, 125 x 125 x 500-µm voxels using 128x128 matrix over
16 mm FOV, total 77 sec scan time.
The total imaging time per mouse was 35 minutes including the set-up on the slider bed and
placement of the tail-vein catheter. This enabled full multiparametric imaging of up to 12 mice in
one imaging day.
Protocols were adjusted for adequate signal-to-noise ratio (SNR) (noise sd < 0.05 resulting in per
voxel SNR of > 70) within single image voxels and small regions-of-interest. Based on pilot
acquisitions, the SNR in individual voxels was 90 + 25; therefore the minimal ROI volume to
achieve an SNR of greater than 70 to ensure that the standard deviation of ADC is less than 2.5%
was 2 voxels, which represents 0.031 mm3. This SNR impacts the precision of imaging
biomarkers and increasing the precision will increase the sensitivity to longitudinal changes
within registered volumes.
3.4 DISCUSSION
Synchronized development of a tumor model and MRI protocol is a novel approach for
designing the tumor model and imaging protocol to facilitate meaningful and efficient data
collection and analysis for the specific aims of the pre-clinical study. With this approach, the
many interdependent requirements and limitations of both the tumor model and imaging protocol
are considered together and in context of the study design. [Figure 3.2]
42
We applied this approach to develop a tumor model and imaging protocol for use in an
experiment evaluating the effects of radiation and sunitinib. For this purpose, it was necessary
for the tumor model and imaging protocol to demonstrate vascular permeability and changes in
vascular physiology. Serial DCE-MRI images for each mouse using repeated tail-vein injections
of gadolinium were used to evaluate longitudinal changes in vascular physiology. To our
knowledge, there are no previous studies evaluating longitudinal changes in DCE-MRI measures
in murine intracranial tumors over multiple measures of DCE, however repeat tail vein injections
have been used to measure changes in DCE metrics in other in vivo models.[177] This study
demonstrates that longitudinal bi-weekly DCE-MRI with gadolinium administration by tail vein
injection is feasible in NOD-SCID mice. This also demonstrates the importance of developing a
tumor model that facilitates the planned imaging follow-up with the feasible MRI schedule.
The U87 orthotopic model selected for future experimentation of radiation and sunitinib based
on the results of this preliminary study has strengths and limitations. Because the tumor may be
treated with radiation in the planned study, a model that produces a localized, well-defined tumor
was desired as this would ensure better delineation and targeting of the tumor with radiation.
Additionally, by ensuring the tumor is localized to the right frontal lobe, the location of the IC
injection, the contralateral brain could be used as an internal control for comparison of MRI
metrics. Furthermore, the U87 orthotopic model had high efficiency of tumor development
following intracranial tumor cell injection with greater than 85% of mice developing MR-visible
tumors after IC injection in all the preliminary studies. A criticism that has been raised about
this model for investigating response to radiation and anti-angiogenic agents is that tumors
created by intracranial injection of cells do not share the same invasive and vascular properties of
human gliomas.
The multiparametric MRI protocol developed in this preliminary study balanced multiple factors
including adequate signal to noise and spatial resolution required to evaluate the small
intracranial tumors at baseline and in early follow-up, temporal resolution for acquisition of the
AIF for perfusion analysis and overall imaging time in order to facilitate acquisition of
multiparametric MRI measures for multiple mice in a longitudinal fashion. As previous studies
using serial DCE-MRI studies for longitudinal follow-up of vascular changes in intracranial
tumor have not been reported, substantial time and work was required to develop the injection
protocol and overall DCE-MRI protocol. We established a protocol that enabled measurement of
43
individual AIF and T1 values for application into the Modified Tofts analysis and that facilitated
serial DCE-MRI measures using repeated tail-vein injections of gadolinium for longitudinal
study. As part of this development, we established that a major limiting factor that dictated the
overall survival for the tumor model and imaging design is the frequency of feasible tail-vein
injection for gadolinium administration. In order to attain meaningful quantitative data, we
aimed to measure individual mouse AIF and this required a high temporal resolution that would
help capture the early rise and peak of the AIF signal intensity data. As a result, a 2-D
acquisition of five 500 µm slices was used rather than a 3-D acquisition to facilitate the required
temporal and spatial resolution. This also required adequate FOV and number of slices to capture
both the tumor and the AIF. These aspects of the DCE-MRI dictated the FOV and spatial
resolution of the other imaging sequences.
This protocol was applied in the subsequent study of radiation and sunitinib in the established
intracranial U87 mouse model. MR imaging was used to exclude mice without visible tumors on
T2-weighted MR images acquired 6 days following IC injection (i.e. day 7 post-IC). These
baseline MR images were used to measure tumor volumes and stratify mice to treatment arms
based on baseline tumor volumes. These baseline MR images were also used to guide conformal
radiation planning. Finally, the entire MRI protocol was repeated longitudinally to monitor
tumor growth and change in the multiparametric MRI measures longitudinally over the course of
treatment and follow-up. A major strength of this approach is that the MR findings are based on
a well-established MRI protocol that has been judiciously designed with a synchronized tumor
model for the specific aims of the experiment and this protocol would be consistently repeated
over the course of the experiment. Because the MR measurements are very sensitive to changes
in the MRI protocol, even small changes of the protocol during the course of the experiment
would potentially affect the MR measurements. Therefore repeating the same MRI protocol
consistently through the duration of a study is essential for meaningful analysis and
interpretation of changes in MRI measurements over time.
44
3.4.1 CONCLUSION
This preliminary work demonstrates an approach for synchronized development of a pre-clinical
animal tumor model and imaging protocol that can be used to evaluate the effects of a specific
therapy and identify potential early imaging biomarkers of response for that treatment. By
establishing the tumor model and MRI protocol through judicious preliminary studies reduces
the likelihood for making changes during the experiment thereby enabling more meaningful
interpretation of the findings.
45
Chapter 4 Imaging Biomarker Dynamics in Intracranial Murine Glioma Study
of Radiation and Anti-angiogenic Therapy
Authors: Caroline Chung1, Warren Foltz1, Kelly Burrell2, Petra Wildgoose1, Patricia Lindsay1,
Christian Graves3, Kevin Camphausen3, David Jaffray1, Gelareh Zadeh4, Cynthia Ménard1
Institutions: 1 Princess Margaret Hospital 2 SickKids Hospital 3 National Cancer Institute
4 Toronto Western Hospital
(submitted to Radiology)
46
4 Abstract
INTRODUCTION: There is a growing need for non-invasive biomarkers that can guide
individualized spatio-temporal delivery of radiotherapy (RT) and anti-angiogenic (AA)
treatments for brain tumors. This study explores the potential of serial MRI to aid in the design,
delivery and early response measure of RT and sunitinib (SU), a tyrosine kinase inhibitor to
VEGFR 1/2, in a murine intracranial glioma model.
METHODS: Mice with visible tumor on MRI were stratified by tumor size to 4 arms: control,
RT, SU and SU+RT. Conformal RT with MRI and on-line cone-beam CT guidance delivered
8Gy in 1fraction to tumor. Serial multiparametric MRI (T2-weighted, diffusion, dynamic
contrast-enhanced, T1-weighted with gadolinium) evaluated tumor volume, diffusion and
perfusion changes. Individually measured T1 and AIF values were applied to Modified Tofts
analysis for perfusion analysis. Serial urine samples, pooled by each arm, were analyzed with
human angiogenesis antibody array.
RESULTS: Mice survived longer in all treatment arms compared to placebo: SU+RT surviving
longest (median survival 35 days, p<0.0001) followed by RT (median survival 30 days, p=0.009)
and SU (median survival 30 days, p=0.01). As early as treatment day 3, while all treatment arms
had stable tumor volumes, the following candidate imaging biomarkers were identified: (1) SU
arms showed decrease in Ktrans of 77% SU (p=0.02) and 73% SU+RT (p=0.03), and (2) RT arms
showed a greater relative increase in ADC (ADC day3/ADC day0) vs. non-RT arms: SU+RT
2.35 (p=0.003) and RT 2.48 (p=0.045) vs. control 1.33 (p=0.2) and SU 1.34(p=0.2). Early ADC
response was correlated with tumor growth delay (R = -0.878, p=0.0002).
CONCLUSION: Early changes in serial diffusion and perfusion imaging biomarkers reflecting
treatment response may guide the optimal dose and scheduling of combined RT and AA therapy.
47
4.1 INTRODUCTION
Advances in radiotherapy and increased integration of anti-angiogenic agents into treatment of
brain tumors are driving the need for non-invasive biomarkers that can guide the temporal and
spatial prescription of treatments. Due to dose-limiting toxicities, either radiation or anti-
angiogenic agents as monotherapy can result in inadequate tumor control. Attempts to improve
tumor control by combining anti-angiogenic agents with radiotherapy in the clinical and pre-
clinical setting have been met with mixed responses.[8, 49, 50, 179] This is, in part, due to the
limited knowledge available to define the optimal sequence and scheduling of concurrent
therapeutics, in particular the combination of AA and RT for individual tumor types. Jain et al.
have introduced the concept of ‘vascular normalization’, whereby anti-angiogenic therapy prunes
the immature and inefficient blood vessels present in tumors, leaving behind more normal blood
vessels that can deliver nutrients, oxygen and therapeutics more effectively to tumor. [8, 168]
However, the timing of onset and duration of this phenomenon has yet to be fully determined,
and may vary between different anti-angiogenic agents, tumor types and individual patients.
Establishing early, non-invasive, reproducible, and quantitative biomarkers that reflect tumor
vascular and physiological changes to therapies will provide a better understanding of the
dynamics of these responses and help determine the optimal schedule for combined therapy and
facilitate individualized, adaptive approaches to treatment.
Pre-clinical animal models of cancer, such as intracranial xenografts, provide an invaluable
proof-of-principle model for evaluating the effects of new therapies and identifying promising
early measures of treatment response.[180] Longitudinal imaging with serial MRI of intracranial
tumors can confirm gross tumor at baseline and follow tumor size as a measure of treatment
response in clinical and pre-clinical studies.[168, 181, 182] However, there is growing interest in
identifying earlier measures of response to therapy that may precede tumor volume changes.
Apparent diffusion coefficient (ADC) is a measure of water mobility that reflects cellularity
within a tumor.[147] Rises in tumor ADC after cytotoxic therapy have been detected prior to
any significant tumor volume change.[142, 143, 149, 157, 169, 170, 183] Measures of vascular
response, such as changes in initial area under the curve at 60 seconds (iAUC60), Ktrans (a
constant reflecting movement of contrast out of vascular space) and/or Kep (a constant reflecting
movement of contrast back into vascular space), following anti-angiogenic therapy can occur
48
prior to or independent of changes in tumor morphology and volume.[105, 106, 111] Therefore,
longitudinal measurement of tumor vascular response and ADC change along with
morphological response would provide a more comprehensive evaluation of the effects of anti-
angiogenic and radiation therapies.
Sunitinib is an oral tyrosine kinase receptor inhibitor that acts at VEGF receptors 1 and 2, PDGF
receptor, stem cell factor receptor (c-KIT), FLT3 and RET kinases. [184] Sunitinib has efficacy
as a monotherapeutic agent in solid cancers [60, 61, 185, 186] as well as synergistic effects in
combination with radiation [62, 187, 188] and is able to cross the blood-brain barrier.[189]
However, the concurrent combination of radiation and sunitinib has not yet been evaluated
intracranially and the optimal timing for combining these therapies is yet to be established.
The purpose of this study was to explore serial multiparametric MRI as a biomarker strategy to
guide the design, delivery and early response evaluation of murine intracranial tumor
investigation of radiation and sunitinib. As frequent serial MRI studies are difficult to acquire in
patients, this study demonstrates how pre-clinical investigation can facilitate discovery of the
most promising biomarkers and time points for translation into the clinical setting.
4.2 METHODS & MATERIALS
Cell Culture. Human malignant glioma (GBM) cell line U87 (gifted by Dr. Abhijit Guha’s lab)
were grown in DMEM containing glutamate (5 mmol/L) and 5% fetal bovine serum under
standard conditions (37 C in 5% CO2 and 95% room air).
Mouse Intracranial Model. As described in detail previously, 6 week-old NOD/SCID mice
were anesthetized with intraperitoneal injection of 0.6-0.8 mL Avertin. U87 GBM (2 x 105cells)
in 10 μL PBS were injected into the right frontal lobe (1mm ant, 2mm lat to bregma at 3mm
depth from the dura). All animal care and studies were carried out in accordance with
institutional animal care guidelines.
Preliminary imaging experiments established that MRI-visible tumors were present by day 7
post-IC injection. T2-weighted MR images were acquired for each mouse at day 7 post-IC
49
injection in order to confirm the presence of tumor and measure tumor size. T2-weighted images
were used to allow for quick, efficient screening for gross tumor in all mice. Mice were
stratified by baseline T2-weighted tumor size so that there were similar numbers of ‘small’ vs.
‘large’ tumors in each of 4 treatment arms: (1) Control (Ctrl) – placebo alone (n=12), (2)
Radiation (RT) – radiation with placebo (n=13), (3) Sunitinib (SU) – sunitinib alone (n=13), and
(4) Radiation and sunitinib (RT+SU) (n=14).
Experiment 1
After confirming the presence of gross tumor on baseline MRI acquired 7 days post-IC, both
sunitinib and radiation treatment started on day 8 post-IC injection in the scheduled summarized
in Figure 4.1.
Figure 4.1 Timeline of the treatments and MRI imaging sessions. MRI on day 0 confirmed and
measured the volume of gross tumor at baseline. Sunitinib (SU) was delivered for 7 weekdays.
Radiation (RT) 8Gy in 1 fraction was delivered on day 1 of treatment, after the first dose of SU.
Multiparametric MRI was acquired bi-weekly on days 3, 7, 10, and 14.
As summarized in Figure 4.2, thirty six mice were followed for survival analysis and 16 mice
were followed with serial MRI and urine collection. Serial multiparametric MRI (T2-weighted,
T1-gad, DCE-MRI, DWI and T1 quantification) were acquired at days 3, 7, 10 and 14 after
baseline imaging to monitor tumor volume and physiological responses over time. Serial urine
samples were also collected at baseline then bi-weekly.
RT
Day 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
SU
MRI
50
Experiment 2
Experiment 2 intended to confirm that the early MRI changes with each treatment arm were
reproducible and to provide pathological correlation for these MRI findings. Intracranial tumors
were established and confirmed in 12 mice using the same protocol as for experiment 1. These
mice were stratified by tumor size to the same 4 treatment arms. Treatment was delivered, as per
treatment arm, from days 1 to 3. Following multiparametric MRI on treatment day 3, all mice
were sacrificed to acquire pathological data to correlate with the early imaging findings.
IC injections (n =28)
Day 7 – MRI to confirm tumor presence and measure baseline tumor size
Placebo alone (n =12) SU alone (n =13) Placebo + RT (n =13) SU + RT (n = 14)
Serial Multiparametric MRI:
Day 3,7,10, 14
IC injections (n =30)
Survival Analysis
Sacrifice when symptomatic
Placebo + RT
(n = 4)
Placebo + RT
(n = 9)
Placebo
(n = 9)
Placebo
(n = 3)
SU
(n =9)
SU
(n =4)
SU + RT
(n = 9)
SU + RT
(n = 5)
Figure 4.2 Flow Diagram Summarizing Experiment 1: Radiation and Sunitinib Study.
Following intracranial (IC) injection, mice were imaged for baseline tumor size at day 7 after
which they were randomized to the 4 treatment arms: placebo, placebo + radiation (RT),
sunitinib (SU) and SU + RT. For each treatment arm, a proportion of the mice were followed
with serial multiparametric MRI and the remaining mice were followed for survival analysis.
51
Systemic treatment. Sunitinib (Pfizer) 40 mg/kg/day, as used by Scheuneman et al. [190],
dissolved in carboxymethylcellulose (CMC) or CMC (placebo) was administered by oral gavage
for 7 weekdays, starting day 8 post-IC injection. Placebo oral gavage was administered in the
non-sunitinib arms to expose all mice to the same stress and risk of complication with the oral
gavage procedure. For mice receiving radiation, oral gavage of sunitinib or placebo was
administered between 1 to 3.5 hours prior to radiation treatment, as the time to peak
concentration ranged between ranged between 1 to 3 hours and plasma half-life ranged between
2.0 – 4.6 hours following single oral doses of sunitinib 40mg/kg or less.[66]
Radiation treatment. Mice were anesthetized using isoflurane and placed in an in-house
custom built immobilization device composed of an MRI compatible bite block and ear pins.
Irradiation was delivered using a cone-beam CT image-guided small animal irradiator
(XRad225Cx, Precision X-Ray, Inc). Radiation (225 kVp) was delivered with anterior-posterior
parallel opposed beams using a 0.5 cm collimator. The irradiation was guided using a cone-beam
CT image set acquired immediately prior to treatment using information about tumor location
from the baseline MRI. [Figure 4.3] A single fraction of 8 Gy was prescribed to 5mm depth
from the dorsum of the skull. Single fraction radiation was used to better enable translation of
our biomarker findings to a concurrent clinical study evaluating the effects of sunitinib with
radiosurgery. All mice, including those that were not irradiated, were anesthetized for cone-beam
CT acquisition to ensure all mice were exposed to similar anesthetic conditions.
MRI. A 7-Tesla Bruker BioSpec 70/30 with the B-GA12 gradient coil, 7.2cm linear volume
transmitter, murine slider bed, and murine head coil was used for serial imaging. For each MR
imaging session, mice were anesthetized with isoflurane, placed on the MR bed with a bite block
and water warming system to maintain temperature. Respiration rate was monitored using a
pneumatic pillow (P-respTM, SAII) throughout the imaging session with isoflurane adjustment to
maintain a consistent respiratory rate. Multiparametric imaging protocols for serial imaging
sessions were developed in-house through preliminary studies that aimed to optimize the balance
of temporal and spatial resolution as well as total imaging time per session.
52
Table 4.1. Multiparametric MRI Protocol
Sequence Details Time T2-weighted RARE (FSE)
Tumor anatomy
TE=72ms; TR=5000ms RARE factor 16 50 kHz readout bandwidth; 125x125x500µm voxels; FOV 16x16mm; 2 averages, averages re-ordered to improve motion suppression
1m 20s
Diffusion-weighted imaging (DWI)
Water mobility, Cellular density
Segmented EPI, 9 segments; TE=24ms; TR=3000ms; 3 nex; 125x125x500µm voxels; FOV 16x16mm; b=0, 1000s/mm2; 3 orthogonal diffusion directions; Fat suppression With respiratory gating: TR ~1500ms; 5nex (~5min) to improve motion sensitivity of segmented-EPI reconstruction
7m 12s
T1 quantification (saturation recovery-RARE)
Used for DCE-MRI analysis
TE=7ms; TR=450,700,1000,1500,3000, 5000ms; RARE factor of 4; 75 kHz readout bandwidth; 250x250µmx500µm voxels; FOV 16x16mm; 2 averages, averages were re-ordered to improve motion suppression
4m 40s
Dynamic contrast-enhanced, 2D-FLASH
Vascular perfusion/ permeability
TE=2.3ms; TR= 39.1ms; flip angle 35 degrees; 81.5 kHz readout bandwidth; 250 x 250 x 500µm voxels; FOV 16 x 16mm; matched spatial resolution and slice prescription to SR-RARE; temporal resolution 2.5 sec/repetition of 5 slices; 100 repetitions; contrast delivery after 6 baseline images (0.38 mmol/kg Gd/DTPA via manual tail vein injection over 6 s using 50µL 27-G Hamilton syringe)
4m 10s
Contrast-enhanced T1-weighted RARE
Tumor anatomy
TE=8ms; TR=1200ms, RARE factor 4; 81.5 kHz readout bandwidth; 125 x 125 x 500µm voxels; FOV 16x16mm; matched slice prescription and image resolution to 2D-RARE; 2 averages; start imaging at 5min post-contrast
1m 20s
*Diffusion weighted imaging acquisition required up to an additional 4 minutes when respiratory
gating was applied. m = minute(s) s = second(s)
53
Image Analysis. Image processing and manual segmentation of regions-of-interest (ROIs) was
supported by MIPAV software (National Institutes of Health, Bethesda, MD). Tumor ROIs were
manually delineated (by a single observer) on post-contrast T1-weighted images, as the
integrated region of signal enhancement. The volume of these tumor ROIs was extracted at
baseline and at each follow-up imaging time point using MIPAV software.
For DCE imaging data, the tumor ROIs delineated on post-contrast T1-weighted (T1-gad)
images were applied directly onto DCE image sets, to extract signal intensity data for the ROI.
Manual segmentation of the basilar artery on the same single slice DCE images as the tumor ROI
were used to extract signal intensity data for the arterial input function (AIF).[191] Initial area
under the signal intensity curve at 60 seconds (iAUC60) was calculated using normalized signal
intensity values. Using The DCE Tool v1.04 (www.TheDCETool.ca, University Health
Network/OICR), both linear and non-linear models were compared for estimating gadolinium
concentration from signal intensity.[192] Modified Tofts analysis was used to calculate iAUC60
for the gadolinium concentration curve, Ktrans and Kep. Individual mouse AIF and individual
mouse T1 were applied in Modified Tofts analysis. In mice where individual T1 measures were
unsuccessful due to respiratory motion artifact, the mean population T1 was used.
For diffusion analysis, tumor ROIs delineated on T1-gad images were directly transposed onto
apparent diffusion coefficient (ADC) maps. The tumor ROI volume was copied and applied in a
similar region of contralateral (CL) brain for the purpose of measuring a comparative control
mean ADC in the CL brain. Voxels clearly including cerebrospinal fluid in the ventricles were
excluded. Mean ADC for the entire tumor ROI and CL brain ROI and standard deviations were
extracted. As the mean ADC in the CL brain ROIs varied from mouse to mouse but did not vary
significantly within each mouse over time, the mean ADC of tumor was normalized to the mean
ADC of the CL brain ROI.
Urine Biomarkers. NOD/SCID mouse urine samples were collected at baseline and bi-weekly,
under sterile conditions by bladder massage and then frozen at -20˚C immediately post-
collection. Urine was pooled for each treatment arm to obtain sample volumes of at least 125μL
per treatment arm as required for analysis using the Human Angiogenesis Antibody Array (R&D
Systems). Human Angiogenesis Antibody Array kit is a multiplex antibody array that detects the
level of 55 different angiogenesis-related proteins in one sample. The manufacturer’s protocol
54
was followed as described briefly. Array Buffer 7 (provided in the kit) was pipetted, 2 mL, into
each well of the 4-Well Multi-dish to block the membranes for 1 hour. Urine was equilibrated
for 3 hours at room temperature. A 125 µL aliquot of pooled mouse urine was added to 0.5 mL
Array Buffer 4 in separate tubes and final volume adjusted to 1.5 mL by adding Array Buffer 5.
Each tube of sample was supplemented with 15 µL of detection antibody cocktail, and incubated
at room temperature for 1 hour. Array Buffer 7 was aspirated from the wells and the
sample/antibody mixtures were added to the membranes and incubated overnight at 4 ˚C with
agitation on a rocking platform. Membranes were then washed three times in 1X wash buffer
with agitation for 10 minutes and supplemented with streptavidin-HRP and incubated at room
temperature for 20 minutes. Each membrane was then incubated with chemiluminescent
detection reagent (Millipore) and chemiluminescence was analyzed within 10 minutes on a
Fujifilm LAS 4000. Mean pixel density (MPD) was calculated using Multigauge version 3.0
(Fujifilm). Background luminescence was subtracted from regions of interest such that data
represent the mean pixel density. Negative MPDs are represented at zero.
Statistical Analysis. Log rank statistics were used for survival analysis. To determine the effect
of treatment on the growth rate of brain tumors in these mice, a linear mixed effects model was
applied, as this model accounts for the effect of treatment, effect of time and the interaction
between treatment group and time. To stabilize the variance and obtain normally distributed
residuals, tumor volume was transformed to the logarithmic scale. Doubling time was
determined using the formula: ln(2)/growth rate. To analyze changes in DCE and ADC
measures from baseline, student’s paired t-test and ANOVA were applied, using a significance
level of p<0.05 for both.
4.3 RESULTS
Tumor Growth Parameters
Five out of 57 mice were excluded from further analysis based on the absence of visible tumor at
baseline MRI at day 7 post-intracranial injection. These 5 mice survived to the end of the
experiment without any signs of tumor development. The 52 mice with visible tumors on
baseline MRI were stratified to treatment arms such that the mean tumor volumes for all arms
55
were comparable, ranging from 0.84 to 1.17 mm3 (p =0.16). Tumor volumes in individual mice
ranged from 0.14 to 2.60 mm3. Figure 4.1(a) displays the range of variability in baseline tumor
size, shape and location.
Figure 4.3 (a) Representative intracranial tumors at baseline demonstrating the variability in size and
location (b) Representative images used for radiation planning and dose evaluation: (i) Axial co-
registered baseline T1-weighted gadolinium-enhanced MRI and treatment day cone-beam CT (ii)
Axial cone-beam CT image with radiation isodoses (10% orange, 90% red, 95% teal) around the
tumor (blue) and the isocentre at the centre of the 2 axes. The isocentre was placed using visual
estimation of the tumor location on the CBCT, using baseline MR information.
(b)
(a)
tumor
(i) (ii) 95% isodose 90% isodose 10% isodose
56
Mice survived longer in all treatment arms compared to placebo, with SURT surviving longest
(p<0.0001) followed by RT (p=0.009) and SU (p=0.01). [Figure 4.4(a)] The combined SURT
arm also had greater survival than SU alone (p = 0.02) and RT alone (p = 0.05). Median survival
was greatest for SURT (35 days) followed by either RT or SU monotherapy (30 days) and lowest
for placebo (27 days). There was one early death immediately following oral gavage in the
sunitinib monotherapy arm.
A logarithmic transformation to stabilize the variance and obtain normally distributed residuals
was used to evaluate change in tumor volume over time in each treatment arm. [Figure 4.4(b)] A
linear mixed effects model was used to account for the effect of different treatments, time and
the interaction between treatment group and time in order to determine the effect of treatment on
tumor growth rate for each treatment arm. Overall, LN tumor growth rate increases per day
significantly differed between the four treatment arms (p<0.0001). Specifically, the daily LN
tumor growth rate increases in the non-radiation control and SU groups (0.08 and 0.098,
respectively) were significantly greater than the daily growth rate increases in the SU+RT and
RT groups (0.029 and 0.025, respectively), p<0.001. There was no significant differences in LN
tumor growth rate increase per day between the RT and the SU + RT groups (p=0.75) or between
the placebo and the SU groups (p=24). When using the logarithmic transformation, the LN tumor
growth rate can be interpreted on the original scale as the percentage increase in volume per day.
Based on this, the control arm grew exponentially at 8.0% per day vs. 9.8% per day for the SU
arm vs. 2.9% per day for the SU+RT arm vs. 2.5% per day for the RT arm. This translated to
tumor double times of 8.0 days for control, 7.0 days for SU, 23.6 days for SU+RT and 27.6 days
for RT.
57
Time (days)0 2 4 6 8 10 12 14
Mea
n L
N R
ela
tive
Tu
mo
r V
olu
me
+/-
SE
0.0
0
.5
1.0
1.
5
2
.0
Time (days)0 2 4 6 8 10 12 14
Mea
n L
N R
ela
tive
Tu
mo
r V
olu
me
+/-
SE
0.0
0
.5
1.0
1.
5
2
.0
0
0.2
0.4
0.6
0.8
1
1 6 11 16 21 26 31 36 41 46 51
Time (days)
Su
rviv
al
Control
SU
RT
SU + RT
(a)
(b)
Figure 4.4 (a) Survival curves. Median survival was 35 days for combined sunitinib and
radiation (SU+RT), 30 days for both radiation (RT) and sunitinib (SU) monotherapies, and 26
days for placebo. (b) Tumor growth curve with mean relative tumor volume for each treatment
group shown on a logarithmic scale. Daily LN tumor growth rate increases in the non-radiation
control and SU groups (0.08 and 0.098, respectively) were greater than daily growth rate
increases in the SU+RT and RT groups (0.029 and 0.025, respectively), p<0.001. Error bars
represent standard deviation.
58
Serial and Multiparametric MRI Analysis
No mice expired due to serial MRI. Bi-weekly tail vein catheterization for serial DCE-MRI was
successful until the last day of imaging. Of the mice followed with serial imaging and urine
collection, two mice died due to technical difficulties, during oral gavage and urine collection.
Perfusion MRI
As there was no enhancement of the contralateral normal brain in any mice, perfusion analysis
was focused on tumor ROI alone.[Figure 4.5(a)] Only SU+RT resulted in a 31% decrease in
iAUC60 from baseline to treatment day 3 (p=0.005), which remained decreased throughout the
duration of SU treatment but eventually rose back to baseline by day 14. [Figure 4.6(a), (b)] The
SU and RT arms did not demonstrate this iAUC60 response. In order to ensure that this finding
was not a result of variable AIF measures in each arm, changes in iAUC60 of the AIF curves
between baseline and day 3 were evaluated for each arm. [Figure 4.6(c)]. As shown in Figures
4.4c and 4.4d there was no correlation between the changes in iAUC60 from baseline to day 3 in
tumor and AIF for each treatment arm. Duplicate experiments also confirmed this decrease in
iAUC60 from baseline to day 3 following SU+RT by 84% (p=0.02), despite variable changes in
AIF. [Figures 4.6(b)]
In this study, 9% of AIF and 15% of T1 acquisitions could not be used for DCE analysis due to
imaging artifacts, predominantly a result of respiratory motion. For all the mice in which
individual AIF was successfully measured, the large error bars noted in Figure 4.5(b)
demonstrates the wide variability in AIF between mice. In the mice where individual T1
measures were not available, mean T1 value for all acquired T1 data was used for modified Tofts
analysis. In general, T1 values for individual mice did not vary more than 500 ms over the
course of serial measurements, therefore T1 data were not used when the T1 values varied
greater than 500 ms or were beyond the physiologic range (>3200 ms). All DCE image sets with
motion artifact interrupting individual AIF measurements were excluded from analysis.
Modified Tofts analysis using all available measured mouse T1 values and AIF data
demonstrated that both SU arms had early decreases in Ktrans by treatment day 3, 5.4% for SU
(p=0.18) and 35.6% for SURT (p=0.048), whereas RT and control arms had increases of Ktrans at
day 3. [Figure 4.7(b)] With longitudinal follow-up, Ktrans remained decreased in both SU arms
59
throughout the duration of SU treatment. When SU was stopped, Ktrans returned to the baseline
value in the SU arm but remained decreased in the SURT arm. [Figure 4.7(a)] A duplicate
experiment with individual T1 and AIF values for all acquisitions, resulted in a significant
decrease in Ktrans at day 3 for both SU arms: 76.8% for SU (p=0.02) and 73.3% for SURT
(p=0.03). [Figure 4.7(b)] Comparison of Ktrans responses applying population mean T1 vs.
individual T1 values in the modified Tofts analysis demonstrates that the significant response in
Ktrans was revealed only when individual T1 values are applied. [Figure 4.7(e)] Although
changes in Kep were not significant, the mean Kep decreased in the two SU arms and increased in
the non-SU arms. [Figure 4.7(c)] Similar to Ktrans responses, Kep remained decreased throughout
the duration of SU in the two SU arms. When individual T1 and AIF data were applied in the
modified Tofts analysis in a validation experiment, larger decreases in Kep from baseline to day 3
were observed: 63.0% for SU (p=0.04) and 51.5% for SURT (p=0.05).[Figure 4.7(c)]
60
(a)
ROI
15 sec 188 sec 45 sec T1-post gad
AIF
Figure 4.5 (a) Representative
images of DCE-MRI with
standard location of AIF and
typical tumor ROI. (b) Signal
Intensity Curve for the mean AIF
of all mice imaged in this
experiment with error bars
representing the standard
deviation.
(b)
61
-100
-50
0
50
100
150
200
0 3 6 9 12 15
Treatment day
% C
ha
ng
e in
iAU
C6
0 f
rom
ba
se
line
Control
RT
SU
SURT
(a)
(c) (d)
Figure 4.6 (a) Mean percent change in iAUC60 for each treatment arm over time from baseline to day 14 (b) Mean percent change in iAUC60 of the ROI from baseline for each treatment arm at treatment day 3 (c) Mean percent change in iAUC60 of the AIF from baseline for each treatment arm at treatment day 3. Error bars reflect standard deviation.
62
-150
-100
-50
0
50
100
150
200
250
0 5 10 15
Treatment day
% C
ha
ng
e K
tra
ns
fro
m b
as
elin
e
ControlRT
SUSURT
(a)
-150
-100
-50
0
50
100
150
200
250
Control RT SU SURT
% C
han
ge
Ktr
ans
Experiment 1
Experiment 2
-150
-100
-50
0
50
100
150
200
250
Control RT SU SURT
% C
han
ge
Kep
Experiment 1
Experiment 2
-150
-100
-50
0
50
100
150
200
250
Control RT SU SURT
% C
han
ge
T1
Experiment 1
Experiment 2
-150
-100
-50
0
50
100
150
200
250
Control RT SU SURT
% C
han
ge
Ktr
ans
Population T1
Individual T1
(d)
(b) (c)
(e)
Figure 4.7 (a) Mean percent change in Ktrans for each treatment arm over time from baseline to day 14.
Percent change from baseline to treatment day 3 (D3) for each treatment arm: (b) Ktrans, based on modified Tofts analysis (c) Kep, based on modified Tofts analysis (d) pre-contrast tumor T1, demonstrating the wide inter and intra-group variability. (e) Ktrans based on modified Tofts analysis using population mean T1 and individual T1 values. Error bars represent standard deviation.
63
Diffusion MRI
Given that mean ADC in tumor was higher than mean ADC in a similar region of contralateral
(CL) brain in all animals at baseline and the tumor ADC increased beyond CL brain over time in
all arms, we compared mean tumor ADC values as their percentage elevations above the CL
brain. Figure 4.8(a) demonstrates that longitudinally, both RT arms demonstrated faster and
larger ADC rises than the non-RT arms from baseline to day 14. Focusing on early changes to
ADC at treatment day 3, ADC response was quantified as the ratio of ADC at day 3 over ADC at
day 0. Looking at this relative changes in ADC from baseline, the two RT arms had greater
increases in ADC from baseline of 1.8 for RT (p=0.09) and 2.33 for SU+RT (p=0.002) compared
with the two non-RT arms, 1.29 for Control (p=0.and 1.05 for SU (p=0.8). A confirmatory study,
utilizing respiratory gating to minimize the effects of respiratory motion on our ADC measures,
showed similar ADC responses with significant relative increases in ADC of 2.35 for SURT
(p=0.003) and 2.48 for RT (p=0.045) compared with 1.33 for control (p=0.2) and 1.34 for SU
(p=0.2).[Figure 4.8(c)] When the magnitude of the relative change in ADC from baseline to day
3 was plotted against the tumor growth on a logarithmic scale for each mouse in the first
experiment, a high correlation was demonstrated between the ADC response and Ln(tumor
growth rate) as shown in Figure 4.8(d). The Pearson correlation coefficient of the ratio of ADC
at day 3 over ADC at day 0 vs. Ln (tumor growth rate) was -0.878 (p=0.002). Figure 4.8(d) also
exhibits that radiation treatment resulted in a greater ADC response and lower tumor growth rate
compared with the non-radiation arms. Sunitinib does not appear to have a great effect on ADC
response and was not associated with lower tumor growth rate.
64
0
10
20
30
40
50
Day 0 Day3 Day7 Day10 Day14
Treatment Day
% A
DC
tum
ou
r/A
DC
co
ntr
ala
tera
l bra
in RT
SURT
SU
CTRL
0
1
2
3
4
Control RT SU SURT
Relative Change ADC Day 3/Day 0
Treatment arms
Experiment 1
Experiment 2
(a) (b)
(c)
Baseline Day 3
T1gad
ADC
Figure 4.8 (a) Percent change in ADC tumor/ADC contralateral brain over time (b) Representative T1-
weighted gadolinium-enhanced images and apparent diffusion coefficient (ADC) maps at baseline and
on treatment day 3 (D3) for a mouse treated with radiation and sunitinib (c) Relative changes in ADC
(day 3/day 0) in each treatment arm, demonstrating a greater increase in ADC for the two RT arms vs.
non-RT arms in both for experiments 1 and 2. Experiment 2 showed significant rises for SU+RT 2.35
(p=0.003) and RT 2.48 (p=0.045) vs. control 1.33 (p=0.2) and SU 1.34(p=0.2) (d) Correlation of mean
relative change in ADC for each mouse from baseline to treatment day 3 versus subsequent Ln(tumor
growth rate), red = radiation, black = no radiation, green outline = sunitinib
(d)
65
Urine biomarkers
Preliminary studies of serial urine samples using a commercially available antibody-based array
demonstrated differential changes over time in the sunitinib arms compared with the non-
sunitinib arms, suggesting that oral delivery of sunitinib in our murine experiment resulted in
systemic delivery and effect. Several markers appeared to show response to sunitinib including
decreased angiogenic markers, VEGF, Angiopoietin-1 and Tissue Factor-III, and increased
invasive markers, MMP-9 and TIMP-1. Rise in VEGF and EG-VEGF were noted following
SURT. [Figure 4.9]
Figure 4.9 Summary of relative changes in candidate urine biomarkers from baseline to
treatment day 4 for placebo, sunitinib monotherapy (SU) and sunitinib + radiation (SURT)
arms. From the panel of biomarkers measured, this figure summarizes the candidate
biomarkers that showed notable changes with treatment. The radiation monotherapy arm
could not be fully analyzed due to limited sample volume.
66
DISCUSSION
Serial MRI served multiple roles in this study evaluating the effects of anti-angiogenic agent and
radiation in an intracranial murine model of U87 glioma. Baseline MRI enabled exclusion of
mice without visible tumor at baseline and stratification of mice to treatment arms. It also guided
more conformal radiation delivery to the tumor using a smaller collimator in order to minimize
radiation dose to the surrounding normal tissues. [Figure 4.3] Using a novel image-guided
radiation delivery technique that largely spares the contralateral brain from radiation dose
enabled similar regions of non-irradiated contralateral brain to be used as internal controls for
MRI measures. Finally, serial multiparametric MRI allowed a single non-invasive imaging
modality to interrogate changes in tumor size, as well as other parameters reflecting tumor
perfusion and water diffusion. This is particularly useful in studies investigating anti-angiogenic
agents, as these can cause vascular responses prior to or independent of tumor volume changes,
and the earliest imaging biomarkers of response will likely be measures of functional change
rather than volume change. [105, 111]
In our study, changes in tumor vascular physiology in mice treated with SU and combined
SU+RT were assessed by longitudinal changes in DCE-MRI measures. Consistent with existing
literature, we observed early and sustained decreases in Ktrans during SU treatment at least from
treatment day 3 to 10 after which the Ktrans appeared to return back to baseline after stopping
sunitinib.[193] A novel finding in our study was that Ktrans remained decreased in the combined
SU+RT arm even after SU was stopped, supporting the hypothesis that permanent vascular
changes may result from combined AA and RT treatment.[Figure 4.7(a)][50] Although
measurable reductions in Ktrans were observed following SU, with or without RT, in our study
iAUC60 response was isolated to the SU+RT arm. In this arm, a reduction in iAUC60 was
observed at treatment day 3 and iAUC60 remained reduced throughout the duration of SU
treatment. [Figure 4.6(a)] This early drop in iAUC60 at day 3 was isolated to the SU+RT arm
again when the same experiment was repeated. However, iAUC60 responses have generally
been variable following anti-angiogenic therapy, likely reflecting the complexity of the multiple
parameters that can affect iAUC60 including blood flow, vascular permeability and fraction of
interstitial space, and arterial input function. [102, 111, 194, 195] Therefore although a
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reproducible drop in iAUC60 isolated to the combined therapy arm was observed, the underlying
mechanism for this is yet unclear.
The results of Modified Tofts analysis supported previous findings that emphasized the need for
fastidious acquisition and application of individual AIF and T1 data, as reductions in Ktrans of
76.8 % for SU arm (p=0.02) and 73.3% for RT+SU (p=0.03) were only significant at treatment
day 3 when individual mouse T1 and AIF data were applied for all mice. When population T1
values were applied, the reduction in Ktrans was no longer statistically significant.[Figure 4.7(e)]
Previous pre-clinical studies support the use of individually measured tissue T1 values [105] and
individual AIF measures for Modified Tofts analysis, with one study demonstrating that the use
of population mean AIF and individual AIF values in Modified Tofts analysis can result in up to
a 35% difference in the resulting mean Ktrans for the same ROI. [120] The large variability in
AIF between mice demonstrated in Figure 4.5(b) further suggests that a population mean AIF
would likely be a poor representation of the individual AIF in most mice and may in turn affect
the parameters, including Ktrans and Kep, derived from Modified Tofts modeling. Therefore, our
findings reinforce the need for fastidious acquisition and application of individual mouse T1 and
AIF values in the Modified Tofts model for the purpose of DCE analysis and demonstrate the
feasibility to achieve this. Using this approach, our study demonstrated that sunitinib, with or
without radiation, results in a decrease in Ktrans as early as treatment day 3 with maintained
reduction in Ktrans throughout sunitinib treatment, at least until day 7. The effect sizes of these
decreases in Ktrans were on the order that they likely represent true biological effect. However, it
would be prudent to obtain the variance in the MRI data to establish a confidence level beyond
which the measured response can be attributed to biological effect as opposed to noise. This is
typically done by repeating the specific measure in the same animal at different time points to
determine the coefficient of variation, but for DCE-MRI in mice repeated measures over a short
period of time were not feasible due to limited tolerance to gadolinium administration and tail
vein access. Future studies to evaluate the duration of Ktrans reduction with prolonged sunitinib
treatment, with and without radiation, would characterize the duration of the vascular changes.
Furthermore, the timing of radiation treatment relative to a measured decrease in Ktrans following
initial sunitinib treatment may result in differing outcomes and warrants further investigation.
Rises in ADC may be sensitive measures of response to cytotoxic therapy, consistent with
reduced cellularity, increased membrane permeability and extracellular water content following
68
cytotoxic therapy, such as radiation.[142, 157] In our study, the two RT arms had a greater rate
and magnitude of rise in ADC following treatment compared with the non-RT arms, which
supports the expectation that RT would reduce tumor cellularity, increase membrane
permeability and increase extracellular water content. However, ADC gradually rose over time
for all arms, even the control arm. Possible mechanisms for this rise in ADC with tumor growth
in the control arm include release of angiogenic factors such as VEGF, which can contribute to
increased vascular permeability, rising proportion of dysfunctional vessels through angiogenesis
and vasculogenesis as well as possible central areas of tumor necrosis as the tumors grow to
larger volumes. A significant difference in ADC response was detected as early as treatment day
3 and the magnitude of ADC response at this early time point was highly correlated with
subsequent tumor growth rate in individual mice, despite variability within each treatment
group.[Figure 6d] This correlation was also observed by Larocque et al. following escalating
single dose radiation treatment to subcutaneous GBM xenografts in nude mice, suggesting that
ADC response is a relatively robust measure of response, independent of tumor model and
treatment modality.[187] The ability to measure a biomarker of response at an early time point,
like treatment day 3, introduces the possibility of adapting therapy in a time sensitive manner.
For instance, this early change in ADC that predicts eventual tumor growth may be used to select
tumors that require combination treatment or radiation dose-escalation.
A major strength of this study is that the perfusion and diffusion biomarker changes were
successfully reproduced when the experiment was repeated. Additional strengths of this study
reflect the use of serial MRI acquisitions to overcome assumptions often made in pre-clinical
studies. Baseline MRI confirmed that gross tumor was present in all mice prior to starting
treatment and thereby ensured that differences in overall survival between arms were more
reflective of gross tumor response to each treatment. This baseline MRI also acknowledged the
heterogeneity in tumor location and was used to ensure local radiation treatment delivery.
Finally, the acquisition of serial MRI measures from each individual mouse allowed for
longitudinal changes in each individual tumor to be measured and compared over time.
The limitations to this study are largely based on the technical challenges of serial
multiparametric MRI using an intracranial tumor model in mice. This includes the challenges of
accurately and reproducibly defining ROIs for analysis and acquiring some of these MRI
perfusion and diffusion measures in small volume tumors, particularly at the early time points.
69
There was some loss of useful data for image analysis, such as AIF and T1 values for each
mouse at each time point. Also, tumor vasculature and physiology in human xenograft tumors
in mice may differ from human brain tumors therefore further investigation is required prior to
translating these biomarkers into clinical practice.
Future Directions
Based on the findings of this study, further pre-clinical and clinical research is planned and
ongoing. We are working to establish biological correlation between the identified promising
imaging biomarker changes, candidate biofluid biomarkers and tumor pathology. This will
include histological evaluation of microvessel density with CD31 staining to correlate with Ktrans
measures, proliferation of tumor cells and endothelial cells with bromodeoxyuridine (BUdR) and
apoptosis with TUNEL to correlate with ADC. Further pre-clinical work aims to utilize the
promising early imaging biomarkers, Ktrans and ADC, in order to guide optimal scheduling of
combining radiation and anti-angiogenic agents. For example, one hypothesis is that employing
radiation when the Ktrans response is greatest in magnitude will maximize the benefit of
combined therapy. More intensive imaging around the promising early day 3 time point will
help identify when Ktrans response is greatest after starting anti-angiogenic therapy. Furthermore,
intensive imaging during sunitinib treatment would help determine the duration of Ktrans
response, which may facilitate delivery of fractionated radiotherapy during this period of time.
Finally, an ongoing clinical study is evaluating the effects of combined sunitinib and single
fraction radiation treatment using conventional response measures along with the identified
diffusion and perfusion imaging biomarkers.
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4.4 CONCLUSIONS
Our study demonstrates the role of image-guidance in designing a mouse model experiment that
allows for meaningful translation of the experimental findings to the clinical setting. It
demonstrated the need and feasibility of baseline imaging to select mice with confirmed tumors
and stratify mice to treatment arms according to baseline tumor size in order for judicious
experimentation with intracranial tumor models. The benefit of using MRI as the imaging
modality is the ability to acquire multiparametric information about tumor presence, size, and
physiology. Several promising early biomarkers of response were determined as early as
treatment day 3. The most notable biomarkers warranting further investigation include a decrease
in Ktrans in perfusion images following sunitinib treatment, with or without radiation, and a rise in
ADC in diffusion imaging following radiotherapy.
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Chapter 5 Towards Individualized Image-Guided Spatio-Temporal Delivery
of Combined Cancer Therapeutics
5 General Discussion
5.1 Tumor Model and Experimental Design
Careful pre-clinical experimental design is paramount to meaningful interpretation and
successful clinical translation. This is particularly true for studies investigating potential imaging
response biomarkers that involve a complex interaction and interdependence of the specific
tumor model and imaging protocol used. This study demonstrated the strengths of first
developing a tumor model in conjunction with the MRI protocol that is catered to the particular
experimental aims. For the purpose of an experiment evaluating the effects of radiation and
sunitinib and identifying promising early imaging response biomarkers, it was critical for the
tumor model and MRI protocol to allow longitudinal follow-up of imaging measures of tumor
response to radiation and anti-angiogenic therapy.
In this study, MRI served a number of roles. The baseline MRI was used to screen and select
mice with appropriate intracranial tumors for use in experiments. As the rate of successful tumor
formation and rate of tumor growth varies with the number of cells injected and particular
species or even strain of animal used, the timing of baseline MRI needed to be established for the
particular model being examined.[166, 196] Preliminary experiments helped establish that
successful tumor formation was achieved in 90% of mice, which is within the range of reported
glioma tumor development following intracranial tumor cell injection.[196] These preliminary
experiments also determined that by day 7 following IC-injection, the majority of mice that
would eventually develop intracranial tumors would have visible tumors on MRI and the volume
of these tumors would be amenable to meaningful MRI biomarker measurement on DCE and
DWI. Using day 7 baseline MRI, we correctly excluded 5 of 57 (9%) mice that failed to develop
tumor after IC injection, as all these mice lacking visible tumor on baseline MRI screening
remained well until the end of the experiment.
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Frequent serial MRI in our study also demonstrated variability in tumor development and growth
in individual mice despite the application of identical tumor inoculation protocol in each mouse.
[Figure 4.3(a)] Stratifying mice by tumor size or selecting mice with similar tumor size is
commonly practiced in experiments using subcutaneous tumor models.[50, 179, 197] The
findings from our study support the benefit of a similar approach to be taken in experiments
using intracranial tumor models. Rather than selecting out tumors that are all of uniform size,
stratifying for tumor size between arms is more efficient use of experimental resources and
keeping a range of tumor sizes per treatment arm may better approximate the setting of clinical
investigations because most clinical trials have heterogeneity in baseline tumor characteristics
within a treatment arm. Despite heterogeneity in baseline tumor sizes within the control arm, the
majority of mice died within a narrow window of time between days 24 and 27 days following
intracranial injection, reflecting fairly uniform tumor impact on mouse survival. The survival of
mice in the radiation arm was also fairly uniform, reflected in the steep drop off in the survival.
In contrast, the two sunitinib arms had more gradual stepwise declines in their survival curves,
possibly reflecting greater heterogeneity in response to sunitinib compared with response to
radiation. [Figure 4.4(a)]
A limitation of the U87 orthotopic model is that tumor vasculature and physiology in human
xenograft tumors in mice likely differ from primary human brain tumors. With this in mind, the
ideal tumor model would be a spontaneous model in which the tumor grows as a localized mass.
With the absence of such a tumor model at the present time and given that the intended
experiment with this model required a defined treatment volume for radiation delivery; we chose
the intracranial xenograft model which offers predictable tumor growth at the location of the IC
injection.
5.2 Treatment Delivery
SPATIAL
The incorporation of image-guidance has greatly improved the spatial delivery of radiation
therapy. However, the use of image-guidance for irradiation experiments in small animals is
very limited. Existing literature supports that image-guidance enables better targeting of the
73
tumor or regions of interest and thereby allows for more conformal radiation delivery techniques
that can spare the surrounding normal structures.[198] This study demonstrates that when the
isocentre of a 5mm collimator was placed by visual estimation of the tumor location on cone-
beam CT using the information from baseline MRI, the tumor was adequately covered by at least
90% of the intended radiation dose, but often the tumor was barely covered by the 90% isodose
line.[Figure 4.3(b)] This was a result of the error introduced by visually estimating the location
of the isocentre on the cone-beam CT, using information from the baseline MRI. With the
application of fusion of the baseline MRI to the cone-beam CT at the time of radiation planning
and delivery, this error in placing the isocentre at the centre of the tumor would be minimized
and thereby would ensure tumor coverage with the intended radiation dose. In turn, this would
facilitate the use of even more conformal radiation approaches that spare more of the
surrounding normal brain tissue and more closely simulate clinical radiation delivery to brain
tumors. Even with the radiation delivery technique that was used in this study, the dose of
radiation to the contralateral brain was minimal and thereby enabled comparison of specific MRI
measures between tumor tissue and non-irradiated contralateral brain, as the internal control at
each time point.
TEMPORAL
MR imaging can also guide the temporal delivery of both systemic and radiation treatment.
Temporal delivery can be defined in a number ways: optimal time to start treatment, duration of
treatment, order and timing of each treatment in combination therapy. Imaging can be used to
guide the start of treatment in an animal model experiment so that it reflects the intended
therapeutic application of new agents or treatments. As the aim of this study was to evaluate the
effects of sunitinib and radiation in gross tumor, we used MRI to confirm that mice had visible
tumors at baseline, prior to starting treatment. The more challenging aspects of temporal
treatment delivery involves the optimal duration, order and timing of each treatment in
monotherapy or combined therapy. The biomarkers identified in this study that reflect
physiological responses to therapy may help guide each of these facets of temporal treatment
delivery. For example, if the hypothesis is that a drop in Ktrans reflects changes in the tumor
microenvironment that will improve radiation effect, delivering radiation at day 3 of sunitinib
when Ktrans significantly dropped may improve tumor control better that delivering concurrent
sunitinib and radiation at treatment day 1.
74
Although we were able to demonstrate significant differences in Ktrans response between
treatment groups, there was variability in individual Ktrans responses. For example although we
observed a drop in Ktrans at day 3 of sunitinib treatment for both groups of mice receiving
sunitinib, when individual mouse responses are evaluated, two mice did not show a drop in Ktrans
until day 7 treatment and some mice may have demonstrated a response sooner than treatment
day 3. Some of this variability may have been a result of underlying variance in the MRI data
due to noise. In order to evaluate the contribution of noise, repeated measures from the same
mouse at different time points would be useful. Although this is commonly done for clinical
trials, repeated DCE-MRI acquisition multiple times a day in mice faces the difficulty of
administering repeated doses of gadolinium and repeated access to the tail vein. One possible
approach to estimating the variance in DCE-MRI data may be to measure the parameters in
different mice with tumors that are the same size, although this would not account for differences
in individual mouse physiology. Another approach for accounting for variance in the AIF and T1
data would be to compare these measures in each mouse at 2 time points, such as baseline and
day 3.
Recognizing the heterogeneity in Ktrans response amongst mice, a potential future step towards
individualized treatment of radiation and sunitinib may be to use individual mouse Ktrans
responses to guide the timing of each treatment. An initial study to help direct this approach
would involve a closer evaluation of the MRI responses at the early time points around treatment
day 3 with greater frequency and with a larger number of mice to evaluate the optimal timing of
these promising early imaging biomarkers, to assess the individual variability in these measures
and to acquire pathological correlation.
ADAPTIVE
Despite variability within each treatment group with regards to individual ADC responses and
tumor growth rate, we found a strong negative correlation between ADC response at treatment
day 3 and subsequent tumor growth rate in individual mice regardless of the specific treatment
they had received. [Figure 4.8(d)] These findings that day 3 ADC response predicts subsequent
tumor growth rate raises the potential to use individual mouse ADC response at day 3 to guide
further therapy. For example, a future experiment could evaluate the effect of delivering
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additional radiation treatment(s) in mice with low ADC response after their first treatment of
radiation.
5.3 Response Evaluation
5.3.1 Imaging
Various imaging techniques have been used to confirm tumor presence and measure tumor size
and growth. For example, by injecting firefly luciferase transfected U87MG human
glioblastoma cells (U87MG-fLuc) intracranially, tumor growth can be tracked by serial
bioluminescence measurements.[199] A strong correlation between bioluminescence measures
and MRI measures of tumor volume has been reported using these techniques. [199, 200]
Specific molecular targets associated with angiogenesis can be interrogated by using molecular
imaging techniques such as PET with specific tracers that probe VEGF, VEGF receptor and
hypoxic cells. [199, 201-204] However, these techniques are generally limited to either
measuring relative tumor size changes or measuring changes in specific molecular targets, rather
than both measures. Furthermore, although these imaging techniques bring forth useful
measures for pre-clinical tumor evaluation, they are less relevant than MRI in this study that
aims to identify imaging markers that can be translated to the clinical setting.
In contrast, MRI is a single imaging modality that can confirm tumor presence, measure tumor
size, evaluate tumor morphology and distribution within the brain, as well as evaluate tumor
physiology such as vasculature, cell density and edema. This is particularly helpful in studies
evaluating the effects of anti-angiogenic agents, as these agents often result in vascular responses
and measurable changes in peri-tumoral edema prior to or independent of tumor volume changes.
Furthermore, it is likely that the earliest imaging biomarkers of response will be measures of
functional changes in the tumor that precede volume changes.
There are several limitations and technical challenges of the serial multiparametric MRI
measures in this study. A number of factors contributing to discrepancies between the
measurement of tumor size using MRI and histological tumor size have been raised. These
include partial volume effects, excessive contrast leakage into surrounding non-tumor tissues due
to vascular leakiness or distortion in the histological specimens during tissue processing.[205,
76
206] Furthermore, almost all clinical trials measure tumor volume as the gadolinium-enhancing
component, which raises additional issues. Contrast-enhancement reflects vascular permeability
rather than tumor but increased vascular permeability is neither specific to tumor tissue nor is it
always present in tumor tissue. Treatments such as radiation can also increase vascular
permeability and affect the volume of contrast-enhancement. Additionally, the amount of
gadolinium enhancement can be affected by the technique of contrast injection and MRI
acquisition. Despite these factors, more recent studies have demonstrated that good correlation
between MRI and histological tumor volumes can be achieved. [182, 206] Although the factors
described above may introduce random or systematic errors in our measures, the impact of
systematic errors on the interpretation of our findings is small, given that our volume
measurements were taken serially with a focus on comparing relative differences in volume
change over time rather than the absolute volume measurements.
Due to the small size of the tumors, analysis of both MRI perfusion and diffusion data were
completed using a region of interest (ROI) rather than voxel-by-voxel analysis, as the tumor
volumes being followed for biomarker changes were as small as 0.16 mm3 using spatial
resolution of 250 x 250 x 500µm voxels for the perfusion and diffusion acquisitions, equating to
voxel volumes of 0.03 mm3. Functional diffusion map (fDM) analysis based on voxel-by-voxel
scatter plots of the registered pre- and post-therapy MR measures has been shown to be a
promising early biomarker for determining therapy response in brain tumor patients.[148] A
major advantage of voxel-by-voxel analysis is that it eliminates the uncertainty and bias
introduced by delineation of an ROI. However, the ability to do accurate voxel-by-voxel
analysis depends on the ability to track a voxel over time. This becomes increasingly difficult in
situations where tumor volumes change dramatically between imaging sessions.
In our experimental data analysis, the ROI was defined manually as the enhancing tumor on the
T1-gad image, which was then transposed to the DCE and DWI image sets, as all image sets
were matched in slice prescription and spatial resolution. Reports have demonstrated that
manual or automated segmentation techniques, which delineate tumor margins based on signal
intensity differences in signal intensity from surrounding brain, provide robust volume
determination. However there can be interobserver and intraobserver bias with manual
segmentation that can be eliminated with an automated technique.[97] One limitation of using
an ROI analysis compared with voxel-by-voxel analysis is that the error and potential bias
77
introduced with the delineation of an ROI can impact the measures of the DCE-MRI and ADC
analysis, which can then influence the findings and interpretation of the study results. In order to
minimize the bias and error in ROI delineation, automated segmentation is favoured and we have
worked towards using this approach for future studies. Conversely, ROI analysis has benefits in
that the ROI approach typically has a signal to noise advantage and for serial measurements of
perfusion and diffusion over time, the challenges associated with voxel tracking over time can be
avoided. Because these tumors were small particularly at the start of the experiment, histogram
analysis of the ROI did not provide any additional useful information about the DCE or ADC
measures within the ROI. Similarly the small tumor volumes favoured ROI-based analysis using
mean values over using voxel-by-voxel analysis, as some of these tumors had baseline volumes
of 0.16 mm3, thereby encompassing as few as 4-5 voxels.
5.3.1.1 DCE
Pre-clinically, studies have demonstrated a strong correlation between DCE measures of vessel
permeability and histological quantification of vessel caliber and density in an orthotopic murine
model of glioma.[207] Recent pre-clinical studies evaluating anti-VEGF tyrosine kinase
inhibitors, including cediranib and sunitinib, have demonstrated post-treatment reductions in
Ktrans and iAUC60.[105, 111] Our study demonstrated a significant decrease in iAUC60 and
Ktrans following combined sunitinib and radiation treatment whereas sunitinib monotherapy
resulted in a significant drop in Ktrans but not in iAUC60. The complexity of factors contributing
to the iAUC60 measure makes interpretation of this value challenging. It can be correlated with
Ktrans in specific circumstances but overall it cannot be used as a surrogate for Ktrans, as
demonstrated by our findings. As iAUC60 is a measure of the amount of contrast agent
delivered to and retained by the tumor in 60 seconds, it is only a summary measurement of the
concentration of contrast agent as a function of time. It does not reflect specific physiological
mechanisms that mediate the contrast agent, unlike Ktrans. However, the benefit of IAUC60 is
that it does not require perfusion modeling, is more easily measured and has the advantage of
good signal-to-noise characteristic.[102]
In our study, durable Ktrans response was observed in both sunitinib arms during sunitinib
treatment with maintained decrease Ktrans at treatment day 7. Once sunitinib was stopped, Ktrans
returned to baseline values in the sunitinib monotherapy arm, consistent with previous
78
studies.[208] However, the Ktrans response was maintained in the combination arm even after
sunitinib was stopped suggesting that combined sunitinib and radiation resulted in a durable
change in vascular physiology. The underlying mechanism of this persistent response to
combination treatment warrants further investigation.
This study demonstrates the importance of judicious acquisition of the parameters T1 and AIF
for each mouse for application in the Modified Tofts model perfusion analysis. Firstly, wide
variability in AIF between mice were observed in our study and therefore we included only mice
with individual AIF data for Modified Tofts analysis.[Figure 4.4(b)] Although notable decreases
in Ktrans from baseline were observed in both sunitinib arms by treatment day 3, the magnitude of
decrease in Ktrans was significant only for the combined sunitinib and radiation arm when
individual AIF and population mean T1 values were applied for Modified Tofts analysis.[Figure
When individual T1 and AIF values were applied in the Modified Tofts analysis for every mouse
at baseline and day 3, a significant decrease in Ktrans was noted for both arms treated with
sunitinib with a 76.8 % decrease for sunitinib alone (p=0.02) and 73.3% decrease for sunitinib
and radiation (p=0.03), [Figure 4.7(e)] emphasizing that these kinetic parameters are very
sensitive to the parameters applied in the model. Previous studies have acknowledged the
importance of applying individually measured T1 or AIF values for DCE analysis. For example,
a recent study directly comparing the use of population mean AIF and individual AIF values in
Modified Tofts analysis demonstrated a 35.8% difference in the mean Ktrans for the region of
interest that resulted by inputting these two AIF values in the Modified Tofts analysis. [120]
Bradley et al. emphasized the application of individual tissue T1 values for Tofts and Kermode
perfusion analysis to generate Ktrans values, while using the vascular input function parameters
derived from mean values of weight-matched control animals in this study.[105] Our study
demonstrated the feasibility and value of acquiring and applying individual mouse T1 and AIF
values in the Modified Tofts analysis for the purpose of prudent DCE analysis.
DCE-MRI measures have also been used to evaluate response to radiation monotherapy. Short-
term rises in Ktrans have been reported following radiation therapy to normal brain and brain
tumors. Our study demonstrated this early rise in iAUC60 and Ktrans by day 3, which may reflect
further breakdown of the blood brain barrier with ionizing radiation exposure. [Figures 4.6(a),
4.7(a)] These findings are consistent with previous studies of acute radiation injury to brain
vascularity. [4] These studies demonstrated long-term decreases in Ktrans after the short-term
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rise in Ktrans following radiation monotherapy. An acute rise in iAUC60 and Ktrans were observed
in this study by day 3 with a subsequent fall in both values by day 7. The possible mechanism
for this temporary acute rise in iAUC60 and Ktrans is a combination of inflammatory reaction,
acute endothelial cell apoptosis, and increased expression of pro-angiogenic cytokines in
response to radiation that result in a temporary increase in vascular permeability. The
subsequent fall in both values may reflect the resulting reduction in microvasculature from the
loss of endothelial cells, consistent with previous reports of decreased microvessel density and
microvascular perfusion following radiotherapy.[114]
5.3.1.2 DWI
Using diffusion MRI, increased water diffusion in tumors following cytotoxic therapy has been
observed, likely due to decreased tumor cell size and density and increased extracellular water
content and membrane permeability with cellular death from cytotoxic therapy.[143, 157] In our
study, tumor ADC was greater in the tumor compared with contralateral normal brain at baseline,
which reflects increased water mobility in the disorganized tumor tissue. Over time, a gradual
rise in tumor ADC was noted in all four arms, including the placebo control arm, [Figure 4.8(a)]
which may at least in part to increased edema and necrosis as the tumors grows. In contrast, the
ADC values of the corresponding areas of contralateral brain remained stable over time.
Although ADC increased in all four arms over time, the ADC response was significantly greater
in the radiation arms vs. the non-radiation arms, which likely reflects the cytotoxic effect of
radiation therapy as opposed to sunitinib or placebo.
Early ADC responses have been reported as soon as 2 days after single fraction radiation
treatment.[187] Our findings also demonstrate ADC changes at this early time point. ADC
response, quantified as the ratio of ADC at day 3 over ADC at day 0, was greater in the two RT
arms compared with the non-RT arms, and this finding was reproducible with repetition of the
experiment. [Figure 4.8(c)] When the magnitude of the relative change in ADC from baseline to
day 3 was plotted against the tumor growth on a logarithmic scale for each mouse in the first
experiment, there was a high negative correlation demonstrated between the ADC response and
Ln(tumor growth rate) with a Pearson correlation coefficient of -0.878 (p=0.002). [Figure 4.8(d)]
This finding has previously been reported by Larocque et al. after treatment with escalating
doses of radiation.[187] This negative correlation is consistent with the hypothesis that a greater
80
rise in ADC is associated with greater reduction in cellularity and increased cellular apoptosis,
which in turn would likely improve tumor control and slow down subsequent tumor growth rate.
Although differences in early ADC response were measurable by treatment day 3, the differences
in ADC responses between treatment arms became even more prominent at later time points.
The advantage of early detection of ADC response is the potential to adapt therapy in a time
sensitive manner. For example, additional therapy may be planned if a poor ADC response is
observed, thereby implicating the likelihood of quicker eventual tumor growth.
5.3.2 Biofluid
Serial evaluation of urine biomarkers were used to investigate the systemic effect of sunitinib
following oral delivery of sunitinib in our murine experiment. Due to the limited volume of
urine that could be collected in each mouse at each time point, the urine was pooled for each
treatment group for analysis using a multiplex antibody array that would measure relative levels
of 55 angiogenesis-related proteins. There were specific markers that appeared to change
differentially in the sunitinib arms compared with the non-sunitinib arms. This exploratory
analysis identified several promising response biomarkers that warrant further investigation. The
reductions in the pro-angiogenic markers, Tissue Factor-III (TF) and VEGF, following sunitinib
therapy suggested systemic delivery and effect of oral sunitinib administration in our mice, as
these markers have also been observed in response to other anti-angiogenic therapy in previous
studies. [209] In addition to angiogenic markers, the urine assay demonstrated elevations in the
invasive markers, MMP-9 and TIMP-1, following sunitinib therapy. Concern has been raised
that anti-angiogenic therapy may increase tumor invasiveness and metastatic potential and our
preliminary findings of increased invasive markers following sunitinib treatment are worrisome
and warrant further investigation. [210]
Further biological correlation of the imaging biomarkers was pursued with tumor pathology. In
the initial experiment, mice were followed for survival measures and therefore the tumors were
only evaluated pathologically after the mice were sacrificed due to tumor progression. Therefore
the pathological changes seen in these tumors represented tumor progression after treatment
rather than changes associated with tumor response. The experiment was repeated with all 4
treatment arms treated in the manner as the initial experiment with planned mouse sacrifice
immediately after treatment day 3 imaging to more closely evaluate the changes in Ktrans and
81
ADC at treatment day 3. Tumor histology was planned to evaluate the biological correlation
between the identified imaging biomarkers and changes in tumor pathology. This included
changes in microvessel density and vessel diameter using CD31 staining, vascular permeability
evaluating the extravasation of FITC-lectin out of the vessels and VEGFR2 expression in
comparison with changes in DCE metrics (iAUC60, Ktrans), and changes in tumor cell
proliferation (BUdR) and apoptosis in comparison with changes in ADC and tumor growth
parameters. We sacrificed mice by cardiac perfusion with prior tail vein injection with BUdR
and FITC-lectin and harvested the brains for frozen section. Unfortunately, in the first 2 brains
that were sectioned, we were unable to identify the tumor. Because the tumors were so small at
baseline, it is possible that this tissue was lost during the process of acquiring slices from frozen
sections. Even the smaller tumors were identified on the paraffin embedded sections from the
first experiment, therefore we will aim to use paraffin sections in future experiments.
Furthermore, it may be possible to start treatment after the tumor has grown to a slightly larger
size for baseline measures of MRI and pathological correlation at baseline and at early follow-up
time points.
5.4 Future Directions and Translation
Future pre-clinical studies will apply the imaging and biofluid biomarkers that were identified
from this study to investigate the optimal schedule for combining radiation and anti-angiogenic
agents. Given that we observed a drop in Ktrans after sunitinib treatment, this may be a marker of
response to this agent and employing radiation during the period of measurable Ktrans response
may maximize the benefit of combined therapy. In our study, the Ktrans response was observed
as early as day 3 of sunitinib treatment in the cohort of mice treated with sunitinib, and therefore
response to delivery of radiation at day 1 of sunitinib vs. day 3, after Ktrans has dropped, may
demonstrate difference in tumor control. As we have observed heterogeneity within each group,
it would be valuable to investigate the sources of this heterogeneity with further measures of
variance in the MRI data, pathological correlation for individual mice to improve our
understanding of these MRI changes, and to ultimately work towards individualizing the
temporal delivery of radiation based on individual MRI responses. Furthermore, based on our
observation of a sustained decrease in Ktrans throughout the duration of sunitinib, fractionated
82
radiation delivery during the period of decreased Ktrans may provide added benefit. Finally,
although sunitinib was given for 7 treatment days, previous studies have demonstrated improved
tumor control in vivo and improved clonogenic survival outcomes with adjuvant sunitinib after
radiation and this may hold true with adjuvant sunitinib following combined sunitinib and
radiation treatment.[62, 89] Serial multiparametric MRI would enable longitudinal monitoring
during the adjuvant sunitinib treatment and potentially help identify the optimal duration of
sunitinib treatment.
Translation of these promising imaging and biofluid biomarkers into clinical studies is ongoing.
These biomarkers are being investigated in patients with brain metastases enrolled in a phase I
dose escalation study of sunitinib combined with single fraction radiation treatment in the form
of radiosurgery. [Appendix 1] These biomarkers are also being investigated in patients receiving
radiotherapy alone, both radiosurgery and fractionated radiotherapy, for brain
metastases.[Appendix 2] In this way, we will gather information to determine whether similar
early changes in Ktrans, iAUC60 and ADC are measurable in human tumors, and whether they
provide valuable clinically-relevant information on which to base treatment decisions.
5.5 Conclusions
With the incorporation of targeted therapies such as anti-angiogenic agents into the management
of brain tumors and the move towards individualized therapy, there is a growing demand for
non-invasive early biomarkers that can predict response to therapies. Pre-clinical tumor models
are important tools that can facilitate preliminary exploration of potential therapeutics and their
associated potential biomarkers. This study demonstrates how synchronized development of an
intracranial tumor model and MRI protocol can facilitate a longitudinal pre-clinical study to
explore promising imaging biomarker measures in response to anti-angiogenic and radiation
therapy. The most notable biomarkers warranting further investigation include a decrease in
Ktrans in DCE-MRI following sunitinib treatment and a rise in ADC in DWI following
radiotherapy. These promising biomarkers need further validation as surrogate markers, but they
introduce the promise of using early response biomarker to guide individualized spatio-temporal
delivery of combined therapy with anti-angiogenic and radiation therapy to optimize the
therapeutic ratio.
83
84
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Appendices
APPENDIX I: A Phase I Study of Stereotactic Radiosurgery Concurrent with Sunitinib in Patients with Brain Metastases Coordinating Center: Princess Margaret Hospital (PMH) Principal Investigators: Dr. Cynthia Ménard
Princess Margaret Hospital Department of Radiation Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected] Dr. Anthony Brade Princess Margaret Hospital Department of Radiation Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected]
Co-Investigators: Dr. Warren Mason
Princess Margaret Hospital Department of Medical Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected] Dr. Gelareh Zadeh Toronto Western Hospital Department of Neurosurgery 399 Bathurst Street, Toronto, Ontario, CANADA M5T 2S8 Email: [email protected]
Study Fellow: Dr. Caroline Chung
Princess Margaret Hospital Department of Radiation Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected]
Research Coordinator: TBD Contracts Coordinator: Linda Purushuttam (Administrative Coordinator, RMP
Clinical Research Program) Tel: (416) 946-4501 ext. 3975 Fax: (416) 946-2828
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Collaborators: UHN Radiosurgery Program – Neurosurgery Dr. Mark Bernstein Dr. Mogdan Hodaie Dr. Michael Schwartz Dr. Michael Cusimano Dr. Fred Gentili Dr. Eugene Yu
UHN Radiosurgery Program – Radiation Oncology Dr. Normand Laperriere Dr. David Payne Dr. Arjun Sahgal Dr. Barbara-Ann Millar
NIH-NCI – Radiation Oncology Branch Dr. Kevin Camphausen
UHN PMH Neuroradiology Program Dr. Eric Bartlett
MRI Physics – University of Toronto Dr. Andrea Kassner Dr. Warren Foltz Dr. Andrei Damyanovich Dr. Adrian Crawley
CT Physics – Radiation Physics Dr. Catherine Coolens
Neuropsychology – UHN Dr. Kim Edelstein
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Schema This will be a single-institution, single-arm, open-label, dose escalation phase I trial. Eligible patients will have pathologically confirmed cancer with 1-3 brain metastases amenable to Stereotactic Radiosurgery (SRS). Three dose levels are planned. For the first two dose levels, patients will be treated with Sunitinib administration (25 mg, 37.5mg) for a total of 4 weeks (Day 0-Day 28) in combination with SRS (delivered on Day 7). If full oral dose (37.5 mg) is reached and appears safe to administer, then a third dose level will be opened to extend drug administration to Day 91 (i.e.13 weeks in total). A total of 10 patients will be accrued at the maximum tolerable dose level.
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TABLE OF CONTENTS
Page SCHEMA..................................................................................................................................... iii 1. OBJECTIVES ..........................................................................................................................1 2. BACKGROUND ......................................................................................................................1 3. PATIENT SELECTION .........................................................................................................5 3.1 Eligibility Criteria ..................................................................................................................5 3.2 Exclusion Criteria...................................................................................................................6 3.3 Inclusion of Minorities ...........................................................................................................7 4. REGISTRATION PROCEDURES........................................................................................8 4.1 Procedures for Central Patient Registration........................................................................8 5. TREATMENT PLAN..............................................................................................................8 5.1 Schema.....................................................................................................................................8 5.2 Radiotherapy...........................................................................................................................9 5.3 Sunitinib Treatment .............................................................................................................11 5.4 General Concomitant Medication and Supportive Care Guidelines................................13 5.5 Duration of Treatment .........................................................................................................14 5.6 Monitoring During Treatment and Follow-up...................................................................14 5.7 Compliance with Study Medication ....................................................................................15 6. PATIENT ASSESSMENT ....................................................................................................15 6.1 Toxicity...................................................................................................................................15 6.2 Acute Toxicity of SRS and Sunitinib...................................................................................15 6.3 Dose Limiting Toxicity ........................................................................................................16 6.4 Management of Toxicities ...................................................................................................17 6.5 Dose Reduction/Delays ........................................................................................................17 6.6 Late SRS-related Toxicity ...................................................................................................19 7. SECONDARY ENDPOINTS AND CORRELATIVE STUDIES .....................................19 7.1 Endpoints................................................................................................................................19 7.2 Correlative Studies.................................................................................................................21 7.3 Statistical Methods.................................................................................................................23 8. PHARMACEUTICAL INFORMATION.............................................................................23 9. STUDY CALENDAR .............................................................................................................29 10. DATA REPORTING / REGULATORY CONSIDERATIONS.......................................31 REFERENCES............................................................................................................................39 APPENDICES.............................................................................................................................44APPENDIX A: Performance Status Criteria ..........................................................................................................44 APPENDIX B: Patient Diary .................................................................................................................................45
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1. OBJECTIVES Primary Objective: • Determine the safety and maximum tolerated dose of Sunitinib when combined concurrently with SRS in patients with 1-3 brain metastases Secondary Objectives: • To capture any observed late toxicities that may be attributable to this combined treatment of Sunitinib and SRS. • Determine time to Intracranial Local Progression, and Intracranial Distant Progression • Determine Brain Progression-free Survival • Determine the influence of Sunitinib on the requirement for supportive corticosteroids. • Quantify alterations in tumor perfusion parameters observed with dynamic contrast enhanced MRI (DCE-MRI) and DCE-CT • Quantify normal tissue effects in brain tissue adjacent to metastatic lesions using MRI • Assess serum biomarkers as potential prognostic or predictive factors • To determine the optimal biological dose (OBD) of Sunitinib when combined with radiosurgery for brain metastases • To measure effect of SRS and sunitinib on neuropsychological function 2. BACKGROUND Brain metastases and Stereotactic Radiosurgery: Brain metastases occur in 20% to 40% of all patients with cancer [1], with an incidence 10 times higher than that of primary malignant brain tumors. The reported median survival of patients with brain metastases is only 1-2 months with corticosteroids [2] and 5-7 months with whole brain radiotherapy (WBRT). But with improvements in neuroimaging, brain metastases are being diagnosed more frequently and with a lower burden of disease, such that approximately 50-60% of patients have 1 to 4 brain metastases at diagnosis [3]. In these patients, stereotactic radiosurgery (SRS), a single high dose of radiation delivered with high precision to the target lesion, is being used increasingly as an alternative to surgical resection or as an adjunct to WBRT. The addition of SRS to WBRT has provided improvements in local control and functional autonomy for patients with oligometastatic brain disease, supporting the hypothesis that SRS increases efficacy against tumors resistant to the significantly lower doses used in WBRT [4, 5]. More recently, multiple studies including two randomized control trials, (one published [6] and one in abstract form) [7] have demonstrated that SRS treatment of oligometastasis without WBRT does not significantly impact overall survival or cause of death. This is despite a higher rate of distant brain recurrences and likely reflects effective salvage with WBRT at the time of recurrence or progression. [8-10] Furthermore, the findings from these studies suggest that, for the subset of patients who may have no further brain recurrences, WBRT and its potential long-term neurotoxic effects may be avoided. To help address these questions, there is an ongoing multi-institutional study evaluating SRS with or without WBRT.
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SRS can accomplish destruction of a defined intracranial target through precise targeting of a high dose of radiation with a sharp dose fall off at the target boundaries and minimal damage to surrounding tissue. Brain metastases are well suited for SRS as they are often small, radiographically well-circumscribed, pseudo-spherical tumors that are non-infiltrative, and they are often located at the gray-white junction, where toxicity to critical structures are minimal [11]. SRS toxicity is low (<5%) [6, 9, 11]. Nausea, vomiting, alopecia, and headaches are the most common mild-to-moderate side effects [12]. Toxicity analysis in patients who have survived for at least 1 year after SRS demonstrates that serious post-SRS sequelae (e.g. radionecrosis, extensive edema) developed in ~2.8% of patients at 1 year [13]. The only factor significantly associated with late risks of complications was treatment volume[14]. Hemorrhage remains an extremely rare complication of SRS[13]. Brain Metastases and Angiogenesis: In order for tumor cells to become brain metastases, they must reach the brain vasculature by attaching to the microvessel endothelial cells, extravasate into the brain parenchyma, induce angiogenesis, and proliferate in response to growth factors [15]. The process of angiogenesis involves a complex interplay of pro-angiogenic and anti-angiogenic factors. Vascular endothelial growth factor (VEGF) is the most potent and specific growth factor for endothelial cell activation and neovascularization [16], and regulates many key functions in the angiogenic cascade. The production of VEGF can be disproportionately up-regulated in tumors and is frequently associated with metastasis and poor survival, supporting the importance of VEGF-induced angiogenesis for disease progression [17]. Furthermore metastatic foci in the brain exhibit a high production of VEGF, which is secreted into the extravascular space, binding the VEGF receptor(s) on endothelial cells and activating angiogenesis [18, 19]. In animal models VEGF expression has been shown to be necessary but not sufficient for the production of brain metastases [15]. Targeting endothelial cells with a VEGF receptor specific tyrosine kinase inhibitor (TKI) in these animal models reduced angiogenesis and restricted the growth of the brain metastases [19]. Several recent publications have demonstrated clinical and radiological responses of brain metastases in patients with metastatic renal cell and breast cancer [20-23]. Combination Radiation and Anti-angiogenic Treatment: Sunitinib is a small molecule with potent activity against members of the split-kinase domain family of receptor tyrosine kinases including VEGF receptor 1 and 2, Platelet-Derived Growth Factor (PDGF)-receptors, the stem cell factor receptor c-KIT, and the FLT3 and RET kinases[24]. It has demonstrated clinical benefit in Phase III studies of patients with metastatic renal cell carcinoma [25, 26] and Gastrointestinal Stromal Tumors [27] as well as documented single agent activity in Phase I studies against a number of other solid tumors [28-30]. While preclinical and clinical trials demonstrate tumor regression following single agent treatment, overall response rates in patients treated with monotherapy have so far been modest [31, 32]. However, there is growing interest in combining these agents with additional cytotoxic therapy to increase tumor regression and improve clinical benefit.
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There is compelling evidence to support the combination of Sunitinib [33] and other antiangiogenic agents with radiotherapy at the pre-clinical level [34-49]. Antiangiogenic agents can transiently normalize the structure and function of tumor neovasculature to make oxygen delivery more efficient, thereby alleviating hypoxia and increasing the efficacy of radiotherapy [50-52]. Emerging data has also suggested that one of the key anti-tumor effects of radiation treatment is mediated by activation of the ceramide pathway in endothelial cells, which triggers induction of apoptosis and cell death. This may be a possible mechanism for the synergistic effects seen with anti-angiogenic agents and radiation [53, 54]. This synergistic effect appears particularly true with single large fractions of radiotherapy, as used in SRS [55, 56]. In addition to the synergistic effects of sunitinib with radiation in the tumors that are irradiated, sunitinib may also have distant brain effects. The current standard of care includes WBRT with SRS to reduce the risk of distant brain recurrences after SRS. However, there are concerns about the toxicity of WBRT. As pre-clinical studies have shown that VEGF expression is necessary for the development of brain metastasis and clinical studies have shown response of gross brain metastases to antiangiogenic treatment, sunitinib may impede development of distant brain metastases after SRS, thereby reduce the risk of distant brain recurrences without WBRT [15, 21, 22] Effect of Anti-angiogenic Therapies on Radiation-related Toxicities: Given that both radiation and anti-angiogenic treatment may affect blood vessels in critical normal tissues and tumor, this treatment approach may not be without risk. In the brain, VEGF-A has been demonstrated to have neurotrophic and neuroprotective effects on neuronal and glial cells in culture and in vivo, and can stimulate the proliferation and survival of neural stem cells[57]. Careful, early phase assessment of toxicity is therefore crucial. No human data evaluating radiation combined with Sunitinib or other VEGF tyrosine kinase inhibitors has been published yet. But severe bowel toxicity has been observed in some patients receiving bevacizumab, an anti-VEGF-1 monoclonal antibody and abdominal or pelvic radiation either concurrently or sequentially[58, 59]. In contrast, no reports of unexpected radiation related toxicities have emerged from large phase III studies evaluating the role of bevacizumab in treatment of patients with metastatic lung or breast cancer, many of whom previously or subsequently received radiation treatment[60]. The above data suggest that the interaction of radiation and anti-angiogenic therapy may be organ specific. There are ongoing phase I studies of combined sorafenib and radiation in the thorax, abdomen and pelvis. Careful, prospective evaluation of toxicity for combination treatment is prudent and necessary in the brain. Although some studies suggest a potential increase in risk of toxicity with the combination of anti-VEGF therapy and radiation, bevacizumab, an anti-VEGF monoclonal antibody, alone and in combination with other agents, has shown reduction in radiation necrosis with decreased capillary leakage and associated brain edema [61]. As tumor necrosis and exacerbation of vasogenic edema are adverse effects of SRS, and VEGF levels correlate with peritumoral edema after SRS [62], the possible anti-edema effects of VEGF inhibitors such as Sunitinib may allow better clinical tolerance to radiotherapy. Trial Rationale • Brain metastases are a common and clinically important problem for patients with
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cancer • SRS improves outcome when used in the initial management of patients with 1-4 brain metastases. • Control of single, small lesions with SRS is good but less favourable results are obtained for patients with larger or multiple lesions emphasizing the need for innovative strategies to improve outcomes. • Preclinical and clinical data suggests that targeting the VEGF axis may provide therapeutic benefit for patients with brain metastases, potentially reducing the risk of distant brain recurrences after SRS alone. • Preclinical and clinical data suggest that endothelial cells are a critical target for radiation therapy and that the anti-endothelial effects of Sunitinib may be of even greater importance in mediating response to high dose per fraction radiation (i.e. SRS) • There is extensive preclinical and early clinical data suggesting that combining anti-VEGF therapy with radiotherapy can improve response and potentially reduce radiation-related toxicity (eg. edema, radionecrosis) • Preliminary clinical data demonstrate that oral Sunitinib 37.5 mg daily is well tolerated and is associated with encouraging anti-tumor activity in patients with a broad range of advanced solid tumors • No clinical data exists evaluating the combination of Sunitinib and radiotherapy in patients with brain metastases • The combination of Sunitinib and SRS has the potential to significantly improve outcome in patients with brain oligometastases 3. PATIENT SELECTION 3.1 Eligibility Criteria 3.1.1 Biopsy proven malignancy (original biopsy is adequate as long as the brain imaging is consistent with brain metastases). 3.1.2 Patients age > 18 years of age, as the effects of Sunitinib at the recommended therapeutic dose are unknown in children. 3.1.3 A contrast-enhanced MRI demonstrating the presence of 1-3 brain metastases performed within two weeks prior to registration. 3.1.4 The dominant contrast-enhancing intraparenchymal brain metastases must be well-circumscribed and must have a maximal diameter of ≤ 4.0 cm in any direction on the enhanced scan. If multiple lesions are present and one lesion is at the maximum diameter, the other(s) must not exceed 3.0cm in maximum diameter. 3.1.5 Life expectancy > 3 months 3.1.6 RPA Class 1 and RPA Class 2 patients with stable primary disease (see Appendix A) 3.1.7 No systemic anti-cancer therapy within 30 days of day 0 of study treatment 3.1.8 Patients must have normal organ and marrow function as defined below:
absolute neutrophil count ≥1.5 x109 /L platelets ≥100 x109 /L hemoglobin ≥80 g/L
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PT-INR/aPTT < 1.5 x upper limit of normal Total bilirubin within normal institutional limits
AST/ALT/GGT ≤5 X institutional upper limit of normal
creatinine <1.5 x ULN OR creatinine clearance > 60 mL/min/1.73 m2
3.1.9 Patients much have left ventricular ejection fraction (LVEF) of at least 55%, based on echocardiogram or MUGA scan 3.1.10 Effects of Sunitinib on the developing human fetus at the recommended therapeutic dose are unknown. Women of child-bearing potential must agree to use adequate contraception (hormonal or barrier method of birth control; abstinence) prior to study entry and for the duration of study participation. Should a woman become pregnant or suspect she is pregnant while participating in this study, she should inform her treating physician immediately. 3.1.11 Ability to understand and the willingness to sign a written informed consent document. 3.2 Exclusion Criteria 3.2.1 Patients with leptomeningeal metastases documented by MRI or CSF evaluation 3.2.2 Evidence of intratumoral or peritumoral hemorrhage deemed significant by the treating physician 3.2.3 Patients with metastases within 5 mm of the optic chiasm or optic nerve 3.2.4 Patients with metastases in the brainstem (midbrain, pons, or medulla). 3.2.5 < 4 weeks since any major surgery. (Previous brain surgery, including craniotomy for tumor resection [except cerebral metastases] or biopsy is permissible.) 3.2.6 Prior resection of cerebral metastasis 3.2.7 Previous cranial radiation. Patients may have had radiation therapy to other anatomical sites, but must have recovered from acute toxic effects prior to registration. At least 2 weeks must have elapsed since last dose of radiation before registration. 3.2.8 Treatment with a non-approved or investigational drug concurrently or within 30 days before Day 0 of study treatment. 3.2.9 Previous treatment with sunitinib or other inhibitors of the VEGF signalling axis. 3.2.10 Bleeding disorders. 3.2.11 Thrombolytic therapy within 4 weeks 3.2.12 Concurrent use of anticoagulant or antiplatelet drugs 3.2.13 Concurrent use of enzyme-inducing anti-epileptic drugs 3.2.14 Patients with any condition that impairs their ability to swallow Sunitinib (e.g. gastrointestinal tract disease resulting in an inability to take oral medication or a requirement for IV alimentation, prior surgical procedures affecting absorption, or active peptic ulcer disease). 3.2.15 Patients with unaddressed esophageal varices or gastrointestinal ulcers that are at significant bleeding risk 3.2.16 Uncontrolled intercurrent illness including, but not limited to, ongoing or active infection or psychiatric illness/social situations that would limit compliance with study requirements. 3.2.17 Patients with poorly controlled hypertension (systolic blood pressure of 150 mmHg or higher, or diastolic blood pressure of 100 mmHg or higher) are ineligible 3.2.18 New York Heart Association (NYHA) Class III or IV disease
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3.2.18.1.1 NYHA class II disease controlled with treatment and documented LVEF of at least 55% are allowed to participate 3.2.19 HIV-positive patients on combination antiretroviral therapy are ineligible because of the potential for pharmacokinetic interactions with Sunitinib. In addition, these patients are at increased risk of lethal infections when treated with marrow-suppressive therapy. Appropriate studies will be undertaken in patients receiving combination antiretroviral therapy when indicated. 3.2.20 Pregnant women. These patients are excluded because there is an unknown but potential risk for adverse events in the fetus. Because there is also an unknown but potential risk for adverse events in nursing infants secondary to treatment of the mother with Sunitinib. Breastfeeding should be discontinued if the mother is treated with Sunitinib. 3.2.21 History of allergic reactions attributed to compounds of similar chemical or biologic composition to Sunitinib. 3.2.22 Individuals with MRI non-compatible metal in the body, or unable to undergo MRI procedures. 3.2.23 Allergy to gadolinium 3.2.24 Allergy to Iodine Contrast Agent 3.2.25 Glomerular Filtration Rate of less than 30ml.min/1.73m2 as measured by creatinine clearance through the Cockcroft-Gault formula [(140-age) X Mass in kg / 72 X plasma creatinine (mg/dl)] 3.2.26 Primary germ cell tumor, small cell carcinoma, or lymphoma 3.3 Inclusion of Minorities This study is designed to include minorities as appropriate. However, the trial is not designed to measure differences in intervention effects. The population of Southern Ontario is ethnically diverse and the proportion of different ethnic groups in the community is provided in the table below. Universal access to health care will ensure that there is no discrimination on the basis of race or gender (Guide to Canadian Human Rights Act: www.chrcccdp. ca/public/guidechra.pdf ). Individual hospital registries and databases do not routinely collect racial data, under the direction of the Canadian Human Rights Code. The population demographics and distribution of minorities in Canada is included in the following table:
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4. REGISTRATION PROCEDURES 4.1 Procedure for Patient Registration • All investigators should call the Research Coordinator to verify study availability for potential patients. • No patient can receive protocol treatment until registration with the Clinical Research Unit (CRU) at the Princess Margaret Hospital (PMH). All eligibility criteria must be met at the time of registration. There will be no exceptions. Any questions should be addressed with the research coordinator principal investigator prior to registration. • The eligibility checklist must be completed, and signed by the investigator prior to registration. • The research coordinator will be responsible for completing the checklist, enrolling patients, patient registration and all data as well as regulatory considerations. • Patient registration will be accepted between the hours of 9 am to 5 pm Monday to Friday, excluding Canadian statutory holidays when the PMH will be closed. 5. TREATMENT PLAN 5.1 Schema This will be a single-institution, single-arm, open-label, dose escalation phase I trial. Eligible patients will have pathologically confirmed cancer with 1-3 brain metastases amenable to SRS. Three dose levels are planned. For the first two dose levels, patients will be treated with Sunitinib administration (25mg and 37.5mg, respectively) for a total of 4 weeks (Day 0-Day 28) in combination with SRS (delivered on Day 7). If full oral dose (37.5 mg) is reached and appears safe to administer, then a third dose level will be opened to extend drug administration to
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Day 91 (i.e.13 weeks in total). For each cohort, two weeks must elapse from the start of treatment of the first patient before patient 2 can start treatment. A decision to proceed with the next dose level will be made when the current cohort of 3 patients (initial or expanded) reaches Day 91 (has completed 13 weeks of therapy +/- follow-up). Each dose level will accrue a minimum of 3 patients. If 1/3 of patients encounter a dose-limiting toxicity (DLT), then a cohort will be expanded to 6 patients. If > 2 of patients encounter a DLT in a given cohort, then that dose level will be declared the maximum administered dose (MAD). Additional patients will be entered into the dose level below the MAD to bring the total treated at that level to 10 (i.e. 7 additional patients if only 3 had been previously entered or 4 if 6 had already been accrued) to increase experience with this treatment regimen. This will be declared the maximum tolerated dose (MTD).
5.2.1 Stereotactic Radiosurgery (SRS) SRS will be delivered using Gamma Knife®- (GK) PFX technology. The Leksell Gamma Knife PFX device contains 192 cobalt-60 sources of approximately 30 curies (1.1 TBq) each, placed in a circular array in a
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heavily shielded assembly. 5.2.1.1 Stereotactic Localization: All patients are fitted with a stereotactic head-frame (Leksell Stereotactic System) for stereotactic localization of brain metastases. Local anaesthesia minimizes patient discomfort during the procedure. 5.2.1.2 Neuroimaging: Patients undergo stereotactic CT and MRI-based imaging. IV Gadolinium is administered as per institutional protocol. Axial MRI and CT images are registered for target delineation. The images, which contain reference points provided by the stereotactic frame, produce the x, y, and z coordinates that form the basis of the Leksell GammaPlan 3-D modeling and treatment planning system. 5.2.1.3 Volume Definition 5.2.1.3.1 Gross Tumor Volume (GTV): enhancing disease as defined on MRI 5.2.1.3.2 Organs at Risk (OARs): Adjacent structures at risk of radiation injury will be delineated to determine dose-volume exposures. 5.2.1.4 Treatment Planning: The precise 3-D geometry of the lesion is defined. Multiple isocenters are used to design a treatment plan that delivers highly conformal radiosurgery to the GTV with a V100 >98%, and conformality index <2. 5.2.1.5 Dose: The marginal dose is defined using the following guidelines:
5.2.1.6 OAR Constraints
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5.2.3 Salvage Whole Brain Radiotherapy (WBRT) WBRT is reserved in the event of disease progression or recurrence. The dose/fractionation and technique of WBRT are at the discretion of the attending Radiation Oncologist. 5.2.4 Toxicities 5.2.4.1 The criteria used for the grading of toxicities encountered in this study are Common Toxicity Criteria (CTC) version 3.0. 5.2.4.2 Radiation Therapy: The administration of radiation therapy is very likely to cause fatigue. It may also 1) cause or aggravate nausea or vomiting and 2) cause or aggravate headaches and/or visual disturbances and/or motor or sensory symptoms. Much less likely, but more serious potential complications include seizures and brain necrosis. 5.2.4.3 Radiation Simulation CT scan: Radiation simulation requires that a CT scan be completed for treatment planning and geometric localization, and is part of standard care radiosurgery practice. The patients are exposed to radiation due to the CT scan, with doses of <12 rem to the region scanned, presenting minimal risk in these patients with brain metastases who will be treated with therapeutic radiation. The CT scan will take 20 minutes. 5.2.4.4 Radiation Simulation MRI: Patients will have a Gd planning MRI scan to delineate gross tumor volume. The risk of a mild reaction to the contrast agent such as nausea or itching or skin rash is 1-2%. The risk of a serious life threatening allergic reaction is extremely rare (< 1 in 100,000). New reports have identified a possible link between Nephrogenic Systemic Fibrosis or Nephrogenic Fibrosing Dermopathy (NSF/NFD) and exposure to gadolinium containing contrast agents used at high doses in patients with kidney failure. Patients in this study are evaluated prior to entry for renal failure. There is no known radiation exposure from MRI. The MRI will take 30 minutes. 5.2.4.5 Any late toxicity that occurs following SRS will be documented. 5.3 Sunitinib Treatment 5.3.1 Phase I Dose Escalation Only patients who are sunitinib-naïve will be accrued to avoid the need for dose reductions in patients already taking sunitinib. Patients will be treated with sunitinib administration alone (following the dose escalation scheme), followed after 1 week by concurrent administration of sunitinib with SRS. Sunitinib administration will continue at study dose for 3 weeks following SRS to maximize radiosensitization of endothelial and tumor cells. Acute dose-limiting toxicity (DLT) is defined in Section 6.2. Please refer to Section 6.5 for specific Sunitinib dose modification guidelines for individual patients who experience toxicity.
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5.3.2 Study levels 1-2
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5.3.3 Study level 3 If accrual is completed for levels 1-2 without DLT >33% then the next cohort of 3 patients will be treated at a dose of Sunitinib 37.5 mg once daily but extended for 8 weeks (total of 13 weeks). The same procedure will be followed to determine DLT as for Study levels 1-2. 5.3.4 Continuous Dosing of Sunitinib A continuous schedule of oral daily Sunitinib without planned rest periods is planned. There is evidence that the biologic effects of Sunitinib are diminished during drug-free intervals [63, 64]. Phase II trial experience with a continuous oral–dosing schedule at a median daily dose of 37.5 mg/d indicates that the spectrum of toxicities with continuous-oral dosing is similar to schedules with planned drug-free intervals and that clinical benefit is comparable [65]. 5.3.5 Number of Patients 3-6 patients per dose level x 3 dose levels; accrual of 4 or 7 additional patients at the MTD or phase 2 dose indicates that the maximum accrual will be 22 patients. 5.3.6 Sunitinib administration Sunitinib will be supplied as 12.5 mg or 25 mg tablets and will be administered based on dose level. Tablet(s) will be taken whole with approximately 250 ml (8 oz.) of water each morning. Tablets may be taken with or without food. 5.4 General Concomitant Medication and Supportive Care Guidelines 5.4.1 Patients will be followed jointly during treatment by a medical and radiation oncologist. General supportive care will be provided in accordance with local institutional practice. CBC, electrolytes, renal function studies and liver function studies will be done per study calendar (section 9). 5.4.2 Nausea/vomiting. Radiation to the brain can induce nausea and vomiting. Patients can receive a 5-HT antagonist prophylactically within 30-60 minutes of SRS (e.g. 1 mg granisetron). If this is inadequate and the nausea does not respond to increasing the dosage of the primary agent, then supplementation with additional anti-nausea agents such as a phenothiazine (e.g. prochlorperazine 10 mg q8h po prn) or a dopamine receptor antagonist (e.g. metoclopramide 10 mg q6h po prn or domperidone 10 mg q6h po prn) is suggested. If this is inadequate, a benzodiazepine should be added until acute nausea is controlled or toxicity is limiting. If nausea and vomiting is thought to be secondary to post-SRS edema then steroid may be added (e.g., dexamethasone 4 mg q6h prn) or if the patient is already taking steroid the dose should be increased.
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5.4.3 Diarrhea should be managed with loperamide: 4 mg at first onset, then 2 mg every 2-4 hours until diarrhea-free for 12 hours (maximum = 16 mg loperamide/day). 5.4.4 Hand-foot syndrome may be treated with topical emollients (such as Aquaphor®), topical/systemic steroids, and/or antihistamine agents. Vitamin B6 (pyridoxine; 50-150 mg orally each day) may also be used. 5.4.5 Routine supportive measures for cancer patients such as erythropoietin, analgesics, blood transfusions, antibiotics, and bisphosphonates are permitted. 5.5 Duration of Treatment Patients will receive Sunitinib and SRS as outlined in the treatment schedule unless one of the following occurs:
1. Clinical disease progression during treatment, 2. Intercurrent illness that prevents further administration of treatment, 3. Unacceptable adverse event(s), 4. Patient decides to withdraw from the study, or 5. General or specific changes in the patient’s condition render the patient unacceptable for further treatment in the judgment of the investigator.
5.6 Monitoring During Treatment, and Follow-up Evaluation for treatment-related toxicity and steroid use will be performed weekly by a member of the clinical trial team (either by contact via telephone or through visits to the UHN) during the first four weeks (until Day 28) of Sunitinib for patients on dose levels 1-2 and weekly for the first 13 weeks for patients on dose level 3 (until Day 91). History and clinical examination by the treating physician will be performed at weeks 1, 4, 9, and 13. Patients will undergo research MRIs at baseline, and on Days 7,8, 28 and 35 (or 98). MRIs on Days 91, 175, 270 and 365 are standard care scans. Thereafter, the responsible physician will evaluate patients at weeks 25, 36, and 52; disease status, toxicity and steroid usage will be recorded. Patients will undergo standard care MRI at each of these visits. If response in the target lesion is documented at any time then a confirmatory scan will be performed within 4-6 weeks afterwards. Patients will then be monitored every 3-4 months thereafter at the discretion of the responsible physician. Any investigations and imaging required at these visits are at the discretion of the responsible physician. Patients removed from study because of unacceptable adverse events will be followed in the same manner (both for further toxicity and for efficacy). 5.7 Compliance with Study Medication Compliance with Sunitinib will be assessed at each weekly visit during treatment. The Patient’s Medication Diary (Appendix B) will be reviewed, and the remaining Sunitinib tablets counted to assure consistency with the Diary.
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6. PATIENT ASSESSMENT 6.1. Toxicity Toxicity assessment for patients on study will be continuous. All patients will be monitored for grade 3 and 4 acute toxicity during and after treatment. It is anticipated, based on prior studies, that sunitinib will be well tolerated as a single agent prior to radiotherapy. However, there is no published experience using sunitinib concurrently with radiotherapy in the setting of brain metastases. 6.2 Acute Toxicity of SRS and Sunitinib SRS has been utilized at PMH for the past fifteen years for primary and metastatic brain tumors. Severe adverse events, including radionecrosis, have occurred in 5% of patients at the dose levels proposed. Most treatment related toxicities for sunitinib administered as a single agent (Sunitinib investigators brochure) are CTCAE grade 1 and 2. In a recent phase III placebo-controlled, double-blind, randomized clinical trial using sunitinib 50 mg OD in the treatment of gastrointestinal stromal tumors, diarrhea (20% above placebo), nausea (10% above placebo), stomatitis (14% above placebo), altered taste, skin abnormalities (skin discoloration, rash, palmar plantar erythrodysesthesia syndrome - 30% above placebo), hypertension (7% above placebo), and bleeding were all more common in patients receiving sunitinib compared to patients receiving placebo. Most of these adverse events were grade 1 and 2. Grade 3 or 4 treatment-related adverse events were reported in 48% of sunitinib patients and 36% of placebo patients. The rates of grade 3 or 4 adverse events were diarrhea (5%), nausea (1%), abdominal pain NOS (6%), vomiting NOS (2%), stomatitis (1%), dyspepsia (1%), abdominal pain upper (2%), anemia NOS (8%), anorexia (1%), arthralgia (1%), back pain (1%), fatigue (7%), asthenia (5%), pyrexia (1%), headache (1%), rash NOS (1%), palmar plantar erythrodysesthesia syndrome (5%), hypertension NOS (4%). Grade 3 or 4 treatment-emergent laboratory abnormalities were seen in 34% of sunitinib patients versus 22% of placebo patients. Elevated liver function tests, elevated pancreatic enzymes, elevated creatinine, decreased left ventricular ejection fraction (LVEF), myelosuppression, and electrolyte disturbances were all more common in sunitinib patients versus placebo patients. Grade 3 and 4 laboratory abnormalities consisted of AST/ALT (2%), ALP (4%), total bilirubin (1%), amylase (5%), lipase (10%), decreased LVEF (1%), creatinine (1%), hypokalemia (1%), uric acid (8%), neutropenia (10%), anemia (3%), thrombocytopenia (5%). Treatment-emergent acquired hypothyroidism was noted in 4% of sunitinib patients and 1% of placebo patients. Similar rates of grade 3 and 4 toxicity were seen in patients taking sunitinib for treatment of metastatic renal cell carcinoma. There is no prior experience with the combination of RT plus sunitinib in patients published or reported in abstract form at the time of this protocol version. 6.3 Dose-Limiting Toxicity The primary objective of this study is to evaluate toxicities that result from the combination of SRS and Sunitinib. Therefore dose escalation will be based on
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toxicities that may be attributable to the combination of Sunitinib and SRS, and dose-limiting toxicities will not take into account expected systemic toxicities related to Sunitinib. If the etiology of toxicity is not clear, it will be attributed to the combination of Sunitinib and SRS. Acute toxicity is defined as that occurring within hours of SRS and Sunitinib or within 12 weeks of completing SRS (Day 91). Dose limiting toxicity (DLT) will be assessed within this time frame and will be scored using NCI Clinical Trials Criteria for Adverse Events (CTCAE) Version 3.0 (http://ctep.info.nih.gov/). A dose limiting toxicity is defined as:
• Grade ≥3 CNS toxicity occurring within 4 weeks following SRS • Grade ≥2 CNS hemorrhage • Grade 4 fatigue
The following Gr 3 or 4 toxicities are expected, as they are common sunitinib induced toxicities and not expected to be exacerbated by stereotactic brain radiation:
• Gr 3/4 nausea/vomiting • Diarrhea • Asymptomatic liver function or electrolyte abnormalities correctable with supportive measures or supplementation; • Hypertension; • Hand foot syndrome
Late radiation toxicities can develop months to years after completion of treatment. In the CNS these can include necrosis and localized brain edema. The development of severe (grade 4) late effects is rare in this patient population. Given the prolonged time period within which these effects can develop as well as their rarity, it is impractical to include them as endpoints for dose escalation rules in phase I studies. However, any combination treatment involving the delivery of an additional therapy concurrent with or following radiation treatment has the potential to enhance late effects. This may occur in the absence of any significant alteration in the incidence or severity of acute toxicity. All patients on this study will therefore be followed until death such that any late toxicities are captured and documented. 6.4 Management of Toxicities 6.4.1 Acute toxicity: Full supportive care for acute toxicity will be given including intravenous fluids, diuretics, steroids, antihistamines, antibiotics, etc. as required. 6.4.2 Non-acute toxicity: In the event of organ specific toxicity, complete history, physical examination, and laboratory evaluation will be taken for documentation. When appropriate and with informed consent, photographs, biopsies or other tests will be obtained. In the event of patient death within 3 months in the absence of disease progression, effort
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will be made to seek evidence of possible treatment effect at autopsy. 6.4.3 All life threatening events (grade 4), which may be due to the treatment, and all fatal events must be reported to the PI (or data manager) and the data and safety monitoring committee within 24 hours of their occurrence. The following adverse events are excluded from serious adverse event (SAE) reporting:
• Hospitalization, secondary to expected cancer morbidity including weight loss, fatigue, electrolyte disturbances, pain management, anxiety or admission for palliative care • Planned hospitalizations, including those for elective surgical procedures • Common toxicities and events secondary to progressive disease are generally excluded from reporting. However, in cases where the specificity or severity of an event is not consistent with the risk information, the event should be reported to the DSM committee.
6.5 Dose Reductions/Delays 6.5.1 Stereotactic Radiosurgery Delay or reduction in the dose of SRS is allowable at the discretion of the treating radiation oncologist but is strongly discouraged and should be discussed first with the principal investigator if possible. Patients will be removed from the study if radiation treatment is delayed >1 week or if the full planned dose is not delivered. If this removal occurs for a patient after documentation of a DLT then the cohort expansion criteria outlined in section 5.2 apply. If a patient does not receive SRS or is delayed inordinately on treatment but no DLT is registered then an additional patient may be added in to the current cohort as a replacement at the discretion of the principal investigator. During any SRS delay, the patient should continue on Sunitinib if possible. If the SRS delay is <1 week then, upon completion of SRS, drug administration should then continue for the planned duration per protocol. 6.5.2 Sunitinib • The NCI Clinical Trials Common Terminology Criteria for Adverse Events (CTCAE) will be used to grade toxicity (http://ctep.info.nih.gov/). • No Sunitinib dose modification will be made for hematologic toxicity. • Dose reductions for non-hematologic toxicities are outlined below. • If there is more than a 2-week delay in treatment due to toxicity, patients will be removed from the trial but included in the analysis for safety • If any patient requires a lengthy dose reduction of Sunitinib (e.g. >25% of the planned total duration of drug treatment) for non-DLT, drug-related toxicities (i.e. hypertension, diarrhea, hand-foot syndrome), the principal investigators will review the case and decide whether an additional patient should be accrued to ensure that safety of that particular dose level has been thoroughly established.
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Toxicity Severity Dose Modification for Sunitinib
Dose modifications for all other non-hematologic toxicities will be at the discretion of the responsible medical and radiation oncologists. 6.6 Late SRS-related Toxicity Any toxicity (per NCI CTCAE 3.0) arising from within the irradiated volume but seen beyond the window for DLT registration (> 12 weeks following completion of SRS), will be classified as a late SRS toxicity. Late SRS toxicity will therefore not influence dose escalation but will be recorded and reviewed by the principal investigators and the DSMB to determine whether discontinuation or modification of any cohort is subsequently warranted. Once a particular cohort has completed accrual and been closed, all attempts will be made to follow patients until death to ensure that any potential radiation-related toxicities are documented so that this information informs the design of subsequent studies using combinations of SRS and Sunitinib. 7. ENDPOINTS and CORRELATIVE STUDIES 7.1. Endpoints
7.1.1. Primary Endpoint The safety and tolerability of the combination of SRS and Sunitinib for patients with 1-3 brain metastases. Acute toxicity is defined as that occurring
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within hours of SRS and Sunitinib or within 12 weeks of completing SRS (Day 91). Dose limiting toxicity (DLT) will be assessed within this time frame and will be scored using NCI Clinical Trials Criteria for Adverse Events (CTCAE) Version 3.0 (http://ctep.info.nih.gov/). 7.1.2. Secondary Endpoints
7.1.2.1. Late SRS-related toxicity defined as any Gr. 3/4 SRS-related toxicity occurring >12 weeks post-SRS 7.1.2.2. Time to Intracranial Local Progression is defined as the time interval between the date of first treatment and the date of objective radiological progression of any one of the treated lesions. 7.1.2.2.1. Objective (Radiological) Progression: Objective progression is defined as increase of contrast uptake on MRI of > 25% as measured by two perpendicular tumor diameters compared to the smallest measurement ever for the same lesion by the same technique. If increase in size is accompanied by substantial amount of edema, further investigations to distinguish radionecrosis from tumor recurrence are warranted prior to determination of progression (e.g. FDG-PET, MRSI, Surgical resection). Where radionecrosis is confirmed, size progression of the metastasis will not constitute CNS progression of disease. 7.1.2.3. Time to Intracranial Distant Progression is defined as the time interval between the date of first treatment and the date of new brain metastases, with or without progression of the treated lesions. 7.1.2.4. Brain Progression free survival is defined as the time interval between the date of first treatment and the date of disease progression in the brain or death due to disease in the brain, whichever comes first. If neither event has been observed, then the patient will be censored at the date of the last disease assessment. 7.1.2.4.1. Disease progression is defined as objective (radiological) and/or symptomatic (neurological/clinical) progression whichever occurs first. The following criteria should be used: 7.1.2.4.2. Objective (Radiological) Progression: Objective progression is defined as increase of contrast uptake on MRI of > 25% as measured by two perpendicular tumor diameters compared to the smallest measurement ever for the same lesion by the same technique, or the appearance of new metastases. If increase in size is accompanied by substantial amount of edema, further investigations to distinguish radionecrosis from tumor recurrence are warranted prior to determination of progression (e.g. FDGPET, MRSI, Surgical resection). Where radionecrosis is confirmed, size progression of the metastasis will not constitute CNS progression of disease. 7.1.2.4.3. Symptomatic (Clinical/Neurological) Progression: Presence of all of the following conditions in the absence of other clinical explanations may indicate tumor progression. Calling this clinical evolution clinical tumor progression is at the investigator's
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discretion. It is strongly recommended to perform, whenever possible, a radiological confirmation of the clinical suspicion. The date of disease progression is defined as the date when the criteria for objective or symptomatic progression are first met. 7.1.2.4.3.1. clinical deterioration of performance status 7.1.2.4.3.2. deterioration of neurological functions 7.1.2.4.3.3. increase in corticosteroid dosage by 50% 7.1.2.5. Changes in the dose and frequency of supportive corticosteroids. 7.1.2.6. Alterations in tumor permeability, extracellular, extravascular, and vascular volumes, and in blood flow will be measured by Dynamic Contrast Enhanced-MRI (DCE-MRI); performed on Days -7, 7, 8, 28, and 35 (or 98) (see section 7.2.1.) and DCE-CT; performed on Days -7, 0 and 28 (see section 7.2.2). Additional tumor-related changes in tissue characteristics measured on MRI will also be evaluated. 7.1.2.7. Normal tissue effects of radiotherapy will be measured using Diffusion-Tensor Magnetic Resonance Imaging (DT-MRI), Magnetic Resonance Spectroscopic Imaging (MRSI), and Fluid-Attenuated Inversion Recovery (FLAIR) MRI to determine normal tissue radiation effects in brain adjacent to metastatic lesions; performed on Days -7, 7, 8, 28, and 35 (or 98). A physician blinded to the order of the scans and treatment status of the patients will quantitatively analyze areas of abnormality. The lesions will be outlined using a volumetric approach and the volumes pre-and post treatment and between cohorts compared. 7.1.2.8. Alterations in blood and urine biomarkers will be measured on blood samples. Blood sampling will occur at baseline, on Days 0 (8 hours after Sunitinib initiation), 7, 8, 28, 35 (Dose levels 1-2 only), 91, 98 (dose level 3 only), 175, 270 and 365. 7.1.2.9. Optimal Biological Dose (OBD) is defined as the lowest dose level at which there is no dose limiting toxicity and maximal observed effect to therapy defined by the following criteria on Dynamic Contrast Enhanced MRI (DCE-MRI): Decrease in tumor permeability measured by DCE-MRI and expressed as the maximum change in Ktrans between measurements on baseline scans and scan measurements on Days 8, 28, and 91. 7.1.2.10. Neuropsychological Evaluation (optional) • Neurocognitive function will be assessed in participants who are able to communicate in English, using empirically-based measures of the following domains: • Attention and working memory (Digit Span Subtest, Wechsler Adult Scale of Intelligence 3rd edition; Brief Test of Attention) • Memory (Hopkins verbal learning test) • Processing speed (Trail Making Test, Part A; Grooved Pegboard Test) • Language (Semantic fluency; Boston Naming Test, short form) • Visual construction (Rey Osterrieth Complex Figure, Copy) • Executive functions (Phonemic Fluency, Trail Making Test, Part B)
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• Changes to health-related quality of life will be assessed using the SF- 36, a standardized screening instrument.
7.2. Correlative Studies 7.2.1. Dynamic Contrast Enhanced MRI (DCE-MRI) DCE-MRI is a method of imaging the physiology of the microcirculation[66]. Clinical studies have shown that DCE-MRI-based measures correlate well with tumor angiogenesis[67]. DCE-MRI is based on the continuous acquisition of 2D or 3D MR images during the distribution of an intravenously administered paramagnetic contrast agent bolus. The contrast agent is a gadolinium-(Gd) based chelate, which is able to enter the extravascular extracellular space (EES) via the capillary bed. The pharmacokinetics of Gd distribution is modeled by a 2- or multicompartment model and has been shown to be a useful predictor of the biological response of angiogenesis inhibitors. The most commonly used model is a 2-compartment model describing the extravasation of Gd into the EES and the reflux from EES to the blood pool by first order kinetics (Toft’s Method) [68]. As a result, the transfer constant Ktrans
, which equals the permeability surface product, is obtained. The initial area under the curve (iAUC) can be additionally evaluated as a data-driven parameter. This value shows good correlation with the pharmacokinetic parameter Ktrans
[69]. The antiangiogenic effect of sunitinib will be monitored using DCE-MRI. Time-signal concentration curves will be taken at 6 different time points, 1 week prior to drug administration (Day -7), immediately before and the day after SRS (Days 7, 8), on termination of sunitinib (Day 28 and Day 91). The Toft’s 2-D compartment model will be used to model the pharmacokinetics of Gd distribution. Ktrans and iAUC parameters will be measured for each patient and compared between cohorts, and pre- and post-treatment, to evaluate the effect of Sunitinib and escalating doses of Sunitinib on tumor permeability, extracellular, extravascular and vascular volumes and blood flow. Other research-related MRI acquisitions will include DTI, and MRSI in order to measure normal brain tissue secondary objectives as in 7.2.1.5. 7.2.2. Dynamic Contrast Enhanced CT (DCE-MRI) DCE-CT has been a long-standing technique for imaging the extent of intracranial hemorrhage in stroke patients, providing physiological measurements of blood flow, blood volume, mean transit time and vascular permeability. The rapid generation of parameter maps and good linearity of iodine-based contrast agent and CT enhancement make DCECT
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a similarly worthwhile tool in radiation oncology. Estimates of microvascular permeability have been shown to be predictive of pathologic grade and to correlate with the mitotic activity of human glioma tumors [70]. The anti-angiogenic effect of Sunitinib will be monitored using DCE-CT. The patients are exposed to radiation due to the CT scan, with doses of 12 rem to the region scanned, presenting minimal risk in these patients with brain metastases who will be treated with therapeutic radiation. Time-signal concentration curves will be taken at 3 different time points, 1 week prior to drug administration (Day -7), at the start of treatment (Day – 0) and on termination of sunitinib (Day 28). The Toft’s 2-D compartment model will be used to model the pharmacokinetics of Iodine distribution. Perfusion parameters will be measured for each patient and compared between cohorts, and pre- and post-treatment, to evaluate the effect of Sunitinib and escalating doses of Sunitinib on tumor permeability, extravascular and vascular volumes and blood flow. 7.2.3. Biomarkers 7.2.3.1. Soluble proteins A common feature observed in the serum/plasma of cancer patients treated with antiangiogenic multitargeted TKIs is a triad of molecular changes involving circulating soluble proteins, namely, increased levels of plasma VEGF and PlGF and decreased levels of soluble VEGF receptor-2. The biological significance of these changes is unknown. Randomized trials using sunitinib have not shown a correlation between increases in VEGF or PlGF and patient response/clinical benefit [26, 63]. A recent study has shown that VEGF levels in the urine may be also be a useful marker reflective of patient outcome [71]. While the evidence suggests a role for circulating soluble proteins as useful indicators of biological anti-angiogenic agents in patients with cancer, the data supporting their clinical use are still too premature for routine clinical application. Thus all analysis will be considered exploratory, and will consist of evaluating pre-treatment serum/plasma values with primary and secondary endpoints, as well as comparisons of serial changes in serum/plasma levels over time. Serum/plasma biomarkers will be measured on blood samples and urine samples will be collected for urine biomarkers. Blood and urine sampling will occur at baseline, on Days 0 (8 hours after Sunitinib initiation), 7, 8, 28, 35 (Dose levels 1-2 only), 91, 98 (dose level 3 only), 175, 270 and 365. The samples will be stored for future analysis. Levels of the following serum biomarkers will be measured: Serum VEGF, bFGF, PlGF, soluble VEGFR1, and soluble VEGFR2. 7.2.3.1.1. Blood and Urine Specimen Collection Guidelines
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Blood -Serum 20cc in two SST (serum separating tubes – Tiger Top) and plasma - two standard vacutainer tubes with sodium citrate Urine – at least 5cc in a sterile collection cup, however the optimal amount would be 25 cc. All specimens should be labeled with study identifier, date, time and time point collected. Blood to be centrifuged at 3000rmp for 10 minutes at 4 degree Celsius within 45 minutes of blood collection. Aliquot Serum and plasma collected through this procedure to be placed in freezer storage tube
(500μl). Ensure correct labeling and store in Dr. Bristow’s lab at –80
degree Celsius. Urine Specimens will be stored at a range of –20c to 4c within 2 hours of collection and until processed. 7.2.3.1.2. Collection Schedule Baseline (-7), prior to radiation therapy (Day 7), after radiation (Day 8) Day 28, Day 35 (dose levels 1-2 only), Day 91, Day 98 (dose level 3 only), 6 months (Day 175), 9 months (Day 270) and one year (Day 365). 7.2.3.1.3. Specimen Analysis • Blood (plasma and serum) and urine specimens will be sent to the laboratory of Dr. Kevin Camphausen on dry ice. Call or email for FEDEX number.
Kevin Camphausen, MD Bldg 10, Rm 3B42 Bethesda, MD 20892 301-496-5457 [email protected]
• In effort to protect the patient’s identity in the laboratory, the samples will be identified by a code that can be linked back to the patient by the investigators, but not other laboratory personnel 7.2.3.1.4. Handling of Specimens collected for Research Purposes • Blood and urine samples collected in the course of this research project may be banked and used in the future to investigate new scientific questions related to this study. However, this research may only be done if the risks of the new questions were covered in the consent document. • No germline mutation testing will be performed on any of the samples collected unless the patient gives separate informed consent or has expired. Tests will be pilot studies related to the Branch’s work on such topics as molecular profiling, and novel molecular therapeutic strategies. • Any new use of the samples will require prospective IRB review and approval. • At the completion of the protocol, the investigator will dispose of all specimens in accordance with the environmental protection laws,
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regulations and guidelines of the Federal Government and the State of Maryland. • Any loss or unintentional destruction of the samples will be reported to the IRB. 7.3. Statistical Methods For this Phase I study, all observed toxicities will be tabulated by grade with acute and late toxicities presented separately for each dose level. Descriptive statistics and graphic displays will be used to characterize the patients and disease features. The time to local progression will be reported for patients by dose level. The patterns and change from baseline for the DCE-MRI, diffusion weighted and diffusion tension MRI (DW-MRI and DTI-MRI), MRSI, and FLAIR MRI as well as blood biomarkers, will be presented graphically by dose cohort. 8. PHARMACEUTICAL INFORMATION Sunitinib, Sunitinib Malate Chemical Name: (Z)-N-[2-(Diethylamino)ethyl]-5-[(5-fluoro-2-oxo-1,2- dihydro-3H-indol-3-ylidene)methyl]-2,4-dimethyl-1Hpyrrole- 3-carboxamide (S)-2-hydroxysuccinate Other Names: Sutent
Classification: Tyrosine kinase inhibitor (PDGFRα, PEGFβ, VEGFR1,
VEGFR2, VEGFR3, KIT, FLT3, CSF-1R, and RET) Mechanism of Action: Sunitinib is a small molecule that inhibits multiple receptor tyrosine kinases (RTKs), some of which are implicated in tumor growth, pathologic angiogenesis, and metastatic progression of cancer. The non-clinical pharmacology program of sunitinib evaluated the ability of sunitinib, and its major active metabolite, to inhibit the activity and function of its receptor tyrosine kinase (RTK) targets in vitro and in vivo as well as its ability to inhibit tumor progression in rodent models of experimental cancer. The primary metabolite exhibits similar potency compared to sunitinib in biochemical and cellular assays. In vivo, sunitinib inhibited the phosphorylation of multiple RTKs in tumor xenografts expressing RTK targets and demonstrated the ability to inhibit tumor growth or cause tumor regression, and/or inhibit metastatic progression in a variety of rodent models of experimental cancer. Sunitinib also demonstrated the ability to
inhibit PDGFRβ- and VEGFR2-dependent tumor angiogenesis.
Molecular Formula: C22H27FN4O2 • C4H6O5
Molecular Mass: 532.57 Daltons Approximate Solubility: 0.19 mg/100 mL in 0.1 N HCl, 453 mg/100 mL in Ethanol, and 2971 mg/100 mL in PEG 400. How Supplied: Sunitinib capsules are supplied as printed hard shell capsules containing sunitinib malate equivalent to 12.5, 25, or 50 mg of sunitinib together with mannitol, croscarmellose sodium, povidone (K-25) and magnesium stearate as inactive ingredients. 12.5 mg capsules: Hard gelatin capsule with orange cap and orange body, printed with white ink “Pfizer” on the cap,
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“STN 12.5 mg” on the body. 25 mg capsules: Hard gelatin capsule with caramel cap and orange body, printed with white ink “Pfizer” on the cap, “STN 25 mg” on the body. 50 mg capsules: Hard gelatin capsule with caramel cap and caramel body, printed with white ink “Pfizer” on the cap, “STN 50 mg” on the body. The orange capsule shells contain gelatin, titanium dioxide, and red iron oxide. The caramel capsule shells also contain yellow iron oxide and black iron oxide. The imprinting ink contains shellac, propylene glycol, sodium hydroxide, povidone and titanium dioxide. Supplied as bottles of 28 capsules. Storage: Store at 25ºC. Excursions permitted to 15ºC - 35ºC. Stability: Not indicated. Route(s) of Administration: Orally Reported Adverse Events and Potential Risks: Body as a whole: Fatigue, flu-like syndromes, fever, arthralgia, headache Gastrointestinal: Diarrhea, pancreatitis, elevated amylase/lipase, abdominal pain/cramping, nausea, flatulence, dyspepsia Hepatic: Increased bilirubin, ALT, AST, and alkaline phosphatase Metabolic: Anorexia Skin: Hand-foot syndrome, characterized by palmar and plantar erythema; rash/desquamation, hypersensitivity reactions, dry skin, alopecia, skin discoloration, depigmentation of the hair or skin Cardiac: Hypertension, Left Ventricular Dysfunction, QT Prolongation Endocrine: Hypothyroidism Vascular: Hemorrhage Hematologic: Neutropenia, Thrombocytopenia, Anemia The following adverse events have been reported on trials but with the relationship to Sunitinib still undetermined: Adrenal insufficiency, pulmonary embolism, seizures, reversible posterior leukoencophalopathy syndrome Method of Administration: Sunitinib malate should be taken with at least 250 mL of water and can be given without regards to meals. Food does not appear to have a clear effect on sunitinib malate pharmacokinetics. It is taken once daily, on a schedule of 4 weeks on treatment followed by 2 weeks off. Potential Drug Interactions: Sunitinib is metabolized primarily by CYP3A4. Potential interactions may occur with drugs/foods/herbs that are inhibitors or inducers of this enzyme system. CYP3A4 Inhibitors: Co-administration of SUTENT (sunitinib malate) with inhibitors of the CYP3A4 family may increase SUTENT concentrations (see ACTION AND CLINICAL PHARMACOLOGY). Concomitant administration of SUTENT with CYP3A4 inhibitors should be avoided. These include, but are not limited to: calcium channel blockers (e.g. diltiazem, verapamil); antifungals (e.g. ketoconazole, fluconazole, itraconazole, voriconazole); macrolide antibiotics (e.g. erythromycin, clarithromycin); fluoroquinolone antibiotics (e.g. ciprofloxacin, norfloxacin); and some HIV antivirals (e.g. ritonavir, indinavir).
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CYP3A4 Inducers: Co-administration of SUTENT with inducers of the CYP3A4 family may decrease SUTENT concentrations (see ACTION AND CLINICAL PHARMACOLOGY). Concomitant administration of SUTENT with CYP3A4 inducers should be avoided. CYP3A4 inducers include, but are not limited to: barbiturates (e.g. phenobarbital); anticonvulsants (e.g. carbamazepine, phenytoin); rifampin; glucocorticoids; pioglitazone; and some HIV antivirals (e.g. efavirenz, nevirapine). Drugs Which Prolong the QT/QTc Interval: The concomitant use of SUTENT with another QT/QTc prolonging drug is discouraged. However, if it is necessary, particular care should be used. Drugs that have been associated with QT/QTc interval prolongation and/or torsade de pointes include, but are not limited to, the examples in the following list. Chemical/pharmacological classes are listed if some, although not necessarily all, class members have been implicated in QT/QTc prolongation and/or torsade de pointes: • Antiarrhythmics (Class IA, e.g., quinidine, procainamide, disopyramide; Class III, e.g. amiodarone, sotalol, ibutilide; Class IC, e.g. flecainide, propafenone) • Antipsychotics (e.g., thioridazine, chlorpromazine, pimozide, haloperidol, droperidol) • Antidepressants (e.g. amitriptyline, imipramine, maprotiline, fluoxetine, venlafaxine) • Opioids (e.g. methadone) • Macrolide antibiotics (e.g. erythromycin, clarithromycin, telithromycin) • Quinolone antibiotics (e.g. moxifloxacin, gatifloxacin, ciprofloxacin) • Antimalarials (e.g. quinine) • Pentamidine • Azole antifungals (e.g. ketoconazole, fluconazole, voriconazole) • Gastrointestinal drugs (e.g. domperidone, 5HT3 antagonists, such as granisetron, ondansetron, dolasetron) • Β2-adrenoreceptor agonists (salmeterol, formoterol) • Tacrolimus Drugs Which Prolong the PR Interval: Caution should be used if SUTENT is prescribed to patients in combination with other drugs that also cause PR interval prolongation, such as beta blockers, calcium channel blockers, digitalis, or HIV protease inhibitors (See WARNINGS AND PRECAUTIONS, Cardiovascular, QT Interval Prolongation). The above list of potentially interacting drugs is not comprehensive. Current scientific literature should be consulted for more information. Potential Food Interactions: Grapefruit juice has CYP3A4 inhibitory activity. Therefore, ingestion of grapefruit juice while on SUTENT therapy may lead to decreased SUTENT metabolism and increased SUTENT plasma concentrations (See Drug-Drug Interactions). Concomitant administration of SUTENT with grapefruit juice should be avoided. Potential Herb Interactions: St. John’s Wort is a potent CYP3A4 inducer. Coadministration
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with SUTENT may lead to increased SUTENT metabolism and decreased SUTENT plasma concentrations (see Drug-Drug Interactions). Patients receiving SUTENT should not take St. John’s Wort concomitantly. Availability/ Agent Ordering Sunitinib is an investigational agent supplied to investigators by Pfizer Canada Inc. Agent Accountability The Investigator, or a responsible party designated by the investigator, must maintain a careful record of the inventory and disposition of all agents received from Pfizer Inc. using a Drug Accountability Record Form. Patient Diary of Compliance Each patient will be required to record daily self-administration of Sunitinib. A sample diary is included in appendix B.
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9. STUDY CALENDAR Baseline evaluations are to be conducted within 1 week prior to administration of
protocol therapy. Scans and x-rays must be done <4 weeks prior to the start of
therapy. a - Patients on dose levels 1-2 [X] receive drug for 4 weeks, for dose level 3[Xa] drug is delivered for an additional 8 weeks post SRS (13 weeks). b - SRS given on Day 7 only
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c - Steroid use is evaluated weekly by the CTC via phone or during scheduled patient evaluation d - Toxicity is evaluated weekly by the CTC via phone or during scheduled patient evaluation, after week 13 collection of toxicity data will be limited to the brain to document any late RT toxicities e - Documentation of history/physical examination (including weight), vital signs (Blood pressure, heart rate, respiratory rate, temperature [degrees celsius]), performance status, f - serum chemistry includes standard serum chemistry, creatinine, liver functions, magnesium, calcium and phosphate g – Twelve-lead electrocardiogram (ECG) at pre-study work-up investigation then in follow-up, as clinically indicated h – Esophagogastroduodenoscopy (EGD) to rule out the presence of esophageal varices or ulcers at risk of bleeding i - MR imaging is required for entry into trial to document measurability as well as for restaging for follow-up; diagnostic MRI sequences include: T1 + gadolinium, T2 FLAIR, DCE j– research MRI sequences (T1 + gadolinium, T2 FLAIR, DCE, MRSI, DTI) will be captured at the indicated time point to assess tumor and normal tissue response k – serum/urine biomarkers evaluated 8 hours after initiation of Sunitinib l – serum/urine biomarkers evaluated before SRS on days 7 and day after SRS (day 8) m – serum/urine biomarkers and MRI evaluated for dose levels 1-2 only n – serum/urine biomarkers and MRI evaluated for dose level 3 only o -for pre-menopausal females p - patients will continue to be followed every 3 months for the second year of follow up and at least every 6 months after this for 3 more years to continue to evaluate for late effects q - research DCE-CT will be captured at the indicated time points to assess tumor perfusion parameters 10. DATA REPORTING / REGULATORY CONSIDERATIONS 10.1. Case Report Form Completion Case Report Forms must be completed using black ink. Any errors must be crossed out so that the original entry is still visible, the correction clearly indicated and then initialled and dated by the individual making the correction. Case Report Forms will be retained by the CRU along with relevant supporting documentation such as scans, progress notes, nursing notes, bloodwork, pathology reports etc. All patient names or other identifying information will be removed and the documents labeled with patient initials, study number and the protocol number. Once data has been checked and quality assurance performed, it will be entered into an Oracle based relational database by CRU staff. Further data quality checks will be performed by the CRU statistician. 10.2. Case Report Forms and Schedule for Completion A list of forms is provided in the table below. All forms have to be signed by the responsible study physician as well as by the study coordinator. Follow-up is required for patients from the time of registration and will apply to all eligible patients. Forms
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should be sent to the study coordinator listed on the front sheet. Data required for the study will be collected in Case Report Forms provided by the CRU. The form submission schedule is outlined below.
10.3. Data Flow Original copies of data forms will be kept at the CRU. Data forms will only be modified by the study coordinator as per the Standard Clarification Guidelines. Collected data will be compared with the medical record. In the case of data inconsistencies, the study coordinator will prepare query letters that must be signed by the responsible study physician and submitted to the CRU within 3 weeks. 10.4. Adverse Events The conduct of the study will comply with all Health Canada safety reporting requirements. All adverse events, whether serious or not, whether observed by the investigator or reported by the patient, must include the following information: patient number age sex weight start and stop date of the event severity of reaction (mild, moderate, severe) relationship to study drug (probably related, unknown relationship, definitely not related) the action taken with respect to the test drug the patient’s outcome date and time of administration of test medications all concomitant medications medical treatment provided for adverse event Pfizer study number
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Toxicity will be scored using NCI Clinical Trials Criteria for Adverse Events (CTCAE) Version 3.0 (http://ctep.info.nih.gov/). All treatment areas have access to a copy of the CTCAE Version 3.0. The investigator must appraise all abnormal laboratory results for their clinical significance. If any abnormal laboratory result is considered clinically significant, the investigator must provide details about the action taken with respect to the test drug and about the patient’s outcome. The investigator must evaluate each adverse experience for its relationship to the test drug and for its seriousness. The investigator is responsible for evaluating all adverse events to determine whether criteria for “serious” as defined below are present. The investigator is responsible for reporting serious adverse events to the Pfizer Drug Safety and the CRU as described below. 10.5. Serious Adverse Event Definition A serious adverse event is one that at any dose (including overdose): Results in death (if related to study treatment, if an attributable to another SAE or if no information related to cause of death is known) Is life-threatening1
Requires inpatient hospitalization or prolongation of existing hospitalization Results in persistent or significant disability or incapacity2
Is a congenital anomaly or birth defect Is an important medical event3
Suspected positive Pregnancy
1“Life-threatening” means that the subject was at immediate risk of death at the time of the serious adverse event; it does not refer to a serious adverse event that hypothetically might have caused death if it were more severe.
2“Persistent or significant disability or incapacity” means that there is a substantial disruption of a person’s ability to carry out normal life functions.
3Medical and scientific judgment should be exercised in deciding whether expedited reporting is appropriate in situations where none of the outcomes listed above occurred. Important medical events that may not be immediately life-threatening or result in death or hospitalization but may jeopardize the patient or may require intervention to prevent one of the other outcomes listed in the definition above should also usually be considered serious. Examples of such events include allergic bronchospasm requiring intensive treatment in an emergency room or at home, blood dyscrasias or convulsions that do not result in inpatient hospitalization, or the development of drug dependency or drug abuse. A new diagnosis of cancer during the course of a treatment should be considered as medically important. 10.6. Expedited Reporting by Investigator to Pfizer Canada Drug Safety Serious adverse events (SAE) are defined above. The investigator should inform the
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Pfizer Canada Drug Safety and CRU of any SAE within 24 hours of being aware of the event. This must be documented on the study specific SAE form. This SAE form must be completed and supplied to the Pfizer Canada Drug Safety and the CRU within 24 hours/1 business day at the latest on the following working day. The initial report must be as complete as possible, including details of the current illness and serious adverse event, and an assessment of the causal relationship between the event and the investigational product(s). Information not available at the time of the initial report (e.g., an end date for the adverse event or laboratory values received after the report) must be documented on a follow-up SAE form. 10.7. Immediate Reporting by investigator to Pfizer Canada Drug Safety/CRU Any suspected fetal exposure to Sunitinib must be reported immediately to the CRU and also to Pfizer Canada Drug Safety. The patient should be referred to an obstetrician/gynecologist experienced in reproductive toxicity for further evaluation and counselling. Pregnancies occurring while the subject is on study drug or within 4 weeks after the subject’s last dose of study drug are considered Expedited reportable events. If the subject is on study drug, the study drug is to be discontinued immediately and the subject is to be instructed to return any unused portion of the study drug to the Investigator. The pregnancy must be reported to Pfizer Canada Drug Safety and the CRU by phone and facsimile using the SAE Form immediately upon the Investigator learning of the pregnancy. The Investigator will follow the subject until completion of the pregnancy, and must notify Pfizer Canada Drug Safety of the outcome as specified below. The Investigator will provide this information as a follow-up to the initial SAE. If the outcome of the pregnancy meets the criteria for immediate classification as a SAE (i.e., spontaneous abortion [any congenital anomaly detected in an aborted fetus is to be documented], stillbirth, neonatal death, or congenital anomaly), the Investigator should follow the procedures for reporting SAEs (i.e., report the event to Pfizer Canada Drug Safety by facsimile within 24 hours of the Investigator’s knowledge of the event). Any suspected fetal exposure to Sunitinib must be reported to Pfizer Canada Drug Safety within 24 hours of being made aware of the event. The patient should be referred to an obstetrician/gynecologist experienced in reproductive toxicity for further evaluation and counselling. All neonatal deaths that occur within 30 days of birth should be reported, without regard to causality, as SAEs. In addition, any infant death after 30 days that the Investigator suspects may be related to the in utero exposure to the study drug should also be reported. In the case of a live “normal” birth, Pfizer Canada Drug Safety should be advised as soon as the information is available. 10.8. Reporting to Health Canada Adverse drug reactions that are Serious, Unexpected, and at least possibly associated to the drug, and that have not previously been reported in the Investigators brochure, or reference safety information document will be reported promptly to Health Canada in writing by Pfizer Canada Drug Safety. A clear description of the suspected reaction should be provided along with an assessment as to whether the event is drug or disease related. Pfizer Canada Drug Safety shall notify Health Canada by
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telephone or by fax of any unexpected fatal or life threatening experience associated with the use of the drug as soon as possible but no later than 7 calendar days after initial receipt of the information. 10.9. Reporting of Adverse Events to the Institutional Review Board The principal Investigator is required to notify the Institutional Review Board (IRB) of a serious adverse event according to institutional policy. 10.10. Pfizer Canada Contact Information Pfizer Canada Inc. Drug Safety: Tel: 1 800 463-6001 10.11. Adverse Event Updates / IND Safety Reports Pfizer shall notify the Investigator via an IND Safety Report of the following information: Any AE associated with the use of study drug in this study or in other studies that is both serious and unexpected. Any finding from tests in laboratory animals that suggests a significant risk for human subjects including reports of mutagenicity, teratogenicity, or carcinogenicity. The Investigator shall notify the IRB/EC promptly of these new serious and unexpected AE(s) or significant risks to subjects. The Investigator must keep copies of all AE information, including correspondence with Pfizer and the IRB/EC, on file (see Section 12.4 for records retention information). 10.12. Quality Assurance 10.12.1. Control of Data Consistency Data monitoring will take place throughout the trial at the CRU. At least 10% of CRF’s will be reviewed against submitted de-identified source documentation from the sites and query letters will be generated for any inconsistencies. Query letters will also be initiated for any deviations from protocol. 10.13. Ethical Considerations 10.13.1. Patient Protection The responsible investigator will ensure that this study is conducted in agreement with either the Declaration of Helsinki (Tokyo, Venice, Hong Kong, Somerset West and Edinburgh amendments) or the laws and regulations of the country, whichever provides the greatest protection of the patient. The protocol has been written, and the study will be conducted according to the ICH Harmonized Tripartite Guideline for Good Clinical Practice (ref: http://www.ifpma.org/pdfifpma/e6.pdf). The protocol will be approved by the Local Ethics Committee. 10.13.2. REB Composition The composition and procedures of the REB must be compliant with the ICH Good Clinical Practice Guidelines and the membership of the REB approving this protocol must also be consistent with Canadian regulatory requirements.
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10.13.3. Initial Approval REB board approval of the protocol and consent form (see below) is required for activation. Documentation of full board approval of the initial protocol and the consent form, as well as a completed other documents outlined in section 10 must be received prior to activation. An REB Attestation Form (Health Canada) must be completed and signed by the REB Chair. This documentation or a comparable assurance must be received by the CRU before the centre can be locally activated. 10.13.4. Annual Re-Approvals Annual re-approval is required for as long as the trial is open to patient accrual or patients are receiving protocol treatment or undergoing protocol mandated interventions. 10.13.5. Amendments / Revisions All amendments or revisions to the protocol must undergo review by the REB and Pfizer prior to implementation. Amendments/revisions will be circulated to all relevant parties in a standard format with clear instructions regarding REB review. If full board approval of an amendment is required it will be specified. Amendments will be reviewed and approved by Health Canada prior to central Implementation of the study, and by the REB prior to implementation, EXCEPT when the amendment eliminates an immediate hazard to clinical trial subjects. An REB Attestation Form (Health Canada) will be distributed with each amendment and must be completed and signed by the REB chair. This documentation (or a comparable assurance) and the date of implementation of the amendment must be received by the CRU. 10.13.6. REB Refusals If the REB refuses to approve this protocol (or an amendment/revision to this protocol) the CRU and Pfizer must be notified immediately of the date of refusal and the reason(s) for the refusal. 10.13.7. Serious Adverse Events, Safety Updates, and Investigator Brochure Updates During the course of the study serious adverse events, safety updates or investigator brochure updates may be distributed for reporting to the REB. If/when this occurs, documentation of REB submission of this information must be forwarded to the CRU. 10.13.8. Informed Consent Document The REB must approve the consent form document, which will be used prior to its local activation; changes to the consent form in the course of the study will also require REB notification/approval. It is essential that the consent form contain a clear statement that gives permission for 1) information to be sent to and 2) source medical records to be reviewed by the CRU and other agencies as necessary. In addition, the consent form should
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include all elements required by ICH-Good Clinical Practice Guidelines. 10.13.9. Consent Process/ Patient Eligibility Patients who cannot give informed consent (i.e. mentally incompetent patients, or those physically incapacitated such as comatose patients) are not to be recruited into the study. Patients competent but physically unable to sign the consent form may have the document signed by their nearest relative or legal guardian. Each patient will be provided with a full explanation of the study before consent is requested. 10.13.10. Retention of Patient Records and Study Files This study is conducted under a CTA with Health Canada, therefore ICH Good Clinical Practice guidelines apply. All essential documents should be retained until at least two years after the last approval of a marketing application in an ICH region and until there are no pending or contemplated marketing applications in ICH region or at least two years have elapsed since the formal discontinuation of clinical development of the investigational product or for 25 years, whichever is longer. These documents should be retained for a longer period however if required by the applicable regulatory requirements. The investigator and the CRU should take measures to prevent accidental or premature destruction of these documents. The CRU will notify all the trial investigators and all the regulatory authorities if clinical development of an investigational product discontinues or when trial related records are no longer needed. 10.14. Publication policy, Authorship of Papers, Meeting Abstracts, Etc. 10.14.1. Authors The first author will generally be the principal investigator of the study. A limited number of the members of the institutions involved on the trial and representatives of Pfizer may be credited as authors depending upon their level of involvement in the study. Additional authors, up to a maximum of 10, will be those who have made the most significant contribution to the overall success of the study. This contribution will be assessed, in part but not entirely, in terms of patients enrolled and will be reviewed at the end of the trial by the principal investigator. 10.14.2. Responsibility for Publication It will be the responsibility of the study chair to write up the results of the study within a reasonable time of its completion. Although the study chair has full discretion to publish some or all of the results of the study, this material will be submitted to Pfizer for review at least 60 days in advance of submission for publication. 10.14.3. Submission of Material for Presentation or Publication Material may not be submitted for presentation or publication without approval by the principal investigator and without prior review by Pfizer. Supporting groups and agencies will be acknowledged.
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Sunitinib with SRS UHN REB ID # 09-0115-C Version 22-Jul-2009 42 34. Lee, C.G., et al., Anti-Vascular endothelial growth factor treatment augments tumor radiation response under normoxic or hypoxic conditions. Cancer Res, 2000. 60(19): p. 5565-70. 35. Hess, C., et al., Effect of VEGF receptor inhibitor PTK787/ZK222584 [correction of ZK222548] combined with ionizing radiation on endothelial cells and tumor growth. Br J Cancer, 2001. 85(12): p. 2010-6. 36. Williams, K.J., et al., ZD6474, a potent inhibitor of vascular endothelial growth factor signaling, combined with radiotherapy: schedule-dependent enhancement of antitumor activity. Clin Cancer Res, 2004. 10(24): p. 8587-93. 37. Huber, P.E., et al., Trimodal cancer treatment: beneficial effects of combined antiangiogenesis, radiation, and chemotherapy. Cancer Res, 2005. 65(9): p. 3643-55. 38. Bischof, M., et al., Triple combination of irradiation, chemotherapy (pemetrexed), and VEGFR inhibition (SU5416) in human endothelial and tumor cells. Int J Radiat Oncol Biol Phys, 2004. 60(4): p. 1220-32. 39. Abdollahi, A., et al., SU5416 and SU6668 attenuate the angiogenic effects of radiation-induced tumor cell growth factor production and amplify the direct anti-endothelial action of radiation in vitro. Cancer Res, 2003. 63(13): p. 3755- 63. 40. Abdollahi, A., et al., Inhibition of alpha(v)beta3 integrin survival signaling enhances antiangiogenic and antitumor effects of radiotherapy. Clin Cancer Res, 2005. 11(17): p. 6270-9. 41. Mauceri, H.J., et al., Combined effects of angiostatin and ionizing radiation in antitumor therapy. Nature, 1998. 394(6690): p. 287-91. 42. Rofstad, E.K., et al., Antiangiogenic treatment with thrombospondin-1 enhances primary tumor radiation response and prevents growth of dormant pulmonary micrometastases after curative radiation therapy in human melanoma xenografts. Cancer Res, 2003. 63(14): p. 4055-61. 43. Li, J., et al., Angiogenesis and radiation response modulation after vascular endothelial growth factor receptor-2 (VEGFR2) blockade. Int J Radiat Oncol Biol Phys, 2005. 62(5): p. 1477-85. 44. Li, L., A. Rojiani, and D.W. Siemann, Targeting the tumor vasculature with combretastatin A-4 disodium phosphate: effects on radiation therapy. Int J Radiat Oncol Biol Phys, 1998. 42(4): p. 899-903. 45. Hoang, T., et al., Augmentation of radiation response with the vascular targeting agent ZD6126. Int J Radiat Oncol Biol Phys, 2006. 64(5): p. 1458-65. 46. Wilson, W.R., et al., Enhancement of tumor radiation response by the antivascular agent 5,6-dimethylxanthenone-4-acetic acid. Int J Radiat Oncol Biol Phys, 1998. 42(4): p. 905-8. 47. Wachsberger, P., R. Burd, and A.P. Dicker, Tumor response to ionizing radiation combined with antiangiogenesis or vascular targeting agents: exploring mechanisms of interaction. Clin Cancer Res, 2003. 9(6): p. 1957-71. 48. Kozin, S.V., et al., Vascular endothelial growth factor receptor-2-blocking antibody potentiates radiation-induced long-term control of human tumor
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xenografts. Cancer Res, 2001. 61(1): p. 39-44. 49. Cao, C., et al., Vascular endothelial growth factor tyrosine kinase inhibitor Sunitinib with SRS UHN REB ID # 09-0115-C Version 22-Jul-2009 43 AZD2171 and fractionated radiotherapy in mouse models of lung cancer. Cancer Res, 2006. 66(23): p. 11409-15. 50. Jain, R.K., Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy. Science, 2005. 307(5706): p. 58-62. 51. Winkler, F., et al., Kinetics of vascular normalization by VEGFR2 blockade governs brain tumor response to radiation: role of oxygenation, angiopoietin-1, and matrix metalloproteinases. Cancer Cell, 2004. 6(6): p. 553-63. 52. Willett, C.G., et al., Direct evidence that the VEGF-specific antibody bevacizumab has antivascular effects in human rectal cancer. Nat Med, 2004. 10(2): p. 145-7. 53. Paris, F., et al., Endothelial apoptosis as the primary lesion initiating intestinal radiation damage in mice. Science, 2001. 293(5528): p. 293-7. 54. Garcia-Barros, M., et al., Tumor response to radiotherapy regulated by endothelial cell apoptosis. Science, 2003. 300(5622): p. 1155-9. 55. Chen, An experimental research on the combination treatment of sFLK-1 gene therapy combined with gamma knife. Sichuan Da Xue Xue Bao Yi Xue Ban, 2006. 37(5): p. 708-11. 56. Staba, M.J., et al., Adenoviral TNF-alpha gene therapy and radiation damage tumor vasculature in a human malignant glioma xenograft. Gene Ther, 1998. 5(3): p. 293-300. 57. Narazaki, M. and G. Tosato, Ligand-induced internalization selects use of common receptor neuropilin-1 by VEGF165 and semaphorin3A. Blood, 2006. 107(10): p. 3892-901. 58. Willett, C.G., et al., Surrogate markers for antiangiogenic therapy and doselimiting toxicities for bevacizumab with radiation and chemotherapy: continued experience of a phase I trial in rectal cancer patients. J Clin Oncol, 2005. 23(31): p. 8136-9. 59. Crane, C.H., et al., Phase I trial evaluating the safety of bevacizumab with concurrent radiotherapy and capecitabine in locally advanced pancreatic cancer. J Clin Oncol, 2006. 24(7): p. 1145-51. 60. Lordick, F., et al., Increased risk of ischemic bowel complications during treatment with bevacizumab after pelvic irradiation: report of three cases. Int J Radiat Oncol Biol Phys, 2006. 64(5): p. 1295-8. 61. Kan, P., et al., Peritumoral edema after stereotactic radiosurgery for intracranial meningiomas and molecular factors that predict its development. J Neurooncol, 2007. 62. Gonzalez, J., et al., Effect of bevacizumab on radiation necrosis of the brain. Int J Radiat Oncol Biol Phys, 2007. 67(2): p. 323-6. 63. Norden-Zfoni, A., et al., Blood-based biomarkers of SU11248 activity and clinical outcome in patients with metastatic imatinib-resistant gastrointestinal stromal tumor. Clin Cancer Res, 2007. 13(9): p. 2643-50. 64. Deprimo, S.E., et al., Circulating protein biomarkers of pharmacodynamic
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APPENDIX II: Discovery of biomarkers to guide individualized therapy in patients with brain metastasis receiving radiotherapy Site: Princess Margaret Hospital (PMH) Principal Investigators: Dr. Cynthia Ménard
Princess Margaret Hospital Department of Radiation Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected]
Co-Investigators: Dr. Caroline Chung
Princess Margaret Hospital Department of Radiation Oncology 610 University Avenue, Toronto, Ontario, CANADA M5G 2M9 Email: [email protected]
Dr. Gelareh Zadeh Toronto Western Hospital Department of Neurosurgery 399 Bathurst Street, Toronto, Ontario, CANADA M5T 2S8 Email: [email protected]
Collaborators: UHN– Neurosurgery Dr. Mark Bernstein
UHN Radiation Oncology Dr. Normand Laperriere Dr. Barbara-Ann Millar Dr. Robert Bristow NIH-NCI – Radiation Oncology Branch Dr. Kevin Camphausen Physics – University of Toronto Dr. Warren Foltz Dr. Andrei Damyanovich Dr. Catherine Coolens Dr. Teodor Stanescu Dr. Young-Bin Cho Dr. Mark Ruschin UHN – Neuroradiology Dr. W. Kucharzyk
Schema This will be a single-institution exploratory study of potential imaging and biofluid
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biomarkers measured in 20 patients receiving RT for brain metastases. Each patient will undergo research 3T MRI scans within 1 week and immediately prior to the start of radiation, then follow-up MRIs at 2 days, 7 days, 3 weeks and 6 months after the first dose of radiation. Patients may also be asked to have an additional follow-up research MRI scans up to 5 years of follow-up.
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TABLE OF CONTENTS
Page SCHEMA ........................................................................................................................ iii 1. OBJECTIVES ............................................................................................................. 1 2. BACKGROUND .........................................................................................................1 3. PATIENT SELECTION .......................................................................................... ..2 3.1 Eligibility Criteria ......................................................................................................2 3.2 Exclusion Criteria ..................................................................................................... 2 4. STUDY PROCEDURES .............................................................................................3 4.1 Schema ....................................................................................................................... 3 4.2 Radiotherapy ..............................................................................................................3 4.3 MRI and CT .............................................................................................................. 4 4.4 Biofluid Biomarkers ..................................................................................................5 5. ENDPOINTS .............................................................................................................. 7 5.1 Endpoints ...................................................................................................................7 6. Statistical Methods .................................................................................................... .9 7. Consent .........................................................................................................................9 8. Risks/Benefits................................................................................................................9 9. Pharmaceutical Information......................................................................................10 REFERENCES ............................................................................................................. 11
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1. OBJECTIVES 1.1. Primary Objective: To identify promising imaging and biofluid (urine and serum) predictive biomarkers of response to radiotherapy (RT) in patients with brain metastases 1.2. Secondary Objectives:
1.2.1. Quantify and compare response to RT in tumor perfusion parameters measured with dynamic contrast enhanced MRI (DCE-MRI) and DCECT. 1.2.2. Quantify response to RT in tumor water diffusion characteristics measured with diffusion weighted MRI (DWI, DTI) 1.2.3. Quantify response to RT in tumor metabolite profile measured with magnetic resonance spectroscopy (MRS) 1.2.4. Quantify response to RT in tumor relaxometry measured with quantitative T1, T2, and T2* (or qBOLD) imaging. 1.2.5. Measure biofluid biomarkers of response to RT
1.3. Tertiary Objectives:
1.3.1. Compare early biomarker responses to radiosurgery (RS) vs fractionated RT 1.3.2. Develop and apply robust methods to account for MR image distortions. 1.3.3. Obtain cone-beam CT measures of image quality and set-up accuracy with the stereotactic frame 1.3.4. Obtain optical measures of set-up accuracy with the stereotactic frame 1.3.5. Explore the technical performance of novel MRI techniques
2. BACKGROUND Brain metastases are the most common brain tumors in adult cancer patients [1]. The standard management of brain metastases includes surgery, whole brain radiotherapy and radiosurgery, but response to these treatments vary widely. In order to optimize treatment for each patient, there is a growing need for biomarkers that reflect tumor biology, reflect the mechanism of the therapeutic intervention and predict treatment response. In recent brain tumor studies, several imaging and biofluid biomarkers have shown promise. Changes in perfusion and diffusion MRI metrics have been associated with tumor response to radiosurgery [2, 3] . A composite marker that combined specific circulating markers and MRI measures has shown promise in predicting survival for patients receiving anti-angiogenic therapy for brain tumors [5]. Urine VEGF levels in cancer patients have also been identified as a promising marker that predicts patient survival [6]. Serial measures of serum and urine biomarkers in combination with imaging have not yet
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been evaluated in patients treated with radiosurgery. However, dynamic contrast-enhanced (DCE) MRI measures correlated well with tumor angiogenesis and reflected the effects of anti-angiogenic therapies [4]. We have successfully completed a preclinical study evaluating these biofluid and imaging biomarkers serially in mice treated with Sunitinib and single-fraction radiation. The promising early imaging biomarkers identified at 2 days after radiation included a significant drop in Ktrans from baseline and rise in apparent diffusion coefficient (ADC) from baseline. The candidate biofluid biomarkers include VEGF, EG-VEGF, CXCL4, Angiopoietin-1 and 2, activin A, TIMP-1 and TGF-β. On the basis of these preclinical findings, these promising biomarkers will be evaluated with judicious clinical investigation proposed here. There is an ongoing Phase I study at Princess Margaret Hospital investigating the combination of Sunitinib (anti-angiogenic tyrosine kinase inhibitor) and radiosurgery in patients with 1 to 3 brain metastases (UHN REB ID # 09-0115-C). As part of this study, serial measures of imaging and biofluid biomarkers are being collected. However, the changes in these biomarker measures may be in response to the anti-angiogenic agent, radiosurgery or both treatments. The present study will serially measure response of imaging, serum and urine vascular biomarkers in patients with brain metastases treated with radiosurgery alone. This will provide data on changes in these biomarker measures in response to radiosurgery and will help interpret the changes in biomarker measures in the Phase I study which combines the anti-angiogenic agent with radiosurgery. Ultimately, discovery of a key biomarker that predicts eventual clinical response to treatment will enable us to move towards individualized therapy as this biomarker would help us to select appropriate treatments for particular patients, optimize the timing of each treatment and detect treatment failure early, such that treatment can be adapted in a timely manner to allow for the best possible outcome. 3. PATIENT SELECTION 3.1 Eligibility Criteria
3.1.1 Biopsy proven malignancy (original biopsy is adequate as long as the brain imaging is consistent with brain metastases). 3.1.2 At least one index lesion with diameter > 1cm and without imaging evidence of hemorrhage 3.1.3 Patients age > 18 years of age 3.1.4 Patients planned for RT to brain metastases 3.1.5 Life expectancy > 3 months 3.1.6 No systemic anti-cancer therapy or WBRT within 3 days of RT 3.1.7 Ability to understand and the willingness to sign a written informed consent document.
3.2 Exclusion Criteria
3.2.1 Previous cranial radiation < 6 months prior to RT. 3.2.2 Previous radiosurgery to the index lesion
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3.2.3 Treatment with a non-approved or investigational drug concurrently or within 3 days of RT 3.2.4 Individuals with MRI non-compatible metal in the body, or unable to undergo MRI procedures. 3.2.5 Allergy to gadolinium 3.2.6 Allergy to Iodine Contrast Agent 3.2.7 Glomerular Filtration Rate of less than 30ml.min/1.73m2 as measured by creatinine clearance through the Cockcroft-Gault formula [(140-age) X Mass in kg / 72 X plasma creatinine (mg/dl)]
4. STUDY PROCEDURES 4.1. Schema This will be a single-institution exploratory study of potential imaging and biofluid biomarkers measured in 20 patients receiving RT for brain metastases. Each patient will undergo research 3T MRI scans within 1 week and immediately prior to the start of radiation, then follow-up MRIs at 2 and 7 days after the first dose of radiation and at 3 weeks. Patients may also be asked to have additional follow-up MRI scans on the 3T scanner (instead of routine 1.5T) up to 5 years of follow-up.
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4.2. Radiotherapy 4.2.1. RS will be delivered using Gamma Knife®- (GK) PFX technology as per standard care procedures 4.2.2. RT will be delivered to the whole brain using a Linac as per standard care procedures 4.3. Investigational MRI procedure 4.3.1. General patient preparation and positioning
4.3.1.1. An intravenous line will be placed for contrast injection 4.3.1.2. Patients are placed supine with ear protection
4.3.2. Specific MRI-acquisition protocols
4.3.2.1. The following MRI-acquisitions per scan session will be completed according to the most current imaging protocol:
4.3.2.1.1. Standard Care: 4.3.2.1.1.1. FLAIR with contrast 4.3.2.1.1.2. High resolution, T1-w gradient echo sequence with contrast
4.3.2.1.2. Research Sequences: 4.3.2.1.2.1. Perfusion (dynamic contrast-enhanced, DCE-MRI, dynamic susceptibility contrast, DSC-MRI) 4.3.2.1.2.2. Diffusion (diffusion weighted, DWI; diffusion tensor, DTI) 4.3.2.1.2.3. Spectroscopy (optional) 4.3.2.1.2.4. T1 quantification 4.3.2.1.2.5. T2 quantification (optional) 4.3.2.1.2.6. qBOLD (optional)
4.3.2.2. Imaging protocols will be predetermined by PI or AI depending on clinical and research requirements and the version of the imaging protocol used per scan session will be documented 4.3.2.3. Maximum scan time per session: 90 min
4.4. Investigational CT procedures 4.4.1. Standard Care:
4.4.1.1. Head CT acquisition 4.4.2. Research:
4.4.2.1. Dynamic contrast-enhanced CT (optional) 4.4.2.2. Cone-beam CT (optional)
4.5. MR image distortion: assessment and correction 4.5.1. For an accurate analysis of patient MR image data, the imaging capabilities of the MRI scanner will be investigated. Specifically, the 3D
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distortion field corresponding to the imaging sequences implied for the acquisition of patient data will be determined. 4.5.2. MR image distortion correction methods will be applied to patient data to remove any spatial inaccuracies. This will unlock the use of inter-modality image registration techniques required for a robust quantitative analysis of patient image data. The corrected images will be used for RS planning once accuracy is confirmed. 4.6. Biofluid Biomarkers 4.6.1. A number of blood/urine biomarkers will be evaluated including biomarkers that reflect pro- and anti-angiogenic, invasive and mitogenic pathways, including the VEGF-associated pathways. Analysis will consist of evaluating pre-treatment serum/plasma values with primary and secondary endpoints, as well as comparisons of serial changes in serum/plasma levels over time. 4.6.2. Specimen Collection and Storage
4.6.2.1. Specimen Collection: Blood and urine samples will be collected at 2 baseline time points (between Day -7 and Day 0, after consent then between Day 0 and Day 1, immediately prior to starting radiotherapy), Day 3, Day 7, Day 20-22 and Day 179-181. All specimens should be labeled with study identifier, date, time and time point collected. In effort to protect the patient’s identity in the laboratory, the samples will be identified by a code that can be linked back to the patient by the investigators, but not other laboratory personnel
4.6.2.1.1. Blood - Serum 40cc in four SST (serum separating tubes – Tiger Top) and plasma - four standard vacutainer tubes with sodium citrate. Blood will be centrifuged at 3000rmp for 10 minutes at 4 degree Celsius within 45 minutes of blood collection. Aliquots of Serum and plasma collected through this procedure will be placed in freezer storage tubes (500�l). 4.6.2.1.2. Urine – at least 5cc in a sterile collection cup, however the optimal amount would be 25 cc. Urine Specimens will be stored at a range of –20c to 4c within 2 hours of collection and until processed.
4.6.2.2. Specimen Storage: Blood samples will stored at -80 C and urine samples at -20C in the UHN Neurooncology Tumor Bank. Temporary storage will be allowed in the RMP clinical trials freezers.
4.6.3. Specimen analysis
4.6.3.1. A portion of the blood (and urine) specimens will be analyzed in the laboratory of Dr. Gelareh Zadeh. 4.6.3.2. A portion of the blood (and urine) specimens may be analyzed in the laboratory of Dr. Robert Bristow.
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4.6.3.3. A portion of the blood (plasma and serum) and urine specimens may be sent to the laboratory of Dr. Kevin Camphausen on dry ice for further analysis. Call or email for FEDEX number. Kevin Camphausen, MD Bldg 10, Rm 3B42 Bethesda, MD 20892 301-496-5457 [email protected]
4.6.4. Handling of Specimens and Images collected for Research Purposes
4.6.4.1. Blood and urine samples and imaging data collected in the course of this research project may be banked and used in the future to investigate new scientific questions related to this study. However, this research may only be done if the risks of the new questions were covered in the consent document. 4.6.4.2. No germline mutation testing will be performed on any of the biofluid samples collected unless the patient gives separate informed consent or has expired. 4.6.4.3. At the completion of the protocol, the investigator will dispose of all specimens in accordance with the institutional environmental protection laws, regulations and guidelines. 4.6.4.4. Any loss or unintentional destruction of the samples will be reported to the REB.
4.7. Cone-beam CT measures of set-up accuracy 4.7.1. Measures of image quality and set-up accuracy will be obtained using cone-beam CT before and after each treatment on Perfexion Gamma Knife
4.7.1.1. Cone-beam CT is not yet available on the Perfexion Gamma Knife unit. However, image-guidance by means of a cone-beam CT is used to improve set-up accuracy on linear accelerators. We will use a custom CBCT Class 1 unit mounted on the Perfexion unit and acquire images immediately prior to, and after radiation delivery. If an unacceptable error in set-up is observed using cone-beam CT, adjustments in set-up will be made prior to radiosurgery treatment.
4.7.1.1.1. Cone-beam CT will only be used under safe operating mode. If there are any concerns of safety arise, cone-beam CT images will not be acquired.
4.7.1.2. Extensive retrospective image-analysis will also be done to evaluate image quality and setup accuracy in order to improve the technique. 4.7.1.3. Cone-beam CT will only be used under safe operating mode. If there are any concerns of safety arise, cone-beam CT images will not be acquired.
4.8. Optical measures of set-up accuracy (optional)
4.8.1.1. Optical measures of set-up accuracy (2-4) may be obtained on the day of treatment at various steps including
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4.8.1.1.1. Immediately after frame placement 4.8.1.1.2. Prior to MRI scanning 4.8.1.1.3. Prior to CT scanning 4.8.1.1.4. Prior to radiation delivery
4.9. Supportive Care 4.9.1. In the event that a patient has a reaction (allergic) to the MRI contrast or develops a seizure, all appropriate medical measures will be taken. 4.10. Off Study Criteria 4.10.1. Administrative
4.10.1.1. Patient refuses the procedure or further procedures. 4.10.1.2. It is deemed in the patient’s best interest as determined by the PI. 4.10.1.3. Serious protocol violation as determined by the PI.
4.10.2. Development of a concurrent serious medical condition that precludes the completion of MRI 4.10.3. The patient is unable to complete the MRI procedure for any reason or is non-compliant with MRI requirements. 4.10.4. The patient has undergone a final MRI examination at 5 years of followup. 5 Endpoints 5.1 Primary Endpoint To identify the biomarker(s) that change at least 1 standard deviation from baseline to 2 days, 7 days (or 3weeks) post-radiation in response to radiotherapy. 5.2 Additional Endpoints associated with imaging and biofluid biomarkers 5.2.1 Response Endpoints:
5.2.1.1 Objective (Radiological) Progression: Objective progression is defined as increase in volume of contrast uptake on MRI of > 25% as measured by two perpendicular tumor diameters compared to the smallest measurement ever for the same lesion by the same technique. If increase in size is accompanied by substantial amount of edema, further investigations to distinguish radionecrosis from tumor recurrence are warranted prior to determination of progression (e.g. FDG-PET, MRSI, Surgical resection). Where radionecrosis is confirmed, size progression of the metastasis will not constitute CNS progression of disease. 5.2.1.2 Objective (Radiological) Response: Objective response is defined as stable or reduced volume of contrast uptake on MRI. (ie all nonprogression)
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5.2.2 Additional Endpoints:
5.2.2.1 Time to Intracranial Local Progression is defined as the time interval between the date of first treatment and the date of objective radiological progression of any one of the treated lesions. 5.2.2.2 Time to Intracranial Distant Progression is defined as the time interval between the date of first treatment and the date of new brain metastases, with or without progression of the treated lesions. 5.2.2.3 Brain Progression free survival is defined as the time interval between the date of first treatment and the date of disease progression in the brain or death due to disease in the brain, whichever comes first. If neither event has been observed, then the patient will be censored at the date of the last disease assessment. 5.2.2.4 Late SRS-related toxicity defined as any Gr. 3/4 SRS-related toxicity
5.3 Safety Reporting 5.3.1 Unexpected and/or serious toxicities which are deemed by the PI to be possibly, probably or definitely attributable to the MRI procedure will be reported as follows:
5.3.1.1 Unexpected (i.e., previously unknown) Reactions: 5.3.1.1.1 Grades 2 - 3 should be reported in writing to the UHN REB and PMH DSMB within 7 calendar days. 5.3.1.1.2 Grades 4 - 5 should be reported within 24 hours to UHN REB and PMH DSMB. A written report should follow within 7 calendar days.
5.3.1.2 Serious Adverse Events 5.3.1.2.1 Serious adverse events include any untoward medical occurrence that
5.3.1.2.1.1 Results in death 5.3.1.2.1.2 Is life threatening 5.3.1.2.1.3 Results in significant or persistent disability 5.3.1.2.1.4 Requires inpatient hospitalization 5.3.1.2.1.5 Occurs with an overdose (any dosage higher than that recommended in the protocol or package insert)
5.3.1.2.2 All serious adverse events must be reported to Dr C. Ménard, Principal Investigator of this study and to UHN REB and PMH DSMB within 24 hours using the standard reporting form, available at: http://www.oci.utoronto.ca/reb/docs/SAE_InternalReportingFo rm_29Jul04_Final.doc 5.3.1.2.3 A comprehensive, follow-up report will be submitted to the REB within 7 calendar days of the date that study staff is aware of the SAE.
6 Statistical Methods This is a pilot study in 20 patients that aims to identify, with 80% power, imaging biomarkers that have a change of greater than 1 standard deviation from baseline at 2
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days, 7 days or 3 weeks after initiating radiation. Two-tailed paired t-tests with an α level of 0.05 will be used to perform analyses. If descriptive statistics suggests a relationship between the magnitude of biomarker response and clinical outcome, analysis to evaluate correlation between biomarker response and outcome (survival, tumor control/response) will be completed. Changes in blood biomarkers will be evaluated with descriptive statistics in order to identify candidate markers for further investigation in a larger prospective study. 7 Consent Process/ Patient Eligibility The Principal Investigator and associates will recruit patients. The purpose and objectives of this study, the procedures involved, and the attendant risks and discomforts will be carefully explained to the patient. A signed informed consent document will be obtained by the research associate or research therapist. It is our goal to be as explicit as possible in verbal and written consent procedures to insure that all participants are joining the study without coercion. Patients who cannot give informed consent (i.e. mentally incompetent patients, or those physically incapacitated such as comatose patients) are not to be recruited into the study. Patients competent but physically unable to sign the consent form may have the document signed by their nearest relative or legal guardian. Each patient will be provided with a full explanation of the study before consent is requested. 8 Risks/Benefits 8.1 Risks of outcome evaluations: Additional time may be required during the patient’s follow-up visit in order to complete study related outcomes assessments. However, no additional follow-up visits are expected beyond standard care practice. 8.2 Risks of Intravenous Access: Drawing a blood sample will involve minimal discomfort to the patient and can occasionally result in mild soreness. This may rarely lead to superficial thrombophlebitis in less than 5% of patients. 8.3 Risks of MRI and IV gadolinium contrast administration: The risk of a mild reaction to the contrast agent such as nausea or itching or skin rash is 1-2%. The risk of a serious life threatening allergic reaction is extremely rare (< 1 in 100,000). New reports have identified a possible link between Nephrogenic Systemic Fibrosis or Nephrogenic Fibrosing Dermopathy (NSF/NFD) and exposure to gadolinium containing contrast agents used at high doses in patients with kidney failure. Patients in this study are evaluated prior to entry for renal failure. There is no known radiation exposure from MRI. The MRI will take 30- 45 minutes. 8.4 Risks of CT and IV iodine contrast administration: Patients are exposed to
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additional radiation due to the research CT scan. But with doses of <12 rem to the region scanned, there is minimal additional risk contributed by the radiation from these CT scans in who will be treated with therapeutic radiation. With IV iodine contrast injection, The risk of a mild reaction to the contrast agent such as nausea or itching or skin rash is 1-2%. The risk of a serious life threatening allergic reaction is extremely rare (< 1 in 100,000). The CT scan will take 20-30 minutes. 8.5 Risks of optical tracking: Patients may experience discomfort with table motion and frame adjustment involved with optical tracking. In the unlikely event that one of the extra devices used for optical tracking interfere with the treatment unit, equipment malfunction may occur. Malfunctions will be immediately apparent and addressed, and may result in a delay of treatment. It is highly unlikely that treatment cannot be delivered because of such an event. 8.6 Risks of using distortion corrected imaging for planning: Images are currently corrected for geometric accuracy using standard commercial software. We plan to improve upon the current standard so that the edges of tumors are not underdosed. However, it is possible that our solution may not improve, or may even reduce the accuracy of the images. If that occurs, the edges of tumors may be underdosed a bit more, which may cause the tumor to grow back and need more treatment. This even is expected to be highly unlikely (<1%). 8.7 Risk of using a new custom cone-beam CT device: Patients are exposed to additional radiation dose of up to 4cGy due to the cone-beam CT. But in patients who will be treated with therapeutic radiation, there is minimal additional risk contributed by the cone-beam CT scans. The safety of this device has been carefully evaluated by our team, including the risks of collisions, malfunctioning, and dose of additional radiation exposure. This information is available in our in-house safety document, if requested. This device will only be used under safe operating mode. 8.8 Patients will be exposed to a CBCT dose up to 4 cGy. 9 Pharmaceutical Information 9.1 MRI contrast agent – Gadopentate dimeglumine Manufacturer: GE Health Care Commercial name: Omniscan Description: This is an FDA approved contrast agent in widespread use. Gadolinium produces MR contrast by altering the relaxivity of neighbouring water protons. Form: Gadopentate dimeglumine is available as Gd-DTPA. It is available as a sterile injectable liquid in single use ampules of 20 ml. The inactive ingredients are meglumine and diethylenetriamine pentaacetic acid. Supply: Omniscan is commercially available and will be supplied by the Department of Radiology, TWH.
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Toxicities: The serious reaction rate (asthma, hives, seizures, hypotension) is less than 0.5%. The dose is 0.1 mmol/kg BW administered IV bolus via mechanical injector. There are no contraindications for its use. Gd-DTPA can be used in patients with elevated Cr. Levels and does not have known nephrotoxicity. Possible complications relate to extravasation of contrast in which localized swelling and pain may develop but because of the small volume (20cc) this does not lead to skin necrosis. There may be headache, nausea, vomiting, and transient sensations of heat or cold or taste disturbances following injection of gadopentetate. 9.2 CT contrast agent – Iodixanol injection USP 320 mg I/mL Manufacturer: GE Health Care Commercial name: Visipaque 320 Description: This is an FDA approved non-ionic radiographic contrast agent in widespread use. Iodixanol increases x-ray absorption and thereby increases the density of enhancement on CT proportionally to the iodine content present. Form: Iodixanol is available as a sterile injectable solution in 50, 100, 250 mL bottles. Sodium chloride and calcium chloride have been added to create and isotonic solution for injection. Visipaque 320 contains 0.044 mg calcium chloride dehydrate per mL and 1.11 mg sodium chloride per mL, providing for both concentrations a sodium/calcium ratio equivalent to blood. It also contains tromehtmaine, edentate calcium disodium and hydrochloric acid to adjust pH between 6.8 and 7.7. Supply: Visipaque is commercially available. Toxicities: The serious reaction rate (asthma, hives, seizures, hypotension) is less than 0.5%. The most frequent adverse reactions, which occurred in 1 to 3.4% of patients, were taste perversion (3.4%), nausea (2.8%), vertigo (2.4%), headache (2.3%), rash/erythematous rash (2.1%), pruritus (1.6%), chest pain (1.1%) and scotoma (1.1%). Less than 1% of patients had injection site pain or local injection site reaction or other more serious reactions. Possible complications relate to extravasation of contrast in which localized swelling and pain may develop but because of the small volume (20cc) this does not lead to skin necrosis VISIPAQUE (iodixanol) should not be administered to patients with known or suspected hypersensitivity to iodixanol. Although there is no contraindication to administering Visipaque to patients with elevated creatinine, additional risk is present and therefore a careful benefit/risk ratio should be considered prior to proceeding with administration.
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