1. health and fitness
2. disease
3. cancer

Digital Comprehensive Summaries of Uppsala Dissertations
from the Faculty of Medicine 1125
Affibody Molecules for PET
Imaging
JOANNA STRAND
ACTA
UNIVERSITATIS
UPSALIENSIS
UPPSALA
2015
ISSN 1651-6206
ISBN 978-91-554-9299-1
urn:nbn:se:uu:diva-259410
Dissertation presented at Uppsala University to be publicly examined in Fåhraeussalen,
Rudbecklaboratoriet, Dag Hammarskjölds väg 20, 751 85, Uppsala, Saturday, 3 October 2015
at 09:00 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will
be conducted in English. Faculty examiner: Professor Sten Nilsson (Karolinska institutet,
institutionen för onkologi-patologi).
Abstract
Strand, J. 2015. Affibody Molecules for PET Imaging. Digital Comprehensive Summaries of
Uppsala Dissertations from the Faculty of Medicine 1125. 70 pp. Uppsala: Acta Universitatis
Upsaliensis. ISBN 978-91-554-9299-1.
Optimization of Affibody molecules would allow for high contrast imaging of cancer associated
surface receptors using molecular imaging. The primary aim of the thesis was to develop
Affibody-based PET imaging agents to provide the highest possible sensitivity of RTK detection
in vivo. The thesis evaluates the effect of radiolabelling chemistry on biodistribution and
targeting properties of Affibody molecules directed against HER2 and PDGFRβ. The thesis is
based on five published papers (I-V).
Paper I. The targeting properties of maleimido derivatives of DOTA and NODAGA for sitespecific labelling of a recombinant HER2-binding Affibody molecule radiolabelled with 68Ga
were compared in vivo. Favourable in vivo properties were seen for the Affibody molecule with
the combination of 68Ga with NODAGA.
Paper II. The aim was to compare the biodistribution of 68Ga- and 111In-labelled HER2targeting Affibody molecules containing DOTA, NOTA and NODAGA at the N-terminus. This
paper also demonstrated favourable in vivo properties for Affibody molecules in combination
with 68Ga and NODAGA placed on the N-terminus.
Paper III. The influence of chelator positioning on the synthetic anti-HER2 affibody
molecule labelled with 68Ga was investigated. The chelator DOTA was conjugated either at
the N-terminus, the middle of helix-3 or at the C-terminus of the Affibody molecules. The Nterminus placement provided the highest tumour uptake and tumour-to-organ ratios.
Paper IV. The aim of this study was to evaluate if the 68Ga labelled PDGFRβ-targeting
Affibody would provide an imaging agent suitable for PDGFRβ visualization using PET. The
68
Ga labelled conjugate provided high-contrast imaging of PDGFRβ-expressing tumours in vivo
using microPET as early as 2h after injection.
Paper V. This paper investigated if the replacement of IHPEM with IPEM as a
linker molecule for radioiodination of Affibody molecules would reduce renal retention of
radioactivity. Results showed that the use of the more lipophilic linker IPEM reduced the renal
radioactivity retention for radioiodinated Affibody molecules.
In conclusion, this thesis clearly demonstrates that the labelling strategy is of great importance
with a substantial influence on the targeting properties of Affibody molecules and should be
taken under serious considerations when developing new imaging agents.
Keywords: Affibody molecules, Molecular imaging, PET, Radiolabelling, HER2, PDGFRβ
Joanna Strand, Department of Immunology, Genetics and Pathology, Rudbecklaboratoriet,
Uppsala University, SE-751 85 Uppsala, Sweden.
© Joanna Strand 2015
ISSN 1651-6206
ISBN 978-91-554-9299-1
urn:nbn:se:uu:diva-259410 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-259410)
To my parents, for their endless
love, support and encouragement.
List of Papers
This thesis is based on the following papers, which are referred to in the text
by their Roman numerals.
I
II
III
IV
V
Altai, M.,* Strand, J.,* Rosik, D., Selvaraju, R.K., Karlström, A.,
Orlova, A., Tolmachev, V. (2013). Influence of nuclides and chelators on imaging using Affibody molecules: comparative evaluation
of recombinant Affibody molecules site-specifically labeled with
68
Ga and 111In via maleimido derivatives of DOTA and NODAGA.
Bioconjug Chem., 24:1102-9
Strand, J., Honarvar, H., Perols, A., Orlova, A., Selvaraju, R.K.,
Eriksson Karlström, A., Tolmachev, V. (2013). Influence of macrocyclic chelators on the targeting properties of 68Ga-labeled synthetic
Affibody molecules: Comparison with 111In-labeled counterparts.
PLoS ONE, 8:e70028
Honarvar, H., Strand, J., Perols, A., Orlova, A., Selvaraju, R.K.,
Eriksson Karlström, A., Tolmachev, V. (2014). Position for sitespecific attachment of a DOTA chelator to synthetic affibody molecules has a different influence on the targeting properties of 68Gacompared to 111In-labeled conjugates. Mol Imaging, 13:1-12.
Strand, J., Varasteh, Z., Eriksson, O., Abrahmsen, L., Orlova, A.,
Tolmachev, V. (2014). Gallium-68-labeled affibody molecule for
PET imaging of PDGFRbeta expression in vivo. Molecular Pharmaceutics, 11:3957-64
Strand, J., Nordeman, P., Honorvar, H., Altai M., Larhed, M., Orlova, A., Tolmachev, V. (2015). Site-specific radioiodination of
HER2-targeting affibody molecules using 4-iodophenetylmaleimide
decreases renal uptake of radioactivity. ChemistryOpen, 4:174-82
* Equal contribution.
Reprints were made with permission from the respective publishers.
Related papers not included in this thesis:
I
Altai, M., Honarvar, H., Wållberg, H., Strand, J., Varasteh, Z., Rosestedt, M., Orlova, A., Dunås, F., Sandström, M., Löfblom, J.,
Tolmachev, V., Ståhl, S. (2014). Selection of an optimal cysteinecontaining peptide-based chelator for labeling of affibody molecules
with (188)Re. Eur J Med Chem., 87:519-28.
II
Altai, M., Wållberg, H., Honarvar, H., Strand, J., Orlova, A., Varasteh, Z., Sandström, M., Löfblom, J., Larsson, E., Strand, S.E.,
Lubberink, M., Ståhl, S., Tolmachev, V. (2014). 188Re-ZHER2:V2, a
promising affibody-based targeting agent against HER2-expressing
tumors: preclinical assessment. J Nucl Med., 55:1842-8.
III
Orlova, A., Malm, M., Rosestedt, M., Varasteh, Z., Andersson, K.,
Selvarajum, R.K., Altai, M., Honarvar, H., Strand, J., Ståhl, S.,
Tolmachev, V., Löfblom, J. (2014). Imaging of HER3-expressing
xenografts in mice using a (99m)Tc(CO) 3-HEHEHE-Z
HER3:08699 affibody molecule. Eur J Nucl Med Mol Imaging.
41:1450-9.
IV
Rosik, D., Thibblin. A., Antoni. G., Honarvar. H., Strand. J., Selvaraju, R.K., Altai, M., Orlova. A., Eriksson Karlström, A., Tolmachev, V. (2014). Incorporation of a triglutamyl spacer improves the
biodistribution of synthetic affibody molecules radiofluorinated at
the
N-terminus
via
oxime
formation
with
(18)F-4fluorobenzaldehyde. Bioconjug Chem.,. 25:82-92.
V
Hofström, C., Altai, M., Honarvar, H., Strand, J., Malmberg, J.,
Hosseinimehr, S.J., Orlova, A., Gräslund, T., Tolmachev, V. (2013).
HAHAHA, HEHEHE, HIHIHI, or HKHKHK: influence of position
and composition of histidine containing tags on biodistribution of
[(99m)Tc(CO)3](+)-labeled affibody molecules. Med Chem.,
56:4966-74.
VI
Orlova, A., Hofström, C., Strand, J., Varasteh, Z., Sandstrom, M.,
Andersson, K., Tolmachev, V., Gräslund, T.J. (2013).
[99mTc(CO)3]+-(HE)3-ZIGF1R:4551, a new Affibody conjugate for
visualization of insulin-like growth factor-1 receptor expression in
malignant tumours. Eur J Nucl Med Mol Imaging. 40:439-49.
VII
Perols, A., Honarvar, H., Strand, J., Selvaraju, R., Orlova, A., Karlström, A.E., Tolmachev, V. (2012). Influence of DOTA chelator position on biodistribution and targeting properties of (111)In-labeled
synthetic anti-HER2 affibody molecules. Bioconjug Chem., 23:166170.
VIII
Evans-Axelsson, S., Ulmert, D., Örbom, A., Peterson, P., Nilsson O.,
Wennerberg, J., Strand J., Wingårdh, K., Olsson, T., Hagman, Z.,
Tolmachev, V., Bjartell, A., Lilja, H., Strand, S.E. (2012). Targeting
free prostate-specific antigen for in vivo imaging of prostate cancer
using a monoclonal antibody specific for unique epitopes accessible
on free prostate-specific antigen alone. Cancer Biother Radiopharm.,
27:243-51.
Contents
Cancer ........................................................................................................... 11
RTK .......................................................................................................... 12
HER2 ................................................................................................... 13
PDGFRβ .............................................................................................. 14
Investigation and diagnosis of cancer ...................................................... 15
Cell/tissue sampling ............................................................................. 15
Cancer staging ..................................................................................... 16
Treatment response monitoring ................................................................ 17
Radionuclide molecular imaging.............................................................. 19
Planar scintillation camera imaging..................................................... 19
SPECT ................................................................................................. 19
PET ...................................................................................................... 20
Imaging agents ......................................................................................... 22
18
F-FDG ............................................................................................... 22
Protein-based imaging agents................................................................... 23
Antibodies and antibody fragments ..................................................... 23
Natural peptide ligands ........................................................................ 24
Engineered scaffold protein-based binders .......................................... 25
Affibody molecules ............................................................................. 25
Factors affecting imaging sensitivity and specificity ............................... 27
Size and Affinity .................................................................................. 27
Labelling procedures ........................................................................... 28
Role of radiocatabolites ............................................................................ 30
Aim of the thesis work .................................................................................. 32
Methodology ................................................................................................. 33
Results ........................................................................................................... 36
Paper I .................................................................................................. 36
Paper II ................................................................................................ 40
Paper III ............................................................................................... 43
Paper IV ............................................................................................... 48
Paper V ................................................................................................ 52
Concluding remarks ...................................................................................... 56
Ongoing and future studies ........................................................................... 58
Acknowledgements ....................................................................................... 60
References ..................................................................................................... 63
Cancer
Cancer constitutes a group of approximately 200 different types of diseases,
all with different molecular mechanisms. Nonetheless, there are certain
common characteristics for all types of cancer, such as sustained proliferative signalling, evasion of growth suppression, resistance to apoptosis, induced angiogenesis and activation of invasion and metastasis. These hallmarks of cancer are reviewed in detail by Hanahan et al. (2011).
Cancer is associated with genomic instability, which may transform normal genes (proto-oncogenes) that promote cell growth and survival into tumour-inducing genes (oncogenes). The causes of transformation include, for
example, a deletion or point mutation in a coding sequence, chromosomal
rearrangement or gene amplification. Gene amplification results in the overexpression of certain types of cell-surface proteins, e.g., receptor tyrosine
kinases (RTK), G-protein coupled receptors or cell adhesion molecules.
Many of these cell-surface proteins serve as targets for anti-cancer drugs.
However, these targets are not expressed on all malignant cells. In fact,
there is great phenotypic variability among malignant cells within the same
tumour (intra-tumour heterogeneity), as well as between a primary tumour
and metastatic sites (inter-tumour heterogeneity). Furthermore, patients with
the same type of cancer do not always express the same type of phenotypic
features, resulting in inter-tumour heterogeneity among patients (Figure 1)
(Marusyk & Almendro, 2012).
Tumour heterogeneity requires that one must tailor treatment to each individual patient to get an effective treatment response and to avoid unnecessary treatments, this necessitates detection of targets (e.g., RTK) for each
individual patient.
11
Figure 1. Different types of tumour heterogeneity 1. Inter-tumour heterogeneity
(between patients) 2. Inter-tumour heterogeneity (between primary and metastatic
sites) 3. Intra-tumour heterogeneity (within tumours)
RTK
Receptor tyrosine kinases comprise a family of receptors with twenty subfamilies, e.g., class I (the Human epidermal growth factor receptor family),
class II (the Insulin receptor family) and class III (the Platelet-derived
growth factor receptor family). An RTK typically consists of an extracellular
domain for ligand binding, a hydrophobic transmembrane domain, and a
cytosolic domain for signalling (the kinase domain). Normally, ligand binding to an RTK induces receptor activation, followed by the activation of
downstream signalling pathways. Signalling from RTKs promotes cell survival, proliferation, motility, angiogenesis and differentiation. (Lemmon &
Schlessinger, 2010)
In this thesis, agents for imaging two RTK targets human epidermal growth
factor receptor 2 (HER2), and platelet-derived growth factor receptor β
(PDGFRβ), were investigated.
12
HER2
There are four members of the HER family: HER1, HER2, HER3 and
HER4. Interestingly, in contrast to its sister receptors, HER2 do not bind to
any known ligand; instead, HER2 forms heterodimers with ligand-bound
HER1, HER3 or HER4. Subsequent activation of intracellular tyrosine kinases initiates downstream singling pathways (regulating proliferation, apoptosis, migration and differentiation).
The gene coding for HER2 can convert into an oncogene via gene amplification, resulting in the overexpression of HER2 on the cell membrane
(Yarden, 2001). HER2 gene amplification is observed in 20-30 % of breast
cancers (Yarden, 2001) 2-76 % of epithelial ovarian cancers (SerranoOlvera, Dueñas-González, Gallardo-Rincón, Candelaria, Garza-Salazar,
2006), 0-30 % of colorectal cancers (NathansonCulliford,Shia, Chen,
D'Alessio, Zeng, 2003), 8 % of prostate cancers (Edwards, Mukherjee, Munro, Wells, Almushatat, 2004) and 2-23 % of non-small cell lung
cancers (Swanton, Futreal, Eisen, 2006).
Because HER2 overexpression is relatively particular to tumours, specific
HER2 targeting agents such as antibodies (trastuzumab, pertuzumab) or tyrosine kinase inhibitors (TKIs) (lapatinib) are suitable cancer therapies. TKIs
act intracellularly by blocking intracellular receptor tyrosine kinase sites. In
contrast, monoclonal antibodies act extracellularly by initiating antibodydependent cellular cytotoxicity and antibody-dependent complement toxicity, blocking receptor dimerization and the forced internalization of HER2
(Arteaga, Sliwkowski, Osborne, Perez, Puglisi, Gianni 2011). The antitumour action of antibodies might be further improved by the conjugation of
cytotoxic drugs or radionuclides (Wu & Senter, 2005; Arteaga et. al 2011).
Because only tumours with HER2 overexpression may respond to HER2
targeting therapies, measurement of the HER2 expression level is required
for optimal treatment planning, so-called personalized therapy. Indeed, the
benefit associated with HER2 measurement has led the American Society of
Clinical Oncology to issue the recommendation that HER2 expression
should be evaluated in patients with invasive breast cancer (Wolff et al.
2013).
13
PDGFRβ
The platelet-derived growth factor receptor (PDGFR) family consists of two
transmembrane tyrosine kinase receptors: PDGFRα and PDGFRβ. Ligand
binding triggers receptor dimerization and downstream signalling, resulting
in cell migration, survival and proliferation (Heldin & Westermark 1990). In
contrast to HER2, PDGFRβ is expressed at a certain levels in normal tissues
(Heldin & Westermark 1990).
The PDGFR family is associated with cancer development, e.g., through
overexpression of the receptors. PDGFRβ overexpression has been found in
prostate cancer, breast cancer and non-small cell lung cancer (Heldin, 2013).
Moreover, PDFGRβ mRNA expression has been demonstrated to predict
prostate cancer recurrence (Singh et al, 2002). Recently, Hanahan et al.
(2011) have suggested that the “tumour microenvironment” which includes
stromal cells, e.g., fibroblasts and pericytes, contribute to the acquisition of
the cancer hallmarks. Interestingly, the presence of tumour stroma cells expressing PDGFRβ has been shown to correlate with a poor prognosis in
breast and prostate cancer (Paulsson et al, 2009; Hägglöf, Hammarsten,
Josefsson, 2010). It has also been demonstrated that inhibiting PDGF receptors on fibroblasts causes a reversible reduction of the interstitial fluid pressure (IFP) of tumours. Importantly, PDGFR inhibition resulted in improved
tumour uptake of a tumour-targeting antibody, presumably due to reduced
IFP (Östman & Heldin, 2007).
These data indicate that targeting PDGFRβ may prolong the survival of
cancer patients, consequently several monoclonal antibodies and TKItargeting PDGFRβ are currently under investigation as potential targeting
drugs for cancer therapy (Ogawa et al 2010; Shen et al. 2009; Stacchiotti et
al. 2012).
There are also several other pathological conditions involving the expression of PDGFRβ, such as atherosclerosis and various fibrotic diseases
(Heldin, 2014).
In conclusion, PDGFRβ and HER2 are promising targets for several
treatments, and detection of HER2 and PDGFRβ could aid in diagnosis and
identification of patients who would most likely benefit from treatment and in
the monitoring of treatment response.
14
Investigation and diagnosis of cancer
Cell/tissue sampling
Tissue sampling (histology) or cell sampling (cytology) are the current cornerstones of cancer diagnosis. A tissue sample or biopsy can be extracted via
open surgery, transcutaneously or endoscopically, and cell sampling is
achieved through transcutaneous needle aspiration.
However, cell or tissue sampling is invasive, with risk of severe adverse
events such as sepsis, bleeding or tissue damage. Furthermore, there is also a
risk of missing the tumour tissue during biopsy sampling due to tumour inaccessibility, e.g., when biopsying prostate cancer in the prostate gland.
Another shortcoming of tissue and cell sampling methods is that only few
samples with small volumes can be collected from limited number of sites,
which is associated with the risk of retrieving a sample that does not represent the entire tumour due to intra-tumour expression heterogeneity
(Marusyk et al, 2012; Choong et al. 2007).
After tissue sampling, the following methods are usually performed on the
tissue sample:
1. Histochemistry (characterization of morphology)
2. Immunohistochemistry (detection of specific proteins)
3. Molecular pathology (gene analysis)
The morphology of a tissue sample is obtained through histological staining
(histochemistry). When assessing morphology, particular features are of
interest, such as tumour invasiveness, infiltration into surrounding tissue,
cell atypia, cell proliferation, necrosis and cell differentiation. These properties grade the malignancy of the tumour and are associated with tumour
growth.
Immunohistochemistry (IHC) is based on the visualization of specific antibody-antigen interactions. The more antigen present, the stronger the staining in the sample, and a subjective interpretation of protein expression can
be made (Laudadio, Quigley, Tubbs, Wolff, 2007). IHC provides information about tumour origin (e.g., the presence of PSA), tumour type (e.g.,
the presence of p63), tumour classification (e.g., the presence CD3) or treatment prediction (e.g., the presence HER2). IHC is the most important primary technique applied to determine RTK status, especially HER2 expression.
The advantages of this technique are its fast and easy performance and
relatively low cost. Regardless, differences in antigen recovery, tissue processing, result interpretation and methodology are all associated with its
reduced reliability (Press et al, 2005; Dei Tos & Ellis 2005; Laudadio et al,
2007; Rhodes et al. 2002)
15
According to DAKO guidelines, the amount of HER2 staining is usually
scored as follows (dako.com, 2015):
• 0 (negative)
• 1+ (negative, a faint perceptible membrane signal)
• 2+ (weak positive, weak intensity in more than 10 % of the tumour cells)
• 3+ (strong positive, strong positive membrane staining in more
than 10 % of tumour cells).
If a tissue sample is scored 3+, the patient will be recommended for
trastuzumab therapy. Further analysis is required for patients with a 2+ score
(Wolff, et al 2013).
Additional analysis usually includes molecular pathology, e.g., fluorescent in situ hybridization (FISH) (Wolff, et al 2013), which provides information about gene amplification, deletion or translocation. Unfortunately,
florescence fades over time, limiting the shelf life of slides. Moreover, the
cost is higher than for IHC, and FISH requires more cumbersome laboratory
procedures.
Other promising molecular pathology techniques include chromogenic in
situ hybridization (CISH), silver in situ hybridization (SISH) and multiplex
ligation-dependent probe amplification (MLPA) (Moelans, de Weger, Van
der Wall, van Diest, 2011).
Cancer staging
Based on the results of tissue sample analysis, the primary tumour is classified according to origin, features, malignancy and invasiveness. If the tumour proves to be malignant and invasive, haematogenic and lymphogenic
spread to other organs/tissues is investigated via dissection of adjacent
lymph nodes and imaging techniques (CT/MRI/molecular imaging).
The results from tissue sample analysis and imaging are then compiled into a tumour staging system, the TNM system. The system describes tumour
invasiveness to surrounding tissue (T), spread to lymph nodes (N), and distant metastases (M). Although the TNM stage indicates prognosis and directs
initial treatment (Burke & Henson, 1993), it provides no information regarding the expression of cancer-related molecular aberrations (e.g., RTKs) in
distant metastases.
16
Treatment response monitoring
Repetitive biopsy sampling is not suitable for routine treatment response
monitoring. Instead, morphological imaging (CT or MRI) and the use of
Response Evaluation Criteria in Solid Tumours (RECIST) are currently used
to monitor response to treatment.
RECIST is based on one-dimensional lesion measurement criteria: first,
the longest diameter (LD) of each target lesion on an CT is measured, and
then the sum of the longest diameters (SLDs) is calculated for all selected
tumours. There should be a minimum of 30 % decrease in the SLD for a
partial response (PR) (Eisenhauer et al. 2009).
However, morphological imaging and RECIST are not optimal for response monitoring, as many anti-RTK medicines are rather cytostatic than
cytotoxic and stabilization of the disease might prolong survival but does not
result in tumour shrinkage (Contractor & Aboagye, 2009). Additionally,
therapy response might be associated with cell necrosis, and CT cannot distinguish between necrotic and physiologically active tissues
(Bodei, Sundin, Kidd, Prasad, Modlin, 2015).
In response to therapy, biochemical changes at a cellular level precede
anatomical changes. Therefore, imaging of a cancer-related aberrations such
as receptor overexpression (e.g., HER2, PDGFRβ) is highly desirable as an
alternative to morphological imaging for therapy response monitoring.
In conclusion, adding information about receptor expression in tumours via
a non-invasive method to existing methods for patient stratification (biopsy
analysis) and therapy response monitoring could improve therapy personalization (Figure 2).
17
Figure 2. A flow chart of the steps included in the investigation, diagnosis and
treatment of cancer and those steps where radionuclide molecular imaging could
add information.
18
Radionuclide molecular imaging
Radionuclide molecular imaging is based on the detection of imaging probes
labelled with positron- or gamma-emitting radionuclides.
There are mainly three clinical radionuclide imaging modalities: planar
scintillation camera imaging, single-photon emission tomography (SPECT)
and positron emission tomography (PET). Some main properties of PET and
SPECT imaging are given in Table 1.
Table 1. PET and SPECT camera properties
Spatial
Quantification
Sensitivity
Availability Cost
Modality
resolution
capability
(mm)
PET
4-8
pmol
Straightforward
+
High
SPECT
7-15
nmol
Cumbersome
++
Medium
Planar scintillation camera imaging
Planar scintillation camera imaging relies on the detection of emitted photons, mostly with energies in the range of 50-400 keV, with detection by a
large NaI(Tl) crystal. To localize the distribution of activity, a parallel-hole
collimator is usually placed in front of the detector; in preclinical imaging,
pinhole collimators are used to achieve a better spatial resolution. Detection
is governed by the system’s spatial, energy and time resolution. The spatial
resolution is determined by the collimator design: large holes will give high
sensitivity but low spatial resolution, whereas small long holes will give a
better spatial resolution but with low sensitivity (Strand et al. 2013).
Quantification in planar scintillation camera imaging is problematic due
to an absence of information on the activity depth and thickness and therefore has limited possibility for accurate attenuation correction. Additionally,
because of the 2-D technique, overlapping of organs and tissues will hamper
quantification.
SPECT
By rotating single or multiple scintillation camera-heads around the patient,
a number of projections are recorded, and tomographic information can be
obtained. By using dedicated reconstruction programs, 3D-activity distribution can be obtained. Compared to planar imaging, much better image contrast is obtained, and activity quantification is possible. Similar to planar
imaging, the choice of collimator governs the sensitivity and spatial resolution. Quantification can be performed when using attenuation and scatter
corrections, and the accuracy can be on the order of 10-20 %
(Sjögreen, Ljungberg, Strand, 1996) (Rahmim & Zaidi, 2008).
19
Some common radionuclides used in planar and SPECT imaging are given in Table 2. All of them decay with the emission of photons with energies
that are suitable for detection with collimated cameras.
PET
PET imaging relies on the following technique: a positron-emitting radionuclide
emits a positron during β+ decay. The
positron travels a short distance in tissue (a
few millimetres) and undergoes multiple
collisions with electrons in the medium,
losing energy, and finally annihilates with
an electron. This results in two highenergy photons (511 keV) emitted in nearly opposite directions (Figure 3). The photons can be simultaneously detected (coin- Figure 3. Illustration of positron
cidence detection) by opposite detector emission and positron-electron
annihilation.
pairs in a PET camera.
The distance from the emission point to
the annihilation point depends on the medium’s stopping power, i.e., the
density of the medium and the positron’s kinetic energy. Radionuclides that
emit positrons with lower kinetic energy will generate better spatial resolution due to their shorter range.
PET cameras are built with ring geometry, meaning that the detectors
completely encircle the patient. Multiple rings are used, which enhances the
field of view. Because no collimators are used, the sensitivity is much higher
for PET than for SPECT imaging (2-3 orders of magnitude) (Tolmachev &
Stone-Elander, 2010; Frey, Humm, Ljungberg, 2011).
The most commonly used short-lived positron-emitting radionuclides for
PET imaging are 18F, 15O, 13N and 11C; among these, 18F is by far the most
utilized. The production, radiochemistry and synthesis of 11C, 18F, 15O and
13
N radiopharmaceuticals require a cyclotron in a radiation-shielded facility
and a radiopharmaceutical laboratory, which are associated with high costs.
Furthermore, radionuclides with very short half-lives such as 11O and 13N
also require that the PET camera is located nearby. 18F, in contrast, can be
transported to a PET centre located within several hundred kilometres from
the cyclotron.
Conversely, 68Ga, which is a relatively recent addition to the short-lived
PET radionuclides, is generator produced, and the availability of a generator
in the clinic might reduce costs and facilitate the preparation of PET tracers
(Velikyan, 2013).
In Table 2, some of the available radionuclides for PET imaging are presented.
20
Table 2. An overview of selected radionuclides used for radionuclide molecular imaging today. (National nuclear data centre, 2015)
Nuclide
Half-life
Imaging modality
Production
Emission
11
C
20 min
PET
Cyclotron
β+ 98 %
13
N
10 min
PET
Cyclotron
β+ 100 %
Ga
67.6 min
PET
Generator
β+ 89 %
68
18
F
109.8 min
PET
Cyclotron
β+ 97 %
44
Sc
3.97 h
PET
Generator
β+ 94%
64
Cu
12.7 h
PET
Cyclotron
β+ 18 %
86
Y
14.7 h
PET
Cyclotron
β+ 33 %
76
Br
16.2 h
PET
Cyclotron
β+ 54 %
55
Co
17.5 h
PET
Cyclotron
β+ 76 %
78.4 h
PET
Cyclotron
β+ 23 %
I
4.17 d
PET
Cyclotron
β+ 23 %
Tc
6h
SPECT
Generator
140 keV γ 89 %
I
13.2 h
SPECT
Cyclotron
159 keV γ 83 %
In
2.8 d
SPECT
Cyclotron
171 keV γ 90.6 %
245 keV γ 94.1 %
89
Zr
124
99m
123
111
21
Imaging agents
The concept of molecular imaging relies on the highly specific molecular
recognition of expressed gene products, e.g., cell-surface receptors, by imaging agents. Efficient tumour imaging requires the unusual expression of
these target molecules by tumours and their absence or low expression in
normal tissues. Examples of imaging agents are antibodies, receptor ligands,
peptides, small molecules, and affinity proteins. In addition to a targetrecognizing moiety, an imaging agent should carry a suitable radionuclide,
and the half-life of the attached radionuclide should be compatible with the
biological half-life of the imaging agent (Lundqvist & Tolmachev 2002).
18
F-FDG
The most frequently used imaging agent for PET in clinics is 18F-2-fluoro-2deoxyglucose (18F-FDG), a glucose analogue taken up by cells in proportion
to their rate of glucose metabolism (Podoloff et al. 2009). As tumour cells
often have upregulated glucose metabolism, the uptake of 18F-FDG by tumours is higher than that of normal tissues and organs.
In oncology, 18F-FDG PET-imaging is very helpful in diagnosis, staging,
treatment monitoring and treatment planning (Hillner et al. 2008; Podoloff et
al. 2009). However, false-positive outcomes due to high glucose uptake can
arise from high muscle activity, trauma, infection, inflammatory diseases,
and benign tumours.
Although 18F-FDG enables the localization of tumours and/or metastases,
it does not provide information concerning the expression of molecular targets, which is essential for both patient stratification for targeted therapies
and the monitoring of response to such therapy.
22
Protein-based imaging agents
Transmembrane receptor overexpression on malignant cells enables the use
of protein-based imaging agents, e.g., antibodies, antibody fragment, natural
proteinaceous ligands or scaffold protein-based binders (Altai, Orlova, Tolmachev, 2014).
Antibodies and antibody fragments
Radiolabelled monoclonal antibodies (Figure 4), mAbs (approximately 150
kDa), have long been considered as potent imaging agents due to their excellent targeting capability. Additionally, when using existing therapeutic antibodies as imaging agents, availability, easy production and already wellestablished safety are ensured. However, not all properties are desirable, the
large size of antibodies contributes to a long circulation time in the bloodstream, and the physical half-life of conventional PET radionuclides is not
compatible with the long circulation time of full-length mAbs (Wu & Olafsen, 2010). Therefore, there has been a recent increasing interest in the production of more long-lived positron-emitting radionuclides, such as 64Cu,
86
Y, 76Br, 55Co, 89Zr and 124I (Pagani, Stone-Elander, Larsson, 1997). In particular, positron emitters with longer physical half-lives such as 124I and 89Zr
are suitable for the labelling of intact mAbs. Preclinical studies of the 89Zr
labelled anti-HER2 monoclonal antibody trastuzumab (Dijkers et al. 2005),
anti-VEGFR bevacizumab (Nagengast et al. 2007) and anti-EGFR cetuximab (Aerts er al. 2009) have demonstrated their specific tumour accumulation and imaging feasibility. However, due to the slow clearance of mAbs,
sufficiently high tumour-to-non-tumour ratios were obtained only a few days
after injection.
Another factor limiting the use of monoclonal antibodies as imaging
agents is a high non-specific accumulation in a non-target expressing tumour
as a result of the highly permeable vasculature of tumours. This phenomenon
is called the enhanced permeability and retention (EPR) effect, which is typical for all agents with a size greater than 45 kDa (Wester & Kessler, 2005;
Heskamp, van Laarhoven, van der Graaf, Oyen, Boerman, 2014).
In order to circumvent some of the limitations associated with antibodies,
modifications was made to reduce their molecular size. Smaller antibody
fragments such as (Fab’)2 (120 kDa) and Fab (55 kDa) (Figure 4) were
generated by proteolytic digestion (Olafsen & Wu 2010). As a result, both
the rate of extravasation and diffusion was improved. Moreover, an excess of
unbound imaging agents is relatively rapidly cleared via the kidneys. These
two factors provide high imaging contrast compared to intact antibodies, and
the imaging can typically be performed on the day after injection (Olafsen el
al. 2010).
23
Positron-emitting radionuclides with medium half-lives (10-20 h) are
more appropriate for labelling (Fab’)2 (T1/2β ≈ 12 h) and Fab (T1/2β ≈ 1.5 h).
Potentially suitable nuclides include 64Cu, 55Co, 76Br and 86Y.
Although the size of fragments has been appreciably reduced compared to
intact mAbs, unspecific uptake remains a problem for (Fab’)2 and Fab fragments due to the EPR effect.
The use of gene engineering has allowed the generation of even smaller
antibody fragments, such as single-chain variable fragment (scFv) (25 kDa),
nanobodies (15 kDa), diabodies (55 kDa) and minibodies (80 kDa) (Figure
4) (Olafsen et al. 2010).
ScFv (T1/2β ≈ 0.5-2 h) demonstrates extremely rapid clearance and elimination from normal tissues compared to intact antibodies, F(ab´)2 and Fab
fragments. However, as a result of this rapid clearance rate, only low radioactivity levels in the tumour were achieved. This can be attributed to a mismatch in the clearance rate and tumour extraversion rate (Wittrup, Thurber,
Schmidt, 2012), which will be explained in more detail below.
Both diabodies (T1/2β ≈ 3-7 h) and minibodies (T1/2β ≈ 6-11 h) exhibit
longer circulation time in the blood compared to ScFv. Due to their bivalency, their affinity and therefore tumour accumulation are significantly improved. However, unspecific uptake due to the EPR effect remains an issue
for these agents (Olafsen et al. 2010).
The smallest and a very promising fragment is the nanobody, which is
derived from a single-chain camelid antibody. Nanobodies have higher affinity (nanomolar range) compared to antibody fragments (Vaneycken et al.
2011), and the rapid clearance of nanobodies permits the labelling of very
short-lived radionuclides, such as 44Sc, 18F, and 68Ga.
Natural peptide ligands
Attractive features of a number of natural peptide ligands include a small
size, low immunogenicity, affinities in the low nanomolar or subnanomolar
ranges and rapid clearance from blood (Okarvi, 2004). These properties are
advantageous when developing an imaging agent.
Consequently, a number of natural peptide ligands for the imaging of tyrosine kinases receptors has been investigated, including PDGFRβ (Kastin,
Akerstrom, Hackler, Pan, 2003), EGFR (Orlova et al, 2000; Reilly et al
2000) VEGFR (Cai et al. 2006) and IGF-1R (Sun et al, 1997; Sun et al.
2000; Cornelissen, McLarty, Kersemans, Reilly, 2008).
However, there is a limited range of natural peptide ligands to choose
from, for example, there is no known ligand for HER2, and therefore imaging of some important targets using natural peptide ligands is impossible.
Other disadvantages of natural peptides include low in vivo stability due to
enzyme degradation (Kastin et al. 2003), binding to plasma proteins (Sun et
24
al. 2000) and agonistic action upon binding to target receptors, which might
restricts the amount of the injected protein dose.
Engineered scaffold protein-based binders
Alternatives to tracers based on natural ligands, antibodies and antibody
fragments are those based on engineered scaffold proteins. In general, scaffold proteins are based on a robust framework of constant amino acids used
to maintain the tertiary structure, with a number of surface-exposed residues
that have been randomized to produce a large library of binders (Nygren &
Skerra 2004). The use of molecular display techniques (e.g., phage display)
enables the selection of proteins that bind with high affinity and specificity
to desirable molecular targets (Nygren et al. 2004; Binz, Amstutz, Plückthun
2005). Some characteristic features of scaffold proteins include high solubility in water, thermodynamic and chemical stability, single-polypeptide
chain format, bacterial expression enabling inexpensive production and often
the absence of disulphide bonds (Nuttall & Walsh 2008).
Several scaffold-based proteins have demonstrated an appreciable potential to serve as imaging probes, e.g., Affibody molecules, knottins, DARpins,
anticalin, and adnectins (Miao, Levim, Chengm, 2011). In this thesis, Affibody molecules as imaging probes were investigated and is further described.
Affibody molecules
Affibody molecules are small robust affinity ligands derived from the Bdomain of the immunoglobulin-binding region of staphylococcal protein A.
The cysteine free B-domain protein is folded into a three-helix bundle structure containing 58 amino acids (6-7 kDa) (Löfblom, Feldwisch, Tolmachev,
Carlsson, Ståhl, Frejd, 2010). Their small size and high affinity (in low nanomolar or sub-nanomolar range) make them good candidates for molecular
imaging probes, providing high contrast images only a few hours after injection (Ahlgren & Tolmachev, 2010). Preclinical studies have shown that Affibody molecules provide much higher contrast than radiolabelled mAbs or
their proteolytic fragments.
Affibody molecules may be selected using several systems, e.g., by phage
display or staphylococcal display. Selection using phage display utilizes
phagemid vectors containing the Affibody gene, and the vector can carry
useful modifications such as a unique cysteine tag for site-specific labelling.
Large-scale production is possible using recombinant techniques (Nygren et
al, 2004). The relatively small number of amino acids in the Affibody scaffold also enables production by solid-phase peptide synthesis (SPPS), which
allows the direct conjugation of a chelator of choice to the scaffold in a sitespecific manner, providing a homogenous product.
25
Affibody molecules have been generated against several RTKs, such as
HER2 (Orlova et al, 2006), EGFR (Tolmachev et al, 2009), insulin-like
growth factor 1-receptor (IGF-1R) (Orlova et al 2013), PDGFRβ (Tolmachev et al, 2014), carbonic anhydrase IX (CAIX) (Hononovar et al. 2015)
and HER3 (Orlova et al. 2014), all with subnanomolar affinities.
As potential PET imaging agents for RTK visualization, Affibody molecules labelled with positron-emitting radionuclides are promising imaging
candidates.
Figure 4. Schematic overview and properties of some targeting agents
26
Factors affecting imaging sensitivity and specificity
The accuracy of radionuclide molecular imaging depends on the sensitivity
and specificity with which the imaging probe shows its target. Specificity is
achieved when the imaging agent dose not accumulate in healthy tissues and
the sensitivity depends on the imaging contrast. Some factors that influence
sensitivity and specificity are size, affinity, radionuclide and labelling procedure, localization of the antigen (extra or intracellular), the EPR effect,
off-target interactions, specific activity and expression level of the target
in normal tissue. Highlighted features above may be altered when developing an imaging agent (Heskamp et al. 2014, Tolmachev et al. 2012).
Size and Affinity
Schmidt et al. (2009), used theoretical analysis to predict tumour uptake in
relation to size and affinity. Their model showed that tracers with the smallest and largest molecular masses exhibited the highest tumour uptake,
whereas tracers with intermediate mass (25-60 kDa) displayed the lowest
tumour uptake. Although tracers with intermediate masses, e.g., antibody
fragments, scFv and diabodies, might provide advantageous extravasation
and intratumoral penetration characteristics, their rapid renal filtration results
in excessively fast clearance from the circulation, which hampers efficient
tumour localization. Decreasing the size further would not increase the renal
excretion but would increase the extravasation rate and therefore tumour
localization. Sufficient tumour localization despite rapid clearance has been
observed for small scaffold-based imaging agents (Zahnd et al. 2010;
Ahlgren et al 2010 b).
Furthermore, Schmid et al. (2009) suggested that small targets need to
have high affinity, in the subnanomolar range, for efficient tumour targeting.
Hence, improving affinity improves tumour uptake directly. The results of
theoretic calculations are consistent with in vivo data (Orlova et al. 2006);
however, experiments have shown that affinity in the single-digit nanomolar
range is sufficient for Affibody molecules with a high target expression level
(>106 receptors per cell), as more targets are available to rebind because they
have penetrated the tumour more deeply. At moderate expression levels
(several tens of thousands receptors per cell), a subnanomolar affinity is
desirable because there is less chance for the low-affinity conjugate to rebind
(Tolmachev et al. 2012).
27
Labelling procedures
Radiolabelling with trivalent radiometals
Metals do not form stable covalent bond with organic substances; therefore
labelling proteins with radiometals, e.g., 111In, 68Ga or 86Y, requires a chelator. Macrocyclic chelators can be covalently conjugated to targeting vectors,
e.g., peptides, antibodies, or scaffold-based proteins, using a number of bioconjugation techniques, reviewed thoroughly by Price et al. 2014.
In this thesis, two techniques for site-specific chelator conjugation to Affibody molecules were used:
•
Introduction of a single cysteine into recombinantly produced Affibody molecules enables thiol-direct chemistry (thioether bond
formation between a maleimide and thiol), which permits the sitespecific conjugation of a chelator containing a maleimide.
•
Direct site-specific incorporation of the carboxy group of a chelator via an amide bond to an amino group of the N-terminus or a
lysine side-chain during the synthesis of Affibody molecules.
The thermodynamic stability and kinetic inertness of radiometal-chelator
complexes are very important parameters influencing the in vivo stability of
the labels. Several macrocyclic chelators are currently in use for the labelling
of peptides with radiometals, in this thesis the flowing three chelators was
used for labelling: 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid
(DOTA), 1,4,7-triazacyclononane-N,N′,N′′triacetic acid (NOTA) and 1-(1,3carboxypropyl)-4,7 carboxymethyl-1,4,7 triazacyclononane (NODAGA).
DOTA is one of the most commonly used chelators for the stable labelling of proteins (De Leon-Rodríguez & Kovacs, 2008; Price et al. 2014). In
the case of Affibody molecules, DOTA has been used for labelling with
111
In, 57Co, 68Ga and 64Cu (Ahlgren et al 2010 a; Kramer-Marek et al. 2011;
Wållberg et al 2010, Cheng et al. 2010). However, DOTA is not always the
chelator of choice. For example, DOTA is a suboptimal chelator for copper
isotopes due to in vivo instability. On the other hand, NOTA, which has a
smaller central cavity than DOTA, has been shown to provide a more stable
complex with 68Ga, 111In and 64Cu than DOTA (Clarke & Martell, 1991;
Clarke & Martell, 1992; Price et al. 2014). NODAGA is similar to NOTA
but contains an extra carboxyl group that can be used for conjugation to a
peptide while leaving the three carboxylic groups available for the formation
of a stable and neutral complex with trivalent metals. Interestingly, substitution of DOTA by NODAGA resulted in more rapid blood clearance of radioactivity for 68Ga-labelled RGD peptides, enabling higher tumour-to-organ
ratios (Knetsch et al. 2011).
28
Due to differences in structure, complexes of various macrocyclic chelators with trivalent metals have different charges. For example, NODAGA
and DOTA will form a complex with trivalent metals with a neutral net
charge and NOTA with a positive net charge when conjugated to a targeting peptide via one of the carboxyl groups. This indicates that the use of
different chelators for labelling the same targeting protein or peptide can
modify the charge distribution of the targeting molecule.
Furthermore, the chemical properties of radiometals influence the properties of their complexes with these chelators. Although radiometals such as
In3+ and Ga3+ are trivalent metals, they differ substantially in their ionic radii
and have different coordination numbers. Hence, there are appreciable differences in the structure of their complexes with DOTA and NOTA (Broan,
Cox, Craig, Kataky, Parker, 1991). One could speculate that NODAGA
would form a similar complex as NOTA. This might influence the interactions of a targeting peptide with its molecular target as well as off-target
interactions, e.g., strength of binding to blood proteins.
The use of an optimal chelator makes it possible to modify and improve
the biodistribution and targeting properties of targeted peptides (Knetsch et
al. 2011; Altai et al. 2012; Malmberg et al. 2012). As has been shown for
99m
Tc-labelled synthetic Affibody molecules, selection of an optimal chelator
enables both the stable attachment of the radionuclide and significantly improves the imaging contrast (Engfeldt et al. 2007; Ekblad et. al 2008; Tran et
al. 2008).
Radiohalogenation
Halogens, such as iodine or bromine, can be attached to proteins or peptides
directly or indirectly by using a precursor molecule.
The most straightforward labelling procedure for iodine is direct labelling, which is usually performed by attaching the label to a tyrosine residue
(Wilbur et al 1992). However, the direct radiolabelling of anti-HER2 Affibody molecules with 125I resulted in an appreciable reduction in binding to
HER2-expressing cells, most likely due to the labelling of a tyrosine located
in the binding site (Steffen et al. 2005).
Conversely, indirect labelling using a prosthetic group N-succinimidyl para-iodobenzoate (SPIB) reacting with the amino group of lysines at the Nterminus of Affibody molecules preserved specific binding to the RTK (Orlova et al. 2006). Although specific binding was achieved, indirect 125I labelling to Affibody molecules using SPIB was not quite reproducible, possibly
due to non-site-specific labelling. This was solved by incorporating a unique
cysteine into the Affibody molecule, which enabled the site-specific coupling of a linker molecule using thiol-directed chemistry. Affibody molecules have also been site-specific labelled with radiohalogens using an aromatic moiety, HPEM, as an intermediate linker molecule. Direct head-tohead comparison of 125I-HPEM- and125I-PIB-labelled Affibody molecules
29
revealed a fourfold reduction of renal uptake for 125I-HPEM but the same
level of tumour uptake as the 125I-PIB-labelled Affibody molecule (Mume et
al. 2005). These results demonstrate that the position of the label on the Affibody molecule can substantially affect retention in normal tissue, especially kidney retention. The exact mechanism of this is not quite clear, and understanding the internalization, degradation and excretion process of radiolabelled Affibody molecule is desirable.
Role of radiocatabolites
If the binding of a radio-conjugate to an RTK triggers receptor internalization, ligand-bound RTKs cluster on the cell membrane and are pinched off as
intracellular vesicles. The vesicles fuse with early endosomes, and the cargo
is either recycled or processed into late endosomes. The late endosomes then
fuse with lysosomes, and the radio-conjugate is proteolytically degraded.
Depending on the physiochemical property of the radiolabel, the radiocatabolites can either diffuse through the cell membrane (non-residualizing)
or remain trapped in the cell (residualizing). Radiocatabolites with nonresidualizing properties are small, hydrophobic, uncharged or non-polar and
typically labelled with 11C, 125I, 67Br and 18F. Residualizing radiocatabolites
are typically conjugates labelled with transitional metals, e.g., 111In, 68Ga,
86
Y or 89Zr (Tolmachev, Stone-Elander, Orlova 2010).
In the case of imaging agents that undergo rapid internalization after binding, e.g., natural peptide ligands, labelling with radiometals permits the high
intracellular accumulation of radioactivity. This would allow for imaging at
later time points because the radiocatabolites are “trapped” inside the cell.
With time, blood retention will clear and result in higher tumour-to-blood
ratios. However, this entrapment might also contribute to high retention of
radioactivity in normal organs, such as excretory organs.
With regard to Affibody molecules, the slow internalization of receptorbound Affibody molecules by cancer cells (approximately 30 % after 24
hours for HER2 targeting) and their high affinity (Wållberg & Orlova, 2008)
make the residualizing properties of radiocatabolites not critical for the accumulation of high radioactivity in tumours. The residualizing properties of
radiocatabolites can instead result in high renal radioactivity retention because Affibody molecules are mainly filtered through the Bowman’s capsules in the glomeruli and thereafter undergo nearly total reabsorption in
tubule cells. High renal radioactivity retention has been shown for several
Affibody molecules labelled with radiometals (Orlova et al. 2013; Perols et
al 2012, Malmberg et al 2012).
Understanding the mechanism by which renal tubular cells internalize Affibody molecules would enable the development of substances that could
block kidney uptake. For numerous small radiolabelled peptides, the mega30
lin\cubilin system is involved in the kidney reabsorption process (Verel,
Visser, van Dongen, 2005; Verroust & Christensen, 2002; Vegt et al. 2011).
To investigate whether this mechanism is also involved in the kidney reabsorption of Affibody molecules, 111In labelled anti-HER2 Affibody molecules were injected into a murine model with megalin knockout. Comparative micro-SPECT imaging between the megalin-deficient and wild-type
mice injected with 111In-DOTA-ZHER2:2395 showed no significant difference in
renal radioactivity uptake. This demonstrates that the megalin system is not
responsible for Affibody molecule reabsorption by the kidney (Altai, Varasteh, Andersson, Eek, Boerman, Orlova 2013).
One solution to reduce kidney radioactivity retention is to label Affibody
molecules with radiohalogens. A head-to-head comparison of 111In labelled
EGFR-targeting Affibody molecule (ZEGFR:1907) and 125I labelled ZEGFR:1907
demonstrated a 21-fold lower radioactivity retention in the kidney for the 125I
labelled conjugate 4 hours after injection (Tolmachev et al. 2009). This is
most likely due to the non-residualizing property of the radiocatabolite.
However, 111In-ZEGFR:1907 provided a higher tumour-to-blood ratio.
In conclusion, the mechanism of Affibody molecule renal uptake is not yet
well understood and requires further investigation. There is currently no
efficient way to block kidney uptake of Affibody molecules, as there is for
somatostatin analogues or other short peptides. The most efficient way to
reduce kidney radioactivity retention is by altering the labelling chemistry
(chelator properties, linker-molecules, radionuclides). Even subtle changes
in the labelling chemistry can substantially reduce kidney retention (Wållberg et al 2011; Altai et al. 2014).
31
Aim of the thesis work
The primary aim of the studies in the present thesis was to develop Affibody-based PET imaging agents to provide the highest possible sensitivity
of RTK detection in vivo. To reach this goal, imaging probes with the highest tumour-to-organ ratios (contrast) are required.
The thesis evaluates the effect of radiolabelling chemistry on the biodistribution and targeting properties of Affibody molecules for imaging of
HER2 and PDGFRβ to identify a labelling strategy providing the highest
contrast.
Papers I, II, and III investigate the impact of
• chelators (DOTA, NOTA, NODAGA)
• radionuclides (68Ga and 111In)
• chelator positioning (C-terminus, middle of helix-3 or N-terminus)
on the biodistribution profile of labelled HER2-targeting Affibody molecules.
Paper IV evaluates the targeting properties of a PDGFRβ-targeting Affibody molecule labelled with 111In or 68Ga.
Paper V investigates whether the use of 3-iodophenetylmaleimide (IPEM)
as a linker molecule compared to the use of IHPEM as a linker molecule
would further reduce the renal retention of the radionuclide after the injection of radioiodinated HER2-targeting Affibody molecules.
32
Methodology
In this thesis, three different cell lines were used to evaluate the receptormediated binding of Affibody molecules (Table 3).
Table 3. Properties of the cell lines used in this thesis (Tolmchev et al. 2012; Malmberg et al. 2012; Tolmachev et al. 2014).
Cell line
Target
Expression/cell
Origin
SKOV-3
HER2
1.6×106
ovarian cancer
DU145
HER2
5×104
prostate cancer
U-87
PDGFRβ
3.6×104
glioma
Half maximal inhibitory concentration IC50
Evaluation of affinity is important when developing a new radiopharmaceutical for imaging. As stated earlier, high affinity is essential to obtain high
tumour-to-organ ratios for radiolabelled HER2-targeting Affibody molecules
(Orlova et al. 2006).
Affinity can be measured using either saturation assays, which directly
measure ligand-receptor binding, or signalling assays, which measure downstream signalling pathways (Hulme & Trevethick, 2010). Receptor-ligand
binding can also be monitored in real time using LigandTracer (Björke &
Andersson, 2006). In paper IV, Affinity was measured using a saturation
assay (half maximal inhibitory concentration, IC50)
In this assay, a PDGFRβ-targeting Affibody molecule was labelled with
either stable natGa or natIn (the competitor). A series of increasing concentrations of the competitor were added to cell samples containing a constant
concentration of 111In-labelled PDGFRβ-targeting Affibody molecule in the
medium. The IC50 value corresponds to the concentration of competitor that
is needed to inhibit 50 % of the 111In-labelled PDGFRβ-targeting Affibody; a
lower IC50 value corresponds to higher affinity.
33
Binding specificity to TKR
To assess the binding specificity of radiolabelled Affibody molecules to the
targeted RTK in vitro, an excess of unlabelled Affibody molecule was added
to saturate the receptors 5 minutes before the addition of the labelled compound. After incubation, the medium was collected, and the cells were detached with trypsin-ethylenediaminetetraacetic acid and collected. The sample containing the culture medium and the cell sample was measured using a
gamma counter. The radioactivity associated with the pre-saturated cell
dishes was compared with non-saturated cells dishes to evaluate the binding
specificity.
Cellular processing
When developing radiopharmaceuticals, both for diagnostic and for therapeutic purposes, it is important to understand the cellular internalization
process of the radiolabelled compound. In the present thesis, the following
internalization assay validated by Wållberg et al (2008) was used to discriminate between internalized and membrane-bound Affibody molecules:
1. The labelled compound was added to several Petri dishes containing approximately 106 cells/dish and incubated at 37°C.
2. At predetermined time points, the medium from 3 dishes was collected.
3. The 3 dishes were washed with ice-cold medium then treated with
0.2 M glycine buffer containing 4 M urea, pH 2.5. This buffer disrupts Affibody-RTK binding and releases the membrane-bound
Affibody into solution. The added glycine buffer was collected,
with the samples representing the membrane-bound Affibody
molecules.
4. The remaining cell-associated radioactivity (considered as internalized) was removed by treating the cells with 1 M of NaOH for
30 minutes at 37°C.
5. The samples containing membrane-bound Affibody molecules and
internalized Affibody molecules were measured using a gamma
counter.
34
Dual isotope technique
In the present thesis, a dual isotope technique was used to investigate and
compare the biodistribution profile of 68Ga- and 111In-labelled HER2- or
PDGFRβ-targeting Affibody molecules in vivo. This approach also keeps
the number of animals to a minimum and improves the statistical power.
In short, 68Ga- and 111In-labelled conjugates containing the same chelators
and having the same chelator position were injected into the same mice.
Directly after dissection of the organs, a large energy window covering both
the gamma emission from 111In and the 511 keV annihilation photons from
68
Ga was applied using a gamma counter, and the counts for each sample and
three standards of injected activity were measured. A second measurement
was performed after the complete decay of 68Ga (approximately after 17 h),
with the same energy setting. Based on the results from the second measurement, which was considered as the 111In-labelled Affibody molecule uptake values, the percent of injected activity per gram of tissue (%IA/g) was
calculated. For the gastrointestinal tract and the remaining carcass, %IA per
whole sample was calculated. Subsequently, indium count rates was corrected for decay and subtracted from count rate obtained during first measurement. The resulting values represented the radioactivity of 68Ga in each organ.
35
Results
Paper I
Influence of nuclides and chelators on imaging using Affibody
molecules: comparative evaluation of recombinant Affibody molecules
site-specifically labelled with ⁶⁸Ga and ¹¹¹In via maleimido derivatives of
DOTA and NODAGA.
Background and aim
The influence of two different chelators, DOTA and NODAGA (Figure 5)
conjugated to the C-terminus of the HER2 targeting Affibody molecule
(ZHER2:2395) labelled with 111In was investigated previously (Altai et al, 2012).
The best imaging properties were observed for the NODAGA-conjugated
variant. The results indicated that selecting an optimal chelator (NODAGA)
for specific radionuclide labelling can substantially improve the biodistribution properties. Labelling with a positron-emitting radionuclide would further increase HER2 imaging sensitivity using PET.
The aim of paper I was to select an optimal chelator for site-specific labelling at the C-terminus of recombinantly produced anti-HER2 Affibody
molecules with 68Ga and to compare the biodistribution properties of the
68
Ga-labelled conjugates with their 111In-labelled counterparts.
Figure 5. Structures of maleimidomonoamido derivatives of DOTA (A) and
NODAGA (B) conjugated to the C-terminal cysteine of an Affibody molecule.
36
Method
A recombinantly produced HER2-targeting Affibody molecule (ZHER2:2395)
containing a C-terminal cysteine was site-specifically conjugated to the maleimido derivatives of the macrocyclic chelators DOTA and NODAGA.
Labelling of the conjugates with 68Ga and 111In was evaluated.
Binding specificity and cellular processing were investigated using the
HER2-expressing cells lines DU145 and SKOV3.
The biodistribution and targeting properties of 68Ga-NODAGA-ZHER2:2395,
68
Ga-DOTA-ZHER2:2395, 111In-NODAGA-ZHER2:2395 and 111In-DOTA-ZHER2:2395
in BALB/C nu/nu mice bearing SKOV-3 xenografts were evaluated in a
comparative study at 1 and 2 h after injection.
Results
The labelling yield of both the 68Ga and 111In conjugates (DOTA-ZHER2:2395
and NODAGA-ZHER2:2395) exceeded 95 %. EDTA challenge demonstrated
the stable binding of the radionuclides to all the conjugates.
There was significantly lower (p<0.001) cell binding of all conjugates after adding an excess of unlabelled HER2-targeting Affibody molecules. This
indicates the retention of binding specificity for HER2 receptors in vitro.
The internalization rate of both conjugates was slow. However, there were
some differences: in the DU145 cell line, 21±4 % of the radioactivity was
internalized at 3 h for 68Ga-DOTA-ZHER2:2395, whereas the equivalent value
for 68Ga-NODAGA-ZHER2:2395 was only 10±3 %. The results from the
SKOV3 cell lines showed similar internalization rates for both of the 68Ga
labelled conjugates.
All conjugates demonstrated highly specific tumour uptake in vivo. The
tumour uptake for all conjugates was similar, except for 111In-NODAGAZHER2:2395, which exhibited approximately 50 % lower tumour uptake at both
time points.
An influence of the differences in radionuclide on the biodistribution pattern was clearly observed (Table 4). There was higher uptake in the liver and
spleen for the 68Ga-labelled conjugates than for the 111In-labelled conjugates,
indicating that different radionuclides influence the biodistribution profile of
HER2-targeting Affibody molecules.
A differences between the chelators was also observed. The uptake of
68
Ga-NODAGA-ZHER2:2395 at 2 h p.i. was significantly lower in the liver and
spleen compared to 68Ga-DOTA-ZHER2:2395.
At 2 h after injection, there were significantly higher tumour-to-liver (8 ±
2 vs. 5.0 ± 0.3) and tumour-to-spleen (18 ± 4 vs. 13 ± 1) ratios for 68GaNODAGA-ZHER2:2395 compared to 68Ga-DOTA-ZHER2:2395 (Figure 6). For the
111
In-labeld conjugates, the difference between 111In-NODAGA-ZHER2:2395
and 111In-DOTA-ZHER2:2395 was much more pronounced, with 111In-DOTAZHER2:2395 providing a significantly higher overall tumour-to-organ ratio.
37
The overall highest tumour-to-organ ratios were obtained for the 111InDOTA-ZHER2:2395 and 68Ga-NODAGA-ZHER2:2395 conjugates.
HER2 expression was visualized with all four conjugates at 1 h after injection in mice bearing SKOV3 xenografts.
Table 4. Comparative biodistribution of NODAGA-ZHER2:2395 and DOTA-ZHER2:2395
labelled with gallium-68 and indium-111 after intravenous injection in female
BALB/C nu/nu mice bearing SKOV-3 xenografts. Data are presented as an average
% IA/g and standard deviation for four mice.
68
blood
lung
liver
spleen
kidney
tumour
muscle
bone
GI tract*
carcass*
GaNODAGAZHER2:2395
1.8±0.2a
2.9±0.2 a
2.5±0.1a
1.6±0.3a
310±5a
15±8a
0.4±0.3a
1.6±0.3
1.4±0.1
12±3a
blood
lung
liver
spleen
kidney
tumour
muscle
bone
GI tract *
carcass*
0.5±0.1
1.0±0.3
2.0±0.3a
0.9±0.1
297±33a
16±3a
0.14±0.03
0.5±0.1
0.7±0.2
5±1
conjugate
Uptake, 1 h pi
111
InNODAGAZHER2:2395
1.2±0.2
2.0±0.1
1.52±0.08 d
1.0±0.2
122±1d
7.2±3.2d
0.33±0.04
1.5±0.1d
1.3±0.3
12±4
Uptake, 2 h pi
0.3±0.1
0.7±0.1 d
1.2±0.2d
0.6±0.1
118±13d
8±2d
0.12±0.09
0.7±0.5
0.6±0.1 d
4.4±0.2 d
68
GaDOTA-
111
ZHER2:2395
1.2±0.1c
2.1±0.2c
3.2±0.4
1.8±0.3
280±19
15±2
0.35±0.06
0.8±0.1c
1.2±0.1
8.8±0.4
InDOTAZHER2:2395
1.2±0.1
2.8±1.2
1.8±0.1b
1.1±0.2b
284±22
17±2
0.37±0.07
0.72±0.09
1.6±0.4
13±4
0.42±0.07
0.85±0.09
3.1±0.1c
1.2±0.2c
303±28
15±1
0.17±0.03
0.6±0.2
0.72±0.05
4.6±0.5
0.35±0.04
0.84±0.05
1.65±0.05b
0.60±0.03b
313±26
17±2
0.18±0.06
0.4±0.1
0.8±0.1
6±1b
*Data for the gastrointestinal (GI) tract and carcass are presented as %IA per whole sample.
a
Significant difference (p<0.05) between 68Ga-NODAGA-Z2395 and 111In-NODAGA-Z2395
b
Significant difference (p<0.05) between 68Ga-DOTA-Z2395 and 111In-DOTA-Z2395
c
Significant difference (p <0.05) between 68Ga-NODAGA-Z2395 and 68Ga-DOTA-Z2395
d
Significant difference (p<0.05) between 111In-NODAGA-Z2395and 111In-DOTA-Z2395
38
Figure 6. Comparison of tumour-to-organ ratios at 1 and 2 h p.i. for 68GaDOTA-ZHER2:2395 and 111In-DOTA-ZHER2:2395 and 68Ga-NODAGA-ZHER2: 2395 and
111
In-NODAGA-ZHER2:2395 in BALB/C nu/nu mice bearing SKOV-3xenografts.
Data are presented as an average and standard deviation for four mice.
39
Paper II
Influence of macrocyclic chelators on the targeting properties of 68Galabeled synthetic Affibody molecules: comparison with 111In-labeled
counterparts.
Background and aim
Chemical peptide synthesis has a number of advantages over recombinant
production, e.g., the site-specific incorporation of chelators and prosthetic
groups, use of unnatural amino acids, and incorporation of pharmacokinetic
modifiers. In addition, peptides with a length of up to 50 amino acids can be
synthesized in high yield.
The aim of paper II was to evaluate the biodistribution profiles of synthetically produced Affibody molecules labelled with 68Ga and 111In using
either DOTA, NOTA or NODAGA chelators (Figure 7) at the N-terminus
and to compare their targeting properties.
Figure 7. Metal complexes of the chelators 1,4,7-triazacyclononane-1,4,7-triacetic
acid (NOTA), 1,4,7,10-tetraazacylododecane-1,4,7,10-tetraacetic acid (DOTA), and
1-(1,3-carboxypropyl)-1,4,7-triazacyclononane-4.7-diacetic acid (NODAGA) conjugated to the N-terminal amino group via amide bonds.
40
Method
A synthetic HER2-targeting Affibody molecule (ZHER2:S1) was synthesized,
and the chelators, DOTA, NOTA and NODAGA were manually conjugated
to the N-terminus via an amide bond.
The conjugates were labelled with 68Ga and 111In, and stability testing was
performed using an EDTA challenge. In vitro binding specificity and cellular
processing assays were performed using HER2-expressing SKOV-3 cells.
The biodistribution properties of the 111In- and 68Ga-labelled conjugates were
compared in BALB/C nu/nu mice bearing SKOV-3 xenografts at 2 h after
injection.
Results
Labelling with 68Ga provided a high yield, 87-95 % (decay corrected) after
15 min at 95°C. A purity of over 97 % was obtained after purification using
a NAP-5 column for all three conjugates. 68Ga was stable under EDTA challenge. Preserved binding specificity to HER2-expressing cells was demonstrated, and a slow internalization rate and similar cellular processing patterns for all three 68Ga-labelled conjugates were observed.
An in vivo saturation experiment demonstrated the HER2-specific accumulation of all conjugates. At 2 h after injection, there was a significantly
higher tumour uptake of 68Ga-DOTA-ZHER2:2395 (18 ± 0.7 %IA/g) than both
68
Ga-NODAGA-ZHER2:S1 (16 ± 0.7 %IA/g) and 68Ga-NOTA-ZHER2:S1 (13 ± 3
%IA/g). A difference in the tumour uptake of the 111In-labelled counterparts
was also observed; however, the difference was more pronounced compared
with the 68Ga-labelled conjugates. It is notable that the 111In-labelled NOTA
conjugate showed significantly higher liver uptake compared to the other
conjugates.
Among the 68Ga-labeled variants, 68Ga-NODAGA-ZHER2:S1 had the highest
tumour-to-blood (60±10), tumour-to-liver (7±2), and tumour-to-spleen
(36±10) ratios (Table 5).
Imaging HER2-expressing tumours using PET was performed at two
hours after injecting 68Ga-NODAGA-ZHER2:S1 in mice bearing SKOV-3 xenografts.
41
Table 5. Tumour-to-organ ratios at 2 h after injection for NODAGA-ZHER2:S1, NOTAZHER2:S1 and DOTA-ZHER2:S1 in BALB/C nu/nu mice bearing SKOV-3 xenografts. Data
are presented as an average and standard deviation for four mice.
Blood
Lung
Liver
Spleen
Kidney
Muscle
Bone
a
DOTA-ZHER2:S1
NOTA-ZHER2:S1
NODAGA-ZHER2:S1
68
68
68
Ga
28±4
25±4
5.5±0.6d
12±2
0.1±0.0d
297±109d
255±185
111
In
44±3a
22±5a
7.4± 0.7a
16.4± 3.7a
0.07±0.01a
98±32
25±3a
Ga
42±11
26±9
3.4±0.6e
19±6e
0.04±0.10e
80±15
25±4
111
In
13±4b
8±5b
1.2±0.2b
7±2b
0.04±0.01b
58±22b
13± 2b
Ga
60±10f
31±12
7±2
36±10f
0.06±0.01
100±25f
35±9
111
In
31±4c
15±1c
5±2c
15±4c
0.05±0.00c
161±58
72±57
significant difference (p<0.05) between 68Ga-DOTA-ZHER2:S1 and 111In-DOTA-ZHER2:S1
significant difference (p<0.05) between 68Ga-NOTA-ZHER2:S1 and 111In-NOTA-ZHER2:S1
c
significant difference (p<0.05) between 68Ga-NODAGA-ZHER2:S1 and 111In-NODAGA-ZHER2:S1
d
significant difference (p<0.05) between 68Ga-DOTA-ZHER2:S1 and 68Ga-NOTA-ZHER2:S1
e
significant difference (p<0.05) between 68Ga-NOTA-ZHER2:S1 and 68Ga-NODAGA-ZHER2:S1
f
significant difference (p<0.05) between 68Ga-NODAGA-ZHER2:S1 and 68Ga-DOTA-ZHER2:S1
b
42
Paper III
Position for site-specific attachment of a DOTA chelator to synthetic
affibody molecules has a different influence on the targeting properties
of 68Ga- compared to 111In-labeled conjugates.
Background and aim
In papers I and II, the same chelators were placed either at the C- or Nterminus of different variants of HER2-targeting Affibody molecules. However, because the Affibody molecules differ in sequence and production, the
influence of the chelator position was difficult to compare. In addition, different chelator conjugation methods were used in these two studies.
Previously, the influence on biodistribution of different positioning of the
DOTA chelator on an anti-HER2 (ZHER2:342) Affibody molecule (N-terminus,
the middle of helix 3 or C-terminus) (Figure 8) was investigated when labelled with 111In (Perols et al 2012). In the present study, the same conjugates were labelled with the positron-emitting radionuclide 68Ga.
The aim of the current study was to evaluate the influence of the position
of the macrocyclic chelator DOTA on the biodistribution of Affibody molecules labelled with 68Ga. 111In-labelled variants were used as comparators.
Figure 8. Positioning of DOTA on the investigated variants of Affibody molecules.
43
Method
DOTA was conjugated via amide bonds to the N-terminus (A1), the middle
of helix 3 (K50) or the C-terminus (K58) of synthetic ZHER2:S1. The conjugates
were labelled with 68Ga or 111In and incubated with an excess of EDTA for 1
hour to evaluate the stability of 68Ga labelling. The in vitro binding specificity and cellular processing were examined using HER2-expressing SKOV-3
cells. The tumour-targeting properties of 111In- and 68Ga-labelled conjugates
were compared in NMRI nu/nu mice bearing SKOV-3 xenografts at 2 hours
after injection.
Results
The radiochemical yield of 68Ga labelling was in the range of 65-95 %. After
purification using a NAP-5 column, the radiochemical purity exceeded 96 %
for all of the 68Ga-labelled conjugates. The conjugates demonstrated high
labelling stability after EDTA challenge.
The in vitro binding specificity test of the 68Ga-labelled conjugates to
HER2-expressing SKOV-3 cells demonstrated preserved binding to HER2
receptors. Cellular processing of the 68Ga-labelled variants demonstrated
similar profiles, with slow internalization (approximately 10 % after 2 h
incubation).
The tumour uptake of the 68Ga- and 111In-labelled conjugates in SKOV-3
xenografts was significantly (p< 0.001) reduced after the pre-injection of
unlabelled HER2-targeting Affibody molecules, indicating specific HER2
binding.
The tumour uptake of the 68Ga-labelled conjugates (12.5±1.4, 10.0±1.4,
12.7±1.6 %ID/g, for DOTA-A1-ZHER2:S1, DOTA-K50-ZHER2:S1, and DOTAK58-ZHER2:S1, respectively) did not differ substantially. However, the 111Inlabelled counterpart showed 20-30 % higher tumour uptake (p<0.05 in a
paired t-test) (Table 6).
There was a clear influence of the chelator position on the biodistribution
profile. For example, 68Ga- DOTA-K50-ZHER2:S1 displayed significantly higher uptake in the blood, liver, spleen, muscle, and bone but lower uptake in
the kidneys compared to 68Ga-DOTA-A1-ZHER2:S1, and 68Ga-DOTA-K58ZHER2:S1.
An influence of the radionuclide was also observed. The 111In-labelled
conjugates, DOTA-A1-ZHER2:S1 and DOTA-K50-ZHER2:S1, provided, for example, a two- to fourfold higher tumour-to-blood ratio than the 68Ga-labelled
counterparts.
The best imaging properties among the 68Ga-labelled conjugates was
demonstrated for 68Ga-DOTA-A1-ZHER2:S1. As expected, high-contrast images of 68Ga-DOTA-A1-ZHER2:S1 were acquired in SKOV-3 xenograft-bearing
mice at 1 h and 2 h after intravenous injection.
44
Table 6. Comparison of tumour-to-organ ratios of 68Ga- and 111In-labeled Affibody
molecules in NMRI nu/nu mice bearing SKOV3 xenografts at 2 h after intravenous
injection.
DOTA-A1ZHER2:S1
68
Ga
111
Blood
Lung
Liver
Spleen
Kidney
39±12
45±5a
7±2a
42±12a
194±42a
In
83±21f
35±8
13±2f
47±9
139±35
Muscle
94±42a
76±22
a
DOTA-K50ZHER2:S1
68
DOTA-K58ZHER2:S1
68
14±4
21.2±3g
4±1g
16±6c,g
85±4.7g
In
62±19
31±4e
10±1
39±6e
136±16
41±26
26±7b
10±3h
42±7h
114±24
In
63±32
22±4d
7±4
26±7d
117±24
25±4c,g
53±10
57±23
50 ±10
Ga
g
111
Ga
111
Data are presented as an average % ID/g value for 4 animals ± standard deviation.
a Significant difference (p<0.05) between 68Ga-DOTA-A1-ZHER2:S1 and 68Ga-DOTA-K50ZHER2:S1;
b Significant difference (p<0.05) between 68Ga-DOTA-A1-ZHER2:S1 and 68Ga-DOTA-K58ZHER2:S1;
c Significant difference (p<0.05) between 68Ga-DOTA-K50-ZHER2:S1 and 68Ga-DOTA-K58ZHER2:S1;
d Significant difference (p<0.05) between 111In-DOTA- A1-ZHER2:S1, and 111In-DOTA-K58ZHER2:S1;
e Significant difference (p<0.05) between 111In-DOTA-K58-ZHER2:S1 and 111In-DOTA-K50ZHER2:S1;
f Significant difference (p<0.05) between 111In-DOTA-A1-ZHER2:S1 and 68Ga-DOTA-A1ZHER2:S1;
g Significant difference (p<0.05) between 111In-DOTA-K50-ZHER2:S1 and 68Ga-DOTA-K50ZHER2:S1;
h Significant difference (p<0.05) between 111In-DOTA-K58-ZHER2:S1 and 68Ga-DOTA-K58ZHER2:S1;
There was no significant difference between 111In-DOTA-A1-ZHER2:S1 and 111In-DOTA-K50ZHER2:S1;
45
Discussion and conclusion for papers I, II and III
The results from papers I, II and II demonstrated that both the chemical nature of the radionuclide, the structure and composition of the chelator and the
positioning of the chelator can influence the targeting properties of HER2targeting Affibody molecules.
In paper I, NODAGA was found to be a superior chelator for 68Ga in the
case of C-terminal placement and maleimido-mediated thiol-directed conjugation chemistry. For the 111In-labelled conjugate, the DOTA chelator provided the overall highest tumour-to-organ ratios.
In paper II, NODAGA conjugated to the N-terminus via an amide bond
also provided a superior targeting property compared to the other chelators
for the 68Ga-labelled conjugates. For example, 68Ga-NODAGA-ZHER2:S1 provided a twofold higher tumour-to-liver ratio than 68Ga-NOTA-ZHER2:S1. The
high liver uptake of 68Ga-NOTA-ZHER2:S1 can possibly be explained by the
positive charge formed by complexation of three-valent metals with NOTA.
A localized positive charge at the N-terminus of Affibody molecules was
found to increase the liver uptake of a 99mTc-labelled HER2-targeting Affibody molecule (Hovström et al 2013). Such unfavourable high liver uptake
might prevent the imaging of liver metastases using the NOTA conjugate.
Furthermore, the influence of chelators was also proven to depend on the
chemical nature of the radionuclide used as the label. A clear influence of
the radionuclide on biodistribution and targeting was observed in all three
studies. Interestingly, the difference was smaller for 68Ga than 111In for different chelators.
The differences between the biodistribution properties in papers I and II
suggest that chelator positioning on an Affibody molecule (N- or Cterminus) influences the biodistribution properties, possibly due to a cooperative effect between the chelator and the surrounding amino acids.
Because the Affibody molecules in papers I and II differed in sequence
and production, it was difficult to decide which chelator position (C- or Nterminal) provides the highest contrast. In addition, different chelator conjugation methods were used in papers I and II. In paper I, a C-terminal cysteine was engineered into the HER2-targeting Affibody molecules, and the
maleimido derivate of DOTA was conjugated through thiol-direct chemistry.
In paper II, the chelators were conjugated to the N-terminus via an amide
bond during peptide synthesis. Therefore, the influence of the position of the
macrocyclic chelator DOTA on the biodistribution of HER2 Affibody molecules labelled with 68Ga or 111In was further evaluated.
The results from paper III also demonstrated that the position of the
DOTA chelator can influence the targeting properties of HER2-targeting
Affibody molecules when labelled with 68Ga. N-terminal placement of the
DOTA chelator provided the best tumour-to-organ ratios for the 68Ga-labeled
synthetic Affibody molecules, and the results from the biodistribution study
46
of 68Ga-DOTA-A1-ZHER2:S1 and 111In-DOTA-A1-ZHER2:S1 were in agreement
with the results from paper II. Both studies showed more rapid clearance of
111
In from blood, higher uptake of 111In in the tumour, lung and bone and
higher uptake of 68Ga in the liver.
The results obtained from papers I, II and III can be explained as follows:
• Different chelator structures result in different local charge distribution
when complexed with metals, which translates into different features of
off-target interactions and affects biodistribution.
• The local distribution of charge in indium and gallium complexes is
different, even when complexed with the same chelator, which might influence off-target interactions and uptake in normal organs.
• Chelator positioning on an Affibody molecule influences biodistribution
properties, possibly due to a co-operative effect between the chelator and
the surrounding amino acids.
In conclusion, placement of a chelator in the middle of helix 3 provides the
lowest tumour uptake and the lowest imaging contrast. Increased negative
charge at the N-terminus of an Affibody molecule is favourable for increasing contrast. NODAGA seems to be the best chelator for 68Ga-labelling of
Affibody molecules for the series of DOTA-, NOTA- and NODAGA- chelators.
47
Paper IV
A gallium-68-labeled Affibody molecule for PET imaging of PDGFRβ
expression in vivo
Background and aim
Previously, our group showed the feasibility of imaging PDGFRβ-expressing
xenografts in mice using an 111In-labelled PDGFRβ-targeting Affibody molecule (Z09591). The study demonstrated a significant increase in tumour–toorgan ratios between 1 and 2 h after injection but very little increase in tumour-to-organ ratios between at 2 and 4 hours. The optimal imaging time
would therefore be between 2 and 4 hours (Tolmachev et al, 2014), which
permits the use of short-lived PET radionuclides such as 68Ga, as a label,
providing enhanced sensitivity compared to SPECT.
The aim of this study was to evaluate whether 68Ga-DOTA- Z09591 (Figure
9) is a suitable imaging agent for PDGFRβ visualization using PET.
Figure 9. Schematic structure of the 68Ga- DOTA- Z09591 conjugate
48
Method
DOTA was site-specifically conjugated to the C-terminus of a PDGFRβbinding Affibody molecule and labelled with either 68Ga or 111In. The conjugate was incubated with an excess of EDTA to evaluate the labelling stability. The binding specificity and cellular processing of 68Ga-PDGFRβ was
evaluated using PDGFRβ-expressing U-87 cells. The binding strength of the
two conjugates was compared by measurement of the half-maximum inhibition concentration (IC50).
The biodistribution profiles for 68Ga-labeled DOTA-conjugated Z09591
were compared with 111In-labeled variants in mice bearing PDGFRβexpressing U-87 MG glioblastoma xenografts at 1 and 2 h post-injection.
Results
Labelling with 68Ga provided an average radiochemical yield of 92.3± 0.6 %.
After purification, the radiochemical purity was 99.4±0.3 %. A challenge
with a 500-fold molar excess of EDTA during 4 h demonstrated high stability of the label (95.3 ±0.7 %).
The binding of 68Ga-DOTA-Z09591 to PDGFRβ-expressing U-87 MG glioma cells was significantly (p<0.001) reduced by adding a large excess of
non-labelled Affibody molecules. This indicated that the binding was receptor mediated.
The internalization of 68Ga-DOTA-Z09591 by PDGFRβ-expressing U-87
MG glioma cells was slow, but increased with time (26±1 % of total cellbound activity after 3 h of incubation). The IC50 value of 68Ga-DOTA-Z09591
(6.6 ± 1.4 nM) was somewhat higher than that of 111In-DOTA- Z09591 (1.4 ±
1.2 nM).
In mice bearing U-87 xenografts, the tumour uptake of 68Ga-DOTA-Z09591
was significantly (p<0.0005) decreased by pre-injection of non-labelled
PDGFRβ-targeting Affibody molecules, indicating PDGFRβ-mediated in
vivo targeting. Additionally, significantly lower uptake was observed in a
number of normal tissues (lung, liver, spleen, and muscle) after blocking the
receptors.
111
In-DOTA-Z09591 demonstrated somewhat faster blood clearance than
68
Ga-DOTA-Z09591, and blood retention was significantly (p<0.05 in the
paired t-test) lower for 111In-DOTA-Z09591 compared to 68Ga-DOTA-Z09591 at
both time points (0.6±0.3 %IA/g vs 0.8±0.3 %IA/g and 0.23± 0.03%IA/g vs
0.46±0.06 %IA/g, respectively).
The tumour-to-organ ratios had similar values for both variants. However,
a paired t-test suggested significantly higher values for 111In-DOTA- Z09591
than 68Ga-DOTA- Z09591 for tumour-to-liver (4.3±1.2 vs. 4.0±1.3) ratios at
one hour after injection.
At two hours after injection, the 111In-labelled conjugate showed significantly higher tumour-to-blood (18.4±8.3 vs. 8.0±3.1), tumour-to-lung (5±1
49
vs. 4±1.), tumour-to-liver (6±3 vs. 5±2) and tumour-to-spleen (2.8±0.9 vs.
2.5±0.8) ratios than the 68Ga-labelled conjugate (Figure 10). As early as two
hours after injection of 68Ga-DOTA-Z09591, the PDGFRβ-expressing xenografts were visualized using microPET.
Discussion and conclusions
Despite ubiquitous expression of PDGFRβ in normal tissue, 68Ga-DOTAZ09591 showed a capacity for the specific imaging of PDGFRβ expression in
tumours. At 2 h after injection, the tumour-to-blood ratio (8.0±3.1) was at
the same level, as can be attained by good antibody imaging of a highly expressed target at several days after injection. The only organ with higher
uptake than the PDGFRβ-expressing tumours was the kidney, which is typical for radiometal-labelled Affibody molecules. As pre-saturation of receptors did not cause a reduction in kidney uptake, target-specific binding in the
kidneys can be excluded. Decreased uptake after presaturation was observed
for the tumour, lung, liver, spleen, and muscle, indicating the expression of
PDGFRβ in these organs and tissue.
The influence of a radionuclide on the biodistribution of anti-PDGFRβ
Affibody molecules was similar to the influence on the biodistribution of
anti-HER2 counterparts. The 111In-DOTA-Z09591 conjugate demonstrated
faster blood clearance than the 68Ga-DOTA-Z09591 conjugate. This might
mean that the entire scaffold, not only a binding site, is essential for the biodistribution profile of an Affibody molecule-chelator-radionuclide combination. In this case, enhancing the biodistribution of one Affibody molecule
might improve the biodistribution of another. For example, it is likely that
the use of NODAGA instead of DOTA as a chelator would improve the biodistribution of 68Ga-labelled anti-PDGFRβ Affibody molecules.
In conclusion, the results from this study demonstrate that 68Ga-DOTAZ09591 is a suitable agent for imaging of PDGFR-expressing xenografts in
vivo using PET due to its rapid and specific targeting of PDGFRβ. As early
as two hours after injection of 68Ga-DOTA-Z09591, PDGFRβ expressing xenografts were visualized using microPET. It is possible that further optimization of the labelling chemistry, e.g., the use of NODAGA instead of DOTA as
a chelator, would further improve the imaging contrast.
50
Figure 10. Comparison of tumour-to-organ ratios at one and two hours p.i for 68GaDOTA-Z09195 and 111In-DOTA-Z09195 in BALB/C nu/nu mice bearing U-87 MG
xenografts. Data are presented as the mean ± SD for 4 mice. *significant difference
(p<0.05) between 68Ga-DOTA-Z09591 and 111In-DOTA-Z09591
51
Paper V
Site-specific radioiodination of HER2-targeting Affibody molecules
using 4-iodophenetylmaleimide decreases the renal uptake of
radioactivity.
Background and aim
In papers I-IV, 68Ga- and 111In-labelled HER2- and PDGFRβ-targeting Affibody molecules demonstrated high tumour-to-organ ratios. However, a
remaining challenge for radiometal labelling is the high reabsorption by the
kidneys. This is might be associated with high kidney radioactivity retention
and low contrast imaging in the lumbar region. One approach to overcome
this issue is based on the fact that the internalization of Affibody molecules
by cancer cells is slow. The accumulation of radioactivity in tumours due to
the residualizing properties of radiocatabolites is not critical; instead, the
non-residualizing properties of a radiocatabolite would facilitate excretion
and reduce renal retention.
In a previous study, the use of radioiodinated 3-iodo-((4hydroxyphenyl)ethyl)maleimide (I-HPEM) for the site-specific labelling of
cysteine-containing Affibody molecules provided lower radioactivity retention in the kidneys compared with the use of N-succinimidyl-4-iodobenzoate
(Mume et al 2005). The exact mechanism of the decrease in kidney uptake is
not entirely clear. Presumably, exoproteases in the tubular cells are involved
in the cleavage of Affibody molecules, and a label at the C-terminus is
cleaved more rapidly. We hypothesized that the use of a more lipophilic
linker than HPEM for the terminal labelling of Affibody molecules might
result in more “leaky” lipophilic radiocatabolites, which could be utilized for
the labelling of Affibody molecules with, e.g., 124I, for PET imaging.
The aim was to test the hypothesis that a more lipophilic linker for radiohalogens confers lower renal retention of radioactivity after Affibody molecule injection. For this purpose, we compared the biodistribution of Affibody
molecules labelled using 125I-IPEM with its 125I-IHPEM-labeled counterpart.
The structure of IPEM and IHPEM are given in Figure 11.
Figure 11. Structures of 125I-3-iodo-((4-hydroxyphenyl)ethyl)maleimide (I-HPEM)
(A) and 125I-4-iodophenetylmaleimide (IPEM) (B) conjugated to an Affibody molecule via a C-terminal cysteine.
52
Methods
The labelling of IPEM with 125I and coupling of 125I-IPEM to pre-reduced
HER2-targeting (ZHER2:2395) Affibody molecule was optimized. To ensure
that the radioiodine was stably attached to the Affibody molecule, a sample
of the conjugate was incubated in 2 M sodium iodide, 30 % ethanol and PBS
as a control. The specificity of binding and the cellular processing of 125IIPEM-ZHER2:2395 and 125I-IHPEM-ZHER2:2395 were compared in vitro using
HER2-expressing SKOV-3 cells. The biodistribution properties of 125IIPEM-ZHER2:2395 and 125I-IHPEM-ZHER2:2395 were compared in normal MRI
mice at 1, 4 and 24 h after injection.
Results
The labelling with IPEM with 125I provided a radiochemical yield of 73±3 %.
After conjugation of 125I-IPEM to ZHER2:2395 at the Affibody:IPEM molar
ration of 2:1, the overall yield of radioiodination was 43±4 %. The different
stability tests demonstrated stable labelling.
The specificity test demonstrated significantly (p<0.00005 ) reduced binding of 125I-IPEM-ZHER2:2395 to HER2-expressing cells, which demonstrated
binding specificity. Cellular processing of 125I-IPEM-ZHER2:2395 showed more
rapid excretion of the radiocatabolites than did the cellular processing of 125IIHPEM-ZHER2:2395.
At 1 and 4 h after injection, there was significantly lower kidney retention
of 125I-IPEM-ZHER2:2395 (24±2 and 5.7±0.3 %IA/g) compared to 125I-IHPEMZHER2:2395 (50±8 and 12±2 %IA/g) (Figure 12). However, 125I-IPEMZHER2:2395 exhibited higher uptake in the liver at 1 h pi (4.1±0.7 %IA/g) compared to 125I-IHPEM-ZHER2:2395 (2.7±0.1 %IA/g) (Table 7). In organs expressing the Na/I symporter (stomach and salivary gland), radioactivity uptake
was significantly (p<0.05) lower at least one time point for 125I-IPEMZHER2:2395. Blood retention was significantly higher for 125I-IPEM-ZHER2:2395
(2.8±0.4, 0.81±0.06 and 0.38±0.003 %IA/g) than 125I-IHPEM-ZHER2:2395
(2.2±0.2, 0.56±0.04 and 0.12±0.07 %IA/g) at all time points.
Discussion and conclusion
The results confirmed our main hypothesis: the use of a more lipophilic linker reduces the renal radioactivity retention of radioiodinated Affibody molecules. The cellular processing showed that the maximum cell-associated
activity was reached earlier for 125I-IPEM-ZHER2:2395 than 125I-IHPEMZHER2:2395 (4 h vs. 8 h), suggesting that 125I-IPEM results in more lipophilic
radiocatabolites that leak rapidly from the cell. A more rapid diffusion of
more lipophilic radiocatabolites through lysosomal and cellular membranes
can also explain why the renal radioactivity was two times lower for 125IIPEM-ZHER2:2395 than 125I-IHPEM-ZHER2:2395 at 1 h and 4 h after injection.
Unfortunately, the higher overall lipophilicity of 125I-IPEM-ZHER2:2395 resulted in a higher liver uptake. This is in agreement with the previous data show53
ing that the modification of Affibody molecules with lipophilic pendant
groups is associated with a higher level of hepatic uptake and/or hepatobiliary excretion (Hoffström et al. 2013). However, the difference disappeared
at later time points. Interestingly, the blood radioactivity concentration was
1.5-fold higher for 125I-IPEM-ZHER2:2395 compared to 125I-IHPEM-ZHER2:2395.
This could possibly be explained by the escape of the radiocatabolites from
the kidney into the blood stream.
In conclusion, the use of labels providing more lipophilic catabolites
might allow for decreased renal retention of radiohalogens. However, further studies are required to solve the problems associated with the use of
lipophilic prosthetic groups, e.g., elevated hepatic uptake and blood-borne
radioactivity.
54
Table 7. Comparison of the biodistribution of 125I-IPEM-ZHER2:2395 and 125I-IHPEMZHER2:2395 in NMRI mice. Uptake is expressed as %IA/g, and presented as the mean ±
S.D. for four mice. Data from the gastrointestinal (GI) tract with content and carcass are presented as % of injected radioactivity per the entire sample.
1h
4h
24 h
IPEM
IPEM
IPEM
IHPEM
IPEM
IHPEM
Blood
2.8±0.4[a]
2.2±0.2
0.81±0.06[a]
0.56±0.04
0.38±0.03 [a]
0.12±0.07
Lung
2.8±0.5
2.6±0.3
0.57±0.04
0.54±0.06
0.13±0.01[a]
0.07±0.01
Liver
4.1±0.7[a]
2.7±0.1
1.4±0.1
1.4±0.3
0.18±0.06[a]
0.07±0.02
Spleen
1.0±0.2
0.9±0.1
0.34±0.04
0.29±0.05
0.12±0.01[a]
0.04±0.03
Stomach
1.1±0.1[a]
2.1±0.4
0.40±0.05[a]
2±1
0.05±00.01
0.07±0.03
Kidney
24±2[a]
50±9
5.7±0.3[a]
12±2
0.90±0.09 [a]
0.6±0.3
Salivary
gland
Muscle
1.0±0.2
1.2±0.6
0.34±0.06[a]
1.6±0.3
0.026±0.008
0.040±0.003
0.6±0.1
1.1±0.9
0.11±0.01
0.12±0.04
0.012±0.003
0.010±0.002
GI tract
9±1[a]
12±1
9.8±0.9[a]
18±3
0.18±0.04
0.32±0.09
Carcass
14±2
14±1
3.1±0.3
3.8±1.0
0.57±0.09
1.18±0.66
[a]
Significant (p<0.05) difference between
the same time point.
125
I-IPEM-ZHER2:2395 and
125
I-IHPEM-ZHER2:2395 at
Figure 12. Comparison of the renal retention of radioactivity after injection of 125IIPEM-ZHER2:2395 and 125I-IHPEM-ZHER2:2395 into NMRI mice. Uptake is expressed as
%IA/g, and presented as the mean ± S.D. for four mice
55
Concluding remarks
The results in the present thesis has demonstrated the feasibility of PET imaging of HER2- and PDGFRβ-expressing tumours in vivo using Affibody
molecules. Furthermore, this thesis has also demonstrated that the in vivo
biodistribution properties of Affibody molecules depend on the selected
chelator, linker molecule, radionuclide and chelator position in the Affibody
molecule. This information is essential for the further development of Affibody molecules for radionuclide molecular imaging of other molecular
targets (e.g., IGF-1R, CAIX and HER3). The information could also be
equally useful when developing other targeting probes.
The major findings from this thesis are as follows:
•
•
•
•
•
56
A clear influence of a radionuclide on biodistribution and targeting was observed. Consequently, 111In-labelled Affibody molecules cannot be used to predict the in vivo properties of their 68Galabelled analogues.
The difference in biodistribution properties for the different chelators for HER2-targeting Affibody molecules was smaller for 68Ga
than for 111In.
The substitution of DOTA with NODAGA was found to provide
superior imaging properties for 68Ga-labelled recombinant HER2targeting Affibody molecules (ZHER2:2395) in the case of C-terminal
placement of the label. For 111In-labelled conjugates, the DOTA
chelator provided the overall highest tumour-to-organ ratios. This
indicates that the choice of chelator can have a significant influence on the biodistribution of Affibody molecules.
NODAGA was also found to provide higher tumour-to-organ ratios compared to DOTA and NOTA for synthetically produced
68
Ga-labelled HER2-targeting Affibody molecules when placed at
the N-terminus. The NOTA conjugate labelled with both 111In and
68
Ga showed unfavourable high liver uptake, a problem for tumour imaging because the liver is a major organ for tumour metastasis.
Chelator positioning of Affibody molecules (N-terminus, middle
of helix 3 or C-terminus) influences biodistribution properties. Positioning of the DOTA chelator at the N-terminus provided the
•
•
•
•
best tumour-to-organ ratios for 68Ga-labeled synthetic HER2targeting Affibody molecules.
Efficient and stable labelling of the PDGFRβ-binding Affibody
molecule with 68Ga was demonstrated. Rapid and specific targeting of PDGFRβ-expressing U-87 MG xenografts in immunodeficient mice using 68Ga-DOTA-Z09591 was shown.
PET imaging using a 68Ga-labelled PDGFRβ-targeting Affibody
molecule provided a high-contrast image of a PDGFRβexpressing xenograft in vivo.
Affibody molecules should provide a useful clinical tool for imaging of PDGFRβ expression in various pathologic conditions.
Using a lipophilic linker for radioiodination reduces renal radioactivity retention of Affibody molecules. However, further studies
are required to solve the problems associated with the use of lipophilic prosthetic groups, e.g., elevated hepatic uptake and bloodborne radioactivity.
In conclusion, this thesis clearly demonstrates that the labelling strategy is
of outmost importance, has substantial influence on the targeting properties
of Affibody molecules and should be taken under serious considerations
when developing new imaging agents.
57
Ongoing and future studies
Previously, a negatively charged amino acid tag placed at the N-terminus of
a HER2-targeting Affibody molecule labelled with 99mTc provided the lowest non-specific accumulation of radioactivity in vivo in comparison to different positions and charges of the tag (Hofström et al, 2013). Based on these
results, I hypothesized that modifications leading to increase of negative
charge at the N-terminus may further improve the biodistribution profile of
Affibody molecules. To test this hypothesis, we considered a macrocyclic
chelator that forms a negative net charge with trivalent metals, i.e., DOTA(GA). We planned a study where DOTA(GA) is coupled to the Nterminus of a HER2-targeting Affibody molecule (ZHER2:2891) with the aim of
comparing the influence of chelators on properties of 68Ga-labelled Affibody
molecules with their influence on the properties of 111In-labelled counterparts
(111In-DOTA(GA)-ZHER2:2891 and 111In-DOTA-ZHER2:2891). Our preliminary
data confirmed this hypothesis, e.g., noticeable decrease of hepatic uptake.
Another approach would be to use divalent metals, e.g. 55Co as the label, in
combination with DOTA, NODAGA and DOTA(GA). 68Ga, which has the
same complex structure but carries an extra positive charge can be used for
comparison. One could also consider the use of a negatively charged linker,
e.g., oligoglutamate, for this purpose. The biodistribution of a series of
NODAGA- or DOTA-conjugated 68Ga-labeled derivatives containing one,
two or three glutamate between a chelator and an Affibody molecule should
be compared. These studies might further improve the contrast of imaging
using Affibody molecules.
Papers I, II and III demonstrated that the influence of the radionuclide
on the biodistribution and targeting properties of anti-HER2 Affibody molecules depends on the chelator used for labelling, as well as on the position of
the chelator. This creates a pre-condition for further optimization of the targeting properties of PDGFRβ-targeting Affibody molecules by selection of
an optimal chelator. I propose to perform an in vivo comparison of antiPDGFRβ Affibody molecules labelled with 68Ga at the C-terminus using
maleimido derivatives of DOTA and NODAGA.
In a recent clinical study, a HER2-targeting Affibody molecule
(ABY025) was labelled with 68Ga for PET imaging and injected into eleven
patients with known metastatic breast cancer. PET imaging was performed,
and the results demonstrated a decrease in activity over time in most normal
organs, with the best contrast provided at 4 hours after injection (Sörensen
58
2014). However, 68Ga is not optimal for imaging at late time points due its
short half-life. This enables the use of a long-lived PET radionuclide such as
64
Cu, 76Br, 124I, 89Zr, 44Sc or 86Y (Pagani et al, 1997). In particular, 44Sc
would be of interest due to its 3.97 hour half-life and its high positron yield
of 94.27 % (Roesch F et al. 2012). The labelling procedure would be similar
to that of 68Ga, though I could speculate that because 44Sc has a smaller radius, NOTA or NODAGA as a chelator would confer better biodistribution
properties.
The clinical implementation is that utilizing Affibody molecule imaging
agents optimized according to the findings of this thesis would facilitate the
goal of improving the personalization of therapy.
59
Acknowledgements
I often get the question of how I could manage to combine two educations
during the same time. The answer is: because of support from friends, family
and colleges. I am tremendously thankful for all of your support during my
thesis work.
I would like to especially thank the following:
My main supervisor, Professor Vladimir Tolmachev, for giving me the
opportunity to become a PhD student. You have taught me everything I
know about radiochemistry; knowledge I will always carry with me in my
future research.
My co-supervisor Associate Professor Anna Orlova. Thank you for supervising me during all the cell studies and animal studies.
I am very grateful for all the fun dinners and group meetings you and Vladimir have hosted at your home, which have contributed to a great group
environment.
My co-supervisor Irina Velikyan, thank you for sharing your knowledge on
68
Ga.
Professor Bo Stenerlöw, you were the first to introduce me to BMS. Thank
you for all the help during these years.
I would probably never have moved to Uppsala, and never be where I am
today if it wasn’t for Jörgen and Anncki Carlsson. Thank you for your
kindness and giving me the best start in Uppsala!
I don’t think many people get both a PhD and friends for life, and I got both!
To the best group mates you could possibly have:
Hadis, you are the most intelligent and strongest person I know. During up’s
and downs both in research and life you have always supported and helped
me. I am so thankful to all you have done for me. If it wasn’t for you I would
never be where I am today
Mohamed Altai, you have taught me so much during these years, not only
about science but also religion, politics and human values. I honestly think
you have made me into a better person.
Maria, tack så mycket för allt stöd under dessa år, minns framför allt hur
mycket det hjälpte mig i Lyon.
Bogdan, when you come to our office and had a simple question, you always ended up staying for a long time talking. You are such a nice person.
Javad, it has been so fun sitting in the ”back” with you.
60
The rest of BMS:
Kicki, tack för all hjälp och goda råd på vägen, du får oss doktorander att
känna oss som hemma på BMS.
Helene, tack för all hjälp med administrering, inte nog med att allt alltid gick
så snabbt och smidigt, du lyckades även alltid ordna med det bästa lösningarna. Vi saknar dig!
Anja, har aldrig blivit så berörd som efter alla fina ord efter min halv-tid.
Jonas & Magda, vi har haft mycket roligt tillsammans, filmer, disputationer, fester och konferenser.
Ram, the best Michael Jackson imitator and friend. Thank you for all the
nice pictures.
Sara A, Amelie, Ann-Sofie, Jennie, Andris, Hanna, Kalle, Marika,
Zohreh, Jos and Diana, thank you for all the fun we have had together.
Our collaborators in KTH, Amelie, Daniel, Helena, Anna, and all the others, thank you for the nice collaborations.
Vänner utanför BMS:
Det var inte lätt att komma till en ny klass i en ny stad utan att känna någon,
men ni fick mig att känna mig som hemma, tack för den bästa tiden i livet!
Elin tack för allt roligt vi har gjort och för att man får sova hos dig när livet
känns lite jobbigt. Karro, tack för att du är en bra vän som man alltid kan
vända sig till. Linnea, tack för allt kul vi har haft, speciellt när du kom till
Kalifornien och hälsade på. Ada, tack för alla roliga fester, middagar och
tentaplugg.
Karin Busk, jag är så otroligt tacksam för all din hjälp i Umeå. Du fixade
boende och delade med dig av anteckning. Tack för att du ljusnade upp en
mörk vinter i Umeå.
Ebba, delar så många minnen med dig: hipp-hoppare, koner, halv-tids panik,
EKG-tolkning, middagar, midsomrar, hemmabryggt vin på nollningen, skidåkning, tentaplugg (!!), BUP och så mycket mer. Genom åren har du blivit
en av mina närmaste vänner. Du kommer bli en fantastisk dubbel doktor.
Trodde aldrig att jag skulle hitta min bästa vän i Umeå. Lisa jag är så glad
att jag träffade dig. Vi har pluggat, gråtit, haft panik och ångest tillsammans
men framför allt har vi haft så kul ihop, du får mig alltid att skatta. Du kommer bli världen bästa läkare. Anton och Majken, är glad att även ni har
blivit mina närmaste vänner.
Sofie, min äldsta vän, sedan dagis! Tack för alla roliga stunder med dig,
Fredrik och Isabella. Mia, så mycket roligt och galet vi har gjort tillsammans under alla år. Du är en av dom finaste vännerna jag har. Sussy, jag
hoppas Alice har turen att hittar en lika bra vän som dig att växa upp med.
Marie-Louise, Anne-Kjersti, Caroline, Cecilie, tack, takk och tak för att ni
gjorde 2009/10 till mitt livs bästa år i Kalifornien, och tack för allt skoj därefter.
61
Louise, min skånska vän i Uppsala. Jag är så glad att jag bara kan springa
över till dig när man behöver prata eller bara vill hänga lite. Du är en vän för
livet.
Min första handledare, Hanna-Linn Wargelius. Tack så mycket för att du
introducerade mig till forskningen och inspirerade mig till att börja läsa på
läkarprogrammet.
Familjen Marcusson tack för all god mat, goda råd och för att jag alltid
känner mig välkommen till er familj.
Familj
David, tack för ditt stöd under denna resa. Du gör mig till den lyckligaste i
världen, även när det är 70 mil mellan oss. Jag ser fram emot att få dela mitt
liv med dig.
Mina syskon, Emil och Filip, man väljer inte sina syskon men om man
gjorde det skulle jag aldrig välja andra syskon än er. Tack för alla intressanta
diskussioner och allt ni har lärt mig.
Mamma och Pappa, utan er hade jag aldrig disputerat. Sven-Erik tack för
att du läst min avhandling nästa lika många gånger som jag har gjort, lärt
mig allt jag kan om fysik och dosimetri, och för alla mil vi har sprungit tillsammans. Mamma tack för ditt oändliga stöd, hjälp och goda råd genom hela
avhandlingen och hela livet. Tack för att ni är världens bästa föräldrar.
Tills sist, mina Mor- och farföräldrar, som aldrig ens hade möjligen att gå
ut grundskolan. Jag glömmer lätt vilket privilegium det har varit att få utbilda mig, så tack för att ni la grunden till min avhandling.
Joanna Strand
24/7-2015 Malmö
62
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Acta Universitatis Upsaliensis
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