Affibody Molecules For Pet Imaging

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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 References Ahlgren, S., Orlova, A., Wållberg, H., Hansson, M., Sandström, M., Lewsley, R., Wennborg, A., Abrahmsén, L., Tolmachev, V., Feldwisch, J. (2010) a. 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Adv Cancer Res, 97:247-74. 70 Acta Universitatis Upsaliensis Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1125 Editor: The Dean of the Faculty of Medicine A doctoral dissertation from the Faculty of Medicine, Uppsala University, is usually a summary of a number of papers. A few copies of the complete dissertation are kept at major Swedish research libraries, while the summary alone is distributed internationally through the series Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine. (Prior to January, 2005, the series was published under the title “Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine”.) Distribution: publications.uu.se urn:nbn:se:uu:diva-259410 ACTA UNIVERSITATIS UPSALIENSIS UPPSALA 2015