Abstract
IntroductionPathological formation of fibrosis, is an important feature in many diseases. Fibrosis in liver and pancreas has been associated to metabolic disease including type 1 and 2 diabetes. The current methods for detecting and diagnosing fibrosis are either invasive, or their sensitivity to detect fibrosis in early stage is limited. Therefore, it is crucial to develop non-invasive methods to detect, stage and study the molecular processes that drive the pathology of liver fibrosis. The peptide LRELHLNNN was previously identified as a selective binder to collagen type I with an affinity of 170 nM. Radiolabelled LRELHLNNN thus constitute a potential PET tracer for fibrosis. MethodLRELHLNNN was conjugated to a DOTA/NOTA moiety via a PEG2-linker. DOTA-PEG2-LRELHLNNN was labelled with Gallium-68 and NOTA- PEG2-LRELHLNNN with aluminium fluoride-18. Biodistribution of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN was performed in healthy rats ex vivo and in vivo. The 68Ga-labelled analogue was evaluated in a mouse model of liver fibrosis by PET/MRI-imaging. The human predicted dosimetry of the tracers was extrapolated from rat ex vivo biodistribution studies at 10, 20, 40, 60, 120, 180 min (only fluoride-18) post-injection. ResultsThe peptides were successfully radiolabelled with gallium-68 and aluminium fluoride-18, respectively. The biodistribution of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN was favorable showing rapid clearance and low background binding in organs where fibrosis may develop. Binding of [68Ga]Ga-DOTA-PEG2-LRELHLNNN to fibrotic liver was higher than surrounding tissues in mice with induced hepatic fibrosis. However, the binding was in the range of SUV 0.3, indicating limited targeting of the tracer to liver. The extrapolated human predicted dosimetric profiles of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN were beneficial, potentially allowing at least three PET examinations annually. ConclusionsWe describe the modification, radiolabelling and evaluation of the collagen type I binding peptide LRELHLNNN. The resulting radiotracer analogues demonstrated suitable biodistribution and dosimetry. [68Ga]Ga-DOTA-PEG2-LRELHLNNN exhibited binding to hepatic fibrotic lesions and is a promising tool for PET imaging of fibrosis. Advances in knowledgeValidation of a new collagen targeting PET tracer. Implications for patient careEarly, non-invasive diagnosis and stratification of fibrosis in order to improve the diagnosis, staging and treatment of patients with diseases involving fibrosis.
Highlights
Pathological formation of fibrosis, is an important feature in many diseases
Non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) involves chronic inflammation triggering the activation of fibroblasts which in turn leads to production and deposition of extracellular matrix such as collagen
DOTA-PEG2-LRELHLNNN was labelled with 68Ga (n = 7) and purified using a solid-phase extraction cartridge, resulting in a radiochemical purity of >97%
Summary
Pathological formation of fibrosis, is an important feature in many diseases. Fibrosis in liver and pancreas has been associated to metabolic disease including type 1 and 2 diabetes. The biodistribution of [68Ga]Ga-DOTA-PEG2-LRELHLNNN and [18F]AlF-NOTA-PEG2-LRELHLNNN was favorable showing rapid clearance and low background binding in organs where fibrosis may develop. Binding of [68Ga] Ga-DOTA-PEG2-LRELHLNNN to fibrotic liver was higher than surrounding tissues in mice with induced hepatic fibrosis. [68Ga] Ga-DOTA-PEG2-LRELHLNNN exhibited binding to hepatic fibrotic lesions and is a promising tool for PET imaging of fibrosis. The treatment and monitoring of hepatic fibrosis is hampered by the lack of suitable methods for detecting and diagnosing the disease The current methods such as fine needle aspiration biopsy is invasive, with risk of injury and sampling errors, and there is a lack of plasma biomarkers that could be used to diagnose and detect the changes in the fibrosis development as response to interventions [4]
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