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Kisspeptins (KPs, KISS1) and their receptor (KISS1R) play a pivotal role as metastasis suppressor for many cancers. Low or lost KP expression is associated with higher tumor grade, increased metastatic potential, and poor prognosis. Therefore, KP expression has prognostic relevance and correlates with invasiveness in cancers. Furthermore, KISS1R represents a very promising target for molecular imaging and therapy for KISS1R-expressing tumors. The goal of this study was to evaluate the developed KISS1-54 derivative, [\(^{68}\)Ga]KISS1-54, as a PET-imaging probe for KISS1R-expressing tumors. The NODAGA-KISS1-54 peptide was labeled by Gallium-68, and the stability of the resulting [\(^{68}\)Ga]KISS1-54 evaluated in injection solution and human serum, followed by an examination in different KISS1R-expressing tumor cell lines, including HepG2, HeLa, MDA-MB-231, MCF7, LNCap, SK-BR-3, and HCT116. Finally, [\(^{68}\)Ga]KISS1-54 was tested in LNCap- and MDA-MB-231-bearing mice, using µ-PET, assessing its potential as an imaging probe for PET. [\(^{68}\)Ga]KISS1-54 was obtained in a 77 ± 7% radiochemical yield and at a >99% purity. The [\(^{68}\)Ga]KISS1-54 cell uptake amounted to 0.6–4.4% per 100,000 cells. Moreover, the accumulation of [\(^{68}\)Ga]KISS1-54 was effectively inhibited by nonradioactive KISS1-54. In [\(^{68}\)Ga]KISS1-54-PET, KISS1R-positive LNCap-tumors were clearly visualized as compared to MDA-MB-231-tumor implant with predominantly intracellular KISS1R expression. Our first results suggest that [\(^{68}\)Ga]KISS1-54 is a promising candidate for a radiotracer for targeting KISS1R-expressing tumors via PET.
AimIn PET imaging, the different types of radiotracers and accumulations, as well as the diversity of disease patterns, make the analysis of molecular imaging data acquired in vivo challenging. Here, we evaluate and validate a semi-automated MRI template-based data analysis tool that allows preclinical PET images to be aligned to a self-created PET template. Based on the user-defined volume-of-interest (VOI), image data can then be evaluated using three different semi-quantitative parameters: normalized activity, standardized uptake value, and uptake ratio.
Materials and MethodsThe nuclear medicine Data Processing Analysis tool (NU_DPA) was implemented in Matlab. Testing and validation of the tool was performed using two types of radiotracers in different kinds of stroke-related brain diseases in rat models. The radiotracers used are 2-[\(^{18}\)F]fluoro-2-deoxyglucose ([\(^{18}\)F]FDG), a metabol\(^{68}\)Ga]Ga-Fucoidan, a target-selective radioligand specifically binding to p-selectin. After manual image import, the NU_DPA tool automatically creates an averaged PET template out of the acquired PET images, to which all PET images are then aligned onto. The added MRI template-based information, resized to the lower PET resolution, defines the VOI and also allows a precise subdivision of the VOI into individual sub-regions. The aligned PET images can then be evaluated semi-quantitatively for all regions defined in the MRI atlas. In addition, a statistical analysis and evaluation of the semi-quantitative parameters can then be performed in the NU_DPA tool.
ResultsUsing ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [\(^{18}\)F]FDG-PET experiment, three different experimental states were compared: healthy control state, ischemic stroke without electrical stimulation, ischemic stroke with electrical stimulation. Thereby, statistical data evaluation using the NU_DPA tool showed that the glucose metabolism in a photothrombotic lesion can be influenced by electrical stimulation.
ConclusionOur NU_DPA tool allows a very flexible data evaluation of small animal PET data in vivo including statistical data evaluation. Using the radiotracers [\(^{18}\)F]FDG and [\(^{68}\)Ga]Ga-Fucoidan, it was shown that the semi-automatic MRI-template based data analysis of the NU_DPA tool is potentially suitable for both metabolic radiotracers as well as target-selective radiotracers.