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A question relevant to nicotine addiction is how nicotine and other nicotinic receptor membrane-permeant ligands, such as the anti-smoking drug varenicline (Chantix), distribute in brain. Ligands, like varenicline, with high pKaand high affinity for α4β2-type nicotinic receptors (α4β2Rs) are trapped in intracellular acidic vesicles containing α4β2Rsin vitro. Nicotine, with lower pKaand α4β2R affinity, is not trapped. Here, we extend our results by imaging nicotinic PET ligandsin vivoin male and female mouse brain and identifying the trapping brain organellein vitroas Golgi satellites (GSats). Two PET18F-labeled imaging ligands were chosen: [18F]2-FA85380 (2-FA) with varenicline-like pKaand affinity and [18F]Nifene with nicotine-like pKaand affinity. [18F]2-FA PET-imaging kinetics were very slow consistent with 2-FA trapping in α4β2R-containing GSats. In contrast, [18F]Nifene kinetics were rapid, consistent with its binding to α4β2Rs but no trapping. Specific [18F]2-FA and [18F]Nifene signals were eliminated in β2 subunit knock-out (KO) mice or by acute nicotine (AN) injections demonstrating binding to sites on β2-containing receptors. Chloroquine (CQ), which dissipates GSat pH gradients, reduced [18F]2-FA distributions while having little effect on [18F]Nifene distributionsin vivoconsistent with only [18F]2-FA trapping in GSats. These results are further supported byin vitrofindings where dissipation of GSat pH gradients blocks 2-FA trapping in GSats without affecting Nifene. By combiningin vitroandin vivoimaging, we mapped both the brain-wide and subcellular distributions of weak-base nicotinic receptor ligands. We conclude that ligands, such as varenicline, are trapped in neurons in α4β2R-containing GSats, which results in very slow release long after nicotine is gone after smoking.SIGNIFICANCE STATEMENTMechanisms of nicotine addiction remain poorly understood. An earlier study usingin vitromethods found that the anti-smoking nicotinic ligand, varenicline (Chantix) was trapped in α4β2R-containing acidic vesicles. Using a fluorescent-labeled high-affinity nicotinic ligand, this study provided evidence that these intracellular acidic vesicles were α4β2R-containing Golgi satellites (GSats).In vivoPET imaging with F-18-labeled nicotinic ligands provided additional evidence that differences in PET ligand trapping in acidic vesicles were the cause of differences in PET ligand kinetics and subcellular distributions. These findings combiningin vitroandin vivoimaging revealed new mechanistic insights into the kinetics of weak base PET imaging ligands and the subcellular mechanisms underlying nicotine addiction.

Development of positron emission tomography (PET) radiotracers that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allows for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. One challenge associated with preclinical PET imaging involves the lack of true tissue reference regions free of specific tracer binding in the rodent brain, impeding accurate quantification of the tracer binding potential. Here, we investigate the use of an image-derived arterial input function for kinetic analysis of radiotracer binding in male and female mice. Two radiotracers were explored in this study: 2-[18F]FA85380 (2-FA), which displays similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, which displays similar pKa and binding affinity to nicotine. For both radiotracers, time-activity curves of the left ventricle of the heart displayed similar standardized uptake values (SUVs) across wild type mice, mice lacking the β2 subunit for tracer binding, and acute nicotine-treated mice, whereas typical reference tissue SUVs displayed high variation between groups. Binding potential values estimated from a two-tissue compartment model (2TCM) fit of the data with the image-derived input function were significantly higher than estimates from reference tissue-based estimations. Rate constants of radiotracer dissociation were very slow for 2-FA and very fast for Nifene, similar to the in vitro dissociation rates reported for varenicline and nicotine, respectively. We conclude that use of an image-derived input function for kinetic modeling of nicotinic PET ligands improves quantification compared to reference tissue-based methods, and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

To identify the optimal threshold insup18/supF-fluoromisonidazole (FMISO) PET images to accurately locate tumor hypoxia by using electron paramagnetic resonance imaging (pOsub2/subEPRI) as ground truth for hypoxia, defined by pOsub2/sub[Formula: see text] 10 mmHg.Tumor hypoxia images in mouse models of SCCVII squamous cell carcinoma (n = 16) were acquired in a hybrid PET/EPRI imaging system 2 h post-injection of FMISO. T2-weighted MRI was used to delineate tumor and muscle tissue. Dynamic contrast enhanced (DCE) MRI parametric images of Ksuptrans/supand vsube/subwere generated to model tumor vascular properties. Images from PET/EPR/MRI were co-registered and resampled to isotropic 0.5 mm voxel resolution for analysis. PET images were converted to standardized uptake value (SUV) and tumor-to-muscle ratio (TMR) units. FMISO uptake thresholds were evaluated using receiver operating characteristic (ROC) curve analysis to find the optimal FMISO threshold and unit with maximum overall hypoxia similarity (OHS) with pOsub2/subEPRI, where OHS = 1 shows perfect overlap and OHS = 0 shows no overlap. The means of dice similarity coefficient, normalized Hausdorff distance, and accuracy were used to define the OHS. Monotonic relationships between EPRI/PET/DCE-MRI were evaluated with the Spearman correlation coefficient ([Formula: see text]) to quantify association of vasculature on hypoxia imaged with both FMISO PET and pOsub2/subEPRI.FMISO PET thresholds to define hypoxia with maximum OHS (both OHS = 0.728 [Formula: see text] 0.2) were SUV [Formula: see text] 1.4 [Formula: see text] SUVsubmean/suband SUV [Formula: see text] 0.6 [Formula: see text] SUVsubmax/sub. Weak-to-moderate correlations (|[Formula: see text]|lt; 0.70) were observed between PET/EPRI hypoxia images with vascular permeability (Ksuptrans/sup) or fractional extracellular-extravascular space (vsube/sub) from DCE-MRI.This is the first in vivo comparison of FMISO uptake with pOsub2/subEPRI to identify the optimal FMISO threshold to define tumor hypoxia, which may successfully direct hypoxic tumor boosts in patients, thereby enhancing tumor control.