Arginine-Selective Bioconjugation Reagent for Effective 18F-labeling of Native Proteins.

Protein-based 18F-PET tracers offer new possibilities in early disease detection and personalized medicine. Their development relies heavily on the availability and effectiveness of 18F-prosthetic groups. We prepared and evaluated a novel arginine-selective prosthetic group, 4-[18F]fluorophenylglyoxal ([18F]FPG). [18F]FPG was radiosynthesized by a one-pot, two-step procedure with a non-decay-corrected (n.d.c.) isolated radiochemical yield (RCY) of 41 ± 8% (n = 10). [18F]FPG constitutes a generic tool for 18F-labeling of various proteins, including human serum albumin (HSA), ubiquitin, interleukin-2, and interleukin-4 in ∼30-60% n.d.c. isolated RCYs. [18F]FPG conjugation with arginine residues is highly selective, even in the presence of a large excess of lysine, cysteine, and histidine. [18F]FPG protein conjugates are able to preserve the binding affinity of the native proteins while also demonstrating excellent in vivo stability. The [18F]FPG-HSA conjugate has prolonged blood retention, which can be applied as a potential blood pool PET imaging agent. Thus, [18F]FPG is an arginine-selective bioconjugation reagent that can be effectively used for the development of 18F-labeled protein radiopharmaceuticals.

Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.

INTRODUCTION: The classification of prostate cancer (PCa) lesions using Prostate Imaging Reporting and Data System (PI-RADS) suffers from poor inter-reader agreement. This study compared quantitative parameters or radiomic features from multiparametric magnetic resonance imaging (mpMRI) or positron emission tomography (PET), as inputs into machine learning (ML) to predict the Gleason scores (GS) of detected lesions for improved PCa lesion classification. METHODS: 20 biopsy-confirmed PCa subjects underwent imaging before radical prostatectomy. A pathologist assigned GS from tumour tissue. Two radiologists and one nuclear medicine physician delineated the lesions on the mpMR and PET images, yielding 45 lesion inputs. Seven quantitative parameters were extracted from the lesions, namely T2-weighted (T2w) image intensity, apparent diffusion coefficient (ADC), transfer constant (KTRANS), efflux rate constant (Kep), and extracellular volume ratio (Ve) from mpMR images, and SUVmean and SUVmax from PET images. Eight radiomic features were selected out of 109 radiomic features from T2w, ADC and PET images. Quantitative parameters or radiomic features, with risk factors of age, prostate-specific antigen (PSA), PSA density and volume, of 45 different lesion inputs were input in different combinations into four ML models - Decision Tree (DT), Support Vector Machine (SVM), k-Nearest-Neighbour (kNN), Ensembles model (EM). RESULTS: SUVmax yielded the highest accuracy in discriminating detected lesions. Among the 4 ML models, kNN yielded the highest accuracies of 0.929 using either quantitative parameters or radiomic features with risk factors as input. CONCLUSIONS: ML models' performance is dependent on the input combinations and risk factors further improve ML classification accuracy.

Imaging Memory T-Cells Stratifies Response to Adjuvant Metformin Combined with αPD-1 Therapy.

The low response rates associated with immune checkpoint inhibitor (ICI) use has led to a surge in research investigating adjuvant combination strategies in an attempt to enhance efficacy. Repurposing existing drugs as adjuvants accelerates the pace of cancer immune therapy research; however, many combinations exacerbate the immunogenic response elicited by ICIs and can lead to adverse immune-related events. Metformin, a widely used type 2 diabetes drug is an ideal candidate to repurpose as it has a good safety profile and studies suggest that metformin can modulate the tumour microenvironment, promoting a favourable environment for T cell activation but has no direct action on T cell activation on its own. In the current study we used PET imaging with [18F]AlF-NOTA-KCNA3P, a radiopharmaceutical specifically targeting KV1.3 the potassium channel over-expressed on active effector memory T-cells, to determine whether combining PD1 with metformin leads to an enhanced immunological memory response in a preclinical colorectal cancer model. Flow cytometry was used to assess which immune cell populations infiltrate the tumours in response to the treatment combination. Imaging with [18F]AlF-NOTA-KCNA3P demonstrated that adjuvant metformin significantly improved anti-PD1 efficacy and led to a robust anti-tumour immunological memory response in a syngeneic colon cancer model through changes in tumour infiltrating effector memory T-cells.

Fluorine-18 Labeling of Difluoromethyl and Trifluoromethyl Groups via Monoselective C-F Bond Activation.

We report a general method for the labeling of both CF3 and CF2 H groups in a broad range of chemical settings (aryl, oxide, sulfide). The method utilizes frustrated Lewis pair mediated selective C-F activation to formally substitute fluorine-19 with fluorine-18 in a two-step defluorination/radiofluorination process, and as such can utilize the target compounds as starting materials. The radiotracer precursors can be isolated as stable salts prior to radiofluorination. The method delivers good radiochemical yields and molar activities (up to 35.2±6.5 % non-decay corrected isolated activity yields and 12.0±1.7 GBq µmol-1 molar activities) and is shown to be applicable to biologically relevant compounds. The ability to utilize the target compound as the starting material and the synthetic simplicity of the method coupled with the ever-increasing use of CF3 and CF2 H groups in pharmaceuticals makes this method attractive for drug and radiotracer development.

Imaging Effector Memory T-Cells Predicts Response to PD1-Chemotherapy Combinations in Colon Cancer.

Often, patients fail to respond to immune checkpoint inhibitor (ICI) treatment despite favourable biomarker status. Numerous chemotherapeutic agents have been shown to promote tumour immunogenicity when used in conjunction with ICIs; however, little is known about whether such combination therapies lead to a lasting immune response. Given the potential toxicity of ICI-chemotherapy combinations, identification of biomarkers that accurately predict how individuals respond to specific treatment combinations and whether these responses will be long lasting is of paramount importance. In this study, we explored [18F]AlF-NOTA-KCNA3P, a peptide radiopharmaceutical that targets the Kv1.3 potassium channel overexpressed on T-effector memory (TEM) cells as a PET imaging biomarker for lasting immunological memory response. The first-line colon cancer chemotherapies oxaliplatin and 5-fluorouracil were assessed in a syngeneic colon cancer model, either as monotherapies or in combination with PD1, comparing radiopharmaceutical uptake to memory-associated immune cells in the tumour. [18F]AlF-NOTA-KCNA3P reliably separated tumours with immunological memory responses from non-responding tumours and could be used to measure Kv1.3-expressing TEM cells responsible for durable immunological memory response to combination therapy in vivo.

Imaging Adipose Tissue Browning using Mitochondrial Complex-I Tracer [18F]BCPP-EF.

Browning of white adipose tissue (WAT) into beige adipocytes has been proposed as a strategy to tackle the ongoing obesity epidemic. Thermogenic stimuli have been investigated with the aim of converting existing white adipose tissue, primarily used for energy storage, into beige adipocytes capable of dissipating energy; however, evaluation is complicated by the dearth of noninvasive methodologies to quantify de novo beige adipocytes in WAT. Imaging with [18F]FDG is commonly used to measure brown adipose tissue (BAT) and beige adipocytes but the relationship between beige adipocytes, thermogenesis and [18F]FDG uptake is unclear. [18F]BCPP-EF, a tracer for mitochondrial complex-I (MC-I), acts as a marker of oxidative metabolism and may be useful for the detection of newly formed beige adipocytes. Mice received doses of the ß3-adrenergic agonist CL-316,243 subchronically for 7 days to induce formation of beige adipocytes in inguinal white fat. PET imaging was performed longitudinally with both [18F]FDG (a marker of glycolysis) and [18F]BCPP-EF (an MC-I marker) to assess the effect of thermogenic stimulation on uptake in browning inguinal WAT and interscapular BAT. Treatment with CL-316,243 led to significant increases in both [18F]FDG and [18F]BCPP-EF in inguinal WAT. The uptake of [18F]BCPP-EF in inguinal WAT was significantly increased above control levels after 3 days of stimulation, whereas [18F]FDG only showed a significant increase after 7 days. The uptake of [18F]BCPP-EF in newly formed beige adipocytes was blocked by pretreatment with an adrenoceptor antagonist suggesting that beige adipocyte formation may be associated with the activation of MC-I. However, in BAT, uptake of [18F]BCPP-EF was unaffected by ß3-adrenergic stimulation, potentially due to the high expression of MC-I. [18F]BCPP-EF can detect newly formed beige adipocytes in WAT generated after subchronic treatment with the ß3-adrenergic agonist CL-316,243 and displays both higher inguinal WAT uptake and earlier detection than [18F]FDG. The MC-I tracer may be a useful tool in the evaluation of new therapeutic strategies targeting metabolic adipose tissues to tackle obesity and metabolic diseases.

Comparison of Three Automated Approaches for Classification of Amyloid-PET Images.

Automated amyloid-PET image classification can support clinical assessment and increase diagnostic confidence. Three automated approaches using global cut-points derived from Receiver Operating Characteristic (ROC) analysis, machine learning (ML) algorithms with regional SUVr values, and deep learning (DL) network with 3D image input were compared under various conditions: number of training data, radiotracers, and cohorts. 276 [11C]PiB and 209 [18F]AV45 PET images from ADNI database and our local cohort were used. Global mean and maximum SUVr cut-points were derived using ROC analysis. 68 ML models were built using regional SUVr values and one DL network was trained with classifications of two visual assessments - manufacturer's recommendations (gray-scale) and with visually guided reference region scaling (rainbow-scale). ML-based classification achieved similarly high accuracy as ROC classification, but had better convergence between training and unseen data, with a smaller number of training data. Naïve Bayes performed the best overall among the 68 ML algorithms. Classification with maximum SUVr cut-points yielded higher accuracy than with mean SUVr cut-points, particularly for cohorts showing more focal uptake. DL networks can support the classification of definite cases accurately but performed poorly for equivocal cases. Rainbow-scale standardized image intensity scaling and improved inter-rater agreement. Gray-scale detects focal accumulation better, thus classifying more amyloid-positive scans. All three approaches generally achieved higher accuracy when trained with rainbow-scale classification. ML yielded similarly high accuracy as ROC, but with better convergence between training and unseen data, and further work may lead to even more accurate ML methods.

Imaging Kv1.3 Expressing Memory T Cells as a Marker of Immunotherapy Response.

Immune checkpoint inhibitors have shown great promise, emerging as a new pillar of treatment for cancer; however, only a relatively small proportion of recipients show a durable response to treatment. Strategies that reliably differentiate durably-responding tumours from non-responsive tumours are a critical unmet need. Persistent and durable immunological responses are associated with the generation of memory T cells. Effector memory T cells associated with tumour response to immune therapies are characterized by substantial upregulation of the potassium channel Kv1.3 after repeated antigen stimulation. We have developed a new Kv1.3 targeting radiopharmaceutical, [18F]AlF-NOTA-KCNA3P, and evaluated whether it can reliably differentiate tumours successfully responding to immune checkpoint inhibitor (ICI) therapy targeting PD-1 alone or combined with CLTA4. In a syngeneic colon cancer model, we compared tumour retention of [18F]AlF-NOTA-KCNA3P with changes in the tumour immune microenvironment determined by flow cytometry. Imaging with [18F]AlF-NOTA-KCNA3P reliably differentiated tumours responding to ICI therapy from non-responding tumours and was associated with substantial tumour infiltration of T cells, especially Kv1.3-expressing CD8+ effector memory T cells.

Granzyme B PET Imaging in Response to In Situ Vaccine Therapy Combined with αPD1 in a Murine Colon Cancer Model.

Immune checkpoint inhibitors (ICIs) block checkpoint receptors that tumours use for immune evasion, allowing immune cells to target and destroy cancer cells. Despite rapid advancements in immunotherapy, durable response rates to ICIs remains low. To address this, combination clinical trials are underway assessing whether adjuvants can enhance responsiveness by increasing tumour immunogenicity. CpG-oligodeoxynucleotides (CpG-ODN) are synthetic DNA fragments containing an unmethylated cysteine-guanosine motif that stimulate the innate and adaptive immune systems by engaging Toll-like receptor 9 (TLR9) present on the plasmacytoid dendritic cells (pDCs) and B cells. Here, we have assessed the ability of AlF-mNOTA-GZP, a peptide tracer targeting granzyme B, to serve as a PET imaging biomarker in response to CpG-ODN 1585 in situ vaccine therapy delivered intratumourally (IT) or intraperitoneally (IP) either as monotherapy or in combination with αPD1. [18F]AlF-mNOTA-GZP was able to differentiate treatment responders from non-responders based on tumour uptake. Furthermore, [18F]AlF-mNOTA-GZP showed positive associations with changes in tumour-associated lymphocytes expressing GZB, namely GZB+ CD8+ T cells, and decreases in suppressive F4/80+ cells. [18F]AlF-mNOTA-GZP tumour uptake was mediated by GZB expressing CD8+ cells and successfully stratifies therapy responders from non-responders, potentially acting as a non-invasive biomarker for ICIs and combination therapy evaluation in a clinical setting.

Parametric mapping for 11C-metomidate PET-computed tomography imaging in the study of primary aldosteronism.

OBJECTIVE: 11C-metomidate (11C-MTO) PET-computed tomography (CT) imaging has shown good sensitivity and specificity for the classification of bilateral or unilateral overexpression of aldosterone. This work seeks to investigate the usefulness of parametric maps via kinetic modeling of 11C-metomidate data into the clinical diagnosis pathway. METHODS: Twenty-five patients were injected with 172 ± 12 MBq of 11C-metomidate and a dynamic PET scan performed of the adrenal glands. A blood time-activity curve was drawn from a volume of interest in the left ventricle and converted to a plasma time-activity curve. Metabolite correction was performed with a population-based correction. We performed regional-based graphical Patlak analysis to calculate the regional uptake rate constant Ki(REG), and also calculated parametric maps of Ki(VOX) using a voxel-based technique. RESULTS: Comparison of Ki(REG), and the maximum lesion voxel from parametric maps Ki(mVOX) demonstrated a high correlation for all subjects (r2 = 0.96). Ki(mVOX) allowed differentiation between cases of active and inactive unilateral adenoma when compared to bilateral hyperplasia (P < 0.017), a feature not observed with standardized uptake ratios (SUVmax) analysis. Ki(mVOX) demonstrated a poor correlation of 0.68 with SUVmax, indicating the differences through the use of static and dynamic imaging. Three false-negative cases based on SUV analysis indicated that Ki(mVOX) was able to successfully differentiate the clinical presentation for these cases. CONCLUSION: Our work demonstrates that parametric Ki(VOX) was able to successfully differentiate between patients with bilateral hyperplasia and patients with unilateral adrenal adenoma in our cohort and that Ki may be considered be an additional useful metric to SUV in 11C-metomidate PET-CT imaging.

PET Imaging of Translocator Protein as a Marker of Malaria-Associated Lung Inflammation.

Malaria-associated acute respiratory distress syndrome (MA-ARDS) is a severe complication of malaria that occurs despite effective antimalarial treatment. Currently, noninvasive imaging procedures such as chest X-rays are used to assess edema in established MA-ARDS, but earlier detection methods are needed to reduce morbidity and mortality. The early stages of MA-ARDS are characterized by the infiltration of leukocytes, in particular monocytes/macrophages; thus, monitoring of immune infiltrates may provide a useful indicator of early pathology. In this study, Plasmodium berghei ANKA-infected C57BL/6 mice, a rodent model of MA-ARDS, were longitudinally imaged using the 18-kDa translocator protein (TSPO) imaging agent [18F]FEPPA as a marker of macrophage accumulation during the development of pathology and in response to combined artesunate and chloroquine diphosphate (ART+CQ) therapy. [18F]FEPPA uptake was compared to blood parasitemia levels and to levels of pulmonary immune cell infiltrates by using flow cytometry. Infected animals showed rapid increases in lung retention of [18F]FEPPA, correlating well with increases in blood parasitemia and pulmonary accumulation of interstitial inflammatory macrophages and major histocompatibility complex class II (MHC-II)-positive alveolar macrophages. Treatment with ART+CQ abrogated this increase in parasitemia and significantly reduced both lung uptake of [18F]FEPPA and levels of macrophage infiltrates. We conclude that retention of [18F]FEPPA in the lungs is well correlated with changes in blood parasitemia and levels of lung-associated macrophages during disease progression and in response to ART+CQ therapy. With further development, TSPO biomarkers may have the potential to accurately assess the early onset of MA-ARDS.

Plasma P-tau181 to Aß42 ratio is associated with brain amyloid burden and hippocampal atrophy in an Asian cohort of Alzheimer's disease patients with concomitant cerebrovascular disease.

INTRODUCTION: There is increasing evidence that phosphorylated tau (P-tau181) is a specific biomarker for Alzheimer's disease (AD) pathology, but its potential utility in non-White patient cohorts and patients with concomitant cerebrovascular disease (CeVD) is unknown. METHODS: Single molecule array (Simoa) measurements of plasma P-tau181, total tau, amyloid beta (Aß)40 and Aß42, as well as derived ratios were correlated with neuroimaging modalities indicating brain amyloid (Aß+), hippocampal atrophy, and CeVD in a Singapore-based cohort of non-cognitively impaired (NCI; n = 43), cognitively impaired no dementia (CIND; n = 91), AD (n = 44), and vascular dementia (VaD; n = 22) subjects. RESULTS: P-tau181/Aß42 ratio showed the highest area under the curve (AUC) for Aß+ (AUC = 0.889) and for discriminating between AD Aß+ and VaD Aß- subjects (AUC = 0.903). In addition, P-tau181/Aß42 ratio was associated with hippocampal atrophy. None of the biomarkers was associated with CeVD. DISCUSSION: Plasma P-tau181/Aß42 ratio may be a noninvasive means of identifying AD with elevated brain amyloid in populations with concomitant CeVD.

Granzyme B PET Imaging of Combined Chemotherapy and Immune Checkpoint Inhibitor Therapy in Colon Cancer.

PURPOSE: Chemotherapeutic adjuvants, such as oxaliplatin (OXA) and 5-fluorouracil (5-FU), that enhance the immune system, are being assessed as strategies to improve durable response rates when used in combination with immune checkpoint inhibitor (ICI) monotherapy in cancer patients. In this study, we explored granzyme B (GZB), released by tumor-associated immune cells, as a PET imaging-based stratification marker for successful combination therapy using a fluorine-18 (18F)-labelled GZB peptide ([18F]AlF-mNOTA-GZP). METHODS: Using the immunocompetent CT26 syngeneic mouse model of colon cancer, we assessed the potential for [18F]AlF-mNOTA-GZP to stratify OXA/5-FU and ICI combination therapy response via GZB PET. In vivo tumor uptake of [18F]AlF-mNOTA-GZP in different treatment arms was quantified by PET, and linked to differences in tumor-associated immune cell populations defined by using multicolour flow cytometry. RESULTS: [18F]AlF-mNOTA-GZP tumor uptake was able to clearly differentiate treatment responders from non-responders when stratified based on changes in tumor volume. Furthermore, [18F]AlF-mNOTA-GZP showed positive associations with changes in tumor-associated lymphocytes expressing GZB, namely GZB+ CD8+ T cells and GZB+ NK+ cells. CONCLUSIONS: [18F]AlF-mNOTA-GZP tumor uptake, driven by changes in immune cell populations expressing GZB, is able to stratify tumor response to chemotherapeutics combined with ICIs. Our results show that, while the immunomodulatory mode of action of the chemotherapies may be different, the ultimate mechanism of tumor lysis through release of Granzyme B is an accurate biomarker for treatment response.

Improved amyloid burden quantification with nonspecific estimates using deep learning.

PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-ß burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we propose a novel amyloid-PET quantification approach that harnesses the intermodal image translation capability of convolutional networks to remove this undesirable source of variability. METHODS: Paired MR and PET images exhibiting very low specific uptake were selected from a Singaporean amyloid-PET study involving 172 participants with different severities of CeVD. Two convolutional neural networks (CNN), ScaleNet and HighRes3DNet, and one conditional generative adversarial network (cGAN) were trained to map structural MR to NS PET images. NS estimates generated for all subjects using the most promising network were then subtracted from SUVr images to determine specific amyloid load only (SAßL). Associations of SAßL with various cognitive and functional test scores were then computed and compared to results using conventional SUVr. RESULTS: Multimodal ScaleNet outperformed other networks in predicting the NS content in cortical gray matter with a mean relative error below 2%. Compared to SUVr, SAßL showed increased association with cognitive and functional test scores by up to 67%. CONCLUSION: Removing the undesirable NS uptake from the amyloid load measurement is possible using deep learning and substantially improves its accuracy. This novel analysis approach opens a new window of opportunity for improved data modeling in Alzheimer's disease and for other neurodegenerative diseases that utilize PET imaging.

Granzyme B PET Imaging Stratifies Immune Checkpoint Inhibitor Response in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a notoriously difficult cancer to treat. The recent development of immune checkpoint inhibitors has revolutionised HCC therapy; however, successful response is only observed in a small percentage of patients. Biomarkers typically used to predict treatment response in other tumour types are ineffective in HCC, which arises in an immune-suppressive environment. However, imaging markers that measure changes in tumour infiltrating immune cells may supply information that can be used to determine which patients are responding to therapy posttreatment. We have evaluated [18F]AlF-mNOTA-GZP, a radiolabeled peptide targeting granzyme B, to stratify response to ICIs in a HEPA 1-tumours, a syngeneic model of HCC. Posttherapy, in vivo tumour retention of [18F]AlF-mNOTA-GZP was correlated to changes in tumour volume and tumour-infiltrating immune cells. [18F]AlF-mNOTA-GZP successfully stratified response to immune checkpoint inhibition in the syngeneic HEPA 1-6 model. FACS indicated significant changes in the immune environment including a decrease in immune suppressive CD4+ T regulatory cells and increases in tumour-associated GZB+ NK+ cells, which correlated well with tumour radiopharmaceutical uptake. While the immune response to ICI therapies differs in HCC compared to many other cancers, [18F]AlF-mNOTA-GZP retention is able to stratify response to ICI therapy associated with tumour infiltrating GZB+ NK+ cells in this complex tumour microenvironment.

Head-to-head comparison of amplified plasmonic exosome Aß42 platform and single-molecule array immunoassay in a memory clinic cohort.

BACKGROUND AND PURPOSE: Various blood biomarkers reflecting brain amyloid-ß (Aß) load have recently been proposed with promising results. However, to date, no comparative study amongst blood biomarkers has been reported. Our objective was to examine the diagnostic performance and cost effectiveness of three blood biomarkers on the same cohort. METHODS: Using the same cohort (n = 68), the performances of the single-molecule array (Simoa) Aß40, Aß42, Aß42/Aß40 and the amplified plasmonic exosome (APEX) Aß42 blood biomarkers were compared using amyloid positron emission tomography (PET) as the reference standard. The extent to which these blood tests can reduce the recruitment cost of clinical trials was also determined by identifying amyloid positive (Aß+) participants. RESULTS: Compared to Simoa biomarkers, APEX-Aß42 showed significantly higher correlations with amyloid PET retention values and excellent diagnostic performance (sensitivity 100%, specificity 93.3%, area under the curve 0.995). When utilized for clinical trial recruitment, our simulation showed that pre-screening with blood biomarkers followed by a confirmatory amyloid PET imaging would roughly half the cost (56.8% reduction for APEX-Aß42 and 48.6% for Simoa-Aß42/Aß40) compared to the situation where only PET imaging is used. Moreover, with 100% sensitivity, APEX-Aß42 pre-screening does not increase the required number of initial participants. CONCLUSIONS: With its high diagnostic performance, APEX is an ideal candidate for Aß+ subject identification, monitoring and primary care screening, and could efficiently enrich clinical trials with Aß+ participants whilst halving recruitment costs.

Dopamine transporter neuroimaging accurately assesses the maturation of dopamine neurons in a preclinical model of Parkinson's disease.

BACKGROUND: Significant developments in stem cell therapy for Parkinson's disease (PD) have already been achieved; however, methods for reliable assessment of dopamine neuron maturation in vivo are lacking. Establishing the efficacy of new cellular therapies using non-invasive methodologies will be critical for future regulatory approval and application. The current study examines the utility of neuroimaging to characterise the in vivo maturation, innervation and functional dopamine release of transplanted human embryonic stem cell-derived midbrain dopaminergic neurons (hESC-mDAs) in a preclinical model of PD. METHODS: Female NIH RNu rats received a unilateral stereotaxic injection of 6-OHDA into the left medial forebrain bundle to create the PD lesion. hESC-mDA cell and sham transplantations were carried out 1 month post-lesion, with treated animals receiving approximately 4 × 105 cells per transplantation. Behavioural analysis, [18F]FBCTT and [18F]fallypride microPET/CT, was conducted at 1, 3 and 6 months post-transplantation and compared with histological characterisation at 6 months. RESULTS: PET imaging revealed transplant survival and maturation into functional dopaminergic neurons. [18F]FBCTT-PET/CT dopamine transporter (DAT) imaging demonstrated pre-synaptic restoration and [18F]fallypride-PET/CT indicated functional dopamine release, whilst amphetamine-induced rotation showed significant behavioural recovery. Moreover, histology revealed that the grafted cells matured differently in vivo producing high- and low-tyrosine hydroxylase (TH) expressing cohorts, and only [18F]FBCTT uptake was well correlated with differentiation. CONCLUSIONS: This study provides further evidence for the value of in vivo functional imaging for the assessment of cell therapies and highlights the utility of DAT imaging for the determination of early post-transplant cell maturation and differentiation of hESC-mDAs.

Modulation of Lymphocyte Potassium Channel KV1.3 by Membrane-Penetrating, Joint-Targeting Immunomodulatory Plant Defensin.

We describe a cysteine-rich, membrane-penetrating, joint-targeting, and remarkably stable peptide, EgK5, that modulates voltage-gated KV1.3 potassium channels in T lymphocytes by a distinctive mechanism. EgK5 enters plasma membranes and binds to KV1.3, causing current run-down by a phosphatidylinositol 4,5-bisphosphate-dependent mechanism. EgK5 exhibits selectivity for KV1.3 over other channels, receptors, transporters, and enzymes. EgK5 suppresses antigen-triggered proliferation of effector memory T cells, a subset enriched among pathogenic autoreactive T cells in autoimmune disease. PET-CT imaging with 18F-labeled EgK5 shows accumulation of the peptide in large and small joints of rodents. In keeping with its arthrotropism, EgK5 treats disease in a rat model of rheumatoid arthritis. It was also effective in treating disease in a rat model of atopic dermatitis. No signs of toxicity are observed at 10-100 times the in vivo dose. EgK5 shows promise for clinical development as a therapeutic for autoimmune diseases.

Granzyme B PET Imaging of Immune Checkpoint Inhibitor Combinations in Colon Cancer Phenotypes.

PURPOSE: Immune checkpoint inhibitor (ICI) monotherapy and combination regimens are being actively pursued as strategies to improve durable response rates in cancer patients. However, the biology surrounding combination therapies is not well understood and may increase the likelihood of immune-mediated adverse events. Accurate stratification of ICI response by non-invasive PET imaging may help ensure safe therapy management across a wide number of cancer phenotypes. PROCEDURES: We have assessed the ability of a fluorine-labelled peptide, [18F]AlF-mNOTA-GZP, targeting granzyme B, to stratify ICI response in two syngeneic models of colon cancer, CT26 and MC38. In vivo tumour uptake of [18F]AlF-mNOTA-GZP following ICI monotherapy, or in combination with PD-1 was characterised and correlated with changes in tumour-associated immune cell populations. RESULTS: [18F]AlF-mNOTA-GZP showed good predictive ability and correlated well with changes in tumour-associated T cells, especially CD8+ T cells; however, overall uptake and response to monotherapy or combination therapies was very different in the CT26 and MC38 tumours, likely due to the immunostimulatory environment imbued by the MSI-high phenotype in MC38 tumours. CONCLUSIONS: [18F]AlF-mNOTA-GZP uptake correlates well with changes in CD8+ T cell populations and is able to stratify tumour response to a range of ICIs administered as monotherapies or in combination. However, tracer uptake can be significantly affected by preexisting phenotypic abnormalities potentially confusing data interpretation.

Longitudinal [18F]FB-IL-2 PET Imaging to Assess the Immunopathogenicity of O'nyong-nyong Virus Infection.

O'nyong-nyong virus (ONNV) is an arthritogenic alphavirus that caused two large epidemics in 1959 and 1996, affecting millions of people in Africa. More recently, sero-surveillance of healthy blood donors conducted in 2019 revealed high rates of unreported ONNV infection in Uganda. Due to similar clinical symptoms with other endemic mosquito-borne pathogens in the region, including chikungunya virus, dengue virus and malaria, ONNV infections are often un- or misdiagnosed. Elucidating the immunopathogenic factors of this re-emerging arbovirus is critical with the expanding geographic distribution of competent vectors. This study reports the establishment of an immune competent C57BL6/J mouse model to mechanistically characterize ONNV infection and assess potential treatment efficacy. This mouse model successfully recapitulated arthralgia and viremia profiles seen in ONNV patients. Furthermore, longitudinal in-vivo PET imaging with [18F]FB-IL-2 (CD25+CD4+ binding probe) and histopathological assessment in this model demonstrated the pathogenic role of CD4+ T cells in driving joint pathology. Concordantly, in vivo CD4+ T cell depletion, or suppression with fingolimod, an FDA-approved immunomodulating drug, abrogated CD4+ T cell-mediated disease. This study demonstrates the importance of this immune competent ONNV model for future studies on factors influencing disease pathogenesis, which could shape the discovery of novel therapeutic strategies for arthritogenic alphaviruses.