Targeting deoxycytidine kinase improves symptoms in mouse models of multiple sclerosis.

Multiple sclerosis (MS) is an autoimmune disease driven by lymphocyte activation against myelin autoantigens in the central nervous system leading to demyelination and neurodegeneration. The deoxyribonucleoside salvage pathway with the rate-limiting enzyme deoxycytidine kinase (dCK) captures extracellular deoxyribonucleosides for use in intracellular deoxyribonucleotide metabolism. Previous studies have shown that deoxyribonucleoside salvage activity is enriched in lymphocytes and required for early lymphocyte development. However, specific roles for the deoxyribonucleoside salvage pathway and dCK in autoimmune diseases such as MS are unknown. Here we demonstrate that dCK activity is necessary for the development of clinical symptoms in the MOG35-55 and MOG1-125 experimental autoimmune encephalomyelitis (EAE) mouse models of MS. During EAE disease, deoxyribonucleoside salvage activity is elevated in the spleen and lymph nodes. Targeting dCK with the small molecule dCK inhibitor TRE-515 limits disease severity when treatments are started at disease induction or when symptoms first appear. EAE mice treated with TRE-515 have significantly fewer infiltrating leukocytes in the spinal cord, and TRE-515 blocks activation-induced B and T cell proliferation and MOG35-55 -specific T cell expansion without affecting innate immune cells or naïve T and B cell populations. Our results demonstrate that targeting dCK limits symptoms in EAE mice and suggest that dCK activity is required for MOG35-55 -specific lymphocyte activation-induced proliferation.

A genetically defined disease model reveals that urothelial cells can initiate divergent bladder cancer phenotypes.

Small cell carcinoma of the bladder (SCCB) is a rare and lethal phenotype of bladder cancer. The pathogenesis and molecular features are unknown. Here, we established a genetically engineered SCCB model and a cohort of patient SCCB and urothelial carcinoma samples to characterize molecular similarities and differences between bladder cancer phenotypes. We demonstrate that SCCB shares a urothelial origin with other bladder cancer phenotypes by showing that urothelial cells driven by a set of defined oncogenic factors give rise to a mixture of tumor phenotypes, including small cell carcinoma, urothelial carcinoma, and squamous cell carcinoma. Tumor-derived single-cell clones also give rise to both SCCB and urothelial carcinoma in xenografts. Despite this shared urothelial origin, clinical SCCB samples have a distinct transcriptional profile and a unique transcriptional regulatory network. Using the transcriptional profile from our cohort, we identified cell surface proteins (CSPs) associated with the SCCB phenotype. We found that the majority of SCCB samples have PD-L1 expression in both tumor cells and tumor-infiltrating lymphocytes, suggesting that immune checkpoint inhibitors could be a treatment option for SCCB. We further demonstrate that our genetically engineered tumor model is a representative tool for investigating CSPs in SCCB by showing that it shares a similar a CSP profile with clinical samples and expresses SCCB-up-regulated CSPs at both the mRNA and protein levels. Our findings reveal distinct molecular features of SCCB and provide a transcriptional dataset and a preclinical model for further investigating SCCB biology.

AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies.

SUMMARY: A number of methods have been devised to address the need for targeted genomic resequencing. One of these methods, region-specific extraction (RSE) is characterized by the capture of long DNA fragments (15-20 kb) by magnetic beads, after enzymatic extension of oligonucleotides hybridized to selected genomic regions. Facilitating the selection of the most appropriate capture oligos for targeting a region of interest, satisfying the properties of temperature (Tm) and entropy (ΔG), while minimizing the formation of primer-dimers in a pooled experiment, is therefore necessary. Manual design and selection of oligos becomes very challenging, complicated by factors such as length of the target region and number of targeted regions. Here we describe, AnthOligo, a web-based application developed to optimally automate the process of generation of oligo sequences used to target and capture the continuum of large and complex genomic regions. Apart from generating oligos for RSE, this program may have wider applications in the design of customizable internal oligos to be used as baits for gene panel analysis or even probes for large-scale comparative genomic hybridization array processes. AnthOligo was tested by capturing the Major Histocompatibility Complex (MHC) of a random sample.The application provides users with a simple interface to upload an input file in BED format and customize parameters for each task. The task of probe design in AnthOligo commences when a user uploads an input file and concludes with the generation of a result-set containing an optimal set of region-specific oligos. AnthOligo is currently available as a public web application with URL: http://antholigo.chop.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Correction to: ITR-Seq, a next-generation sequencing assay, identifies genome-wide DNA editing sites in vivo following adeno-associated viral vector-mediated genome editing.

An amendment to this paper has been published and can be accessed via the original article.

ITR-Seq, a next-generation sequencing assay, identifies genome-wide DNA editing sites in vivo following adeno-associated viral vector-mediated genome editing.

BACKGROUND: Identifying nuclease-induced double-stranded breaks in DNA on a genome-wide scale is critical for assessing the safety and efficacy of genome editing therapies. We previously demonstrated that after administering adeno-associated viral (AAV) vector-mediated genome-editing strategies in vivo, vector sequences integrated into the host organism's genomic DNA at double-stranded breaks. Thus, identifying the genomic location of inserted AAV sequences would enable us to identify DSB events, mainly derived from the nuclease on- and off-target activity. RESULTS: Here, we developed a next-generation sequencing assay that detects insertions of specific AAV vector sequences called inverted terminal repeats (ITRs). This assay, ITR-Seq, enables us to identify off-target nuclease activity in vivo. Using ITR-Seq, we analyzed liver DNA samples of rhesus macaques treated with AAV vectors expressing a meganuclease. We found dose-dependent off-target activity and reductions in off-target events induced by further meganuclease development. In mice, we identified the genomic locations of ITR integration after treatment with Cas9 nucleases and their corresponding single-guide RNAs. CONCLUSIONS: In sum, ITR-Seq is a powerful method for identifying off-target sequences induced by AAV vector-delivered genome-editing nucleases. ITR-Seq will help us understand the specificity and efficacy of different genome-editing nucleases in animal models and clinical studies. This information can help enhance the safety profile of gene-editing therapies.

The GPI-Linked Protein LY6A Drives AAV-PHP.B Transport across the Blood-Brain Barrier.

Efficient delivery of gene therapy vectors across the blood-brain barrier (BBB) is the holy grail of neurological disease therapies. A variant of the neurotropic vector adeno-associated virus (AAV) serotype 9, called AAV-PHP.B, was shown to very efficiently deliver transgenes across the BBB in C57BL/6J mice. Based on our recent observation that this phenotype is mouse strain dependent, we used whole-exome sequencing-based genetics to map this phenotype to a specific haplotype of lymphocyte antigen 6 complex, locus A (Ly6a) (stem cell antigen-1 [Sca-1]), which encodes a glycosylphosphatidylinositol (GPI)-anchored protein whose function had been thought to be limited to the biology of hematopoiesis. Additional biochemical and genetic studies definitively linked high BBB transport to the binding of AAV-PHP.B with LY6A (SCA-1). These studies identify, for the first time, a ligand for this GPI-anchored protein and suggest a role for it in BBB transport that could be hijacked by viruses in natural infections or by gene therapy vectors to treat neurological diseases.

Functional screen identifies kinases driving prostate cancer visceral and bone metastasis.

Mutationally activated kinases play an important role in the progression and metastasis of many cancers. Despite numerous oncogenic alterations implicated in metastatic prostate cancer, mutations of kinases are rare. Several lines of evidence suggest that nonmutated kinases and their pathways are involved in prostate cancer progression, but few kinases have been mechanistically linked to metastasis. Using a mass spectrometry-based phosphoproteomics dataset in concert with gene expression analysis, we selected over 100 kinases potentially implicated in human metastatic prostate cancer for functional evaluation. A primary in vivo screen based on overexpression of candidate kinases in murine prostate cells identified 20 wild-type kinases that promote metastasis. We queried these 20 kinases in a secondary in vivo screen using human prostate cells. Strikingly, all three RAF family members, MERTK, and NTRK2 drove the formation of bone and visceral metastasis confirmed by positron-emission tomography combined with computed tomography imaging and histology. Immunohistochemistry of tissue microarrays indicated that these kinases are highly expressed in human metastatic castration-resistant prostate cancer tissues. Our functional studies reveal the strong capability of select wild-type protein kinases to drive critical steps of the metastatic cascade, and implicate these kinases in possible therapeutic intervention.

Positron emission tomography probe demonstrates a striking concentration of ribose salvage in the liver.

PET is a powerful technique for quantifying and visualizing biochemical pathways in vivo. Here, we develop and validate a novel PET probe, [(18)F]-2-deoxy-2-fluoroarabinose ([(18)F]DFA), for in vivo imaging of ribose salvage. DFA mimics ribose in vivo and accumulates in cells following phosphorylation by ribokinase and further metabolism by transketolase. We use [(18)F]DFA to show that ribose preferentially accumulates in the liver, suggesting a striking tissue specificity for ribose metabolism. We demonstrate that solute carrier family 2, member 2 (also known as GLUT2), a glucose transporter expressed in the liver, is one ribose transporter, but we do not know if others exist. [(18)F]DFA accumulation is attenuated in several mouse models of metabolic syndrome, suggesting an association between ribose salvage and glucose and lipid metabolism. These results describe a tool for studying ribose salvage and suggest that plasma ribose is preferentially metabolized in the liver.

The next generation of target capture technologies - large DNA fragment enrichment and sequencing determines regional genomic variation of high complexity.

BACKGROUND: The ability to capture and sequence large contiguous DNA fragments represents a significant advancement towards the comprehensive characterization of complex genomic regions. While emerging sequencing platforms are capable of producing several kilobases-long reads, the fragment sizes generated by current DNA target enrichment technologies remain a limiting factor, producing DNA fragments generally shorter than 1 kbp. The DNA enrichment methodology described herein, Region-Specific Extraction (RSE), produces DNA segments in excess of 20 kbp in length. Coupling this enrichment method to appropriate sequencing platforms will significantly enhance the ability to generate complete and accurate sequence characterization of any genomic region without the need for reference-based assembly. RESULTS: RSE is a long-range DNA target capture methodology that relies on the specific hybridization of short (20-25 base) oligonucleotide primers to selected sequence motifs within the DNA target region. These capture primers are then enzymatically extended on the 3'-end, incorporating biotinylated nucleotides into the DNA. Streptavidin-coated beads are subsequently used to pull-down the original, long DNA template molecules via the newly synthesized, biotinylated DNA that is bound to them. We demonstrate the accuracy, simplicity and utility of the RSE method by capturing and sequencing a 4 Mbp stretch of the major histocompatibility complex (MHC). Our results show an average depth of coverage of 164X for the entire MHC. This depth of coverage contributes significantly to a 99.94 % total coverage of the targeted region and to an accuracy that is over 99.99 %. CONCLUSIONS: RSE represents a cost-effective target enrichment method capable of producing sequencing templates in excess of 20 kbp in length. The utility of our method has been proven to generate superior coverage across the MHC as compared to other commercially available methodologies, with the added advantage of producing longer sequencing templates amenable to DNA sequencing on recently developed platforms. Although our demonstration of the method does not utilize these DNA sequencing platforms directly, our results indicate that the capture of long DNA fragments produce superior coverage of the targeted region.

Generation of Full-Length Class I Human Leukocyte Antigen Gene Consensus Sequences for Novel Allele Characterization.

BACKGROUND: Routine, high-resolution human leukocyte antigen (HLA) genotyping by next generation sequencing within clinical immunogenetics laboratories can now provide the full-length gene sequence characterization of fully phased HLA alleles. This powerful technique provides insights into HLA variation beyond the traditionally characterized antigen recognition domain, providing sequence annotation across the entire gene including untranslated and intronic regions and may be used to characterize novel alleles from massively parallel sequencing runs. METHODS: We evaluated the utility of the Omixon Holotype HLA assay to generate credible, fully phased full-length gene consensus sequences for 50 individuals at major histocompatibility complex, class I, A (HLA-A), HLA-B, and HLA-C loci (300 genotyped alleles in total) to identify and characterize novel class I HLA alleles using our downstream analytical pipeline. RESULTS: Our analysis revealed that 7.7% (23/300) of genotyped class I HLA alleles contain novel polymorphisms. Interestingly, all of the novel alleles identified by our analysis were found to harbor sequence variations within intronic regions of the respective locus. In total our analysis identified 17 unique novel class I HLA alleles from 23 of the 300 genotyped alleles and generated full-length gene sequence annotations for 9 previously incompletely annotated HLA class I allele sequences derived from 14 of the 300 genotyped alleles. CONCLUSIONS: The demonstrated utility of the Omixon Holotype HLA assay in combination with our downstream analytical framework to generate fully phased, full-length gene consensus sequences for the identification and characterization of novel HLA alleles, facilitates the study of HLA polymorphism beyond the antigen recognition domain in human health and disease.

Emerging Approaches for Targeting Metabolic Vulnerabilities in Malignant Glioma.

Malignant gliomas are intractable and among the most lethal human malignancies. Like other cancers, metabolic reprogramming is a key feature of glioma and is thought to accommodate the heightened nutrient requirements for tumor cell proliferation, growth, and survival. This metabolic rewiring, driven by oncogenic signaling and molded by the unique environment of the brain, may impose vulnerabilities that could be exploited therapeutically for increased tumor control. In this review, we discuss the prominent metabolic features of malignant glioma, the key pathways regulating glioma metabolism, and the potential therapeutic opportunities for targeting metabolic processes.

Dynamic O-GlcNAc modification regulates CREB-mediated gene expression and memory formation.

The transcription factor cyclic AMP-response element binding protein (CREB) is a key regulator of many neuronal processes, including brain development, circadian rhythm and long-term memory. Studies of CREB have focused on its phosphorylation, although the diversity of CREB functions in the brain suggests additional forms of regulation. Here we expand on a chemoenzymatic strategy for quantifying glycosylation stoichiometries to characterize the functional roles of CREB glycosylation in neurons. We show that CREB is dynamically modified with an O-linked ß-N-acetyl-D-glucosamine sugar in response to neuronal activity and that glycosylation represses CREB-dependent transcription by impairing its association with CREB-regulated transcription coactivator (CRTC; also known as transducer of regulated CREB activity). Blocking glycosylation of CREB alters cellular function and behavioral plasticity, enhancing both axonal and dendritic growth and long-term memory consolidation. Our findings demonstrate a new role for O-glycosylation in memory formation and provide a mechanistic understanding of how glycosylation contributes to critical neuronal functions. Moreover, we identify a previously unknown mechanism for the regulation of activity-dependent gene expression, neural development and memory.

Elucidating glycosaminoglycan-protein-protein interactions using carbohydrate microarray and computational approaches.

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan-protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan-protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan-protein-protein interactions, as well as a molecular-level understanding of those complexes.

EGGNet, a Generalizable Geometric Deep Learning Framework for Protein Complex Pose Scoring.

Computational prediction of molecule-protein interactions has been key for developing new molecules to interact with a target protein for therapeutics development. Previous work includes two independent streams of approaches: (1) predicting protein-protein interactions (PPIs) between naturally occurring proteins and (2) predicting binding affinities between proteins and small-molecule ligands [also known as drug-target interaction (DTI)]. Studying the two problems in isolation has limited the ability of these computational models to generalize across the PPI and DTI tasks, both of which ultimately involve noncovalent interactions with a protein target. In this work, we developed Equivariant Graph of Graphs neural Network (EGGNet), a geometric deep learning (GDL) framework, for molecule-protein binding predictions that can handle three types of molecules for interacting with a target protein: (1) small molecules, (2) synthetic peptides, and (3) natural proteins. EGGNet leverages a graph of graphs (GoG) representation constructed from the molecular structures at atomic resolution and utilizes a multiresolution equivariant graph neural network to learn from such representations. In addition, EGGNet leverages the underlying biophysics and makes use of both atom- and residue-level interactions, which improve EGGNet's ability to rank candidate poses from blind docking. EGGNet achieves competitive performance on both a public protein-small-molecule binding affinity prediction task (80.2% top 1 success rate on CASF-2016) and a synthetic protein interface prediction task (88.4% area under the precision-recall curve). We envision that the proposed GDL framework can generalize to many other protein interaction prediction problems, such as binding site prediction and molecular docking, helping accelerate protein engineering and structure-based drug development.

Pacritinib inhibits glucose consumption in squamous cell lung cancer cells by targeting FLT3.

Squamous cell lung cancer maintains its growth through elevated glucose consumption, but selective glucose consumption inhibitors are lacking. Here, we discovered using a high-throughput screen new compounds that block glucose consumption in three squamous cell lung cancer cell lines and identified 79 compounds that block glucose consumption in one or more of these cell lines. Based on its ability to block glucose consumption in all three cell lines, pacritinib, an inhibitor of FMS Related Receptor Tyrosine Kinase 3 (FLT3) and Janus Kinase 2 (JAK2), was further studied. Pacritinib decreased glucose consumption in squamous cell lung cancer cells in cell culture and in vivo without affecting glucose consumption in healthy tissues. Pacritinib blocked hexokinase activity, and Hexokinase 1 and 2 mRNA and protein expression. Overexpression of Hexokinase 1 blocked the ability of pacritinib to inhibit glucose consumption in squamous cell lung cancer cells. Overexpression of FLT3 but not JAK2 significantly increased glucose consumption and blocked the ability of pacritinib to inhibit glucose consumption in squamous cell lung cancer cells. Additional FLT3 inhibitors blocked glucose consumption in squamous cell lung cancer cells. Our study identifies FLT3 inhibitors as a new class of inhibitors that can block glucose consumption in squamous cell lung cancer.

Early Reduction of Glucose Consumption Is a Biomarker of Kinase Inhibitor Efficacy Which Can Be Reversed with GLUT1 Overexpression in Lung Cancer Cells.

PURPOSE: Small molecule inhibitors that target oncogenic driver kinases are an important class of therapies for non-small cell lung cancer (NSCLC) and other malignancies. However, these therapies are not without their challenges. Each inhibitor works on only a subset of patients, the pharmacokinetics of these inhibitors is variable, and these inhibitors are associated with significant side effects. Many of these inhibitors lack non-invasive biomarkers to confirm pharmacodynamic efficacy, and our understanding of how these inhibitors block cancer cell growth remains incomplete. Limited clinical studies suggest that early (< 2 weeks after start of therapy) changes in tumor glucose consumption, measured by [18F]FDG PET imaging, can predict therapeutic efficacy, but the scope of this strategy and functional relevance of this inhibition of glucose consumption remains understudied. Here we demonstrate that early inhibition of glucose consumption as can be measured clinically with [18F]FDG PET is a consistent phenotype of efficacious targeted kinase inhibitors and is necessary for the subsequent inhibition of growth across models of NSCLC. METHODS: We tested nine NSCLC cell lines (A549, H1129, H1734, H1993, H2228, H3122, H460, HCC827, and PC9 cells) and ten targeted therapies (afatinib, buparlisib, ceritinib, cabozantinib, crizotinib, dovitinib, erlotinib, ponatinib, trametinib, and vemurafenib) across concentrations ranging from 1.6 nM to 5 µM to evaluate whether these inhibitors block glucose consumption at 24-h post-drug treatment and cell growth at 72-h post-drug treatment. We overexpressed the facilitative glucose transporter SLC2A1 (GLUT1) to test the functional connection between blocked glucose consumption and cell growth after treatment with a kinase inhibitor. A subset of these inhibitors and cell lines were studied in vivo. RESULTS: Across the nine NSCLC cell lines, ten targeted therapies, and a range of inhibitor concentrations, whether a kinase inhibitor blocked glucose consumption at 24-h post-drug treatment strongly correlated with whether that inhibitor blocked cell growth at 72-h post-drug treatment in cell culture. These results were confirmed in vivo with [18F]FDG PET imaging. GLUT1 overexpression blocked the kinase inhibitors from limiting glucose consumption and cell growth. CONCLUSIONS: Our results demonstrate that the early inhibition of lung cancer glucose consumption in response to a kinase inhibitor is a strong biomarker of and is often required for the subsequent inhibition of cell growth. Early inhibition of glucose consumption may provide complementary information to other biomarkers in determining whether a drug will effectively limit tumor growth.

Signaling Pathways That Drive 18F-FDG Accumulation in Cancer.

18F-FDG measures glucose consumption and is an integral part of cancer management. Most cancer types upregulate their glucose consumption, yielding elevated 18F-FDG PET accumulation in those cancer cells. The biochemical pathway through which 18F-FDG accumulates in cancer cells is well established. However, beyond well-known regulators such as c-Myc, PI3K/PKB, and HIF1α, the proteins and signaling pathways that cancer cells modulate to activate the facilitated glucose transporters and hexokinase enzymes that drive elevated 18F-FDG accumulation are less well understood. Understanding these signaling pathways could yield additional biologic insights from 18F-FDG PET scans and could suggest new uses of 18F-FDG PET in the management of cancer. Work over the past 5 years, building on studies from years prior, has identified new proteins and signaling pathways that drive glucose consumption in cancer. Here, we review these recent studies and discuss current limitations to our understanding of glucose consumption in cancer.

LM-GVP: an extensible sequence and structure informed deep learning framework for protein property prediction.

Proteins perform many essential functions in biological systems and can be successfully developed as bio-therapeutics. It is invaluable to be able to predict their properties based on a proposed sequence and structure. In this study, we developed a novel generalizable deep learning framework, LM-GVP, composed of a protein Language Model (LM) and Graph Neural Network (GNN) to leverage information from both 1D amino acid sequences and 3D structures of proteins. Our approach outperformed the state-of-the-art protein LMs on a variety of property prediction tasks including fluorescence, protease stability, and protein functions from Gene Ontology (GO). We also illustrated insights into how a GNN prediction head can inform the fine-tuning of protein LMs to better leverage structural information. We envision that our deep learning framework will be generalizable to many protein property prediction problems to greatly accelerate protein engineering and drug development.

Chemical approaches to understanding O-GlcNAc glycosylation in the brain.

O-GlcNAc glycosylation is a unique, dynamic form of glycosylation found on intracellular proteins of all multicellular organisms. Studies suggest that O-GlcNAc represents a key regulatory modification in the brain, contributing to transcriptional regulation, neuronal communication and neurodegenerative disease. Recently, several new chemical tools have been developed to detect and study the modification, including chemoenzymatic tagging methods, quantitative proteomics strategies and small-molecule inhibitors of O-GlcNAc enzymes. Here we highlight some of the emerging roles for O-GlcNAc in the nervous system and describe how chemical tools have significantly advanced our understanding of the scope, functional significance and cellular dynamics of this modification.

18F-FAC PET Visualizes Brain-Infiltrating Leukocytes in a Mouse Model of Multiple Sclerosis.

Brain-infiltrating leukocytes contribute to multiple sclerosis (MS) and autoimmune encephalomyelitis and likely play a role in traumatic brain injury, seizure, and stroke. Brain-infiltrating leukocytes are also primary targets for MS disease-modifying therapies. However, no method exists for noninvasively visualizing these cells in a living organism. 1-(2'-deoxy-2'-18F-fluoroarabinofuranosyl) cytosine (18F-FAC) is a PET radiotracer that measures deoxyribonucleoside salvage and accumulates preferentially in immune cells. We hypothesized that 18F-FAC PET could noninvasively image brain-infiltrating leukocytes. Methods: Healthy mice were imaged with 18F-FAC PET to quantify if this radiotracer crosses the blood-brain barrier (BBB). Experimental autoimmune encephalomyelitis (EAE) is a mouse disease model with brain-infiltrating leukocytes. To determine whether 18F-FAC accumulates in brain-infiltrating leukocytes, EAE mice were analyzed with 18F-FAC PET, digital autoradiography, and immunohistochemistry, and deoxyribonucleoside salvage activity in brain-infiltrating leukocytes was analyzed ex vivo. Fingolimod-treated EAE mice were imaged with 18F-FAC PET to assess if this approach can monitor the effect of an immunomodulatory drug on brain-infiltrating leukocytes. PET scans of individuals injected with 2-chloro-2'-deoxy-2'-18F-fluoro-9-ß-d-arabinofuranosyl-adenine (18F-CFA), a PET radiotracer that measures deoxyribonucleoside salvage in humans, were analyzed to evaluate whether 18F-CFA crosses the human BBB. Results:18F-FAC accumulates in the healthy mouse brain at levels similar to 18F-FAC in the blood (2.54 ± 0.2 and 3.04 ± 0.3 percentage injected dose per gram, respectively) indicating that 18F-FAC crosses the BBB. EAE mice accumulate 18F-FAC in the brain at 180% of the levels of control mice. Brain 18F-FAC accumulation localizes to periventricular regions with significant leukocyte infiltration, and deoxyribonucleoside salvage activity is present at similar levels in brain-infiltrating T and innate immune cells. These data suggest that 18F-FAC accumulates in brain-infiltrating leukocytes in this model. Fingolimod-treated EAE mice accumulate 18F-FAC in the brain at 37% lower levels than control-treated EAE mice, demonstrating that 18F-FAC PET can monitor therapeutic interventions in this mouse model. 18F-CFA accumulates in the human brain at 15% of blood levels (0.08 ± 0.01 and 0.54 ± 0.07 SUV, respectively), indicating that 18F-CFA does not cross the BBB in humans. Conclusion:18F-FAC PET can visualize brain-infiltrating leukocytes in a mouse MS model and can monitor the response of these cells to an immunomodulatory drug. Translating this strategy into humans will require exploring additional radiotracers.