18F-FDG PET Visualizes Systemic STING Agonist-Induced Lymphocyte Activation in Preclinical Models.

Stimulator of interferon genes (STING) is a mediator of immune recognition of cytosolic DNA, which plays important roles in cancer, cytotoxic therapies, and infections with certain pathogens. Although pharmacologic STING activation stimulates potent antitumor immune responses in animal models, clinically applicable pharmacodynamic biomarkers that inform of the magnitude, duration, and location of immune activation elicited by systemic STING agonists are yet to be described. We investigated whether systemic STING activation induces metabolic alterations in immune cells that can be visualized by PET imaging. Methods: C57BL/6 mice were treated with systemic STING agonists and imaged with 18F-FDG PET after 24 h. Splenocytes were harvested 6 h after STING agonist administration and analyzed by single-cell RNA sequencing and flow cytometry. 18F-FDG uptake in total splenocytes and immunomagnetically enriched splenic B and T lymphocytes from STING agonist-treated mice was measured by γ-counting. In mice bearing prostate or pancreas cancer tumors, the effects of STING agonist treatment on 18F-FDG uptake, T-lymphocyte activation marker levels, and tumor growth were evaluated. Results: Systemic delivery of structurally distinct STING agonists in mice significantly increased 18F-FDG uptake in the spleen. The average spleen SUVmax in control mice was 1.90 (range, 1.56-2.34), compared with 4.55 (range, 3.35-6.20) in STING agonist-treated mice (P < 0.0001). Single-cell transcriptional and flow cytometry analyses of immune cells from systemic STING agonist-treated mice revealed enrichment of a glycolytic transcriptional signature in both T and B lymphocytes that correlated with the induction of immune cell activation markers. In tumor-bearing mice, STING agonist administration significantly delayed tumor growth and increased 18F-FDG uptake in secondary lymphoid organs. Conclusion: These findings reveal hitherto unknown functional links between STING signaling and immunometabolism and suggest that 18F-FDG PET may provide a widely applicable approach toward measuring the pharmacodynamic effects of systemic STING agonists at a whole-body level and guiding their clinical development.

Purine nucleoside phosphorylase enables dual metabolic checkpoints that prevent T cell immunodeficiency and TLR7-associated autoimmunity.

Purine nucleoside phosphorylase (PNP) enables the breakdown and recycling of guanine nucleosides. PNP insufficiency in humans is paradoxically associated with both immunodeficiency and autoimmunity, but the mechanistic basis for these outcomes is incompletely understood. Here, we identify two immune lineage-dependent consequences of PNP inactivation dictated by distinct gene interactions. During T cell development, PNP inactivation is synthetically lethal with downregulation of the dNTP triphosphohydrolase SAMHD1. This interaction requires deoxycytidine kinase activity and is antagonized by microenvironmental deoxycytidine. In B lymphocytes and macrophages, PNP regulates Toll-like receptor 7 signaling by controlling the levels of its (deoxy)guanosine nucleoside ligands. Overriding this regulatory mechanism promotes germinal center formation in the absence of exogenous antigen and accelerates disease in a mouse model of autoimmunity. This work reveals that one purine metabolism gene protects against immunodeficiency and autoimmunity via independent mechanisms operating in distinct immune lineages and identifies PNP as a potentially novel metabolic immune checkpoint.

Reprogramming of nucleotide metabolism by interferon confers dependence on the replication stress response pathway in pancreatic cancer cells.

We determine that type I interferon (IFN) response biomarkers are enriched in a subset of pancreatic ductal adenocarcinoma (PDAC) tumors; however, actionable vulnerabilities associated with IFN signaling have not been systematically defined. Integration of a phosphoproteomic analysis and a chemical genomics synergy screen reveals that IFN activates the replication stress response kinase ataxia telangiectasia and Rad3-related protein (ATR) in PDAC cells and sensitizes them to ATR inhibitors. IFN triggers cell-cycle arrest in S-phase, which is accompanied by nucleotide pool insufficiency and nucleoside efflux. In combination with IFN, ATR inhibitors induce lethal DNA damage and downregulate nucleotide biosynthesis. ATR inhibition limits the growth of PDAC tumors in which IFN signaling is driven by stimulator of interferon genes (STING). These results identify a cross talk between IFN, DNA replication stress response networks, and nucleotide metabolism while providing the rationale for targeted therapeutic interventions that leverage IFN signaling in tumors.

STING-driven interferon signaling triggers metabolic alterations in pancreas cancer cells visualized by [18F]FLT PET imaging.

Type I interferons (IFNs) are critical effectors of emerging cancer immunotherapies designed to activate pattern recognition receptors (PRRs). A challenge in the clinical translation of these agents is the lack of noninvasive pharmacodynamic biomarkers that indicate increased intratumoral IFN signaling following PRR activation. Positron emission tomography (PET) imaging enables the visualization of tissue metabolic activity, but whether IFN signaling-induced alterations in tumor cell metabolism can be detected using PET has not been investigated. We found that IFN signaling augments pancreatic ductal adenocarcinoma (PDAC) cell nucleotide metabolism via transcriptional induction of metabolism-associated genes including thymidine phosphorylase (TYMP). TYMP catalyzes the first step in the catabolism of thymidine, which competitively inhibits intratumoral accumulation of the nucleoside analog PET probe 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT). Accordingly, IFN treatment up-regulates cancer cell [18F]FLT uptake in the presence of thymidine, and this effect is dependent upon TYMP expression. In vivo, genetic activation of stimulator of interferon genes (STING), a PRR highly expressed in PDAC, enhances the [18F]FLT avidity of xenograft tumors. Additionally, small molecule STING agonists trigger IFN signaling-dependent TYMP expression in PDAC cells and increase tumor [18F]FLT uptake in vivo following systemic treatment. These findings indicate that [18F]FLT accumulation in tumors is sensitive to IFN signaling and that [18F]FLT PET may serve as a pharmacodynamic biomarker for STING agonist-based therapies in PDAC and possibly other malignancies characterized by elevated STING expression.

High-fat diet fuels prostate cancer progression by rewiring the metabolome and amplifying the MYC program.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.

Defining HLA-II Ligand Processing and Binding Rules with Mass Spectrometry Enhances Cancer Epitope Prediction.

Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Histone demethylase KDM6A directly senses oxygen to control chromatin and cell fate.

Oxygen sensing is central to metazoan biology and has implications for human disease. Mammalian cells express multiple oxygen-dependent enzymes called 2-oxoglutarate (OG)-dependent dioxygenases (2-OGDDs), but they vary in their oxygen affinities and hence their ability to sense oxygen. The 2-OGDD histone demethylases control histone methylation. Hypoxia increases histone methylation, but whether this reflects direct effects on histone demethylases or indirect effects caused by the hypoxic induction of the HIF (hypoxia-inducible factor) transcription factor or the 2-OG antagonist 2-hydroxyglutarate (2-HG) is unclear. Here, we report that hypoxia promotes histone methylation in a HIF- and 2-HG-independent manner. We found that the H3K27 histone demethylase KDM6A/UTX, but not its paralog KDM6B, is oxygen sensitive. KDM6A loss, like hypoxia, prevented H3K27 demethylation and blocked cellular differentiation. Restoring H3K27 methylation homeostasis in hypoxic cells reversed these effects. Thus, oxygen directly affects chromatin regulators to control cell fate.

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations.

Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics.

The Role of Mass Spectrometry and Proteogenomics in the Advancement of HLA Epitope Prediction.

A challenge in developing personalized cancer immunotherapies is the prediction of putative cancer-specific antigens. Currently, predictive algorithms are used to infer binding of peptides to human leukocyte antigen (HLA) heterodimers to aid in the selection of putative epitope targets. One drawback of current epitope prediction algorithms is that they are trained on datasets containing biochemical HLA-peptide binding data that may not completely capture the rules associated with endogenous processing and presentation. The field of MS has made great improvements in instrumentation speed and sensitivity, chromatographic resolution, and proteogenomic database search strategies to facilitate the identification of HLA-ligands from a variety of cell types and tumor tissues. As such, these advances have enabled MS profiling of HLA-binding peptides to be a tractable, orthogonal approach to lower throughput biochemical assays for generating comprehensive datasets to train epitope prediction algorithms. In this review, we will highlight the progress made in the field of HLA-ligand profiling enabled by MS and its impact on current and future epitope prediction strategies.

Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.

Functional Proteomic Analysis of Repressive Histone Methyltransferase Complexes Reveals ZNF518B as a G9A Regulator.

Cell-type specific gene silencing by histone H3 lysine 27 and lysine 9 methyltransferase complexes PRC2 and G9A-GLP is crucial both during development and to maintain cell identity. Although studying their interaction partners has yielded valuable insight into their functions, how these factors are regulated on a network level remains incompletely understood. Here, we present a new approach that combines quantitative interaction proteomics with global chromatin profiling to functionally characterize repressive chromatin modifying protein complexes in embryonic stem cells. We define binding stoichiometries of 9 new and 12 known interaction partners of PRC2 and 10 known and 29 new interaction partners of G9A-GLP, respectively. We demonstrate that PRC2 and G9A-GLP interact physically and share several interaction partners, including the zinc finger proteins ZNF518A and ZNF518B. Using global chromatin profiling by targeted mass spectrometry, we discover that even sub-stoichiometric binding partners such as ZNF518B can positively regulate global H3K9me2 levels. Biochemical analysis reveals that ZNF518B directly interacts with EZH2 and G9A. Our systematic analysis suggests that ZNF518B may mediate the structural association between PRC2 and G9A-GLP histone methyltransferases and additionally regulates the activity of G9A-GLP.

Building the Connectivity Map of epigenetics: chromatin profiling by quantitative targeted mass spectrometry.

Epigenetic control of genome function is an important regulatory mechanism in diverse processes such as lineage commitment and environmental sensing, and in disease etiologies ranging from neuropsychiatric disorders to cancer. Here we report a robust, high-throughput targeted, quantitative mass spectrometry (MS) method to rapidly profile modifications of the core histones of chromatin that compose the epigenetic landscape, enabling comparisons among cells with differing genetic backgrounds, genomic perturbations, and drug treatments.