The Untapped Opportunity and Challenge of Immunometabolism: A New Paradigm for Drug Discovery.

Here, we explore the manipulation of immune cell metabolism as a strategy in target discovery and drug development for immune-mediated diseases. Comparing exploitation of metabolic pathways to kill tumor cells for cancer treatment with the reprogramming of immune cells to treat autoimmune diseases highlights differences that confer several advantages to the latter (including a more favorable therapeutic index and greater target stability). We discuss technological capabilities and gaps, including the challenge of relating in vitro observations to in vivo biology. Finally, we conclude by identifying future opportunities that will move the field forward and accelerate drug discovery.

Metabolic control of TH17 and induced Treg cell balance by an epigenetic mechanism.

Metabolism has been shown to integrate with epigenetics and transcription to modulate cell fate and function. Beyond meeting the bioenergetic and biosynthetic demands of T-cell differentiation, whether metabolism might control T-cell fate by an epigenetic mechanism is unclear. Here, through the discovery and mechanistic characterization of a small molecule, (aminooxy)acetic acid, that reprograms the differentiation of T helper 17 (TH17) cells towards induced regulatory T (iTreg) cells, we show that increased transamination, mainly catalysed by GOT1, leads to increased levels of 2-hydroxyglutarate in differentiating TH17 cells. The accumulation of 2-hydroxyglutarate resulted in hypermethylation of the Foxp3 gene locus and inhibited Foxp3 transcription, which is essential for fate determination towards TH17 cells. Inhibition of the conversion of glutamate to α-ketoglutaric acid prevented the production of 2-hydroxyglutarate, reduced methylation of the Foxp3 gene locus, and increased Foxp3 expression. This consequently blocked the differentiation of TH17 cells by antagonizing the function of transcription factor RORγt and promoted polarization into iTreg cells. Selective inhibition of GOT1 with (aminooxy)acetic acid ameliorated experimental autoimmune encephalomyelitis in a therapeutic mouse model by regulating the balance between TH17 and iTreg cells. Targeting a glutamate-dependent metabolic pathway thus represents a new strategy for developing therapeutic agents against TH17-mediated autoimmune diseases.

GAM: a web-service for integrated transcriptional and metabolic network analysis.

Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/.

Integration of omics: more than the sum of its parts.

Genome scale data on biological systems has increasingly become available by sequencing of DNA and RNA, and by mass spectrometric quantification of proteins and metabolites. The cellular components from which these -omics regimes are derived act as one integrated system in vivo; thus, there is a natural instinct to integrate -omics data types. Statistical analyses, the use of previous knowledge in the form of networks, and the use of time-resolved measurements are three key design elements for life scientists to consider in planning integrated -omics studies. These design elements are reviewed in the context of multiple recent systems biology studies that leverage data from different types of -omics analyses. While most of these studies rely on well-established model organisms, the concepts for integrating -omics data that were developed in these studies can help to enable systems research in the field of cancer biology.

Network integration of parallel metabolic and transcriptional data reveals metabolic modules that regulate macrophage polarization.

Macrophage polarization involves a coordinated metabolic and transcriptional rewiring that is only partially understood. By using an integrated high-throughput transcriptional-metabolic profiling and analysis pipeline, we characterized systemic changes during murine macrophage M1 and M2 polarization. M2 polarization was found to activate glutamine catabolism and UDP-GlcNAc-associated modules. Correspondingly, glutamine deprivation or inhibition of N-glycosylation decreased M2 polarization and production of chemokine CCL22. In M1 macrophages, we identified a metabolic break at Idh, the enzyme that converts isocitrate to alpha-ketoglutarate, providing mechanistic explanation for TCA cycle fragmentation. (13)C-tracer studies suggested the presence of an active variant of the aspartate-arginosuccinate shunt that compensated for this break. Consistently, inhibition of aspartate-aminotransferase, a key enzyme of the shunt, inhibited nitric oxide and interleukin-6 production in M1 macrophages, while promoting mitochondrial respiration. This systems approach provides a highly integrated picture of the physiological modules supporting macrophage polarization, identifying potential pharmacologic control points for both macrophage phenotypes.

Metabolic and functional genomic studies identify deoxythymidylate kinase as a target in LKB1-mutant lung cancer.

The LKB1/STK11 tumor suppressor encodes a serine/threonine kinase, which coordinates cell growth, polarity, motility, and metabolism. In non-small cell lung carcinoma, LKB1 is somatically inactivated in 25% to 30% of cases, often concurrently with activating KRAS mutations. Here, we used an integrative approach to define novel therapeutic targets in KRAS-driven LKB1-mutant lung cancers. High-throughput RNA interference screens in lung cancer cell lines from genetically engineered mouse models driven by activated KRAS with or without coincident Lkb1 deletion led to the identification of Dtymk, encoding deoxythymidylate kinase (DTYMK), which catalyzes dTTP biosynthesis, as synthetically lethal with Lkb1 deficiency in mouse and human lung cancer lines. Global metabolite profiling showed that Lkb1-null cells had a striking decrease in multiple nucleotide metabolites as compared with the Lkb1-wild-type cells. Thus, LKB1-mutant lung cancers have deficits in nucleotide metabolism that confer hypersensitivity to DTYMK inhibition, suggesting that DTYMK is a potential therapeutic target in this aggressive subset of tumors.

Phosphofructokinase 1 glycosylation regulates cell growth and metabolism.

Cancer cells must satisfy the metabolic demands of rapid cell growth within a continually changing microenvironment. We demonstrated that the dynamic posttranslational modification of proteins by O-linked ß-N-acetylglucosamine (O-GlcNAcylation) is a key metabolic regulator of glucose metabolism. O-GlcNAcylation was induced at serine 529 of phosphofructokinase 1 (PFK1) in response to hypoxia. Glycosylation inhibited PFK1 activity and redirected glucose flux through the pentose phosphate pathway, thereby conferring a selective growth advantage on cancer cells. Blocking glycosylation of PFK1 at serine 529 reduced cancer cell proliferation in vitro and impaired tumor formation in vivo. These studies reveal a previously uncharacterized mechanism for the regulation of metabolic pathways in cancer and a possible target for therapeutic intervention.

Functional genomics reveal that the serine synthesis pathway is essential in breast cancer.

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation. RNA interference (RNAi)-based loss-of-function screening has proven powerful for the identification of new and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumour suppressor genes. Here we developed a method for identifying novel cancer targets via negative-selection RNAi screening using a human breast cancer xenograft model at an orthotopic site in the mouse. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumorigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of oestrogen receptor (ER)-negative breast cancers. PHGDH catalyses the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have increased serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not in those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of α-ketoglutarate, another output of the pathway and a tricarboxylic acid (TCA) cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH overexpression and demonstrate the utility of in vivo negative-selection RNAi screens for finding potential anticancer targets.

Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations.

Mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2), are present in most gliomas and secondary glioblastomas, but are rare in other neoplasms. IDH1/2 mutations are heterozygous, and affect a single arginine residue. Recently, IDH1 mutations were identified in 8% of acute myelogenous leukemia (AML) patients. A glioma study revealed that IDH1 mutations cause a gain-of-function, resulting in the production and accumulation of 2-hydroxyglutarate (2-HG). Genotyping of 145 AML biopsies identified 11 IDH1 R132 mutant samples. Liquid chromatography-mass spectrometry metabolite screening revealed increased 2-HG levels in IDH1 R132 mutant cells and sera, and uncovered two IDH2 R172K mutations. IDH1/2 mutations were associated with normal karyotypes. Recombinant IDH1 R132C and IDH2 R172K proteins catalyze the novel nicotinamide adenine dinucleotide phosphate (NADPH)-dependent reduction of alpha-ketoglutarate (alpha-KG) to 2-HG. The IDH1 R132C mutation commonly found in AML reduces the affinity for isocitrate, and increases the affinity for NADPH and alpha-KG. This prevents the oxidative decarboxylation of isocitrate to alpha-KG, and facilitates the conversion of alpha-KG to 2-HG. IDH1/2 mutations confer an enzymatic gain of function that dramatically increases 2-HG in AML. This provides an explanation for the heterozygous acquisition of these mutations during tumorigenesis. 2-HG is a tractable metabolic biomarker of mutant IDH1/2 enzyme activity.

Cancer-associated IDH1 mutations produce 2-hydroxyglutarate.

Mutations in the enzyme cytosolic isocitrate dehydrogenase 1 (IDH1) are a common feature of a major subset of primary human brain cancers. These mutations occur at a single amino acid residue of the IDH1 active site, resulting in loss of the enzyme's ability to catalyse conversion of isocitrate to alpha-ketoglutarate. However, only a single copy of the gene is mutated in tumours, raising the possibility that the mutations do not result in a simple loss of function. Here we show that cancer-associated IDH1 mutations result in a new ability of the enzyme to catalyse the NADPH-dependent reduction of alpha-ketoglutarate to R(-)-2-hydroxyglutarate (2HG). Structural studies demonstrate that when arginine 132 is mutated to histidine, residues in the active site are shifted to produce structural changes consistent with reduced oxidative decarboxylation of isocitrate and acquisition of the ability to convert alpha-ketoglutarate to 2HG. Excess accumulation of 2HG has been shown to lead to an elevated risk of malignant brain tumours in patients with inborn errors of 2HG metabolism. Similarly, in human malignant gliomas harbouring IDH1 mutations, we find markedly elevated levels of 2HG. These data demonstrate that the IDH1 mutations result in production of the onco-metabolite 2HG, and indicate that the excess 2HG which accumulates in vivo contributes to the formation and malignant progression of gliomas.

The exploration of macrocycles for drug discovery--an underexploited structural class.

Macrocyclic natural products have evolved to fulfil numerous biochemical functions, and their profound pharmacological properties have led to their development as drugs. A macrocycle provides diverse functionality and stereochemical complexity in a conformationally pre-organized ring structure. This can result in high affinity and selectivity for protein targets, while preserving sufficient bioavailability to reach intracellular locations. Despite these valuable characteristics, and the proven success of more than 100 marketed macrocycle drugs derived from natural products, this structural class has been poorly explored within drug discovery. This is in part due to concerns about synthetic intractability and non-drug-like properties. This Review describes the growing body of data in favour of macrocyclic therapeutics, and demonstrates that this class of compounds can be both fully drug-like in its properties and readily prepared owing to recent advances in synthetic medicinal chemistry.

Protein fucosylation regulates synapsin Ia/Ib expression and neuronal morphology in primary hippocampal neurons.

Although fucose-alpha(1-2)-galactose [Fucalpha(1-2)Gal] carbohydrates have been implicated in cognitive processes such as long-term memory, the molecular mechanisms by which these sugars influence neuronal communication are not well understood. Here, we present molecular insights into the functions of Fucalpha(1-2)Gal sugars, demonstrating that they play a role in the regulation of synaptic proteins and neuronal morphology. We show that synapsins Ia and Ib, synapse-specific proteins involved in neurotransmitter release and synaptogenesis, are the major Fucalpha(1-2)Gal glycoproteins in mature cultured neurons and the adult rat hippocampus. Fucosylation has profound effects on the expression and turnover of synapsin in cells and protects synapsin from degradation by the calcium-activated protease calpain. Our studies suggest that defucosylation of synapsin has critical consequences for neuronal growth and morphology, leading to stunted neurite outgrowth and delayed synapse formation. We also demonstrate that Fucalpha(1-2)Gal carbohydrates are not limited to synapsin but are found on additional glycoproteins involved in modulating neuronal architecture. Together, our studies identify important roles for Fucalpha(1-2)Gal sugars in the regulation of neuronal proteins and morphological changes that may underlie synaptic plasticity.

Integrating transcriptional and metabolite profiles to direct the engineering of lovastatin-producing fungal strains.

We describe a method to decipher the complex inter-relationships between metabolite production trends and gene expression events, and show how information gleaned from such studies can be applied to yield improved production strains. Genomic fragment microarrays were constructed for the Aspergillus terreus genome, and transcriptional profiles were generated from strains engineered to produce varying amounts of the medically significant natural product lovastatin. Metabolite detection methods were employed to quantify the polyketide-derived secondary metabolites lovastatin and (+)-geodin in broths from fermentations of the same strains. Association analysis of the resulting transcriptional and metabolic data sets provides mechanistic insight into the genetic and physiological control of lovastatin and (+)-geodin biosynthesis, and identifies novel components involved in the production of (+)-geodin, as well as other secondary metabolites. Furthermore, this analysis identifies specific tools, including promoters for reporter-based selection systems, that we employed to improve lovastatin production by A. terreus.