BackgroundStable isotope tracing is a powerful technique for following the fate of individual atoms through metabolic pathways. Measuring isotopic enrichment in metabolites provides quantitative insights into the biosynthetic network and enables flux analysis as a function of external perturbations. NMR and mass spectrometry are the techniques of choice for global profiling of stable isotope labeling patterns in cellular metabolites. However, meaningful biochemical interpretation of the labeling data requires both quantitative analysis and complex modeling. Here, we demonstrate a novel approach that involved acquiring and modeling the timecourses of 13C isotopologue data for UDP-N-acetyl-D-glucosamine (UDP-GlcNAc) synthesized from [U-13C]-glucose in human prostate cancer LnCaP-LN3 cells. UDP-GlcNAc is an activated building block for protein glycosylation, which is an important regulatory mechanism in the development of many prominent human diseases including cancer and diabetes.ResultsWe utilized a stable isotope resolved metabolomics (SIRM) approach to determine the timecourse of 13C incorporation from [U-13C]-glucose into UDP-GlcNAc in LnCaP-LN3 cells. 13C Positional isotopomers and isotopologues of UDP-GlcNAc were determined by high resolution NMR and Fourier transform-ion cyclotron resonance-mass spectrometry. A novel simulated annealing/genetic algorithm, called 'Genetic Algorithm for Isotopologues in Metabolic Systems' (GAIMS) was developed to find the optimal solutions to a set of simultaneous equations that represent the isotopologue compositions, which is a mixture of isotopomer species. The best model was selected based on information theory. The output comprises the timecourse of the individual labeled species, which was deconvoluted into labeled metabolic units, namely glucose, ribose, acetyl and uracil. The performance of the algorithm was demonstrated by validating the computed fractional 13C enrichment in these subunits against experimental data. The reproducibility and robustness of the deconvolution were verified by replicate experiments, extensive statistical analyses, and cross-validation against NMR data.ConclusionsThis computational approach revealed the relative fluxes through the different biosynthetic pathways of UDP-GlcNAc, which comprises simultaneous sequential and parallel reactions, providing new insight into the regulation of UDP-GlcNAc levels and O-linked protein glycosylation. This is the first such analysis of UDP-GlcNAc dynamics, and the approach is generally applicable to other complex metabolites comprising distinct metabolic subunits, where sufficient numbers of isotopologues can be unambiguously resolved and accurately measured.

Arsenic induces clinical remission in patients with acute promyelocytic leukemia and has potential for treatment of other cancers. The current study examines factors influencing sensitivity to arsenic using human malignant melanoma cell lines. A375 and SK-Mel-2 cells were sensitive to clinically achievable concentrations of arsenite, whereas SK-Mel-3 and SK-Mel-28 cells required supratherapeutic levels for toxicity. Inhibition of glutathione synthesis, glutathione S-transferase (GST) activity, and multidrug resistance protein (MRP) transporter function attenuated arsenite resistance, consistent with studies suggesting arsenite is extruded from the cell as a glutathione conjugate by MRP-1. However, MRP-1 was not overexpressed in resistant lines and GST-π was only slightly elevated. ICP-MS analysis indicated arsenite-resistant SK-Mel-28 cells did not accumulate less arsenic than arsenite-sensitive A375 cells, suggesting resistance was not attributable to reduced arsenic accumulation but rather to intrinsic properties of resistant cell lines. The mode of arseniteinduced cell death was apoptosis. Arsenite-induced apoptosis is associated with cell cycle alterations. Cell cycle analysis revealed arsenite-sensitive cells arrested in mitosis whereas arsenite-resistant cells did not, suggesting induction of mitotic arrest occurs at lower intracellular arsenic concentrations. Higher intracellular arsenic levels induced cell cycle arrest in S-phase and G 2 -phase in SK-Mel-3 and SK-Mel-28 cells, respectively. The lack of arsenite-induced mitotic arrest in resistant cell lines was associated with a weakened spindle checkpoint resulting from reduced expression of spindle checkpoint protein BUBR1. These data suggest arsenite has potential for treatment of solid tumors but a functional spindle checkpoint is a prerequisite for a positive response to its clinical application.

Inhibitory checkpoint blockade therapy is an immunomodulatory strategy that results in the restoration of T cell functions, and its efficacy depends on the recognition of tumor cells for destruction. Considering the factors at play, one could propose that anti-tumor responses will not occur if tumor cells are immunologically invisible to T cells. In this study, we tested a strategy based on the modulation of cancer cell's immunovisibility through HDAC inhibition. In a model (heterotopic and orthotopic) of mouse urothelial bladder cancer, we demonstrated that the use of intratumoral or intravesical HDACi in combination with systemic anti-PD-1 was effective at inducing curative responses with durable anti-tumor immunity capable of preventing tumor growth at a distal site. Mechanistically, we determined that protective responses were dependent on CD8 cells, but not NK cells. Of significance, in an in vitro human model, we found that fully activated T cells fail at killing bladder cancer cells unless tumor cells were pretreated with HDACi. Complementary to this observation, we found that HDACi cause gene deregulation, that results in the upregulation of genes responsible for mediating immunorecognition, NKG2D ligands and HSP70. Taken together, these data indicate that HDAC inhibition results in the elimination of the tumor cell's "invisibility cloak" that prevents T cells from recognizing and killing them. Finally, as checkpoint blockade therapy moves into the adjuvant setting, its combined use with locally administrated HDACi represents a new approach to be included in our current therapeutic treatment toolbox.

Large clinical trials and model systems studies suggest that the chemical form of selenium dictates chemopreventive and chemotherapeutic efficacy. Selenite induces excess ROS production, which mediates autophagy and eventual cell death in non‐small cell lung cancer adenocarcinoma A549 cells. As the mechanisms underlying these phenotypic effects are unclear, the clinical relevance of selenite for cancer therapy remains to be determined. The authors' previous stable isotope‐resolved metabolomics and gene expression analysis showed that selenite disrupts glycolysis, the Krebs cycle, and polyamine metabolism in A549 cells, potentially through perturbed glutaminolysis, a vital anaplerotic process for proliferation of many cancer cells. Herein, the role of the glutaminolytic enzyme glutaminase 1 (GLS1) in selenite's toxicity in A549 cells and in patient‐derived lung cancer tissues is investigated. Using [13C6]‐glucose and [13C5,15N2]‐glutamine tracers, selenite's action on metabolic networks is determined. Selenite inhibits glutaminolysis and glutathione synthesis by suppressing GLS1 expression, and blocks the Krebs cycle, but transiently activates pyruvate carboxylase activity. Glutamate supplementation partially rescues these anti‐proliferative and oxidative stress activities. Similar metabolic perturbations and necrosis are observed in selenite‐treated human patients' cancerous lung tissues ex vivo. The results support the hypothesis that GLS1 suppression mediates part of the anti‐cancer activity of selenite both in vitro and ex vivo.

We describe preparation and use of the quaternary ammonium-based α-iodoacetamide QDE and its isotopologue *QDE as reagents for chemoselective derivatization of cellular thiols. Direct addition of the reagents to live cells followed by adduct extraction into n-butanol and analysis by FT-ICR-MS provided a registry of matched isotope peaks from which molecular formulae of thiol metabolites were derived. Acidification to pH 4 during cell lysis and adduct formation further improves the chemoselectivity for thiol derivatization. Examination of A549 human lung adenocarcinoma cells using this approach revealed cysteine, cysteinylglycine, glutathione, and homocysteine as principal thiol metabolites as well as the sulfinic acid hypotaurine. The method is also readily applied to quantify the thiol metabolites, as demonstrated here by the quantification of both glutathione and glutathione disulfide in A549 cells at concentrations of 34.4±11.5 and 10.1± 4.0 nmol/mg protein, respectively.