Inhibition of indoleamine 2,3-dioxygenase in mixed lymphocyte reaction affects glucose influx and enzymes involved in aerobic glycolysis and glutaminolysis in alloreactive T-cells

Indoleamine 2,3-dioxygenase (IDO) suppresses adaptive immunity. T-cell proliferation and differentiation to effector cells require increased glucose consumption, aerobic glycolysis and glutaminolysis. The effect of IDO on the above metabolic pathways was evaluated in alloreactive T-cells. Mixed lymphocyte reaction (MLR) in the presence or not of the IDO inhibitor, 1-DL-methyl-tryptophane (1-MT), was used. In MLRs, 1-MT decreased tryptophan consumption, increased cell proliferation, glucose influx and lactate production, whereas it decreased tricarboxylic acid cycle activity. In T-cells, from the two pathways that could sense tryptophan depletion, i.e. general control nonrepressed 2 (GCN2) kinase and mammalian target of rapamycin complex 1, 1-MT reduced only the activity of the GCN2 kinase. Additionally 1-MT treatment of MLRs altered the expression and/or the phosphorylation state of glucose transporter-1 and of key enzymes involved in glucose metabolism and glutaminolysis in alloreactive T-cells in a way that favors glucose influx, aerobic glycolysis and glutaminolysis. Thus in alloreactive T-cells, IDO through activation of the GCN2 kinase, decreases glucose influx and alters key enzymes involved in metabolism, decreasing aerobic glycolysis and glutaminolysis. Acting in such a way, IDO could be considered as a constraining factor for alloreactive T-cell proliferation and differentiation to effector T-cell subtypes.

Multi-parametric metabolic assessment of cells under stress conditions

Glycolysis, glutaminolysis, the Krebs cycle and oxidative phosphorylation are the main metabolic pathways. Exposing cells to key metabolic substrates (glucose, glutamine and pyruvate); investigation of the contribution of substrates in stress conditions such as uncoupling and hypoxia was conducted. Glycolysis, O2 consumption, O2 and ATP levels and hypoxia inducible factor (HIF) signalling in PC12 cells were investigated. Upon uncoupling with FCCP mitochondria were depolarised similarly in all cases, but a strong increase in respiration was only seen in the cells fed on glutamine with either glucose or pyruvate. Inhibition of glutaminolysis reversed the glutamine dependant effect. Differential regulation of the respiratory response to FCCP by metabolic environment suggests mitochondrial uncoupling has a potential for substrate-specific inhibition of cell function. At reduced O2 availability (4 % and 0 % O2), cell bioenergetics and local oxygenation varied depending on the substrate composition. Results indicate that both supply and utilisation of key metabolic substrates can affect the pattern of HIF-1/2α accumulation by differentially regulating iO2¬, ATP levels and Akt/Erk/AMPK pathways. Inhibition of key metabolic pathways can modulate HIF regulatory pathways, metabolic responses and survival of cancer cells in hypoxia. Hypoxia leads to transcriptional activation, by HIF, of pyruvate dehydrogenase (PDH) kinase which phosphorylates and inhibits PDH, a mitochondrial enzyme that converts pyruvate into acetyl-CoA. The levels of PDH (total and phosphorylated), PDH kinase and HIF-1α were analysed in HCT116 and HCT116 SCO2-/- (deficient in complex IV of the respiratory chain) grown under 20.9 % and 3 % O2. Data indicate that regulation of PDH can occur in a manner independent of the HIF-1/PDH kinase 1 axis, mitochondrial respiration and the demand for acetyl-CoA. Collectively these results can be applied to many diseases; reduced nutrient supply and O2 during ischemia/stroke, hypoglycaemia in diabetes mellitus and cancer associated changes in uncoupling protein expression levels.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

A STUDY ON THE FUNCTION OF 14-3-3SIGMA IN REGULATING CANCER ENERGY METABOLISM

Metabolic reprogramming has been shown to be a major cancer hallmark providing tumor cells with significant advantages for survival, proliferation, growth, metastasis and resistance against anti-cancer therapies. Glycolysis, glutaminolysis and mitochondrial biogenesis are among the most essential cancer metabolic alterations because these pathways provide cancer cells with not only energy but also crucial metabolites to support large-scale biosynthesis, rapid proliferation and tumorigenesis. In this study, we find that 14-3-3σ suppresses all these three metabolic processes by promoting the degradation of their main driver, c-Myc. In fact, 14-3-3s significantly enhances c-Myc poly-ubiquitination and subsequent degradation, reduces c-Myc transcriptional activity, and down-regulates c-Myc-induced metabolic target genes expression. Therefore, 14-3-3σ remarkably blocks glycolysis, decreases glutaminolysis and diminishes mitochondrial mass of cancer cells both in vitro and in vivo, thereby severely suppressing cancer bioenergetics and metabolism. As a result, a high level of 14-3-3σ in tumors is strongly associated with increased breast cancer patients’ overall and metastasis-free survival as well as better clinical outcomes. Thus, this study reveals a new role for 14-3-3s as a significant regulator of cancer bioenergetics and a promising target for the development of anti-cancer metabolism therapies.

Latent and Lytic KSHV Infection Require Host Cell Metabolism

Thesis (Ph.D.)--University of Washington, 2016-06