| dc.description.abstract | In recent years it has become evident that altered metabolism is a hallmark of cancer and offers many opportunities for therapeutic intervention. This dissertation presents the development of a novel metabolic flux analysis (MFA) technique and its application to in vitro and in vivo models of oncogene-driven cancer. The P493-6 B-cell model is a unique system for studying the effects of the Myc oncoprotein because it is able to express three distinct levels of Myc (High, Low, and None) on an isogenic background. Myc is a global transcription factor and has dysregulated expression in over 30% of all cancers. High Myc cells, representative of Burkitt’s lymphoma, form tumors in mice while Low Myc cells do not. Using these cells, we optimized an isotopically nonstationary MFA (INST-MFA) method where the isotope labeling is measured in stable, macromolecule pools prior to isotopic steady-state. Advantages of this technique are decreased experimental time, increased signal-to-noise ratios, and extensibility to in vivo and 3D culture systems. We also describe preliminary studies to translate INST-MFA to in vivo models of Myc-driven cancer.
Using INST-MFA, we examined High and Low Myc P493-6 B-cells in normoxic and hypoxic environments. Application of 13C-INST-MFA to P493-6 cells under normoxia revealed that High Myc cells relied more on oxidative phosphorylation (OXPHOS) than Low Myc cells. This finding runs somewhat counter to the so-called ‘Warburg Effect’, where cancerous cells aerobically switch to fermentation and decrease their reliance on OXPHOS. We then sought to understand how these MFA results could be used to aid in selecting novel drug targets. Oxamate and phenformin, small-molecule inhibitors of lactate production and OXPHOS, respectively, were used individually and in combination. High Myc cells exhibited greater sensitivity to phenformin while Low Myc cells, which relied more on glycolysis for energy generation, were more sensitive to oxamate. When treated with the two drugs simultaneously, there was a greater synergistic effect on High Myc cells than Low Myc. These results offer insight into how MFA studies can predict drug responses and highlight the importance of phenotyping individual cancers. | |
