Human melanoma metabolic network analysis with combined 13C NMR/bioreactor technique: testing the Warburg effect

Abstract

The bioreactor techniques are becoming an important tool to study cancer cell metabolism(1). The goal of the present work was to develop a 13C metabolic “bonded cumomer” modeling approach adapted for fitting bioreactor data obtained with 13C glucose as substrate and to calculate the extent of the Warburg effect and how much energy comes from aerobic glycolysis vs oxidative phosphorylation.ResultsFigure 1 shows experimental time courses for labeled glutamate obtained during [1,6‐13C2] glucose perfusion of melanoma cells cultured in a CST bioreactor. Using extracted fluxes we estimated that 54% of the energy coming from oxidative phosphorylation (from which 44% are from glucose) and 46% from aerobic glycolysis and the extent of the Warburg effect (aerobic glycolysis) was 87%.ConclusionsUnder aerobic conditions glycolysis provides nearly as much ATP as oxidative phosphorylation. The model is validated by excellent agreement between model predicted and experimentally measured values of CMRO2 and cytosolic glutamate pool size. Dynamic high‐resolution MR spectra is very sensitive to changing/adding biochemical pathways and flux values, and bonded cumomer modeling allows one to check precisely the feasibility of assumed general bionetworks and particular metabolic pathways.This work was supported by NIH grants 2U24‐CA083105 and 5R01CA129544–02