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The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand.

ABSTRACT: To maintain optimal fitness, a cell must balance the risk of inadequate energy reserve for response to a potentially fatal perturbation against the long-term cost of maintaining high concentrations of ATP to meet occasional spikes in demand. Here we apply a game theoretic approach to address the dynamics of energy production and expenditure in eukaryotic cells. Conventionally, glucose metabolism is viewed as a function of oxygen concentrations in which the more efficient oxidation of glucose to CO2 and H2O produces all or nearly all ATP except under hypoxic conditions when less efficient (2 ATP/ glucose vs. about 36ATP/glucose) anaerobic metabolism of glucose to lactic acid provides an emergency backup. We propose an alternative in which energy production is governed by the complex temporal and spatial dynamics of intracellular ATP demand. In the short term, a cell must provide energy for constant baseline needs but also maintain capacity to rapidly respond to fluxes in demand particularly due to external perturbations on the cell membrane. Similarly, longer-term dynamics require a trade-off between the cost of maintaining high metabolic capacity to meet uncommon spikes in demand versus the risk of unsuccessfully responding to threats or opportunities. Here we develop a model and computationally explore the cell's optimal mix of glycolytic and oxidative capacity. We find the Warburg effect, high glycolytic metabolism even under normoxic conditions, is represents a metabolic strategy that allow cancer cells to optimally meet energy demands posed by stochastic or fluctuating tumor environments.

SUBMITTER: Epstein T

PROVIDER: S-EPMC5602667 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand.

Epstein Tamir T Gatenby Robert A RA Brown Joel S JS

PloS one 20170918 9

To maintain optimal fitness, a cell must balance the risk of inadequate energy reserve for response to a potentially fatal perturbation against the long-term cost of maintaining high concentrations of ATP to meet occasional spikes in demand. Here we apply a game theoretic approach to address the dynamics of energy production and expenditure in eukaryotic cells. Conventionally, glucose metabolism is viewed as a function of oxygen concentrations in which the more efficient oxidation of glucose to ...[more]

PMID: 28922380

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Project description:BackgroundAlterations on glucose consumption and biosynthetic activity of amino acids, lipids and nucleotides are metabolic changes for sustaining cell proliferation in cancer cells. Irrevocable evidence of this fact is the Warburg effect which establishes that cancer cells prefers glycolysis over oxidative phosphorylation to generate ATP. Regulatory action over metabolic enzymes has opened a new window for designing more effective anti-cancer treatments. This enterprise is not trivial and the development of computational models that contribute to identifying potential enzymes for breaking the robustness of cancer cells is a priority.Methodology/principal findingsThis work presents a constraint-base modeling of the most experimentally studied metabolic pathways supporting cancer cells: glycolysis, TCA cycle, pentose phosphate, glutaminolysis and oxidative phosphorylation. To evaluate its predictive capacities, a growth kinetics study for Hela cell lines was accomplished and qualitatively compared with in silico predictions. Furthermore, based on pure computational criteria, we concluded that a set of enzymes (such as lactate dehydrogenase and pyruvate dehydrogenase) perform a pivotal role in cancer cell growth, findings supported by an experimental counterpart.Conclusions/significanceAlterations on metabolic activity are crucial to initiate and sustain cancer phenotype. In this work, we analyzed the phenotype capacities emerged from a constructed metabolic network conformed by the most experimentally studied pathways sustaining cancer cell growth. Remarkably, in silico model was able to resemble the physiological conditions in cancer cells and successfully identified some enzymes currently studied by its therapeutic effect. Overall, we supplied evidence that constraint-based modeling constitutes a promising computational platform to: 1) integrate high throughput technology and establish a crosstalk between experimental validation and in silico prediction in cancer cell phenotype; 2) explore the fundamental metabolic mechanism that confers robustness in cancer; and 3) suggest new metabolic targets for anticancer treatments. All these issues being central to explore cancer cell metabolism from a systems biology perspective.

Project description:Ovarian cancer (OVCA) is among the most lethal gynecological cancers leading to high mortality rates among women. Increasing evidence indicate that cancer cells undergo metabolic transformation during tumorigenesis and growth through nutrients and growth factors available in tumor microenvironment. This altered metabolic rewiring further enhances tumor progression. Recent studies have begun to unravel the role of amino acids in the tumor microenvironment on the proliferation of cancer cells. One critically important, yet often overlooked, component to tumor growth is the metabolic reprogramming of nitric oxide (NO) pathways in cancer cells. Multiple lines of evidence support the link between NO and tumor growth in some cancers, including pancreas, breast and ovarian. However, the multifaceted role of NO in the metabolism of OVCA is unclear and direct demonstration of NO's role in modulating OVCA cells' metabolism is lacking. This study aims at indentifying the mechanistic links between NO and OVCA metabolism. We uncover a role of NO in modulating OVCA metabolism: NO positively regulates the Warburg effect, which postulates increased glycolysis along with reduced mitochondrial activity under aerobic conditions in cancer cells. Through both NO synthesis inhibition (using L-arginine deprivation, arginine is a substrate for NO synthase (NOS), which catalyzes NO synthesis; using L-Name, a NOS inhibitor) and NO donor (using DETA-NONOate) analysis, we show that NO not only positively regulates tumor growth but also inhibits mitochondrial respiration in OVCA cells, shifting these cells towards glycolysis to maintain their ATP production. Additionally, NO led to an increase in TCA cycle flux and glutaminolysis, suggesting that NO decreases ROS levels by increasing NADPH and glutathione levels. Our results place NO as a central player in the metabolism of OVCA cells. Understanding the effects of NO on cancer cell metabolism can lead to the development of NO targeting drugs for OVCAs.

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The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand.

Publications

The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand.

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