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Microeconomics of Metabolism: The Warburg Effect as Giffen Behaviour.

ABSTRACT: Metabolic behaviours of proliferating cells are often explained as a consequence of rational optimization of cellular growth rate, whereas microeconomics formulates consumption behaviours as optimization problems. Here, we pushed beyond the analogy to precisely map metabolism onto the theory of consumer choice. We thereby revealed the correspondence between long-standing mysteries in both fields: the Warburg effect, a seemingly wasteful but ubiquitous strategy where cells favour aerobic glycolysis over more energetically efficient oxidative phosphorylation, and Giffen behaviour, the unexpected consumer behaviour where a good is demanded more as its price rises. We identified the minimal, universal requirements for the Warburg effect: a trade-off between oxidative phosphorylation and aerobic glycolysis and complementarity, i.e. impossibility of substitution for different metabolites. Thus, various hypotheses for the Warburg effect are integrated into an identical optimization problem with the same universal structure. Besides, the correspondence between the Warburg effect and Giffen behaviour implies that oxidative phosphorylation is counter-intuitively stimulated when its efficiency is decreased by metabolic perturbations such as drug administration or mitochondrial dysfunction; the concept of Giffen behaviour bridges the Warburg effect and the reverse Warburg effect. This highlights that the application of microeconomics to metabolism can offer new predictions and paradigms for both biology and economics.

SUBMITTER: Yamagishi JF

PROVIDER: S-EPMC8558188 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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:Compared to normal cells, cancer cells strongly upregulate glucose uptake and glycolysis to give rise to increased yield of intermediate glycolytic metabolites and the end product pyruvate. Moreover, glycolysis is uncoupled from the mitochondrial tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS) in cancer cells. Consequently, the majority of glycolysis-derived pyruvate is diverted to lactate fermentation and kept away from mitochondrial oxidative metabolism. This metabolic phenotype is known as the Warburg effect. While it has become widely accepted that the glycolytic intermediates provide essential anabolic support for cell proliferation and tumor growth, it remains largely elusive whether and how the Warburg metabolic phenotype may play a role in tumor progression. We hereby review the cause and consequence of the restrained oxidative metabolism, in particular in the context of tumor metastasis. Cells change or lose their extracellular matrix during the metastatic process. Inadequate/inappropriate matrix attachment generates reactive oxygen species (ROS) and causes a specific type of cell death, termed anoikis, in normal cells. Although anoikis is a barrier to metastasis, cancer cells have often acquired elevated threshold for anoikis and hence heightened metastatic potential. As ROS are inherent byproducts of oxidative metabolism, forced stimulation of glucose oxidation in cancer cells raises oxidative stress and restores cells' sensitivity to anoikis. Therefore, by limiting the pyruvate flux into mitochondrial oxidative metabolism, the Warburg effect enables cancer cells to avoid excess ROS generation from mitochondrial respiration and thus gain increased anoikis resistance and survival advantage for metastasis. Consistent with this notion, pro-metastatic transcription factors HIF and Snail attenuate oxidative metabolism, whereas tumor suppressor p53 and metastasis suppressor KISS1 promote mitochondrial oxidation. Collectively, these findings reveal mitochondrial oxidative metabolism as a critical suppressor of metastasis and justify metabolic therapies for potential prevention/intervention of tumor metastasis.

Project description:BackgroundTwo recent observations regarding the Warburg effect are that (i) the metabolism of stem cells is constitutive (aerobic) glycolysis while normal cellular differentiation involves a transition to oxidative phosphorylation and (ii) the degree of glucose uptake of a malignancy as imaged by 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is associated with histologic measures of tumor differentiation. Combining these observations, we hypothesized that the high levels of glucose uptake observed in poorly differentiated cancers may reflect persistence of the glycolytic metabolism of stem cells in malignant cells that fail to fully differentiate.Patients and methodsTumor glucose uptake was measured by FDG-PET in 552 patients with histologically diverse cancers. We used normal mixture modeling to explore FDG-PET standardized uptake value (SUV) distributions and tested for associations between glucose uptake and histological differentiation, risk of lymph node metastasis, and survival. Using RNA-seq data, we carried out pathway and transcription factor analyses to compare tumors with high and low levels of glucose uptake.ResultsWe found that well-differentiated tumors had low FDG uptake, while moderately and poorly differentiated tumors had higher uptake. The distribution of SUV for each histology was bimodal, with a low peak around SUV 2-5 and a high peak at SUV 8-14. The cancers in the two modes were clinically distinct in terms of the risk of nodal metastases and death. Carbohydrate metabolism and the pentose-related pathway were elevated in the poorly differentiated/high SUV clusters. Embryonic stem cell-related signatures were activated in poorly differentiated/high SUV clusters.ConclusionsOur findings support the hypothesis that the biological basis for the Warburg effect is a persistence of stem cell metabolism (i.e. aerobic glycolysis) in cancers as a failure to transition from glycolysis-utilizing undifferentiated cells to oxidative phosphorylation-utilizing differentiated cells. We found that cancers cluster along the differentiation pathway into two groups, utilizing either glycolysis or oxidative phosphorylation. Our results have implications for multiple areas of clinical oncology.

Project description:Cancer metabolism has received renewed interest as a potential target for cancer therapy. In this study, we use a multi-scale modeling approach to interrogate the implications of three metabolic scenarios of potential clinical relevance: the Warburg effect, the reverse Warburg effect and glutamine addiction. At the intracellular level, we construct a network of central metabolism and perform flux balance analysis (FBA) to estimate metabolic fluxes; at the cellular level, we exploit this metabolic network to calculate parameters for a coarse-grained description of cellular growth kinetics; and at the multicellular level, we incorporate these kinetic schemes into the cellular automata of an agent-based model (ABM), iDynoMiCS. This ABM evaluates the reaction-diffusion of the metabolites, cellular division and motion over a simulation domain. Our multi-scale simulations suggest that the Warburg effect provides a growth advantage to the tumor cells under resource limitation. However, we identify a non-monotonic dependence of growth rate on the strength of glycolytic pathway. On the other hand, the reverse Warburg scenario provides an initial growth advantage in tumors that originate deeper in the tissue. The metabolic profile of stromal cells considered in this scenario allows more oxygen to reach the tumor cells in the deeper tissue and thus promotes tumor growth at earlier stages. Lastly, we suggest that glutamine addiction does not confer a selective advantage to tumor growth with glutamine acting as a carbon source in the tricarboxylic acid (TCA) cycle, any advantage of glutamine uptake must come through other pathways not included in our model (e.g., as a nitrogen donor). Our analysis illustrates the importance of accounting explicitly for spatial and temporal evolution of tumor microenvironment in the interpretation of metabolic scenarios and hence provides a basis for further studies, including evaluation of specific therapeutic strategies that target metabolism.

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Microeconomics of Metabolism: The Warburg Effect as Giffen Behaviour.

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