Cancer Cell Metabolism: Warburg and Beyond

Whitehead Institute for Biomedical Research and Massachusetts Institute of Technology Department of Biology, Cambridge, MA 02142, USA.
Cell (Impact Factor: 32.24). 10/2008; 134(5):703-7. DOI: 10.1016/j.cell.2008.08.021
Source: PubMed


Described decades ago, the Warburg effect of aerobic glycolysis is a key metabolic hallmark of cancer, yet its significance remains unclear. In this Essay, we re-examine the Warburg effect and establish a framework for understanding its contribution to the altered metabolism of cancer cells.

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    • "This pathway is related to glutamate and proline metabolisms, regulating bioenergetics and redox status [26]. Most cancer cells demonstrate an increase in glucose uptake, a higher rate of glycolysis, and an increase in lactate secretion despite the presence of oxygen, a phenomenon known as the Warburg effect [27]. Here we report the analysis of potential changes in the concentration of metabolites in serum samples of pancreatic cancer patients in order to find possible associations between the mutual concentration of these metabolites and clinical pathological features in a selected and well characterized cohort of patients with PDAC. "
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    ABSTRACT: Purpose: Survival among patients with adenocarcinoma pancreatic cancer (PDCA) is highly variable, which ranges from 0% to 20% at 5 years. Such a wide range is due to tumor size and stage, as well other patients' characteristics. We analyzed alterations in the metabolomic profile, of PDCA patients, which are potentially predictive of patient's one-year mortality. Experimental design: A targeted metabolomic assay was conducted on serum samples of patients diagnosed with pancreatic cancer. Statistical analyses were performed only for those 27 patients with information on vital status at follow-up and baseline clinical features. Random Forest analysis was performed to identify all metabolites and clinical variables with the best capability to predict patient's mortality risk at one year. Regression coefficients were estimated from multivariable Weibull survival model, which included the most associated metabolites. Such coefficients were used as weights to build a metabolite risk score (MRS) which ranged from 0 (lowest mortality risk) to 1 (highest mortality risk). The stability of these weights were evaluated performing 10,000 bootstrap resamplings. Results: MRS was built as a weighted linear combination of the following five metabolites: Valine (HR = 0.62, 95%CI: 0.11-1.71 for each standard deviation (SD) of 98.57), Sphingomyeline C24:1 (HR = 2.66, 95%CI: 1.30-21.09, for each SD of 20.67), Lysine (HR = 0.36, 95%CI: 0.03-0.77, for each SD of 51.73), Tripentadecanoate TG15 (HR = 0.25, 95%CI: 0.01-0.82, for each SD of 2.88) and Symmetric dimethylarginine (HR = 2.24, 95%CI: 1.28-103.08, for each SD of 0.62), achieving a very high discrimination ability (survival c-statistic of 0.855, 95%CI: 0.816-0.894). Such association was still present even after adjusting for the most associated clinical variables (confounders). Conclusions: The mass spectrometry-based metabolomic profiling of serum represents a valid tool for discovering novel candidate biomarkers with prognostic ability to predict one-year mortality risk in patients with pancreatic adenocarcinoma.
    Full-text · Article · Feb 2016 · Oncotarget
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    • "Biofilm formation, sporulation or nutrient limitation in prokaryotes are conditions systematically associated with modulation of the OXPHOS outcome [1] [2] [3] [4] [5] [6] [7]. The same is true during eukaryotic cell differentiation or proliferation (see for instance, [8] [9] [10]). "
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    • "These data support a similar link between oncogenetic stress, lysophospholipid biosynthesis, and CD1-restricted T cell responses. Lipolytic release and remodeling of free fatty acids are associated with metabolic changes in tumor cells (Hsu and Sabatini, 2008;Vander Heiden et al., 2009) and could contribute to mLPA accumulation in cancers. Tumor cells often express increased levels of monoacylglycerol lipase, an enzyme which also generates lysophospholipids (Nomura et al., 2010) and induces accumulation of LPA. "
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