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Review
. 2020 Apr 10;368(6487):eaaw5473.
doi: 10.1126/science.aaw5473.

Metabolic reprogramming and cancer progression

Affiliations
Review

Metabolic reprogramming and cancer progression

Brandon Faubert et al. Science. .

Abstract

Metabolic reprogramming is a hallmark of malignancy. As our understanding of the complexity of tumor biology increases, so does our appreciation of the complexity of tumor metabolism. Metabolic heterogeneity among human tumors poses a challenge to developing therapies that exploit metabolic vulnerabilities. Recent work also demonstrates that the metabolic properties and preferences of a tumor change during cancer progression. This produces distinct sets of vulnerabilities between primary tumors and metastatic cancer, even in the same patient or experimental model. We review emerging concepts about metabolic reprogramming in cancer, with particular attention on why metabolic properties evolve during cancer progression and how this information might be used to develop better therapeutic strategies.

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Conflict of interest statement

Competing Interests: R.J.D. is an advisor for Agios Pharmaceuticals.

Figures

Fig. 1.
Fig. 1.. Intrinsic and extrinsic factors contribute to metabolic phenotypes in tumors.
Intrinsic factors include characteristics of the parental tissue as well as new properties arising in the malignant cells as a consequence of altered signaling and transcriptional networks. Extrinsic factors include metabolic stresses imposed by the microenvironment and metabolism of the patient.
Fig. 2.
Fig. 2.. Accumulation of somatically acquired mutations changes tumor biology and causes metabolic liabilities to evolve.
KRAS mutations initiate tumorigenesis in the lung, driving nutrient uptake and anabolism. Mutation of STK11 increases key aspects of aggressive tumor biology, including metastatic efficiency and therapy resistance, but increases sensitivity to some metabolic inhibitors. KEAP1 mutations enhance resistance to oxidative stress by stimulating glutathione biosynthesis but induce dependence on glutaminase to supply precursors to produce glutathione. Cells are color-coded according to their genotype.
Fig. 3.
Fig. 3.. Tumor metabolism supports multiple steps of the metastatic cascade.
Bottlenecks occur at several steps of metastasis, and metabolic reprogramming supports successful navigation of some of these barriers. Extracellular acidification promotes intravasation of cells from the primary tumor. A major bottleneck occurs after cells enter the circulation, when survival requires mechanisms to produce NADPH and glutathione (GSH) to counteract oxidative stress. Successful seeding of distant organs and survival during dormancy may require harmony between the new microenvironment and the needs of cancer cells in micrometastatic lesions. Last, anabolic metabolism is reactivated during macrometastatic tumor growth.
Fig. 4.
Fig. 4.. Prospects for using in vivo analysis to match tumor metabolism with metabolic therapies.
Several new approaches to assess metabolism in intact tumors, particularly with new imaging approaches, have been used in humans and experimental models to report subtype-selective metabolic properties, some of which correlate with therapeutic sensitivities. MRS, magnetic resonance spectroscopy; D-2HG, D-2-hydroxyglutarate; mIDH, mutant isocitrate dehydrogenase; MCT1, monocarboxylate transporter-1; 18F-BnTP, 4-[18F]fluorobenzy7l-triphenylphosphonium; Gln, glutamine; PET, positron emission tomography; GLS, glutaminase.

Comment in

References

    1. Vander Heiden MG, Cantley LC, Thompson CB, Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009). doi: 10.1126/science.1160809 - DOI - PMC - PubMed
    1. Kim J, DeBerardinis RJ, Mechanisms and implications of metabolic heterogeneity in cancer. Cell Metab. 30, 434–446 (2019). doi: 10.1016/j.cmet.2019.08.013 - DOI - PMC - PubMed
    1. Hoadley KA, et al. , Yau C et al. , Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell 173, 291–304.e6 (2018). doi: 10.1016/j.cell.2018.03.022 - DOI - PMC - PubMed
    1. Hu J et al. , Heterogeneity of tumor-induced gene expression changes in the human metabolic network. Nat. Biotechnol. 31, 522–529 (2013). doi: 10.1038/nbt.2530 - DOI - PMC - PubMed
    1. Yuneva MO et al. , The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metab. 15, 157–170 (2012). doi: 10.1016/j.cmet.2011.12.015 - DOI - PMC - PubMed

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