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Cancer cells depend on environmental lipids for proliferation when electron acceptors are limited

Abstract

Production of oxidized biomass, which requires regeneration of the cofactor NAD+, can be a proliferation bottleneck that is influenced by environmental conditions. However, a comprehensive quantitative understanding of metabolic processes that may be affected by NAD+ deficiency is currently missing. Here, we show that de novo lipid biosynthesis can impose a substantial NAD+ consumption cost in proliferating cancer cells. When electron acceptors are limited, environmental lipids become crucial for proliferation because NAD+ is required to generate precursors for fatty acid biosynthesis. We find that both oxidative and even net reductive pathways for lipogenic citrate synthesis are gated by reactions that depend on NAD+ availability. We also show that access to acetate can relieve lipid auxotrophy by bypassing the NAD+ consuming reactions. Gene expression analysis demonstrates that lipid biosynthesis strongly anti-correlates with expression of hypoxia markers across tumor types. Overall, our results define a requirement for oxidative metabolism to support biosynthetic reactions and provide a mechanistic explanation for cancer cell dependence on lipid uptake in electron acceptor-limited conditions, such as hypoxia.

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Fig. 1: Increased lipid synthesis results in increased oxygen consumption and is predicted to increase cellular demand for NAD+.
Fig. 2: Electron acceptor availability dictates proliferation rate in the absence of exogenous lipids.
Fig. 3: Electron acceptor limitation suppresses oxidative and reductive citrate production.
Fig. 4: Lipid starvation induces dephosphorylation of PDHA.
Fig. 5: Reductive tricarboxylic acid cycle flux is gated by electron acceptor availability.
Fig. 6: Complementation of electron transport chain with NADH oxidase stimulates reductive tricarboxylic acid cycle flux.
Fig. 7: Bypassing oxidative steps in fatty acid synthesis rescues proliferation in electron acceptor-deficient cells.
Fig. 8: Correlations between mRNA expression of fatty acid synthesis or fatty acid uptake genes and markers of tumor hypoxia.

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Source data are provided with this paper.

Code availability

All code is available at https://github.com/kostyat/Lipid_synthesis/.

References

  1. Hosios, A. M. et al. Amino acids rather than glucose account for the majority of cell mass in proliferating mammalian cells. Dev. Cell 36, 540–549 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Yao, C.-H. et al. Exogenous fatty acids are the preferred source of membrane lipids in proliferating fibroblasts. Cell Chem. Biol. 23, 483–493 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Jain, M. et al. Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation. Science 336, 1040 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Damaraju, V. L. et al. Nucleoside anticancer drugs: the role of nucleoside transporters in resistance to cancer chemotherapy. Oncogene 22, 7524–7536 (2003).

    Article  CAS  PubMed  Google Scholar 

  5. Muir, A., Danai, L. V. & Vander Heiden, M. G. Microenvironmental regulation of cancer cell metabolism: implications for experimental design and translational studies. Dis. Models Mech. 11, dmm035758–12 (2018).

    Article  Google Scholar 

  6. Sullivan, M. R. et al. Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability. Elife 8, e44235 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Vaupel, P., Kallinowski, F. & Okunieff, P. Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res. 49, 6449 (1989).

    CAS  PubMed  Google Scholar 

  8. Eales, K. L., Hollinshead, K. E. R. & Tennant, D. A. Hypoxia and metabolic adaptation of cancer cells. Oncogenesis 5, e190–8 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hu, J. et al. Heterogeneity of tumor-induced gene expression changes in the human metabolic network. Nat. Biotechnol. 31, 522–529 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Gui, D. Y. et al. Environment dictates dependence on mitochondrial complex I for NAD+ and aspartate Production and determines cancer cell sensitivity to metformin. Cell Metab. 24, 716–727 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sullivan, L. B. et al. Supporting aspartate biosynthesis is an essential function of respiration in proliferating cells. Cell 162, 552–563 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sullivan, L. B. et al. Aspartate is an endogenous metabolic limitation for tumour growth. Nat. Cell Biol. 20, 1–12 (2018).

    Article  Google Scholar 

  13. Birsoy, K. et al. An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell 162, 540–551 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Garcia-Bermudez, J. et al. Aspartate is a limiting metabolite for cancer cell proliferation under hypoxia and in tumours. Nat. Cell Biol. 20, 1–12 (2018).

    Google Scholar 

  15. Fernandez-de-Cossio-Diaz, J. & Vazquez, A. Limits of aerobic metabolism in cancer cells. Sci. Rep. 7, 13488 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Titov, D. V. et al. Complementation of mitochondrial electron transport chain by manipulation of the NAD+/NADH ratio. Science 352, 231–235 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Diehl, F. F., Lewis, C. A., Fiske, B. P. & Vander Heiden, M. G. Cellular redox state constrains serine synthesis and nucleotide production to impact cell proliferation. Nat. Metab. 1, 861–867 (2019).

  18. Bao, X. R. et al. Mitochondrial dysfunction remodels one-carbon metabolism in human cells. Elife 5, e10575 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Murphy, J. P. et al. The NAD+ salvage pathway supports PHGDH-driven serine biosynthesis. Cell Rep. 24, 2381–2391 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kim, W. et al. Polyunsaturated fatty acid desaturation is a mechanism for glycolytic NAD+ recycling. Cell Metab. 1–42 (2019).

  21. Price, N. C. & Stevens, L. Fundamentals of Enzymology (Oxford University Press, 2000).

  22. Los, D. A. & Murata, N. Structure and expression of fatty acid desaturases. Biochim. Biophys. Acta 1394, 3–15 (1998).

    Article  CAS  PubMed  Google Scholar 

  23. Park, S. H. et al. Phosphorylation-activity relationships of AMPK and acetyl-CoA carboxylase in muscle. J. Appl. Physiol. 92, 2475–2482 (2002).

    Article  CAS  PubMed  Google Scholar 

  24. Schulz, H. Beta oxidation of fatty acids. Biochim. Biophys. Acta 1081, 109–120 (1991).

    Article  CAS  PubMed  Google Scholar 

  25. Kamphorst, J. J. et al. Hypoxic and Ras-transformed cells support growth by scavenging unsaturated fatty acids from lysophospholipids. Proc. Natl Acad. Sci. USA 110, 8882 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ackerman, D. et al. Triglycerides promote lipid homeostasis during hypoxic stress by balancing fatty acid saturation. Cell Rep. 24, 2596–2605 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Bensaad, K. et al. Fatty acid uptake and lipid storage induced by HIF-1α contribute to cell growth and survival after hypoxia-reoxygenation. Cell Rep. 9, 349–365 (2014).

    Article  CAS  PubMed  Google Scholar 

  28. Jain, I. H. et al. Genetic screen for cell fitness in high or low oxygen highlights mitochondrial and lipid metabolism. Cell 181, 716–727 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Luengo, A. et al. Increased demand for NAD+ relative to ATP drives aerobic glycolysis. Mol. Cell 81, 691–707 (2021).

    Article  CAS  PubMed  Google Scholar 

  30. Harris, A. L. Hypoxia—a key regulatory factor in tumour growth. Nat. Rev. Cancer 2, 38–47 (2002).

    Article  CAS  PubMed  Google Scholar 

  31. Wise, D. R. et al. Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability. Proc. Natl Acad. Sci. USA 108, 19611–19616 (2011).

    Article  PubMed Central  Google Scholar 

  32. Metallo, C. M. et al. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature 481, 380–384 (2012).

    Article  CAS  Google Scholar 

  33. Mullen, A. R. et al. Reductive carboxylation supports growth in tumour cells with defective mitochondria. Nature 481, 385–388 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Dupuy, F. et al. PDK1-dependent metabolic reprogramming dictates metastatic potential in breast cancer. Cell Metab. 22, 577–589 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Duarte, N. C. et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl Acad. Sci. USA 104, 1777–1782 (2007).

    Article  PubMed Central  Google Scholar 

  36. Orth, J. D., Thiele, I. & Palsson, B. Ø. What is flux balance analysis? Nat. Biotechnol. 28, 245–248 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Jerby, L., Shlomi, T. & Ruppin, E. Computational reconstruction of tissue‐specific metabolic models: application to human liver metabolism. Mol. Syst. Biol. 6, 401 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zielinski, D. C. et al. Systems biology analysis of drivers underlying hallmarks of cancer cell metabolism. Sci. Rep. 7, 41241 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Saggerson, E. D. The regulation of glyceride synthesis in isolated white-fat cells. The effects of acetate, pyruvate, lactate, palmitate, electron-acceptors, uncoupling agents and oligomycin. Biochem. J. 128, 1069–1078 (1972).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Wise, E. M. Jr & Ball, E. G. Malic enzyme and lipogenesis. Proc. Natl Acad. Sci. USA 52, 1255–1263 (1964).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Liu, L. et al. Malic enzyme tracers reveal hypoxia-induced switch in adipocyte NADPH pathway usage. Nat. Chem. Biol. 12, 345–352 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hosios, A. M. & Vander Heiden, M. G. The redox requirements of proliferating mammalian cells. J. Biol. Chem. 293, 7490–7498 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. DeBerardinis, R. J. et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl Acad. Sci. USA 104, 19345 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Santos, C. R. & Schulze, A. Lipid metabolism in cancer. FEBS J. 279, 2610–2623 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Hosios, A., Li, Z., Lien, E. & Vander Heiden, M. Preparation of lipid-stripped serum for the study of lipid metabolism in cell culture. Bio. Protoc. 8, e2876 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Gameiro, P. A. et al. In vivo HIF-mediated reductive carboxylation is regulated by citrate levels and sensitizes VHL-deficient cells to glutamine deprivation. Cell Metab. 17, 372–385 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Kaplon, J. et al. A key role for mitochondrial gatekeeper pyruvate dehydrogenase in oncogene-induced senescence. Nature 498, 109–112 (2013).

    Article  CAS  PubMed  Google Scholar 

  48. Linn, T. C., Pettit, F. H. & Reed, L. J. α-keto acid dehydrogenase complexes, X. Regulation of the activity of pyruvate dehydrogenase complex from beef kidney mitochondria by phosphorylation and dephosphorylation. Proc. Natl Acad. Sci. USA 62, 234–241 (1969).

    Article  PubMed Central  Google Scholar 

  49. Schell, J. C. et al. A role for the mitochondrial pyruvate carrier as a repressor of the Warburg effect and colon cancer cell growth. Mol. Cell 56, 400–413 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Vacanti, N. M. et al. Regulation of substrate utilization by the mitochondrial pyruvate carrier. Mol. Cell 56, 425–435 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Yang, C. et al. Glutamine oxidation maintains the TCA cycle and cell survival during impaired mitochondrial pyruvate transport. Mol. Cell 56, 414–424 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bricker, D. K. et al. A mitochondrial pyruvate carrier required for pyruvate uptake in yeast, Drosophila and humans. Science 337, 96–100 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Herzig, S. et al. Identification and functional expression of the mitochondrial pyruvate carrier. Science 337, 93–96 (2012).

    Article  Google Scholar 

  54. Fendt, S.-M. et al. Reductive glutamine metabolism is a function of the α-ketoglutarate-to-citrate ratio in cells. Nat. Commun. 4, 2236 (2013).

    Article  PubMed  Google Scholar 

  55. Owen, M. R., Doran, E. & Halestrap, A. P. Evidence that metformin exerts its anti-diabetic effects through inhibition of complex 1 of the mitochondrial respiratory chain. Biochem. J. 348, 607–614 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Bücher, T. et al. State of oxidation–reduction and state of binding in the cytosolic NADH-system as disclosed by equilibration with extracellular lactate/pyruvate in hemoglobin-free perfused rat liver. Eur. J. Biochem. 27, 301–317 (1972).

    Article  PubMed  Google Scholar 

  57. Hung, Y. P., Albeck, J. G., Tantama, M. & Yellen, G. Imaging cytosolic NADH–NAD+ redox state with a genetically encoded fluorescent biosensor. Cell Metab. 14, 545–554 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hatzivassiliou, G. et al. ATP citrate lyase inhibition can suppress tumor cell growth. Cancer Cell 8, 311–321 (2005).

    Article  CAS  PubMed  Google Scholar 

  59. Faubert, B. et al. Lactate metabolism in human lung tumors. Cell 171, 358–371 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Hui, S. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115–118 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Zhao, Y. et al. In vivo monitoring of cellular energy metabolism using SoNar, a highly responsive sensor for NAD+/NADH redox state. Nat. Protoc. 11, 1345–1359 (2016).

    Article  CAS  PubMed  Google Scholar 

  62. Garcia, D. & Shaw, R. J. AMPK: mechanisms of cellular energy sensing and restoration of metabolic balance. Mol. Cell 66, 789–800 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Latasa, M. J., Moon, Y. S., Kim, K. H. & Sul, H. S. Nutritional regulation of the fatty acid synthase promoter in vivo: sterol regulatory element binding protein functions through an upstream region containing a sterol regulatory element. Proc. Natl Acad. Sci. USA 97, 10619–10624 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lewis, C. A. et al. SREBP maintains lipid biosynthesis and viability of cancer cells under lipid- and oxygen-deprived conditions and defines a gene signature associated with poor survival in glioblastoma multiforme. Oncogene 34, 5128–5140 (2015).

  65. Comerford, S. A. et al. Acetate dependence of tumors. Cell 159, 1591–1602 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Mashimo, T. et al. Acetate Is a bioenergetic substrate for human glioblastoma and brain metastases. Cell 159, 1603–1614 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Schug, Z. T. et al. Acetyl-CoA synthetase 2 promotes acetate utilization and maintains cancer cell growth under metabolic stress. Cancer Cell 27, 57–71 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Bulusu, V. et al. Acetate recapturing by nuclear acetyl-CoA synthetase 2 prevents loss of histone acetylation during oxygen and serum limitation. Cell Rep. 18, 647–658 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Liu, X. et al. Acetate production from glucose and coupling to mitochondrial metabolism in mammals. Cell 175, 502–513 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Röhrig, F. & Schulze, A. The multifaceted roles of fatty acid synthesis in cancer. Nat. Rev. Cancer 16, 732–749 (2016).

    Article  PubMed  Google Scholar 

  71. Jones, M. E., Lipmann, F., Hilz, H. & Lynen, F. On the enzymatic mechanism of coenzyme A acetylation with adenosine triphosphate and acetate. J. Am. Chem. Soc. 75, 3285–3286 (1953).

    Article  CAS  Google Scholar 

  72. Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Mense, S. M. et al. Gene expression profiling reveals the profound upregulation of hypoxia-responsive genes in primary human astrocytes. Physiol. Genomics 25, 435–449 (2006).

    Article  CAS  PubMed  Google Scholar 

  74. Horton, J. D., Goldstein, J. L. & Brown, M. S. SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver. J. Clin. Invest. 109, 1125–1131 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Davidson, S. M. et al. Environment impacts the metabolic dependencies of Ras-driven non-small cell lung cancer. Cell Metab. 23, 517–528 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Davidson, S. M. et al. Direct evidence for cancer-cell-autonomous extracellular protein catabolism in pancreatic tumors. Nat. Med. 23, 235–241 (2017).

    Article  CAS  PubMed  Google Scholar 

  77. Sullivan, M. R. et al. Increased serine synthesis provides an advantage for tumors arising in tissues where serine levels are limiting. Cell Metab. 29, 1410–1421 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Savino, A. M. et al. Metabolic adaptation of acute lymphoblastic leukemia to the central nervous system microenvironment depends on stearoyl-CoA desaturase. Nat. Cancer 1, 998–1009 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Jin, X. et al. A metastasis map of human cancer cell lines. Nature 588, 331–336 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Summons, R. E., Bradley, A. S., Jahnke, L. L. & Waldbauer, J. R. Steroids, triterpenoids and molecular oxygen. Philos. Trans. R. Soc. Lond. B Biol. Sci. 361, 951–968 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Maddocks, O. D. K. et al. Modulating the therapeutic response of tumours to dietary serine and glycine starvation. Nature 544, 372–376 (2017).

    Article  CAS  PubMed  Google Scholar 

  82. Li, L. et al. Identification of DHODH as a therapeutic target in small-cell lung cancer. Sci. Transl. Med. 11, eaaw7852 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Sousa, C. M. et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature 536, 479–483 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Parker, S. J. et al. Selective alanine transporter utilization creates a targetable metabolic niche in pancreatic cancer. Cancer Discov. 10, 1018–1037 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Hsueh, E. C. et al. Deprivation of arginine by recombinant human arginase in prostate cancer cells. J. Hematol. Oncol. 5, 17 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the members of the D.V. and M.G.V.H. laboratories for helpful discussions. The results published here are in part based upon data generated by the TCGA Research Network. This work was supported by the National Institutes of Health (NIH) grants R01CA201276 (to D.V. and M.G.V.H.) and T32GM007367 (to B.W.J.), the MD-PhD program at Columbia University (to B.W.J.) and NIH grants U54CA209997 (to P.D., K.T., B.W.J. and D.V.) and T32GM007287 (Z.L. and K.L.A.). E.C.L. is a Damon Runyon Fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2299-17). A.M.H. was supported by an HHMI International Student Fellowship. J.C.R. is supported by the Harvard/MIT MD-PhD Program NIH award T32GM007753. L.B.S. acknowledges support from a Pathway to Independence award from the NIH (K99CA218679/R00CA218679). E.F.G. was supported by the MIT MSRP program. M.G.V.H. also acknowledges support from the Lustgarten Foundation, SU2C, the Ludwig Center at MIT, the NCI (R35CA242379 and P30CA014051), the MIT Center for Precision Cancer Medicine, the Emerald Foundation and a Faculty Scholar award from HHMI. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the NIH.

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Authors and Affiliations

Authors

Contributions

B.W.J, Z.L., P.D.D., M.G.V.H. and D.V. conceived the study. Z.L., B.W.J., P.D.D., K.T., M.G.V.H. and D.V. wrote the manuscript. B.W.J., K.T. and P.D.D. developed and executed the computation analysis of global metabolic flux and NAD+ costs analysis. Z.L., A.M.H., E.F.G., K.L.A. and L.B.S. performed proliferation assays. Z.L. performed oxygen consumption assays. Z.L. and E.C.L. performed serum delipidation. Z.L. performed kinetic isotope tracing and lipid synthesis assays. Z.L. and J.C.R. performed immunoblot assays. Z.L and A.M.W. performed NAD+ measurement assays. Z.L. performed mass spectrometry and analysis for metabolites. Z.L. generated cell lines used for this study. B.W.J., K.T. and P.D.D. performed TCGA analysis of gene expression correlations. M.G.V.H. and D.V. supervised the project.

Corresponding authors

Correspondence to Matthew G. Vander Heiden or Dennis Vitkup.

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Competing interests

A.M.W. is a current employee of Revitope. M.G.V.H. is a consultant and scientific advisor for Agios Pharmaceuticals, iTeos Therapeutics, Droia Ventures, Faeth Therapeutics, Sage Therapeutics and Auron Therapeutics. All other authors declare no competing interests.

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Nature Metabolism thanks Navdeep Chandel and the other, anonymous, reviewers for their contribution to the peer review of this work. Primary Handling Editors: Alfredo Gimenez-Cassina and George Caputa, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Effects of lipid depletion and fatty acid synthesis inhibition on cell proliferation.

a, Cell culture media was prepared with delipidated serum, and then reconstituted with 1% Lipid Mixture (2 μg/ml arachidonic and 10 μg/ml each linoleic, linolenic, myristic, oleic, palmitic and stearic acid, and 0.22 mg/ml cholesterol) (+lipids) or vehicle (–lipids). Proliferation rates of HeLa cells cultured in media +lipids or –lipids without and with the FASN inhibitor GSK2194069 (0.3 µM) as indicated (n = 3 per condition from a representative experiment). b, Relative palmitate synthesis rates of HeLa cells cultured in media +lipids or –lipids without and with GSK2194069 (0.3 µM), or without and with phenformin (100 µM) as indicated (n = 3 per condition from a representative experiment). c, Oxygen consumption rate (OCR) of HeLa cells cultured in media +lipids or –lipids as indicated (n = 10 per condition from a representative experiment). d, OCR of H1299 cells cultured in media +lipids or –lipids as indicated (n = 10 per condition from a representative experiment). e, OCR of H1299 cells cultured in –lipid and acutely treated with 1% Lipid Mixture or Tween-80 and Pluronic F-68 equivalent to what is present in 1% Lipid Mixture (n = 10 per condition from a representative experiment). f, OCR of HeLa cell cultures in media +lipids or –lipids acutely treated with the SCD1 inhibitor A939572 (1 µM) and rotenone (1.5 µM) + antimycin A (1.5 µM) as indicated (n = 8 per condition from a representative experiment). All bar charts and line graphs show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

Source data

Extended Data Fig. 2 Electron acceptor availability dictates proliferation rate in the absence of exogenous lipids.

a, Proliferation rates of H1299, PANC-1, AL1376, A549, and 143B cells cultured in media +lipids or –lipids in normoxia (21% oxygen) or hypoxia (0.5% or 1% oxygen), without or with pyruvate (1 mM, P) and/or lactate (10 mM, L) as indicated (n = 3 per condition from a representative experiment). b, Proliferation rate of HeLa cells cultured in media +lipids or –lipids with a titration of phenformin (Complex I inhibitor), rotenone (Complex I inhibitor), or antimycin A (Complex III inhibitor) as indicated (n = 3 per condition from a representative experiment). c, Proliferation rate of H1299 cells cultured in media +lipids or –lipids with a titration of phenformin, rotenone, or antimycin A as indicated (n = 3 per condition from a representative experiment). d, Proliferation rates of HeLa cells cultured in media containing the indicated doses of Phenformin with dialyzed fetal bovine serum that has been untreated, delipidated and reconstituted with 1% Lipid Mixture (2 μg/ml arachidonic and 10 μg/ml each linoleic, linolenic, myristic, oleic, palmitic and stearic acid, and 0.22 mg/ml cholesterol), or delipidated and reconstituted with Tween-80 and Pluronic F-68 equivalent to what is present in 1% Lipid Mixture (n = 3 per condition from a representative experiment). e, Proliferation rates of HeLa cells cultured in media –lipids treated with phenformin (100 µM), when indicated, and supplemented with either 1% Lipid Mixture or the equivalent amounts of oleate (O) and/or mevalonate (M) found in 1% Lipid Mixture (n = 3 per condition from a representative experiment). f, Proliferation rates of H1299 cells cultured in media –lipids treated with phenformin (10 µM), when indicated, and supplemented with either 1% Lipid Mixture or the equivalent amounts of oleate (O) and/or mevalonate (M) found in 1% Lipid Mixture (n = 3 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

Source data

Extended Data Fig. 3 Orthogonal mechanisms of electron acceptor regeneration restore lipid synthesis under ETC inhibition.

a, Proliferation rates of H1299 cells cultured in media +lipids or –lipids, without or with phenformin (10 µM), pyruvate (1 mM, P), and/or lactate (10 mM, L) as indicated (n = 3 per condition from a representative experiment). b, Proliferation rates of H1299 cells cultured in media +lipids or –lipids without or with antimycin A (15 nM), pyruvate (1 mM, P), and/or lactate (10 mM, L) as indicated (n = 3 per condition from a representative experiment). c, Relative NAD+ /NADH ratio in H1299 cells cultured in media +lipids or –lipids without or with phenformin (10 µM), pyruvate (1 mM, P), and/or lactate (10 mM, L) as indicated (n = 3 per condition from a representative experiment). d, Proliferation rates of HeLa cells cultured in medium –lipids without or with 1% Lipid Mixture, phenformin (100 µM), and/or pyruvate (1 mM, P), as indicated (n = 3 per condition from a representative experiment). e, Proliferation rates of H1299 cells cultured in medium –lipids without or with 1% Lipid Mixture, phenformin (10 µM), and/or pyruvate (1 mM, P), as indicated (n = 3 per condition from a representative experiment). f, Proliferation rates of HeLa cells cultured in medium –lipids without or with 1% Lipid Mixture, phenformin (100 µM), and/or α-ketobutyrate (1 mM, αKB), as indicated (n = 3 per condition from a representative experiment). g, Proliferation rates of HeLa cells cultured in media +lipids or –lipids without or with phenformin (100 µM), pyruvate (1 mM, P), and/or alpha-ketobutyrate (1 mM, Ak) as indicated (n = 3 per condition from a representative experiment). h, Relative proliferation rates of HeLa cells expressing empty vector (EV) or lbNOX cultured in –lipids with phenformin (100 µM) as indicated. Data were normalized to HeLa-EV cells (n = 3 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

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Extended Data Fig. 4 Effects of aspartate on proliferation in the absence of lipids.

a, Proliferation rates of HeLa cells cultured in media +lipids or –lipids, without or with phenformin (100 µM), and/or aspartic acid (10 mM or 20 mM) as indicated (n = 3 per condition from a representative experiment). b, Proliferation rates of HeLa cells cultured in media +lipids or –lipids, without or with phenformin (100 µM), and/or sodium aspartate (10 mM) as indicated (n = 3 per condition from a representative experiment). c, Proliferation rates of H1299 cells cultured in media +lipids or –lipids, without or with phenformin (10 µM), and/or sodium aspartate (10 mM) as indicated (n = 3 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

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Extended Data Fig. 5 Effects of exogenous metabolites on ACC phosphorylation.

a, Representative immunoblot of total ACC and ACC serine 79 phosphorylation in HeLa cells cultured for 24 hours in media +lipids or –lipids without or with phenformin (100 µM), pyruvate (1 mM, Pyr), lactate (10 mM, Lac), and/or acetate (200 µM, Ac) as indicated. b, (top) Representative immunoblot of FASN, phosphorylated PDHA (Serine 293), total PDHA, and vinculin in HeLa or H1299 cells overexpressing eGFP or constitutively mature SREBP1a. (bottom) Representative immunoblot of phosphorylated PDHA (Serine 293) and Vinculin in HeLa cultured in –lipids for 24hrs, treated with vehicle, phenformin, antimycin, pyruvate, and/or alpha-ketobutyrate at the indicated doses. All experiments were repeated three times or more.

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Extended Data Fig. 6 Inhibition of mitochondrial electron transport decreases intracellular citrate levels.

a, Relative fractional distribution of citrate isotopomers in HeLa cells cultured for 24 hours in media +lipids or –lipids with U-13C-Glutamine, without and with phenformin (100 µM), pyruvate (1 mM, Pyr), and/or lactate (10 mM, Lac) as indicated (n = 3 per condition from a representative experiment). b, Normalized intracellular ratio of αKG to citrate in HeLa cells cultured in +lipids or –lipids with or without phenformin (100 µM). (n = 6 per condition from a representative experiment). c, Isotopomer distribution of total levels of intracellular citrate in HeLa cells cultured for 24 hours in media +lipids or –lipids with U-13C-Glutamine, without and with phenformin (100 µM), pyruvate (1 mM, Pyr), and/or lactate (10 mM, Lac) as indicated (n = 3 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more. (n = 3 per condition from a representative experiment).

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Extended Data Fig. 7 Bypassing oxidative steps in fatty acid synthesis rescues proliferation in electron acceptor-deficient cells.

a, Proliferation rates of H1299 cells cultured in media +lipids or –lipids without or with phenformin (10 µM) and/or acetate (200 µM) as indicated (n = 3 per condition from a representative experiment). b, Proliferation rates of H1299 cells cultured in media +lipids or –lipids without or with antimycin A (15 nM) and/or acetate (200 µM) as indicated (n = 3 per condition from a representative experiment). c, Relative NAD+ /NADH ratio in H1299 cells cultured in media +lipids or –lipids without or with phenformin (10 µM) and/or acetate (200 µM) as indicated (n = 3 per condition from a representative experiment). d, Proliferation rates of H1299 cells cultured in media +lipids or –lipids in normoxia (21% oxygen), hypoxia (1% oxygen), and/or acetate (200 µM) as indicated. Data from the first four conditions are the same as those presented in Extended Data Fig. 2a. (n = 3 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

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Extended Data Fig. 8 Effect of exogenous acetate on levels of TCA cycle intermediates.

a, Relative intracellular alpha-ketoglutarate (αKG) levels in HeLa cells cultured for 24 hours in medium –lipids without or with phenformin (100 µM) and/or acetate (200 µM) as indicated (n = 6 per condition from a representative experiment). b, Relative intracellular succinate levels in HeLa cells cultured for 24 hours in medium –lipids without or with phenformin (100 µM) and/or acetate (200 µM) as indicated (n = 6 per condition from a representative experiment). c, Relative intracellular fumarate levels in HeLa cells for 24 hours in medium –lipids without or with phenformin (100 µM) and/or acetate (200 µM) (n = 6 per condition from a representative experiment). d, Relative intracellular malate levels in HeLa cells cultured for 24 hours in medium –lipids without or with phenformin (100 µM) and/or acetate (200 µM) (n = 6 per condition from a representative experiment). All bar charts show means with error bars representing ± s.d. Unpaired Student’s t-test was performed where statistics are shown. All experiments were repeated three times or more.

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Extended Data Fig. 9 Gene expression correlations between lipid metabolism genes and hypoxia signature genes.

a, Pearson correlation coefficients and corresponding p-values, for each of 34 different tumor types, between expression of hypoxia signature genes and expression of fatty acid synthesis genes (third column), lipid uptake genes (fourth column), and beta-oxidation genes (fifth column). Insignificant correlations, based on the 1% FDR cutoff, are marked in red. Depicted p-values on Pearson correlation coefficients are calculated using two-sided Student’s t-test, and significance threshold is adjusted for multiple comparisons at 1% FDR using the Benjamini-Hochberg method. b, Scatter plots showing, for each considered tumor type, the correlation between the tumor hypoxia score and expression of genes participating in fatty acid synthesis, with dots representing individual TCGA samples. c, Scatter plots showing, for each considered tumor type, the correlation between the tumor hypoxia score and expression of genes participating in lipid uptake, with dots representing individual TCGA samples.

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Extended Data Fig. 10 Gene expression correlations between lipid metabolism genes and hypoxia signature genes.

a, Correlation of mRNA expression of SREBF1/2 and of gene markers of fatty acid synthesis within individual hypoxia score quintiles. Pearson’s correlation coefficients were calculated for each of five equally-sized bins of TCGA samples, corresponding to five hypoxia score quintiles, for SREBF1 (left) and SREBF2 (right). TCGA samples were sorted into quintiles based on their hypoxia scores from the lowest hypoxia score (quintile 1) to the highest score (quintile 5). b, Density plot of the correlation between the average mRNA expression of gene markers of tumor hypoxia and mRNA expression of Stearoyl-CoA desaturase 1 (SCD1) gene. Density counts represent the number of TCGA samples with the corresponding expression values, with red color representing high-density regions and blue color representing low-density regions, and the Pearson’s correlation coefficient (R) and the p-value are shown in the figure. Depicted p-value on Pearson correlation coefficients is calculated using two-sided Student’s t-test.

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Li, Z., Ji, B.W., Dixit, P.D. et al. Cancer cells depend on environmental lipids for proliferation when electron acceptors are limited. Nat Metab 4, 711–723 (2022). https://doi.org/10.1038/s42255-022-00588-8

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