Skip to main content

Advertisement

SpringerLink
Log in

Cancer cell metabolic plasticity in migration and metastasis

  • Review
  • Published:
Clinical & Experimental Metastasis Aims and scope Submit manuscript

Abstract

Metabolic reprogramming is a hallmark of cancer metastasis in which cancer cells manipulate their metabolic profile to meet the dynamic energetic requirements of the tumor microenvironment. Though cancer cell proliferation and migration through the extracellular matrix are key steps of cancer progression, they are not necessarily fueled by the same metabolites and energy production pathways. The two main metabolic pathways cancer cells use to derive energy from glucose, glycolysis and oxidative phosphorylation, are preferentially and plastically utilized by cancer cells depending on both their intrinsic metabolic properties and their surrounding environment. Mechanical factors in the microenvironment, such as collagen density, pore size, and alignment, and biochemical factors, such as oxygen and glucose availability, have been shown to influence both cell migration and glucose metabolism. As cancer cells have been identified as preferentially utilizing glycolysis or oxidative phosphorylation based on heterogeneous intrinsic or extrinsic factors, the relationship between cancer cell metabolism and metastatic potential is of recent interest. Here, we review current in vitro and in vivo findings in the context of cancer cell metabolism during migration and metastasis and extrapolate potential clinical applications of this work that could aid in diagnosing and tracking cancer progression in vivo by monitoring metabolism. We also review current progress in the development of a variety of metabolically targeted anti-metastatic drugs, both in clinical trials and approved for distribution, and highlight potential routes for incorporating our recent understanding of metabolic plasticity into therapeutic directions. By further understanding cancer cell energy production pathways and metabolic plasticity, more effective and successful clinical imaging and therapeutics can be developed to diagnose, target, and inhibit metastasis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

ATP:

Adenosine tri-phosphate

Cav1:

Caveolin-1

TCA:

Citric acid cycle

CAT:

Collective to amoeboid transition

EMT:

Epithelial to mesenchymal transition

ECM:

Extracellular matrix

FLIM:

Fluorescence lifetime imaging

GLUT1:

Glucose transporter 1

HIF-1:

Hypoxia-inducible factor-1

IDH-2:

Isocitrate dehydrogenase 2

LDH-A:

Lactate dehydrogenase A

mTOR:

Mammalian target of rapamycin

MMP:

Matrix metalloproteinase

MAT:

Mesenchymal to amoeboid transition

MCT4:

Monocarboxylate transporter 4

NAD:

Nicotinamide adenine dinucleotide

NADH:

Nicotinamide adenine dinucleotide+hydrogen

OxPhos:

Oxidative phosphorylation

PCG-1α:

Peroxisome proliferator-associated receptor gamma, coactivator 1-alpha

PET:

Positron emission tomography

PDH1:

Pyruvate dehydrogenase 1

PDK1:

Pyruvate hydrogenase kinase 1

ROS:

Reactive oxygen species

TME:

Tumor microenvironment

TNBC:

Triple negative breast cancer

18-FDG:

18-Fluorodeoxyglucose

References

  1. Hapach LA, Mosier JA, Wang W, Reinhart-King CA (2019) Engineered models to parse apart the metastatic cascade. NPJ Precis Oncol 3:1–8

    Google Scholar 

  2. Zanotelli MR et al (2019) Energetic costs regulated by cell mechanics and confinement are predictive of migration path during decision-making. Nat Commun 10:1–12

    CAS  Google Scholar 

  3. Zanotelli MR et al (2018) Regulation of ATP utilization during metastatic cell migration by collagen architecture. MBoC 29:1–9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324:1029–1033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Lunt SY, Vander Heiden MG (2011) Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Ann Rev Cell Dev Biol 27:441–464

    Article  CAS  Google Scholar 

  6. Icard P et al (2018) How the Warburg effect supports aggressiveness and drug resistance of cancer cells? Drug Resist Updat 38:1–11

    Article  PubMed  Google Scholar 

  7. Liberti MV, Locasale JW (2016) The Warburg effect: how does it benefit cancer cells? Trends Biochem Sci 41:211–218

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sousa B, Pereira J, Paredes J (2019) The crosstalk between cell adhesion and cancer metabolism. Int J Mol Sci 20:1933

    Article  CAS  PubMed Central  Google Scholar 

  9. Lee SH, Dominguez R (2010) Regulation of actin cytoskeleton dynamics in cells. Mol Cells 29:311–325

    Article  CAS  PubMed  Google Scholar 

  10. Suzuki R, Hotta K, Oka K (2015) Spatiotemporal quantification of subcellular ATP levels in a single HeLa cell during changes in morphology. Sci Rep. https://doi.org/10.1038/srep16874

    Article  PubMed  PubMed Central  Google Scholar 

  11. Passam F et al (2018) Mechano-redox control of integrin de-adhesion. Elife. https://doi.org/10.7554/eLife.34843

    Article  PubMed  PubMed Central  Google Scholar 

  12. Fedotov S, Iomin A (2007) Migration and proliferation dichotomy in tumor-cell invasion. Phys Rev Lett 98:118101

    Article  PubMed  CAS  Google Scholar 

  13. Giese A et al (1996) Dichotomy of astrocytoma migration and proliferation. Int J Cancer 67:275–282

    Article  CAS  PubMed  Google Scholar 

  14. Zheng P-P, Severijnen L-A, van der Weiden M, Willemsen R, Kros JM (2009) Cell proliferation and migration are mutually exclusive cellular phenomena in vivo: implications for cancer therapeutic strategies. Cell Cycle 8:950–951

    Article  CAS  PubMed  Google Scholar 

  15. Garay T et al (2013) Cell migration or cytokinesis and proliferation?—Revisiting the “go or grow” hypothesis in cancer cells in vitro. Exp Cell Res 319:3094–3103

    Article  CAS  PubMed  Google Scholar 

  16. Lewis CA et al (2014) Tracing compartmentalized NADPH metabolism in the cytosol and mitochondria of mammalian cells. Mol Cell 55:253–263

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Webster KA (2003) Evolution of the coordinate regulation of glycolytic enzyme genes by hypoxia. J Exp Biol 206:2911–2922

    Article  CAS  PubMed  Google Scholar 

  18. Hay N (2016) Reprogramming glucose metabolism in cancer: can it be exploited for cancer therapy? Nat Rev Cancer 16:635–649

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ge T et al (2020) The role of the pentose phosphate pathway in diabetes and cancer. Front. Endocrinol 11:365

    Article  Google Scholar 

  20. Cluntun AA, Lukey MJ, Cerione RA, Locasale JW (2017) Glutamine metabolism in cancer: understanding the heterogeneity. Trends Cancer 3:169–180

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Paudel BB, Quaranta V (2019) Metabolic plasticity meets gene regulation. Proc Natl Acad Sci U S A 116:3370–3372

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Koczula KM et al (2016) Metabolic plasticity in CLL: adaptation to the hypoxic niche. Leukemia 30:65–73

    Article  CAS  PubMed  Google Scholar 

  23. Jia D et al (2019) Elucidating cancer metabolic plasticity by coupling gene regulation with metabolic pathways. Proc Natl Acad Sci USA 116:3909–3918

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Warburg O (1925) The metabolism of carcinoma cells. J Cancer Res 9:148–163

    Article  CAS  Google Scholar 

  25. Ward PS, Thompson CB (2012) Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell 21:297–308

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Vaupel P, Schmidberger H, Mayer A (2019) The Warburg effect: essential part of metabolic reprogramming and central contributor to cancer progression. Int J Radiat Biol 95:912–919

    Article  CAS  PubMed  Google Scholar 

  27. Elstrom RL et al (2004) Akt stimulates aerobic glycolysis in cancer cells. Cancer Res 64:3892–3899

    Article  CAS  PubMed  Google Scholar 

  28. Shim H et al (1997) c-Myc transactivation of LDH-A: implications for tumor metabolism and growth. Proc Natl Acad Sci U S A 94:6658–6663

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. van Zijl F, Krupitza G, Mikulits W (2011) Initial steps of metastasis: cell invasion and endothelial transmigration. Mutat Res Rev Mutat Res 728:23–34

    Article  CAS  Google Scholar 

  30. Giampieri S et al (2009) Localized and reversible TGFbeta signalling switches breast cancer cells from cohesive to single cell motility. Nat Cell Biol 11:1287–1296

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. te Boekhorst V et al (2020) Calpain-2 regulates hypoxia/HIF-induced amoeboid reprogramming and metastasis. bioRxiv. https://doi.org/10.1101/2020.01.06.892497

    Article  Google Scholar 

  32. Chung Y-C et al (2016) Rab11 collaborates E-cadherin to promote collective cell migration and indicates a poor prognosis in colorectal carcinoma. Eur J Clin Invest 46:1002–1011

    Article  CAS  PubMed  Google Scholar 

  33. Friedl P, Wolf K (2003) Tumour-cell invasion and migration: diversity and escape mechanisms. Nat Rev Cancer 3:362–374

    Article  CAS  PubMed  Google Scholar 

  34. Emad A et al (2020) Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature. Breast Cancer Res 22:74

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Tolde O et al (2018) Quantitative phase imaging unravels new insight into dynamics of mesenchymal and amoeboid cancer cell invasion. Sci Rep 8:12020

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Parri M, Taddei ML, Bianchini F, Calorini L, Chiarugi P (2009) EphA2 reexpression prompts invasion of melanoma cells shifting from mesenchymal to amoeboid-like motility style. Cancer Res 69:2072–2081

    Article  CAS  PubMed  Google Scholar 

  37. Haga H, Irahara C, Kobayashi R, Nakagaki T, Kawabata K (2005) Collective movement of epithelial cells on a collagen gel substrate. Biophys J 88:2250–2256

    Article  CAS  PubMed  Google Scholar 

  38. De Donatis A, Ranaldi F, Cirri P (2010) Reciprocal control of cell proliferation and migration. Cell Commun Signal 8:20

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Hecht I et al (2015) Tumor invasion optimization by mesenchymal-amoeboid heterogeneity. Sci Rep 5:10622

    Article  PubMed  PubMed Central  Google Scholar 

  40. Zhang J et al (2019) Energetic regulation of coordinated leader–follower dynamics during collective invasion of breast cancer cells. PNAS 116:7867–7872

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. LeBleu VS et al (2014) PGC-1α mediates mitochondrial biogenesis and oxidative phosphorylation in cancer cells to promote metastasis. Nat Cell Biol 16:992–1003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Commander R et al (2020) Subpopulation targeting of pyruvate dehydrogenase and GLUT1 decouples metabolic heterogeneity during collective cancer cell invasion. Nat Commun 11:1–17

    Article  CAS  Google Scholar 

  43. Carmeliet P, De Smet F, Loges S, Mazzone M (2009) Branching morphogenesis and antiangiogenesis candidates: tip cells lead the way. Nat Rev Clin Oncol 6:315–326

    Article  CAS  PubMed  Google Scholar 

  44. Friedl P, Alexander S (2011) Cancer invasion and the microenvironment: plasticity and reciprocity. Cell 147:992–1009

    Article  CAS  PubMed  Google Scholar 

  45. Polacheck WJ, Zervantonakis IK, Kamm RD (2013) Tumor cell migration in complex microenvironments. Cell Mol Life Sci 70:1335–1356

    Article  CAS  PubMed  Google Scholar 

  46. Lintz M, Muñoz A, Reinhart-King CA (2017) The mechanics of single cell and collective migration of tumor cells. J Biomech Eng 139:0210051–0210059

    Article  PubMed Central  Google Scholar 

  47. Friedl P, Wolf K (2010) Plasticity of cell migration: a multiscale tuning model. J Cell Biol 188:11–19

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Aiello NM et al (2018) EMT subtype influences epithelial plasticity and mode of cell migration. Dev Cell 45:681-695.e4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wang Y, Zhou BP (2013) Epithelial-mesenchymal transition–-A hallmark of breast cancer metastasis. Cancer Hallm 1:38–49

    Article  PubMed  PubMed Central  Google Scholar 

  50. Vincent-Salomon A, Thiery JP (2003) Host microenvironment in breast cancer development: epithelial–mesenchymal transition in breast cancer development. Breast Cancer Res 5:101–106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Shiraishi T et al (2015) Glycolysis is the primary bioenergetic pathway for cell motility and cytoskeletal remodeling in human prostate and breast cancer cells. Oncotarget 6:130–143

    Article  PubMed  Google Scholar 

  52. Berx G, Raspé E, Christofori G, Thiery JP, Sleeman JP (2007) Pre-EMTing metastasis? Recapitulation of morphogenetic processes in cancer. Clin Exp Metastasis 24:587–597

    Article  CAS  PubMed  Google Scholar 

  53. Kim NH et al (2017) Snail reprograms glucose metabolism by repressing phosphofructokinase PFKP allowing cancer cell survival under metabolic stress. Nat Commun 8:14374

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Cooke VG et al (2012) Pericyte depletion results in hypoxia-associated epithelial-to-mesenchymal transition and metastasis mediated by met signaling pathway. Cancer Cell 21:66–81

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Yang M-H et al (2008) Direct regulation of TWIST by HIF-1alpha promotes metastasis. Nat Cell Biol 10:295–305

    Article  CAS  PubMed  Google Scholar 

  56. Mosier JA et al (2019) Extent of cell confinement in microtracks affects speed and results in differential matrix strains. Biophys J 117:1692–1701

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lee IJ et al (2006) Hepatocellular carcinoma model cell lines with two distinct migration modes. Biochem Biophys Res Commun 346:1217–1227

    Article  CAS  PubMed  Google Scholar 

  58. Huang B et al (2014) The three-way switch operation of Rac1/RhoA GTPase-based circuit controlling amoeboid-hybrid-mesenchymal transition. Sci Rep 4:6449

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Holle AW et al (2019) Cancer cells invade confined microchannels via a self-directed mesenchymal-to-amoeboid transition. Nano Lett 19:2280–2290

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Čermák V et al (2020) High-throughput transcriptomic and proteomic profiling of mesenchymal-amoeboid transition in 3D collagen. Sci Data 7:160

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Thejer BM et al (2020) PGRMC1 phosphorylation affects cell shape, motility, glycolysis, mitochondrial form and function, and tumor growth. BMC Mol Cell Biol 21:24

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Anesti V, Scorrano L (2006) The relationship between mitochondrial shape and function and the cytoskeleton. Biochim Biophys Acta 1757:692–699

    Article  CAS  PubMed  Google Scholar 

  63. Bartolák-Suki E, Imsirovic J, Nishibori Y, Krishnan R, Suki B (2017) Regulation of mitochondrial structure and dynamics by the cytoskeleton and mechanical factors. Int J Mol Sci 18:1812

    Article  PubMed Central  CAS  Google Scholar 

  64. Ali MH, Pearlstein DP, Mathieu CE, Schumacker PT (2004) Mitochondrial requirement for endothelial responses to cyclic strain: implications for mechanotransduction. Am J Physiol Lung Cell Mol Physiol 287:486–496

    Article  Google Scholar 

  65. Kondo H et al (2021) Single-cell resolved imaging reveals intra-tumor heterogeneity in glycolysis, transitions between metabolic states, and their regulatory mechanisms. Cell Rep 34:108750

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Kelley LC et al (2019) Adaptive F-actin polymerization and localized ATP production drive basement membrane invasion in the absence of MMPs. Dev Cell 48:313-328.e8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Cunniff B, McKenzie AJ, Heintz NH, Howe AK (2016) AMPK activity regulates trafficking of mitochondria to the leading edge during cell migration and matrix invasion. MBoC 27:2662–2674

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Porporato PE et al (2014) A mitochondrial switch promotes tumor metastasis. Cell Rep 8:754–766

    Article  CAS  PubMed  Google Scholar 

  69. Yoshida S et al (2013) Molecular chaperone TRAP1 regulates a metabolic switch between mitochondrial respiration and aerobic glycolysis. PNAS 110:E1604–E1612

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Krakhmal NV, Zavyalova MV, Denisov EV, Vtorushin SV, Perelmuter VM (2015) Cancer invasion: patterns and mechanisms. Acta Nat 7:17–28

    Article  CAS  Google Scholar 

  71. Duda DG et al (2010) Malignant cells facilitate lung metastasis by bringing their own soil. Proc Natl Acad Sci USA. https://doi.org/10.1073/pnas.1016234107

    Article  PubMed  PubMed Central  Google Scholar 

  72. Klameth L et al (2017) Small cell lung cancer: model of circulating tumor cell tumorospheres in chemoresistance. Sci Rep 7:5337

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  73. Plou J et al (2018) From individual to collective 3D cancer dissemination: roles of collagen concentration and TGF-β. Sci Rep 8:12723

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Aceto N et al (2014) Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 158:1110–1122

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Wu J-S et al (2019) Cathepsin B defines leader cells during the collective invasion of salivary adenoid cystic carcinoma. Int J Oncol 54:1233–1244

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Wolf K et al (2007) Multi-step pericellular proteolysis controls the transition from individual to collective cancer cell invasion. Nat Cell Biol 9:893–904

    Article  CAS  PubMed  Google Scholar 

  77. Glentis A et al (2017) Cancer-associated fibroblasts induce metalloprotease-independent cancer cell invasion of the basement membrane. Nat Commun 8:924

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Shih W, Yamada S (2012) N-cadherin as a key regulator of collective cell migration in a 3D environment. Cell Adhes Migr 6:513–517

    Article  Google Scholar 

  79. Elisha Y, Kalchenko V, Kuznetsov Y, Geiger B (2018) Dual role of E-cadherin in the regulation of invasive collective migration of mammary carcinoma cells. Sci Rep 8:4986

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. De Bock K et al (2013) Role of PFKFB3-driven glycolysis in vessel sprouting. Cell 154:651–663

    Article  PubMed  CAS  Google Scholar 

  81. Cruys B et al (2016) Glycolytic regulation of cell rearrangement in angiogenesis. Nat Commun 7:12240

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Xie J et al (2014) Beyond Warburg effect—dual metabolic nature of cancer cells. Sci Rep 4:4927

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  83. Lu W et al (2012) Novel role of NOX in supporting aerobic glycolysis in cancer cells with mitochondrial dysfunction and as a potential target for cancer therapy. PLoS Biol 10:e1001326

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Payen VL, Porporato PE, Baselet B, Sonveaux P (2016) Metabolic changes associated with tumor metastasis, part 1: tumor pH, glycolysis and the pentose phosphate pathway. Cell Mol Life Sci 73:1333–1348

    Article  CAS  PubMed  Google Scholar 

  85. Busco G et al (2010) NHE1 promotes invadopodial ECM proteolysis through acidification of the peri-invadopodial space. FASEB J 24:3903–3915

    Article  CAS  PubMed  Google Scholar 

  86. Schwager SC, Taufalele PV, Reinhart-King CA (2019) Cell-cell mechanical communication in cancer. Cel Mol Bioeng 12:1–14

    Article  Google Scholar 

  87. Bear JE, Haugh JM (2014) Directed migration of mesenchymal cells: where signaling and the cytoskeleton meet. Curr Opin Cell Biol 0:74–82

    Article  CAS  PubMed Central  Google Scholar 

  88. Walker C, Mojares E, del Río Hernández A (2018) Role of extracellular matrix in development and cancer progression. Int J Mol Sci 19:3028

    Article  PubMed Central  CAS  Google Scholar 

  89. Grassian AR, Coloff JL, Brugge JS (2011) Extracellular matrix regulation of metabolism and implications for tumorigenesis. Cold Spring Harb Symp Quant Biol 76:313–324

    Article  CAS  PubMed  Google Scholar 

  90. Mah EJ, Lefebvre AEYT, McGahey GE, Yee AF, Digman MA (2018) Collagen density modulates triple-negative breast cancer cell metabolism through adhesion-mediated contractility. Sci Rep 8:17094

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  91. Weber GF (2016) Time and circumstances: cancer cell metabolism at various stages of disease progression. Front Oncol. https://doi.org/10.3389/fonc.2016.00257

    Article  PubMed  PubMed Central  Google Scholar 

  92. Morris BA et al (2016) Collagen matrix density drives the metabolic shift in breast cancer cells. EBioMedicine 13:146–156

    Article  PubMed  PubMed Central  Google Scholar 

  93. Haeger A, Krause M, Wolf K, Friedl P (2014) Cell jamming: collective invasion of mesenchymal tumor cells imposed by tissue confinement. Biochim Biophys Acta 1840:2386–2395

    Article  CAS  PubMed  Google Scholar 

  94. Wolf K et al (2009) Collagen-based cell migration models in vitro and in vivo. Semin Cell Dev Biol 20:931–941

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Alexander S, Koehl GE, Hirschberg M, Geissler EK, Friedl P (2008) Dynamic imaging of cancer growth and invasion: a modified skin-fold chamber model. Histochem Cell Biol 130:1147–1154

    Article  CAS  PubMed  Google Scholar 

  96. Weigelin B, Bakker G-J, Friedl P (2012) Intravital third harmonic generation microscopy of collective melanoma cell invasion: principles of interface guidance and microvesicle dynamics. Intravital 1:32–43

    Article  PubMed  Google Scholar 

  97. Semenza GL, Roth PH, Fang HM, Wang GL (1994) Transcriptional regulation of genes encoding glycolytic enzymes by hypoxia-inducible factor 1. J Biol Chem 269:23757–23763

    Article  CAS  PubMed  Google Scholar 

  98. O’Rourke JF, Pugh CW, Bartlett SM, Ratcliffe PJ (1996) Identification of hypoxically inducible mRNAs in HeLa cells using differential-display PCR. Role of hypoxia-inducible factor-1. Eur J Biochem. 241:403–410

    Article  PubMed  Google Scholar 

  99. Lehmann S et al (2017) Hypoxia induces a HIF-1-dependent transition from collective-to-amoeboid dissemination in epithelial cancer cells. Curr Biol 27:392–400

    Article  CAS  PubMed  Google Scholar 

  100. Molavian HR, Kohandel M, Sivaloganathan S (2016) High concentrations of H2O2 make aerobic glycolysis energetically more favorable for cellular respiration. Front Physiol 7:362

    Article  PubMed  PubMed Central  Google Scholar 

  101. Druzhkova IN et al (2016) The metabolic interaction of cancer cells and fibroblasts - coupling between NAD(P)H and FAD, intracellular pH and hydrogen peroxide. Cell Cycle 15:1257–1266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Mailloux RJ et al (2007) The tricarboxylic acid cycle, an ancient metabolic network with a novel twist. PLoS ONE 2:e690

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Takatani-Nakase T, Matsui C, Maeda S, Kawahara S, Takahashi K (2014) High glucose level promotes migration behavior of breast cancer cells through zinc and its transporters. PLoS ONE 9:e90136

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  104. Lyssiotis CA, Kimmelman AC (2017) Metabolic interactions in the tumor microenvironment. Trends Cell Biol 27:863–875

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Ho P-C et al (2015) Phosphoenolpyruvate Is a metabolic checkpoint of anti-tumor T cell responses. Cell 162:1217–1228

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Chang C-H et al (2015) Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162:1229–1241

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Gould CM, Courtneidge SA (2014) Regulation of invadopodia by the tumor microenvironment. Cell Adh Migr 8:226–235

    Article  PubMed  PubMed Central  Google Scholar 

  108. Debreova M et al (2019) CAIX regulates invadopodia formation through both a pH-dependent mechanism and interplay with actin regulatory proteins. Int J Mol Sci 20:2745

    Article  CAS  PubMed Central  Google Scholar 

  109. Nelson CM et al (2005) Emergent patterns of growth controlled by multicellular form and mechanics. PNAS 102:11594–11599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Kato Y et al (2007) Acidic extracellular pH increases calcium influx-triggered phospholipase D activity along with acidic sphingomyelinase activation to induce matrix metalloproteinase-9 expression in mouse metastatic melanoma. FEBS J 274:3171–3183

    Article  CAS  PubMed  Google Scholar 

  111. de la Cruz-López KG, Castro-Muñoz LJ, Reyes-Hernández DO, García-Carrancá A, Manzo-Merino J (2019) Lactate in the regulation of tumor microenvironment and therapeutic approaches. Front Oncol. https://doi.org/10.3389/fonc.2019.01143

    Article  PubMed  PubMed Central  Google Scholar 

  112. Wu H, Ying M, Hu X (2016) Lactic acidosis switches cancer cells from aerobic glycolysis back to dominant oxidative phosphorylation. Oncotarget 7:40621–40629

    Article  PubMed  PubMed Central  Google Scholar 

  113. Khacho M et al (2014) Acidosis overrides oxygen deprivation to maintain mitochondrial function and cell survival. Nat Commun 5:3550

    Article  PubMed  CAS  Google Scholar 

  114. Sotgia F et al (2012) Caveolin-1 and cancer metabolism in the tumor microenvironment: markers, models, and mechanisms. Annu Rev Pathol 7:423–467

    Article  CAS  PubMed  Google Scholar 

  115. Mougeolle A et al (2015) Oxidative stress induces caveolin 1 degradation and impairs caveolae functions in skeletal muscle cells. PLoS ONE 10:e0122654

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  116. Pavlides S et al (2009) The reverse Warburg effect: aerobic glycolysis in cancer associated fibroblasts and the tumor stroma. Cell Cycle 8:3984–4001

    Article  CAS  PubMed  Google Scholar 

  117. Martinez-Outschoorn UE et al (2011) Anti-estrogen resistance in breast cancer is induced by the tumor microenvironment and can be overcome by inhibiting mitochondrial function in epithelial cancer cells. Cancer Biol Ther 12:924–938

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Jiang E et al (2019) Tumoral microvesicle–activated glycometabolic reprogramming in fibroblasts promotes the progression of oral squamous cell carcinoma. FASEB J 33:5690–5703

    Article  CAS  PubMed  Google Scholar 

  119. Schwager SC et al (2019) Matrix stiffness regulates microvesicle-induced fibroblast activation. Am J Physiol Cell Physiol 317:C82–C92

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Sedgwick AE, Clancy JW, Olivia Balmert M, D’Souza-Schorey C (2015) Extracellular microvesicles and invadopodia mediate non-overlapping modes of tumor cell invasion. Sci Rep 5:14748

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Begum HM et al (2019) Spatial regulation of mitochondrial heterogeneity by stromal confinement in micropatterned tumor models. Sci Rep 9:11187

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  122. Erdogan B et al (2017) Cancer-associated fibroblasts promote directional cancer cell migration by aligning fibronectin. J Cell Biol 216:3799–3816

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Otranto M et al (2012) The role of the myofibroblast in tumor stroma remodeling. Cell Adh Migr 6:203–219

    Article  PubMed  PubMed Central  Google Scholar 

  124. Provenzano PP et al (2006) Collagen reorganization at the tumor-stromal interface facilitates local invasion. BMC Med 4:38

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  125. Menk AV et al (2018) Early TCR signaling induces rapid aerobic glycolysis enabling distinct acute T cell effector functions. Cell Rep 22:1509–1521

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Bantug GR, Galluzzi L, Kroemer G, Hess C (2018) The spectrum of T cell metabolism in health and disease. Nat Rev Immunol 18:19–34

    Article  CAS  PubMed  Google Scholar 

  127. Lim AR, Rathmell WK, Rathmell JC (2020) The tumor microenvironment as a metabolic barrier to effector T cells and immunotherapy. Elife 9:e55185

    Article  PubMed  PubMed Central  Google Scholar 

  128. Macintyre AN et al (2014) The glucose transporter glut1 is selectively essential for CD4 T cell activation and effector function. Cell Metab 20:61–72

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Angiari S et al (2019) Regulation of T cell activation and pathogenicity by dimeric pyruvate kinase M2 (PKM2). J Immunol 202:125.11

    Article  Google Scholar 

  130. Cavalli LR, Varella-Garcia M, Liang BC (1997) Diminished tumorigenic phenotype after depletion of mitochondrial DNA. Cell Growth Differ 8:1189–1198

    CAS  PubMed  Google Scholar 

  131. Morais R et al (1994) Tumor-forming ability in athymic nude mice of human cell lines devoid of mitochondrial DNA. Cancer Res 54:3889–3896

    CAS  PubMed  Google Scholar 

  132. Chen EI et al (2007) Adaptation of energy metabolism in breast cancer brain metastases. Cancer Res 67:1472–1486

    Article  CAS  PubMed  Google Scholar 

  133. Porporato PE, Sonveaux P (2015) Paving the way for therapeutic prevention of tumor metastasis with agents targeting mitochondrial superoxide. Mol Cell Oncol 2:e968043

    Article  PubMed  CAS  Google Scholar 

  134. Li AM et al (2020) Metabolic profiling reveals a dependency of human metastatic breast cancer on mitochondrial serine and one-carbon unit metabolism. Mol Cancer Res 18:599–611

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Rademaker G et al (2019) Myoferlin contributes to the metastatic phenotype of pancreatic cancer cells by enhancing their migratory capacity through the control of oxidative phosphorylation. Cancers 11:853

    Article  CAS  PubMed Central  Google Scholar 

  136. Zhang T et al (2018) A small molecule targeting myoferlin exerts promising anti-tumor effects on breast cancer. Nat Commun 9:3726

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  137. Davis RT et al (2020) Transcriptional diversity and bioenergetic shift in human breast cancer metastasis revealed by single-cell RNA sequencing. Nat Cell Biol 22:310–320

    Article  CAS  PubMed  Google Scholar 

  138. Huang M, Xiong H, Luo D, Xu B, Liu H (2020) CSN5 upregulates glycolysis to promote hepatocellular carcinoma metastasis via stabilizing the HK2 protein. Exp Cell Res 388:111876

    Article  CAS  PubMed  Google Scholar 

  139. Wiel C et al (2019) BACH1 stabilization by antioxidants stimulates lung cancer metastasis. Cell 178:330–345

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  141. Kim HM, Jung WH, Koo JS (2014) Site-specific metabolic phenotypes in metastatic breast cancer. J Transl Med 12:354

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  142. Stein EM et al (2017) Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood 130:722–731

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Heredia V et al (2017) AG-120, a novel IDH1 targeted molecule, inhibits invasion and migration of chondrosarcoma cells in vitro. Ann Oncol 28:v538

    Article  Google Scholar 

  144. Beloueche-Babari M et al (2020) Monocarboxylate transporter 1 blockade with AZD3965 inhibits lipid biosynthesis and increases tumour immune cell infiltration. Br J Cancer 122:895–903

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Kong SC et al (2016) Monocarboxylate transporters MCT1 and MCT4 regulate migration and invasion of pancreatic ductal adenocarcinoma cells. Pancreas 45:1036–1047

    Article  CAS  PubMed  Google Scholar 

  146. Gao L et al (2020) CPI-613 rewires lipid metabolism to enhance pancreatic cancer apoptosis via the AMPK-ACC signaling. J Exp Clin Cancer Res. https://doi.org/10.1186/s13046-020-01579-x

    Article  PubMed  PubMed Central  Google Scholar 

  147. Saraei P, Asadi I, Kakar MA, Moradi-Kor N (2019) The beneficial effects of metformin on cancer prevention and therapy: a comprehensive review of recent advances. Cancer Manag Res 11:3295–3313

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Alimova IN et al (2009) Metformin inhibits breast cancer cell growth, colony formation and induces cell cycle arrest in vitro. Cell Cycle 8:909–915

    Article  CAS  PubMed  Google Scholar 

  149. Jang SY et al (2014) Metformin inhibits tumor cell migration via down-regulation of MMP9 in tamoxifen-resistant breast cancer cells. Anticancer Res 34:4127–4134

    CAS  PubMed  Google Scholar 

  150. Raninga PV et al (2020) Marizomib suppresses triple-negative breast cancer via proteasome and oxidative phosphorylation inhibition. Theranostics 10:5259–5275

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Huang Q et al (2020) Novel ginsenoside derivative 20( S )-Rh2E2 suppresses tumor growth and metastasis in vivo and in vitro via intervention of cancer cell energy metabolism. Cell Death Dis 11:1–19

    Article  CAS  Google Scholar 

  152. Langer A (2010) A systematic review of PET and PET/CT in oncology: a way to personalize cancer treatment in a cost-effective manner? BMC Health Serv Res 10:283

    Article  PubMed  PubMed Central  Google Scholar 

  153. Zhu A, Lee D, Shim H (2011) Metabolic PET imaging in cancer detection and therapy response. Semin Oncol 38:55–69

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Chen K, Chen X (2011) Positron emission tomography imaging of cancer biology: current status and future prospects. Semin Oncol 38:70–86

    Article  PubMed  PubMed Central  Google Scholar 

  155. Moses WW (2011) Fundamental limits of spatial resolution in PET. Nucl Instrum Methods Phys Res A 648(Supplement 1):S236–S240

    Article  CAS  PubMed  Google Scholar 

  156. Culverwell AD, Scarsbrook AF, Chowdhury FU (2011) False-positive uptake on 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron-emission tomography/computed tomography (PET/CT) in oncological imaging. Clin Radiol 66:366–382

    Article  CAS  PubMed  Google Scholar 

  157. Jose C, Bellance N, Rossignol R (2011) Choosing between glycolysis and oxidative phosphorylation: a tumor’s dilemma? Biochim Biophys Acta 1807:552–561

    Article  CAS  PubMed  Google Scholar 

  158. Feng H et al (2019) Nuclear imaging of glucose metabolism: beyond 18F-FDG. Contrast Media Mol Imaging 2019:1–12

    Article  CAS  Google Scholar 

  159. Croteau E et al (2016) PET metabolic biomarkers for cancer. Biomark Cancer 8:61–69

    CAS  PubMed  PubMed Central  Google Scholar 

  160. Spick C, Herrmann K, Czernin J (2016) Evaluation of prostate cancer with 11C-acetate PET/CT. J Nucl Med 57:30S-37S

    Article  CAS  PubMed  Google Scholar 

  161. Karaayvaz M et al (2018) Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nat Commun 9:3588

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  162. Cheng J et al (2020) TRIM21 and PHLDA3 negatively regulate the crosstalk between the PI3K/AKT pathway and PPP metabolism. Nat Commun 11:1880

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Gerber T et al (2017) Mapping heterogeneity in patient-derived melanoma cultures by single-cell RNA-seq. Oncotarget 8:846–862

    Article  PubMed  Google Scholar 

  164. El-Mir MY et al (2000) Dimethylbiguanide inhibits cell respiration via an indirect effect targeted on the respiratory chain complex I. J Biol Chem 275:223–228

    Article  CAS  PubMed  Google Scholar 

  165. Mediani L et al (2016) Reversal of the glycolytic phenotype of primary effusion lymphoma cells by combined targeting of cellular metabolism and PI3K/Akt/ mTOR signaling. Oncotarget 7:5521–5537

    Article  PubMed  Google Scholar 

  166. Raez LE et al (2013) A phase I dose-escalation trial of 2-deoxy-D-glucose alone or combined with docetaxel in patients with advanced solid tumors. Cancer Chemother Pharmacol 71:523–530

    Article  CAS  PubMed  Google Scholar 

  167. Chapiro J et al (2014) Systemic delivery of microencapsulated 3-bromopyruvate for the therapy of pancreatic cancer. Clin Cancer Res 20:6406–6417

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Baggstrom MQ et al (2011) A phase II study of AT-101 (gossypol) in chemotherapy-sensitive recurrent extensive stage small cell lung cancer (ES-SCLC). J Thorac Oncol 6:1757–1760

    Article  PubMed  PubMed Central  Google Scholar 

  169. Lycan TW et al (2016) A phase II clinical trial of CPI-613 in patients with relapsed or refractory small cell lung carcinoma. PLoS ONE 11:e0164244

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  170. Velpula KK, Bhasin A, Asuthkar S, Tsung AJ (2013) Combined targeting of PDK1 and EGFR triggers regression of glioblastoma by reversing the Warburg effect. Cancer Res 73:7277–7289

    Article  CAS  PubMed  Google Scholar 

  171. Chu QS-C et al (2015) A phase I open-labeled, single-arm, dose-escalation, study of dichloroacetate (DCA) in patients with advanced solid tumors. Invest New Drugs 33:603–610

    Article  CAS  PubMed  Google Scholar 

  172. Moore Z et al (2015) NAMPT inhibition sensitizes pancreatic adenocarcinoma cells to tumor-selective, PAR-independent metabolic catastrophe and cell death induced by β-lapachone. Cell Death Dis 6:e1599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Golub D et al (2019) Mutant isocitrate dehydrogenase inhibitors as targeted cancer therapeutics. Front Oncol. https://doi.org/10.3389/fonc.2019.00417

    Article  PubMed  PubMed Central  Google Scholar 

  174. DiNardo CD et al (2018) Durable remissions with ivosidenib in IDH1-mutated relapsed or refractory AML. N Engl J Med 378:2386–2398

    Article  CAS  PubMed  Google Scholar 

  175. Amadori D et al (1998) Modulating effect of lonidamine on response to doxorubicin in metastatic breast cancer patients: results from a multicenter prospective randomized trial. Breast Cancer Res Treat 49:209–217

    Article  CAS  PubMed  Google Scholar 

  176. Nath K et al (2015) Lonidamine induces intracellular tumor acidification and ATP depletion in breast, prostate and ovarian cancer xenografts and potentiates response to doxorubicin. NMR Biomed 28:281–290

    Article  CAS  PubMed  Google Scholar 

  177. Spencer A et al (2018) A phase 1 clinical trial evaluating marizomib, pomalidomide and low-dose dexamethasone in relapsed and refractory multiple myeloma (NPI-0052-107): final study results. Br J Haematol 180:41–51

    Article  CAS  PubMed  Google Scholar 

  178. Gee JR et al (2017) A phase II randomized, double-blind, presurgical trial of polyphenon E in bladder cancer patients to evaluate pharmacodynamics and bladder tissue biomarkers. Cancer Prev Res 10:298–307

    Article  CAS  Google Scholar 

  179. Berman AY, Motechin RA, Wiesenfeld MY, Holz MK (2017) The therapeutic potential of resveratrol: a review of clinical trials. NPJ Precis Oncol. https://doi.org/10.1038/s41698-017-0038-6

    Article  PubMed  PubMed Central  Google Scholar 

  180. Sato A, Asano T, Ito K, Asano T (2012) Ritonavir interacts with bortezomib to enhance protein ubiquitination and histone acetylation synergistically in renal cancer cells. Urology 79(966):e13-21

    Google Scholar 

  181. Vander Heiden MG et al (2010) Identification of small molecule inhibitors of pyruvate kinase M2. Biochem Pharmacol 79:1118–1124

    Article  CAS  PubMed  Google Scholar 

  182. Clem B et al (2008) Small-molecule inhibition of 6-phosphofructo-2-kinase activity suppresses glycolytic flux and tumor growth. Mol Cancer Ther 7:110–120

    Article  CAS  PubMed  Google Scholar 

  183. Clem BF et al (2013) Targeting 6-phosphofructo-2-kinase (PFKFB3) as a therapeutic strategy against cancer. Mol Cancer Ther 12:1461–1470

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Redman RA, Pohlmann PR, Kurman MR, Tapolsky G, Chesney JA (2015) A phase I, dose-escalation, multi-center study of PFK-158 in patients with advanced solid malignancies explores a first-in-man inhbibitor of glycolysis. JCO 33:TPS2606

    Article  Google Scholar 

  185. Ocaña MC, Martínez-Poveda B, Marí-Beffa M, Quesada AR, Medina MÁ (2020) Fasentin diminishes endothelial cell proliferation, differentiation and invasion in a glucose metabolism-independent manner. Sci Rep 10:6132

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  186. Wang Y et al (2016) GEN-27, a newly synthetic isoflavonoid, inhibits the proliferation of colon cancer cells in inflammation microenvironment by suppressing NF-κB pathway. Mediat Inflamm 2016:2853040

    Article  Google Scholar 

  187. Kumagai S, Narasaki R, Hasumi K (2008) Glucose-dependent active ATP depletion by koningic acid kills high-glycolytic cells. Biochem Biophys Res Commun 365:362–368

    Article  CAS  PubMed  Google Scholar 

  188. Ozerlat I (2011) Targeted therapy of glucose uptake via GLUT1 kills RCC cells. Nat Rev Urol 8:471–471

    Article  PubMed  Google Scholar 

  189. Liu Y et al (2012) A small-molecule inhibitor of glucose transporter 1 downregulates glycolysis, induces cell-cycle arrest, and inhibits cancer cell growth in vitro and in vivo. Mol Cancer Ther 11:1672–1682

    Article  CAS  PubMed  Google Scholar 

  190. National Library of Medicine (U.S.) (2019) A study of CPI-613 for patients with relapsed or refractory burkitt lymphoma/leukemia or high-grade B-cell lymphoma with high-risk translocations. https://clinicaltrials.gov/ct2/show/NCT03793140. Accessed 17 Nov 2020

Download references

Acknowledgements

This work was supported by funding from the NIH (GM131178) to C.A.R.-K., the W.M. Keck Foundation to C.A.R.-K., and by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1937963 awarded to J.A.M. and S.C.S.

Author information

Author notes

  1. Jenna A. Mosier and Samantha C. Schwager contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA

    Jenna A. Mosier, Samantha C. Schwager & Cynthia A. Reinhart-King

  2. Department of Radiology, Weill Cornell Medical College, New York, NY, USA

    David A. Boyajian

Authors
  1. Jenna A. Mosier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Samantha C. Schwager
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David A. Boyajian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cynthia A. Reinhart-King
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cynthia A. Reinhart-King.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mosier, J.A., Schwager, S.C., Boyajian, D.A. et al. Cancer cell metabolic plasticity in migration and metastasis. Clin Exp Metastasis 38, 343–359 (2021). https://doi.org/10.1007/s10585-021-10102-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10585-021-10102-1

Keywords

Search

Navigation