Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Metabolic reprogramming in clear cell renal cell carcinoma

Nature Reviews Nephrology volume 13, pages 410–419 (2017)Cite this article

Subjects

Key Points

  • The incidence of kidney cancer, particularly clear cell renal cell carcinoma, is increasing and knowledge of its pathophysiology is essential for nephrologists

  • Reprogramming of metabolic pathways enables cancer cells to rapidly proliferate, survive in conditions of nutrient depletion and hypoxia, and evade the immune system

  • Most forms of kidney cancer are associated with reprogramming of metabolic pathways including oxygen sensing, the tricarboxylic acid cycle and the metabolism of tryptophan, fatty acids, glucose, glutamine and arginine

  • Metabolic reprogramming provides opportunities for functional imaging approaches based on the altered pathways

  • Novel therapies for kidney cancers that target critical proteins or enzymes that are involved in dysregulated metabolic pathways are being developed

Abstract

Research in many cancers has uncovered changes in metabolic pathways that control tumour energetics and biosynthesis, so-called metabolic reprogramming. Studies in clear cell renal cell carcinoma (ccRCC) have been particularly revealing, leading to the concept that ccRCC is a metabolic disease. ccRCC is generally accompanied by reprogramming of glucose and fatty acid metabolism and of the tricarboxylic acid cycle. Metabolism of tryptophan, arginine and glutamine is also reprogrammed in many ccRCCs, and these changes provide opportunities for new therapeutic strategies, biomarkers and imaging modalities. In particular, metabolic reprogramming facilitates the identification of novel and repurposed drugs that could potentially be used to treat ccRCC, which when metastatic has currently limited long-term treatment options. Further research and dissemination of these concepts to nephrologists and oncologists will lead to clinical trials of therapeutics specifically targeted to tumour metabolism, rather than generally toxic to all proliferating cells. Such novel agents are highly likely to be more effective and to have far fewer adverse effects than existing drugs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Metabolic reprogramming in clear cell renal cell carcinoma (ccRCC).
Figure 2: Altered tryptophan metabolism in clear cell renal cell carcinoma (ccRCC).
Figure 3: Altered energy and glutamine metabolism in clear cell renal cell carcinoma (ccRCC).
Figure 4: Altered arginine metabolism in clear cell renal cell carcinoma (ccRCC).

Similar content being viewed by others

References

  1. Cline, M. J., Slamon, D. J. & Lipsick, J. S. Oncogenes: implications for the diagnosis and treatment of cancer. Ann. Intern. Med. 101, 223–233 (1984).

    Article  CAS  PubMed  Google Scholar 

  2. Warburg, O. On the origin of cancer cells. Science 123, 309–314 (1956). The classic work of Warburg demonstrating the eponymous aerobic glycolysis effect.

    Article  CAS  PubMed  Google Scholar 

  3. Weiss, R. H. & Lin, P.-Y. Kidney cancer: identification of novel targets for therapy. Kidney Int. 69, 224–232 (2006).

    Article  CAS  PubMed  Google Scholar 

  4. Hu, S. L. et al. The nephrologist's tumor: basic biology and management of renal cell carcinoma. J. Am. Soc. Nephrol. 27, 2227–2237 (2016). A discussion of what practicing and research nephrologists need to know about kidney cancer.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cantor, J. R. & Sabatini, D. M. Cancer cell metabolism: one hallmark, many faces. Cancer Discov. 2, 881–898 (2012). A detailed description of the concept of metabolic reprogramming in cancer.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. van der Mijn, J. C., Panka, D. J., Geissler, A. K., Verheul, H. M. & Mier, J. W. Novel drugs that target the metabolic reprogramming in renal cell cancer. Cancer Metab. 4, 14 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Hakimi, A. A. et al. An integrated metabolic atlas of clear cell renal cell carcinoma. Cancer Cell 29, 104–116 (2016). Use of ccRCC transcriptomics and metabolomics to develop a visualization tool and demonstration of discordance between the transcriptome and metabolome in this disease.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wettersten, H. I. et al. Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis. Cancer Res. 75, 2541–2552 (2015). Use of metabolomics and proteomics to demonstrate metabolic reprogramming in ccRCC and to identify new drug targets.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Linehan, W. M. & Ricketts, C. J. The metabolic basis of kidney cancer. Semin. Cancer Biol. 23, 46–55 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. Linehan, W. M., Srinivasan, R. & Schmidt, L. S. The genetic basis of kidney cancer: a metabolic disease. Nat. Rev. Urol. 7, 277–285 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Motzer, R. J., Bacik, J. & Mazumdar, M. Prognostic factors for survival of patients with stage IV renal cell carcinoma: memorial sloan-kettering cancer center experience. Clin. Cancer Res. 10, 6302s–6303s (2004).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  14. Mullen, A. R. et al. Reductive carboxylation supports growth in tumour cells with defective mitochondria. Nature 481, 385–388 (2012). Introducing the concept of reductive carboxylation in ccRCC.

    Article  CAS  Google Scholar 

  15. Jiang, P., Du, W. & Wu, M. Regulation of the pentose phosphate pathway in cancer. Protein Cell 5, 592–602 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sayin, V. I. et al. Antioxidants accelerate lung cancer progression in mice. Sci. Transl Med. 6, 221ra15 (2014). Discussion of the possibility that antioxidants can worsen cancer; this effect might be related to glutamine reprogramming to the glutathione pathway.

    Article  PubMed  CAS  Google Scholar 

  17. Wise, D. R. & Thompson, C. B. Glutamine addiction: a new therapeutic target in cancer. Trends Biochem. Sci. 35, 427–433 (2010). A concise discussion of glutamine reprogramming in cancer.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Baldewijns, M. M. et al. VHL and HIF signalling in renal cell carcinogenesis. J. Pathol. 221, 125–138 (2010).

    Article  CAS  PubMed  Google Scholar 

  19. Bausch, B. et al. Renal cancer in von Hippel–Lindau disease and related syndromes. Nat. Rev. Nephrol. 9, 529–538 (2013).

    Article  CAS  PubMed  Google Scholar 

  20. Perroud, B., Ishimaru, T., Borowsky, A. D. & Weiss, R. H. Grade-dependent proteomics characterization of kidney cancer. Mol. Cell. Proteomics 8, 971–985 (2008).

    Article  CAS  Google Scholar 

  21. Rabinovich, S. et al. Diversion of aspartate in ASS1-deficient tumours fosters de novo pyrimidine synthesis. Nature 527, 379–383 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Yoon, C. Y. et al. Renal cell carcinoma does not express argininosuccinate synthetase and is highly sensitive to arginine deprivation via arginine deiminase. Int. J. Cancer 120, 897–905 (2007). The first description of the use of ADI-PEG to target arginine reprogramming in a murine homograft RCC model.

    Article  CAS  PubMed  Google Scholar 

  23. Gross, M. I. et al. Antitumor activity of the glutaminase inhibitor CB-839 in triple-negative breast cancer. Mol. Cancer Ther. 13, 890–901 (2014). The first description of the use of a glutaminase inhibitor in cancer.

    Article  CAS  PubMed  Google Scholar 

  24. Chen, W. et al. Targeting renal cell carcinoma with a HIF-2 antagonist. Nature 539, 112–117 (2016). Demonstration of HIF-2 antagonism as a possible therapeutic approach in RCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nickerson, M. L. et al. Improved identification of von Hippel–Lindau gene alterations in clear cell renal tumors. Clin. Cancer Res. 14, 4726–4734 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kaelin, W. G. Jr. The von Hippel–Lindau tumor suppressor gene and kidney cancer. Clin. Cancer Res. 10, 6290s–6295s (2004).

    Article  CAS  PubMed  Google Scholar 

  27. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499, 43–49 (2013). The Cancer Genome Atlas transcriptomic description of ccRCC.

  28. Perroud, B. et al. Pathway analysis of kidney cancer using proteomics and metabolic profiling. Mol. Cancer 5, 64 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Schaechter, J. D. & Wurtman, R. J. Serotonin release varies with brain tryptophan levels. Brain Res. 532, 203–210 (1990).

    Article  CAS  PubMed  Google Scholar 

  30. Fallarino, F. et al. T cell apoptosis by tryptophan catabolism. Cell Death Differ. 9, 1069–1077 (2002).

    Article  CAS  PubMed  Google Scholar 

  31. Shimizu, T., Nomiyama, S., Hirata, F. & Hayaishi, O. Indoleamine 2,3-dioxygenase. Purification and some properties. J. Biol. Chem. 253, 4700–4706 (1978).

    CAS  PubMed  Google Scholar 

  32. Lee, G. K. et al. Tryptophan deprivation sensitizes activated T cells to apoptosis prior to cell division. Immunology 107, 452–460 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Riesenberg, R. et al. Expression of indoleamine 2,3-dioxygenase in tumor endothelial cells correlates with long-term survival of patients with renal cell carcinoma. Clin. Cancer Res. 13, 6993–7002 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Trott, J. F. et al. Inhibiting tryptophan metabolism enhances interferon therapy in kidney cancer. Oncotarget 7, 66540–66557 (2016). The first description of the use of a modulator of tryptophan reprogramming in a murine homograft RCC model.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kim, K. et al. Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer. OMICS 15, 293–303 (2011). The first non-targeted urine metabolomics study in RCC, which identified immune modulators as possible biomarkers of ccRCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Carracedo, A., Cantley, L. C. & Pandolfi, P. P. Cancer metabolism: fatty acid oxidation in the limelight. Nat. Rev. Cancer 13, 227–232 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Wakil, S. J. Fatty acid synthase, a proficient multifunctional enzyme. Biochemistry 28, 4523–4530 (1989).

    Article  CAS  PubMed  Google Scholar 

  38. Enoch, H. G., Catala, A. & Strittmatter, P. Mechanism of rat liver microsomal stearyl-CoA desaturase. Studies of the substrate specificity, enzyme–substrate interactions, and the function of lipid. J. Biol. Chem. 251, 5095–5103 (1976).

    CAS  PubMed  Google Scholar 

  39. Gebhard, R. L. et al. Abnormal cholesterol metabolism in renal clear cell carcinoma. J. Lipid Res. 28, 1177–1184 (1987).

    CAS  PubMed  Google Scholar 

  40. von Roemeling, C. A. et al. Stearoyl-CoA desaturase 1 is a novel molecular therapeutic target for clear cell renal cell carcinoma. Clin. Cancer Res. 19, 2368–2380 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Horiguchi, A. et al. Fatty acid synthase over expression is an indicator of tumor aggressiveness and poor prognosis in renal cell carcinoma. J. Urol. 180, 1137–1140 (2008).

    Article  CAS  PubMed  Google Scholar 

  42. Ganti, S. et al. Urinary acylcarnitines are altered in kidney cancer. Int. J. Cancer 130, 2791–2800 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Weidemann, A. & Johnson, R. S. Biology of HIF-1alpha. Cell Death Differ. 15, 621–627 (2008).

    Article  CAS  PubMed  Google Scholar 

  44. Warburg, O., Wind, F. & Negelein, E. The metabolism of tumors in the body. J. Gen. Physiol. 8, 519–530 (1927).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ward, P. S. & Thompson, C. B. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell 21, 297–308 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wu, J., Ocampo, A. & Izpisua Belmonte, J. C. Cellular metabolism and induced pluripotency. Cell 166, 1371–1385 (2016).

    Article  CAS  PubMed  Google Scholar 

  47. Sellers, K. et al. Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Invest. 125, 687–698 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Ozcan, A., Shen, S. S., Zhai, Q. J. & Truong, L. D. Expression of GLUT1 in primary renal tumors: morphologic and biologic implications. Am. J. Clin. Pathol. 128, 245–254 (2007).

    Article  CAS  PubMed  Google Scholar 

  49. Li, B. et al. Fructose-1,6-bisphosphatase opposes renal carcinoma progression. Nature 513, 251–255 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Singer, K. et al. Warburg phenotype in renal cell carcinoma: high expression of glucose-transporter 1 (GLUT-1) correlates with low CD8+ T-cell infiltration in the tumor. Int. J. Cancer 128, 2085–2095 (2011).

    Article  CAS  PubMed  Google Scholar 

  51. Fischer, K. et al. Inhibitory effect of tumor cell-derived lactic acid on human T cells. Blood 109, 3812–3819 (2007).

    Article  CAS  PubMed  Google Scholar 

  52. Mandriota, S. J. et al. HIF activation identifies early lesions in VHL kidneys: evidence for site-specific tumor suppressor function in the nephron. Cancer Cell 1, 459–468 (2002).

    Article  CAS  PubMed  Google Scholar 

  53. Semenza, G. L. Regulation of cancer cell metabolism by hypoxia-inducible factor 1. Semin. Cancer Biol. 19, 12–16 (2009).

    Article  CAS  PubMed  Google Scholar 

  54. Semenza, G. L. HIF-1: upstream and downstream of cancer metabolism. Curr. Opin. Genet. Dev. 20, 51–56 (2010).

    Article  CAS  PubMed  Google Scholar 

  55. Papandreou, I., Cairns, R. A., Fontana, L., Lim, A. L. & Denko, N. C. HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption. Cell Metab. 3, 187–197 (2006).

    Article  CAS  PubMed  Google Scholar 

  56. Kim, J. W., Tchernyshyov, I., Semenza, G. L. & Dang, C. V. HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab. 3, 177–185 (2006).

    Article  PubMed  CAS  Google Scholar 

  57. Huang, X. et al. Hypoxia-inducible mir-210 regulates normoxic gene expression involved in tumor initiation. Mol. Cell 35, 856–867 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Valera, V. A., Walter, B. A., Linehan, W. M. & Merino, M. J. Regulatory effects of microRNA-92 (miR-92) on VHL gene expression and the hypoxic activation of miR-210 in clear cell renal cell carcinoma. J. Cancer 2, 515–526 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. White, N. M. et al. miRNA profiling in metastatic renal cell carcinoma reveals a tumour-suppressor effect for miR-215. Br. J. Cancer 105, 1741–1749 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Ivan, M. & Huang, X. miR-210: fine-tuning the hypoxic response. Adv. Exp. Med. Biol. 772, 205–227 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Cho, H. et al. On-target efficacy of a HIF-2alpha antagonist in preclinical kidney cancer models. Nature 539, 107–111 (2016). A classic paper showing the link between HIF-1 and VHL and its role in RCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Catchpole, G. et al. Metabolic profiling reveals key metabolic features of renal cell carcinoma. J. Cell. Mol. Med. 15, 109–118 (2011).

    Article  CAS  PubMed  Google Scholar 

  63. 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 

  64. Shim, E. H. et al. L-2-hydroxyglutarate: an epigenetic modifier and putative oncometabolite in renal cancer. Cancer Discov. 4, 1290–1298 (2014). An early demonstration of a newly identified oncometabolite active in RCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).

    Article  CAS  PubMed  Google Scholar 

  66. Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457–D462 (2016).

    Article  CAS  PubMed  Google Scholar 

  67. 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 

  68. Kamm, D. E. & Strope, G. L. The effects of acidosis and alkalosis on the metabolism of glutamine and glutamate in renal cortex slices. J. Clin. Invest. 51, 1251–1263 (1972).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Gatto, F., Miess, H., Schulze, A. & Nielsen, J. Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism. Sci. Rep. 5, 10738 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Chakrabarti, G. et al. Targeting glutamine metabolism sensitizes pancreatic cancer to PARP-driven metabolic catastrophe induced by ss-lapachone. Cancer Metab. 3, 12 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Jacque, N. et al. Targeting glutaminolysis has antileukemic activity in acute myeloid leukemia and synergizes with BCL-2 inhibition. Blood 126, 1346–1356 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Meric-Bernstam, F. et al. Phase 1 study of CB-839, a small molecule inhibitor of glutaminase (GLS), alone and in combination with everolimus (E) in patients (pts) with renal cell cancer (RCC) [abstract]. J. Clin. Oncol. 34 (Suppl.), 4568 (2016).

    Article  Google Scholar 

  73. Wu, G. & Morris, S. M. Jr. Arginine metabolism: nitric oxide and beyond. Biochem. J. 336, 1–17 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Husson, A., Brasse-Lagnel, C., Fairand, A., Renouf, S. & Lavoinne, A. Argininosuccinate synthetase from the urea cycle to the citrulline–NO cycle. Eur. J. Biochem. 270, 1887–1899 (2003).

    Article  CAS  PubMed  Google Scholar 

  75. Haines, R. J., Pendleton, L. C. & Eichler, D. C. Argininosuccinate synthase: at the center of arginine metabolism. Int. J. Biochem. Mol. Biol. 2, 8–23 (2011).

    CAS  PubMed  Google Scholar 

  76. Delage, B. et al. Arginine deprivation and argininosuccinate synthetase expression in the treatment of cancer. Int. J. Cancer 126, 2762–2772 (2010).

    CAS  PubMed  Google Scholar 

  77. Qiu, F. et al. Arginine starvation impairs mitochondrial respiratory function in ASS1-deficient breast cancer cells. Sci. Signal. 7, ra31 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Allen, M. D. et al. Prognostic and therapeutic impact of argininosuccinate synthetase 1 control in bladder cancer as monitored longitudinally by PET imaging. Cancer Res. 74, 896–907 (2014).

    Article  CAS  PubMed  Google Scholar 

  79. Kobayashi, E. et al. Reduced argininosuccinate synthetase is a predictive biomarker for the development of pulmonary metastasis in patients with osteosarcoma. Mol. Cancer Ther. 9, 535–544 (2010).

    Article  CAS  PubMed  Google Scholar 

  80. Weber, W. A., Schwaiger, M. & Avril, N. Quantitative assessment of tumor metabolism using FDG-PET imaging. Nucl. Med. Biol. 27, 683–687 (2000).

    Article  CAS  PubMed  Google Scholar 

  81. Shankar, L. K. et al. Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute trials. J. Nucl. Med. 47, 1059–1066 (2006).

    CAS  PubMed  Google Scholar 

  82. Tunariu, N., Kaye, S. B. & Desouza, N. M. Functional imaging: what evidence is there for its utility in clinical trials of targeted therapies? Br. J. Cancer 106, 619–628 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Juweid, M. E. & Cheson, B. D. Positron-emission tomography and assessment of cancer therapy. N. Engl. J. Med. 354, 496–507 (2006).

    Article  CAS  PubMed  Google Scholar 

  84. Robey, I. F. et al. Regulation of the Warburg effect in early-passage breast cancer cells. Neoplasia (New York, N.Y.) 10, 745–756 (2008).

    Article  CAS  Google Scholar 

  85. Gofrit, O. N. & Orevi, M. Diagnostic challenges in kidney cancer: a systematic review of the role of PET/CT. J. Urol. 196, 648–657 (2016).

    Article  PubMed  Google Scholar 

  86. Aide, N. et al. Efficiency of [18F]FDG PET in characterising renal cancer and detecting distant metastases: a comparison with CT. Eur. J. Nucl. Med. Mol. Imaging 30, 1236–1245 (2003).

    Article  PubMed  Google Scholar 

  87. Ueno, D. et al. Early assessment by FDG-PET/CT of patients with advanced renal cell carcinoma treated with tyrosine kinase inhibitors is predictive of disease course. BMC Cancer 12, 162 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Kayani, I. et al. Sequential FDG-PET/CT as a biomarker of response to Sunitinib in metastatic clear cell renal cancer. Clin. Cancer Res. 17, 6021–6028 (2011).

    Article  CAS  PubMed  Google Scholar 

  89. Ma, W. W. et al. [18F]fluorodeoxyglucose positron emission tomography correlates with Akt pathway activity but is not predictive of clinical outcome during mTOR inhibitor therapy. J. Clin. Oncol. 27, 2697–2704 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Mizuno, T. et al. Clinically significant association between the maximum standardized uptake value on 18F-FDG PET and expression of phosphorylated Akt and S6 kinase for prediction of the biological characteristics of renal cell cancer. BMC Cancer 15, 1097 (2015).

    Article  PubMed  CAS  Google Scholar 

  91. Nakaigawa, N. et al. FDG PET/CT as a prognostic biomarker in the era of molecular-targeting therapies: max SUVmax predicts survival of patients with advanced renal cell carcinoma. BMC Cancer 16, 67 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  92. Hambardzumyan, D., Amankulor, N. M., Helmy, K. Y., Becher, O. J. & Holland, E. C. Modeling adult gliomas using RCAS/t-va technology. Transl Oncol. 2, 89–95 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Mills, C. D. M1 and M2 macrophages: oracles of health and disease. Crit. Rev. Immunol. 32, 463–488 (2012).

    Article  CAS  PubMed  Google Scholar 

  94. Wu, C., Li, F., Niu, G. & Chen, X. PET imaging of inflammation biomarkers. Theranostics 3, 448–466 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  95. Carman, A. J., Mills, J. H., Krenz, A., Kim, D. G. & Bynoe, M. S. Adenosine receptor signaling modulates permeability of the blood–brain barrier. J. Neurosci. 31, 13272–13280 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Lieberman, B. P. et al. PET imaging of glutaminolysis in tumors by 18F-(2S,4R)4-fluoroglutamine. J. Nucl. Med. 52, 1947–1955 (2011). First description of the potential use of glutamine-PET for evaluation of cancer metabolism.

    Article  CAS  PubMed  Google Scholar 

  97. Venneti, S. et al. Glutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo. Sci. Transl Med. 7, 274ra17 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  98. Choi, C. Y. et al. Molecular imaging of hypoxia-inducible factor 1 alpha and von Hippel–Lindau interaction in mice. Mol. Imaging 7, 139–146 (2008).

    Article  CAS  PubMed  Google Scholar 

  99. Moroz, E. et al. Real-time imaging of HIF-1alpha stabilization and degradation. PLoS ONE 4, e5077 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Riazalhosseini, Y. & Lathrop, M. Precision medicine from the renal cancer genome. Nat. Rev. Nephrol. 12, 655–666 (2016).

    Article  CAS  PubMed  Google Scholar 

  101. Schmidinger, M. Understanding and managing toxicities of vascular endothelial growth factor (VEGF) inhibitors. EJC Suppl. 11, 172–191 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  102. US National Library of Medicine. ClinicalTrials.govhttps://clinicaltrials.gov/ct2/show/NCT02293980 (2017).

  103. Gupta, S. Obesity: the fat advantage. Nature 537, S100–S102 (2016).

    Article  CAS  PubMed  Google Scholar 

  104. Heuer, T. S. et al. FASN inhibition and taxane treatment combine to enhance anti-tumor efficacy in diverse xenograft tumor models throgh disruption of tubulin palmitoylation and microtubule organization and FASN inhibition-mediated effects on oncogenic signaling and gene expression. EBioMedicine 16, 51–62 (2017).

    Article  PubMed  Google Scholar 

  105. US National Library of Medicine. ClinicalTrials.govhttps://clinicaltrials.gov/ct2/show/NCT02223247 (2017).

  106. Sheridan, C. IDO inhibitors move center stage in immuno-oncology. Nat. Biotechnol. 33, 321–322 (2015).

    Article  CAS  PubMed  Google Scholar 

  107. Jochems, C. et al. The IDO1 selective inhibitor epacadostat enhances dendritic cell immunogenicity and lytic ability of tumor antigen-specific T cells. Oncotarget 7, 37762–37772 (2016).

    PubMed  PubMed Central  Google Scholar 

  108. Incyte. Press releases. Incyte http://phx.corporate-ir.net/phoenix.zhtml?c=69764&p=irol-newsArticle_print&ID=2210055 (2017).

  109. Yoon, J. K., Frankel, A. E., Feun, L. G., Ekmekcioglu, S. & Kim, K. B. Arginine deprivation therapy for malignant melanoma. Clin. Pharmacol. 5, 11–19 (2013).

    CAS  PubMed  Google Scholar 

  110. US National Library of Medicine. ClinicalTrials.govhttps://clinicaltrials.gov/ct2/results?term=ADI-PEG20+&Search=Search (2017).

  111. Peyser, N. D. & Grandis, J. R. Cancer genomics: spot the difference. Nature 541, 162–163 (2017).

    Article  CAS  PubMed  Google Scholar 

  112. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012). Discussion of the occurrence of intratumoral heterogeneity in ccRCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Xu, K. Y. & Wu, S. Update on the treatment of metastatic clear cell and non-clear cell renal cell carcinoma. Biomark. Res. 3, 5 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  114. King, S. C., Pollack, L. A., Li, J., King, J. B. & Master, V. A. Continued increase in incidence of renal cell carcinoma, especially in young patients and high grade disease: United States 2001 to 2010. J. Urol. 191, 1665–1670 (2014). Discussion of potential reasons for the increase in RCC incidence in the USA.

    Article  PubMed  PubMed Central  Google Scholar 

  115. Tosaka, A. et al. Incidence and properties of renal masses and asymptomatic renal cell carcinoma detected by abdominal ultrasonography. J. Urol. 144, 1097–1099 (1990).

    Article  CAS  PubMed  Google Scholar 

  116. Quinn, D. I. & Lara, P. N. Jr. Renal-cell cancer—targeting an immune checkpoint or multiple kinases. N. Engl. J. Med. 373, 1872–1874 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Sumitomo, M. et al. Synergy in tumor suppression by direct interaction of neutral endopeptidase with PTEN. Cancer Cell 5, 67–78 (2004).

    Article  CAS  PubMed  Google Scholar 

  118. Lee, H. J. et al. Prognostic significance of biallelic loss of PTEN in clear cell renal cell carcinoma. J. Urol. 192, 940–946 (2014).

    Article  CAS  PubMed  Google Scholar 

  119. Inoki, K., Li, Y., Zhu, T., Wu, J. & Guan, K. L. TSC2 is phosphorylated and inhibited by Akt and suppresses mTOR signalling. Nat. Cell Biol. 4, 648–657 (2002).

    Article  CAS  PubMed  Google Scholar 

  120. Bjornsson, J., Short, M. P., Kwiatkowski, D. J. & Henske, E. P. Tuberous sclerosis-associated renal cell carcinoma. Clinical, pathological, and genetic features. Am. J. Pathol. 149, 1201–1208 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  121. Elstrom, R. L. et al. Akt stimulates aerobic glycolysis in cancer cells. Cancer Res. 64, 3892–3899 (2004).

    Article  CAS  PubMed  Google Scholar 

  122. Miyamoto, S., Murphy, A. N. & Brown, J. H. Akt mediates mitochondrial protection in cardiomyocytes through phosphorylation of mitochondrial hexokinase-II. Cell Death Differ. 15, 521–529 (2008).

    Article  CAS  PubMed  Google Scholar 

  123. Toschi, A., Lee, E., Gadir, N., Ohh, M. & Foster, D. A. Differential dependence of hypoxia-inducible factors 1 alpha and 2 alpha on mTORC1 and mTORC2. J. Biol. Chem. 283, 34495–34499 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Park, J. Y., Lin, P. Y. & Weiss, R. H. Targeting the PI3K–Akt pathway in kidney cancer. Expert Rev. Anticancer Ther. 7, 863–870 (2007).

    Article  CAS  PubMed  Google Scholar 

  125. Ohh, M. et al. Ubiquitination of hypoxia-inducible factor requires direct binding to the beta-domain of the von Hippel–Lindau protein. Nat. Cell Biol. 2, 423–427 (2000).

    Article  CAS  PubMed  Google Scholar 

  126. Schwartzenberg-Bar-Yoseph, F., Armoni, M. & Karnieli, E. The tumor suppressor p53 down-regulates glucose transporters GLUT1 and GLUT4 gene expression. Cancer Res. 64, 2627–2633 (2004).

    Article  CAS  PubMed  Google Scholar 

  127. Bensaad, K. et al. TIGAR, a p53-inducible regulator of glycolysis and apoptosis. Cell 126, 107–120 (2006).

    Article  CAS  PubMed  Google Scholar 

  128. Suzuki, S. et al. Phosphate-activated glutaminase (GLS2), a p53-inducible regulator of glutamine metabolism and reactive oxygen species. Proc. Natl Acad. Sci. USA 107, 7461–7466 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Gurova, K. V., Hill, J. E., Razorenova, O. V., Chumakov, P. M. & Gudkov, A. V. p53 pathway in renal cell carcinoma is repressed by a dominant mechanism. Cancer Res. 64, 1951–1958 (2004).

    Article  CAS  PubMed  Google Scholar 

  130. Shaw, R. J. et al. The tumor suppressor LKB1 kinase directly activates AMP-activated kinase and regulates apoptosis in response to energy stress. Proc. Natl Acad. Sci. USA 101, 3329–3335 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Yalniz, Z. et al. Novel mutations and role of the LKB1 gene as a tumor suppressor in renal cell carcinoma. Tumour Biol. 35, 12361–12368 (2014).

    Article  CAS  PubMed  Google Scholar 

  132. Duivenvoorden, W. C. et al. Underexpression of tumour suppressor LKB1 in clear cell renal cell carcinoma is common and confers growth advantage in vitro and in vivo. Br. J. Cancer 108, 327–333 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Kim, J. W., Gao, P., Liu, Y. C., Semenza, G. L. & Dang, C. V. Hypoxia-inducible factor 1 and dysregulated c-Myc cooperatively induce vascular endothelial growth factor and metabolic switches hexokinase 2 and pyruvate dehydrogenase kinase 1. Mol. Cell. Biol. 27, 7381–7393 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Gao, P. et al. c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature 458, 762–765 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Shroff, E. H. et al. MYC oncogene overexpression drives renal cell carcinoma in a mouse model through glutamine metabolism. Proc. Natl Acad. Sci. USA 112, 6539–6544 (2015). Discussion of the interaction of c-Myc with glutamine reprogramming in RCC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Gordan, J. D. et al. HIF-alpha effects on c-Myc distinguish two subtypes of sporadic VHL-deficient clear cell renal carcinoma. Cancer Cell 14, 435–446 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

All authors researched the data for the article, made substantial contributions to discussions of the content, wrote the article and reviewed or edited the manuscript before submission.

Author information

Authors and Affiliations

  1. University of California, San Diego, Sanford Consortium for Regenerative Medicine, Room 4810, 2880 Torrey Pines Scenic Drive, La Jolla, 92037–0695, California, USA

    Hiromi I. Wettersten

  2. Division of Nephrology, University of California Davis, Genome and Biomedical Sciences Facility, Room 6311, 451 Health Sciences Drive, Davis, 95616, California, USA

    Omran Abu Aboud & Robert H. Weiss

  3. University of California Davis Comprehensive Cancer Center, 4501 X Street, Suite 3003, Sacramento, 95817, California, USA

    Primo N. Lara Jr

Authors
  1. Hiromi I. Wettersten
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omran Abu Aboud
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Primo N. Lara Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Robert H. Weiss
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert H. Weiss.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Glossary

Tricarboxylic acid (TCA) cycle

A series of chemical reactions that comprises the oxidation of acetyl-CoA to release stored energy.

Warburg effect

The phenomenon of cells producing energy primarily by glycolysis followed by lactate fermentation, rather than by glycolysis followed by the tricarboxylic acid (TCA) cycle in mitochondria.

Oncometabolite

A small molecule component of normal metabolism that on accumulation, results in metabolic dysregulation and consequently primes cells for progression to malignancy.

Semi-essential amino acid

An amino acid that can only be synthesized under specific metabolic conditions. Also known as a conditionally essential amino acid.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wettersten, H., Aboud, O., Lara, P. et al. Metabolic reprogramming in clear cell renal cell carcinoma. Nat Rev Nephrol 13, 410–419 (2017). https://doi.org/10.1038/nrneph.2017.59

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrneph.2017.59

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer