Advertisement

The Metabolism of Renal Cell Carcinomas and Liver Cancer

  • Tu Nguyen
  • Anne LeEmail author
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1063)

Abstract

According to data from the American Cancer Society, cancer is one of the deadliest health problems globally. Annually, renal cell carcinoma (RCC) and liver cancer cause more than 100,000 and 800,000 deaths worldwide, respectively [1–4], creating an urgent need to develop effective therapeutic treatments to increase patient survival outcomes. New therapeutic treatments are expected to address a major factor contributing to cancer’s resistance to standard therapies: oncogenic heterogeneity. Because gene expression can vary tremendously among different types of cancers, different patients of the same tumor type, and even within individual tumors, various metabolic phenotypes can emerge, making single-therapy approaches insufficient. This heterogeneity translates into changes in the landscape of metabolic enzymes and biomolecules within both the cancer cell and tumor microenvironment. Novel strategies targeting the diverse metabolism of cancers aim to overcome this obstacle, and though some have yielded positive results, it remains a challenge to uncover all of the distinct metabolic profiles of RCC and liver cancer. Nonetheless, the metabolic-oriented research focusing on these cancers has offered different, fresh new perspectives, which are expected to contribute heavily to the development of new therapeutic treatments.

Keywords

Renal cell carcinoma Primary liver cancer Metabolic phenotypes Glucose metabolism Glutamine metabolism Oncogenic heterogeneity 

Abbreviations

α-KG

α-Ketoglutarate

ACC

Acetyl-CoA carboxylase

AMPK

AMP-activated protein kinase

ATP

Adenosine triphosphate

ccRCC

Clear-cell renal cell carcinoma

CL

Cardiolipin

COX5B

Cytochrome C oxidase subunit 5B

DEN

Diethylnitrosamine

ePC

Ether-type phosphatidylcholine

ePE

Ether-type PE

ERRα

Estrogen-related receptor Α

FASN

Fatty acid synthase

FH

Fumarate hydratase

G6PH

Glucose-6-phosphate dehydrogenase

GLS2

Glutaminase 2

Glu

Glutamine

GLUT1

Glucose transporter 1

GLUT2

Glucose transporter 2

HCC

Hepatocellular carcinoma

HIF

Hypoxia-inducible factor

HIF-1α

Hypoxia-inducible factor 1-alpha

HK2

Hexokinase 2

LCSCs

Liver cancer stem cells

LDHA

Lactate dehydrogenase A

LRH-1

Liver receptor homolog 1

Me1

Malic enzyme 1

MIR21

MicroRNAs-21

mTORC1

Mechanistic target of rapamycin complex 1

NADPH

Nicotinamide adenine dinucleotide phosphate

Non-LCSCs

Non-liver cancer stem cells

PE

Phosphatidylethanolamine

PGK1

Phosphoglycerate kinase 1

PGLS

6-Phosphogluconolactonase

PI3K

Phosphatidylinositol-3 kinases

PTEN

Phosphatase and tensin homolog deleted in chromosome 10

RCC

Renal cell carcinoma

ROS

Reactive oxygen species

SM

Sphingomyelin

STF-31

4-[[[[4-(1,1-Dimethylethyl)phenyl]sulfonyl]amino]methyl]-N-3-pyridinyl-benzamide

TALDO

Transaldolase

TKT

Transketolase

TSC2

Tuberous sclerosis 2

VEGFR

Vascular endothelial growth factor receptor

VHL

Von Hippel-Lindau tumor suppressor gene

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

References

  1. 1.
    Jemal, A., et al. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61(2), 69–90.Google Scholar
  2. 2.
    Siegel, R. L., Miller, K. D., & Jemal, A. (2017). Cancer statistics, 2017. CA: A Cancer Journal for Clinicians, 67(1), 7–30.Google Scholar
  3. 3.
    GBD 2015 Mortality and Causes of Death Collaborators. (2016). Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: A systematic analysis for the global burden of disease study 2015. Lancet, 388(10053), 1459–1544.CrossRefGoogle Scholar
  4. 4.
    Global Burden of Disease Liver Cancer Collaboration. (2017). The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national Level: Results from the global burden of disease study 2015. JAMA Oncology, 3(12), 1683–1691.CrossRefGoogle Scholar
  5. 5.
    Gu, F. L., et al. (1991). Cellular origin of renal cell carcinoma—an immunohistological study on monoclonal antibodies. Scandinavian Journal of Urology and Nephrology. Supplementum, 138, 203–206.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Sudarshan, S., et al. (2013). Metabolism of kidney cancer: From the lab to clinical practice. European Urology, 63(2), 244–251.CrossRefPubMedGoogle Scholar
  7. 7.
    Rini, B. I., Campbell, S. C., & Escudier, B. (2009). Renal cell carcinoma. Lancet, 373(9669), 1119–1132.CrossRefPubMedGoogle Scholar
  8. 8.
    Nickerson, M. L., et al. (2008). Improved identification of von Hippel-Lindau gene alterations in clear cell renal tumors. Clinical Cancer Research, 14(15), 4726–4734.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Sato, Y., et al. (2013). Integrated molecular analysis of clear-cell renal cell carcinoma. Nature Genetics, 45(8), 860–867.CrossRefPubMedGoogle Scholar
  10. 10.
    Czyzyk-Krzeska, M. F., & Meller, J. (2004). von Hippel-Lindau tumor suppressor: Not only HIF’s executioner. Trends in Molecular Medicine, 10(4), 146–149.CrossRefPubMedGoogle Scholar
  11. 11.
    Gordan, J. D., Thompson, C. B., & Simon, M. C. (2007). HIF and c-Myc: Sibling rivals for control of cancer cell metabolism and proliferation. Cancer Cell, 12(2), 108–113.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Stubbs, M., & Griffiths, J. R. (2010). The altered metabolism of tumors: HIF-1 and its role in the Warburg effect. Advances in Enzyme Regulation, 50(1), 44–55.CrossRefPubMedGoogle Scholar
  13. 13.
    Semenza, G. L. (2007). HIF-1 mediates the Warburg effect in clear cell renal carcinoma. Journal of Bioenergetics and Biomembranes, 39(3), 231–234.CrossRefPubMedGoogle Scholar
  14. 14.
    Pinthus, J. H., et al. (2011). Metabolic features of clear-cell renal cell carcinoma: Mechanisms and clinical implications. Canadian Urological Association Journal, 5(4), 274–282.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Cancer Genome Atlas Research Network. (2013). Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature, 499(7456), 43–49.CrossRefGoogle Scholar
  16. 16.
    Rini, B. I., & Atkins, M. B. (2009). Resistance to targeted therapy in renal-cell carcinoma. The Lancet Oncology, 10(10), 992–1000.CrossRefPubMedGoogle Scholar
  17. 17.
    Gameiro, P. A., et al. (2013). In vivo HIF-mediated reductive carboxylation is regulated by citrate levels and sensitizes VHL-deficient cells to glutamine deprivation. Cell Metabolism, 17(3), 372–385.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Jang, Y., et al. (2015). Suppression of mitochondrial respiration with auraptene inhibits the progression of renal cell carcinoma: Involvement of HIF-1alpha degradation. Oncotarget, 6, 38127.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Chan, D. A., et al. (2011). Targeting GLUT1 and the Warburg effect in renal cell carcinoma by chemical synthetic lethality. Science Translational Medicine, 3(94), 94ra70.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Yang, Y., et al. (2010). UOK 262 cell line, fumarate hydratase deficient (FH-/FH-) hereditary leiomyomatosis renal cell carcinoma: In vitro and in vivo model of an aberrant energy metabolic pathway in human cancer. Cancer Genetics and Cytogenetics, 196(1), 45–55.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Tong, W. H., et al. (2011). The glycolytic shift in fumarate-hydratase-deficient kidney cancer lowers AMPK levels, increases anabolic propensities and lowers cellular iron levels. Cancer Cell, 20(3), 315–327.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Xie, H., et al. (2009). LDH-A inhibition, a therapeutic strategy for treatment of hereditary leiomyomatosis and renal cell cancer. Molecular Cancer Therapeutics, 8(3), 626–635.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Liu, J., et al. (2013). Metformin inhibits renal cell carcinoma in vitro and in vivo xenograft. Urologic Oncology, 31(2), 264–270.CrossRefPubMedGoogle Scholar
  24. 24.
    Saito, K., et al. (2016). Lipidomic signatures and associated transcriptomic profiles of clear cell renal cell carcinoma. Scientific Reports, 6, 28932.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Fagone, P., & Jackowski, S. (2013). Phosphatidylcholine and the CDP-choline cycle. Biochimica et Biophysica Acta, 1831(3), 523–532.CrossRefPubMedGoogle Scholar
  26. 26.
    Vance, J. E., & Tasseva, G. (2013). Formation and function of phosphatidylserine and phosphatidylethanolamine in mammalian cells. Biochimica et Biophysica Acta, 1831(3), 543–554.CrossRefPubMedGoogle Scholar
  27. 27.
    Vance, J. E. (2008). Phosphatidylserine and phosphatidylethanolamine in mammalian cells: Two metabolically related aminophospholipids. Journal of Lipid Research, 49(7), 1377–1387.CrossRefPubMedGoogle Scholar
  28. 28.
    Farine, L., & Butikofer, P. (2013). The ins and outs of phosphatidylethanolamine synthesis in Trypanosoma brucei. Biochimica et Biophysica Acta, 1831(3), 533–542.CrossRefPubMedGoogle Scholar
  29. 29.
    Barcelo-Coblijn, G., et al. (2011). Sphingomyelin and sphingomyelin synthase (SMS) in the malignant transformation of glioma cells and in 2-hydroxyoleic acid therapy. Proceedings of the National Academy of Sciences of the United States of America, 108(49), 19569–19574.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Ding, T., et al. (2008). SMS overexpression and knockdown: Impact on cellular sphingomyelin and diacylglycerol metabolism, and cell apoptosis. Journal of Lipid Research, 49(2), 376–385.CrossRefPubMedGoogle Scholar
  31. 31.
    Catchpole, G., et al. (2011). Metabolic profiling reveals key metabolic features of renal cell carcinoma. Journal of Cellular and Molecular Medicine, 15(1), 109–118.CrossRefPubMedGoogle Scholar
  32. 32.
    Menendez, J. A., & Lupu, R. (2007). Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nature Reviews Cancer, 7(10), 763–777.CrossRefPubMedGoogle Scholar
  33. 33.
    Ham, A. J., & Liebler, D. C. (1997). Antioxidant reactions of vitamin E in the perfused rat liver: Product distribution and effect of dietary vitamin E supplementation. Archives of Biochemistry and Biophysics, 339(1), 157–164.CrossRefPubMedGoogle Scholar
  34. 34.
    Llovet, J. M., et al. (2016). Hepatocellular carcinoma. Nature Reviews Disease Primers, 2, 16018.CrossRefPubMedGoogle Scholar
  35. 35.
    Theise, N. D., et al. (2010). In F. T. Bosman et al. (Eds.), Hepatocellular carcinoma in WHO classification of tumor of the digestive system. Lyon, France: International Agency for Research on Cancer.Google Scholar
  36. 36.
    Forner, A., Llovet, J. M., & Bruix, J. (2012). Hepatocellular carcinoma. Lancet, 379(9822), 1245–1255.CrossRefPubMedGoogle Scholar
  37. 37.
    Zucman-Rossi, J., et al. (2015). Genetic landscape and biomarkers of hepatocellular carcinoma. Gastroenterology, 149(5), 1226–1239.e4.CrossRefPubMedGoogle Scholar
  38. 38.
    Schulze, K., Nault, J.-C., & Villanueva, A. (2016). Genetic profiling of hepatocellular carcinoma using next-generation sequencing. Journal of Hepatology, 65(5), 1031–1042.CrossRefPubMedGoogle Scholar
  39. 39.
    Bobrovnikova-Marjon, E., & Hurov, J. B. (2014). Targeting metabolic changes in cancer: Novel therapeutic approaches. Annual Review of Medicine, 65, 157–170.CrossRefPubMedGoogle Scholar
  40. 40.
    Wolpaw, A. J., & Dang, C. V. (2018). Exploiting metabolic vulnerabilities of cancer with precision and accuracy. Trends in Cell Biology, 28, 201.CrossRefPubMedGoogle Scholar
  41. 41.
    Ally, A., et al. (2017). Comprehensive and integrative genomic characterization of hepatocellular carcinoma. Cell, 169(7), 1327–1341.e23.CrossRefGoogle Scholar
  42. 42.
    Calderaro, J., et al. (2017). Histological subtypes of hepatocellular carcinoma are related to gene mutations and molecular tumour classification. Journal of Hepatology, 67(4), 727–738.CrossRefPubMedGoogle Scholar
  43. 43.
    Zheng, H., et al. (2018). Single cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma. Hepatology.  https://doi.org/10.1002/hep.29778.
  44. 44.
    Xue, R., et al. (2016). Variable intra-tumor genomic heterogeneity of multiple lesions in patients with hepatocellular carcinoma. Gastroenterology, 150(4), 998–1008.CrossRefPubMedGoogle Scholar
  45. 45.
    Lin, D. C., et al. (2017). Genomic and epigenomic heterogeneity of hepatocellular carcinoma. Cancer Research, 77(9), 2255–2265.CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Yuneva, M. O., et al. (2012). The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metabolism, 15(2), 157–170.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Wise, D. R., et al. (2008). Myc regulates a transcriptional program that stimulates mitochondrial glutaminolysis and leads to glutamine addiction. Proceedings of the National Academy of Sciences of the United States of America, 105(48), 18782–18787.CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Xu, P., et al. (2016). LRH-1-dependent programming of mitochondrial glutamine processing drives liver cancer. Genes & Development, 30(11), 1255–1260.CrossRefGoogle Scholar
  49. 49.
    Laplante, M., & Sabatini, D. M. (2012). mTOR signaling in growth control and disease. Cell, 149(2), 274–293.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Hu, H., et al. (2017). Acetylation of PGK1 promotes liver cancer cell proliferation and tumorigenesis. Hepatology, 65(2), 515–528.CrossRefPubMedGoogle Scholar
  51. 51.
    Dang, C. V., Le, A., & Gao, P. (2009). MYC-induced cancer cell energy metabolism and therapeutic opportunities. Clinical Cancer Research, 15(21), 6479–6483.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Dang, C. V. (2010). Rethinking the Warburg effect with Myc micromanaging glutamine metabolism. Cancer Research, 70(3), 859–862.CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Hur, W., et al. (2017). Systems approach to characterize the metabolism of liver cancer stem cells expressing CD133. Scientific Reports, 7, 45557.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PathologyJohns Hopkins University School of MedicineBaltimoreUSA
  2. 2.Department of Pathology and OncologyJohns Hopkins University School of MedicineBaltimoreUSA

Personalised recommendations

Cite chapter

Buy options