Abstract
Despite advances in screening, therapy, and surveillance that have improved survival rates, breast cancer is still the most commonly diagnosed cancer and the second leading cause of cancer mortality among women [1]. Breast cancer is a highly heterogeneous disease rooted in a genetic basis and reflected in clinical behavior. The diversity of breast cancer hormone receptor status and the expression of surface molecules has guided therapy decisions for decades; however, subtype-specific treatment often yields diverse responses due to varying tumor evolution and malignant potential. Although understanding the mechanisms behind breast cancer heterogeneity is still a challenge, available evidence suggests that studying its metabolism has the potential to give valuable insight into the causes of these variations, as well as viable targets for intervention.
Abbreviations
- 3HP:
-
3-Phosphohydroxypyruvate
- 3PG:
-
3-Phosphoglycerate
- αKG:
-
Alpha-ketoglutarate
- CK:
-
Choline kinase
- COMT:
-
Catechol-O-methyltransferase
- D-2HG:
-
D-2-hydroxyglutarate
- E2:
-
17b-Estradiol
- ER:
-
Estrogen receptor
- GLUT:
-
Glucose transporter
- GSTP:
-
Glutathione S-transferase P
- HER2:
-
Human epidermal growth factor receptor 2
- PCho:
-
Phosphocholine
- PHGDH:
-
Phosphoglycerate dehydrogenase
- PR:
-
Progesterone receptor
- PSAT1:
-
Phosphoserine aminotransferase 1
- PSPH:
-
Phosphoserine phosphatase
- PtdCho:
-
Phosphatidylcholine
- TCA:
-
Tricarboxylic acid
- TNBC:
-
Triple-negative breast cancer
References
Gutierrez, T., et al. (2013). IL-21 promotes the production of anti-DNA IgG but is dispensable for kidney damage in lyn(−/−) mice. European Journal of Immunology, 43(2), 382–393.
Hu, X., et al. (2009). Genetic alterations and oncogenic pathways associated with breast cancer subtypes. Molecular Cancer Research, 7(4), 511–522.
Birnbaum, D. J., et al. (2011). Genome profiling of pancreatic adenocarcinoma. Genes, Chromosomes & Cancer, 50(6), 456–465.
Son, J., et al. (2013). Glutamine supports pancreatic cancer growth through a KRAS-regulated metabolic pathway. Nature, 496(7443), 101–105.
Lyssiotis, C. A., et al. (2013). Pancreatic cancers rely on a novel glutamine metabolism pathway to maintain redox balance. Cell Cycle, 12(13), 1987–1988.
Telang, S., et al. (2007). The oncoprotein H-RasV12 increases mitochondrial metabolism. Molecular Cancer, 6, 77.
White, E. (2013). Exploiting the bad eating habits of Ras-driven cancers. Genes & Development, 27(19), 2065–2071.
Martinez-Outschoorn, U. E., et al. (2012). BRCA1 mutations drive oxidative stress and glycolysis in the tumor microenvironment: Implications for breast cancer prevention with antioxidant therapies. Cell Cycle, 11(23), 4402–4413.
Warburg, O., Wind, F., & Negelein, E. (1927). The metabolism of tumors in the body. The Journal of General Physiology, 8(6), 519–530.
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009). Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science, 324(5930), 1029–1033.
Gatenby, R. A., & Gillies, R. J. (2004). Why do cancers have high aerobic glycolysis? Nature Reviews. Cancer, 4(11), 891–899.
Waki, A., et al. (1998). The importance of glucose transport activity as the rate-limiting step of 2-deoxyglucose uptake in tumor cells in vitro. Nuclear Medicine and Biology, 25(7), 593–597.
Choi, J., Jung, W. H., & Koo, J. S. (2013). Metabolism-related proteins are differentially expressed according to the molecular subtype of invasive breast cancer defined by surrogate immunohistochemistry. Pathobiology, 80(1), 41–52.
Grover-McKay, M., et al. (1998). Role for glucose transporter 1 protein in human breast cancer. Pathology Oncology Research, 4(2), 115–120.
Lloyd, S. M., Arnold, J., & Sreekumar, A. (2015). Metabolomic profiling of hormone-dependent cancers: A bird’s eye view. Trends in Endocrinology and Metabolism, 26(9), 477–485.
Katz-Brull, R., et al. (2002). Metabolic markers of breast cancer: Enhanced choline metabolism and reduced choline-ether-phospholipid synthesis. Cancer Research, 62(7), 1966–1970.
Eliyahu, G., Kreizman, T., & Degani, H. (2007). Phosphocholine as a biomarker of breast cancer: Molecular and biochemical studies. International Journal of Cancer, 120(8), 1721–1730.
Aboagye, E. O., & Bhujwalla, Z. M. (1999). Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Research, 59(1), 80–84.
Hilvo, M., et al. (2011). Novel theranostic opportunities offered by characterization of altered membrane lipid metabolism in breast cancer progression. Cancer Research, 71(9), 3236–3245.
Ramirez de Molina, A., et al. (2002). Increased choline kinase activity in human breast carcinomas: Clinical evidence for a potential novel antitumor strategy. Oncogene, 21(27), 4317–4322.
Rodriguez-Gonzalez, A., et al. (2004). Choline kinase inhibition induces the increase in ceramides resulting in a highly specific and selective cytotoxic antitumoral strategy as a potential mechanism of action. Oncogene, 23(50), 8247–8259.
Glunde, K., Bhujwalla, Z. M., & Ronen, S. M. (2011). Choline metabolism in malignant transformation. Nature Reviews. Cancer, 11(12), 835–848.
Fuhrman, B. J., et al. (2012). Estrogen metabolism and risk of breast cancer in postmenopausal women. Journal of the National Cancer Institute, 104(4), 326–339.
Cicatiello, L., et al. (2010). Estrogen receptor alpha controls a gene network in luminal-like breast cancer cells comprising multiple transcription factors and microRNAs. The American Journal of Pathology, 176(5), 2113–2130.
Acconcia, F., & Kumar, R. (2006). Signaling regulation of genomic and nongenomic functions of estrogen receptors. Cancer Letters, 238(1), 1–14.
Jia, M., et al. (2016). Estrogen receptor alpha promotes breast cancer by reprogramming choline metabolism. Cancer Research, 76(19), 5634–5646.
Devanesan, P., et al. (2001). Catechol estrogen conjugates and DNA adducts in the kidney of male Syrian golden hamsters treated with 4-hydroxyestradiol: Potential biomarkers for estrogen-initiated cancer. Carcinogenesis, 22(3), 489–497.
Cavalieri, E., et al. (2000). Estrogens as endogenous genotoxic agents--DNA adducts and mutations. Journal of the National Cancer Institute. Monographs, 27, 75–93.
Bradlow, H. L., et al. (1996). 2-hydroxyestrone: The ‘good’ estrogen. The Journal of Endocrinology, 150(Suppl), S259–S265.
Possemato, R., et al. (2011). Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature, 476(7360), 346–350.
Fan, J., et al. (2015). Human phosphoglycerate dehydrogenase produces the oncometabolite D-2-hydroxyglutarate. ACS Chemical Biology, 10(2), 510–516.
Rakheja, D., et al. (2013). The emerging role of d-2-hydroxyglutarate as an oncometabolite in hematolymphoid and central nervous system neoplasms. Frontiers in Oncology, 3, 169.
Terunuma, A., et al. (2014). MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis. The Journal of Clinical Investigation, 124(1), 398–412.
Yue, W., et al. (2003). Genotoxic metabolites of estradiol in breast: Potential mechanism of estradiol induced carcinogenesis. The Journal of Steroid Biochemistry and Molecular Biology, 86(3-5), 477–486.
Mullarky, E., et al. (2016). Identification of a small molecule inhibitor of 3-phosphoglycerate dehydrogenase to target serine biosynthesis in cancers. Proceedings of the National Academy of Sciences of the United States of America, 113(7), 1778–1783.
Jerby, L., et al. (2012). Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. Cancer Research, 72(22), 5712–5720.
Shen, L., et al. (2015). Metabolic reprogramming in triple-negative breast cancer through Myc suppression of TXNIP. Proceedings of the National Academy of Sciences of the United States of America, 112(17), 5425–5430.
Jove, M., et al. (2017). A plasma metabolomic signature discloses human breast cancer. Oncotarget, 8(12), 19522–19533.
Huang, S., et al. (2016). Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis. Genome Medicine, 8(1), 34.
Giskeodegard, G. F., et al. (2010). Multivariate modeling and prediction of breast cancer prognostic factors using MR metabolomics. Journal of Proteome Research, 9(2), 972–979.
Mountford, C. E., et al. (2001). Diagnosis and prognosis of breast cancer by magnetic resonance spectroscopy of fine-needle aspirates analysed using a statistical classification strategy. The British Journal of Surgery, 88(9), 1234–1240.
Asiago, V. M., et al. (2010). Early detection of recurrent breast cancer using metabolite profiling. Cancer Research, 70(21), 8309–8318.
Oakman, C., et al. (2011). Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods. Annals of Oncology, 22(6), 1295–1301.
Jobard, E., et al. (2014). A serum nuclear magnetic resonance-based metabolomic signature of advanced metastatic human breast cancer. Cancer Letters, 343(1), 33–41.
Simoes, R. V., et al. (2015). Metabolic plasticity of metastatic breast cancer cells: Adaptation to changes in the microenvironment. Neoplasia, 17(8), 671–684.
Wei, S., et al. (2013). Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer. Molecular Oncology, 7(3), 297–307.
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Tan, J., Le, A. (2018). Breast Cancer Metabolism. In: Le, A. (eds) The Heterogeneity of Cancer Metabolism. Advances in Experimental Medicine and Biology, vol 1063. Springer, Cham. https://doi.org/10.1007/978-3-319-77736-8_6
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DOI: https://doi.org/10.1007/978-3-319-77736-8_6
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