The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Anticancer Agents That Counteract Tumor Glycolysis
Open accessAbstract
Can we consider cancer to be a “metabolic disease”? Tumors are the result of a metabolic selection, forming tissues composed of heterogeneous cells that generally express an overactive metabolism as a common feature. In fact, cancer cells have increased needs for both energy and biosynthetic intermediates to support their growth and invasiveness. However, their high proliferation rate often generates regions that are insufficiently oxygenated. Therefore, their carbohydrate metabolism must rely mostly on a glycolytic process that is uncoupled from oxidative phosphorylation. This metabolic switch, also known as the Warburg effect, constitutes a fundamental adaptation of tumor cells to a relatively hostile environment, and supports the evolution of aggressive and metastatic phenotypes. As a result, tumor glycolysis may constitute an attractive target for cancer therapy. This approach has often raised concerns that antiglycolytic agents may cause serious side effects toward normal cells. The key to selective action against cancer cells can be found in their hyperbolic addiction to glycolysis, which may be exploited to generate new anticancer drugs with minimal toxicity. There is growing evidence to support many glycolytic enzymes and transporters as suitable candidate targets for cancer therapy. Herein we review some of the most relevant antiglycolytic agents that have been investigated thus far for the treatment of cancer.
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Cites
Regulation of cancer cell metabolism
Cairns, R. A., Harris, I. S., & Mak, T. W. (2011) · Nature Reviews Cancer · doi:10.1038/nrc2981 · Cited by 4,744
Kim, J.-W., Tchernyshyov, I., Semenza, G. L., & Dang, C. V. (2006) · Cell Metabolism · doi:10.1016/j.cmet.2006.02.002 · Cited by 3,905
The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth
Christofk, H. R., Vander Heiden, M. G., Harris, M. H., Ramanathan, A., Gerszten, R. E., Wei, R., Fleming, M. D., Schreiber, S. L., & Cantley, L. C. (2008) · Nature · doi:10.1038/nature06734 · Cited by 2,820
Tumor cell metabolism: cancer's Achilles' heel
Kroemer, G., & Pouyssegur, J. (2008) · Cancer Cell · doi:10.1016/j.ccr.2008.05.005 · Cited by 2,337
Insulin and insulin-like growth factor signalling in neoplasia
Pollak, M. (2008) · Nature Reviews Cancer · doi:10.1038/nrc2536 · Cited by 2,059
IDH mutation impairs histone demethylation and results in a block to cell differentiation
Lu, C., Ward, P. S., Kapoor, G. S., Rohle, D., Turcan, S., Abdel-Wahab, O., Edwards, C. R., Khanin, R., Figueroa, M. E., Melnick, A., et al. (2012) · Nature · doi:10.1038/nature10860 · Cited by 1,985
Hypoxia, HIF1 and glucose metabolism in the solid tumour
Denko, N. C. (2008) · Nature Reviews Cancer · doi:10.1038/nrc2468 · Cited by 1,707
Fantin, V. R., St-Pierre, J., & Leder, P. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.04.023 · Cited by 1,635
c-Myc transactivation of LDH-A : Implications for tumor metabolism and growth
Shim, H., Dolde, C., Lewis, B. C., Wu, C.-S., Dang, G., Jungmann, R. A., Dalla-Favera, R., & Dang, C. V. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.13.6658 · Cited by 1,092
Isozymes of mammalian hexokinase: structure, subcellular localization and metabolic function
Wilson, J. E. (2003) · Journal of Experimental Biology · doi:10.1242/jeb.00241 · Cited by 1,085
Cited by
Eelen, G., de Zeeuw, P., Treps, L., Harjes, U., Wong, B. W., & Carmeliet, P. (2018) · Physiological Reviews · doi:10.1152/physrev.00001.2017 · Cited by 572
Glucose Conjugation for the Specific Targeting and Treatment of Cancer
Calvaresi, E. C., & Hergenrother, P. J. (2013) · Chemical Science · doi:10.1039/c3sc22205e · Cited by 398
The metabolic landscape of lung cancer: New insights in a disturbed glucose metabolism
Vanhove, K., Graulus, G.-J., Mesotten, L., Thomeer, M., Derveaux, E., Noben, J.-P., Guedens, W., & Adriaensens, P. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.01215 · Cited by 147
New drugs are not enough‑drug repositioning in oncology: An update
Armando, R., Mengual G�mez, D., & Gomez, D. (2020) · International Journal of Oncology · doi:10.3892/ijo.2020.4966 · Cited by 90
Targeting endothelial metabolism for anti-angiogenesis therapy: A pharmacological perspective
Missiaen, R., Morales-Rodriguez, F., Eelen, G., & Carmeliet, P. (2017) · Vascular Pharmacology · doi:10.1016/j.vph.2017.01.001 · Cited by 58
Metadata
- Authors
- Granchi, C., & Minutolo, F.
- Venue
- ChemMedChem
- Publisher
- Wiley
- Published
- 2012-06-08
- Volume
- 7
- Issue
- 8
- Pages
- 1318-1350
- ISSN
- 1860-7179 (ISSN-L)
- 1860-7187
- OpenAlex
- W2031299955
- Cited by
- 166
- References
- 22
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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