The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice
Open accessAbstract
Tumors contain oxygenated and hypoxic regions, so the tumor cell population is heterogeneous. Hypoxic tumor cells primarily use glucose for glycolytic energy production and release lactic acid, creating a lactate gradient that mirrors the oxygen gradient in the tumor. By contrast, oxygenated tumor cells have been thought to primarily use glucose for oxidative energy production. Although lactate is generally considered a waste product, we now show that it is a prominent substrate that fuels the oxidative metabolism of oxygenated tumor cells. There is therefore a symbiosis in which glycolytic and oxidative tumor cells mutually regulate their access to energy metabolites. We identified monocarboxylate transporter 1 (MCT1) as the prominent path for lactate uptake by a human cervix squamous carcinoma cell line that preferentially utilized lactate for oxidative metabolism. Inhibiting MCT1 with alpha-cyano-4-hydroxycinnamate (CHC) or siRNA in these cells induced a switch from lactate-fueled respiration to glycolysis. A similar switch from lactate-fueled respiration to glycolysis by oxygenated tumor cells in both a mouse model of lung carcinoma and xenotransplanted human colorectal adenocarcinoma cells was observed after administration of CHC. This retarded tumor growth, as the hypoxic/glycolytic tumor cells died from glucose starvation, and rendered the remaining cells sensitive to irradiation. As MCT1 was found to be expressed by an array of primary human tumors, we suggest that MCT1 inhibition has clinical antitumor potential.
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Cites
Exploiting tumour hypoxia in cancer treatment
Brown, J. M., & Wilson, W. R. (2004) · Nature Reviews Cancer · doi:10.1038/nrc1367 · Cited by 2,828
Martinive, P., Defresne, F., Bouzin, C., Saliez, J., Lair, F., Grégoire, V., Michiels, C., Dessy, C., & Feron, O. (2006) · Cancer Research · doi:10.1158/0008-5472.can-06-2056 · Cited by 190
Mathupala, S. P., Parajuli, P., & Sloan, A. E. (2004) · Neurosurgery · doi:10.1227/01.neu.0000143034.62913.59 · Cited by 147
The Effects of Endotoxin on Oxygen-Consumption of various Cell-Types In-Vitro—an EPR Oximetry Study
James, P. E., Jackson, S. K., Grinberg, O. Y., & Swartz, H. M. (1995) · Free Radical Biology and Medicine · doi:10.1016/0891-5849(94)00179-n · Cited by 70
Cited by
Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197
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
Otto Warburg's contributions to current concepts of cancer metabolism
Koppenol, W. H., Bounds, P. L., & Dang, C. V. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3038 · Cited by 3,427
Metabolic Reprogramming: A Cancer Hallmark Even Warburg Did Not Anticipate
Ward, P. S., & Thompson, C. B. (2012) · Cancer Cell · doi:10.1016/j.ccr.2012.02.014 · Cited by 3,233
Targeting hypoxia in cancer therapy
Wilson, W. R., & Hay, M. P. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3064 · Cited by 3,172
Metadata
- Authors
- Sonveaux, P., Végran, F., Schroeder, T., Wergin, M. C., Verrax, J., Rabbani, Z. N., De Saedeleer, C. J., Kennedy, K. M., Diepart, C., Jordan, B. F., Kelley, M. J., Gallez, B., Wahl, M. L., Feron, O., & Dewhirst, M. W.
- Venue
- Journal of Clinical Investigation
- Published
- 2008-11-20
- Volume
- 118
- Issue
- 12
- Pages
- 3930-42
- ISSN
- 0021-9738 (ISSN-L)
- OpenAlex
- W2017007251
- Cited by
- 1,624
- References
- 4
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- green
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- Sonveaux, P., Végran, F., Schroeder, T., Wergin, M. C., Verrax, J., Rabbani, Z. N., De Saedeleer, C. J., Kennedy, K. M., Diepart, C., Jordan, B. F., Kelley, M. J., Gallez, B., Wahl, M. L., Feron, O., & Dewhirst, M. W. (2008). Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. Journal of Clinical Investigation. https://doi.org/10.1172/jci36843
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