The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Exogenous lipids promote the growth of breast cancer cells via CD36
Open accessAbstract
Cancer cells present sustained de novo fatty acid (FA) synthesis with increased production of saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs). This change in FA metabolism is associated with overexpression of stearoyl-CoA desaturase 1 (SCD1), which catalyses the transformation of SFAs into MUFAs (e.g., oleic acid). In this study, we provide new evidence that SCD1 inhibition leads to the anti-proliferation effect of breast cancer cells through induction of apoptosis, cell cycle arrest and migration prevention. However, the antitumor effect of the SCD1 inhibitor can be reversed by exogenous oleic acid. We hypothesize that, in addition to de novo synthesis, cancer cells may uptake exogenous FAs actively. CD36, also known as FA translocase (FAT), that functions as a transmembrane protein and mediates the uptake of FAs, is observed to be highly expressed in breast cancer tissues. Furthermore, the anti-proliferation effect caused by the SCD1 inhibitor can not be reversed by exogenous oleic acid supplementation in CD36 knockdown breast cancer cells. Our study revealed that the lipid metabolism of breast cancer is regulated not only by de novo lipogenesis but also by the availability of lipids outside cancer cells. Consistent with FA synthesis, FA uptake and transport will be another important target pathway for anticancer therapy, and the FA channel protein CD36 may provide a promising therapeutic target. Lipogenesis combined with FA transport will be a new orientation for antitumor therapy.
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Cites
Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012
Ferlay, J., Soerjomataram, I., Dikshit, R., Eser, S., Mathers, C., Rebelo, M., Parkin, D. M., Forman, D., & Bray, F. (2015) · International Journal of Cancer · doi:10.1002/ijc.29210 · Cited by 28,766
Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis
Menendez, J. A., & Lupu, R. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2222 · Cited by 2,941 · cited 1×
“In addition, FAs can also be used to produce protumorigenic signaling lipids and be used for mitchondrial β-oxidation to produce ATP (4).”
BackgroundCoburn, C. T., Knapp, F. F., Febbraio, M., Beets, A. L., Silverstein, R. L., & Abumrad, N. A. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.m003826200 · Cited by 726
Lipoprotein lipase links dietary fat to solid tumor cell proliferation
Kuemmerle, N. B., Rysman, E., Lombardo, P. S., Flanagan, A. J., Lipe, B. C., Wells, W. A., Pettus, J. R., Froehlich, H. M., Memoli, V. A., Morganelli, P. M., et al. (2011) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-10-0802 · Cited by 286
Cited by
Lipid metabolism reprogramming and its potential targets in cancer
Cheng, C., Geng, F., Cheng, X., & Guo, D. (2018) · Cancer Communications · doi:10.1186/s40880-018-0301-4 · Cited by 850
Lipid metabolism in cancer: New perspectives and emerging mechanisms
Broadfield, L. A., Pane, A. A., Talebi, A., Swinnen, J. V., & Fendt, S.-M. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.04.013 · Cited by 758
Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention
Butler, L. M., Perone, Y., Dehairs, J., Lupien, L. E., de Laat, V., Talebi, A., Loda, M., Kinlaw, W. B., & Swinnen, J. V. (2020) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2020.07.013 · Cited by 589
Lipids in the tumor microenvironment: From cancer progression to treatment
Corn, K. C., Windham, M. A., & Rafat, M. (2020) · Progress in Lipid Research · doi:10.1016/j.plipres.2020.101055 · Cited by 469
Glatz, J. C., & Luiken, J. F. P. (2018) · Journal of Lipid Research · doi:10.1194/jlr.r082933 · Cited by 299
Metadata
- Authors
- Zhao, J., Zhi, Z., Wang, C., Xing, H., Song, G., Yu, X., Zhu, Y., Wang, X., Zhang, X., & Di, Y.
- Venue
- Oncology Reports
- Publisher
- Spandidos Publications
- Published
- 2017-04
- Volume
- 38
- Issue
- 4
- Pages
- 2105-2115
- ISSN
- 1021-335X (ISSN-L)
- 1791-2431
- OpenAlex
- W2741826106
- Cited by
- 182
- References
- 4
- FWCI
- 4.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zhao, J., Zhi, Z., Wang, C., Xing, H., Song, G., Yu, X., Zhu, Y., Wang, X., Zhang, X., & Di, Y. (2017). Exogenous lipids promote the growth of breast cancer cells via CD36. Oncology Reports. https://doi.org/10.3892/or.2017.5864
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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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