The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Squalene accumulation in cholesterol auxotrophic lymphomas prevents oxidative cell death
Open accessAbstract
Cholesterol is essential for cells to grow and proliferate. Normal mammalian cells meet their need for cholesterol through its uptake or de novo synthesis1, but the extent to which cancer cells rely on each of these pathways remains poorly understood. Here, using a competitive proliferation assay on a pooled collection of DNA-barcoded cell lines, we identify a subset of cancer cells that is auxotrophic for cholesterol and thus highly dependent on its uptake. Through metabolic gene expression analysis, we pinpoint the loss of squalene monooxygenase expression as a cause of cholesterol auxotrophy, particularly in ALK+ anaplastic large cell lymphoma (ALCL) cell lines and primary tumours. Squalene monooxygenase catalyses the oxidation of squalene to 2,3-oxidosqualene in the cholesterol synthesis pathway and its loss results in accumulation of the upstream metabolite squalene, which is normally undetectable. In ALK+ ALCLs, squalene alters the cellular lipid profile and protects cancer cells from ferroptotic cell death, providing a growth advantage under conditions of oxidative stress and in tumour xenografts. Finally, a CRISPR-based genetic screen identified cholesterol uptake by the low-density lipoprotein receptor as essential for the growth of ALCL cells in culture and as patient-derived xenografts. This work reveals that the cholesterol auxotrophy of ALCLs is a targetable liability and, more broadly, that systematic approaches can be used to identify nutrient dependencies unique to individual cancer types. The authors find that loss of squalene monooxygenase expression alters the lipid metabolism of cancer cells, which confers protection from ferroptotic cell death and thus promotes tumour growth.
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Cites
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Regulation of Ferroptotic Cancer Cell Death by GPX4
Yang, W. S., SriRamaratnam, R., Welsch, M. E., Shimada, K., Skouta, R., Viswanathan, V. S., Cheah, J. H., Clemons, P. A., Shamji, A. F., Clish, C. B., et al. (2014) · Cell · doi:10.1016/j.cell.2013.12.010 · Cited by 7,713
Regulation of the mevalonate pathway
Goldstein, J. L., & Brown, M. S. (1990) · Nature · doi:10.1038/343425a0 · Cited by 5,394
Inactivation of the ferroptosis regulator Gpx4 triggers acute renal failure in mice
Friedmann Angeli, J. P., Schneider, M., Proneth, B., Tyurina, Y. Y., Tyurin, V. A., Hammond, V. J., Herbach, N., Aichler, M., Walch, A., Eggenhofer, E., et al. (2014) · Nature Cell Biology · doi:10.1038/ncb3064 · Cited by 3,732
Xu, W., Yang, H., Liu, Y., Yang, Y., Wang, P., Kim, S.-H., Ito, S., Yang, C., Wang, P., Xiao, M.-T., et al. (2011) · Cancer Cell · doi:10.1016/j.ccr.2010.12.014 · Cited by 2,875
Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition
Hangauer, M. J., Viswanathan, V. S., Ryan, M. J., Bole, D., Eaton, J. K., Matov, A., Galeas, J., Dhruv, H. D., Berens, M. E., Schreiber, S. L., et al. (2017) · Nature · doi:10.1038/nature24297 · Cited by 1,799
Isaacs, J. S., Jung, Y. J., Mole, D. R., Lee, S., Torres-Cabala, C., Chung, Y.-L., Merino, M., Trepel, J., Zbar, B., Toro, J., et al. (2005) · Cancer Cell · doi:10.1016/j.ccr.2005.06.017 · Cited by 958
NFS1 undergoes positive selection in lung tumours and protects cells from ferroptosis
Alvarez, S. W., Sviderskiy, V. O., Terzi, E. M., Papagiannakopoulos, T., Moreira, A. L., Adams, S., Sabatini, D. M., Birsoy, K., & Possemato, R. (2017) · Nature · doi:10.1038/nature24637 · Cited by 787
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Letouzé, E., Martinelli, C., Loriot, C., Burnichon, N., Abermil, N., Ottolenghi, C., Janin, M., Menara, M., Nguyen, A. T., Benit, P., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.04.018 · Cited by 776
Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides
Birsoy, K., Possemato, R., Lorbeer, F. K., Bayraktar, E. C., Thiru, P., Yucel, B., Wang, T., Chen, W. W., Clish, C. B., & Sabatini, D. M. (2014) · Nature · doi:10.1038/nature13110 · Cited by 710
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Metadata
- Authors
- Garcia-Bermudez, J., Baudrier, L., Bayraktar, E. C., Shen, Y., La, K., Guarecuco, R., Yucel, B., Fiore, D., Tavora, B., Freinkman, E., Chan, S. H., Lewis, C., Min, W., Inghirami, G., Sabatini, D. M., & Birsoy, K.
- Venue
- Nature
- Published
- 2019-02-13
- Volume
- 567
- Issue
- 7746
- Pages
- 118-122
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2911647752
- Cited by
- 424
- References
- 14
- FWCI
- 12.79
- Type
- journal article
- Language
- en
- Open access
- green
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- Garcia-Bermudez, J., Baudrier, L., Bayraktar, E. C., Shen, Y., La, K., Guarecuco, R., Yucel, B., Fiore, D., Tavora, B., Freinkman, E., Chan, S. H., Lewis, C., Min, W., Inghirami, G., Sabatini, D. M., & Birsoy, K. (2019). Squalene accumulation in cholesterol auxotrophic lymphomas prevents oxidative cell death. Nature. https://doi.org/10.1038/s41586-019-0945-5
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