The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
A metabolic prosurvival role for PML in breast cancer
Open accessAbstract
Cancer cells exhibit an aberrant metabolism that facilitates more efficient production of biomass and hence tumor growth and progression. However, the genetic cues modulating this metabolic switch remain largely undetermined. We identified a metabolic function for the promyelocytic leukemia (PML) gene, uncovering an unexpected role for this bona fide tumor suppressor in breast cancer cell survival. We found that PML acted as both a negative regulator of PPARγ coactivator 1A (PGC1A) acetylation and a potent activator of PPAR signaling and fatty acid oxidation. We further showed that PML promoted ATP production and inhibited anoikis. Importantly, PML expression allowed luminal filling in 3D basement membrane breast culture models, an effect that was reverted by the pharmacological inhibition of fatty acid oxidation. Additionally, immunohistochemical analysis of breast cancer biopsies revealed that PML was overexpressed in a subset of breast cancers and enriched in triple-negative cases. Indeed, PML expression in breast cancer correlated strikingly with reduced time to recurrence, a gene signature of poor prognosis, and activated PPAR signaling. These findings have important therapeutic implications, as PML and its key role in fatty acid oxidation metabolism are amenable to pharmacological suppression, a potential future mode of cancer prevention and treatment.
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
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
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
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
Nutrient control of glucose homeostasis through a complex of PGC-1α and SIRT1
Rodgers, J. T., Lerin, C., Haas, W., Gygi, S. P., Spiegelman, B. M., & Puigserver, P. (2005) · Nature · doi:10.1038/nature03354 · Cited by 3,160
Self-citationCrucial role of p53-dependent cellular senescence in suppression of Pten-deficient tumorigenesis
Chen, Z., Trotman, L. C., Shaffer, D., Lin, H.-K., Dotan, Z. A., Niki, M., Koutcher, J. A., Scher, H. I., Ludwig, T., Gerald, W., et al. (2005) · Nature · doi:10.1038/nature03918 · Cited by 1,993
Metabolic control of muscle mitochondrial function and fatty acid oxidation through SIRT1/PGC‐1α
Gerhart‐Hines, Z., Rodgers, J. T., Bare, O., Lerin, C., Kim, S., Mostoslavsky, R., Alt, F. W., Wu, Z., & Puigserver, P. (2007) · The EMBO Journal · doi:10.1038/sj.emboj.7601633 · Cited by 1,294
Self-citationDefects in Adaptive Energy Metabolism with CNS-Linked Hyperactivity in PGC-1α Null Mice
Lin, J., Wu, P.-H., Tarr, P. T., Lindenberg, K. S., St-Pierre, J., Zhang, C.-Y., Mootha, V. K., Jäger, S., Vianna, C. R., Reznick, R. M., et al. (2004) · Cell · doi:10.1016/j.cell.2004.09.013 · Cited by 1,162
Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment
Schafer, Z. T., Grassian, A. R., Song, L., Jiang, Z., Gerhart-Hines, Z., Irie, H. Y., Gao, S., Puigserver, P., & Brugge, J. S. (2009) · Nature · doi:10.1038/nature08268 · Cited by 1,031
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Metabolic requirements for the maintenance of self-renewing stem cells
Ito, K., & Suda, T. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3772 · Cited by 1,014
Self-citationLipids 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
Induction of autophagy supports the bioenergetic demands of quiescent muscle stem cell activation
Tang, A. H., & Rando, T. A. (2014) · The EMBO Journal · doi:10.15252/embj.201488278 · Cited by 294
Metabolic reprogramming in triple-negative breast cancer
Wang, Z., Jiang, Q., & Dong, C. (2020) · Cancer Biology and Medicine · doi:10.20892/j.issn.2095-3941.2019.0210 · Cited by 248
“…receptor gamma coactivator 1-alpha (PGC1-α ), the master regulator of mitochondria biogenesis and respiration 74 , which activates FAO to promote energy homeostasis and cell viability, especially under attachment loss or metabolic stress, thus promoting the metastasis of TNBC 77 .”
BackgroundZaytseva, Y. Y., Harris, J. W., Mitov, M. I., Kim, J. T., Butterfield, D. A., Lee, E. Y., Weiss, H. L., Gao, T., & Evers, B. M. (2015) · Oncotarget · doi:10.18632/oncotarget.3783 · Cited by 153
Metadata
- Authors
- Carracedo, A., Weiss, D., Leliaert, A. K., Bhasin, M., de Boer, V. C. J., Laurent, G., Adams, A. C., Sundvall, M., Song, S. J., Ito, K., Finley, L. S., Egia, A., Libermann, T., Gerhart-Hines, Z., Puigserver, P., Haigis, M. C., Maratos-Flier, E., Richardson, A. L., Schafer, Z. T., & Pandolfi, P. P.
- Venue
- Journal of Clinical Investigation
- Published
- 2012-09-04
- Volume
- 122
- Issue
- 9
- Pages
- 3088-3100
- ISSN
- 0021-9738 (ISSN-L)
- OpenAlex
- W2037209340
- Cited by
- 269
- References
- 14
- FWCI
- 6.22
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Carracedo, A., Weiss, D., Leliaert, A. K., Bhasin, M., de Boer, V. C. J., Laurent, G., Adams, A. C., Sundvall, M., Song, S. J., Ito, K., Finley, L. S., Egia, A., Libermann, T., Gerhart-Hines, Z., Puigserver, P., Haigis, M. C., Maratos-Flier, E., Richardson, A. L., Schafer, Z. T., & Pandolfi, P. P. (2012). A metabolic prosurvival role for PML in breast cancer. Journal of Clinical Investigation. https://doi.org/10.1172/jci62129
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
