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Anti-tumor Activity of the Type I PRMT Inhibitor, GSK3368715, Synergizes with PRMT5 Inhibition through MTAP Loss
Open accessAbstract
Type I protein arginine methyltransferases (PRMTs) catalyze asymmetric dimethylation of arginines on proteins. Type I PRMTs and their substrates have been implicated in human cancers, suggesting inhibition of type I PRMTs may offer a therapeutic approach for oncology. The current report describes GSK3368715 (EPZ019997), a potent, reversible type I PRMT inhibitor with anti-tumor effects in human cancer models. Inhibition of PRMT5, the predominant type II PRMT, produces synergistic cancer cell growth inhibition when combined with GSK3368715. Interestingly, deletion of the methylthioadenosine phosphorylase gene (MTAP) results in accumulation of the metabolite 2-methylthioadenosine, an endogenous inhibitor of PRMT5, and correlates with sensitivity to GSK3368715 in cell lines. These data provide rationale to explore MTAP status as a biomarker strategy for patient selection.
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The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484
Skyline: an open source document editor for creating and analyzing targeted proteomics experiments
MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., & MacCoss, M. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq054 · Cited by 4,697
RSeQC: quality control of RNA-seq experiments
Wang, L., Wang, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts356 · Cited by 2,788
Shen, S., Park, J. W., Lu, Z.-X., Lin, L., Henry, M. D., Wu, Y. N., Zhou, Q., & Xing, Y. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419161111 · Cited by 2,713
Protein Arginine Methylation in Mammals: Who, What, and Why
Bedford, M. T., & Clarke, S. G. (2009) · Molecular Cell · doi:10.1016/j.molcel.2008.12.013 · Cited by 1,792
EZH2 inhibition as a therapeutic strategy for lymphoma with EZH2-activating mutations
McCabe, M. T., Ott, H. M., Ganji, G., Korenchuk, S., Thompson, C., Van Aller, G. S., Liu, Y., Graves, A. P., III, A. D. P., Diaz, E., et al. (2012) · Nature · doi:10.1038/nature11606 · Cited by 1,786
Self-citationHulsen, T., de Vlieg, J., & Alkema, W. (2008) · BMC Genomics · doi:10.1186/1471-2164-9-488 · Cited by 1,674
Analysis of drug combinations: current methodological landscape
Foucquier, J., & Guedj, M. (2015) · Pharmacology Research & Perspectives · doi:10.1002/prp2.149 · Cited by 1,115
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Pappalardi, M. B., Keenan, K., Cockerill, M., Kellner, W. A., Stowell, A., Sherk, C., Wong, K., Pathuri, S., Briand, J., Steidel, M., et al. (2021) · Nature Cancer · doi:10.1038/s43018-021-00249-x · Cited by 283
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Metadata
- Authors
- Fedoriw, A., Rajapurkar, S. R., O'Brien, S., Gerhart, S. V., Mitchell, L. H., Adams, N. D., Rioux, N., Lingaraj, T., Ribich, S. A., Pappalardi, M. B., Shah, N., Laraio, J., Liu, Y., Butticello, M., Carpenter, C. L., Creasy, C., Korenchuk, S., McCabe, M. T., McHugh, C. F., Nagarajan, R., Wagner, C., Zappacosta, F., Annan, R., Concha, N. O., Thomas, R. A., Hart, T. K., Smith, J. J., Copeland, R. A., Moyer, M. P., Campbell, J., Stickland, K., Mills, J., Jacques-O’Hagan, S., Allain, C., Johnston, D., Raimondi, A., Porter Scott, M., Waters, N., Swinger, K., Boriack-Sjodin, A., Riera, T., Shapiro, G., Chesworth, R., Prinjha, R. K., Kruger, R. G., Barbash, O., & Mohammad, H. P.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 36
- Issue
- 1
- Pages
- 100-114.e25
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W2954328834
- Cited by
- 339
- References
- 48
- FWCI
- 9.31
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Anti-tumor Activity of the Type I PRMT Inhibitor, GSK3368715, Synergizes with PRMT5 Inhibition through MTAP Loss. https://app.cochat.ai/papers/10.1016/j.ccell.2019.05.014
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- Fedoriw, A., Rajapurkar, S. R., O'Brien, S., Gerhart, S. V., Mitchell, L. H., Adams, N. D., Rioux, N., Lingaraj, T., Ribich, S. A., Pappalardi, M. B., Shah, N., Laraio, J., Liu, Y., Butticello, M., Carpenter, C. L., Creasy, C., Korenchuk, S., McCabe, M. T., McHugh, C. F., . . . Mohammad, H. P. (2019). Anti-tumor Activity of the Type I PRMT Inhibitor, GSK3368715, Synergizes with PRMT5 Inhibition through MTAP Loss. Cancer Cell. https://doi.org/10.1016/j.ccell.2019.05.014
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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.