The DOI matches its Crossref record; 244 of the 244 references it cites were found in a registry or an index.
Advancing targeted protein degradation for cancer therapy
Open accessAbstract
The human proteome contains approximately 20,000 proteins, and it is estimated that more than 600 of them are functionally important for various types of cancers, including nearly 400 non-enzyme proteins that are challenging to target by traditional occupancy-driven pharmacology. Recent advances in the development of small-molecule degraders, including molecular glues and heterobifunctional degraders such as proteolysis-targeting chimeras (PROTACs), have made it possible to target many proteins that were previously considered undruggable. In particular, PROTACs form a ternary complex with a hijacked E3 ubiquitin ligase and a target protein, leading to polyubiquitination and degradation of the target protein. The broad applicability of this approach is facilitated by the flexibility of individual E3 ligases to recognize different substrates. The vast majority of the approximately 600 human E3 ligases have not been explored, thus presenting enormous opportunities to develop degraders that target oncoproteins with tissue, tumour and subcellular selectivity. In this Review, we first discuss the molecular basis of targeted protein degradation. We then offer a comprehensive account of the most promising degraders in development as cancer therapies to date. Lastly, we provide an overview of opportunities and challenges in this exciting field. The development of small-molecule degraders such as proteolysis-targeting chimeras (PROTACs) has made it possible to target oncoproteins previously considered undruggable. This Review discusses recent advances in the field, with a focus on opportunities and challenges for future development.
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Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Mutations of the BRAF gene in human cancer
Davies, H., Bignell, G. R., Cox, C., Stephens, P., Edkins, S., Clegg, S., Teague, J., Woffendin, H., Garnett, M. J., Bottomley, W., et al. (2002) · Nature · doi:10.1038/nature00766 · Cited by 10,674
Hershko, A., & Ciechanover, A. (1998) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.67.1.425 · Cited by 8,840
In Vivo Activation of the p53 Pathway by Small-Molecule Antagonists of MDM2
Vassilev, L. T., Vu, B. T., Graves, B., Carvajal, D., Podlaski, F., Filipovic, Z., Kong, N., Kammlott, U., Lukacs, C., Klein, C., et al. (2004) · Science · doi:10.1126/science.1092472 · Cited by 4,661
Defining a Cancer Dependency Map
Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., Gill, S., Harrington, W. F., Pantel, S., Krill-Burger, J. M., et al. (2017) · Cell · doi:10.1016/j.cell.2017.06.010 · Cited by 3,276
Mechanisms Underlying Ubiquitination
Pickart, C. M. (2001) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.70.1.503 · Cited by 3,184
ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets
Souers, A. J., Leverson, J. D., Boghaert, E. R., Ackler, S. L., Catron, N. D., Chen, J., Dayton, B. D., Ding, H., Enschede, S. H., Fairbrother, W. J., et al. (2013) · Nature Medicine · doi:10.1038/nm.3048 · Cited by 3,058
Sakamoto, K. M., Kim, K. B., Kumagai, A., Mercurio, F., Crews, C. M., & Deshaies, R. J. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.141230798 · Cited by 2,609
Antitumor Activity of Thalidomide in Refractory Multiple Myeloma
Singhal, S., Mehta, J., Desikan, R., Ayers, D., Roberson, P., Eddlemon, P., Munshi, N., Anaissie, E., Wilson, C., Dhodapkar, M., et al. (1999) · New England Journal of Medicine · doi:10.1056/nejm199911183412102 · Cited by 2,575
Identification of a Primary Target of Thalidomide Teratogenicity
Ito, T., Ando, H., Suzuki, T., Ogura, T., Hotta, K., Imamura, Y., Yamaguchi, Y., & Handa, H. (2010) · Science · doi:10.1126/science.1177319 · Cited by 2,136
Cited by
The emerging role of mass spectrometry-based proteomics in drug discovery
Meissner, F., Geddes-McAlister, J., Mann, M., & Bantscheff, M. (2022) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00409-3 · Cited by 341
Target and tissue selectivity of PROTAC degraders
Guenette, R. G., Yang, S. W., Min, J., Pei, B., & Potts, P. R. (2022) · Chemical Society Reviews · doi:10.1039/d2cs00200k · Cited by 324
Chemistries of bifunctional PROTAC degraders
Cao, C., He, M., Wang, L., He, Y., & Rao, Y. (2022) · Chemical Society Reviews · doi:10.1039/d2cs00220e · Cited by 313
Antibody targeting of E3 ubiquitin ligases for receptor degradation
Marei, H., Tsai, W.-T. K., Kee, Y.-S., Ruiz, K., He, J., Cox, C., Sun, T., Penikalapati, S., Dwivedi, P., Choi, M., et al. (2022) · Nature · doi:10.1038/s41586-022-05235-6 · Cited by 273
PROTACs: great opportunities for academia and industry (an update from 2020 to 2021)
He, M., Cao, C., Ni, Z., Liu, Y., Song, P., Hao, S., He, Y., Sun, X., & Rao, Y. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00999-9 · Cited by 283
Metadata
- Authors
- Dale, B., Cheng, M., Park, K.-S., Kaniskan, H. Ü., Xiong, Y., & Jin, J.
- Venue
- Nature Reviews Cancer
- Published
- 2021-06-15
- Volume
- 21
- Issue
- 10
- Pages
- 638-654
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- OpenAlex
- W3166285126
- Cited by
- 632
- References
- 244
- FWCI
- 8.81
- Type
- journal article
- Language
- en
- Open access
- green
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