Targeted cancer therapies, which act on specific cancer-associated molecular targets, are predominantly inhibitors of oncogenic kinases. While these drugs have achieved some clinical success, the inactivation of kinase signaling via stimulation of endogenous phosphatases has received minimal attention as an alternative targeted approach. Here, we have demonstrated that activation of the tumor suppressor protein phosphatase 2A (PP2A), a negative regulator of multiple oncogenic signaling proteins, is a promising therapeutic approach for the treatment of cancers. Our group previously developed a series of orally bioavailable small molecule activators of PP2A, termed SMAPs. We now report that SMAP treatment inhibited the growth of KRAS-mutant lung cancers in mouse xenografts and transgenic models. Mechanistically, we found that SMAPs act by binding to the PP2A Aα scaffold subunit to drive conformational changes in PP2A. These results show that PP2A can be activated in cancer cells to inhibit proliferation. Our strategy of reactivating endogenous PP2A may be applicable to the treatment of other diseases and represents an advancement toward the development of small molecule activators of tumor suppressor proteins.
Jaya Sangodkar, Abbey Perl, Rita Tohme, Janna Kiselar, David B. Kastrinsky, Nilesh Zaware, Sudeh Izadmehr, Sahar Mazhar, Danica D. Wiredja, Caitlin M. O’Connor, Divya Hoon, Neil S. Dhawan, Daniela Schlatzer, Shen Yao, Daniel Leonard, Alain C. Borczuk, Giridharan Gokulrangan, Lifu Wang, Elena Svenson, Caroline C. Farrington, Eric Yuan, Rita A. Avelar, Agnes Stachnik, Blake Smith, Vickram Gidwani, Heather M. Giannini, Daniel McQuaid, Kimberly McClinch, Zhizhi Wang, Alice C. Levine, Rosalie C. Sears, Edward Y. Chen, Qiaonan Duan, Manish Datt, Shozeb Haider, Avi Ma’ayan, Analisa DiFeo, Neelesh Sharma, Matthew D. Galsky, David L. Brautigan, Yiannis A. Ioannou, Wenqing Xu, Mark R. Chance, Michael Ohlmeyer, Goutham Narla
Usage data is cumulative from April 2020 through April 2021.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.