To date, there are no inhibitors that directly and specifically target activated STAT3 and c-Myc in the clinic. Although peptide-based inhibitors can selectively block activated targets, their clinical usage is limited because of low cell penetration and/or serum stability. Here, we generated cell-penetrating acetylated (acet.) STAT3, c-Myc, and Gp130 targeting peptides by attaching phosphorothioated (PS) polymer backbone to peptides. The cell-penetrating peptides efficiently penetrated cells and inhibited activation of the intended targets and their downstream genes. Locally or systemically treating tumor-bearing mice with PS-acet.-STAT3 peptide at low concentrations effectively blocked STAT3 in vivo, resulting in significant antitumor effects in 2 human xenograft models. Moreover, PS-acet.-STAT3 peptide penetrated and activated splenic CD8+ T cells in vitro. Treating immune-competent mice bearing mouse melanoma with PS-acet.-STAT3 peptide inhibited STAT3 in tumor-infiltrating T cells, downregulating tumor-infiltrating CD4+ T regulatory cells while activating CD8+ T effector cells. Similarly, systemic injections of the cell-penetrating c-Myc and Gp130 peptides prevented pancreatic tumor growth and induced antitumor immune responses. Taken together, we have developed therapeutic peptides that effectively and specifically block challenging cancer targets, resulting in antitumor effects through both direct tumor cell killing and indirectly through antitumor immune responses.
Maryam Aftabizadeh, Yi-Jia Li, Qianqian Zhao, Chunyan Zhang, Nigus Ambaye, Jieun Song, Toshikage Nagao, Christoph Lahtz, Marwan Fakih, David K. Ann, Hua Yu, Andreas Herrmann
Usage data is cumulative from January 2021 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.