Christopher E. Whitehead, Elizabeth K. Ziemke, Christy L. Frankowski-McGregor, Rachel A. Mumby, June Chung, Jinju Li, Nathaniel Osher, Oluwadara Coker, Veerabhadran Baladandayuthapani, Scott Kopetz, Judith S. Sebolt-Leopold
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引用次数: 0
Abstract
Despite tremendous progress in precision oncology, adaptive resistance mechanisms limit the long-term effectiveness of molecularly targeted agents. Here we evaluated the pharmacological profile of MTX-531 that was computationally designed to selectively target two key resistance drivers, epidermal growth factor receptor and phosphatidylinositol 3-OH kinase (PI3K). MTX-531 exhibits low-nanomolar potency against both targets with a high degree of specificity predicted by cocrystal structural analyses. MTX-531 monotherapy uniformly resulted in tumor regressions of squamous head and neck patient-derived xenograft (PDX) models. The combination of MTX-531 with mitogen-activated protein kinase kinase or KRAS-G12C inhibitors led to durable regressions of BRAF-mutant or KRAS-mutant colorectal cancer PDX models, resulting in striking increases in median survival. MTX-531 is exceptionally well tolerated in mice and uniquely does not lead to the hyperglycemia commonly seen with PI3K inhibitors. Here, we show that MTX-531 acts as a weak agonist of peroxisome proliferator-activated receptor-γ, an attribute that likely mitigates hyperglycemia induced by PI3K inhibition. This unique feature of MTX-531 confers a favorable therapeutic index not typically seen with PI3K inhibitors. Sebolt-Leopold and colleagues design and develop a small-molecule inhibitor that can target both epidermal growth factor receptor and phosphatidylinositol 3-OH kinase, which can be leveraged to overcome resistance to targeted therapies in vivo.
期刊介绍:
Cancer is a devastating disease responsible for millions of deaths worldwide. However, many of these deaths could be prevented with improved prevention and treatment strategies. To achieve this, it is crucial to focus on accurate diagnosis, effective treatment methods, and understanding the socioeconomic factors that influence cancer rates.
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