EGFR activation is both a key molecular driver of disease progression and the target of a broad class of molecular agents designed to treat advanced cancer. Nevertheless, resistance develops through several mechanisms, including activation of AKT signaling. Though much is known about the specific molecular lesions conferring resistance to anti-EGFR–based therapies, additional molecular characterization of the downstream mediators of EGFR signaling may lead to the development of new classes of targeted molecular therapies to treat resistant disease. We identified a transcriptional network involving the tumor suppressors Krüppel-like factor 6 (KLF6) and forkhead box O1 (FOXO1) that negatively regulates activated EGFR signaling in both cell culture and in vivo models. Furthermore, the use of the FDA-approved drug trifluoperazine hydrochloride (TFP), which has been shown to inhibit FOXO1 nuclear export, restored sensitivity to AKT-driven erlotinib resistance through modulation of the KLF6/FOXO1 signaling cascade in both cell culture and xenograft models of lung adenocarcinoma. Combined, these findings define a novel transcriptional network regulating oncogenic EGFR signaling and identify a class of FDA-approved drugs as capable of restoring chemosensitivity to anti-EGFR–based therapy for the treatment of metastatic lung adenocarcinoma.
Jaya Sangodkar, Neil S. Dhawan, Heather Melville, Varan J. Singh, Eric Yuan, Huma Rana, Sudeh Izadmehr, Caroline Farrington, Sahar Mazhar, Suzanna Katz, Tara Albano, Pearlann Arnovitz, Rachel Okrent, Michael Ohlmeyer, Matthew Galsky, David Burstein, David Zhang, Katerina Politi, Analisa DiFeo, Goutham Narla
Usage data is cumulative from June 2021 through June 2022.
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.