Constitutive JAK2 signaling is central to myeloproliferative neoplasm (MPN) pathogenesis and results in activation of STAT, PI3K/AKT, and MEK/ERK signaling. However, the therapeutic efficacy of current JAK2 inhibitors is limited. We investigated the role of MEK/ERK signaling in MPN cell survival in the setting of JAK inhibition. Type I and II JAK2 inhibition suppressed MEK/ERK activation in MPN cell lines in vitro, but not in Jak2V617F and MPLW515L mouse models in vivo. JAK2 inhibition ex vivo inhibited MEK/ERK signaling, suggesting that cell-extrinsic factors maintain ERK activation in vivo. We identified PDGFRα as an activated kinase that remains activated upon JAK2 inhibition in vivo, and PDGF-AA/PDGF-BB production persisted in the setting of JAK inhibition. PDGF-BB maintained ERK activation in the presence of ruxolitinib, consistent with its function as a ligand-induced bypass for ERK activation. Combined JAK/MEK inhibition suppressed MEK/ERK activation in Jak2V617F and MPLW515L mice with increased efficacy and reversal of fibrosis to an extent not seen with JAK inhibitors. This demonstrates that compensatory ERK activation limits the efficacy of JAK2 inhibition and dual JAK/MEK inhibition provides an opportunity for improved therapeutic efficacy in MPNs and in other malignancies driven by aberrant JAK-STAT signaling.
Simona Stivala, Tamara Codilupi, Sime Brkic, Anne Baerenwaldt, Nilabh Ghosh, Hui Hao-Shen, Stephan Dirnhofer, Matthias S. Dettmer, Cedric Simillion, Beat A. Kaufmann, Sophia Chiu, Matthew Keller, Maria Kleppe, Morgane Hilpert, Andreas S. Buser, Jakob R. Passweg, Thomas Radimerski, Radek C. Skoda, Ross L. Levine, Sara C. Meyer
Usage data is cumulative from February 2019 through December 2019.
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.