Angiogenesis, new blood vessel formation from preexisting vessels, is critical for solid tumor growth. As such, there have been efforts to inhibit angiogenesis as a means to obstruct tumor growth. However, antiangiogenic therapy faces major challenges to the selective targeting of tumor-associated-vessels, as current antiangiogenic targets also disrupt steady-state vessels. Here, we demonstrate that the developmentally critical transcription factor Etv2 is selectively upregulated in both human and mouse tumor-associated endothelial cells (TAECs) and is required for tumor angiogenesis. Two-photon imaging revealed that Etv2-deficient tumor-associated vasculature remained similar to that of steady-state vessels. Etv2-deficient TAECs displayed decreased Flk1 (also known as Vegfr2) expression, FLK1 activation, and proliferation. Endothelial tube formation, proliferation, and sprouting response to VEGF, but not to FGF2, was reduced in Etv2-deficient ECs. ROS activated Etv2 expression in ECs, and ROS blockade inhibited Etv2 expression in TAECs in vivo. Systemic administration of Etv2 siRNA nanoparticles potently inhibited tumor growth and angiogenesis without cardiovascular side effects. These studies highlight a link among vascular oxidative stress, Etv2 expression, and VEGF response that is critical for tumor angiogenesis. Targeting the ETV2 pathway might offer a unique opportunity for more selective antiangiogenic therapies.
Ashraf Ul Kabir, Tae-Jin Lee, Hua Pan, Jeffrey C. Berry, Karen Krchma, Jun Wu, Fang Liu, Hee-Kyoung Kang, Kristina Hinman, Lihua Yang, Samantha Hamilton, Qingyu Zhou, Deborah J. Veis, Robert P. Mecham, Samuel A. Wickline, Mark J. Miller, Kyunghee Choi
Usage data is cumulative from November 2023 through November 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 435 | 153 |
80 | 35 | |
Figure | 195 | 4 |
Supplemental data | 62 | 4 |
Citation downloads | 29 | 0 |
Totals | 801 | 196 |
Total Views | 997 |
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.