Overexpression of FGF receptor 3 (FGFR3) is implicated in the development of t(4;14)-positive multiple myeloma. While FGFR3 is frequently overexpressed and/or activated through mutations in bladder cancer, the functional importance of FGFR3 and its potential as a specific therapeutic target in this disease have not been elucidated in vivo. Here we report that inducible knockdown of FGFR3 in human bladder carcinoma cells arrested cell-cycle progression in culture and markedly attenuated tumor progression in xenografted mice. Further, we developed a unique antibody (R3Mab) that inhibited not only WT FGFR3, but also various mutants of the receptor, including disulfide-linked cysteine mutants. Biochemical analysis and 2.1-Å resolution crystallography revealed that R3Mab bound to a specific FGFR3 epitope that simultaneously blocked ligand binding, prevented receptor dimerization, and induced substantial conformational changes in the receptor. R3Mab exerted potent antitumor activity against bladder carcinoma and t(4;14)-positive multiple myeloma xenografts in mice by antagonizing FGFR3 signaling and eliciting antibody-dependent cell-mediated cytotoxicity (ADCC). These studies provide in vivo evidence demonstrating an oncogenic role of FGFR3 in bladder cancer and support antibody-based targeting of FGFR3 in hematologic and epithelial cancers driven by WT or mutant FGFR3.
Jing Qing, Xiangnan Du, Yongmei Chen, Pamela Chan, Hao Li, Ping Wu, Scot Marsters, Scott Stawicki, Janet Tien, Klara Totpal, Sarajane Ross, Susanna Stinson, David Dornan, Dorothy French, Qian-Rena Wang, Jean-Philippe Stephan, Yan Wu, Christian Wiesmann, Avi Ashkenazi
Usage data is cumulative from May 2024 through May 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,147 | 240 |
145 | 68 | |
Figure | 511 | 16 |
Supplemental data | 88 | 15 |
Citation downloads | 61 | 0 |
Totals | 1,952 | 339 |
Total Views | 2,291 |
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.