原癌基因酪氨酸蛋白激酶Src
癌症研究
达沙替尼
甲状腺间变性癌
生物
自分泌信号
信号转导
癌基因
甲状腺癌
细胞生物学
癌症
细胞培养
细胞周期
遗传学
酪氨酸激酶
作者
Brittelle E. Kessler,Katie M. Mishall,M. Kellett,Erin G. Clark,Umarani Pugazhenthi,Nikita Pozdeyev,Jihye Kim,Aik Choon Tan,Rebecca E. Schweppe
出处
期刊:Oncogene
[Springer Nature]
日期:2018-12-10
卷期号:38 (14): 2565-2579
被引量:14
标识
DOI:10.1038/s41388-018-0617-1
摘要
Few therapy options exist for patients with advanced papillary and anaplastic thyroid cancer. We and others have previously identified c-Src as a key mediator of thyroid cancer pro-tumorigenic processes and a promising therapeutic target for thyroid cancer. To increase the efficacy of targeting Src in the clinic, we sought to define mechanisms of resistance to the Src inhibitor, dasatinib, to identify key pathways to target in combination. Using a panel of thyroid cancer cell lines expressing clinically relevant mutations in BRAF or RAS, which were previously developed to be resistant to dasatinib, we identified a switch to a more invasive phenotype in the BRAF-mutant cells as a potential therapy escape mechanism. This phenotype switch is driven by FAK kinase activity, and signaling through the p130Cas>c-Jun signaling axis. We have further shown this more invasive phenotype is accompanied by alterations in the secretome through the increased expression of pro-inflammatory cytokines, including IL-1β, and the pro-invasive metalloprotease, MMP-9. Furthermore, IL-1β signals via a feedforward autocrine loop to promote invasion through a FAK>p130Cas>c-Jun>MMP-9 signaling axis. We further demonstrate that upfront combined inhibition of FAK and Src synergistically inhibits growth and invasion, and induces apoptosis in a panel of BRAF- and RAS-mutant thyroid cancer cell lines. Together our data demonstrate that acquired resistance to single-agent Src inhibition promotes a more invasive phenotype through an IL-1β>FAK>p130Cas>c-Jun >MMP signaling axis, and that combined inhibition of FAK and Src has the potential to block this inhibitor-induced phenotype switch.
科研通智能强力驱动
Strongly Powered by AbleSci AI