信号网络动态的综合建模识别了FGFR4驱动癌症的细胞类型选择性治疗策略
Sung-Young Shin1,2, Nicole J Chew1,2, Milad Ghomlaghi1,2
1Cancer Program, Biomedicine Discovery Institute, Monash University, Melbourne, Australia.
Cancer research
|August 1, 2024
概括
在癌症中准FGFR4可以导致耐药性. 计算建模显示,将FGFR4抑制剂与AKT或ErbB激酶抑制剂结合起来,可以克服某些癌症的耐药性,提高向治疗的有效性.
科学领域:
- 在瘤学瘤学.
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 瘤性FGFR4信号传递是癌症的治疗点,如三阴性乳腺癌和肝细胞癌.
- 对单剂FGFR4治疗的耐药性需要开发有效的组合治疗方法.
研究的目的:
- 开发FGFR4信号的计算模型,以了解电阻机制.
- 确定针对FGFR4向治疗的协同组合疗法.
主要方法:
- 集成计算网络建模和实验验证.
- 系统模拟共同准特定网络节点的系统模拟.
- 纳入来自不同癌细胞系的蛋白质表达数据.
主要成果:
- 在FGFR4向三阴性乳腺癌细胞时观察到AKT的重新激活.
- 预测并验证了与AKT或ErbB激酶共同向FGFR4的协同作用,但不是PI3K.
- 在特定的肝细胞癌细胞系中观察到ERK的活性和与MEK抑制的协同作用.
结论:
- 计算建模提供了对药物诱导的网络改造和抵抗的见解.
- 蛋白质表达异质性影响向治疗反应.
- 这种方法可以设计细胞类型选择性组合疗法,用于精确的癌症治疗.
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