Laboratory for Systems Biology and Bio-inspired Engineering, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
Oncogene. 2020 May;39(19):3803-3820. doi: 10.1038/s41388-020-1255-y. Epub 2020 Mar 10.
Targeted drugs aim to treat cancer by directly inhibiting oncogene activity or oncogenic pathways, but drug resistance frequently emerges. Due to the intricate dynamics of cancer signaling networks, which contain complex feedback regulations, cancer cells can rewire these networks to adapt to and counter the cytotoxic effects of a drug, thereby limiting the efficacy of targeted therapies. To identify a combinatorial drug target that can overcome such a limitation, we developed a Boolean network simulation and analysis framework and applied this approach to a large-scale signaling network of colorectal cancer with integrated genomic information. We discovered Src as a critical combination drug target that can overcome the adaptive resistance to the targeted inhibition of mitogen-activated protein kinase pathway by blocking the essential feedback regulation responsible for resistance. The proposed framework is generic and can be widely used to identify drug targets that can overcome adaptive resistance to targeted therapies.
靶向药物旨在通过直接抑制癌基因活性或致癌途径来治疗癌症，但耐药性经常出现。由于癌症信号网络的复杂动力学，其中包含复杂的反馈调节，癌细胞可以重新布线这些网络以适应和对抗药物的细胞毒性作用，从而限制了靶向治疗的疗效。为了确定可以克服这种限制的组合药物靶点，我们开发了一个布尔网络模拟和分析框架，并将该方法应用于具有综合基因组信息的结直肠癌大型信号网络。我们发现Src 是一个关键的组合药物靶点，可以通过阻断负责耐药的基本反馈调节来克服对丝裂原活化蛋白激酶途径的靶向抑制的适应性耐药。所提出的框架是通用的，可以广泛用于识别可以克服对靶向治疗的适应性耐药的药物靶点。
