通过标志性网络,通过数据驱动对瘤发生的普遍洞察力
Jiahe Wang1, Yan Wu1, Yuke Hou1
1Institute of Operations Research and Information Engineering, Beijing University of Technology, Beijing, China.
NPJ systems biology and applications
|November 19, 2025
概括
癌症 癌症 癌症 癌症
科学领域:
- 系统生物学 系统生物学
- 基因组学就是基因组学.
- 癌症研究 癌症研究
背景情况:
- 癌症涉及复杂的调节网络变化超出单个基因.
- 现有的模型难以捕捉癌症发展的全谱.
研究的目的:
- 开发一个全基因组数据驱动的框架来建模癌症的发展.
- 通过基因调节网络分析癌症特征的动态变化.
主要方法:
- 构建了癌症特征的粗粒基因调节网络.
- 使用随机微分方程模拟瘤发生.
- 分析了网络拓变化之前的标志转移.
主要成果:
- 网络拓重新配置之前的标志性水平转移,表明早期恶性瘤.
- "组织侵袭和转移"的标志显示了最大的正常与癌症之间的差异.
- "重编程能量代谢"标志显示15种癌症类型的差异最小.
结论:
- 癌症的进化是一个系统的过程.
- 基于网络的系统生物学提供了对瘤发生过渡的见解.
- 通过网络分析,可以早期检测恶性瘤.
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