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网络驱动的癌细胞化身用于DNA损伤反应抑制剂的组合发现和生物标记物识别

Orsolya Papp¹, Viktória Jordán¹, Szabolcs Hetey¹

¹Turbine Simulated Cell Technologies, Budapest, Hungary.

NPJ systems biology and applications

|June 21, 2024

概括

确定有效的癌症药物组合是具有挑战性的. 本研究介绍了模拟细胞TM,一种网络生物学方法,可以准确预测协同作用的药物对及其生物标志物,改进癌症治疗策略.

科学领域:

计算生物学计算生物学
系统生物学系统生物学
癌症研究癌症研究

背景情况:

组合疗法通过克服耐药性,比单一疗法提供更好的癌症治疗疗效.
鉴定最佳药物组合是一个重大挑战,因为大量的潜在配对.

研究的目的:

开发和验证网络生物学驱动的模拟方法,用于预测协同作用的癌症药物组合.
确定与药物组合协同作用相关的生物标志物,并了解潜在的机制.

主要方法:

利用模拟细胞TM平台,将omics数据与策划的信号网络集成在一起.
在97个癌细胞系中进行了大规模的组合性药物敏感性查,其中包括684种药物组合.
采用网络生物学和模拟来预测组合的有效性,并确定协同作用的对.

主要成果:

准确预测了66348个具有高性能的组合细胞系对 (BAC=0.62,AUC=0.7).
突出了针对DNA损伤反应通路的协同药物组合.
通过深度网络分析,确定了推动组合协同作用的关键生物标志物.

结论:

模拟细胞TM准确地预测了协同作用的药物组合及其潜在机制.
这种方法有助于确定有效的组合疗法和临床转化生物标志物.
网络生物学驱动的模拟提供了一种强大的策略,用于在癌症中进行组合药物发现.

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