基于通路响应基因组的化学疗法耐药性药物发现及其在乳腺癌中的应用
Dehua Feng1, Jingwen Hao2, Lingxu Li1
1School of Intelligent Medicine and Technology, Kidney Disease Research Institute, Hainan Engineering Research Center for Health Big Data, Hainan Medical University, Haikou, Hainan, China.
Frontiers in bioinformatics
|October 2, 2025
概括
我们开发了通路响应基因组 (PRGS) 来识别癌症药物耐药性通路. PRGS精确检测动态基因变化,指导开发新型组合疗法,如博尔特佐米布 - 布莱米辛,以改善患者的治疗结果.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 计算生物学 计算生物学
背景情况:
- 在癌症患者中,化疗反应有很大差异,因此需要采取克服化疗抵抗的策略.
- 使用静态基因组的传统途径丰富方法无法捕捉动态的,药物诱导的转录变化对于理解耐药性至关重要.
研究的目的:
- 开发和验证Pathway-Responsive Gene Sets (PRGS) 框架,用于识别与化学抵抗相关的途径.
- 为了能够精确地识别药物诱导的途径失调,并指导针对性抗抗药疗法的开发.
主要方法:
- 开发了PRGS框架,将其性能与传统途径成员基因集 (PMGS) 相比较.
- 在PRGS中使用了类似GSEA的方法,通过对比分析与Hypergeometric和Bates基于测试的方法进行验证.
- 将PRGS应用于GDSC数据集以识别耐药性途径,并选针对性的药物.
主要成果:
- 与PMGS相比,PRGS证明了统计独立性 (p < 0.0001) 和更好的检测化疗驱动的途径失调.
- 在GDSC数据集上使用PRGS识别了8个与化学抵抗相关的途径.
- 一项体外研究证实了在T47D细胞中的博特佐米布-白胺组合的协同细胞毒性 (IDAcomboScore = 0.014),验证了PRGS指导策略.
结论:
- PRGS框架提供了一种新的方法方法,将基因组扰乱与精确瘤学整合起来.
- 通过分析动态途径的改变,PRGS有效地解读了癌症药物耐药性机制.
- 这种方法具有显著的潜力,可以指导开发更有效的治疗策略来对抗抗化学性癌症.
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