药物SurvPlot:一个新的基于Web的平台,利用药物敏感性得分作为泛癌症生存预后的分子生物标志物
Ying Shi1,2, Qirui Shen1,2, Aimin Jiang3
1Department of Oncology, Zhujiang Hospital, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510282, Guangdong, China.
Current gene therapy
|July 30, 2025
概括
预测的药物敏感度得分现在可以作为生存生物标志物,增强精确医学. 药物SurvPlot工具提供了一个无代码平台,用于分析许多癌症类型和药物的药物生存关系.
科学领域:
- 计算瘤学是一种计算瘤学.
- 生物信息学是一种生物信息学.
- 精准医学是一门精准的医学.
背景情况:
- 基因组引导的方法在临床试验中存在局限性.
- 预测的药物敏感度得分显示出作为生存生物标志物的前景.
- 改进精准医学需要新的生物标志物.
研究的目的:
- 介绍DrugSurvPlot,这是一个交互式网络工具,用于分析预测的药物敏感性得分作为生存生物标志物.
- 为计算瘤学研究提供一个用户友好的无代码平台.
- 为了促进药物敏感性数据与患者生存结果的整合.
主要方法:
- 使用R (v4.3.1) 开发了DrugSurvPlot,其中Shiny用于交互性,DT用于数据处理.
- 整合了189个GEO和33个TCGA数据集,包括52种癌症类型的85,531条记录.
- 整合了来自GDSC2的198种抗癌药物的数据,并使用了OncoPredict进行预处理.
主要成果:
- DrugSurvPlot集成了广泛的数据集,用于泛癌症药物敏感性和生存分析.
- 该平台支持多种切断策略和先进的生存分析方法.
- 允许可定制,高清可视化卡普兰-梅尔分析.
结论:
- DrugSurvPlot 建立了预测的药物敏感性得分作为新的预后生物标志物.
- 该工具为药物生存调查提供了一个全面的无代码解决方案.
- 未来的工作包括扩大药物和数据集覆盖范围,并纳入单细胞数据.
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