通过对纵向和多模式数据的建模,推进精确瘤学
IEEE reviews in biomedical engineering
|July 3, 2025
概括
癌症是动态的,但目前的研究经常使用单一的快照. 纵向多式联络分析使用多种数据追踪随时间变化的变化,使得更好的癌症监测和个性化治疗成为可能.
科学领域:
- 在瘤学瘤学.
- 生物医学数据科学 生物医学数据科学
- 计算生物学 计算生物学
背景情况:
- 癌症的持续进化涉及遗传,表观遗传,微环境和表型变化,使监测和治疗复杂化.
- 目前的瘤学研究主要依赖于横截面的单一模式数据,阻碍了对癌症动态异质性的充分理解.
- 耐治疗性,免疫逃避和转移是由癌症的动态性驱动的,需要先进的分析方法.
研究的目的:
- 审查癌症研究中纵向和多模式建模的方法.
- 为个人化瘤学突出纵向和多式联络数据的协同作用.
- 讨论精确瘤学的纵向多式联络分析的挑战和未来方向.
主要方法:
- 调查癌症的纵向数据分析现有方法.
- 检查整合多式联运数据源的技术.
- 专注于生物标志物发现的计算方法.
主要成果:
- 纵向数据揭示了单个时间点分析遗漏的疾病进展和治疗反应模式.
- 多模式数据集成为精确的风险评估和治疗向提供了补充信息.
- 纵向和多模式方法的协同作用为个性化癌症护理提供了多方面的见解.
结论:
- 纵向多模式分析对于理解和管理癌症的动态性质至关重要.
- 数据收集和计算方法的进步使得精确瘤学的强大生物标志物的发现成为可能.
- 解决纵向多式联络分析当前的挑战,将进一步推进个性化癌症护理.
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