精准医学在多学科时代:数据海可以指导合理的治疗决策吗?
M Aldea1, L Friboulet2, S Apcher2
1Department of Medical Oncology, Gustave Roussy, Villejuif; PRISM, INSERM, Gustave Roussy, Villejuif.
ESMO open
|September 28, 2023
概括
精准医学整合了多维生物学来模拟癌症的进展. 根据可操作性对基因组改变进行排名是有效的癌症治疗的关键,特别是新兴驱动因素.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 癌症的精准医学越来越多地整合了多维生物数据.
- 识别多个瘤驱动因素使治疗决策复杂化,需要先进的分析方法.
研究的目的:
- 讨论用于精确癌症医学的高通量基因组学的进展.
- 探索精准医学研究的优势,局限性和未来前景.
主要方法:
- 对高通量基因组数据集成的审查.
- 基于目标可操作性,克隆起源和基因组改变的药物敏感性分析.
主要成果:
- 基因组测序揭示了在治疗失败时出现的各种驱动因素,为临床试验和药物重新用途提供了目标.
- 优先考虑治疗需要根据已证明的可操作性对基因组改变进行排名.
结论:
- 未来的精准医学必须解决癌症的空间和时间异质性.
- 人工智能对于精确瘤学中分析复杂的生物数据至关重要.
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