辐射敏感性:来自患者的预测性癌症模型的兴起
Liliana L Berube1, Kwang-Ok P Nickel2, Mari Iida2
1Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, WI; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI.
Seminars in radiation oncology
|June 18, 2023
概括
来自患者的癌症模型为放射治疗提供了个性化的见解. 研究探讨了它们作为预测化身的使用,以及为量身定制的癌症治疗策略开发算法.
科学领域:
- 在瘤学瘤学.
- 翻译医学是一种翻译医学.
- 癌症研究 癌症研究
背景情况:
- 患者衍生癌症模型 (PDCMs) 对于理解癌症生物学和评估治疗非常重要.
- 辐射输送方面的进步提高了PDCM在研究辐射敏感剂和个体患者敏感性的实用性.
- 优化患者衍生的异种移植和球形培养的使用仍然是一个活跃的研究领域.
研究的目的:
- 审查患者衍生癌症模型在瘤学的进展和应用.
- 讨论PDCM在小鼠和斑马鱼模型中作为个性化的预测化身的作用.
- 评估患者衍生球体的优缺点,以及用于预测算法的大型模型存储库的潜力.
主要方法:
- 对患者衍生癌症模型现有文献的综述.
- 讨论各种PDCM平台,包括异种移植,球形,鼠标和斑马鱼模型.
- 分析建立PDCM的方法和影响其应用的因素.
主要成果:
- 对于个性化医疗来说,PDCM越来越有价值,特别是在辐射瘤学中.
- 来自患者的异种移植和球体显示出有前途的预测化身,但需要进一步优化.
- 大量的PDCM存储库可以促进治疗选择预测算法的开发.
结论:
- 来自患者的癌症模型对于推进个性化癌症治疗和辐射敏感性研究至关重要.
- 需要进一步的研究来完善用于临床决策的PDCM,特别是异种移植和球体的使用.
- 使用PDCM的预测算法的开发具有指导个性化癌症治疗策略的巨大潜力.
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