走向数据驱动的RT处方:将基因组学纳入RT临床实践
Javier F Torres-Roca1, G Daniel Grass2, Jacob G Scott3
1Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL; Department of Bioinformatics and Biostatistics, Moffitt Cancer Center, Tampa, FL; Department of Oncologic Sciences, University of South Florida College of Medicine, Tampa, FL.
基因组数据可以个性化放射治疗 (RT) 剂量,超越目前的一种适合所有人的方法. 将瘤基因组学整合到RT处方中可以优化治疗,并加深对RT的理解.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 辐射瘤学 辐射瘤学
背景情况:
- 基因组诊断在瘤学中是化疗,向治疗和免疫治疗决策的标准.
- 放射治疗 (RT) 处方目前缺乏基因组信息,取决于癌症类型和阶段.
- 瘤基因组异质性在当前的RT剂量设定实践中没有得到解决.
研究的目的:
- 审查将基因组学纳入放射治疗 (RT) 剂量优化的潜力.
- 探索基因组数据如何为改善患者结果提供RT处方的信息.
- 通过基因组优化,讨论临床影响和通过基因组优化对RT疗效的新见解的潜力.
主要方法:
- 对临床瘤学和放射治疗当前实践的审查.
- 基因组基础诊断在癌症治疗决策中的作用分析.
- 讨论将瘤基因组学整合到RT剂量优化策略中.
主要成果:
- 基因组诊断经常指导化学疗法,向药物和免疫疗法的决策.
- 放射治疗 (RT) 剂量处方仍然主要基于癌症诊断和阶段,无视基因组异质性.
- 基因组优化为个性化RT剂量和提高治疗疗效提供了一条途径.
结论:
- 将基因组学纳入RT处方是一个重要的临床机会.
- 基因组信息RT剂量优化可以克服当前"一刀切"方法的局限性.
- 这种整合有望促进我们对放射治疗的临床益处和瘤生物学的理解.
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