迈向数据驱动的RT处方:整合基因组学到RT临床实践

IF 2.6 3区 医学 Q3 ONCOLOGY Seminars in Radiation Oncology Pub Date : 2023-07-01 DOI:10.1016/j.semradonc.2023.03.007
Javier F. Torres-Roca , G. Daniel Grass , Jacob G. Scott , Steven A. Eschrich
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引用次数: 0

摘要

基因组时代极大地改变了临床肿瘤学的实践。基于基因组的分子诊断(包括预后基因组特征和新一代测序)的使用已成为细胞毒性化疗、靶向药物和免疫疗法临床决策的常规。相反,关于放射治疗(RT)的临床决策仍然不了解肿瘤的基因组异质性。在这篇综述中,我们讨论了利用基因组学优化RT剂量的临床机会。尽管从技术角度来看,RT一直在走向数据驱动的方法,但RT处方剂量仍然基于一刀切的方法,大多数RT剂量基于癌症诊断和分期。这种方法与认识到肿瘤是生物异质性的,癌症不是一种单一的疾病直接冲突。在这里,我们讨论了基因组学如何整合到RT处方剂量中,这种方法的临床潜力,以及RT剂量的基因组优化如何导致对RT临床益处的新理解。
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Towards Data Driven RT Prescription: Integrating Genomics into RT Clinical Practice

The genomic era has significantly changed the practice of clinical oncology. The use of genomic-based molecular diagnostics including prognostic genomic signatures and new-generation sequencing has become routine for clinical decisions regarding cytotoxic chemotherapy, targeted agents and immunotherapy. In contrast, clinical decisions regarding radiation therapy (RT) remain uninformed about the genomic heterogeneity of tumors. In this review, we discuss the clinical opportunity to utilize genomics to optimize RT dose. Although from the technical perspective, RT has been moving towards a data-driven approach, RT prescription dose is still based on a one-size-fits all approach, with most RT dose based on cancer diagnosis and stage. This approach is in direct conflict with the realization that tumors are biologically heterogeneous, and that cancer is not a single disease. Here, we discuss how genomics can be integrated into RT prescription dose, the clinical potential for this approach and how genomic-optimization of RT dose could lead to new understanding of the clinical benefit of RT.

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来源期刊
CiteScore
5.80
自引率
0.00%
发文量
48
审稿时长
>12 weeks
期刊介绍: Each issue of Seminars in Radiation Oncology is compiled by a guest editor to address a specific topic in the specialty, presenting definitive information on areas of rapid change and development. A significant number of articles report new scientific information. Topics covered include tumor biology, diagnosis, medical and surgical management of the patient, and new technologies.
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