利用全基因组关联研究,尽量减少辐射引起的不良副作用。

IF 1.8 Q3 ONCOLOGY Radiation Oncology Journal Pub Date : 2020-12-01 Epub Date: 2020-11-25 DOI:10.3857/roj.2020.00556
Cecil M Benitez, Susan J Knox
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引用次数: 3

摘要

放疗是约三分之二癌症的最终治疗方法。然而,像任何治疗一样,放射有显著的急性和长期副作用,包括继发性恶性肿瘤。即使使用类似的辐射参数,5%-10%的患者也会出现不良的辐射副作用。基因组易感性被认为对观察到的约40%的临床变异性负责。在精准医疗时代,遗传易感性与辐射引起的副作用之间的联系正在进一步加强。全基因组关联研究(GWAS)已经开始确定单核苷酸多态性(snp)归因于乳腺癌、前列腺癌和其他癌症放射治疗后的整体和组织特异性毒性。在这里,我们回顾了GWAS在识别预测急性和长期辐射引起的副作用的多态性中的应用,重点是胸部、骨盆和头颈部照射。将GWAS研究与“组学”数据、患者特征和临床相关性整合到预测模型中可以减少辐射引起的副作用,同时提高治疗效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Harnessing genome-wide association studies to minimize adverse radiation-induced side effects.

Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%-10% of patients will experience adverse radiation side effects. Genomic susceptibility is thought to be responsible for approximately 40% of the clinical variability observed. In the era of precision medicine, the link between genetic susceptibility and radiation-induced side effects is further strengthening. Genome-wide association studies (GWAS) have begun to identify single-nucleotide polymorphisms (SNPs) attributed to overall and tissue-specific toxicity following radiation for treatment of breast cancer, prostate cancer, and other cancers. Here, we review the use of GWAS in identifying polymorphisms that are predictive of acute and long-term radiation-induced side effects with a focus on chest, pelvic, and head-and-neck irradiation. Integration of GWAS studies with "omic" data, patient characteristics, and clinical correlates into predictive models could decrease radiation-induced side effects while increasing therapeutic efficacy.

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来源期刊
CiteScore
3.50
自引率
4.30%
发文量
24
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