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将基因生物标志物纳入正常组织毒性预测模型

Incorporating Genetic Biomarkers into Predictive Models of Normal Tissue Toxicity.

作者信息

Barnett G C, Kerns S L, Noble D J, Dunning A M, West C M L, Burnet N G

机构信息

Oncology Centre, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.

Rubin Center for Cancer Survivorship, Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY, USA.

出版信息

Clin Oncol (R Coll Radiol). 2015 Oct;27(10):579-87. doi: 10.1016/j.clon.2015.06.013. Epub 2015 Jul 10.

Abstract

There is considerable variation in the level of toxicity patients experience for a given dose of radiotherapy, which is associated with differences in underlying individual normal tissue radiosensitivity. A number of syndromes have a large effect on clinical radiosensitivity, but these are rare. Among non-syndromic patients, variation is less extreme, but equivalent to a ±20% variation in dose. Thus, if individual normal tissue radiosensitivity could be measured, it should be possible to optimise schedules for individual patients. Early investigations of in vitro cellular radiosensitivity supported a link with tissue response, but individual studies were equivocal. A lymphocyte apoptosis assay has potential, and is currently under prospective validation. The investigation of underlying genetic variation also has potential. Although early candidate gene studies were inconclusive, more recent genome-wide association studies are revealing definite associations between genotype and toxicity and highlighting the potential for future genetic testing. Genetic testing and individualised dose prescriptions could reduce toxicity in radiosensitive patients, and permit isotoxic dose escalation to increase local control in radioresistant individuals. The approach could improve outcomes for half the patients requiring radical radiotherapy. As a number of patient- and treatment-related factors also affect the risk of toxicity for a given dose, genetic testing data will need to be incorporated into models that combine patient, treatment and genetic data.

摘要

对于给定剂量的放射治疗,患者所经历的毒性水平存在相当大的差异,这与个体正常组织放射敏感性的差异有关。一些综合征对临床放射敏感性有很大影响,但这些情况很罕见。在非综合征患者中,差异没有那么极端,但相当于剂量有±20%的变化。因此,如果能够测量个体正常组织的放射敏感性,就应该有可能为个体患者优化治疗方案。早期对体外细胞放射敏感性的研究支持了其与组织反应的联系,但个别研究结果并不明确。淋巴细胞凋亡检测具有潜力,目前正在进行前瞻性验证。对潜在基因变异的研究也有潜力。尽管早期的候选基因研究没有定论,但最近的全基因组关联研究正在揭示基因型与毒性之间的明确关联,并突出了未来基因检测的潜力。基因检测和个体化剂量处方可以降低放射敏感患者的毒性,并允许在放射抵抗个体中进行等毒性剂量递增以提高局部控制率。这种方法可以改善一半需要根治性放疗患者的治疗结果。由于一些与患者和治疗相关的因素也会影响给定剂量下的毒性风险,基因检测数据将需要纳入结合患者、治疗和基因数据的模型中。

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