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放射基因组学:一种用于理解放疗毒性遗传风险因素的系统生物学方法?

Radiogenomics: A systems biology approach to understanding genetic risk factors for radiotherapy toxicity?

作者信息

Herskind Carsten, Talbot Christopher J, Kerns Sarah L, Veldwijk Marlon R, Rosenstein Barry S, West Catharine M L

机构信息

Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Germany.

Department of Genetics, University of Leicester, Leicester, UK.

出版信息

Cancer Lett. 2016 Nov 1;382(1):95-109. doi: 10.1016/j.canlet.2016.02.035. Epub 2016 Mar 2.

Abstract

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review 'omics' approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different 'omics' approaches may be more efficient in identifying critical pathways than pathway analysis based on single 'omics' data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterised by different mechanisms. Thus 'omics' and functional approaches may synergise if they are integrated into radiogenomics 'systems biology' to facilitate the goal of individualised radiotherapy.

摘要

放射治疗(RT)后正常组织中的不良反应限制了给予肿瘤细胞的剂量。由于据估计临床反应中80%的个体差异是由患者相关因素引起的,识别这些因素可能有助于预测发生严重反应风险增加的患者。虽然细胞更新的失活被认为是早期反应正常组织中毒性的主要原因,但涉及多种细胞类型、细胞因子和缺氧的复杂相互作用似乎对晚期反应很重要。在此,我们综述了“组学”方法,如基因多态性筛查或基因表达分析,并评估表观遗传因素、翻译后修饰、信号转导和代谢的潜力。此外,功能测定表明可能与不良反应的临床风险相关。与基于单一“组学”数据集的通路分析相比,整合不同“组学”方法的通路分析在识别关键通路方面可能更有效。将这些通路与功能测定相结合,在识别以不同机制为特征的多个放疗患者亚组方面可能很强大。因此,如果将“组学”和功能方法整合到放射基因组学“系统生物学”中以促进个体化放疗的目标,它们可能会产生协同作用。

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