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RadioGx:一种新型的临床前工具,用于模拟内在放射敏感性。

RadioGx: A New Preclinical Tool to Model Intrinsic Radiosensitivity.

机构信息

Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan.

Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.

出版信息

Cancer Res. 2019 Dec 15;79(24):6076-6078. doi: 10.1158/0008-5472.CAN-19-3277.

Abstract

Radiotherapy is perhaps the most ubiquitous single treatment modality for patients with cancer. Despite its routine use, biomarkers of treatment response are critically lacking, and the biology underlying the heterogeneity in clinical response to radiation treatment remain largely unknown. In this issue of , Manem and colleagues seek to change this paradigm and detail the development of a radiation response computational platform (RadioGx) that allows for the integrative analysis of radiation response using radiogenomic data derived from preclinical, sources (1). This platform holds promise for novel hypothesis generation and may allow for the discovery of novel mediators of radiation response that may improve the therapeutic efficacy of radiation. Importantly, it also moves us closer to uncovering and validating radiation response biomarkers that may prove clinically useful..

摘要

放疗或许是癌症患者最常用的单一治疗手段。尽管它被常规应用,但缺乏治疗反应的生物标志物,而且辐射治疗临床反应异质性的生物学基础在很大程度上仍是未知的。在本期 杂志中,Manem 及其同事试图改变这种模式,并详细介绍了一种辐射反应计算平台(RadioGx)的开发,该平台允许使用源自临床前和临床源的放射基因组数据进行辐射反应的综合分析(1)。该平台具有产生新假说的潜力,并且可能有助于发现新的辐射反应介质,从而提高辐射的治疗效果。重要的是,它也使我们更接近于发现和验证可能具有临床应用价值的辐射反应生物标志物。

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