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利用高复杂度条形码研究癌症治疗反应中的克隆动力学。

Studying clonal dynamics in response to cancer therapy using high-complexity barcoding.

机构信息

Oncology Disease Area, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.

Translational Clinical Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.

出版信息

Nat Med. 2015 May;21(5):440-8. doi: 10.1038/nm.3841. Epub 2015 Apr 13.

Abstract

Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.

摘要

癌症治疗的耐药性是一个重大的临床挑战。最近的研究表明肿瘤内异质性是产生治疗耐药性的一个原因。然而,尚不清楚耐药性主要是由预先存在的还是新出现的改变驱动的,部分原因是下一代测序的分辨率限制。为了解决这个问题,我们开发了一种高复杂度的条形码文库 ClonTracer,它能够在药物治疗下高分辨率地跟踪超过 100 万个癌细胞。在两个临床相关的模型中,ClonTracer 研究表明,大多数耐药克隆是预先存在的小亚群的一部分,这些亚群在治疗挑战下选择性地逃逸。此外,ClonTracer 方法还能够定量评估联合治疗抑制耐药克隆的能力。这些发现表明,耐药克隆在治疗前就已经存在,这将使针对非重叠耐药性的预先联合治疗成为一种首选方法。因此,ClonTracer 条形码可能是优化治疗方案的一种有价值的工具,目标是为癌症提供治愈性的联合治疗。

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