整合基因组特征用于非侵入性早期肺癌检测
Jacob J Chabon1,2, Emily G Hamilton3, David M Kurtz4,5,6
1Stanford Cancer Institute, Stanford University, Stanford, CA, USA.
Nature
|April 10, 2020
概括
通过分析无细胞DNA (cfDNA), 改善了早期肺癌检测的新方法. 这种名为 Lung-CLiP 的创新方法有望增加高危人群的肺癌查率.
科学领域:
- 癌症学
- 基因组学
- 生物标志物发现
背景情况:
- 肺癌查降低了死亡率, 但在美国的普及率很低.
- 基于血液的测试可以提高查参与度.
- 循环瘤DNA (ctDNA) 分析显示了早期癌症检测的潜力.
研究的目的:
- 改进肺癌查中的ctDNA分析.
- 开发一种基于血液的检测方法来检测早期的肺癌.
- 在无细胞DNA中区分癌症衍生突变和克隆造血.
主要方法:
- 通过深度测序 (CAPP-Seq) 进行增强癌症个性化分析,用于ctDNA分析.
- 来自肺癌患者和对照组的无细胞DNA (cfDNA) 的体质突变分析.
- 机器学习模型 (Lung-CLiP) 的开发和未来验证.
主要成果:
- 在大多数早期肺癌中存在并具有预后性ctDNA.
- 大多数肺癌和对照患者的cfDNA突变来自克隆造血,而不是瘤.
- 肺CLiP准确地将早期肺癌患者与对照患者区分开来,类似于瘤信息的ctDNA测试.
结论:
- 在肺癌查中,cfDNA分析具有显著的潜力.
- 肺CLiP试验在识别早期肺癌方面表现强.
- 在基于cfDNA的查研究中,对病例和对照的准确风险匹配至关重要.
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