CancerDetector: ultrasensitive and non-invasive cancer detection at the resolution of individual reads using cell-free DNA methylation sequencing data.

CancerDetector: ultrasensitive and non-invasive cancer detection at the resolution of individual reads using cell-free DNA methylation sequencing data.
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DOI:
10.1093/nar/gky423
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发表时间:
2018-09-06
影响因子:
14.9
通讯作者:
Zhou XJ
Zhou XJ
中科院分区:
生物学2区
文献类型:
--
作者:
Li W;Li Q;Kang S;Same M;Zhou Y;Sun C;Liu CC;Matsuoka L;Sher L;Wong WH;Alber F;Zhou XJ

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血浆中肿瘤源游离DNA的检测是肿瘤诊断中最有前途的方向之一。这种方法的主要挑战是如何从血液中的总无细胞DNA中识别出微量的肿瘤DNA。在这里,我们提出了一种超灵敏的癌症检测方法,称为“癌症检测器”,使用无细胞DNA的DNA甲基化谱。我们的方法的关键是对单个测序读段上多个相邻CpG位点的联合甲基化状态进行概率建模,以便利用DNA甲基化的普遍性质进行信号放大。因此,CancerDetector可以在单个读数的水平上灵敏地识别血浆中痕量的肿瘤cfDNA。我们在模拟数据上评估了CancerDetector,并显示出预测和真实肿瘤分数的高度一致性。在真实的血浆数据上测试CancerDetector证明了其在检测肿瘤cfDNA方面的高灵敏度和特异性。此外,预测的肿瘤分数显示出与肿瘤大小和生存结局的高度一致性。请注意,所有这些测试都是在低至中等覆盖率(1×至10×)下对测序数据进行的。因此,CancerDetector具有早期和经济有效地检测癌症的巨大潜力。
The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such an approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed ‘CancerDetector’, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation states of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor fraction. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor cfDNAs. In addition, the predicted tumor fraction showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1× to 10×). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.
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