CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA.
CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA.
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DOI：
10.1186/s13059-017-1191-5
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发表时间：
2017-03-24
期刊：
影响因子：
12.3
通讯作者：
Zhou XJ
中科院分区：
文献类型：
--
作者：
Kang S;Li Q;Chen Q;Zhou Y;Park S;Lee G;Grimes B;Krysan K;Yu M;Wang W;Alber F;Sun F;Dubinett SM;Li W;Zhou XJ
我们提出了一种概率方法，癌症，它利用无细胞DNA的诊断潜力，不仅确定存在，而且还确定肿瘤的位置。CancerSurvey使用全基因组DNA甲基化数据同时推断血液样品中肿瘤来源的无细胞DNA的比例和起源组织。在模拟和真实的数据上，即使在无细胞DNA场景中肿瘤衍生DNA的比例较低的情况下，癌症分类也优于两种已建立的多类分类方法。Cancerabine还在具有低DNA甲基化测序覆盖率的患者血浆样品上取得了有希望的结果。本文的在线版本（doi：10.1186/s13059-017-1191-5）包含补充材料，可供授权用户使用。
We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. CancerLocator outperforms two established multi-class classification methods on simulations and real data, even with the low proportion of tumor-derived DNA in the cell-free DNA scenarios. CancerLocator also achieves promising results on patient plasma samples with low DNA methylation sequencing coverage. The online version of this article (doi:10.1186/s13059-017-1191-5) contains supplementary material, which is available to authorized users.