Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21287.
Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21287.
Proc Natl Acad Sci U S A. 2018 Feb 20;115(8):1871-1876. doi: 10.1073/pnas.1717846115. Epub 2018 Feb 5.
Aneuploidy is a feature of most cancer cells, and a myriad of approaches have been developed to detect it in clinical samples. We previously described primers that could be used to amplify ∼38,000 unique long interspersed nucleotide elements (LINEs) from throughout the genome. Here we have developed an approach to evaluate the sequencing data obtained from these amplicons. This approach, called Within-Sample AneupLoidy DetectiOn (WALDO), employs supervised machine learning to detect the small changes in multiple chromosome arms that are often present in cancers. We used WALDO to search for chromosome arm gains and losses in 1,677 tumors and in 1,522 liquid biopsies of blood from cancer patients or normal individuals. Aneuploidy was detected in 95% of cancer biopsies and in 22% of liquid biopsies. Using single-nucleotide polymorphisms within the amplified LINEs, WALDO concomitantly assesses allelic imbalances, microsatellite instability, and sample identification. WALDO can be used on samples containing only a few nanograms of DNA and as little as 1% neoplastic content and has a variety of applications in cancer diagnostics and forensic science.
非整倍体是大多数癌细胞的特征，已经开发出许多方法来在临床样本中检测它。我们之前描述了可以从整个基因组中扩增约 38000 个独特的长散布核元件 (LINEs) 的引物。在这里，我们开发了一种评估从这些扩增子获得的测序数据的方法。这种方法称为样本内非整倍性检测 (WALDO)，它采用有监督的机器学习来检测癌症中经常存在的多个染色体臂的微小变化。我们使用 WALDO 在 1677 个肿瘤和 1522 个来自癌症患者或正常人血液的液体活检中搜索染色体臂的增益和丢失。在 95%的癌症活检和 22%的液体活检中检测到非整倍性。WALDO 使用扩增的 LINE 内的单核苷酸多态性，同时评估等位基因失衡、微卫星不稳定性和样本识别。WALDO 可用于仅包含几个纳克 DNA 和低至 1%肿瘤含量的样本，并且在癌症诊断和法医学中有多种应用。
