Jiang Yuchao, Qiu Yu, Minn Andy J, Zhang Nancy R
Genomics and Computational Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104;
Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; Institute of Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104.
Proc Natl Acad Sci U S A. 2016 Sep 13;113(37):E5528-37. doi: 10.1073/pnas.1522203113. Epub 2016 Aug 29.
Cancer is a disease driven by evolutionary selection on somatic genetic and epigenetic alterations. Here, we propose Canopy, a method for inferring the evolutionary phylogeny of a tumor using both somatic copy number alterations and single-nucleotide alterations from one or more samples derived from a single patient. Canopy is applied to bulk sequencing datasets of both longitudinal and spatial experimental designs and to a transplantable metastasis model derived from human cancer cell line MDA-MB-231. Canopy successfully identifies cell populations and infers phylogenies that are in concordance with existing knowledge and ground truth. Through simulations, we explore the effects of key parameters on deconvolution accuracy and compare against existing methods. Canopy is an open-source R package available at https://cran.r-project.org/web/packages/Canopy/.
癌症是一种由体细胞遗传和表观遗传改变的进化选择驱动的疾病。在此,我们提出了Canopy,一种使用来自单个患者的一个或多个样本中的体细胞拷贝数改变和单核苷酸改变来推断肿瘤进化系统发育的方法。Canopy应用于纵向和空间实验设计的批量测序数据集以及源自人癌细胞系MDA-MB-231的可移植转移模型。Canopy成功识别了细胞群体并推断出与现有知识和基本事实一致的系统发育。通过模拟,我们探索了关键参数对反卷积准确性的影响,并与现有方法进行了比较。Canopy是一个开源R包,可在https://cran.r-project.org/web/packages/Canopy/获取。