Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Bioinformatics. 2020 Jul 1;36(Suppl_1):i161-i168. doi: 10.1093/bioinformatics/btaa471.
Cancer is caused by the accumulation of somatic mutations that lead to the formation of distinct populations of cells, called clones. The resulting clonal architecture is the main cause of relapse and resistance to treatment. With decreasing costs in DNA sequencing technology, rich cancer genomics datasets with many spatial sequencing samples are becoming increasingly available, enabling the inference of high-resolution tumor clones and prevalences across different spatial coordinates. While temporal and phylogenetic aspects of tumor evolution, such as clonal evolution over time and clonal response to treatment, are commonly visualized in various clonal evolution diagrams, visual analytics methods that reveal the spatial clonal architecture are missing.
This article introduces ClonArch, a web-based tool to interactively visualize the phylogenetic tree and spatial distribution of clones in a single tumor mass. ClonArch uses the marching squares algorithm to draw closed boundaries representing the presence of clones in a real or simulated tumor. ClonArch enables researchers to examine the spatial clonal architecture of a subset of relevant mutations at different prevalence thresholds and across multiple phylogenetic trees. In addition to simulated tumors with varying number of biopsies, we demonstrate the use of ClonArch on a hepatocellular carcinoma tumor with ∼280 sequencing biopsies. ClonArch provides an automated way to interactively examine the spatial clonal architecture of a tumor, facilitating clinical and biological interpretations of the spatial aspects of intra-tumor heterogeneity.
癌症是由体细胞突变积累引起的，这些突变导致形成称为克隆的不同细胞群体。由此产生的克隆结构是复发和治疗耐药的主要原因。随着 DNA 测序技术成本的降低，越来越多具有丰富空间测序样本的癌症基因组学数据集变得可用，从而能够推断出不同空间坐标处的高分辨率肿瘤克隆和流行率。虽然肿瘤进化的时间和系统发育方面，例如随时间推移的克隆进化和克隆对治疗的反应，通常在各种克隆进化图中可视化，但缺乏揭示空间克隆结构的可视化分析方法。
本文介绍了 ClonArch，这是一种基于网络的工具，可在单个肿瘤块中交互式可视化系统发育树和克隆的空间分布。ClonArch 使用前进方格算法绘制封闭边界，以表示真实或模拟肿瘤中克隆的存在。ClonArch 使研究人员能够在不同的流行率阈值和多个系统发育树中检查相关突变子集的空间克隆结构。除了具有不同活检数量的模拟肿瘤外，我们还在约 280 个测序活检的肝细胞癌肿瘤上演示了 ClonArch 的使用。ClonArch 提供了一种自动交互检查肿瘤空间克隆结构的方法，有助于对肿瘤内异质性的空间方面进行临床和生物学解释。
