Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892-7434, USA.
Bioinformatics. 2012 Jun 15;28(12):1555-61. doi: 10.1093/bioinformatics/bts168. Epub 2012 Apr 6.
Tumors are thought to develop and evolve through a sequence of genetic and epigenetic somatic alterations to progenitor cells. Early stages of human tumorigenesis are hidden from view. Here, we develop a method for inferring some aspects of the order of mutational events during tumorigenesis based on genome sequencing data for a set of tumors. This method does not assume that the sequence of driver alterations is the same for each tumor, but enables the degree of similarity or difference in the sequence to be evaluated.
To evaluate the new method, we applied it to colon cancer tumor sequencing data and the results are consistent with the multi-step tumorigenesis model previously developed based on comparing stages of cancer. We then applied the new method to DNA sequencing data for a set of lung cancers. The model may be a useful tool for better understanding the process of tumorigenesis.
The software is available at: http://linus.nci.nih.gov/Data/YounA/OrderMutation.zip.
肿瘤被认为是通过祖细胞的一系列遗传和表观遗传体细胞改变而发展和演变的。人类肿瘤发生的早期阶段是看不见的。在这里，我们开发了一种基于一组肿瘤的基因组测序数据推断肿瘤发生过程中突变事件顺序的某些方面的方法。该方法不假设驱动突变的顺序对于每个肿瘤都是相同的，而是能够评估序列的相似性或差异性。
为了评估新方法，我们将其应用于结肠癌肿瘤测序数据，结果与先前基于比较癌症阶段开发的多步肿瘤发生模型一致。然后，我们将新方法应用于一组肺癌的 DNA 测序数据。该模型可能是更好地理解肿瘤发生过程的有用工具。
该软件可在以下网址获得：http://linus.nci.nih.gov/Data/YounA/OrderMutation.zip。
