A comparison of next-generation sequencing analysis methods for cancer xenograft samples

作     者：Wentao Dai Jixiang Liu Quanxue Li Wei Liu Yi-Xue Li Yuan-Yuan Li 

作者机构：shanghai center for bioinformation technologyShanghai 201203China shanghai engineering research center of pharmaceutical translation&shanghai industrial technology instituteShanghai 201203China school of biotechnologyeast china university of science and technologyShanghai 201203China shanghai industrial technology instituteShanghai 200237China 

出 版 物：《Journal of Genetics and Genomics》 (遗传学报（英文版）)

年 卷 期：2018年第45卷第7期

页      面：345-350页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 09[农学] 

基　　金：supported by the grants from the National Natural Science Foundation of China(Nos.,81672736 and 91529302) the Shanghai Industrial Technology Institute(17CXXF008) the Shanghai Sailing Program(16YF1408600) the Shanghai Municipal Commission of Science and Technology(14DZ2252000) the administrative committee of Shanghai Zhangjiang Hi-Teck Park(2016e08) the Medical engineering cross fund of Shanghai Jiao Tong University(YG2015QN27) 

主　　题：Patient-derived xenograft Next-generation sequencing Host contamination control Alignment 

摘      要：The application of next-generation sequencing （NGS） technology in cancer is influenced by the quality and purity of tissue samples. This issue is especially critical for patient-derived xenograft （PDX） models, which have proven to be by far the best preclinical tool for investigating human tumor biology, because the sensitivity and specificity of NGS analysis in xenograft samples would be compromised by the contamination of mouse DNA and RNA. This definitely affects downstream analyses by causing inaccurate mutation calling and gene expression estimates. The reliability of NGS data analysis for cancer xenograft samples is therefore highly dependent on whether the sequencing reads derived from the xenograft could be distinguished from those originated from the host. That is, each sequence read needs to be accurately assigned to its original species. Here, we review currently available methodologies in this field, including Xenome, Disambiguate, bamcmp and pdxBlacklist, and provide guidelines for users.