Next-Generation Sequencing Analysis and Algorithms for PDX and CDX Models.

摘要: Patient-derived xenograft (PDX) and circulating tumor cell-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these have been applied to multiple questions, including metastatic progression, genetic evolution, therapeutic drug responses. As PDX CDX can recapitulate highly heterogeneous characteristics a patient tumor, as well their response chemotherapy, there is considerable interest in combining them with next-generation sequencing monitor genomic, transcriptional, epigenetic changes that accompany oncogenesis. When used this purpose, reliability dependent on being able accurately distinguish between reads originate from host, those arise itself. Here, we demonstrate failure correctly identify contaminating host when analyzing DNA- RNA-sequencing (DNA-Seq RNA-Seq) data major confounding factor lead incorrect mutation calls canonical signatures associated tumorigenicity. addition, sensitive algorithm open source software tool identifying removing sequences described. Importantly, melanoma, its utility selective correction PDX- CDX-derived whole-exome RNA-Seq data.Implications: This describes method applicable other forms deep sequencing. Mol Cancer Res; 15(8); 1012-6. ©2017 AACR.