Abstract 817: Genomic evolution landscape of patient tumor derived xenograft of gastric cancer.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Patient-derived xenograft (PDX) models have emerged as key model systems to understand the efficacy of anti-cancer agents. PDX systems have demonstrated superiority over cell lines with regards to higher histological resemblance to primary tumor, presence of stroma and also in mimicking response to therapeutic agents. However, the genomic evolution landscape of model establishment is not a well studied topic. In order to do that, we systematically collected materials from the first three passages of xenografts derived from eight gastric cancer patients from Seoul National University, Korea from 2008-2011. We subsequently generated comprehensive genomic profiles of the first three passages, parent primary tumor, and matched normal tissues for the eight patients. The genomic profiling data included whole-exome sequencing data (Agilent exome capture, paired-end sequencing on Illumina HiSeq 2000), mRNA expression (Affymetrix U133 Plus2.0), copy number data (Affymetrix SNP6), miRNA expression (Agilent miRNA array v16.0) and DNA methylation data (Illumina HumanMethylation27). The analysis is focused on two types of events: a) Cancer-related genomic changes derived from normal vs. tumor comparison, and their subsequent assessment in early passages; b) Passage-specific genomic changes derived from tumor vs. passages comparison. A further refinement of passage-specific genomic changes is done to differentiate ‘true’ passage-specific events from the ones that appear due to the difference in tumor purity that is lower in primary tumor due to the normal contamination. Overall, we describe the genomic landscape of evolution along xenograft establishment in gastric cancer and provide a comprehensive picture of genetic and genomic similarities (and differences) of xenografts to the primary tumor. This analysis will help us to better interpret the in vivo results emanating from experiments using xenografts and to translate the findings appropriately to the clinic. Citation Format: Kun Yu, Swee Seong Wong, Jason C. Ting, Thompson N. Doman, Yong Yue, Amit aggarwal, Gregory P. Donoho, Rebekka Krumbach, Heiner H. Feibig, Seong-Ho kong, Woo-ho Kim, Han-kwang Yang, Christoph Reinhard. Genomic evolution landscape of patient tumor derived xenograft of gastric cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 817. doi:10.1158/1538-7445.AM2013-817 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.